Pedigree reconstruction based on genotype data in chickens by Yan Zhou, Qunpu Wang, Qiulian Wang, Yiyuan Yan, Guangqi Li, Guiqin Wu, Ning Yang, Chaoliang Wen

“…Here, to reconstruct pedigrees in chickens, we detected high-quality SNPs from 2866 parent–offspring pairs and calculated their genomic relationship and identity by descent (IBD). …”
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Parameter Analysis of Pile Foundation Bearing Characteristics Based on Pore Water Pressure Using Rapid Load Test by Jing-Jie Su, Xue-Liang Zhao, Qing Guo, Wei-Ming Gong, Yu-Chen Wang, Tong-Xing Zeng

“…A numerical model incorporating the damping coefficient and permeability coefficient is developed, yielding the time history features of load, displacement, and acceleration. The findings indicate that (1) the long pulse vibration equation, predicated on dynamic effects, aligns more closely with the actual bearing capacity of pile foundations than traditional detection theory; (2) in the rapid load test method, the maximum load applied to sand pile foundations occurs prior to peak displacement, while the ultimate bearing capacity, after accounting for inertial forces, corresponds to the maximum displacement value; (3) the permeability coefficient significantly influences the ultra-static pore water pressure, and the testing error regarding the bearing capacity of low permeability sand pile foundations using the rapid loading method is elevated.…”
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THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

“…In radiology, AI aims to assist with image analysis and interpretation, potentially reducing human error and alleviating the radiological workload. …”
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Using fuzzy decision support to create a positive mental health environment for preschoolers by Xinyue Li

“…The dataset used in this study may lack sufficient diversity, limiting the generalizability of the findings across different socio-economic, cultural, and demographic groups. …”
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Enhancing Speaker Recognition with CRET Model: a fusion of CONV2D, RESNET and ECAPA-TDNN by Pinyan Li, Lap Man Hoi, Yapeng Wang, Xu Yang, Sio Kei Im

“…Our model performs the best on the VoxCeleb2 dataset with 1024 channels, achieving an accuracy of 0.97828, an equal error rate (EER) of 0.03612 on the VoxCeleb1-O dataset, and a minimum detection cost function (MinDCF) of 0.43967. …”
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Practice patterns in pediatric myopia management: Insights from a 2023 survey among Indian ophthalmologists by Lav Kochgaway, Anuradha Chandra, Ipsita Basu, Debarpita Chaudhury, Jitendra Jethani, Arup Bhaumik

“…The recommended mean age for a child's first eye checkup is 3 years, underscoring the importance of early detection. Refractive error thresholds for prescribing spectacles are set at 3.0 D for infants, 2.0 D for preschool children, and 1.0 D for school-going children older than 3 years. …”
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Implementation of MF block in CNN for advanced REB fault diagnosis by M. Pandiyan, Narendiranath Babu T.

“…Statistical significance tests and error bars validate the robustness of the model’s performance. …”
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Association of Conventional Cardiovascular Risk Factors with Carotid Atherosclerosis Prevalence in General Population by V. S. Kaveshnikov, V. N. Serebryakova, I. A. Trubacheva, S. A. Shalnova

“…Study of relationships was carried out with logistic regression analysis. The error probability of less than 5% was considered statistically significant.Results. …”
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Representation Learning for Place Recognition Using MIMO Radar by Prashant Kumar Rai, Nataliya Strokina, Reza Ghabcheloo

“…During runtime, for place recognition and loop closure detection, cosine similarity is applied to query scan feature representation and the database to find the closest matches. …”
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Estimating individual tree DBH and biomass of durable Eucalyptus using UAV LiDAR by Ning Ye, Euan Mason, Cong Xu, Justin Morgenroth

“…This study aimed to estimate individual tree dimensions (diameter at breast height, DBH) and above-ground biomass (AGB) for Eucalyptus globoidea and E. bosistoana using light detection and ranging (LiDAR) data acquired by an unpiloted aerial vehicle (UAV). …”
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Robust Tracking Method for Small and Weak Multiple Targets Under Dynamic Interference Based on Q-IMM-MHT by Ziqian Yang, Hongbin Nie, Yuxuan Liu, Chunjiang Bian

“…Furthermore, the algorithm utilizes Support Vector Machines (SVMs) for anomaly detection and trajectory recovery, thereby enhancing the accuracy of data association and the overall robustness of the system. …”
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An Investigation of Interpolation Techniques to Generate 2D Intensity Image From LIDAR Data by Imran Ashraf, Soojung Hur, Yongwan Park

“…Light detection and ranging (LIDAR) has become a part and parcel of ongoing research in autonomous vehicles. …”
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Sensor-Based Gait Analysis: A Comparative Study of Ultrasonic and Laser Sensors for Gait Monitoring in Rollator-Assisted Walking by Ivan Omeko, Stefan Twieg, Martin Obert

“…A crucial aspect of this system is the detection and correction of the user's posture of legs. …”
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An eco-friendly chemometrics assisted UV spectrophotometric method for simultaneous determination of sofosbuvir, simeprevir and ledipasvir in pharmaceuticals by Adil Alshehri, Ali Alqahtani, Abdulrhman Alsayari, Ahmed A. Almrasy

“…SRACLS models demonstrated superior analytical performance with lower detection limits (0.5171, 0.5175, 0.2950 μg/mL), higher precision (relative bias corrected mean square error of prediction, RBCMSEP: 0.1481–0.2509%), and better predictive capability (relative root mean square error of prediction, RRMSEP: 1.0285%, 1.2668%, 1.8933%) compared to CRACLS models (RRMSEP: 3.0655%, 1.9264%, 2.7201%). …”
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Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…Assessment metrics, such as the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE), emphasize the MLP model’s exceptional performance. …”
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Impact evaluation of a digital health platform empowering Kenyan women across the pregnancy-postpartum care continuum: A cluster randomized controlled trial. by Rajet Vatsa, Wei Chang, Sharon Akinyi, Sarah Little, Catherine Gakii, John Mungai, Cynthia Kahumbura, Anneka Wickramanayake, Sathyanath Rajasekharan, Jessica Cohen, Margaret McConnell

“…A limitation of our study was that outcomes were self-reported, and the study was not powered to detect effects on health outcomes.<h4>Conclusions</h4>Digital health tools indicate promise in addressing shortcomings in pregnant and postpartum women's health care, amidst systems that do not reliably deliver a minimally adequate standard of care. …”
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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…Ultimately, the findings showed that the input of combined features significantly reduced the regression error for the mixed gas.…”
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Comparative evaluation of sequencing technologies and primer sets for mouse gut microbiota profiling by Aleksandra Strokach, Polina Zoruk, Daria Boldyreva, Maxim Morozov, Evgenii Olekhnovich, Vladimir Veselovsky, Vladislav Babenko, Oksana Selezneva, Natalia Zakharevich, Andrey Larin, Severina Koldman, Severina Koldman, Vail Koldman, Vail Koldman, Maya Odorskaya, Roman Yunes, Vladislav Pavlov, Anna Kudryavtseva, Valeriy Danilenko, Ksenia Klimina, Ksenia Klimina

“…This study systematically evaluates these factors in mouse gut microbiota analysis, comparing 16S rRNA gene sequencing and metagenome sequencing (MS) across both platforms.ResultsOur findings highlight the critical influence of primer selection on 16S rRNA sequencing results, with certain primer combinations detecting unique taxa that others miss. …”
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An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms by Ahmad Almadhor, Stephen Ojo, Thomas I. Nathaniel, Shtwai Alsubai, Abdullah Alharthi, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…Conventional Schizophrenia diagnosis techniques are time- consuming and prone to error. The study proposes a novel automated technique for diagnosing Schizophrenia based on electroencephalogram (EEG) sensor data, aiming to enhance interpretability and prediction performance.MethodsThis research utilizes Deep Learning (DL) models, including the Deep Neural Network (DNN), Bi-Directional Long Short-Term Memory-Gated Recurrent Unit (BiLSTM- GRU), and BiLSTM with Attention, for the detection of Schizophrenia based on EEG data. …”
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A Flow-Speed Model for Motorways in England: Analysis Under Various Weather Conditions by Ye Liu, Haibo Chen, Chuhan Yin, Vivi Michalaki, Phillip Proctor, Gavin Rowley, Xiaowei Wang, Hongyuan Wei

“…Further analysis of extensive data over a wider space and time is required to test the transferability of these findings to other contexts.…”
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