Search · four archives
Search · four archives
24 papers · ranked by Valyu relevance
Authors not listed
Quantitative Structure Activity Relationship (QSAR) remains an effective tool for early-stage chemical modelling and virtual screening in drug design. The advancements in this field are led by two core paradigms, 1) descriptor engineering, where complex fixed-length vectors of compounds are generated and conventional…
Ömer Karakoç, Samet Memiş, Bahar Sennaroglu, Rajesh Kumar
This study provides a comprehensive evaluation and classification of 35 soft decision-making (SDM) algorithms based on fuzzy parameterized fuzzy soft matrices (fpfs-matrices). Although fpfs-matrices offer a strong mathematical framework for modeling uncertainty, there has been a lack of large-scale comparisons of their…
Tjorven Hinzke, Benoit J. Kunath, J. Alfredo Blakeley-Ruiz, Abigail Korenek + 3 more
Metaproteomics characterizes and compares molecular phenotypes of organisms in communities by comprehensively analyzing their protein expression profiles using statistical methods. However, not all statistical methods are suitable for determining differentially abundant protein groups in metaproteomic analyses.…
Muhammad Muneeb, David B. Ascher
Polygenic risk score (PRS) tools differ substantially in statistical assumptions, input requirements, and implementation complexity, making direct comparison difficult. We developed a harmonized, implementation-aware benchmarking framework to evaluate 46 PRS tools across seven binary UK Biobank phenotypes and one…
Mohamed Bilel Besbes, Gregory Mierzwinski, Suhaib Mujahid, Philipp Leitner + 3 more
Software performance regressions can have significant business consequences, making automated detection a critical component of modern continuous integration pipelines. At Mozilla, performance anomaly detection is handled by Perfherder, Mozilla's performance engineering management system that relies on a Student's…
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Fabricio Cravo, Alex Fischbach, Hallee Shearer, Matt Rosenblatt + 2 more
Low statistical power in neuroimaging often undermines research in the field, leading to missed effects, wasted resources, and reduced reproducibility. Performing power analyses during the study design phase is extremely important, but often prohibitively difficult due to a lack of analytical solutions and high…
Yoshitaka Morishita, Genta Ochi, Daiki Takahashi, Kodai Kato + 3 more
Pitch selection-the ability to discriminate balls from strikes-is fundamental to baseball batting success. This study examined whether this ability relates to executive function and batting performance in collegiate players. Furthermore, this ability may be supported by brain functions such as executive functions, and…
Authors not listed
Background: Batch reactor process optimization has traditionally relied on Analysis of Variance (ANOVA) for factor effect quantification. However, Structural Equation Modeling (SEM) and machine learning (ML) offer complementary mechanistic and predictive capabilities that remain underexplored in chemical engineering…
Mushuai Hao, Haonan Qi, Hong Qin, Liang Zhao + 3 more
Objective This study aimed to investigate the effects of a 14-week tempo-based strength periodization training program on muscle strength, power, and sport-specific performance in coastal rowers. Design A single-group pre-post study design was implemented. Method Twelve well-trained coastal rowers (age 20 ± 2.34 years…
Qizheng Dong, Zaidong Li, Jeremy P Loenneke
Although pacing strategy is widely recognized as critical for marathon performance, the actual distribution of pacing patterns among recreational runners and their associations with finish time across demographic groups have not been systematically characterized in large samples. This study analyzed split time data…
Alexander Muacevic, John R Adler, Frederick F Strale Jr., Rachael M German + 4 more
Background Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT, is increasingly being used for statistical interpretation and research support. While traditional statistical software such as IBM SPSS remains the gold standard for transparent and reproducible analyses, concerns…
Panagiotis Giannakopoulos, Bart van Knippenberg, Kishor Chandra Joshi, Nicola Calabretta + 1 more
Distributed applications increasingly demand low end-to-end latency, especially in edge and cloud environments where co-located workloads contend for limited resources. Traditional load-balancing strategies are typically reactive and rely on outdated or coarse-grained metrics, often leading to suboptimal routing…
Roberto C.M. Leite, Rhaí A. Arriel, Rodney Paixão, Leandro Sant’Ana + 1 more
Statistical inference underpins the credibility of sports science research, yet concerns remain regarding the rigor of statistical reporting and analysis. This study assessed the adequacy of statistical practices in sports science research according to established methodological guidelines. A total of 167 original…
Shimul Debnath, William Hart, Lori Pollock, Donald Lien + 1 more
Cloud performance fluctuates due to factors such as resource contention and workload changes. These factors can be short-term, seasonal, or long-term. Their effects are often intertwined in performance traces, making performance management difficult. Prior work on cloud performance engineering used time-series…
Philipp Krumm, Nicole Böttcher, Richard Ottermanns, Thomas Pufe + 1 more
Robust statistical analysis is essential for scientific validity and to ensure good scientific practice. Yet many researchers, especially in biomedical fields, struggle with checking assumptions, selecting the correct tests, and interpreting results. These obstacles can lead to misleading conclusions and undermine…
Authors not listed
Incorporating prior domain knowledge into Bayesian optimization (BO) remains difficult for statistical methods, which also typically suffer from limited interpretability. Large language models (LLMs) offer complementary strengths in reasoning and knowledge integration, but it remains unclear when and how they improve…
Rafael Terra, Diego Carvalho, Denis Jacob Machado, Carla Osthoff + 1 more
Advances in High-Performance Computing (HPC) have enabled increasingly complex genomic analyses, including those in phylogenomics. These analyses contribute to understanding the evolution of viruses and pathogens, improving our knowledge of disease transmission, and supporting targeted public health strategies.…
Aliva Sholihat, Risto Halonen, Riikka Möttönen, Anu-Katriina Pesonen
Learning in adulthood is embedded in everyday social life, in which periods of psychosocial stress alternate with recovery. The autonomic nervous system regulates how the body responds to environmental demands, yet individuals differ markedly in this regulation. It remains unknown whether such individual differences in…
Authors not listed
Mechanical agitation (stirring) is a cornerstone of organic synthesis, but has received little scientific attention due to its “obvious” role in facilitating reactions. A very recent study by Huang and coworkers compared the isolated yields in approximately 600 paired stirred and unstirred reactions, across a range of…
Reza Hosseini
Online controlled experiments face growing challenges from overlapping tests on shared traffic, where interactions between concurrent experiments obscure insights into feature combinations and produce effect estimates that do not correspond to any actionable launch scenario. While traffic splitting, layering, and…
Dragana Grbic
As exascale systems reach unprecedented concurrency, traditional performance analysis tools struggle with the overhead of massive-scale telemetry. We present an accelerated infrastructure for the hpcanalysis framework that leverages a high-performance C++ API and GPU parallelism to enable high-throughput diagnostics.…
Ellen Schmaljohn, Olalekan Usman, Christian Brommel, Kyle J. Kinney + 10 more
Chromosomal translocations are rare structural rearrangement outcomes of genome editing, requiring analytical frameworks that combine high quantitative accuracy with performant sensitivity and specificity. Amplicon sequencing offers a scalable means to detect rare rearrangements with ultra-deep targeted sequencing, but…
François Bechet, Jérôme Maquoi, Luís Cruz, Benoît Vanderose + 1 more
Green software engineering is emerging as a crucial response to information technology's rising energy impact, especially in continuous development. However, there remain challenges in devising automated methods for identifying energy regressions across commits and their associated code change patterns. In particular…