Multi-Person Fall Detection Using Data Assimilation Method With Kalman Filter by Jinmo Yang, Ye Jin Jin, R. Young Chul Kim

“…Fall detection is an essential technology for ensuring the safety of elderly individuals, as falling accidents are critical and can cause significant functional damage in old age. …”
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Harnessing polydiacetylene (PDA): A review of structural mechanics and infectious disease detection by Soumendu Patra, Harshita Shand, Sayan Ghosal, Suvankar Ghorai

“…These biosensors can also be functionalized with particular capture agents, such as antibodies or nucleic acid probes, to selectively bind and detect the target analytes. …”
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Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

“…Key findings are summarized in a comparative matrix, highlighting trends, gaps, and inconsistencies across publication sources. This review identifies critical research gaps—including the underuse of hybrid models, lack of benchmark datasets, and limited integration between detection and control layers—and offers concrete recommendations for future research. …”
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Detection of Elementary White Mucosal Lesions by an AI System: A Pilot Study by Gaetano La Mantia, Federico Kiswarday, Giuseppe Pizzo, Giovanna Giuliana, Giacomo Oteri, Mario G. C. A. Cimino, Olga Di Fede, Giuseppina Campisi

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Allelic diversity of the <i>FaOMT</i> gene (mesifurane biosynthesis) in promising strawberry cultivars and selected forms developed at the I.V. Michurin Federal Science Center by A. S. Lyzhin, I. V. Luk’yanchuk

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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…In addition, the superiority of the proposed fault detection and classification approaches using ML tools was assessed by comparing the detection and classification efficiency through some statistical performance parameter comparisons among the classifiers.…”
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Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential by Miguel A. Ramallo-Luna, Sara Gonzalez-Torre, Álvaro Rodríguez-Mora, Gabriel G. de la Torre

“…Introduction: The increasing use of drones in both military and civilian applications underscores the critical need for the proper selection and training of pilots. Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. …”
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Electronic–Oxygen Synergy at Ca-Fe Dual-Metal Interfaces for Selective Syngas Regulation in Biomass Chemical Looping Gasification by Yijie Wang, Jiajie Li, Sitao Zhu, Michael Hitch

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Effect of cochlear implant surgery on vestibular function: meta-analysis study by Iman Ibrahim, Sabrina Daniela da Silva, Bernard Segal, Anthony Zeitouni

“…No significant effect of CI surgery was detected in HIT, posturography, or DHI scores. Overall, the clinical effect of CI surgery on the vestibular function was found to be insignificant. …”
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Automatic Recognition of Authors Identity in Persian based on Systemic Functional Grammar by Fatemeh Soltanzadeh, Azadeh Mirzaei, Mohammad Bahrani, Shahram Modarres Khiabani

“…First, a corpus composed of documents written by seven contemporary Iranian authors was collected. Second, a list of function words was extracted from the corpus. Moreover, conjunction, modality and comment adjunct system networks were applied to form a lexicon using linguistics resources. …”
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Automated identification of soil functional components based on NanoSIMS data by Yahan Hu, Johann Maximilian Zollner, Carmen Höschen, Martin Werner, Steffen A. Schweizer

“…The tool is provided as an open-source software toolbox (NanoT). In addition, a two-step unsupervised segmentation method was developed to identify soil functional components based on NanoSIMS analyses. …”
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Quantifying Truthfulness: A Probabilistic Framework for Atomic Claim-Based Misinformation Detection by Fahim Sufi, Musleh Alsulami

“…This paper addresses this gap by proposing a novel probabilistic framework that decomposes complex assertions into semantically atomic claims and computes their veracity through a structured evaluation of source credibility and evidence frequency. Each atomic unit is matched against a curated corpus of 11,928 cyber-related news entries using a binary alignment function, and its truthfulness is quantified via a composite score integrating both source reliability and support density. …”
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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. …”
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Social Network Community Detection by Combining Self-Organizing Maps and Genetic Algorithms by Mehdi Ellouze

“…To this end, many research works in the literature offer users some tools that can help them take advantage of this mine of information. Community detection is one of these tools and aims to detect a set of entities that share some features within a social network. …”
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YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

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Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images by Resky Adhyaksa, Bedy Purnama

“…The training and testing phases utilized an 80:20 split of the data, employing binary cross-entropy as the loss function and the Adam optimizer for efficient weight updates. …”
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Video Analysis and Frame Prediction Based on Improved Object Detection and ConvGRU by Xijuan Wang, Ru Chen

“…The loss function and average accuracy mean have been improved, with a maximum detection accuracy of 0.947. …”
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First Detection of Low-frequency Striae in Interplanetary Type III Radio Bursts by Vratislav Krupar, Eduard P. Kontar, Jan Soucek, Lynn B. Wilson III, Adam Szabo, Oksana Kruparova, Hamish A. S. Reid, Mychajlo Hajos, David Pisa, Ondrej Santolik, Milan Maksimovic, Jolene S. Pickett

“…By combining high-resolution radio observations with well-calibrated in situ electron velocity distribution function data from the Wind spacecraft, we characterized the plasma properties of the burst source region near 0.32 au. …”
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A Comprehensive Approach for Detecting and Handling MitM-ARP Spoofing Attacks by Standy Oei, Yohanes Suyanto, Reza Pulungan

“…In the host, we employ a combination of ping Round-Trip Time (RTT) anomaly detection, the SendARP function, static entry, and ping confirmation to detect and mitigate attacks. …”
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Near-source wastewater surveillance of SARS-CoV-2, norovirus, influenza virus and RSV across five different sites in the UK. by Jay C Bullen, Mina Mohaghegh, Fatima Tahir, Charlotte Hammer, Jacob Sims, Frederico Myers, Lucas Eisinger, Ali Reza Kasmati, Claire F Trant

“…The key findings are (1) near-source wastewater detections were linked to local events (staff sickness, enhanced cleaning, changing populations); (2) wastewater detections decreased in the order norovirus GII > norovirus GI > SARS-CoV-2 ≈ influenza A ≈ RSV A > influenza B ≈ RSV B; (3) correlation between near-source wastewater data and national surveillance data increases as a function of catchment size and viral prevalence (examples include the SARS-CoV-2 BA.4/BA.5 variant peak at a museum and wastewater tracking the winter norovirus season); (4) strong weekday periodicity in near-source wastewater SARS-CoV-2 detections, with the correlation against COVID-19 case numbers increasing when modelling variable lag times between faecal shedding onset and clinical diagnosis (R2 = 0.45 increases to 0.84-0.86); (5) a log-linear relationship between the frequency of wastewater SARS-CoV-2 detection and log(catchment size⋅viral prevalence) (R2 = 0.6914-0.9066). …”
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