Negative / Null Result ReportMedicine
Jiang Y, Luo J, Zheng L et al. · 2026 · The journal of obstetrics and gynaecology research
Aim To examine the association between the distribution of energy and macronutrients between dinner and breakfast and depressive symptoms in early pregnancy. Methods This study used baseline data from a maternity cohort conducted in Wuhan,…
View details →DOI: 10.1111/jog.70298 Negative / Null Result ReportMedicine
Kagami M, Kataoka Y, Hirao Y et al. · 2026 · IEEE transactions on visualization and computer graphics
Augmented Reality (AR) can enhance accessibility by anchoring virtual windows to the user's body. Among common approaches, head-following windows help maintain floating virtual windows within the user's field of view. Previous studies have…
View details →DOI: 10.1109/tvcg.2026.3679137 Negative / Null Result ReportMedicine
Myllylä IL, Wiklund M, Haakana V et al. · 2026 · Clinical linguistics & phonetics
Speech of persons on the autism spectrum is often described as prosodically distinctive, yet the perceptual basis and acoustic correlates of these judgements remain undefined. We investigated how prosodic typicality is perceived in…
View details →DOI: 10.1080/02699206.2026.2642726 Negative / Null Result ReportOpen accessMedicine
Filtness AJ, Miller KA, Maynard S et al. · 2026 · Scientific reports
Driver sleepiness contributes to a substantial proportion of road crashes. Drivers experiencing sleepiness are advised to take a break and have a caffeinated drink followed by a short nap (caffeine nap). However, previous research…
View details →DOI: 10.1038/s41598-026-42894-1 Negative / Null Result Report
Widłak P, Malara M, Kuk A et al. · 2026 · Preprint
Abstract Movement quality and postural control are crucial for performance and injury prevention in team-sport athletes. Although FMS and YBT are commonly used, their ability to predict injury risk is limited when used alone. Therefore,…
View details →DOI: 10.21203/rs.3.rs-9464599/v1 Negative / Null Result Report
Etoundi JC, Juhel A · 2026 · Preprint
Social media use has been identified as a significant risk factor for the development and maintenance of eating disorders, particularly among young adults. Despite the growing urgency of this public health issue, effective prevention…
View details →DOI: 10.31234/osf.io/txeqz_v1 Negative / Null Result ReportMedicine
Chowdhury A, Dasgupta D · 2026 · Anthropologischer Anzeiger; Bericht uber die biologisch-anthropologische Literatur
Objective : Present study delineates to explore the relation of actual body weight and body self-image perception among tribal adolescent girls and boys. Materials and methods : This cross sectional study is conducted at Purulia district…
View details →DOI: 10.1127/anthranz/1945 Negative / Null Result ReportOpen accessMedicine
Zanco B, Mirth CK, Sgrò CM et al. · 2026 · npj aging
Dietary restriction may extend lifespan by improving late-life gut health. Because micronutrients mediate the effects of macronutrient ratios on longevity, we examined how cholesterol limitation affects gut health in female Drosophila…
View details →DOI: 10.1038/s41514-026-00341-5 Negative / Null Result ReportOpen accessPhysics
Yoav Simhon, Alex Segal, Ofer Amrani et al. · 2025 · arXiv
Scintillator-SiPM Particle Detectors (SSPDs) are compact, low-power devices with applications including particle physics, underground tomography, cosmic-ray studies, and space instrumentation. They are based on a prism-shaped scintillator with corner-mounted SiPMs. Previous work has demonstrated that analytic algorithms based on a physical model of light propagation can reconstruct particle impinging positions and tracks and estimate deposited energy and Linear Energy Transfer (LET) with moderate accuracy. In this study, we enhance this approach by applying machine learning (ML) methods, speci
Negative / Null Result ReportOpen accessComputer Science
Yang Liu, Yixing Luo, Xiaofeng Li et al. · 2026 · arXiv
Time series anomaly detection (TSAD) is essential for ensuring the safety and reliability of aerospace software systems. Although large language models (LLMs) provide a promising training-free alternative to unsupervised approaches, their effectiveness in aerospace settings remains under-examined because of complex telemetry, misaligned evaluation metrics, and the absence of domain knowledge. To address this gap, we introduce ATSADBench, the first benchmark for aerospace TSAD. ATSADBench comprises nine tasks that combine three pattern-wise anomaly types, univariate and multivariate signals, an
Negative / Null Result ReportOpen accessComputer Science
Mandhapati P. Raju, Siddhartha Khaitan · 2009 · arXiv
The study deals with the parallelization of finite element based Navier-Stokes codes using domain decomposition and state-ofart sparse direct solvers. There has been significant improvement in the performance of sparse direct solvers. Parallel sparse direct solvers are not found to exhibit good scalability. Hence, the parallelization of sparse direct solvers is done using domain decomposition techniques. A highly efficient sparse direct solver PARDISO is used in this study. The scalability of both Newton and modified Newton algorithms are tested.
Negative / Null Result ReportOpen accessPhysics
Dominic M. Bowman, Daniel L. Holdsworth · 2019 · arXiv
Context. Modern space telescopes are currently providing high-precision light curves for a large fraction of the sky, such that many new variable stars are being discovered. However, some stars have periodic variability with periods of order minutes and require high-cadence photometry to probe the physical mechanisms responsible. A cadence of less than a minute is often required to remove Nyquist ambiguities and confirm rapid variability which forces observers to obtain high-cadence ground-based photometry. Aims. We aim to provide a modern software package to reduce ground-based photometric ti
Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Francisco Rodríguez · 2022 · arXiv
We revisit the results of a recent paper by Equipo Anova, who claim to find evidence of an improvement in Venezuelan imports of food and medicines associated with the adoption of U.S. financial sanctions towards Venezuela in 2017. We show that their results are consequence of data coding errors and questionable methodological choices, including the use an unreasonable functional form that implies a counterfactual of negative imports in the absence of sanctions, the omission of data accounting for four-fifths of the country's food imports at the time of sanctions and incorrect application of re
Negative / Null Result ReportOpen accessPhysics
Sarbani Basu, H. M. Antia · 1999 · arXiv
Ring diagram analysis can be used to study large scale velocity fields in the outer part of the solar convection zone. All previous works assume that the peak profiles in the solar oscillation power spectrum are symmetric. However, it has now been demonstrated that the peaks are not symmetric. In this work we study how the explicit use of asymmetric peak profiles in ring-diagram analysis influences the estimated velocity fields. We find that the use of asymmetric profiles leads to significant improvement in the fits, but the estimated velocity fields are not substantially different from those
Negative / Null Result ReportOpen accessPhysics
Xian-Yu Wang, Yong-Hao Wang, Songhu Wang et al. · 2021 · arXiv
We present 127 new transit light curves for 39 hot Jupiter systems, obtained over the span of five years by two ground-based telescopes. A homogeneous analysis of these newly collected light curves together with archived spectroscopic, photometric, and Doppler velocimetric data using EXOFASTv2 leads to a significant improvement in the physical and orbital parameters of each system. All of our stellar radii are constrained to accuracies of better than 3\%. The planetary radii for 37 of our 39 targets are determined to accuracies of better than $5\%$. Compared to our results, the literature ecce
Negative / Null Result ReportOpen accessComputer Science
Andreas Hocker · 2001 · arXiv
The recent precise measurement of the muon magnetic anomaly (g-2)_{mu} at BNL opens a window into possible new physics, provided the contribution from hadronic vacuum polarization is well understood. This talk summarizes the development in the evaluation of the leading order hadronic contributions. Significant improvement has been achieved in a series of analyses which is presented historically in three steps: (1), use of tau spectral functions in addition to e+e- cross sections, (2), extended use of perturbative QCD and (3), application of QCD sum rule techniques. The uncertainties, in partic
Negative / Null Result ReportOpen accessComputer Science
Prabhav Jain, Nikolai Miklin, Mariami Gachechiladze · 2026 · arXiv
Information Causality was introduced as a physical principle for constraining the set of nonlocal correlations. In recent work, we proposed an extension of Information Causality that allows correlations among Alice's inputs. This extended principle yields tighter constraints than the original formulation and recovers part of the quantum boundary in certain Bell scenarios. In this work, we further investigate the implications of extended Information Causality and apply it to scenarios beyond binary inputs and outputs. We derive a family of quantum Bell inequalities that strengthen previously kn
Negative / Null Result ReportOpen accessComputer Science
Jirui Qi, Raquel Fernández, Arianna Bisazza · 2023 · arXiv
Multilingual large-scale Pretrained Language Models (PLMs) have been shown to store considerable amounts of factual knowledge, but large variations are observed across languages. With the ultimate goal of ensuring that users with different language backgrounds obtain consistent feedback from the same model, we study the cross-lingual consistency (CLC) of factual knowledge in various multilingual PLMs. To this end, we propose a Ranking-based Consistency (RankC) metric to evaluate knowledge consistency across languages independently from accuracy. Using this metric, we conduct an in-depth analys
Negative / Null Result ReportOpen accessComputer Science
Gil Katz, Pablo Piantanida, Merouane Debbah · 2016 · arXiv
A collaborative distributed binary decision problem is considered. Two statisticians are required to declare the correct probability measure of two jointly distributed memoryless process, denoted by $X^n=(X_1,\dots,X_n)$ and $Y^n=(Y_1,\dots,Y_n)$, out of two possible probability measures on finite alphabets, namely $P_{XY}$ and $P_{\bar{X}\bar{Y}}$. The marginal samples given by $X^n$ and $Y^n$ are assumed to be available at different locations. The statisticians are allowed to exchange limited amount of data over multiple rounds of interactions, which differs from previous work that deals mai
Negative / Null Result ReportOpen accessMathematics
Giulio Cantone, Venera Tomaselli · 2022 · arXiv
Snowball sampling is the common name for sampling designs on human populations where respondents are requested to share the questionnaire among their social ties. With some exceptions, estimates from snowball samplings are considered biased. However, the magnitude of the bias is influenced by a combination of elements of the sampling design and features of the target population. Hybrid Probabilistic-Snowball Sampling Designs (HPSSD) aims to reduce the main source of bias in the snowball sample through randomly oversampling the first stage 0 of the snowball. To check the behaviour of HPSSD for
Negative / Null Result ReportOpen accessComputer Science
Rumman Ahmed Prodhan, Sumya Akter, Tanmoy Sarkar Pias et al. · 2023 · arXiv
The human brain is a complex organ, still completely undiscovered, that controls almost all the parts of the body. Apart from survival, the human brain stimulates emotions. Recent research indicates that brain signals can be very effective for emotion recognition. However, which parts of the brain exhibit most of the emotions is still under-explored. In this study, we empirically analyze the contribution of each part of the brain in exhibiting emotions. We use the DEAP dataset to find the most optimal electrode set which eventually leads to the effective brain part associated with emotions. We
Negative / Null Result ReportOpen accessComputer Science
Roberto Casadio, Fabio Finelli, Mattia Luzzi et al. · 2004 · arXiv
Improved Wentzel-Kramers-Brillouin (WKB)-type approximations are presented in order to study cosmological perturbations beyond the lowest order. Our methods are based on functions which approximate the true perturbation modes over the complete range of the independent (Langer) variable, from sub-horizon to super-horizon scales, and include the region near the turning point. We employ both a perturbative Green's function technique and an adiabatic (or ``semiclassical'') expansion (for a linear turning point) in order to compute higher order corrections. Improved general expressions for the WKB
Negative / Null Result ReportOpen accessPhysics
Florian Sammüller, Sophie Hermann, Matthias Schmidt · 2022 · arXiv
We reexamine results obtained with the recently proposed density functional theory framework based on forces (force-DFT) [Tschopp et al., Phys. Rev. E 106, 014115 (2022)]. We compare inhomogeneous density profiles for hard sphere fluids to results from both standard density functional theory and from computer simulations. Test situations include the equilibrium hard sphere fluid adsorbed against a planar hard wall and the dynamical relaxation of hard spheres in a switched harmonic potential. The comparison to grand canonical Monte Carlo simulation profiles shows that equilibrium force-DFT alon
Negative / Null Result ReportOpen accessComputer Science
Abdul Waheed, Zhen Wu, Dareen Alharthi et al. · 2025 · arXiv
Precisely evaluating video understanding models remains challenging: commonly used metrics such as BLEU, ROUGE, and BERTScore fail to capture the fineness of human judgment, while obtaining such judgments through manual evaluation is costly. Recent work has explored using large language models (LLMs) or multimodal LLMs (MLLMs) as evaluators, but their extension to video understanding remains relatively unexplored. In this work, we introduce VideoJudge, a 3B and 7B-sized MLLM judge specialized to evaluate outputs from video understanding models (\textit{i.e.}, text responses conditioned on vide
Negative / Null Result ReportOpen accessComputer Science
Ryosuke Kohita, Seiichiro Yoshioka · 2026 · arXiv
Memes are a popular element of modern web communication, used not only as static artifacts but also as interactive replies within conversations. While computational research has focused on analyzing the intrinsic properties of memes, the dynamic and contextual use of memes to create humor remains an understudied area of web science. To address this gap, we introduce the Meme Reply Selection task and present MaMe-Re (Manga Meme Reply Benchmark), a benchmark of 100,000 human-annotated pairs (500,000 total annotations from 2,325 unique annotators) consisting of openly licensed Japanese manga pane
Negative / Null Result ReportOpen accessPhysics
Laura Stricker, Benjamin Dollet, David Fernandez Rivas et al. · 2013 · arXiv
Acoustically driven air pockets trapped in artificial crevices on a sur- face can emit bubbles which organize in (interacting) bubble clusters. With increasing driving power Fernandez Rivas et al. [Angew. Chem. Int. Ed., 2010] observed three different behaviors: clusters close to the very pits out of which they had been created, clusters pointing toward each other, and merging clusters. The latter behavior is highly undesired for technological purposes as it is associated with a reduction of the radical production and an enhancement of the erosion of the reactor walls. The dependence on the co
Negative / Null Result ReportOpen accessEngineering
Deepak Singla, Soham Chatterjee, Lavanya Ramapantulu et al. · 2020 · arXiv
Applications in the Internet of Video Things (IoVT) domain have very tight constraints with respect to power and area. While neuromorphic vision sensors (NVS) may offer advantages over traditional imagers in this domain, the existing NVS systems either do not meet the power constraints or have not demonstrated end-to-end system performance. To address this, we improve on a recently proposed hybrid event-frame approach by using morphological image processing algorithms for region proposal and address the low-power requirement for object detection and classification by exploring various convolut
Negative / Null Result ReportOpen accessMathematics
Nicolas Banholzer, Thomas Mellan, H Juliette T Unwin et al. · 2023 · arXiv
Short-term forecasts of infectious disease spread are a critical component in risk evaluation and public health decision making. While different models for short-term forecasting have been developed, open questions about their relative performance remain. Here, we compare short-term probabilistic forecasts of popular mechanistic models based on the renewal equation with forecasts of statistical time series models. Our empirical comparison is based on data of the daily incidence of COVID-19 across six large US states over the first pandemic year. We find that, on average, probabilistic forecast
Negative / Null Result ReportOpen accessComputer Science
Evgeniia Razumovskaia, Ivan Vulić, Anna Korhonen · 2024 · arXiv
Supervised fine-tuning (SFT), supervised instruction tuning (SIT) and in-context learning (ICL) are three alternative, de facto standard approaches to few-shot learning. ICL has gained popularity recently with the advent of LLMs due to its simplicity and sample efficiency. Prior research has conducted only limited investigation into how these approaches work for multilingual few-shot learning, and the focus so far has been mostly on their performance. In this work, we present an extensive and systematic comparison of the three approaches, testing them on 6 high- and low-resource languages, thr
Negative / Null Result ReportOpen accessComputer Science
Zijie Zhao, Roy E. Welsch · 2026 · arXiv
Financial retrieval-augmented generation (RAG) systems typically rank evidence by textual relevance, but in financial markets evidence utility depends on event type, forecast horizon, and market context. We study news-triggered event-impact prediction as a point-in-time financial RAG problem. For each company-news anchor, the system retrieves financial news and SEC filing passages, appends a pre-decision market-context card, and predicts multi-horizon residual-return signals. Our method keeps the LLM frozen and adapts retrieval through an external Bayesian source memory updated from matured re
