ACADEMIC | Pagerbird World News

Colour season analysis: how a younger generation warmed to 80s style rules

- Regional

The Iron Sheik, charismatic former pro wrestling villain and Twitter personality, dies at 81

- World

Jenna Ortega Says ‘Wednesday’ Season 2 Is ‘Ditching Any Romantic Love Interest’ and ‘Leaning Into Horror’ More

- Television, Entertainment

'I can taste the air': Canadian wildfire smoke spreads hazardous haze at home and in the US

- World

TRIUMPH ANNOUNCES NOTICE TO WARRANT HOLDERS OF INTENDED REDEMPTION

- Company

DJs And Influencers Reveal Their Favorite American Cities For Summer

- Lifestyle

These ETFs Are Key To Monitoring The Sustainability Of U.S. And Global Stock Rallies

- Business, Finance

Summersalt and Diane von Furstenberg Collaborated on the Swimwear Collection of Our Dreams

- Fashion, Lifestyle

SaverOne Expands its Footprint Among Private Bus Fleets with Over 160 New Installations

- Company

'Ton of questions' about LIV Adelaide after merger

- Sports, Regional

Boeing uncovers new defect on 787 planes under repair in Everett

- Business, Seattle, Washington

Sure, Selling Feet Pics Is Cool, But Have You Ever Turned a Guy Into Your Paying Foot Worshiper?

- Fashion, Entertainment

Cisco and AT&T Join Forces to Help Businesses Expand Connectivity for a Growing Mobile-First Workforce

- Company

How to watch CNN's town hall with former Vice President Mike Pence | CNN Politics

- Politics

Scientists record first known ‘virgin birth’ in female crocodile in Costa Rica

- Regional

Forecasting the Performance of US Stock Market Indices During COVID-19: RF vs LSTM. (arXiv:2306.03620v1 [econ.EM])

- Academic, ECON

Real Madrid agree deal to sign Bellingham

- General

Integrity of Sydney’s main Warragamba dam at risk from extreme flooding, says study

- National

Journeyman goalie Adin Hill has Vegas Golden Knights up 2-0 over Florida in the Stanley Cup Final

- Sports

BBC Weather forecast on Canada wildfire smoke

- General

Enjoy content with a refurbished iPad, Beats Headphones for under $200

- General

Argentine fintech Uala to offer high-yield accounts in Mexico

- General

Coco Gauff is 0-7 against No. 1 Iga Swiatek after losing to her in the French Open quarterfinals

- Sports

Sorry, Trump — Rishi Sunak’s too busy to see you

- Politics

AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions. (arXiv:2306.03329v1 [cs.LG])

- Academic, BIO

Dylan Mulvaney takes aim at her critics after Bud Light disaster

- General

North Dakota GOP Gov. Doug Burgum files to run for president in 2024 | CNN Politics

- Politics

Worksite Labs, Inc. Announces Two New Board Members: Roberta Luskin-Hawk, M.D. and Afsaneh Naimollah

- Company

Did German Pilots Just Pass NATO’s Tactics to China?

- World

Canada's Quebec expects thousands more to flee wildfires

- World

academic

Some Results On Equivalence Of Multi-letter Quantum Finite Automata
Two quantum finite automata are equivalent if for all input string $ω$ over the input alphabet the two automata accept $ω$ with equal probability. In [Theoret. Comput. Sci. 410 (2009) 3006-3017], it was shown that a $k_1$-letter QFA $mathcal{A}_1$ and a $k_2$-letter QFA $mathcal{A}_2$ over $Σ={σ}$, ...

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Generating Private Synthetic Data With Genetic Algorithms. (arXiv:2306.03257v1 [cs.OH])
We study the problem of efficiently generating differentially private synthetic data that approximate the statistical properties of an underlying sensitive dataset. In recent years, there has been a growing line of work that approaches this problem using first-order optimization techniques. However,...

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Surrogate-assisted Distributed Swarm Optimisation For Computationally Expensive Geoscientific Models. (arXiv:2201.06843v2 [cs.DC] UPDATED)
Evolutionary algorithms provide gradient-free optimisation which is beneficial for models that have difficulty in obtaining gradients; for instance, geoscientific landscape evolution models. However, such models are at times computationally expensive and even distributed swarm-based optimisation wit...

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Consumer's Behavior Analysis Of Electric Vehicle Using Cloud Computing In The State Of New York. (arXiv:2306.01888v1 [cs.CY])
Sales of Electric Vehicles (EVs) in the United States have grown fast in the past decade. We analyze the Electric Vehicle Drive Clean Rebate data from the New York State Energy Research and Development Authority (NYSERDA) to understand consumer behavior in EV purchasing and their potential environme...

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Auditable Data Structures: Theory And Applications. (arXiv:2306.01886v1 [cs.DC])
Every digital process needs to consume some data in order to work properly. It is very common for applications to use some external data in their processes, getting them by sources such as external APIs. Therefore, trusting the received data becomes crucial in such scenarios, considering that if the...

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Optimizing Irregular Communication With Neighborhood Collectives And Locality-Aware Parallelism. (arXiv:2306.01876v1 [cs.DC])
Irregular communication often limits both the performance and scalability of parallel applications. Typically, applications individually implement irregular messages using point-to-point communications, and any optimizations are added directly into the application. As a result, these optimizations l...

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The Current Opportunities And Challenges Of Web 3.0. (arXiv:2306.03351v1 [cs.CY])
With recent advancements in AI and 5G technologies,as well as the nascent concepts of blockchain and metaverse,a new revolution of the Internet,known as Web 3.0,is emerging. Given its significant potential impact on the internet landscape and various professional sectors,Web 3.0 has captured conside...

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Inference Under Constrained Distribution Shifts. (arXiv:2306.03302v1 [stat.ME])
Large-scale administrative or observational datasets are increasingly used to inform decision making. While this effort aims to ground policy in real-world evidence, challenges have arise as that selection bias and other forms of distribution shift often plague observational data. Previous attempts ...

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ChatGPT As A Mapping Assistant: A Novel Method To Enrich Maps With Generative AI And Content Derived From Street-level Photographs. (arXiv:2306.03204v1 [cs.CY])
This paper explores the concept of leveraging generative AI as a mapping assistant for enhancing the efficiency of collaborative mapping. We present results of an experiment that combines multiple sources of volunteered geographic information (VGI) and large language models (LLMs). Three analysts de...

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A Technical Report For Polyglot-Ko: Open-Source Large-Scale Korean Language Models. (arXiv:2306.02254v2 [cs.CL] UPDATED)
Polyglot is a pioneering project aimed at enhancing the non-English language performance of multilingual language models. Despite the availability of various multilingual models such as mBERT (Devlin et al., 2019), XGLM (Lin et al., 2022), and BLOOM (Scao et al., 2022), researchers and developers of...

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Enhancing Programming ETextbooks With ChatGPT Generated Counterfactual-Thinking-Inspired Questions
Digital textbooks have become an integral part of everyday learning tasks. In this work, we consider the use of digital textbooks for programming classes. Generally, students struggle with utilizing textbooks on programming to the maximum, with a possible reason being that the example programs provi...

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Self-supervised Predictive Coding Models Encode Speaker And Phonetic Information In Orthogonal Subspaces
Self-supervised speech representations are known to encode both speaker and phonetic information, but how they are distributed in the high-dimensional space remains largely unexplored. We hypothesize that they are encoded in orthogonal subspaces, a property that lends itself to simple disentanglemen...

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Joint Repetition Suppression And Content Moderation Of Large Language Models. (arXiv:2304.10611v2 [cs.CL] UPDATED)
Natural language generation (NLG) is one of the most impactful fields in NLP, and recent years have witnessed its evolution brought about by large language models (LLMs). As the key instrument for writing assistance applications, they are generally prone to replicating or extending offensive content...

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A Universal Discriminator For Zero-Shot Generalization. (arXiv:2211.08099v2 [cs.CL] UPDATED)
Generative modeling has been the dominant approach for large-scale pretraining and zero-shot generalization. In this work, we challenge this convention by showing that discriminative approaches perform substantially better than generative ones on a large number of NLP tasks. Technically, we train a ...

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Differentially Private Episodic Reinforcement Learning With Heavy-tailed Rewards. (arXiv:2306.01121v2 [cs.LG] UPDATED)
In this paper, we study the problem of (finite horizon tabular) Markov decision processes (MDPs) with heavy-tailed rewards under the constraint of differential privacy (DP). Compared with the previous studies for private reinforcement learning that typically assume rewards are sampled from some boun...

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SnapFusion: Text-to-Image Diffusion Model On Mobile Devices Within Two Seconds. (arXiv:2306.00980v2 [cs.CV] UPDATED)
Text-to-image diffusion models can create stunning images from natural language descriptions that rival the work of professional artists and photographers. However, these models are large, with complex network architectures and tens of denoising iterations, making them computationally expensive and ...

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STEVE-1: A Generative Model For Text-to-Behavior In Minecraft. (arXiv:2306.00937v2 [cs.AI] UPDATED)
Constructing AI models that respond to text instructions is challenging, especially for sequential decision-making tasks. This work introduces an instruction-tuned Video Pretraining (VPT) model for Minecraft called STEVE-1, demonstrating that the unCLIP approach, utilized in DALL-E 2, is also effect...

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In-Context Analogical Reasoning With Pre-Trained Language Models. (arXiv:2305.17626v2 [cs.AI] UPDATED)
Analogical reasoning is a fundamental capacity of human cognition that allows us to reason abstractly about novel situations by relating them to past experiences. While it is thought to be essential for robust reasoning in AI systems, conventional approaches require significant training and/or hard-...

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Detecting Edit Failures In Large Language Models: An Improved Specificity Benchmark
Recent model editing techniques promise to mitigate the problem of memorizing false or outdated associations during LLM training. However, we show that these techniques can introduce large unwanted side effects which are not detected by existing specificity benchmarks. We extend the existing Counter...

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Answering Unanswered Questions Through Semantic Reformulations In Spoken QA. (arXiv:2305.17393v2 [cs.CL] UPDATED)
Spoken Question Answering (QA) is a key feature of voice assistants, usually backed by multiple QA systems. Users ask questions via spontaneous speech which can contain disfluencies, errors, and informal syntax or phrasing. This is a major challenge in QA, causing unanswered questions or irrelevant ...

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Trust-Aware Resilient Control And Coordination Of Connected And Automated Vehicles
We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area. Adversarial attacks such as Sybil attacks can cause safety violations resulting in collisions and traffic jams. In addition, uncooperative (but not necessarily adversarial...

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Theoretically Principled Federated Learning For Balancing Privacy And Utility. (arXiv:2305.15148v2 [cs.LG] UPDATED)
We propose a general learning framework for the protection mechanisms that protects privacy via distorting model parameters, which facilitates the trade-off between privacy and utility. The algorithm is applicable to arbitrary privacy measurements that maps from the distortion to a real value. It ca...

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Unsupervised Visible-Infrared Person ReID By Collaborative Learning With Neighbor-Guided Label Refinement. (arXiv:2305.12711v2 [cs.CV] UPDATED)
Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims at learning modality-invariant features from unlabeled cross-modality dataset, which is crucial for practical applications in video surveillance systems. The key to essentially address the USL-VI-ReID task is to solve...

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Efficient Bilateral Cross-Modality Cluster Matching For Unsupervised Visible-Infrared Person ReID. (arXiv:2305.12673v2 [cs.CV] UPDATED)
Unsupervised visible-infrared person re-identification (USL-VI-ReID) aims to match pedestrian images of the same identity from different modalities without annotations. Existing works mainly focus on alleviating the modality gap by aligning instance-level features of the unlabeled samples. However, ...

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Context-Dependent Embedding Utterance Representations For Emotion Recognition In Conversations. (arXiv:2304.08216v2 [cs.CL] UPDATED)
Emotion Recognition in Conversations (ERC) has been gaining increasing importance as conversational agents become more and more common. Recognizing emotions is key for effective communication, being a crucial component in the development of effective and empathetic conversational agents. Knowledge a...

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Transformer And Snowball Graph Convolution Learning For Brain Functional Network Classification. (arXiv:2303.16132v2 [cs.LG] UPDATED)
Advanced deep learning methods, especially graph neural networks (GNNs), are increasingly expected to learn from brain functional network data and identify the functional connections between brain disorder and health. In this paper, we proposed a novel Transformer and snowball encoding networks (TSE...

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LIDA: A Tool For Automatic Generation Of Grammar-Agnostic Visualizations And Infographics Using Large Language Models. (arXiv:2303.02927v2 [cs.AI] UPDATED)
Systems that support users in the automatic creation of visualizations must address several subtasks - understand the semantics of data, enumerate relevant visualization goals and generate visualization specifications. In this work, we pose visualization generation as a multi-stage generation proble...

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Diffusion Model-Augmented Behavioral Cloning. (arXiv:2302.13335v2 [cs.LG] UPDATED)
Imitation learning addresses the challenge of learning by observing an expert's demonstrations without access to reward signals from environments. Most existing imitation learning methods that do not require interacting with environments either model the expert distribution as the conditional probab...

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Byzantine-Robust Learning On Heterogeneous Data Via Gradient Splitting. (arXiv:2302.06079v2 [cs.LG] UPDATED)
Federated learning has exhibited vulnerabilities to Byzantine attacks, where the Byzantine attackers can send arbitrary gradients to a central server to destroy the convergence and performance of the global model. A wealth of robust AGgregation Rules (AGRs) have been proposed to defend against Byzan...

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Adaptive Computation With Elastic Input Sequence. (arXiv:2301.13195v2 [cs.LG] UPDATED)
Humans have the ability to adapt the type of information they use, the procedure they employ, and the amount of time they spend when solving problems. However, most standard neural networks have a fixed function type and computation budget regardless of the sample's nature or difficulty. Adaptivity ...

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Arbitrarily Large Labelled Random Satisfiability Formulas For Machine Learning Training. (arXiv:2211.15368v2 [cs.AI] UPDATED)
Applying deep learning to solve real-life instances of hard combinatorial problems has tremendous potential. Research in this direction has focused on the Boolean satisfiability (SAT) problem, both because of its theoretical centrality and practical importance. A major roadblock faced, though, is th...

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Diffusion Denoising Process For Perceptron Bias In Out-of-distribution Detection. (arXiv:2211.11255v2 [cs.CV] UPDATED)
Out-of-distribution (OOD) detection is a crucial task for ensuring the reliability and safety of deep learning. Currently, discriminator models outperform other methods in this regard. However, the feature extraction process used by discriminator models suffers from the loss of critical information,...

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Meta Optimal Transport
We study the use of amortized optimization to predict optimal transport (OT) maps from the input measures, which we call Meta OT. This helps repeatedly solve similar OT problems between different measures by leveraging the knowledge and information present from past problems to rapidly predict and s...

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Hierarchies Of Reward Machines
Reward machines (RMs) are a recent formalism for representing the reward function of a reinforcement learning task through a finite-state machine whose edges encode subgoals of the task using high-level events. The structure of RMs enables the decomposition of a task into simpler and independently s...

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VisualGPTScore: Visio-Linguistic Reasoning With Multimodal Generative Pre-Training Scores. (arXiv:2306.01879v1 [cs.CV])
Vision-language models (VLMs) discriminatively pre-trained with contrastive image-text matching losses such as $P(text{match}|text{text}, text{image})$ have been criticized for lacking compositional understanding. This means they might output similar scores even if the original caption is rearranged...

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Probabilistic Adaptation Of Text-to-Video Models. (arXiv:2306.01872v1 [cs.AI])
Large text-to-video models trained on internet-scale data have demonstrated exceptional capabilities in generating high-fidelity videos from arbitrary textual descriptions. However, adapting these models to tasks with limited domain-specific data, such as animation or robotics videos, poses a signif...

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No Bidding, No Regret: Pairwise-Feedback Mechanisms For Digital Goods And Data Auctions. (arXiv:2306.01860v1 [cs.GT])
The growing demand for data and AI-generated digital goods, such as personalized written content and artwork, necessitates effective pricing and feedback mechanisms that account for uncertain utility and costly production. Motivated by these developments, this study presents a novel mechanism design...

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Spatially Resolved Gene Expression Prediction From H&E Histology Images Via Bi-modal Contrastive Learning. (arXiv:2306.01859v1 [cs.CV])
Histology imaging is an important tool in medical diagnosis and research, enabling the examination of tissue structure and composition at the microscopic level. Understanding the underlying molecular mechanisms of tissue architecture is critical in uncovering disease mechanisms and developing effect...

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5IDER: Unified Query Rewriting For Steering, Intent Carryover, Disfluencies, Entity Carryover And Repair
Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem. Handling multi-turn interactions requires the system to understand various conversational use-cases, such as steering, intent carryover, disfluencies, entity carryover, and repair. The complexity of...

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Unifying (Machine) Vision Via Counterfactual World Modeling. (arXiv:2306.01828v1 [cs.CV])
Leading approaches in machine vision employ different architectures for different tasks, trained on costly task-specific labeled datasets. This complexity has held back progress in areas, such as robotics, where robust task-general perception remains a bottleneck. In contrast, "foundation models" of...

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Sensing Wellbeing In The Workplace, Why And For Whom? Envisioning Impacts With Organizational Stakeholders. (arXiv:2303.06794v2 [cs.HC] UPDATED)
With the heightened digitization of the workplace, alongside the rise of remote and hybrid work prompted by the pandemic, there is growing corporate interest in using passive sensing technologies for workplace wellbeing. Existing research on these technologies often focus on understanding or improvi...

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Navigating Multi-Stakeholder Incentives And Preferences: Co-Designing Alternatives For The Future Of Gig Worker Well-Being. (arXiv:2302.13436v2 [cs.HC] UPDATED)
Gig workers, and the products and services they provide, play an increasingly ubiquitous role in our daily lives. But despite growing evidence suggesting that worker well-being in gig economy platforms have become significant societal problems, few studies have investigated possible solutions. We ta...

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Dance Generation By Sound Symbolic Words. (arXiv:2306.03646v1 [cs.LG])
This study introduces a novel approach to generate dance motions using onomatopoeia as input, with the aim of enhancing creativity and diversity in dance generation. Unlike text and music, onomatopoeia conveys rhythm and meaning through abstract word expressions without constraints on expression and...

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Real-Time Onboard Object Detection For Augmented Reality: Enhancing Head-Mounted Display With YOLOv8
This paper introduces a software architecture for real-time object detection using machine learning (ML) in an augmented reality (AR) environment. Our approach uses the recent state-of-the-art YOLOv8 network that runs onboard on the Microsoft HoloLens 2 head-mounted display (HMD). The primary motiva...

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Measuring User Experience Of Adaptive User Interfaces Using EEG: A Replication Study. (arXiv:2306.03525v1 [cs.HC])
Adaptive user interfaces have the advantage of being able to dynamically change their aspect and/or behaviour depending on the characteristics of the context of use, i.e. to improve user experience(UX). UX is an important quality factor that has been primarily evaluated with classical measures but t...

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Towards Adapting Computer Science Courses To AI Assistants' Capabilities. (arXiv:2306.03289v1 [cs.HC])
The use of AI assistants, along with the challenges they present, has sparked significant debate within the community of computer science education. While these tools demonstrate the potential to support students' learning and instructors' teaching, they also raise concerns about enabling unethical ...

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AHA!: Facilitating AI Impact Assessment By Generating Examples Of Harms. (arXiv:2306.03280v1 [cs.HC])
While demands for change and accountability for harmful AI consequences mount, foreseeing the downstream effects of deploying AI systems remains a challenging task. We developed AHA! (Anticipating Harms of AI), a generative framework to assist AI practitioners and decision-makers in anticipating pot...

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Ten Steps To Becoming A Musculoskeletal Simulation Expert: A Half-Century Of Progress And Outlook For The Future
Over the past half-century, musculoskeletal simulations have deepened our knowledge of human and animal movement. This article outlines ten steps to becoming a musculoskeletal simulation expert so you can contribute to the next half-century of technical innovation and scientific discovery. We advoca...

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Serious Games: An Updated Systematic Literature Review
Serious games are simulation software designed to assist people in learning the practical concepts of various application fields such as Health, wellness, Education and Culture. People improve their individual knowledge, skills and attitude through training. This study identified the changing trends...

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High Fidelity Speech Enhancement With Band-split RNN. (arXiv:2212.00406v2 [eess.AS] UPDATED)
Despite the rapid progress in speech enhancement (SE) research, enhancing the quality of desired speech in environments with strong noise and interfering speakers remains challenging. In this paper, we extend the application of the recently proposed band-split RNN (BSRNN) model to full-band SE and p...

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On The Robustness Of Arabic Speech Dialect Identification
Arabic dialect identification (ADI) tools are an important part of the large-scale data collection pipelines necessary for training speech recognition models. As these pipelines require application of ADI tools to potentially out-of-domain data, we aim to investigate how vulnerable the tools may be ...

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Streaming Speech-to-Confusion Network Speech Recognition
In interactive automatic speech recognition (ASR) systems, low-latency requirements limit the amount of search space that can be explored during decoding, particularly in end-to-end neural ASR. In this paper, we present a novel streaming ASR architecture that outputs a confusion network while mainta...

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Some Voices Are Too Common: Building Fair Speech Recognition Systems Using The Common Voice Dataset
Automatic speech recognition (ASR) systems become increasingly efficient thanks to new advances in neural network training like self-supervised learning. However, they are known to be unfair toward certain groups, for instance, people speaking with an accent. In this work, we use the French Common V...

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Emotion-Conditioned Melody Harmonization With Hierarchical Variational Autoencoder. (arXiv:2306.03718v1 [cs.SD])
Existing melody harmonization models have made great progress in improving the quality of generated harmonies, but most of them ignored the emotions beneath the music. Meanwhile, the variability of harmonies generated by previous methods is insufficient. To solve these problems, we propose a novel L...

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Experimenting With Additive Margins For Contrastive Self-Supervised Speaker Verification. (arXiv:2306.03664v1 [eess.AS])
Most state-of-the-art self-supervised speaker verification systems rely on a contrastive-based objective function to learn speaker representations from unlabeled speech data. We explore different ways to improve the performance of these methods by: (1) revisiting how positive and negative pairs are ...

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Ada-TTA: Towards Adaptive High-Quality Text-to-Talking Avatar Synthesis. (arXiv:2306.03504v1 [cs.CV])
We are interested in a novel task, namely low-resource text-to-talking avatar. Given only a few-minute-long talking person video with the audio track as the training data and arbitrary texts as the driving input, we aim to synthesize high-quality talking portrait videos corresponding to the input te...

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A Generative Framework For Conversational Laughter: Its 'language Model' And Laughter Sound Synthesis
As the phonetic and acoustic manifestations of laughter in conversation are highly diverse, laughter synthesis should be capable of accommodating such diversity while maintaining high controllability. This paper proposes a generative model of laughter in conversation that can produce a wide variety ...

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Phase Perturbation Improves Channel Robustness For Speech Spoofing Countermeasures. (arXiv:2306.03389v1 [cs.SD])
In this paper, we aim to address the problem of channel robustness in speech countermeasure (CM) systems, which are used to distinguish synthetic speech from human natural speech. On the basis of two hypotheses, we suggest an approach for perturbing phase information during the training of time-doma...

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Reef Elegy: An Auditory Display Of Hawaii's 2019 Coral Bleaching Data
This paper describes an auditory display of Hawaii's 2019 coral bleaching data via means of spatial audio and parameter mapping methods. Selected data fields spanning 78 days are mapped to sound surrogates of coral reefs' natural soundscapes, which are progressively altered in their constituent elem...

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LipVoicer: Generating Speech From Silent Videos Guided By Lip Reading. (arXiv:2306.03258v1 [eess.AS])
Lip-to-speech involves generating a natural-sounding speech synchronized with a soundless video of a person talking. Despite recent advances, current methods still cannot produce high-quality speech with high levels of intelligibility for challenging and realistic datasets such as LRS3. In this work...

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DeepVQE: Real Time Deep Voice Quality Enhancement For Joint Acoustic Echo Cancellation, Noise Suppression And Dereverberation. (arXiv:2306.03177v1 [cs.SD])
Acoustic echo cancellation (AEC), noise suppression (NS) and dereverberation (DR) are an integral part of modern full-duplex communication systems. As the demand for teleconferencing systems increases, addressing these tasks is required for an effective and efficient online meeting experience. Most ...

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Lattice-Based Quantum Advantage From Rotated Measurements
Trapdoor claw-free functions (TCFs) are immensely valuable in cryptographic interactions between a classical client and a quantum server. Typically, a protocol has the quantum server prepare a superposition of two-bit strings of a claw and then measure it using Pauli-$X$ or $Z$ measurements. In this...

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Compiling Quantum Circuits For Dynamically Field-Programmable Neutral Atoms Array Processors. (arXiv:2306.03487v1 [quant-ph])
Dynamically field-programmable qubit arrays (DPQA) have recently emerged as a promising platform for quantum information processing. In DPQA, atomic qubits are selectively loaded into arrays of optical traps that can be reconfigured during the computation itself. Leveraging qubit transport and paral...

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High-Round QAOA For MAX $k$-SAT On Trapped Ion NISQ Devices. (arXiv:2306.03238v1 [quant-ph])
The Quantum Alternating Operator Ansatz (QAOA) is a hybrid classical-quantum algorithm that aims to sample the optimal solution(s) of discrete combinatorial optimization problems. We present optimized QAOA circuit constructions for sampling MAX $k$-SAT problems, specifically for $k=3$ and $k=4$. The...

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Complexity Of Anchored Crossing Number And Crossing Number Of Almost Planar Graphs. (arXiv:2306.03490v1 [cs.DM])
In this paper we deal with the problem of computing the exact crossing number of almost planar graphs and the closely related problem of computing the exact anchored crossing number of a pair of planar graphs. It was shown by [Cabello and Mohar, 2013] that both problems are NP-hard; although they re...

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Accelerating Range Minimum Queries With Ray Tracing Cores. (arXiv:2306.03282v1 [cs.DC])
During the last decade GPU technology has shifted from pure general purpose computation to the inclusion of application specific integrated circuits (ASICs), such as Tensor Cores and Ray Tracing (RT) cores. Although these special purpose GPU cores were designed to further accelerate specific fields ...

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On The Parameterized Complexity Of Computing $st$-Orientations With Few Transitive Edges. (arXiv:2306.03196v1 [cs.DS])
Orienting the edges of an undirected graph such that the resulting digraph satisfies some given constraints is a classical problem in graph theory, with multiple algorithmic applications. In particular, an $st$-orientation orients each edge of the input graph such that the resulting digraph is acycl...

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Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents. (arXiv:2306.02704v1 [cs.GT] CROSS LISTED)
In this paper, we introduce a generalization of the standard Stackelberg Games (SGs) framework: Calibrated Stackelberg Games (CSGs). In CSGs, a principal repeatedly interacts with an agent who (contrary to standard SGs) does not have direct access to the principal's action but instead best-responds ...

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Greedy-Mine: A Profitable Mining Attack Strategy In Bitcoin-NG. (arXiv:2306.03540v1 [cs.CR])
Bitcoin-NG is an extensible blockchain protocol based on the same trust model as Bitcoin. It divides each epoch into one Key-Block and multiple Micro-Blocks, effectively improving transaction processing capacity. Bitcoin-NG adopts a special incentive mechanism (i.e., the transaction fees in each epo...

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UAV-Assisted Wireless Communications: An Experimental Analysis Of A2G And G2A Channels. (arXiv:2303.16986v2 [cs.NI] UPDATED)
Unmanned Aerial Vehicles (UAVs) offer promising potential as communications node carriers, providing on-demand wireless connectivity to users. While existing literature presents various wireless channel models, it often overlooks the impact of UAV heading. This paper provides an experimental charact...

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DANSE: Data-driven Non-linear State Estimation Of Model-free Process In Unsupervised Learning Setup. (arXiv:2306.03897v1 [eess.SY])
We address the tasks of Bayesian state estimation and forecasting for a model-free process in an unsupervised learning setup. In the article, we propose DANSE -- a Data-driven Nonlinear State Estimation method. DANSE provides a closed-form posterior of the state of the model-free process, given line...

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A Communication-Efficient Adaptive Algorithm For Federated Learning Under Cumulative Regret
We consider the problem of online stochastic optimization in a distributed setting with $M$ clients connected through a central server. We develop a distributed online learning algorithm that achieves order-optimal cumulative regret with low communication cost measured in the total number of bits tr...

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FaaSwap: SLO-Aware, GPU-Efficient Serverless Inference Via Model Swapping. (arXiv:2306.03622v1 [cs.DC])
The dynamic request patterns of machine learning (ML) inference workloads have driven an increasing trend towards exploiting serverless computing for scalable ML model serving. However, today's serverless platforms lack efficient support for GPUs -- provisioning functions on GPUs incurs extremely hi...

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A Lightweight Method For Tackling Unknown Participation Probabilities In Federated Averaging. (arXiv:2306.03401v1 [cs.LG])
In federated learning (FL), clients usually have diverse participation probabilities that are unknown a priori, which can significantly harm the performance of FL if not handled properly. Existing works aiming at addressing this problem are usually based on global variance reduction, which requires ...

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Exploiting Scratchpad Memory For Deep Temporal Blocking: A Case Study For 2D Jacobian 5-point Iterative Stencil Kernel (j2d5pt)
General Purpose Graphics Processing Units (GPGPU) are used in most of the top systems in HPC. The total capacity of scratchpad memory has increased by more than 40 times in the last decade. However, existing optimizations for stencil computations using temporal blocking have not aggressively exploit...

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Better Write Amplification For Streaming Data Processing
Many current applications have to perform data processing in a streaming fashion. Doing so at a large scale requires a parallel system that must be equipped to handle straggling workers and different kinds of failures. YT is the main driver behind distributed systems at Yandex, home to its distribut...

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An Alternate Proof Of Near-Optimal Light Spanners
In 2016, a breakthrough result of Chechik and Wulff-Nilsen [SODA '16] established that every $n$-node graph $G$ has a $(1+varepsilon)(2k-1)$-spanner of lightness $O_{varepsilon}(n^{1/k})$, and recent followup work by Le and Solomon [STOC '23] generalized the proof strategy and improved the dependenc...

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Computing The Theta Function
Let $f: {Bbb R}^n longrightarrow {Bbb R}$ be a positive definite quadratic form and let $y in {Bbb R}^n$ be a point. We present a fully polynomial randomized approximation scheme (FPRAS) for computing $sum_{x in {Bbb Z}^n} e^{-f(x)}$, provided the eigenvalues of $f$ lie in the interval roughly betwe...

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Notes On Randomized Algorithms
Lecture notes for the Yale Computer Science course CPSC 469/569 Randomized Algorithms. Suitable for use as a supplementary text for an introductory graduate or advanced undergraduate course on randomized algorithms. Discusses tools from probability theory, including random variables and expectations...

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Collectively Canalizing Boolean Functions. (arXiv:2008.13741v3 [cs.DM] UPDATED)
This paper studies the mathematical properties of collectively canalizing Boolean functions, a class of functions that has arisen from applications in systems biology. Boolean networks are an increasingly popular modeling framework for regulatory networks, and the class of functions studied here cap...

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Utterance Classification With Logical Neural Network: Explainable AI For Mental Disorder Diagnosis. (arXiv:2306.03902v1 [cs.CL])
In response to the global challenge of mental health problems, we proposes a Logical Neural Network (LNN) based Neuro-Symbolic AI method for the diagnosis of mental disorders. Due to the lack of effective therapy coverage for mental disorders, there is a need for an AI solution that can assist thera...

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Multimodal Imaging Of The Mouse Eye Using Visible Light Photoacoustic Ophthalmoscopy And Near-infrared-II Optical Coherence Tomography. (arXiv:2306.03870v1 [physics.med-ph])
Non-invasive imaging plays a crucial role in diagnosing and studying eye diseases. However, existing photoacoustic ophthalmoscopy (PAOM) techniques in mice have limitations due to handling restrictions, suboptimal optical properties, limited availability of light sources and permissible light fluenc...

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Small-Coupling Dynamic Cavity: A Bayesian Mean-field Framework For Epidemic Inference. (arXiv:2306.03829v1 [cond-mat.dis-nn])
A novel generalized mean field approximation, called the Small-Coupling Dynamic Cavity (SCDC) method, for Bayesian epidemic inference and risk assessment is presented. The method is developed within a fully Bayesian framework and accounts for non-causal effects generated by the presence of observati...

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Computation With Sequences In The Brain. (arXiv:2306.03812v1 [cs.NE])
Even as machine learning exceeds human-level performance on many applications, the generality, robustness, and rapidity of the brain's learning capabilities remain unmatched. How cognition arises from neural activity is a central open question in neuroscience, inextricable from the study of intellig...

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Active Learning Of The Thermodynamics-dynamics Tradeoff In Protein Condensates
Phase-separated biomolecular condensates exhibit a wide range of dynamical properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separ...

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Trial Matching: Capturing Variability With Data-constrained Spiking Neural Networks. (arXiv:2306.03603v1 [q-bio.NC])
Simultaneous behavioral and electrophysiological recordings call for new methods to reveal the interactions between neural activity and behavior. A milestone would be an interpretable model of the co-variability of spiking activity and behavior across trials. Here, we model a cortical sensory-motor ...

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Bernoulli Factories And Duality In Wright-Fisher And Allen-Cahn Models Of Population Genetics. (arXiv:2306.03539v1 [math.PR])
Mathematical models of genetic evolution often come in pairs, connected by a so-called duality relation. The most seminal example are the Wright-Fisher diffusion and the Kingman coalescent, where the former describes the stochastic evolution of neutral allele frequencies in a large population forwar...

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The Mutation Process On The Ancestral Line Under Selection. (arXiv:2306.03512v1 [math.PR])
We consider the Moran model of population genetics with two types, mutation, and selection, and investigate the line of descent of a randomly-sampled individual from a contemporary population. We trace this ancestral line back into the distant past, far beyond the most recent common ancestor of the ...

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Scalable Telomere-to-telomere Assembly For Diploid And Polyploid Genomes With Double Graph
Despite recent advances in the length and the accuracy of long-read data, building haplotype-resolved genome assemblies from telomere to telomere still requires considerable computational resources. In this study, we present an efficient de novo assembly algorithm that combines multiple sequencing t...

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AVIDa-hIL6: A Large-Scale VHH Dataset Produced From An Immunized Alpaca For Predicting Antigen-Antibody Interactions. (arXiv:2306.03329v1 [cs.LG])
Antibodies have become an important class of therapeutic agents to treat human diseases. To accelerate therapeutic antibody discovery, computational methods, especially machine learning, have attracted considerable interest for predicting specific interactions between antibody candidates and target ...

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Evaluation Of Software Impact Designed For Biomedical Research: Are We Measuring What's Meaningful?. (arXiv:2306.03255v1 [cs.SE])
Software is vital for the advancement of biology and medicine. Analysis of usage and impact metrics can help developers determine user and community engagement, justify additional funding, encourage additional use, identify unanticipated use cases, and help define improvement areas. However, there a...

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Optimal Transport For Automatic Alignment Of Untargeted Metabolomic Data. (arXiv:2306.03218v1 [q-bio.QM])
Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery,...

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Navigation Through The Complex World -- The Neurophysiology Of Decision-making Processes
Current theories suggest that adaptive decision-making necessitates the interaction between multiple decision-making systems. The computational definitions of different models of decision-making suggest interactions with task demands and complexity. We review these computational theories and derive ...

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The Feasibility Of Combining Communication BCIs With FES For Individuals With Locked-in Syndrome. (arXiv:2306.03159v1 [q-bio.NC])
Individuals with a locked-in state live with severe whole-body paralysis that limits their ability to communicate with family and loved ones. Recent advances in the brain-computer interface (BCI) technology have presented a potential alternative for these people to communicate by detecting neural ac...

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Score-based Enhanced Sampling For Protein Molecular Dynamics. (arXiv:2306.03117v1 [q-bio.QM])
The dynamic nature of proteins is crucial for determining their biological functions and properties, and molecular dynamics (MD) simulations stand as a predominant tool to study such phenomena. By utilizing empirically derived force fields, MD simulations explore the conformational space through num...

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Bootstrapped Training Of Score-Conditioned Generator For Offline Design Of Biological Sequences. (arXiv:2306.03111v1 [q-bio.QM])
We study the problem of optimizing biological sequences, e.g., proteins, DNA, and RNA, to maximize a black-box score function that is only evaluated in an offline dataset. We propose a novel solution, bootstrapped training of score-conditioned generator (BootGen) algorithm. Our algorithm repeats a t...

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Machine Learning Force Fields With Data Cost Aware Training. (arXiv:2306.03109v1 [q-bio.QM])
Machine learning force fields (MLFF) have been proposed to accelerate molecular dynamics (MD) simulation, which finds widespread applications in chemistry and biomedical research. Even for the most data-efficient MLFFs, reaching chemical accuracy can require hundreds of frames of force and energy la...

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Some Impossibility Results For Inference With Cluster Dependence With Large Clusters
This paper focuses on a setting with observations having a cluster dependence structure and presents two main impossibility results. First, we show that when there is only one large cluster, i.e., the researcher does not have any knowledge on the dependence structure of the observations, it is not p...

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Instrument Validity For Heterogeneous Causal Effects. (arXiv:2009.01995v5 [econ.EM] UPDATED)
This paper provides a general framework for testing instrument validity in heterogeneous causal effect models. The generalization includes the cases where the treatment can be multivalued ordered or unordered. Based on a series of testable implications, we propose a nonparametric test which is prove...

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Orthogonal Statistical Learning. (arXiv:1901.09036v4 [math.ST] UPDATED)
We provide non-asymptotic excess risk guarantees for statistical learning in a setting where the population risk with respect to which we evaluate the target parameter depends on an unknown nuisance parameter that must be estimated from data. We analyze a two-stage sample splitting meta-algorithm th...

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Reparametrization And The Semiparametric Bernstein-von-Mises Theorem. (arXiv:2306.03816v1 [math.ST])
This paper considers Bayesian inference for the partially linear model. Our approach exploits a parametrization of the regression function that is tailored toward estimating a low-dimensional parameter of interest. The key property of the parametrization is that it generates a Neyman orthogonal mome...

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Uniform Inference For Cointegrated Vector Autoregressive Processes
Uniformly valid inference for cointegrated vector autoregressive processes has so far proven difficult due to certain discontinuities arising in the asymptotic distribution of the least squares estimator. We show how asymptotic results from the univariate case can be extended to multiple dimensions ...

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Forecasting The Performance Of US Stock Market Indices During COVID-19: RF Vs LSTM. (arXiv:2306.03620v1 [econ.EM])
The US stock market experienced instability following the recession (2007-2009). COVID-19 poses a significant challenge to US stock traders and investors. Traders and investors should keep up with the stock market. This is to mitigate risks and improve profits by using forecasting models that accoun...

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Robust Inference For The Treatment Effect Variance In Experiments Using Machine Learning
Experimenters often collect baseline data to study heterogeneity. I propose the first valid confidence intervals for the VCATE, the treatment effect variance explained by observables. Conventional approaches yield incorrect coverage when the VCATE is zero. As a result, practitioners could be prone t...

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Surface Passivation Method For Super-repellence Of Aqueous Macromolecular Condensates. (arXiv:2306.02198v1 [cond-mat.soft] CROSS LISTED)
Solutions of macromolecules can undergo liquid-liquid phase separation to form droplets with ultra-low surface tension. Droplets with such low surface tension wet and spread over common surfaces such as test tubes and microscope slides, complicating textit{in vitro} experiments. Development of an un...

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Bubble Nucleation And Jetting Inside A Millimetric Droplet. (arXiv:2303.15047v2 [physics.flu-dyn] UPDATED)
In this work, we present experiments and simulations on the nucleation and successive dynamics of laser-induced bubbles inside liquid droplets in free-fall motion, i.e. a case with a free boundary in all directions. The droplets of a millimetric size have a nearly spherical shape by the moment the b...

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Electric Interface Condition For Sliding And Viscous Contacts. (arXiv:2303.00718v2 [physics.class-ph] UPDATED)
First principles of electromagnetism impose that the tangential electric field must be continuous at the interface between two media. The definition of the electric field depends on the frame of reference leading to an ambiguity in the mathematical expression of the continuity condition when the two...

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Performance Of The 1-ton Prototype Neutrino Detector At CJPL-I
China Jinping Underground Laboratory provides an ideal site for solar, geo-, and supernova neutrino studies. With a prototype neutrino detector running since 2017, containing 1-ton liquid scintillator, we tested its experimental hardware, performed the detector calibration and simulation, and measur...

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Context-aware Multi-head Self-attentional Neural Network Model For Next Location Prediction. (arXiv:2212.01953v2 [physics.soc-ph] UPDATED)
Accurate activity location prediction is a crucial component of many mobility applications and is particularly required to develop personalized, sustainable transportation systems. Despite the widespread adoption of deep learning models, next location prediction models lack a comprehensive discussio...

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Social Contagion Induced By Uncertain Information. (arXiv:2212.01755v2 [physics.soc-ph] UPDATED)
Information and individual activities often spread globally through the network of social ties. While social contagion phenomena have been extensively studied within the framework of threshold models, it is common to make an assumption that may be violated in reality: each individual is able to obse...

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ITVOLT: An Iterative Solver For The Time-Dependent Schrödinger Equation
We present a novel approach for solving the time-dependent Schrödinger equation (TDSE). The method we propose converts the TDSE to an equivalent Volterra integral equation; introducing a global Lagrange interpolation of the integrand transforms the equation to a linear system, which is then solved i...

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Control Of An Atomic Quadrupole Transition In A Phase-stable Standing Wave
Using a single calcium ion confined in a surface-electrode trap, we study the interaction of electric quadrupole transitions with a passively phase-stable optical standing wave field sourced by photonics integrated within the trap. We characterize the optical fields through spatial mapping of the Ra...

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Robust Free-Space Optical Communication Utilizing Polarization
Free-space optical (FSO) communication can be subject to various types of distortion and loss as the signal propagates through non-uniform media. In experiment and simulation, we demonstrate that the state of polarization and degree of polarization of light passed though underwater bubbles, causing ...

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Coherent Qubit Measurement In Cavity-Transmon Quantum Systems. (arXiv:2112.09272v3 [quant-ph] UPDATED)
A measurement of the time between quantum jumps implies the capability to measure the next jump. During the time between jumps the quantum system is not evolving in a closed or unitary manner. While the wave function maintains phase coherence it evolves according to a non-Hermitian effective Hamilto...

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Experimental Study On Wave Attenuation By Vegetation By Means Of Particle Imaging Velocimetry. (arXiv:2010.07198v3 [physics.flu-dyn] UPDATED)
Coastal vegetation serves as an ecological defense and plays an important role when facing marine disaster such as storm surge. In this study, we investigated experimentally the wave attenuation, including wave height and wave force decay, and flow field within rigid vegetation by means of particle ...

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Laboratory Study Of Wave Attenuation By Mangrove Forest. (arXiv:2010.07173v3 [physics.flu-dyn] UPDATED)
Coastal vegetation can dissipate the energy of storm surge and tsunami, which serves a natural barrier for coastal protection. The experimental study of waves-mangroves interaction was carried out to evaluate the efficiency of wave attenuation by vegetation (WDV). In particular, the model mangrove c...

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Laboratory Study Of Turbulent Kinetic Energy Within Mangrove Forest Under Waves. (arXiv:2010.07148v3 [physics.flu-dyn] UPDATED)
Laboratory study was set out to investigate the flow structure and turbulent kinetic energy ($TKE$) within mangrove forest considering flexible canopies and rigid stems under various wave conditions. Canopies and stems have different effects on turbulence generation. The flexible leaves in canopy sc...

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Quantum Computation And Simulation Using Fermion-Pair Registers. (arXiv:2306.03905v1 [quant-ph])
We propose and analyze an approach to realize quantum computation and simulation using fermionic particles under quantum gas microscopes. Our work is inspired by a recent experimental demonstration of large-scale quantum registers, where tightly localized fermion pairs are used to encode qubits exhi...

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Synchronous Micromechanically Resonant Programmable Photonic Circuits. (arXiv:2306.03895v1 [physics.optics])
Programmable photonic integrated circuits (PICs) are emerging as powerful tools for the precise manipulation of light, with applications in quantum information processing, optical range finding, and artificial intelligence. The leading architecture for programmable PICs is the mesh of Mach-Zehnder i...

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Vortex Rings Generated By A Translating Disk From Start To Stop. (arXiv:2306.03867v1 [physics.flu-dyn])
In this article, we investigate experimentally and numerically the time evolution of vortex rings generated by the translation of a rigid disk in a fluid initially at rest and submitted to an acceleration followed by a deceleration. The size of the disk and its motion in terms of stroke length and t...

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Data-driven Modeling Of An Oscillating Surge Wave Energy Converter Using Dynamic Mode Decomposition. (arXiv:2306.03861v1 [physics.flu-dyn])
Modeling wave energy converters (WECs) to accurately predict their hydrodynamic behavior has been a challenge for the wave energy field. Often, this results in either low-fidelity, linear models that break down in energetic seas, or high-fidelity numerical models that are too computationally expensi...

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Observation Of Landau Levels And Topological Edge States In Photonic Crystals Through Pseudomagnetic Fields Induced By Synthetic Strain. (arXiv:2306.03860v1 [physics.optics])
The control over light propagation and localization in photonic crystals offers wide applications from sensing and on-chip routing to lasing and quantum light-matter interfaces. While in electronic crystals magnetic fields can be used to induce a multitude of unique phenomena, the uncharged nature o...

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Polarizability Plays A Decisive Role In Modulating Association Between Molecular Cations And Anions. (arXiv:2306.03851v1 [physics.chem-ph])
Electrostatic interactions involving proteins depend not just on the ionic charges involved but also on their chemical identities. Here we examine the origins of incompletely understood differences in the strength of association of different pairs of monovalent molecular ions that are relevant to pr...

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Topological Nature Of Non-Hermitian Degenerate Bands In Structural Parameter Space
In photonics, band degeneracies at high-symmetry points in wavevector space have been shown to exhibit rich physical phenomena. However, obtaining degenerate bands away from such points is highly nontrivial. In this work, we achieve complex band degeneracy in a photonic crystal structure over a regi...

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Spherical Fourier Neural Operators: Learning Stable Dynamics On The Sphere. (arXiv:2306.03838v1 [cs.LG])
Fourier Neural Operators (FNOs) have proven to be an efficient and effective method for resolution-independent operator learning in a broad variety of application areas across scientific machine learning. A key reason for their success is their ability to accurately model long-range dependencies in ...

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High Speed Flows With Particles On Demand: Boundary Conditions. (arXiv:2306.03821v1 [physics.flu-dyn])
The particles on demand (PonD) method is a new kinetic theory model that allows for simulation of high speed compressible flows. While standard Lattice-Boltzmann is limited by a fixed reference frame, significantly reducing the range of applicable of Mach numbers, PonD takes advantage of adaptive re...

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Azimuthal Ion Movement In HiPIMS Plasmas -- Part II: Lateral Growth Fluxes. (arXiv:2306.03811v1 [physics.plasm-ph])
The transport of sputtered species from the target of a magnetron plasma to a collecting surface at the circumference of the plasma is analyzed using a particle tracer technique. A small chromium insert at the racetrack position inside a titanium target is used as the source of tracer particles, whi...

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Localization And Mobility Edges In Non-Hermitian Disorder-free Lattices. (arXiv:2306.03807v1 [cond-mat.dis-nn])
The non-Hermitian skin effect (NHSE) is a significant phenomenon observed in non-Hermitian systems under open boundary conditions, where the extensive bulk eigenstates tend to accumulate at the lattice edges. In this article, we investigate how an electric field affects the localization properties i...

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Azimuthal Ion Movement In HiPIMS Plasmas -- Part I: Velocity Distribution Function. (arXiv:2306.03794v1 [physics.plasm-ph])
Magnetron sputtering discharges feature complex magnetic field configurations to confine the electrons close to the cathode surface. This magnetic field configuration gives rise to a strong electron drift in azimuthal direction, with typical drift velocities on the order of SI{100}{kilometerpersecon...

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Development Of On-Ground Hardware In Loop Simulation Facility For Space Robotics. (arXiv:2306.03785v1 [cs.RO])
Over a couple of decades, space junk has increased rapidly, which has caused significant threats to the LEO operation satellites. An Active Debris Removal $(ADR)$ concept continuously evolves for space junk removal. One of the ADR methods is Space Robotics, whose function is to chase, capture and de...

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Future Green Technology: Freezing Water Micro-droplet As An All-optical Switch Based On Time Domain Photonic Hook
Here we show that mesoscale freezing water droplet with low Bond number can behave as fully biocompatible natural microlenses to form the photonic hook in application to tunable optical switch. We first introduce and demonstrated the basic concepts of all-optical switch without changes in the wavele...

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Imitation Dynamics On Networks With Incomplete Social Information. (arXiv:2306.03781v1 [physics.soc-ph])
Imitation is an important social learning heuristic in animal and human societies that drives the evolution of collective behaviors. Previous explorations find that the fate of cooperators has a sensitive dependence on the protocol of imitation, including the number of social peers used for comparis...

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Thermal Extraction Of Volatiles From Lunar And Asteroid Regolith In Axisymmetric Crank-Nicholson Modeling. (arXiv:2306.03776v1 [astro-ph.EP])
A physics-based computer model has been developed to support the development of volatile extraction from regolith of the Moon and asteroids. The model is based upon empirical data sets for extraterrestrial soils and simulants, including thermal conductivity of regolith and mixed composition ice, hea...

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Accelerating Optimal Elemental Configuration Search In Crystal Using Ising Machine
This research demonstrates that Ising machines can effectively solve optimal elemental configuration searches in crystals, with Au-Cu alloys serving as an example. The energy function is derived using the cluster expansion method in the form of a QUBO function, enabling efficient problem-solving via...

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A Fast Tunable Driver Of Light Source For The TRIDENT Pathfinder Experiment. (arXiv:2305.01967v2 [physics.ins-det] UPDATED)
TRIDENT (The tRopIcal DEep-sea Neutrino Telescope) is a proposed next-generation neutrino telescope to be constructed in the South China Sea. In September 2021, the TRIDENT Pathfinder experiment (TRIDENT EXplorer, T-REX for short) was conducted to evaluate the in-situ optical properties of seawater....

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Spatial Intermittency Of Particle Distribution In Relativistic Plasma Turbulence. (arXiv:2304.11000v2 [physics.plasm-ph] UPDATED)
Relativistic magnetically dominated turbulence is an efficient engine for particle acceleration in a collisionless plasma. Ultrarelativistic particles accelerated by interactions with turbulent fluctuations form non-thermal power-law distribution functions in the momentum (or energy) space, $f(gamma...

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The Spinorial Ball: A Macroscopic Object Of Spin-1/2. (arXiv:2303.15215v2 [physics.ed-ph] UPDATED)
Historically, the observation of half-spin particles was one of the most surprising features of quantum mechanics. They are often described as "objects that do not come back to their initial state after one turn but do after two turns". There are macroscopic implementations using constraints such as...

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Inexact Iterative Numerical Linear Algebra For Neural Network-based Spectral Estimation And Rare-event Prediction
Understanding dynamics in complex systems is challenging because there are many degrees of freedom, and those that are most important for describing events of interest are often not obvious. The leading eigenfunctions of the transition operator are useful for visualization, and they can provide an e...

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Automated Patent Extraction Powers Generative Modeling In Focused Chemical Spaces. (arXiv:2303.08272v2 [physics.chem-ph] UPDATED)
Deep generative models have emerged as an exciting avenue for inverse molecular design, with progress coming from the interplay between training algorithms and molecular representations. One of the key challenges in their applicability to materials science and chemistry has been the lack of access t...

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3D Tracking Of Particles In A Dusty Plasma By Laser Sheet Tomography
The collective behavior of levitated particles in a weakly-ionized plasma (dusty plasma) has raised significant scientific interest. This is due to the complex array of forces acting on the particles, and their potential to act as in-situ diagnostics of the plasma environment. Ideally, the three-dim...

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Hydrogen And Hydrogen-like-ion Bound States And Hyperfine Splittings: Finite Nuclear Size Effects}. (arXiv:2302.06288v2 [physics.atom-ph] UPDATED)
Using the Dirac equation, we study corrections to electron binding energies and hyperfine splittings of atomic hydrogen and hydrogen-like ions due to finite nuclear size (FNS) effects, relativistic QED radiative corrections and nuclear recoil corrections. Three models for the charge distribution and...

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Analog Photonics Computing For Information Processing, Inference And Optimisation. (arXiv:2301.11760v2 [physics.optics] UPDATED)
This review presents an overview of the current state-of-the-art in photonics computing, which leverages photons, photons coupled with matter, and optics-related technologies for effective and efficient computational purposes. It covers the history and development of photonics computing and modern a...

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Near-Landauer-Bound Quantum Computing Using Single Spins
This study is the first experimental verification of the Landauer bound on a single spin, which is the smallest information carrier in size. We used four experiments (single spin experiment, giant spin experiment, nanomagnet experiment, and Stern-Gerlach experiment) to demonstrate that a single spin...

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Solenoidal Force Balances In Numerical Dynamos. (arXiv:2212.13625v2 [physics.geo-ph] UPDATED)
Numerical simulations of the geodynamo (and other planetary dynamos) have made significant progress in recent years. As computing power has advanced, some new models claim to be ever more appropriate for understanding Earth's core dynamics. One measure of the success of such models is the ability to...

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Achiral Dielectric Metasurfaces For Spectral And Polarization Control Of Valley Specific Light Emission From Monolayer MoS2. (arXiv:2212.09147v2 [physics.optics] UPDATED)
Excitons in two-dimensional transition metal dichalcogenides have a valley degree of freedom that can be optically accessed and manipulated for quantum information processing. Here, we integrate MoS2 with achiral silicon disk array metasurfaces to enhance and control valley-specific absorption and e...

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Bayesian Learning Of Coupled Biogeochemical-Physical Models. (arXiv:2211.06714v2 [cs.CE] UPDATED)
Predictive dynamical models for marine ecosystems are used for a variety of needs. Due to sparse measurements and limited understanding of the myriad of ocean processes, there is however significant uncertainty. There is model uncertainty in the parameter values, functional forms with diverse parame...

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Optical Scattering Imaging With Sub-nanometer Precision Based On Position-ultra-sensitive Giant Lamb Shift. (arXiv:2211.03247v2 [quant-ph] UPDATED)
The Lamb shift of a quantum emitter very close to a plasmonic nanostructure, mainly induced by the higher-order plasmonic dark modes, can be three or more orders of magnitude larger than that in the free space and it is ultra-sensitive to the emitter position and polarization. We show that this gian...

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CBLab: Supporting The Training Of Large-scale Traffic Control Policies With Scalable Traffic Simulation. (arXiv:2210.00896v2 [physics.soc-ph] UPDATED)
Traffic simulation provides interactive data for the optimization of traffic control policies. However, existing traffic simulators are limited by their lack of scalability and shortage in input data, which prevents them from generating interactive data from traffic simulation in the scenarios of re...

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Inferring The Dense Matter Equation Of State From Neutron Star Observations Via Artificial Neural Networks. (arXiv:2208.13163v2 [nucl-th] UPDATED)
The difficulty in describing the equation of state (EoS) for nuclear matter at densities above the saturation density ($rho_0$) has led to the emergence of a multitude of models based on different assumptions and techniques. These EoSs, when used to describe a neutron star (NS), lead to differing va...

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Enhancing The Sensitivity Of Nonlinearity Sensors Through Homodyne Detection In Dissipatively Coupled Systems
In this manuscript, we propose a new sensing mechanism to enhance the sensitivity of a quantum system to nonlinearities by homodyning the amplitude quadrature of the cavity field. The system consists of two dissipatively coupled cavity modes, one of which is subject to single- and two-photon drives....

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A Single Particle Model With Electrolyte And Side Reactions For Degradation Of Lithium-ion Batteries. (arXiv:2206.05078v2 [physics.chem-ph] UPDATED)
Battery degradation, which is the reduction of performance over time, is one of the main roadblocks to the wide deployment of lithium-ion batteries. Physics-based models, such as those based on the Doyle-Fuller-Newman model, are invaluable tools to understand and predict such phenomena. However, the...

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Multi-tasking Via Baseline Control In Recurrent Neural Networks
Changes in an animal's behavioral state, such as arousal and movements, induce {complex modulations of the baseline input currents to sensory areas, eliciting sensory modality-specific effects. A simple computational principle explaining the effects of baseline modulations to recurrent cortical circ...

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Correlated Reference-assisted Variational Quantum Eigensolver
We propose an active-space approximation to reduce the quantum resources required for variational quantum eigensolver (VQE). Starting from the double exponential unitary coupled-cluster ansatz and employing the downfolding technique, we arrive at an effective Hamiltonian for active space composed of...

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Universality Of SIS Epidemics Starting From Small Initial Conditions
We are investigating deterministic SIS dynamics on large networks starting from only a few infected individuals. Under mild assumptions we show that any two epidemic curves - on the same network and with the same parameters - are almost identical up to time translation when initial conditions are sm...

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All-optical Determination Of One Or Two Emitters Using Quantum Polarization With Nitrogen-vacancy Centers In Diamond. (arXiv:2203.16101v2 [quant-ph] UPDATED)
Qubit technologies using nitrogen-vacancy color centers in diamonds require precise knowledge of the centers, including the number of emitters within a diffraction-limited spot and their orientations. However, the number of emitters is challenging to determine when there is finite background, which ...

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An 8 GeV Linac As The Booster Replacement In The Fermilab Power Upgrade: A Snowmass 2021 White Paper
Following the PIP-II 800 MeV Linac, Fermilab will need an accelerator that extends from that linac to the MI injection energy of ~8 GeV, completing the modernization of the Fermilab high-intensity accelerator complex. This will maximize the beam available for neutrino production for the long baselin...

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Reflectionless Plasma Ignition Via High-Power Virtual Perfect Absorption. (arXiv:2306.03071v1 [physics.plasm-ph])
Plasma ignition is critical in various scientific and industrial applications, demanding an efficient and robust execution mechanism. In this work, we present an innovative approach to plasma ignition by incorporating the analysis of fundamental aspects of light scattering in the complex frequency p...

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Influence Of The Finite Transverse Size Of The Accelerating Region On The Relativistic Feedback. (arXiv:2306.03059v1 [physics.ao-ph])
Terrestrial gamma-ray flashes (TGFs) are commonly associated with relativistic runaway electron avalanches (RREAs). However, research shows that a single RREA cannot generate observable TGF fluxes. In an attempt to settle this issue the relativistic feedback mechanism was suggested by Joseph Dwyer. ...

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Light-activated Memristor By Au-nanoparticle Embedded HfO2-bilayer/p-Si MOS Device. (arXiv:2306.03044v1 [physics.app-ph])
The current work proposes a novel scheme for developing a light-activated non-filamentary memristor device by fabricating an Au-nanoparticle embedded HfO2-bilayer/p-Si MOS structure. Under illumination, the electrons in such embedded Au-nanoparticles are excited from d-level to quantized s-p level a...

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Circular Dichroism Induction In WS2 By A Chiral Plasmonic Metasurface
We investigate the interaction between a monolayer of WS2 and a chiral plasmonic metasurface. WS2 possesses valley excitons that selectively couple with one-handed circularly polarised light. At the same time, the chiral plasmonic metasurface exhibits spin-momentum locking, leading to a robust polar...

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Evaluation Of Ultrasound Sensors For Transcranial Photoacoustic Sensing And Imaging. (arXiv:2306.03020v1 [physics.med-ph])
Biomedical photoacoustic (PA) imaging is typically used to exploit absorption-based contrast in soft tissue at depths of several centimeters. When it is applied to measuring PA waves generated in the brain, the acoustic properties of the skull bone cause not only strong attenuation but also a distor...

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Hubbard Parameters For Programmable Tweezer Arrays. (arXiv:2306.03019v1 [cond-mat.quant-gas])
The experimental realization of Fermi-Hubbard tweezer arrays opens a new stage for engineering fermionic matter, where programmable lattice geometries and Hubbard model parameters are combined with single-site imaging. In order to use these versatile experimental Fermi-Hubbard models as quantum simu...

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Stockmayer Supracolloidal Magnetic Polymers Under The Influence Of An Applied Magnetic Field And A Shear Flow. (arXiv:2306.03005v1 [cond-mat.soft])
The idea of creating magnetically controllable colloids whose rheological properties can be finely tuned on the nano- or micro-scale has caused a lot of experimental and theoretical effort. The latter resulted in systems whose building blocks are ranging between single magnetic nanoparticles to comp...

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Predicting Temporal Aspects Of Movement For Predictive Replication In Fog Environments. (arXiv:2306.00575v2 [cs.DC] UPDATED)
To fully exploit the benefits of the fog environment, efficient management of data locality is crucial. Blind or reactive data replication falls short in harnessing the potential of fog computing, necessitating more advanced techniques for predicting where and when clients will connect. While spatia...

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Scheduling Fork-Join Task Graphs To Heterogeneous Processors. (arXiv:2305.17556v2 [cs.DC] UPDATED)
The scheduling of task graphs with communication delays has been extensively studied. Recently, new results for the common sub-case of fork-join shaped task graphs were published, including an EPTAS and polynomial algorithms for special cases. These new results modelled the target architecture to co...

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FilFL: Client Filtering For Optimized Client Participation In Federated Learning. (arXiv:2302.06599v2 [cs.LG] UPDATED)
Federated learning is an emerging machine learning paradigm that enables clients to train collaboratively without exchanging local data. The clients participating in the training process have a crucial impact on the convergence rate, learning efficiency, and model generalization. In this work, we pr...

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DVFO: Dynamic Voltage, Frequency Scaling And Workload Offloading For DNN Edge Inference. (arXiv:2306.01811v1 [cs.LG])
Due to edge device resource constraints and different characteristics of deep neural network (DNN) models, it is a big challenge to optimize DNN inference performance in terms of energy consumption and inference latency on edge devices. In addition to the dynamic voltage frequency scaling (DVFS) tec...

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Scaling Multi-Objective Security Games Provably Via Space Discretization Based Evolutionary Search. (arXiv:2303.15821v2 [cs.LG] UPDATED)
In the field of security, multi-objective security games (MOSGs) allow defenders to simultaneously protect targets from multiple heterogeneous attackers. MOSGs aim to simultaneously maximize all the heterogeneous payoffs, e.g., life, money, and crime rate, without merging heterogeneous attackers. In...

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Multifunctionality In A Connectome-Based Reservoir Computer. (arXiv:2306.01885v1 [cs.LG])
Multifunctionality describes the capacity for a neural network to perform multiple mutually exclusive tasks without altering its network connections; and is an emerging area of interest in the reservoir computing machine learning paradigm. Multifunctionality has been observed in the brains of humans...

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ErfReLU: Adaptive Activation Function For Deep Neural Network. (arXiv:2306.01822v1 [cs.NE])
Recent research has found that the activation function (AF) selected for adding non-linearity into the output can have a big impact on how effectively deep learning networks perform. Developing activation functions that can adapt simultaneously with learning is a need of time. Researchers recently s...

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Understanding Idea Creation In Collaborative Discourse Through Networks: The Joint Attention-Interaction-Creation (AIC) Framework
In Computer-Supported Collaborative Learning, ideas generated through collaborative discourse are informative indicators of students' learning and collaboration. Idea creation is a product of emergent and interactive socio-cognitive endeavors. Therefore, analyzing ideas requires capturing contextual...

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Reconstructing Graph Diffusion History From A Single Snapshot. (arXiv:2306.00488v2 [cs.LG] UPDATED)
Diffusion on graphs is ubiquitous with numerous high-impact applications. In these applications, complete diffusion histories play an essential role in terms of identifying dynamical patterns, reflecting on precaution actions, and forecasting intervention effects. Despite their importance, complete ...

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Beyond Rankings: Exploring The Impact Of SERP Features On Organic Click-through Rates. (arXiv:2306.01785v1 [cs.IR])
Search Engine Result Pages (SERPs) serve as the digital gateways to the vast expanse of the internet. Past decades have witnessed a surge in research primarily centered on the influence of website ranking on these pages, to determine the click-through rate (CTR). However, during this period, the lan...

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Capacity Constrained Influence Maximization In Social Networks. (arXiv:2306.01782v1 [cs.SI])
Influence maximization (IM) aims to identify a small number of influential individuals to maximize the information spread and finds applications in various fields. It was first introduced in the context of viral marketing, where a company pays a few influencers to promote the product. However, apart...

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Comparative Analysis Of Widely Use Object-Oriented Languages
Programming is an integral part of computer science discipline. Every day the programming environment is not only rapidly growing but also changing and languages are constantly evolving. Learning of object-oriented paradigm is compulsory in every computer science major so the choice of language to t...

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Tiebout Meets Schelling Online: Sorting In Cybercommunities. (arXiv:2110.05608v2 [econ.GN] UPDATED)
This paper proposes a stylised model to address the issue of online sorting. There are two large homogeneous groups of individuals. Everyone must choose between two online platforms, one of which has superior amenities. Each individual enjoys interacting online with those from their own group but di...

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Significance Bands For Local Projections
An impulse response function describes the dynamic evolution of an outcome variable following a stimulus or treatment. A common hypothesis of interest is whether the treatment affects the outcome. We show that this hypothesis is best assessed using significance bands rather than relying on commonly ...

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Frequency Regulation With Storage: On Losses And Profits. (arXiv:2306.02987v1 [math.OC])
Low-carbon societies will need to store vast amounts of electricity to balance intermittent generation from wind and solar energy, for example, through frequency regulation. Here, we derive an analytical solution to the decision-making problem of storage operators who sell frequency regulation power...

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Improving The Accuracy Of Bubble Date Estimators Under Time-varying Volatility
In this study, we consider a four-regime bubble model under the assumption of time-varying volatility and propose the algorithm of estimating the break dates with volatility correction: First, we estimate the emerging date of the explosive bubble, its collapsing date, and the recovering date to the ...

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Rebooting Internet Immunity. (arXiv:2306.02876v1 [econ.GN])
We do everything online. We shop, travel, invest, socialize, and even hold garage sales. Even though we may not care whether a company operates online or in the physical world, however, the question has dramatic consequences for the companies themselves. Online and offline entities are governed by d...

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Toward Textual Internet Immunity. (arXiv:2306.02875v1 [econ.GN])
Internet immunity doctrine is broken. Under Section 230 of the Communications Decency Act of 1996, online entities are absolutely immune from lawsuits related to content authored by third parties. The law has been essential to the internet's development over the last twenty years, but it has not kep...

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Big Tech's Tightening Grip On Internet Speech. (arXiv:2306.02874v1 [econ.GN])
Online platforms have completely transformed American social life. They have democratized publication, overthrown old gatekeepers, and given ordinary Americans a fresh voice in politics. But the system is beginning to falter. Control over online speech lies in the hands of a select few -- Facebook, ...

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Synthetic Matching Control Method. (arXiv:2306.02584v1 [econ.EM])
Estimating weights in the synthetic control method involves an optimization procedure that simultaneously selects and aligns control units in order to closely match the treated unit. However, this simultaneous selection and alignment of control units may lead to a loss of efficiency in the synthetic...

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Physical Energy Cost Serves As The ''invisible Hand'' Governing Economic Valuation: Direct Evidence From Biogeochemical Data And The U.S. Metal Market. (arXiv:2306.02328v1 [econ.GN])
Energy supply is mandatory for the production of economic value. Nevertheless, tradition dictates that an enigmatic 'invisible hand' governs economic valuation. Physical scientists have long proposed alternative but testable energy cost theories of economic valuation, and have shown the gross correl...

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Buying Time: Latency Racing Vs. Bidding In Fair Transaction Ordering
We design a practical algorithm for transaction ordering that takes into account both transaction timestamps and bids. The algorithm guarantees that users get their transactions published with bounded delay against a bid, while it extracts a fair value from sophisticated users that have an edge in l...

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Individual Causal Inference Using Panel Data With Multiple Outcomes
Policy evaluation in empirical microeconomics has been focusing on estimating the average treatment effect and more recently the heterogeneous treatment effects, often relying on the unconfoundedness assumption. We propose a method based on the interactive fixed effects model to estimate treatment e...

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The Synthetic Control Method With Nonlinear Outcomes: Estimating The Impact Of The 2019 Anti-Extradition Law Amendments Bill Protests On Hong Kong's Economy. (arXiv:2306.01967v1 [econ.EM])
The synthetic control estimator (Abadie et al., 2010) is asymptotically unbiased assuming that the outcome is a linear function of the underlying predictors and that the treated unit can be well approximated by the synthetic control before the treatment. When the outcome is nonlinear, the bias of th...

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Rank-heterogeneous Preference Models For School Choice. (arXiv:2306.01801v1 [stat.AP])
School choice mechanism designers use discrete choice models to understand and predict families' preferences. The most widely-used choice model, the multinomial logit (MNL), is linear in school and/or household attributes. While the model is simple and interpretable, it assumes the ranked preference...

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Nash Equilibrium And Axiom Of Choice Are Equivalent
In this paper, I prove that existence of pure-strategy Nash equilibrium in games with infinitely many players is equivalent to the axiom of choice.

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ACETest: Automated Constraint Extraction For Testing Deep Learning Operators. (arXiv:2305.17914v2 [cs.SE] UPDATED)
Deep learning (DL) applications are prevalent nowadays as they can help with multiple tasks. DL libraries are essential for building DL applications. Furthermore, DL operators are the important building blocks of the DL libraries, that compute the multi-dimensional data (tensors). Therefore, bugs in...

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Privet: A Privacy-Preserving Vertical Federated Learning Service For Gradient Boosted Decision Tables. (arXiv:2305.12652v2 [cs.CR] UPDATED)
Vertical federated learning (VFL) has recently emerged as an appealing distributed paradigm empowering multi-party collaboration for training high-quality models over vertically partitioned datasets. Gradient boosting has been popularly adopted in VFL, which builds an ensemble of weak learners (typi...

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NNSplitter: An Active Defense Solution For DNN Model Via Automated Weight Obfuscation. (arXiv:2305.00097v2 [cs.LG] UPDATED)
As a type of valuable intellectual property (IP), deep neural network (DNN) models have been protected by techniques like watermarking. However, such passive model protection cannot fully prevent model abuse. In this work, we propose an active model IP protection scheme, namely NNSplitter, which act...

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Decentralized Threshold Signatures With Dynamically Private Accountability. (arXiv:2304.07937v3 [cs.CR] UPDATED)
Threshold signatures are a fundamental cryptographic primitive used in many practical applications. As proposed by Boneh and Komlo (CRYPTO'22), TAPS is a threshold signature that is a hybrid of privacy and accountability. It enables a combiner to combine t signature shares while revealing nothing ab...

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Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. (arXiv:2302.01677v2 [cs.LG] UPDATED)
In this work, besides improving prediction accuracy, we study whether personalization could bring robustness benefits to backdoor attacks. We conduct the first study of backdoor attacks in the pFL framework, testing 4 widely used backdoor attacks against 6 pFL methods on benchmark datasets FEMNIST a...

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Protecting Cache States Against Both Speculative Execution Attacks And Side-channel Attacks. (arXiv:2302.00732v2 [cs.CR] UPDATED)
Hardware caches are essential performance optimization features in modern processors to reduce the effective memory access time. Unfortunately, they are also the prime targets for attacks on computer processors because they are high-bandwidth and reliable side or covert channels for leaking secrets....

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Stochastic Differentially Private And Fair Learning. (arXiv:2210.08781v2 [cs.LG] UPDATED)
Machine learning models are increasingly used in high-stakes decision-making systems. In such applications, a major concern is that these models sometimes discriminate against certain demographic groups such as individuals with certain race, gender, or age. Another major concern in these application...

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Systemic Risk And Vulnerability Analysis Of Multi-cloud Environments. (arXiv:2306.01862v1 [cs.CR])
With the increasing use of multi-cloud environments, security professionals face challenges in configuration, management, and integration due to uneven security capabilities and features among providers. As a result, a fragmented approach toward security has been observed, leading to new attack vect...

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Differential Privacy With Random Projections And Sign Random Projections. (arXiv:2306.01751v1 [cs.CR])
In this paper, we develop a series of differential privacy (DP) algorithms from a family of random projections (RP), for general applications in machine learning, data mining, and information retrieval. Among the presented algorithms, textbf{iDP-SignRP} is remarkably effective under the setting of `...

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Fast $(1+\varepsilon)$-Approximation Algorithms For Binary Matrix Factorization. (arXiv:2306.01869v1 [cs.DS])
We introduce efficient $(1+varepsilon)$-approximation algorithms for the binary matrix factorization (BMF) problem, where the inputs are a matrix $mathbf{A}in{0,1}^{ntimes d}$, a rank parameter $k>0$, as well as an accuracy parameter $varepsilon>0$, and the goal is to approximate $mathbf{A}$ as a pr...

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Revisiting Garg's 2-Approximation Algorithm For The K-MST Problem In Graphs
This paper revisits the 2-approximation algorithm for $k$-MST presented by Garg in light of a recent paper of Paul et al.. In the $k$-MST problem, the goal is to return a tree spanning $k$ vertices of minimum total edge cost. Paul et al. extend Garg's primal-dual subroutine to improve the approximat...

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A Survey Of Approximation Algorithms For Capacitated Vehicle Routing Problems
Finding the shortest travelling tour of vehicles with capacity k from the depot to the customers is called the Capacity vehicle routing problem (CVRP). CVRP plays an essential position in logistics systems, and it is the most intensively studied problem in combinatorial optimization. In complexity, ...

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Embedding Security Into Ferroelectric FET Array Via In-Situ Memory Operation. (arXiv:2306.01863v1 [cs.ET])
Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared ...

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Prototyping The Use Of Large Language Models (LLMs) For Adult Learning Content Creation At Scale. (arXiv:2306.01815v1 [cs.CY])
As Large Language Models (LLMs) and other forms of Generative AI permeate various aspects of our lives, their application for learning and education has provided opportunities and challenges. This paper presents an investigation into the use of LLMs in asynchronous course creation, particularly with...

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Citizen Perspectives On Necessary Safeguards To The Use Of AI By Law Enforcement Agencies
In the light of modern technological advances, Artificial Intelligence (AI) is relied upon to enhance performance, increase efficiency, and maximize gains. For Law Enforcement Agencies (LEAs), it can prove valuable in optimizing evidence analysis and establishing proactive prevention measures. Never...

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Voluminous Yet Vacuous? Semantic Capital In An Age Of Large Language Models. (arXiv:2306.01773v1 [cs.CY])
Large Language Models (LLMs) have emerged as transformative forces in the realm of natural language processing, wielding the power to generate human-like text. However, despite their potential for content creation, they carry the risk of eroding our Semantic Capital (SC) - the collective knowledge w...

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Data Science In An Agent-Based Simulation World. (arXiv:2306.01764v1 [cs.CY])
In data science education, the importance of learning to solve real-world problems has been argued. However, there are two issues with this approach: (1) it is very costly to prepare multiple real-world problems (using real data) according to the learning objectives, and (2) the learner must suddenl...

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Channel-Aware Pretraining Of Joint Encoder-Decoder Self-Supervised Model For Telephonic-Speech ASR
This paper proposes a novel technique to obtain better downstream ASR performance from a joint encoder-decoder self-supervised model when trained with speech pooled from two different channels (narrow and wide band). The joint encoder-decoder self-supervised model extends the HuBERT model with a Tra...

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Position Tracking Of A Varying Number Of Sound Sources With Sliding Permutation Invariant Training
Recent data- and learning-based sound source localization (SSL) methods have shown strong performance in challenging acoustic scenarios. However, little work has been done on adapting such methods to track consistently multiple sources appearing and disappearing, as would occur in reality. In this p...

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Disentangling Speech From Surroundings With Neural Embeddings
We present a method to separate speech signals from noisy environments in the embedding space of a neural audio codec. We introduce a new training procedure that allows our model to produce structured encodings of audio waveforms given by embedding vectors, where one part of the embedding vector rep...

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On The Behavior Of Intrusive And Non-intrusive Speech Enhancement Metrics In Predictive And Generative Settings. (arXiv:2306.03014v1 [eess.AS])
Since its inception, the field of deep speech enhancement has been dominated by predictive (discriminative) approaches, such as spectral mapping or masking. Recently, however, novel generative approaches have been applied to speech enhancement, attaining good denoising performance with high subjecti...

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PolyVoice: Language Models For Speech To Speech Translation
We propose PolyVoice, a language model-based framework for speech-to-speech translation (S2ST) system. Our framework consists of two language models: a translation language model and a speech synthesis language model. We use discretized speech units, which are generated in a fully unsupervised way, ...

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Simultaneous Or Sequential Training? How Speech Representations Cooperate In A Multi-Task Self-Supervised Learning System. (arXiv:2306.02972v1 [eess.AS])
Speech representation learning with self-supervised algorithms has resulted in notable performance boosts in many downstream tasks. Recent work combined self-supervised learning (SSL) and visually grounded speech (VGS) processing mechanisms for representation learning. The joint training with SSL an...

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N-Shot Benchmarking Of Whisper On Diverse Arabic Speech Recognition. (arXiv:2306.02902v1 [cs.CL])
Whisper, the recently developed multilingual weakly supervised model, is reported to perform well on multiple speech recognition benchmarks in both monolingual and multilingual settings. However, it is not clear how Whisper would fare under diverse conditions even on languages it was evaluated on su...

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Vocoder Drift In X-vector-based Speaker Anonymization. (arXiv:2306.02892v1 [eess.AS])
State-of-the-art approaches to speaker anonymization typically employ some form of perturbation function to conceal speaker information contained within an x-vector embedding, then resynthesize utterances in the voice of a new pseudo-speaker using a vocoder. Strategies to improve the x-vector anonym...

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Video-LLaMA: An Instruction-tuned Audio-Visual Language Model For Video Understanding. (arXiv:2306.02858v1 [cs.CL])
We present Video-LLaMA, a multi-modal framework that empowers Large Language Models (LLMs) with the capability of understanding both visual and auditory content in the video. Video-LLaMA bootstraps cross-modal training from the frozen pre-trained visual & audio encoders and the frozen LLMs. Unlike p...

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EffCRN: An Efficient Convolutional Recurrent Network For High-Performance Speech Enhancement
Fully convolutional recurrent neural networks (FCRNs) have shown state-of-the-art performance in single-channel speech enhancement. However, the number of parameters and the FLOPs/second of the original FCRN are restrictively high. A further important class of efficient networks is the CRUSE topolog...

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The Learning Prescription, A Neural Network Hearing Aid Core
The definition of a hearing aid core which is based on a prescription neural network (such as NAL-NL2) is defined here. This hearing aid core replaces a traditional compressor hearing aid core which mimics the said hearing aid prescription. Whilst the replacement of the compressors for a neural netw...

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Multiple Output Samples For Each Input In A Single-output Gaussian Process. (arXiv:2306.02719v1 [cs.CL])
The standard Gaussian Process (GP) only considers a single output sample per input in the training set. Datasets for subjective tasks, such as spoken language assessment, may be annotated with output labels from multiple human raters per input. This paper proposes to generalise the GP to allow for t...

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End-to-End Word-Level Pronunciation Assessment With MASK Pre-training. (arXiv:2306.02682v1 [cs.CL])
Pronunciation assessment is a major challenge in the computer-aided pronunciation training system, especially at the word (phoneme)-level. To obtain word (phoneme)-level scores, current methods usually rely on aligning components to obtain acoustic features of each word (phoneme), which limits the p...

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BeAts: Bengali Speech Acts Recognition Using Multimodal Attention Fusion. (arXiv:2306.02680v1 [cs.CL])
Spoken languages often utilise intonation, rhythm, intensity, and structure, to communicate intention, which can be interpreted differently depending on the rhythm of speech of their utterance. These speech acts provide the foundation of communication and are unique in expression to the language. Re...

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Rethinking The Visual Cues In Audio-visual Speaker Extraction
The Audio-Visual Speaker Extraction (AVSE) algorithm employs parallel video recording to leverage two visual cues, namely speaker identity and synchronization, to enhance performance compared to audio-only algorithms. However, the visual front-end in AVSE is often derived from a pre-trained model or...

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Controllable Lyrics-to-Melody Generation. (arXiv:2306.02613v1 [cs.SD])
Lyrics-to-melody generation is an interesting and challenging topic in AI music research field. Due to the difficulty of learning the correlations between lyrics and melody, previous methods suffer from low generation quality and lack of controllability. Controllability of generative models enables ...

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A Novel Interpretable And Generalizable Re-synchronization Model For Cued Speech Based On A Multi-Cuer Corpus. (arXiv:2306.02596v1 [eess.AS])
Cued Speech (CS) is a multi-modal visual coding system combining lip reading with several hand cues at the phonetic level to make the spoken language visible to the hearing impaired. Previous studies solved asynchronous problems between lip and hand movements by a cuerfootnote{The people who perform...

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Divided Spectro-temporal Attention For Sound Event Localization And Detection In Real Scenes For DCASE2023 Challenge. (arXiv:2306.02591v1 [eess.AS])
Localizing sounds and detecting events in different room environments is a difficult task, mainly due to the wide range of reflections and reverberations. When training neural network models with sounds recorded in only a few room environments, there is a tendency for the models to become overly spe...

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Cross-Lingual Transfer Learning For Phrase Break Prediction With Multilingual Language Model
Phrase break prediction is a crucial task for improving the prosody naturalness of a text-to-speech (TTS) system. However, most proposed phrase break prediction models are monolingual, trained exclusively on a large amount of labeled data. In this paper, we address this issue for low-resource langua...

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OTF: Optimal Transport Based Fusion Of Supervised And Self-Supervised Learning Models For Automatic Speech Recognition
Self-Supervised Learning (SSL) Automatic Speech Recognition (ASR) models have shown great promise over Supervised Learning (SL) ones in low-resource settings. However, the advantages of SSL are gradually weakened when the amount of labeled data increases in many industrial applications. To further i...

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Incorporating L2 Phonemes Using Articulatory Features For Robust Speech Recognition
The limited availability of non-native speech datasets presents a major challenge in automatic speech recognition (ASR) to narrow the performance gap between native and non-native speakers. To address this, the focus of this study is on the efficient incorporation of the L2 phonemes, which in this w...

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End-To-End Deep Learning-based Adaptation Control For Linear Acoustic Echo Cancellation. (arXiv:2306.02450v1 [eess.AS])
The attenuation of acoustic loudspeaker echoes remains to be one of the open challenges to achieve pleasant full-duplex hands free speech communication. In many modern signal enhancement interfaces, this problem is addressed by a linear acoustic echo canceler which subtracts a loudspeaker echo estim...

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SingNet: A Real-time Singing Voice Beat And Downbeat Tracking System. (arXiv:2306.02372v1 [eess.AS])
Singing voice beat and downbeat tracking posses several applications in automatic music production, analysis and manipulation. Among them, some require real-time processing, such as live performance processing and auto-accompaniment for singing inputs. This task is challenging owing to the non-trivi...

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Influence Of Lossy Speech Codecs On Hearing-aid, Binaural Sound Source Localisation Using DNNs. (arXiv:2306.02344v1 [eess.AS])
Hearing aids are typically equipped with multiple microphones to exploit spatial information for source localisation and speech enhancement. Especially for hearing aids, a good source localisation is important: it not only guides source separation methods but can also be used to enhance spatial cues...

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SpellMapper: A Non-autoregressive Neural Spellchecker For ASR Customization With Candidate Retrieval Based On N-gram Mappings
Contextual spelling correction models are an alternative to shallow fusion to improve automatic speech recognition (ASR) quality given user vocabulary. To deal with large user vocabularies, most of these models include candidate retrieval mechanisms, usually based on minimum edit distance between fr...

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End-to-End Joint Target And Non-Target Speakers ASR
This paper proposes a novel automatic speech recognition (ASR) system that can transcribe individual speaker's speech while identifying whether they are target or non-target speakers from multi-talker overlapped speech. Target-speaker ASR systems are a promising way to only transcribe a target speak...

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CoAIcoder: Examining The Effectiveness Of AI-assisted Collaborative Qualitative Analysis. (arXiv:2304.05560v2 [cs.HC] UPDATED)
While the domain of individual-level AI-assisted analysis has been extensively explored in previous studies, the field of AI-assisted collaborative qualitative analysis remains relatively unexplored. After identifying CQA practices and design opportunities through formative interviews, we introduce ...

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Understanding And Supporting Debugging Workflows In Multiverse Analysis
Multiverse analysis, a paradigm for statistical analysis that considers all combinations of reasonable analysis choices in parallel, promises to improve transparency and reproducibility. Although recent tools help analysts specify multiverse analyses, they remain difficult to use in practice. In thi...

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Fast Interactive Search With A Scale-Free Comparison Oracle. (arXiv:2306.01814v1 [cs.IR])
A comparison-based search algorithm lets a user find a target item $t$ in a database by answering queries of the form, ``Which of items $i$ and $j$ is closer to $t$?'' Instead of formulating an explicit query (such as one or several keywords), the user navigates towards the target via a sequence of ...

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Local Message Passing On Frustrated Systems. (arXiv:2306.01494v1 [cs.LG] CROSS LISTED)
Message passing on factor graphs is a powerful framework for probabilistic inference, which finds important applications in various scientific domains. The most wide-spread message passing scheme is the sum-product algorithm (SPA) which gives exact results on trees but often fails on graphs with man...

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Cooperative Sense And Avoid For UAVs Using Secondary Radar. (arXiv:2306.03046v1 [eess.SP])
A new Sense and Avoid (SAA) method for safe navigation of small-sized UAVs within an airspace is proposed in this paper. The proposed method relies upon cooperation between the UAV and the surrounding transponder-equipped aviation obstacles. To do so, the aviation obstacles share their altitude and ...

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Secrecy Of Opportunistic User Scheduling In RIS-Aided Systems: A Comparison With NOMA Scheduling
In this paper, we propose an opportunistic user scheduling scheme in a multi-user reconfigurable intelligent surface (RIS) aided wireless system to improve secrecy. We derive the secrecy outage probability (SOP) and its asymptotic expression in approximate closed form. The asymptotic analysis shows ...

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Integrated Sensing, Computation, And Communication For UAV-assisted Federated Edge Learning. (arXiv:2306.02990v1 [cs.IT])
Federated edge learning (FEEL) enables privacy-preserving model training through periodic communication between edge devices and the server. Unmanned Aerial Vehicle (UAV)-mounted edge devices are particularly advantageous for FEEL due to their flexibility and mobility in efficient data collection. I...

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Knowledge-Driven Semantic Communication Enabled By The Geometry Of Meaning. (arXiv:2306.02917v1 [eess.SP])
As our world grows increasingly connected and new technologies arise, global demands for data traffic continue to rise exponentially. Limited by the fundamental results of information theory, to meet these demands we are forced to either increase power or bandwidth usage. But what if there was a way...

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Catch Me If You Can: Deep Meta-RL For Search-and-Rescue Using LoRa UAV Networks. (arXiv:2306.02911v1 [cs.NI])
Long range (LoRa) wireless networks have been widely proposed as a efficient wireless access networks for the battery-constrained Internet of Things (IoT) devices. In many practical search-and-rescue (SAR) operations, one challenging problem is finding the location of devices carried by a lost perso...

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Selection Combining Over Log-Logistic Fading Channels With Applications To Underwater Optical Wireless Communications. (arXiv:2306.02853v1 [cs.IT])
We study the performance of a selection combining (SC) receiver operating over independent but non-identically distributed log-logistic ($mathcal{LL})$ fading channels. We first characterize the statistics of the output instantaneous signal-to-noise ratio (SNR) of the SC receiver. Based on the SNR s...

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On The Role Of ViT And CNN In Semantic Communications: Analysis And Prototype Validation. (arXiv:2306.02759v1 [eess.SP])
Semantic communications have shown promising advancements by optimizing source and channel coding jointly. However, the dynamics of these systems remain understudied, limiting research and performance gains. Inspired by the robustness of Vision Transformers (ViTs) in handling image nuisances, we pro...

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Learning-Based Rich Feedback HARQ For Energy-Efficient Short Packet Transmission. (arXiv:2306.02726v1 [cs.IT])
The trade-off between reliability, latency, and energy-efficiency is a central problem in communication systems. Advanced hybrid automated repeat request (HARQ) techniques can reduce the number of retransmissions required for reliable communication, but they have a significant computational cost. On...

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DAGrid: Directed Accumulator Grid. (arXiv:2306.02589v1 [cs.CV])
Recent research highlights that the Directed Accumulator (DA), through its parametrization of geometric priors into neural networks, has notably improved the performance of medical image recognition, particularly with small and imbalanced datasets. However, DA's potential in pixel-wise dense predict...

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Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, And Future Directions. (arXiv:2306.02444v1 [cs.NI])
Technology solutions must effectively balance economic growth, social equity, and environmental integrity to achieve a sustainable society. Notably, although the Internet of Things (IoT) paradigm constitutes a key sustainability enabler, critical issues such as the increasing maintenance operations,...

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Joint Activity Detection And Channel Estimation In Massive Machine-Type Communications With Low-Resolution ADC
In massive machine-type communications, data transmission is usually considered sporadic, and thus inherently has a sparse structure. This paper focuses on the joint activity detection (AD) and channel estimation (CE) problems in massive-connected communication systems with low-resolution analog-to-...

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Riemannian Low-Rank Model Compression For Federated Learning With Over-the-Air Aggregation. (arXiv:2306.02433v1 [eess.SP])
Low-rank model compression is a widely used technique for reducing the computational load when training machine learning models. However, existing methods often rely on relaxing the low-rank constraint of the model weights using a regularized nuclear norm penalty, which requires an appropriate hyper...

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MIMO Precoding Design With QoS And Per-Antenna Power Constraints
Precoding design for the downlink of multiuser multiple-input multiple-output (MU-MIMO) systems is a fundamental problem. In this paper, we aim to maximize the weighted sum rate (WSR) while considering both quality-of-service (QoS) constraints of each user and per-antenna power constraints (PAPCs) i...

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Movable Antennas For Wireless Communication: Opportunities And Challenges
Movable antenna (MA) technology is a recent development that fully exploits the wireless channel spatial variation in a confined region by enabling local movement of the antenna. Specifically, the positions of antennas at the transmitter and/or receiver can be dynamically changed to obtain better ch...

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LoRa Backscatter Communications: Temporal, Spectral, And Error Performance Analysis. (arXiv:2306.02323v1 [cs.IT])
LoRa backscatter (LB) communication systems can be considered as a potential candidate for ultra low power wide area networks (LPWAN) because of their low cost and low power consumption. In this paper, we comprehensively analyze LB modulation from various aspects, i.e., temporal, spectral, and error...

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SubspaceNet: Deep Learning-Aided Subspace Methods For DoA Estimation. (arXiv:2306.02271v1 [eess.SP])
Direction of arrival (DoA) estimation is a fundamental task in array processing. A popular family of DoA estimation algorithms are subspace methods, which operate by dividing the measurements into distinct signal and noise subspaces. Subspace methods, such as Multiple Signal Classification (MUSIC) a...

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DataAI-6G: A System Parameters Configurable Channel Dataset For AI-6G Research
With the acceleration of the commercialization of fifth generation (5G) mobile communication technology and the research for 6G communication systems, the communication system has the characteristics of high frequency, multi-band, high speed movement of users and large antenna array. These bring man...

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Fast And Interpretable Nonlocal Neural Networks For Image Denoising Via Group-Sparse Convolutional Dictionary Learning. (arXiv:2306.01950v1 [eess.IV])
Nonlocal self-similarity within natural images has become an increasingly popular prior in deep-learning models. Despite their successful image restoration performance, such models remain largely uninterpretable due to their black-box construction. Our previous studies have shown that interpretable ...

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Topological Comparison Of Some Dimension Reduction Methods Using Persistent Homology On EEG Data. (arXiv:2306.01895v1 [math.GT])
In this paper, we explore how to use topological tools to compare dimension reduction methods. We first make a brief overview of some of the methods often used dimension reduction such as Isometric Feature Mapping, Laplacian Eigenmaps, Fast Independent Component Analysis, Kernel Ridge Regression, t-...

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Atmospheric Influence On The Path Loss At High Frequencies For Deployment Of 5G Cellular Communication Networks. (arXiv:2306.01894v1 [eess.SP])
Over the past few decades, the development of cellular communication technology has spanned several generations in order to add sophisticated features in the updated versions. Moreover, different high-frequency bands are considered for advanced cellular generations. The presence of updated generatio...

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Minimizing Visible Edges In Polyhedra
We prove that, given a polyhedron $mathcal P$ in $mathbb{R}^3$, every point in $mathbb R^3$ that does not see any vertex of $mathcal P$ must see eight or more edges of $mathcal P$, and this bound is tight. More generally, this remains true if $mathcal P$ is any finite arrangement of internally disjo...

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Colorful Helly Theorem For Piercing Boxes With Multiple Points
Let $H_c=H_c(d,n)$ denote the smallest positive integer such that if we have a collection of families $mathcal{F}_{1}, dots, mathcal{F}_{H_{c}}$ of axis-parallel boxes in $mathbb{R}^{d}$ with the property that every colorful $H_{c}$-tuple from the above families can be pierced by $n$ points then the...

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Geometric Convergence Of Distributed Heavy-Ball Nash Equilibrium Algorithm Over Time-Varying Digraphs With Unconstrained Actions. (arXiv:2303.16385v2 [cs.GT] UPDATED)
This paper presents a new distributed algorithm that leverages heavy-ball momentum and a consensus-based gradient method to find a Nash equilibrium (NE) in a class of non-cooperative convex games with unconstrained action sets. In this approach, each agent in the game has access to its own smooth lo...

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Pairwise Ranking Losses Of Click-Through Rates Prediction For Welfare Maximization In Ad Auctions. (arXiv:2306.01799v1 [cs.GT])
We study the design of loss functions for click-through rates (CTR) to optimize (social) welfare in advertising auctions. Existing works either only focus on CTR predictions without consideration of business objectives (e.g., welfare) in auctions or assume that the distribution over the participants...

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Extragradient SVRG For Variational Inequalities: Error Bounds And Increasing Iterate Averaging
We study variance reduction methods for extragradient (EG) algorithms for a class of variational inequalities satisfying a classical error-bound condition. Previously, linear convergence was only known to hold under strong monotonicity. The error-bound condition is much weaker than strong monotonici...

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Class Anchor Margin Loss For Content-Based Image Retrieval. (arXiv:2306.00630v2 [cs.CV] UPDATED)
The performance of neural networks in content-based image retrieval (CBIR) is highly influenced by the chosen loss (objective) function. The majority of objective functions for neural models can be divided into metric learning and statistical learning. Metric learning approaches require a pair minin...

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Candidate Set Re-ranking For Composed Image Retrieval With Dual Multi-modal Encoder. (arXiv:2305.16304v2 [cs.CV] UPDATED)
Composed image retrieval aims to find an image that best matches a given multi-modal user query consisting of a reference image and text pair. Existing methods commonly pre-compute image embeddings over the entire corpus and compare these to a reference image embedding modified by the query text at ...

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AdaTT: Adaptive Task-to-Task Fusion Network For Multitask Learning In Recommendations. (arXiv:2304.04959v2 [cs.IR] UPDATED)
Multi-task learning (MTL) aims to enhance the performance and efficiency of machine learning models by simultaneously training them on multiple tasks. However, MTL research faces two challenges: 1) effectively modeling the relationships between tasks to enable knowledge sharing, and 2) jointly learn...

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LexMAE: Lexicon-Bottlenecked Pretraining For Large-Scale Retrieval. (arXiv:2208.14754v2 [cs.IR] UPDATED)
In large-scale retrieval, the lexicon-weighting paradigm, learning weighted sparse representations in vocabulary space, has shown promising results with high quality and low latency. Despite it deeply exploiting the lexicon-representing capability of pre-trained language models, a crucial gap remain...

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The Effect Of News Article Quality On Ad Consumption. (arXiv:2306.01781v1 [cs.IR])
Practical news feed platforms generate a hybrid list of news articles and advertising items (e.g., products, services, or information) and many platforms optimize the position of news articles and advertisements independently. However, they should be arranged with careful consideration of each other...

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Learning Joint 2D & 3D Diffusion Models For Complete Molecule Generation. (arXiv:2305.12347v2 [q-bio.BM] UPDATED)
Designing new molecules is essential for drug discovery and material science. Recently, deep generative models that aim to model molecule distribution have made promising progress in narrowing down the chemical research space and generating high-fidelity molecules. However, current generative models...

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Lingo3DMol: Generation Of A Pocket-based 3D Molecule Using A Language Model. (arXiv:2305.10133v2 [cs.LG] UPDATED)
Structure-based drug design powered by deep generative models have attracted increasing research interest in recent years. Language models have demonstrated a robust capacity for generating valid molecules in 2D structures, while methods based on geometric deep learning can directly produce molecule...

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Automatic Differentiation Is No Panacea For Phylogenetic Gradient Computation. (arXiv:2211.02168v2 [q-bio.PE] UPDATED)
Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning. These calculations are readily available for arbitrary models via automatic differentiation implemented in general-purpose machine-learning libraries ...

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No Sensitivity To Functional Forms In The Rosenzweig-MacArthur Model With Strong Environmental Stochasticity. (arXiv:2209.01185v3 [q-bio.PE] UPDATED)
The classic Rosenzweig-MacArthur predator-prey model has been shown to exhibit, like other coupled nonlinear ordinary differential equations (ODEs) from ecology, worrying sensitivity to model structure. This sensitivity manifests as markedly different community dynamics arising from saturating funct...

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Microscopy Image Reconstruction With Physics-informed Denoising Diffusion Probabilistic Model. (arXiv:2306.02929v1 [q-bio.QM])
Light microscopy is a widespread and inexpensive imaging technique facilitating biomedical discovery and diagnostics. However, light diffraction barrier and imperfections in optics limit the level of detail of the acquired images. The details lost can be reconstructed among others by deep learning m...

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Branching Model With State Dependent Offspring Distribution For Chlamydia Spread
Chlamydiae are bacteria with an interesting unusual developmental cycle. A single bacterium in its infectious form (elementary body, EB) enters the host cell, where it converts into its dividing form (reticulate body, RB), and divides by binary fission. Since only the EB form is infectious, before t...

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Automated Importance Sampling Via Optimal Control For Stochastic Reaction Networks: A Markovian Projection-based Approach. (arXiv:2306.02660v1 [math.NA])
We propose a novel alternative approach to our previous work (Ben Hammouda et al., 2023) to improve the efficiency of Monte Carlo (MC) estimators for rare event probabilities for stochastic reaction networks (SRNs). In the same spirit of (Ben Hammouda et al., 2023), an efficient path-dependent measu...

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R-Mixup: Riemannian Mixup For Biological Networks. (arXiv:2306.02532v1 [cs.LG])
Biological networks are commonly used in biomedical and healthcare domains to effectively model the structure of complex biological systems with interactions linking biological entities. However, due to their characteristics of high dimensionality and low sample size, directly applying deep learning...

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Intermittent Migration Can Induce Pulses Of Speciation In A Two-island System. (arXiv:2306.02510v1 [q-bio.PE])
Geographic barriers prevent migration between populations, thereby facilitating speciation through allopatry. However, these barriers can exhibit dynamic behavior in nature, promoting cycles of expansion and contraction of populations. Such oscillations cause temporal variations in migration that do...

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From Multiscale Biophysics To Digital Twins Of Tissues And Organs: Future Opportunities For In Silico Pharmacology. (arXiv:2306.02369v1 [q-bio.QM])
With many advancements in in silico biology in recent years, the paramount challenge is to translate the accumulated knowledge into exciting industry partnerships and clinical applications. Achieving models that characterize the link of molecular interactions to the activity and structure of a whole...

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Mitigating Molecular Aggregation In Drug Discovery With Predictive Insights From Explainable AI. (arXiv:2306.02206v1 [q-bio.BM])
As the importance of high-throughput screening (HTS) continues to grow due to its value in early stage drug discovery and data generation for training machine learning models, there is a growing need for robust methods for pre-screening compounds to identify and prevent false-positive hits. Small, c...

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Brainlife.io: A Decentralized And Open Source Cloud Platform To Support Neuroscience Research. (arXiv:2306.02183v1 [cs.DC])
Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR data analysis to portions of the worldwide resear...

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Microbiome Abundance Patterns As Attractors And The Implications For The Inference Of Microbial Interaction Networks. (arXiv:2306.02100v1 [q-bio.PE])
Inferring microbial interaction networks from abundance patterns is an important approach to advance our understanding of microbial communities in general and the human microbiome in particular. Here we suggest discriminating two levels of information contained in microbial abundance data: (1) the q...

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Ebola Transmission Dynamics: Will Future Ebola Outbreaks Become Cyclic?. (arXiv:2306.02075v1 [q-bio.PE])
The Ebola Virus Disease (EVD) can persist in some body fluids after clinical recovery. In Guinea and the Democratic Republic of the Congo, there are well-documented cases of EVD reemergence that were associated with previous outbreaks. In many cases, male EVD survivors were associated with the re-in...

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CellProfiler Plugins -- An Easy Image Analysis Platform Integration For Containers And Python Tools
CellProfiler is a widely used software for creating reproducible, reusable image analysis workflows without needing to code. In addition to the >90 modules that make up the main CellProfiler program, CellProfiler has a plugins system that allows for creation of new modules which integrate with other...

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Enhancing The Protein Tertiary Structure Prediction By Multiple Sequence Alignment Generation. (arXiv:2306.01824v1 [q-bio.QM])
The field of protein folding research has been greatly advanced by deep learning methods, with AlphaFold2 (AF2) demonstrating exceptional performance and atomic-level precision. As co-evolution is integral to protein structure prediction, AF2's accuracy is significantly influenced by the depth of mu...

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DiffPack: A Torsional Diffusion Model For Autoregressive Protein Side-Chain Packing. (arXiv:2306.01794v1 [q-bio.QM])
Proteins play a critical role in carrying out biological functions, and their 3D structures are essential in determining their functions. Accurately predicting the conformation of protein side-chains given their backbones is important for applications in protein structure prediction, design and prot...

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Understanding Biofilm-Phage Interactions In Cystic Fibrosis Patients Using Mathematical Frameworks. (arXiv:2306.01791v1 [q-bio.QM])
When planktonic bacteria adhere together to a surface, they begin to form biofilms, or communities of bacteria. Biofilm formation in a host can be extremely problematic if left untreated, especially since antibiotics can be ineffective in treating the bacteria. Certain lung diseases such as cystic f...

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Small-Coupling Dynamic Cavity: a Bayesian mean-field framework for epidemic inference. (arXiv:2306.03829v1 [cond-mat.dis-nn])

- Academic, BIO

Canada wildfire smoke: millions in the US under air quality alerts – live

- Environment, Lifestyle

Active learning of the thermodynamics-dynamics tradeoff in protein condensates

- Academic, BIO

Reparametrization and the Semiparametric Bernstein-von-Mises Theorem. (arXiv:2306.03816v1 [math.ST])

- Academic, ECON

MOHAMAD EXPRESSES CONCERN OVER TREND OF SPREADING STATEMENTS THAT THREATEN UNITY

- Regional

Silver Fern defender Elle Temu moving to Australia, unavailable for 2024 ANZ Premiership

- General, Opinion

NVIDIA Corporation (NVDA) Rosenblatt's Annual Technology Summit - The age of AI scaling (Part I) Conference (Transcript)

- Business, Finance

Travellers in descend on Appleby for Europe's biggest horse fair

- General

Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. (arXiv:2306.03838v1 [cs.LG])

- Academic, PHYSICS

'Get the hell out of my face': Reporter destroys obnoxious fan on live TV

- Sports, Regional

Australia in ‘retail recession’ as inflation and rate hikes hit spending, says report

- National

2 killed in head-on crash west of Carleton Place

- Regional

Nazi symbol to be banned from public display

- Regional

Graphics show how smoke from Canadian wildfires is turning US skies hazy – and hazardous

- General

Umno must realise it's no longer a dominant party, says Zahid

- General

Afternoon Briefing: Jockeying for the Bears’ next home continues

- Entertainment

Novel crimes: which is worst – folded corners, cracked spines, marginalia or cheese bookmarks?

- Regional

Maryland suspects face manslaughter charges after crashing in construction zone, killing 6 workers

- Regional

Labour donor Dale Vince: ‘I do want to influence policy but not by buying access’

- Environment, Lifestyle

Ottawa looking at options for a national disaster response agency as wildfires rage

- Regional, Thunderbay

Deadly shooting at Va. graduation ceremony

- General

Ex-WWE star Wesley Blake wishes late wife Sara Lee a 'happy heavenly birthday'

- Entertainment