Negative / Null Result ReportOpen accessComputer Science
Tristan Piater, Niklas Penzel, Gideon Stein et al. · 2024 · arXiv
A substantial body of research has focused on developing systems that assist medical professionals during labor-intensive early screening processes, many based on convolutional deep-learning architectures. Recently, multiple studies explored the application of so-called self-attention mechanisms in the vision domain. These studies often report empirical improvements over fully convolutional approaches on various datasets and tasks. To evaluate this trend for medical imaging, we extend two widely adopted convolutional architectures with different self-attention variants on two different medical
Negative / Null Result ReportOpen accessComputer Science
Amir Yunus, Peng Rend Gay, Oon Teng Lee · 2025 · arXiv
This study examines the development and deployment of a Generative AI proof-of-concept (POC) designed to support lecturers in a vocational education setting in Singapore. Employing a user-centred, mixed-methods design process, we co-developed an AI chatbot with lecturers to address recurring instructional challenges during exam preparation, specifically managing repetitive questions and scaling feedback delivery. The POC achieved its primary operational goals: lecturers reported streamlined workflows, reduced cognitive load, and observed improved student confidence in navigating course content
Negative / Null Result ReportOpen accessComputer Science
Nima Akhlaghi, Ananya Dhawan, Amir A. Khan et al. · 2018 · arXiv
Objective: The objectives of this paper are to determine the optimal location for ultrasound transducer placement on the anterior forearm for imaging maximum muscle deformations during different hand motions and to investigate the effect of using a sparse set of ultrasound scanlines for motion classification for ultrasound-based muscle computer interfaces (MCIs). Methods: The optimal placement of the ultrasound transducer along the forearm is identified using freehand 3D reconstructions of the muscle thickness during rest and motion completion. From the ultrasound images acquired from the opti
Negative / Null Result ReportOpen accessAgricultural and Biological Sciences
Denis Boyer, Peter D. Walsh · 2010 · arXiv
Thanks to recent technological advances, it is now possible to track with an unprecedented precision and for long periods of time the movement patterns of many living organisms in their habitat. The increasing amount of data available on single trajectories offers the possibility of understanding how animals move and of testing basic movement models. Random walks have long represented the main description for micro-organisms and have also been useful to understand the foraging behaviour of large animals. Nevertheless, most vertebrates, in particular humans and other primates, rely on sophistic
Negative / Null Result ReportOpen accessComputer Science
Weronika Ormaniec, Michael Vollenweider, Elisa Hoskovec · 2025 · arXiv
In this paper, we explore the idea of combining GCNs into one model. To that end, we align the weights of different models layer-wise using optimal transport (OT). We present and evaluate three types of transportation costs and show that the studied fusion method consistently outperforms the performance of vanilla averaging. Finally, we present results suggesting that model fusion using OT is harder in the case of GCNs than MLPs and that incorporating the graph structure into the process does not improve the performance of the method.
Negative / Null Result ReportOpen accessComputer Science
Felix Krejca, Tobias Kietreiber, Alexander Buchelt et al. · 2025 · arXiv
The increasing volume of online discussions requires advanced automatic content moderation to maintain responsible discourse. While hate speech detection on social media is well-studied, research on German-language newspaper forums remains limited. Existing studies often neglect platform-specific context, such as user history and article themes. This paper addresses this gap by developing and evaluating binary classification models for automatic content moderation in German newspaper forums, incorporating contextual information. Using LSTM, CNN, and ChatGPT-3.5 Turbo, and leveraging the One Mi
Negative / Null Result ReportMedicine
Orhan B, Nauta M · 2026 · Death studies
Meaning Management Theory suggests that engaging with meaning-related resources helps individuals constructively regulate consciously experienced death anxiety. Consistent with that theory, we tested whether a single-session, online…
View details →DOI: 10.1080/07481187.2026.2659888 Negative / Null Result ReportOpen accessAgricultural and Biological Sciences
Louis Jalouzot, Alexis Thual, Yair Lakretz et al. · 2025 · arXiv
We investigate optimal strategies for decoding perceived natural speech from fMRI data acquired from a limited number of participants. Leveraging Lebel et al. (2023)'s dataset of 8 participants, we first demonstrate the effectiveness of training deep neural networks to predict LLM-derived text representations from fMRI activity. Then, in this data regime, we observe that multi-subject training does not improve decoding accuracy compared to single-subject approach. Furthermore, training on similar or different stimuli across subjects has a negligible effect on decoding accuracy. Finally, we fin
Negative / Null Result Report
Jose A. Rivera, Carmen E. Gonzalez, Tonita Bates · 2024 · JCO Oncology Practice
327 Background: Delayed assessment of diagnostic imaging (DI) significant actionable findings (AFs) at an oncological center prompted the creation of a safety net system which used technological advancements to improve communication…
View details →DOI: 10.1200/op.2024.20.10_suppl.327 Negative / Null Result ReportOpen accessComputer Science
Jan Tiemann, Matthew McGinity, Ulrik Günther · 2026 · arXiv
In contemporary biology and medicine, 3D microscopy is one of the most widely-used techniques for imaging and manipulation of various kinds of samples. Navigating such a micrometer-sized, 3-dimensional sample under the microscope -- e.g. to find relevant imaging regions -- can pose a tedious challenge for the experimenter. In this paper, we examine whether 2D desktop, 3D desktop, or Virtual Reality (VR) interfaces provide the best user experience and performance for the exploration of 3D samples. We invited 12 skilled microscope operators to perform two different exploration tasks in 2D, 3D an
Negative / Null Result ReportOpen accessEngineering
Arjun D. Desai, Francesco Caliva, Claudia Iriondo et al. · 2020 · arXiv
Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a hold-out test set. Simil
Negative / Null Result ReportOpen accessComputer Science
Zhen Xuen Brandon Low, Rory Zhang, Hang Min et al. · 2025 · arXiv
Enlarged perivascular spaces (PVS) are increasingly recognized as biomarkers of cerebral small vessel disease, Alzheimer's disease, stroke, and aging-related neurodegeneration. However, manual segmentation of PVS is time-consuming and subject to moderate inter-rater reliability, while existing automated deep learning models have moderate performance and typically fail to generalize across diverse clinical and research MRI datasets. We adapted MedNeXt-L-k5, a Transformer-inspired 3D encoder-decoder convolutional network, for automated PVS segmentation. Two models were trained: one using a homog
Negative / Null Result ReportOpen accessComputer Science
John T. Holodnak, Allan B. Wollaber · 2021 · arXiv
Multiple techniques for producing calibrated predictive probabilities using deep neural networks in supervised learning settings have emerged that leverage approaches to ensemble diverse solutions discovered during cyclic training or training from multiple random starting points (deep ensembles). However, only a limited amount of work has investigated the utility of exploring the local region around each diverse solution (posterior mode). Using three well-known deep architectures on the CIFAR-10 dataset, we evaluate several simple methods for exploring local regions of the weight space with re
Negative / Null Result ReportOpen accessPhysics
Tim Gould · 2012 · arXiv
The "ACFD-RPA" correlation energy functional has been widely applied to a variety of systems to successfully predict energy differences, and less successfully predict absolute correlation energies. Here we present a parameter-free exchange-correlation kernel that systematically improves absolute correlation energies, while maintaining most of the good numerical properties that make the ACFD-RPA numerically tractable. The "RXH" kernel is constructed to approximate the true exchange kernel via a carefully weighted, easily computable radial averaging. Correlation energy errors of atoms with two t
Negative / Null Result Report
Uchechi Vanessa Alintah-Abel, Francisca Nkachukwu Okeke, Eucharia Chika Enebe · 2025 · British Journal of Multidisciplinary and Advanced Studies
The goal of most countries is the desire to maintain a stable price level of goods and services. This however, appears to be an uphill task given the incidence of subsidy removal that is presently ravaging the developing economies of the…
View details →DOI: 10.37745/bjmas.2022.04253 Negative / Null Result Report
· 2025 · European Journal of Clinical Pharmacy
Pediatric nephrolithiasis is an increasing concern and often requires complete stone clearance due to high recurrence risk. Managing large renal stones (>2 cm), lower calyceal stones (>1 cm), and stones refractory to Extracorporeal Shock…
View details →DOI: 10.61336/ejcp/25-08-441 Negative / Null Result Report
· 2025 · International Journal of Medicine and Medical Research
Lifestyle-related disorders, particularly diabetes, pose a significant global health challenge. Diabetic macular oedema, a microvascular complication, highlights the importance of managing insulin resistance and hyperlipidaemia for optimal…
View details →DOI: 10.63341/ijmmr/1.2025.22 Negative / Null Result Report
Ciana Bowhay, Michael Nattrass · 2026 · NACTA Journal
Undergraduate students in agriculture often struggle to connect theoretical course concepts with real-world agricultural practices. Additionally, with expanding digitalization of professional markets, building a professional online…
View details →DOI: 10.56103/nactaj.v69itt.356 Negative / Null Result ReportOpen accessComputer Science
Xu Ma, Jiajie Zhang, Fujing Xie et al. · 2025 · arXiv
Global localization is essential for autonomous robotics, especially in indoor environments where the GPS signal is denied. We propose a novel WiFi-based localization framework that leverages ubiquitous wireless infrastructure and the OpenStreetMap Area Graph (osmAG) for large-scale indoor environments. Our approach integrates signal propagation modeling with osmAG's geometric and topological priors. In the offline phase, an iterative optimization algorithm localizes WiFi Access Points (APs) by modeling wall attenuation, achieving a mean localization error of 3.79 m (35.3\% improvement over tr
Negative / Null Result ReportOpen accessComputer Science
Sunwoong Yang, Ricardo Vinuesa, Namwoo Kang · 2024 · arXiv
This study addresses the critical challenge of error accumulation in spatio-temporal auto-regressive (AR) predictions within scientific machine learning models by exploring temporal integration schemes and adaptive multi-step rollout strategies. We introduce the first implementation of the two-step Adams-Bashforth method specifically tailored for data-driven AR prediction, leveraging historical derivative information to enhance numerical stability without additional computational overhead. To validate our approach, we systematically evaluate time integration schemes across canonical 2D PDEs be
Negative / Null Result Report
Dorothy Ochs, null null, null null et al. · 2022 · John Heinrichs Scholarly & Creative Activities Day
Purpose: The purpose of this poster is to explore various types of discussion formats in order to find ones that keep the students thoughtfully engaged and motivated. • Methods: The poster will compare and contrast several different types…
View details →DOI: 10.58809/mkeu5488 Negative / Null Result Report
Michelle Storey, null null, null null et al. · 2020 · John Heinrichs Scholarly & Creative Activities Day
Bisphenol A (BPA) is a ubiquitous raw material used in the production of many everyday things such as food packaging and baby bottles. While there have been many studies about the effect that this can have on water and animals, there are…
View details →DOI: 10.58809/vacy9619 Negative / Null Result Report
Bobbie Call, null null, null null et al. · 2020 · John Heinrichs Scholarly & Creative Activities Day
Mental health stigma is prevalent and many people are affected all around the world (Watson, 2002). Stigma often prevents individuals with a mental illness from engaging in typical life routines (Corrigan, 2004). Individuals of ethnic…
View details →DOI: 10.58809/ccrp9120 Negative / Null Result Report
Il‐Young Kim, Scott Schutzler, Nicolaas Deutz et al. · 2014 · The FASEB Journal
A reduction in nitric oxide (NO) bioavailability that impairs peripheral blood flow regulation is a natural consequence of aging. Therefore , we investigated the effect of ingestion of citrulline, the precursor of arginine, on de novo…
View details →DOI: 10.1096/fasebj.28.1_supplement.698.6 Negative / Null Result Report
Nativ Henkin, Ifat Karilker, Sergio L. Kobal et al. · 2023 · Journal of Clinical Medicine
Echocardiographic stress tests are often used to evaluate patients who complain of chest pain. However, some patients fail to reach the target heart rate required for the test to be conclusive (usually defined as 85% of the predicted…
View details →DOI: 10.3390/jcm12144832 Negative / Null Result Report
Thula Cannon Walter-Rittel, Boris Gorodetski, Alexander Hartenstein et al. · 2026 · Current Oncology
Background: The use of [68Ga]Ga-PSMA-PET/CT for prostate cancer (PCa) staging is limited by cost and availability. This study evaluates whether radiomic features from contrast-enhanced (CE) CT can predict PSMA-positive lymph nodes (LNs) as…
View details →DOI: 10.3390/curroncol33030146 Negative / Null Result Report
Xianglong Tan, Matteo Pellegrini, Su Yon Jung · 2026 · Clinical Epigenetics
Abstract Background Epigenetic aging bridges the gap between biological and chronological age by exploiting DNA methylation (DNAm) patterns. Over the past decade, successive DNAm-based clocks have been introduced, beginning with the…
View details →DOI: 10.1186/s13148-026-02102-3 Negative / Null Result Report
Noble Charles, Nilkanth Pal, Jeevan Vernekar · 2025 · African Journal of Urology
Abstract Background The radiologist faces the dilemma of characterizing adrenal lesions, especially in oncology patients, as this finding can alter the patient’s management and prognosis. The objectives of this study were (1) to evaluate…
View details →DOI: 10.1186/s12301-025-00499-6 Negative / Null Result Report
Bahadır Kartal, Mehmet Berksun Tutan, Fatih Şahin et al. · 2024 · Hitit Medical Journal
Objective: Gastric cancer surgery, including curative and palliative procedures, is crucial for managing gastric cancer. Accurate assessment of nutritional status is essential for risk stratification and improving patient outcomes. This…
View details →DOI: 10.52827/hititmedj.1516777 Negative / Null Result Report
Emma Zaal, John Hoeks, Yfke Ongena · 2025 · Journal of Survey Statistics and Methodology
Abstract Social Desirability Bias (SDB), providing a favorable image of oneself in self-reports, is a persistent problem in survey research on sensitive topics. However, face-saving approaches appear promising in discouraging SDB.…
View details →DOI: 10.1093/jssam/smaf017 