Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor... by Alkinoos Athanasiou, Chrysa Lithari, Konstantina Kalogianni, Manousos A. Klados, Panagiotis D. Bamidis

“…Sensorimotor cortex is activated similarly during motor execution and motor imagery. The study of functional connectivity networks (FCNs) aims at successfully modeling the dynamics of information flow between cortical areas. …”
Get full text

Substitution of non-forage fibre sources for cereal grains and molasses in calf starter on performance and development of ruminal function by D.B. Vagnoni, C. Sousa, M.A. Messman

Get full text

New source of cellulase production using a metagenomic technique by Safaa M. Ali, Nadia A. Soliman

“…The soil metagenome is an affluent source for the discovery of new natural products. …”
Get full text

The aftermath of trauma on resting state source-level MEG microstate dynamics by Massimo Bertoli, Pierpaolo Croce, Filippo Zappasodi, Rosalia Di Matteo, Federica Vellante, Mauro Pettorruso, Giovanni Martinotti, Marcella Brunetti

“…Resilience may arise from successful integration of cognitive and sensorimotor processes, detectable as distinct patterns of brain dynamics during rest.…”
Get full text

Distributed Decision Making for Electromagnetic Radiation Source Localization Using Multi-Agent Deep Reinforcement Learning by Jiteng Chen, Zehui Zhang, Dan Fan, Chaoqun Hou, Yue Zhang, Teng Hou, Xiangni Zou, Jun Zhao

“…The detection and localization of radiation sources in urban areas present significant challenges in electromagnetic spectrum operations, particularly with the proliferation of small UAVs. …”
Get full text

Detection, Parameter Estimation and Direction Finding of Periodic Pulse Signals by V. B. Manelis, I. S. Faustov, V. A. Kozmin

“…Simple-to-implement algorithms for detecting periodic pulse signals, evaluating their parameters, and direction finding of the source have been developed. …”
Get full text

PA-YOLO-Based Multifault Defect Detection Algorithm for PV Panels by Wang Yin, Zhao Jingyong, Xie Gang, Zhao Zhicheng, Hu Xiao

“…For the occlusion problem of dense targets in the dataset, we introduce a repulsive loss function, which successfully reduces the occurrence of false detection situations. …”
Get full text

Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection by Ali Nizam, Ertugrul Islamoglu, Omer Kerem Adali, Musa Aydin

“…Although code embedding-based systems have been successfully applied to various source code analysis tasks, further research is required to enhance code embedding for better code analysis capabilities, aiming to surpass the performance and functionality of static code analysis tools. …”
Get full text

A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys by Letizia Lamperti, Olivier François, David Mouillot, Laëtitia Mathon, Théophile Sanchez, Camille Albouy, Loïc Pellissier, Stéphanie Manel

“…In the regional analysis of Mediterranean eDNA samples, our method successfully identifies different pools, allowing the detection of not only geographic gradients but also human‐induced gradients corresponding to protection levels. …”
Get full text

Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs by Yan LI, Weizhong QIANG, Zhen LI, Deqing ZOU, Hai JIN

“…In recent years, software vulnerabilities have been causing a multitude of security incidents, and the early discovery and patching of vulnerabilities can effectively reduce losses.Traditional rule-based vulnerability detection methods, relying upon rules defined by experts, suffer from a high false negative rate.Deep learning-based methods have the capability to automatically learn potential features of vulnerable programs.However, as software complexity increases, the precision of these methods decreases.On one hand, current methods mostly operate at the function level, thus unable to handle inter-procedural vulnerability samples.On the other hand, models such as BGRU and BLSTM exhibit performance degradation when confronted with long input sequences, and are not adept at capturing long-term dependencies in program statements.To address the aforementioned issues, the existing program slicing method has been optimized, enabling a comprehensive contextual analysis of vulnerabilities triggered across functions through the combination of intra-procedural and inter-procedural slicing.This facilitated the capture of the complete causal relationship of vulnerability triggers.Furthermore, a vulnerability detection task was conducted using a Transformer neural network architecture equipped with a multi-head attention mechanism.This architecture collectively focused on information from different representation subspaces, allowing for the extraction of deep features from nodes.Unlike recurrent neural networks, this approach resolved the issue of information decay and effectively learned the syntax and semantic information of the source program.Experimental results demonstrate that this method achieves an F1 score of 73.4% on a real software dataset.Compared to the comparative methods, it shows an improvement of 13.6% to 40.8%.Furthermore, it successfully detects several vulnerabilities in open-source software, confirming its effectiveness and applicability.…”
Get full text

A powerful molecular marker to detect mutations at sorghum LOW GERMINATION STIMULANT 1 by Adedayo O. Adeyanju, Patrick J. Rich, Gebisa Ejeta

“…The LGS1 marker is useful for both detecting sources of lgs1 and introgressing Striga resistance into new genetic backgrounds.…”
Get full text

Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading by Katarzyna PANASIUK, Krzysztof DUDZIK, Grzegorz HAJDUKIEWICZ

“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
Get full text

GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation by Jialin Yue, Tianyuan Yao, Ruining Deng, Siqi Lu, Junlin Guo, Quan Liu, Juming Xiong, Mengmeng Yin, Haichun Yang, Yuankai Huo

“…Artificial intelligence (AI) has demonstrated significant success in automating the detection of glomeruli—key functional units of the kidney—from whole slide images (WSIs) in kidney pathology. …”
Get full text

Let ants find them: Using ants as eDNA samplers for detecting the invasive spotted lanternfly by Wei-Jiun Lin, Fang-Ling Chloe Liu, Lucie Cho, Chin-Cheng Scotty Yang

“…Compared to non-ant insects, ants exhibited higher SLF DNA concentrations, suggesting that honeydew ingestion serves as the primary eDNA source. These findings demonstrate that ants can function as efficient SLF eDNA samplers, providing a scalable and cost-effective alternative to existing SLF detection methods.…”
Get full text

Hybrid Deep Neural Network Optimization with Particle Swarm and Grey Wolf Algorithms for Sunburst Attack Detection by Mohammad Almseidin, Amjad Gawanmeh, Maen Alzubi, Jamil Al-Sawwa, Ashraf S. Mashaleh, Mouhammd Alkasassbeh

“…The strength of DNNs is derived from their ability to model complex functions and to improve detection engines through deeper architecture. …”
Get full text

Detection and classification of hypertensive retinopathy based on retinal image analysis using a deep learning approach by Bambang Krismono Triwijoyo, Ahmat Adil, Muhammad Zulfikri

“…Methods: This research utilizes secondary data, specifically a retinal image dataset from the open-source Messidor database. This database comprises 1200 retinal images, each measuring 1440 × 940 pixels. …”
Get full text

A Method for Extracting Features of the Intrinsic Mode Function’s Energy Arrangement Entropy in the Shaft Frequency Electric Field of Vessels by Xiaoguang Ma, Zhaolong Sun, Runxiang Jiang, Xinquan Yue, Qi Liu

“…To address the challenge of detecting low-frequency electric field signals from vessels in complex marine environments, a vessel shaft frequency electric field feature extraction method based on intrinsic mode function energy arrangement entropy values is proposed, building upon a scaled model. …”
Get full text

Patient-derived esophageal adenocarcinoma organ chip: a physiologically relevant platform for functional precision oncology by Sanjima Pal, Elee Shimshoni, Salvador Flores Torres, Mingyang Kong, Kulsum Tai, Veena Sangwan, Nicholas Bertos, Swneke Donovan Bailey, Julie Bérubé, Donald E. Ingber, Lorenzo Ferri

Get full text

Yarn-electrospun PVDF-HFP/CNC smart textiles for self-powered sensor in wearable electronics by Jiawei Chen, Subhamoy Mahajan, Manisha Gupta, Cagri Ayranci, Tian Tang

“…The success of developing such sensor-integrated touchscreen gloves paves new avenues for human-technology interactions, highlights the dual functionality of these yarns as power sources and sensors, and represents a milestone in broadening the applications of wearable technologies.…”
Get full text

Wearable MXene-enhanced organic Bio-FET paper patch for glucose detection in sweat with pH and temperature calibration by Milad Farahmandpour, Zoheir Kordrostami

Get full text