Tootfinder

für frankophile #bach-fans: bei france musique gibt es die radiosendungs- und #podcast-reihe "Le Bach du dimanche": htt…

A Pan-STARRS1 Search for Planet Nine: #PlanetNine with the characteristics of that predicted in Brown & Batygin (2021) to a 50% completion depth of V=21.5. This survey, along with previous analyses of the Zwicky Transient Facility (ZTF) and Dark EnergySurvey (DES) data, rules out 78% of the Brown & Batygin parameter space."

Text Sentiment Analysis and Classification Based on Bidirectional Gated Recurrent Units (GRUs) Model
Wei Xu, Jianlong Chen, Zhicheng Ding, Jinyin Wang
https://arxiv.org/abs/2404.17123

Text Sentiment Analysis and Classification Based on Bidirectional Gated Recurrent Units (GRUs) Model
This paper explores the importance of text sentiment analysis and classification in the field of natural language processing, and proposes a new approach to sentiment analysis and classification based on the bidirectional gated recurrent units (GRUs) model. The study firstly analyses the word cloud model of the text with six sentiment labels, and then carries out data preprocessing, including the steps of removing special symbols, punctuation marks, numbers, stop words and non-alphabetic parts.…

A Pan-STARRS1 Search for Planet Nine: #PlanetNine with the characteristics of that predicted in Brown & Batygin (2021) to a 50% completion depth of V=21.5. This survey, along with previous analyses of the Zwicky Transient Facility (ZTF) and Dark EnergySurvey (DES) data, rules out 78% of the Brown & Batygin parameter space."

This https://arxiv.org/abs/2404.14563 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Exploring Algorithmic Explainability: Generating Explainable AI Insights for Personalized Clinical Decision Support Focused on Cannabis Intoxication in Young Adults
This study explores the possibility of facilitating algorithmic decision-making by combining interpretable artificial intelligence (XAI) techniques with sensor data, with the aim of providing researchers and clinicians with personalized analyses of cannabis intoxication behavior. SHAP analyzes the importance and quantifies the impact of specific factors such as environmental noise or heart rate, enabling clinicians to pinpoint influential behaviors and environmental conditions. SkopeRules simpl…

ConstraintFlow: A DSL for Specification and Verification of Neural Network Analyses
Avaljot Singh, Yasmin Sarita, Charith Mendis, Gagandeep Singh
https://arxiv.org/abs/2403.18729 …

ConstraintFlow: A DSL for Specification and Verification of Neural Network Analyses
The uninterpretability of DNNs hinders their deployment to safety-critical applications. Recent works have shown that Abstract-Interpretation-based formal certification techniques provide promising avenues for building trust in DNNs to some extent. The intricate mathematical background of Abstract Interpretation poses two challenges: (i) easily designing the algorithms that capture the intricate DNN behavior by balancing cost vs. precision tradeoff, and (ii) maintaining the over-approximation-b…

This https://arxiv.org/abs/2404.04013 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Tidal heating as a discriminator for horizons in equatorial eccentric extreme mass ratio inspirals
Tidal heating in a binary black hole system is driven by the absorption of energy and angular momentum by the black hole's horizon. Previous works have shown that this phenomenon becomes particularly significant during the late stages of an extreme mass ratio inspiral (EMRI) into a rapidly spinning massive black hole, a key focus for future low-frequency gravitational-wave observations by (for instance) the LISA mission. Past analyses have largely focused on quasi-circular inspiral geometry, wi…

This https://arxiv.org/abs/2403.13989 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

FastFlip: Compositional Error Injection Analysis
Instruction-level error injection analyses aim to find instructions where errors often lead to unacceptable outcomes like Silent Data Corruptions (SDCs). These analyses require significant time, which is especially problematic if developers wish to regularly analyze software that evolves over time. We present FastFlip, a combination of empirical error injection and symbolic SDC propagation analyses that enables fast, compositional error injection analysis of evolving programs. FastFlip calcul…

Quantifying Lifetime Productivity Changes: A Longitudinal Study of 325,000 Late-Career Scientists
Marek Kwiek, Lukasz Szymula
https://arxiv.org/abs/2404.16835 https://arxiv.org/pdf/2404.16835
arXiv:2404.16835v1 Announce Type: new
Abstract: This study focuses on persistence in research productivity over the course of an individual's entire scientific careers. We track 'late-career' scientists (N=324,463) in 16 STEMM disciplines (science, technology, engineering, mathematics, and medicine) from 38 OECD countries for up to five decades. We examine the details of their mobility patterns between the top, middle, and bottom productivity classes. Methodologically, we turn a large-scale publication and citation bibliometric dataset into a comprehensive, longitudinal data source for research on careers in science. The global science system emerges as highly immobile: 60% of global top performers continue their careers as top performers and half of global bottom performers as bottom performers. Jumpers-Up and Droppers-Down are extremely rare in science. Our regression analyses show that productivity is highly path dependent: for all disciplines examined, there is a single most important predictor of being a top performer: being a top performer at an earlier career stage.

This https://arxiv.org/abs/2311.17732 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Supernovae in 2023 (review): possible breakthroughs by late observations
I present a review of how late observations of supernovae, of the nebular phase, and much later of supernova remnants (SNRs), and their analysis in 2023 made progress towards possible breakthroughs in supporting the jittering jets explosion mechanism (JJEM) for core-collapse supernovae (CCSNe) and in introducing the group of lonely white dwarf (WD) scenarios for type Ia supernovae (SNe Ia). The new analyses of CCSN remnants (CCSNRs) reveal point-symmetric morphologies in a way unnoticed before …

V2C-Long: Longitudinal Cortex Reconstruction with Spatiotemporal Correspondence
Fabian Bongratz, Jan Fecht, Anne-Marie Rickmann, Christian Wachinger
https://arxiv.org/abs/2402.17438

V2C-Long: Longitudinal Cortex Reconstruction with Spatiotemporal Correspondence
Reconstructing the cortex from longitudinal MRI is indispensable for analyzing morphological changes in the human brain. Despite the recent disruption of cortical surface reconstruction with deep learning, challenges arising from longitudinal data are still persistent. Especially the lack of strong spatiotemporal point correspondence hinders downstream analyses due to the introduced noise. To address this issue, we present V2C-Long, the first dedicated deep learning-based cortex reconstruction …

This https://arxiv.org/abs/2311.17149 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Monojets reveal overlapping excesses for light compressed higgsinos
The ATLAS and CMS collaborations have recently presented results of searches for compressed electroweakinos in final states including soft leptons. These searches are sensitive to mass splittings ranging from quite small values of about 5 GeV to O(10) GeV, which are endemic to scenarios with wino-like and higgsino-like lightest supersymmetric particles (LSPs). While all experimental results exhibit apparently compatible mild excesses, these soft-lepton analyses, taken together with disappearing…

On the Joint Effect of Culture and Discussion Topics on X (Twitter) Signed Ego Networks
Jack Tacchi, Chiara Boldrini, Andrea Passarella, Marco Conti
https://arxiv.org/abs/2402.18235

On the Joint Effect of Culture and Discussion Topics on X (Twitter) Signed Ego Networks
Humans are known to structure social relationships according to certain patterns, such as the Ego Network Model (ENM). These patterns result from our innate cognitive limits and can therefore be observed in the vast majority of large human social groups. Until recently, the main focus of research was the structural characteristics of this model. The main aim of this paper is to complement previous findings with systematic and data-driven analyses on the positive and negative sentiments of socia…

This https://arxiv.org/abs/2301.13701 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

On the Stability of General Bayesian Inference
We study the stability of posterior predictive inferences to the specification of the likelihood model and perturbations of the data generating process. In modern big data analyses, useful broad structural judgements may be elicited from the decision-maker but a level of interpolation is required to arrive at a likelihood model. As a result, an often computationally convenient canonical form is used in place of the decision-maker's true beliefs. Equally, in practice, observational datasets ofte…

This https://arxiv.org/abs/2211.13512 has been replaced.
link: https://scholar.google.com/scholar?q=a

The basics of primordial black hole formation and abundance estimation
This paper is a biased review of primordial black hole (PBH) formation and abundance estimation. We first review the three-zone model for PBH formation to help an intuitive understanding of the PBH formation process. Then, for more accurate analyses, we introduce necessary tools such as cosmological long-wavelength solutions, the definition of the mass and compaction function in a spherically symmetric spacetime and peak theory. Combining all these tools, we calculate the PBH mass spectrum for …

Deep Learning-based Kinetic Analysis in Paper-based Analytical Cartridges Integrated with Field-effect Transistors
Hyun-June Jang, Hyou-Arm Joung, Artem Goncharov, Anastasia Gant Kanegusuku, Clarence W. Chan, Kiang-Teck Jerry Yeo, Wen Zhuang, Aydogan Ozcan, Junhong Chen
https://arxiv.org/abs/2402.17209

Deep Learning-based Kinetic Analysis in Paper-based Analytical Cartridges Integrated with Field-effect Transistors
This study explores the fusion of a field-effect transistor (FET), a paper-based analytical cartridge, and the computational power of deep learning (DL) for quantitative biosensing via kinetic analyses. The FET sensors address the low sensitivity challenge observed in paper analytical devices, enabling electrical measurements with kinetic data. The paper-based cartridge eliminates the need for surface chemistry required in FET sensors, ensuring economical operation (cost < $0.15/test). The DL a…

The death of Vulcan: NEID reveals the planet candidate orbiting HD 26965 is stellar activity
Abigail Burrows, Samuel Halverson, Jared C. Siegel, Christian Gilbertson, Jacob Luhn, Jennifer Burt, Chad F. Bender, Arpita Roy, Ryan C. Terrien, Selma Vangstein, Suvrath Mahadevan, Jason T. Wright, Paul Robertson, Eric B. Ford, Gu{\dh}mundur Stef\'ansson, Joe P. Ninan, Cullen H. Blake, Michael W. McElwain, Christian Schwab, Jinglin Zhao

The death of Vulcan: NEID reveals the planet candidate orbiting HD 26965 is stellar activity
We revisit the long-studied radial velocity (RV) target HD26965 using recent observations from the NASA-NSF 'NEID' precision Doppler facility. Leveraging a suite of classical activity indicators, combined with line-by-line RV analyses, we demonstrate that the claimed 45-day signal previously identified as a planet candidate is most likely an activity-induced signal. Correlating the bulk (spectrally-averaged) RV with canonical line activity indicators confirms a multi-day 'lag' between the obser…

This is really good. The devil is always in the details. https://fediscience.org/@UlrikeHahn/111991242698794397

Bounds on the Index of an Umbilic Point
John Guckenheimaer
https://arxiv.org/abs/2402.17060 https://arxiv.org/pdf/2402.17060

Bounds on the Index of an Umbilic Point
Umbilics are points of a surface embedded in three space where normal curvatures are independent of direction. The (in)famous Carathéodory Conjecture states that a compact simply connected embedded surface has at least two umbilic points. A counterexample to this conjecture would be a surface whose principal foliation has index two at a single umbilic. All (purported) proofs of the Carathéodory Conjecture are based on analyses of the index of an umbilic, concluding that it is at most one. Thi…

Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy
Muzi Chen, Yuhang Wang, Boyao Wu, Difang Huang
https://arxiv.org/abs/2403.19439

Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy
The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion. Based on daily stock returns in the Shanghai Stock Exchange (SSE) A-shares, this paper divides the period between 2005 and 2018 into eight bull and bear market stages to investigate interactive patterns in the Chinese financial market. We employ the LASSO method to construct the stock network and further use the Map Equation method to analyze the evolution of modu…

Double, double, toil, and trouble: The tails, bubbles, and knots of the local compact obscured nucleus galaxy NGC4418
C. F. Wethers, S. Aalto, G. C. Privon, F. Stanley, J. Gallagher, M. Gorski, S. K\"onig, K. Onishi, M. Sato, C. Yang, R. Beswick, L. Barcos-Munoz F. Combes, T. Diaz-Santos, A. S. Evans, I. Garcia-Bernete, C. Henkel, M. Imanishi, S. Mart\'in, S. Muller, Y. Nishimura, C. Ricci, D. Rigopoulou, S. Viti

Double, double, toil, and trouble: The tails, bubbles, and knots of the local compact obscured nucleus galaxy NGC4418
Compact obscured nuclei (CONs) are an extremely obscured (N$_{H2}$ >10$^{25}$ cm$^{-2}$) class of galaxy nuclei thought to exist in 20-40 per cent of nearby (ultra-)luminous infrared galaxies. While they have been proposed to represent a key phase of the active galactic nucleus (AGN) feedback cycle, the nature of these CONs - what powers them, their dynamics, and their impact on the host galaxy - remains unknown. This work analyses the large-scale optical properties of the local CON, NGC4418 (z…

A Public and Reproducible Assessment of the Topics API on Real Data
Yohan Beugin, Patrick McDaniel
https://arxiv.org/abs/2403.19577 https://

A Public and Reproducible Assessment of the Topics API on Real Data
The Topics API for the web is Google's privacy-enhancing alternative to replace third-party cookies. Results of prior work have led to an ongoing discussion between Google and research communities about the capability of Topics to trade off both utility and privacy. The central point of contention is largely around the realism of the datasets used in these analyses and their reproducibility; researchers using data collected on a small sample of users or generating synthetic datasets, while Goog…

ConstraintFlow: A DSL for Specification and Verification of Neural Network Analyses
Avaljot Singh, Yasmin Sarita, Charith Mendis, Gagandeep Singh
https://arxiv.org/abs/2403.18729 …

ConstraintFlow: A DSL for Specification and Verification of Neural Network Analyses
The uninterpretability of DNNs hinders their deployment to safety-critical applications. Recent works have shown that Abstract-Interpretation-based formal certification techniques provide promising avenues for building trust in DNNs to some extent. The intricate mathematical background of Abstract Interpretation poses two challenges: (i) easily designing the algorithms that capture the intricate DNN behavior by balancing cost vs. precision tradeoff, and (ii) maintaining the over-approximation-b…

AI & beer 😃 (no LLMs involved)
#ai #beer

Predicting and improving complex beer flavor through machine learning - Nature Communications
Perception and appreciation of food flavour depends on many factors, posing a challenge for effective prediction. Here, the authors combine extensive chemical and sensory analyses of 250 commercial Belgian beers to train machine learning models that enable flavour and consumer appreciation prediction.

What happens when artificial intelligence analyzes human thoughts about AI and copyright?
https://flipboard.com/@thekenyeung/the-a…

Can AI analyses about AI content reveal anything about AI and copyright?
What happens when artificial intelligence analyzes human thoughts about AI and copyright? As tech giants and startups alike move forward with AI …

Handling Open Research Data within the Max Planck Society -- Looking Closer at the Year 2020
Martin Boosen, Michael Franke, Yves Vincent Grossmann, Sy Dat Ho, Larissa Leiminger, Jan Matthiesen
https://arxiv.org/abs/2402.18182

Handling Open Research Data within the Max Planck Society -- Looking Closer at the Year 2020
This paper analyses the practice of publishing research data within the Max Planck Society in the year 2020. The central finding of the study is that up to 40\% of the empirical text publications had research data available. The aggregation of the available data is predominantly analysed. There are differences between the sections of the Max Planck Society but they are not as great as one might expect. In the case of the journals, it is also apparent that a data policy can increase the availabi…

This https://arxiv.org/abs/2301.13701 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

On the Stability of General Bayesian Inference
We study the stability of posterior predictive inferences to the specification of the likelihood model and perturbations of the data generating process. In modern big data analyses, useful broad structural judgements may be elicited from the decision-maker but a level of interpolation is required to arrive at a likelihood model. As a result, an often computationally convenient canonical form is used in place of the decision-maker's true beliefs. Equally, in practice, observational datasets ofte…

Impact of Systematic Redshift Errors on the Cross-correlation of the Lyman-$\alpha$ Forest with Quasars at Small Scales Using DESI Early Data
Abby Bault, David Kirkby, Julien Guy, Allyson Brodzeller, J. Aguilar, S. Ahlen, S. Bailey, D. Brooks, L. Cabayol-Garcia, J. Chaves-Montero, T. Claybaugh, A. Cuceu, K. Dawson, R. de la Cruz, A. de la Macorra, Arjun Dey, P. Doel, S. Filbert, A. Font-Ribera, J. E. Forero-Romero, E. Gazta\~naga, S. Gontcho A Gontcho, C. Gordon, H. K. Herrera-Alcantar…

Impact of Systematic Redshift Errors on the Cross-correlation of the Lyman-$α$ Forest with Quasars at Small Scales Using DESI Early Data
The Dark Energy Spectroscopic Instrument (DESI) will measure millions of quasar spectra by the end of its 5 year survey. Quasar redshift errors impact the shape of the Lyman-$α$ forest correlation functions, which can affect cosmological analyses and therefore cosmological interpretations. Using data from the DESI Early Data Release and the first two months of the main survey, we measure the systematic redshift error from an offset in the cross-correlation of the Lyman-$α$ forest with quasars…

Season combinatorial intervention predictions with Salt & Peper
Thomas Gaudelet, Alice Del Vecchio, Eli M Carrami, Juliana Cudini, Chantriolnt-Andreas Kapourani, Caroline Uhler, Lindsay Edwards
https://arxiv.org/abs/2404.16907

Season combinatorial intervention predictions with Salt & Peper
Interventions play a pivotal role in the study of complex biological systems. In drug discovery, genetic interventions (such as CRISPR base editing) have become central to both identifying potential therapeutic targets and understanding a drug's mechanism of action. With the advancement of CRISPR and the proliferation of genome-scale analyses such as transcriptomics, a new challenge is to navigate the vast combinatorial space of concurrent genetic interventions. Addressing this, our work concen…

End-to-End Analysis Automation over Distributed Resources with Luigi Analysis Workflows
Marcel Rieger
https://arxiv.org/abs/2402.17949 https://

End-to-End Analysis Automation over Distributed Resources with Luigi Analysis Workflows
In particle physics, workflow management systems are primarily used as tailored solutions in dedicated areas such as Monte Carlo production. However, physicists performing data analyses are usually required to steer their individual, complex workflows manually, frequently involving job submission in several stages and interaction with distributed storage systems by hand. This process is not only time-consuming and error-prone, but also leads to undocumented relations between particular workload…

Quantitative Tools for Time Series Analysis in Natural Language Processing: A Practitioners Guide
W. Benedikt Schmal
https://arxiv.org/abs/2404.18499 https…

Quantitative Tools for Time Series Analysis in Natural Language Processing: A Practitioners Guide
Natural language processing tools have become frequently used in social sciences such as economics, political science, and sociology. Many publications apply topic modeling to elicit latent topics in text corpora and their development over time. Here, most publications rely on visual inspections and draw inference on changes, structural breaks, and developments over time. We suggest using univariate time series econometrics to introduce more quantitative rigor that can strengthen the analyses. …

This https://arxiv.org/abs/2404.13570 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

ALMA 2D Super-resolution Imaging of Taurus-Auriga Protoplanetary Disks: Probing Statistical Properties of Disk Substructures
In the past decade, ALMA observations of protoplanetary disks revealed various substructures including gaps and rings. Their origin may be probed through statistical studies on the physical properties of the substructures. We present the analyses of archival ALMA Band 6 continuum data of 43 disks (39 Class II and 4 Herbig Ae) in the Taurus-Auriga region. We employ a novel 2D super-resolution imaging technique based on sparse modeling to obtain images with high fidelity and spatial resolution. A…

Strong-ARM Dynamic Latch Comparators: Design and Analyses on CAD Platform
Kasi Bandla, Dipankar Pal
https://arxiv.org/abs/2402.14519 https://

Strong-ARM Dynamic Latch Comparators: Design and Analyses on CAD Platform
Strong-ARM Dynamic Latch Comparators are widely used in high-speed analog-to-digital converters (ADCs), sense amplifiers in memory, RFID applications, and data receivers. This paper presents different methods to improve the performance of Strong-Arm latch-based comparators. The comparator's significant features such as power dissipation, propagation delay, offset voltage, clock feedthrough, area, and kickback noises are discussed and compared with state-of-the-art candidate topologies. Simulati…

Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy
Muzi Chen, Yuhang Wang, Boyao Wu, Difang Huang
https://arxiv.org/abs/2403.19439

Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy
The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion. Based on daily stock returns in the Shanghai Stock Exchange (SSE) A-shares, this paper divides the period between 2005 and 2018 into eight bull and bear market stages to investigate interactive patterns in the Chinese financial market. We employ the LASSO method to construct the stock network and further use the Map Equation method to analyze the evolution of modu…

#Jepsen test on #RavenDB 6.0.2
https://jepsen.io/analyses/ravendb-6.0.2

This is not news to some folks.
Bias hiding in plain sight: Decades of analyses suggest US media skews anti-#Palestinian | Salon.com
https://www.

Bias hiding in plain sight: Decades of analyses suggest US media skews anti-Palestinian
Anti-Palestinian bias in the U.S. and other countries’ media is often subtle, albeit in plain view.

"...we show that extreme dimension reduction, from hundreds or thousands of dimensions to 2, inevitably induces significant distortion of high-dimensional dataset. "
I was tinkering with t-SNE, UMAP, PCA, and MDS — I noticed this distortion for the first two methods.
https://

This https://arxiv.org/abs/2402.13768 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMS_…

Democratizing Uncertainty Quantification
Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulation codes. It breaks down the technical complexity of advanced UQ applications and enables separation of concerns between experts. UM-Bridg…

Spatial confounding under infill asymptotics
David Bolin, Jonas Wallin
https://arxiv.org/abs/2403.18961 https://arxiv.org/pdf/2403.18…

Spatial confounding under infill asymptotics
The estimation of regression parameters in spatially referenced data plays a crucial role across various scientific domains. A common approach involves employing an additive regression model to capture the relationship between observations and covariates, accounting for spatial variability not explained by the covariates through a Gaussian random field. While theoretical analyses of such models have predominantly focused on prediction and covariance parameter inference, recent attention has shi…

Validating Prior-informed Fisher-matrix Analyses against GWTC Data
Ulyana Dupletsa, Jan Harms, Ken K. Y. Ng, Jacopo Tissino, Filippo Santoliquido, Andrea Cozzumbo
https://arxiv.org/abs/2404.16103

Validating Prior-informed Fisher-matrix Analyses against GWTC Data
Next-generation gravitational-wave detectors, such as the Einstein Telescope (ET), are expected to observe a few 100,000 signals each year. This will require efficient analysis tools and computational resources well beyond the needs of current detectors. Such resources are not presently available to the science community. Therefore, to investigate ET observational capabilities and science cases, Fisher-matrix methods are used to predict how precisely parameters like mass, spin, source distance …

Hybrid Warfare Analytical Group/UCMC. Episode 4, Cinematic Propaganda The Hybrid Warfare Analytical Group’s (UCMC) analysts convene to delve into the realms of Russian disinformation, propaganda, and Source : https://uacrisis.org/en/hybrid-warfare

"by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions ... inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action... a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions."
How close is

This https://arxiv.org/abs/2403.16251 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Spectroscopic approaches for studies of site-specific DNA base and backbone "breathing" using exciton-coupled dimer-labeled DNA
DNA regulation and repair processes require direct interactions between proteins and DNA at specific sites. Local fluctuations of the sugar-phosphate backbones and bases of DNA (a form of DNA "breathing") play a central role in such processes. Here we review the development and application of novel spectroscopic methods and analyses - both at the ensemble and single-molecule levels - to study structural and dynamic properties of exciton-coupled cyanine and fluorescent nucleobase analogue dimer-…

This https://arxiv.org/abs/2402.06988 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Three Subtyping Algorithms for Binary Session Types and their Complexity Analyses (full version)
Session types are a type discipline for describing and specifying communication behaviours of concurrent processes. Session subtyping, firstly introduced by Gay and Hole, is widely used for enlarging typability of session programs. This paper gives the complexity analysis of three algorithms for subtyping of synchronous binary session types. First, we analyse the complexity of the algorithm from the original paper, which is based on an inductive tree search. We then introduce its optimised vers…

Fossil Signatures of Main-sequence Convective Core Overshoot Estimated through Asteroseismic Analyses
Christopher J. Lindsay, J. M. Joel Ong, Sarbani Basu
https://arxiv.org/abs/2402.12461

Fossil Signatures of Main-sequence Convective Core Overshoot Estimated through Asteroseismic Analyses
Some physical processes that occur during a star's main-sequence evolution also affect its post main-sequence evolution. It is well known that stars with masses above approximately 1.1 $M_{\odot}$ have well-mixed convective cores on the main sequence, however, the structure of the star in the neighborhood of the convective core regions is currently underconstrained. We use asteroseismology to study the properties of the stellar core, in particular, convective boundary mixing through convective …

Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
Michael Lingzhi Li, Kosuke Imai
https://arxiv.org/abs/2404.17019

Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today's scientists across disciplines. In this paper, we demonstrate that Neyman's methodology can also be used to experimentally evaluate the efficacy of individualized treatment rules (ITRs), which are derived by modern causal machine learning algorithm…

This https://arxiv.org/abs/2211.07551 has been replaced.
link: https://scholar.google.com/scholar?q=a

Review of the online analyses of multi-messenger alerts and electromagnetic transient events with the ANTARES neutrino telescope
By constantly monitoring at least one complete hemisphere of the sky, neutrino telescopes are well designed to detect neutrinos emitted by transient astrophysical events. Real-time searches with the ANTARES telescope have been performed to look for neutrino candidates coincident with gamma-ray bursts detected by the Swift and Fermi satellites, highenergy neutrino events registered by IceCube, transient events from blazars monitored by HAWC, photon-neutrino coincidences by AMON notices and gravi…

This https://arxiv.org/abs/2402.06142 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Developing a Theoretical Model for the Resummation of Infrared Effects in the Post-Reconstruction Power Spectrum (youtu.be/u1-xx3_4xCg)
Since galaxy distribution reconstruction effectively reduces non-Gaussian terms in the power spectrum covariance matrix, it has attracted interest not only for Baryon Acoustic Oscillation (BAO) signals but also for various cosmological signal analyses. To this end, this paper presents a novel theoretical model that addresses infrared (IR) effects in the post-reconstruction galaxy power spectrum, including 1-loop corrections. In particular, we discuss the importance of incorporating non-perturba…

How open are hybrid journals included in transformative agreements?
Najko Jahn
https://arxiv.org/abs/2402.18255 https://arxiv.org/pdf…

How open are hybrid journals included in transformative agreements?
The ongoing controversy surrounding transformative agreements, which aim to transition journal publishing to full open access, highlight the need for large-scale studies assessing the uptake of open access in hybrid journals. This includes evaluating the extent to which transformative agreements enabled open access. By combining publicly available data from various sources, including cOAlition S Journal Checker, Crossref, and OpenAlex, this study presents a novel approach that analyses over 700…

This https://arxiv.org/abs/2301.01530 has been replaced.
link: https://scholar.google.com/scholar?q=a

Nonlinear conjugate gradient methods: worst-case convergence rates via computer-assisted analyses
We propose a computer-assisted approach to the analysis of the worst-case convergence of nonlinear conjugate gradient methods (NCGMs). Those methods are known for their generally good empirical performances for large-scale optimization, while having relatively incomplete analyses. Using our computer-assisted approach, we establish novel complexity bounds for the Polak-Ribière-Polyak (PRP) and the Fletcher-Reeves (FR) NCGMs for smooth strongly convex minimization. In particular, we construct ma…

This https://arxiv.org/abs/2305.06301 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Dispersive Analysis of $B\to K^{(*)}$ and $B_s\to ϕ$ Form Factors
We propose a stronger formulation of the dispersive (or unitarity) bounds à la Boyd-Grinstein-Lebed (BGL), which are commonly applied in analyses of the hadronic form factors for $B$ decays. In our approach, the existing bounds are split into several new bounds, thereby disentangling form factors that are jointly bounded in the common approach. This leads to stronger constraints for these objects, to a significant simplification of our numerical analysis, and to the removal of spurious correla…

This https://arxiv.org/abs/2312.13938 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

How Does Stake Distribution Influence Consensus? Analyzing Blockchain Decentralization
In the PoS blockchain landscape, the challenge of achieving full decentralization is often hindered by a disproportionate concentration of staked tokens among a few validators. This study analyses this challenge by first formalizing decentralization metrics for weighted consensus mechanisms. An empirical analysis across ten permissionless blockchains uncovers significant weight concentration among validators, underscoring the need for an equitable approach. To counter this, we introduce the Squ…

Kemp, Jennifer, Charles Watkinson, and Christina Drummond. 2024. ‘Exploring National Infrastructures to Support Impact Analyses of Publicly Accessible Research: A Need for Trust, Transparency and Collaboration at Scale’. doi: 10.7302/22166.
https://dx.doi.org/10.7302/22166

This https://arxiv.org/abs/2303.10599 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
Understanding stochastic gradient descent (SGD) and its variants is essential for machine learning. However, most of the preceding analyses are conducted under amenable conditions such as unbiased gradient estimator and bounded objective functions, which does not encompass many sophisticated applications, such as variational Monte Carlo, entropy-regularized reinforcement learning and variational inference. In this paper, we consider the SGD algorithm that employ the Markov Chain Monte Carlo (MC…

FastFlip: Compositional Error Injection Analysis
Keyur Joshi, Rahul Singh, Tommaso Bassetto, Sarita Adve, Darko Marinov, Sasa Misailovic
https://arxiv.org/abs/2403.13989

FastFlip: Compositional Error Injection Analysis
Instruction-level error injection analyses aim to find instructions where errors often lead to unacceptable outcomes like Silent Data Corruptions (SDCs). These analyses require significant time, which is especially problematic if developers wish to regularly analyze software that evolves over time. We present FastFlip, a combination of empirical error injection and symbolic SDC propagation analyses that enables fast, compositional error injection analysis of evolving programs. FastFlip calcul…

This https://arxiv.org/abs/2402.06988 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Three Subtyping Algorithms for Binary Session Types and their Complexity Analyses (full version)
Session types are a type discipline for describing and specifying communication behaviours of concurrent processes. Session subtyping, firstly introduced by Gay and Hole, is widely used for enlarging typability of session programs. This paper gives the complexity analysis of three algorithms for subtyping of synchronous binary session types. First, we analyse the complexity of the algorithm from the original paper, which is based on an inductive tree search. We then introduce its optimised vers…

This https://arxiv.org/abs/2310.09321 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Robustness- and weight-based resource measures without convexity restriction: Multicopy witness and operational advantage in static and dynamical quantum resource theories
Quantum resource theories (QRTs) provide a unified framework to analyze quantum properties as resources for achieving advantages in quantum information processing. The generalized robustness and the weight of resource have been gaining increasing attention as useful resource quantifiers. However, the existing analyses of these measures were restricted to the cases where convexity of the set of free states is assumed, and physically motivated resources do not necessarily satisfy this restriction…

Antisocial Analagous Behavior, Alignment and Human Impact of Google AI Systems: Evaluating through the lens of modified Antisocial Behavior Criteria by Human Interaction, Independent LLM Analysis, and AI Self-Reflection
Alan D. Ogilvie
https://arxiv.org/abs/2403.15479

Antisocial Analagous Behavior, Alignment and Human Impact of Google AI Systems: Evaluating through the lens of modified Antisocial Behavior Criteria by Human Interaction, Independent LLM Analysis, and AI Self-Reflection
Google AI systems exhibit patterns mirroring antisocial personality disorder (ASPD), consistent across models from Bard on PaLM to Gemini Advanced, meeting 5 out of 7 ASPD modified criteria. These patterns, along with comparable corporate behaviors, are scrutinized using an ASPD-inspired framework, emphasizing the heuristic value in assessing AI's human impact. Independent analyses by ChatGPT 4 and Claude 3.0 Opus of the Google interactions, alongside AI self-reflection, validate these concerns…

LLMs in HCI Data Work: Bridging the Gap Between Information Retrieval and Responsible Research Practices
Neda Taghizadeh Serajeh, Iman Mohammadi, Vittorio Fuccella, Mattia De Rosa
https://arxiv.org/abs/2403.18173

LLMs in HCI Data Work: Bridging the Gap Between Information Retrieval and Responsible Research Practices
Efficient and accurate information extraction from scientific papers is significant in the rapidly developing human-computer interaction research in the literature review process. Our paper introduces and analyses a new information retrieval system using state-of-the-art Large Language Models (LLMs) in combination with structured text analysis techniques to extract experimental data from HCI literature, emphasizing key elements. Then We analyze the challenges and risks of using LLMs in the worl…

Effects of anisotropy in an anisotropic extension of $w$CDM model
Vikrant Yadav, Santosh Kumar Yadav, Rajpal
https://arxiv.org/abs/2402.16885 https://

Effects of anisotropy in an anisotropic extension of $w$CDM model
In this paper, we derive observational constraints on an anisotropic $w$CDM model from observational data including Baryonic Acoustic Oscillations (BAOs), Cosmic Chronometer (CC), Big Bang Nucleosynthesis (BBN), Pantheon Plus (PP) compilation of Type Ia supernovae, and SH0ES Cepheid host distance anchors. We find that anisotropy is of the order $10^{-13}$, and its presence in the $w$CDM model reduces $H_0$ tension by $\sim 2σ$ and $\sim 1σ$ in the analyses with BAO+CC+BBN+PP and BAO+CC+BBN+PP…

This https://arxiv.org/abs/2402.09763 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Quantifying Systematic Uncertainties in Experimental Physics: An Approximation Method
In the domain of physics experiments, data fitting is a pivotal technique for extracting insights from both experimental and simulated datasets. This article presents an approximation method designed to estimate the systematic errors prevalent in data analyses. By applying our method to the Nab experiment, we compare our findings with simulation-derived results, thereby confirming the concordance of our approach with established simulation outcomes. This corroboration highlights the versatility…

Runtime Analyses of NSGA-III on Many-Objective Problems
Andre Opris, Duc-Cuong Dang, Dirk Sudholt
https://arxiv.org/abs/2404.11433 https://

Runtime Analyses of NSGA-III on Many-Objective Problems
NSGA-II and NSGA-III are two of the most popular evolutionary multi-objective algorithms used in practice. While NSGA-II is used for few objectives such as 2 and 3, NSGA-III is designed to deal with a larger number of objectives. In a recent breakthrough, Wietheger and Doerr (IJCAI 2023) gave the first runtime analysis for NSGA-III on the 3-objective OneMinMax problem, showing that this state-of-the-art algorithm can be analyzed rigorously. We advance this new line of research by presenting the…

This https://arxiv.org/abs/2302.14534 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face
We present Spacerini, a tool that integrates the Pyserini toolkit for reproducible information retrieval research with Hugging Face to enable the seamless construction and deployment of interactive search engines. Spacerini makes state-of-the-art sparse and dense retrieval models more accessible to non-IR practitioners while minimizing deployment effort. This is useful for NLP researchers who want to better understand and validate their research by performing qualitative analyses of training co…

This https://arxiv.org/abs/2206.11117 has been replaced.
link: https://scholar.google.com/scholar?q=a

Causal inference in multi-cohort studies using the target trial framework to identify and minimize sources of bias
Longitudinal cohort studies, which follow a group of individuals over time, provide the opportunity to examine causal effects of complex exposures on long-term health outcomes. Utilizing data from multiple cohorts has the potential to add further benefit by improving precision of estimates through data pooling and by allowing examination of effect heterogeneity through replication of analyses across cohorts. However, the interpretation of findings can be complicated by biases that may be compou…

Costless correction of chain based nested sampling parameter estimation in gravitational wave data and beyond
Metha Prathaban, Will Handley
https://arxiv.org/abs/2404.16428

Costless correction of chain based nested sampling parameter estimation in gravitational wave data and beyond
Nested sampling parameter estimation differs from evidence estimation, in that it incurs an additional source of error. This error affects estimates of parameter means and credible intervals in gravitational wave analyses and beyond, and yet, it is typically not accounted for in standard error estimation methods. In this paper, we present two novel methods to quantify this error more accurately for any chain based nested sampler, using the additional likelihood calls made at runtime in producin…

Thank you, @…, Heather Cox Richardson's analyses are spot on every day. Sununu admitting, on video, he (and all who will follow the OrangeFace) are greedy, immoral scunge is just the beginning of this dissection. After reading her, you feel good anyway. You feel determined.
#Politics

Hybrid Warfare Analytical Group/UCMC. Episode 4, Cinematic Propaganda The Hybrid Warfare Analytical Group’s (UCMC) analysts convene to delve into the realms of Russian disinformation, propaganda, and Source : https://uacrisis.org/en/hybrid-warfare

"by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions ... inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action... a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions."
How close is

This https://arxiv.org/abs/2311.06610 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Intrinsic Geometry of Collider Observations and Forman Ricci Curvature
We study the persistent homology and combinatorial Forman Ricci curvature distributions of a multi-lepton pattern reconstructed at the detectors. The topological properties exhibit an almost constant scaling behaviour with integrated luminosity and event selection parameters. This exploratory study suggests that the higher-order geometric features could supplement the traditional cut-and-count analyses, differentiating the BSM signals from the SM background.

Fossil Signatures of Main-sequence Convective Core Overshoot Estimated through Asteroseismic Analyses
Christopher J. Lindsay, J. M. Joel Ong, Sarbani Basu
https://arxiv.org/abs/2402.12461

Fossil Signatures of Main-sequence Convective Core Overshoot Estimated through Asteroseismic Analyses
Some physical processes that occur during a star's main-sequence evolution also affect its post main-sequence evolution. It is well known that stars with masses above approximately 1.1 $M_{\odot}$ have well-mixed convective cores on the main sequence, however, the structure of the star in the neighborhood of the convective core regions is currently underconstrained. We use asteroseismology to study the properties of the stellar core, in particular, convective boundary mixing through convective …

This https://arxiv.org/abs/2308.07994 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Bound circumplanetary orbits under the influence of radiation pressure: Application to dust in directly imaged exoplanet systems
We examine the population of simply periodic orbits in the Hill problem with radiation pressure included, in order to understand the distribution of gravitationally bound dust in orbit around a planet. We study a wide range of radiation pressure strengths, which requires the inclusion of additional terms beyond those discussed in previous analyses of this problem. In particular, our solutions reveal two distinct populations of stable wide, retrograde, orbits, as opposed to the single family tha…

Grad-CAMO: Learning Interpretable Single-Cell Morphological Profiles from 3D Cell Painting Images
Vivek Gopalakrishnan, Jingzhe Ma, Zhiyong Xie
https://arxiv.org/abs/2403.17615

Grad-CAMO: Learning Interpretable Single-Cell Morphological Profiles from 3D Cell Painting Images
Despite their black-box nature, deep learning models are extensively used in image-based drug discovery to extract feature vectors from single cells in microscopy images. To better understand how these networks perform representation learning, we employ visual explainability techniques (e.g., Grad-CAM). Our analyses reveal several mechanisms by which supervised models cheat, exploiting biologically irrelevant pixels when extracting morphological features from images, such as noise in the backgr…

Early Stopping for Ensemble Kalman-Bucy Inversion
Maia Tienstra
https://arxiv.org/abs/2403.18353 https://arxiv.org/pdf/2403.18353

Early Stopping for Ensemble Kalman-Bucy Inversion
Bayesian linear inverse problems aim to recover an unknown signal from noisy observations, incorporating prior knowledge. This paper analyses a data dependent method to choose the scale parameter of a Gaussian prior. The method we study arises from early stopping methods, which have been successfully applied to a range of problems for statistical inverse problems in the frequentist setting. These results are extended to the Bayesian setting. We study the use of a discrepancy based stopping rule…

This https://arxiv.org/abs/2403.04639 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

MaCmS: Magahi Code-mixed Dataset for Sentiment Analysis
The present paper introduces new sentiment data, MaCMS, for Magahi-Hindi-English (MHE) code-mixed language, where Magahi is a less-resourced minority language. This dataset is the first Magahi-Hindi-English code-mixed dataset for sentiment analysis tasks. Further, we also provide a linguistics analysis of the dataset to understand the structure of code-mixing and a statistical study to understand the language preferences of speakers with different polarities. With these analyses, we also train …

This https://arxiv.org/abs/2311.03491 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Baryonic Imprints on DM Halos: the concentration-mass relation and its dependence on halo and galaxy properties
The halo concentration-mass relation has ubiquitous use in modeling the matter field for cosmological and astrophysical analyses, and including the imprints from galaxy formation physics is tantamount to its robust usage. Many analyses, however, probe the matter around halos selected by a given halo/galaxy property -- rather than by halo mass -- and the imprints under each selection choice can be different. We employ the CAMELS simulation suite to quantify the astrophysics and cosmology depende…

This https://arxiv.org/abs/2402.11858 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Stochastic Hessian Fittings on Lie Groups
This paper studies the fitting of Hessian or its inverse for stochastic optimizations using a Hessian fitting criterion from the preconditioned stochastic gradient descent (PSGD) method, which is intimately related to many commonly used second order and adaptive gradient optimizers, e.g., BFGS, Gaussian-Newton and natural gradient descent, AdaGrad, etc. Our analyses reveal the efficiency and reliability differences among a wide range of preconditioner fitting methods, from closed-form to iterat…

This https://arxiv.org/abs/2308.07994 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Bound circumplanetary orbits under the influence of radiation pressure: Application to dust in directly imaged exoplanet systems
We examine the population of simply periodic orbits in the Hill problem with radiation pressure included, in order to understand the distribution of gravitationally bound dust in orbit around a planet. We study a wide range of radiation pressure strengths, which requires the inclusion of additional terms beyond those discussed in previous analyses of this problem. In particular, our solutions reveal two distinct populations of stable wide, retrograde, orbits, as opposed to the single family tha…

Unveiling Crowdfunding Futures: Analyzing Campaign Outcomes through Distributed Models and Big Data Perspectives
Giuseppe Pipit\`o, Emanuele Macca
https://arxiv.org/abs/2402.14111

Unveiling Crowdfunding Futures: Analyzing Campaign Outcomes through Distributed Models and Big Data Perspectives
Crowdfunding has emerged as a widespread strategy for startups seeking financing, particularly through reward-based methods. However, understanding its economic impact at both micro and macro levels requires thorough analysis, often involving advanced studies on past campaigns to extract insights that aiding companies in optimizing their crowdfunding project types and launch methodologies. Such analyses are often beyond the scope of basic data analysis techniques and frequently demand advanced …

Costless correction of chain based nested sampling parameter estimation in gravitational wave data and beyond
Metha Prathaban, Will Handley
https://arxiv.org/abs/2404.16428

Costless correction of chain based nested sampling parameter estimation in gravitational wave data and beyond
Nested sampling parameter estimation differs from evidence estimation, in that it incurs an additional source of error. This error affects estimates of parameter means and credible intervals in gravitational wave analyses and beyond, and yet, it is typically not accounted for in standard error estimation methods. In this paper, we present two novel methods to quantify this error more accurately for any chain based nested sampler, using the additional likelihood calls made at runtime in producin…

Optimal Survival Analyses With Prevalent and Incident Patients
Nicholas Hartman
https://arxiv.org/abs/2403.15302 https://arxiv.org/pd…

Optimal Survival Analyses With Prevalent and Incident Patients
Period-prevalent cohorts are often used for their cost-saving potential in epidemiological studies of survival outcomes. Under this design, prevalent patients allow for evaluations of long-term survival outcomes without the need for long follow-up, whereas incident patients allow for evaluations of short-term survival outcomes without the issue of left-truncation. In most period-prevalent survival analyses from the existing literature, patients have been recruited to achieve an overall sample s…

Linear dynamics and classical tests of the gravitational quantum field theory
Yuan-Kun Gao, Da Huang, Yong-Liang Ma, Yong Tang, Yue-Liang Wu, Yu-Feng Zhou
https://arxiv.org/abs/2403.17619

Linear dynamics and classical tests of the gravitational quantum field theory
We explore the new physics phenomena of gravidynamics governed by the inhomogeneous spin gauge symmetry based on the gravitational quantum field theory. Such a gravidynamics enables us to derive the generalized Einstein equation and an equation beyond it. To simplify the analyses, we linearize the dynamic equations of gravitational interaction by keeping terms up to the leading order in the dual gravigauge field. We then apply the linearized dynamic equations into two particular gravitational p…

CSSTs: A Dynamic Data Structure for Partial Orders in Concurrent Execution Analysis
H\"unkar Can Tun\c{c}, Ameya Prashant Deshmukh, Berk \c{C}irisci, Constantin Enea, Andreas Pavlogiannis
https://arxiv.org/abs/2403.17818

CSSTs: A Dynamic Data Structure for Partial Orders in Concurrent Execution Analysis
Dynamic analyses are a standard approach to analyzing and testing concurrent programs. Such techniques observe program traces and analyze them to infer the presence or absence of bugs. At its core, each analysis maintains a partial order $P$ that represents order dependencies between events of the analyzed trace $σ$. Naturally, the scalability of the analysis largely depends on how efficiently it maintains $P$. The standard data structure for this task has thus far been vector clocks. These, h…

One flow to correct them all: improving simulations in high-energy physics with a single normalising flow and a switch
Caio Cesar Daumann, Mauro Donega, Johannes Erdmann, Massimiliano Galli, Jan Lukas Sp\"ah, Davide Valsecchi
https://arxiv.org/abs/2403.18582

One flow to correct them all: improving simulations in high-energy physics with a single normalising flow and a switch
Simulated events are key ingredients in almost all high-energy physics analyses. However, imperfections in the simulation can lead to sizeable differences between the observed data and simulated events. The effects of such mismodelling on relevant observables must be corrected either effectively via scale factors, with weights or by modifying the distributions of the observables and their correlations. We introduce a correction method that transforms one multidimensional distribution (simulatio…

CSSTs: A Dynamic Data Structure for Partial Orders in Concurrent Execution Analysis
H\"unkar Can Tun\c{c}, Ameya Prashant Deshmukh, Berk \c{C}irisci, Constantin Enea, Andreas Pavlogiannis
https://arxiv.org/abs/2403.17818

CSSTs: A Dynamic Data Structure for Partial Orders in Concurrent Execution Analysis
Dynamic analyses are a standard approach to analyzing and testing concurrent programs. Such techniques observe program traces and analyze them to infer the presence or absence of bugs. At its core, each analysis maintains a partial order $P$ that represents order dependencies between events of the analyzed trace $σ$. Naturally, the scalability of the analysis largely depends on how efficiently it maintains $P$. The standard data structure for this task has thus far been vector clocks. These, h…

Some Findings from the Longitudinal Migration of Starspots
N. \"O. Kaya, H. A. Dal
https://arxiv.org/abs/2403.16946 https://arxi…

Some Findings from the Longitudinal Migration of Starspots
We present results regarding the longitudinal migrations of cool stellar spots that exhibit remarkable oscillations and explore their possible causes. We conducted analyses using high-quality data from nine target systems of various spectral types, spanning from F to M, which were observed by the Kepler Satellite. The systems in which the behaviour of the spots was examined are as follows: KIC 4357272, KIC 6025466, KIC 6058875, KIC 6962018, KIC 7798259, KIC 9210828, KIC 11706658, KIC 12599700, …

Systematic errors in searches for nanohertz gravitational waves
Valentina Di Marco, Andrew Zic, Ryan M. Shannon, Eric Thrane
https://arxiv.org/abs/2403.13175

Systematic errors in searches for nanohertz gravitational waves
A number of pulsar timing arrays have recently reported preliminary evidence for the existence of a nanohertz frequency gravitational-wave background. These analyses rely on detailed noise analyses, which are inherently complex due to the many astrophysical and instrumental factors that contribute to the pulsar noise budget. We investigate whether realistic systematic errors, stemming from misspecified noise models that fail to capture salient features of the pulsar timing noise, could bias the…

Exploring Algorithmic Explainability: Generating Explainable AI Insights for Personalized Clinical Decision Support Focused on Cannabis Intoxication in Young Adults
Tongze Zhang, Tammy Chung, Anind Dey, Sang Won Bae
https://arxiv.org/abs/2404.14563

Exploring Algorithmic Explainability: Generating Explainable AI Insights for Personalized Clinical Decision Support Focused on Cannabis Intoxication in Young Adults
This study explores the possibility of facilitating algorithmic decision-making by combining interpretable artificial intelligence (XAI) techniques with sensor data, with the aim of providing researchers and clinicians with personalized analyses of cannabis intoxication behavior. SHAP analyzes the importance and quantifies the impact of specific factors such as environmental noise or heart rate, enabling clinicians to pinpoint influential behaviors and environmental conditions. SkopeRules simpl…

This https://arxiv.org/abs/2107.06238 has been replaced.
link: https://scholar.google.com/scholar?q=a

GENIUS-MAWII: For Robust Mendelian Randomization with Many Weak Invalid Instruments
Mendelian randomization (MR) has become a popular approach to study causal effects by using genetic variants as instrumental variables. We propose a new MR method, GENIUS-MAWII, which simultaneously addresses the two salient phenomena that adversely affect MR analyses: many weak instruments and widespread horizontal pleiotropy. Similar to MR GENIUS (Tchetgen Tchetgen et al., 2021), we achieve identification of the treatment effect by leveraging heteroscedasticity of the exposure. We then derive…

Identifying CP Basis Invariants in SMEFT
Neda Darvishi, Yining Wang, Jiang-Hao Yu
https://arxiv.org/abs/2403.18732 https://arxiv.org/…

Identifying CP Basis Invariants in SMEFT
Building on our automated framework that uses ring diagrams for classifying CP basis invariants [1], this paper broadens the application of the methodology with more extensive examples and a wider scope of theoretical frameworks. Here, we showcase its versatility through detailed analyses in the Standard Model Effective Field Theory (SMEFT) up to dim-2n, and SMEFT with sterile neutrinos (νSMEFT) up to dimension-7. By integrating the ring-diagram technique with the Cayley-Hamilton theorem, we h…

This https://arxiv.org/abs/1907.10130 has been replaced.
link: https://scholar.google.com/scholar?q=a

Lensing convergence and anisotropic dark energy in galaxy redshift surveys
Analyses of upcoming galaxy surveys will require careful modelling of relevant observables such as the power spectrum of galaxy counts in harmonic space $C_\ell(z,z')$. We investigate the impact of disregarding relevant relativistic effects by considering a model of dark energy including constant sound speed $c_{\rm eff}^2$, constant equation of state $w$, and anisotropic stress sourced by matter perturbations $π$. Cosmological constraints were computed using cosmic microwave background anisot…

Inference on the proportion of variance explained in principal component analysis
Ronan Perry, Snigdha Panigrahi, Jacob Bien, Daniela Witten
https://arxiv.org/abs/2402.16725

Inference on the proportion of variance explained in principal component analysis
Principal component analysis (PCA) is a longstanding and well-studied approach for dimension reduction. It rests upon the assumption that the underlying signal in the data has low rank, and thus can be well-summarized using a small number of dimensions. The output of PCA is typically represented using a scree plot, which displays the proportion of variance explained (PVE) by each principal component. While the PVE is extensively reported in routine data analyses, to the best of our knowledge th…

This https://arxiv.org/abs/2309.13117 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Testing strengths, limitations and biases of current Pulsar Timing Arrays detection analyses on realistic data
State-of-the-art searches for gravitational waves (GWs) in pulsar timing array (PTA) datasets model the signal as an isotropic, Gaussian and stationary process described by a power-law. In practice, none of these properties are expected to hold for an incoherent superposition of GWs generated by a cosmic ensemble of supermassive black hole binaries (SMBHBs), which is expected to be the primary signal in the PTA band. We perform a systematic investigation of the performance of current search alg…

Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks
Supranta S. Boruah, Tim Eifler, Vivian Miranda, Elyas Farah, Jay Motka, Elisabeth Krause, Xiao Fang, Paul Rogozenski, The LSST Dark Energy Science Collaboration
https://arxiv.org/abs/2403.11797

Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks
Validating modeling choices through simulated analyses and quantifying the impact of different systematic effects will form a major computational bottleneck in the preparation for 3$\times$2 analysis with Stage-IV surveys such as Vera Rubin Observatory's Legacy Survey of Space and Time (LSST). We can significantly reduce the computational requirements by using machine learning based emulators, which allow us to run fast inference while maintaining the full realism of the data analysis pipeline.…

Three Subtyping Algorithms for Binary Session Types and their Complexity Analyses
Thien Udomsrirungruang, Nobuko Yoshida
https://arxiv.org/abs/2402.06988 h…

Three Subtyping Algorithms for Binary Session Types and their Complexity Analyses
Session types are a type discipline for describing and specifying communication behaviours of concurrent processes. Session subtyping, firstly introduced by Gay and Hole, is widely used for enlarging typability of session programs. This paper gives the complexity analysis of three algorithms for subtyping of synchronous binary session types. First, we analyse the complexity of the algorithm from the original paper, which is based on an inductive tree search. We then introduce its optimised vers…

Covariate-adjusted Group Sequential Comparisons of Survival Probabilities
Peter Zhang, Brent Logan, Michael Martens
https://arxiv.org/abs/2403.17117 https:…

Covariate-adjusted Group Sequential Comparisons of Survival Probabilities
In confirmatory clinical trials, survival outcomes are frequently studied and interim analyses for efficacy and/or futility are often desirable. Methods such as the log rank test and Cox regression model are commonly used to compare treatments in this setting. They rely on a proportional hazards (PH) assumption and are subject to type I error rate inflation and loss of power when PH are violated. Such violations may be expected a priori, particularly when the mechanisms of treatments differ suc…

This https://arxiv.org/abs/2307.09064 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Newtonian Program Analysis of Probabilistic Programs
Due to their quantitative nature, probabilistic programs pose non-trivial challenges for designing compositional and efficient program analyses. Many analyses for probabilistic programs rely on iterative approximation. This article presents an interprocedural dataflow-analysis framework, called NPA-PMA, for designing and implementing (partially) non-iterative program analyses of probabilistic programs with unstructured control-flow, nondeterminism, and general recursion. NPA-PMA is based on New…

A frequentist test of proportional colocalization after selecting relevant genetic variants
Ashish Patel, John C. Whittaker, Stephen Burgess
https://arxiv.org/abs/2402.12171

A frequentist test of proportional colocalization after selecting relevant genetic variants
Colocalization analyses assess whether two traits are affected by the same or distinct causal genetic variants in a single gene region. A class of Bayesian colocalization tests are now routinely used in practice; for example, for genetic analyses in drug development pipelines. In this work, we consider an alternative frequentist approach to colocalization testing that examines the proportionality of genetic associations with each trait. The proportional colocalization approach uses markedly dif…

This https://arxiv.org/abs/2312.06437 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Posterior Ramifications of Prior Dependence Structures
In fully Bayesian analyses, prior distributions are specified before observing data. Prior elicitation methods transfigure prior information into quantifiable prior distributions. Recently, methods that leverage copulas have been proposed to accommodate more flexible dependence structures when eliciting multivariate priors. We prove that under broad conditions, the posterior cannot retain many of these flexible prior dependence structures in large-sample settings. We emphasize the impact of thi…