Optimized Temporal Interference Stimulation Based on Convex Optimization: A Computational Study by Chao Geng, Yang Li, Long Li, Xiaoqi Zhu, Xiaohan Hou, Tian Liu

“…Performance analysis of CVXTI shows superior results compared to other methods, particularly in deep brain regions. Subject variability analysis on four individuals highlights the necessity of customized stimulus optimization. …”
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HEE-SegGAN: A holistically-nested edge enhanced GAN for pulmonary nodule segmentation. by Yong Wang, Seri Mastura Mustaza, Mohammad Syuhaimi Ab-Rahman, Siti Salasiah Mokri

“…However, this task remains challenging due to the complex morphological variability of pulmonary nodules in CT images and the limited availability of well-annotated datasets. …”
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Ionospheric Correction Based on Ingestion of Global Ionospheric Maps into the NeQuick 2 Model by Xiao Yu, Chengli She, Weimin Zhen, Nava Bruno, Dun Liu, Xinan Yue, Ming Ou, Jisheng Xu

“…The accuracy of TEC prediction can be improved further through performing a four-coefficient function expression of Az versus MODIP. …”
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Smart Fermentation Technologies: Microbial Process Control in Traditional Fermented Foods by Chong Shin Yee, Nur Asyiqin Zahia-Azizan, Muhamad Hafiz Abd Rahim, Nurul Aqilah Mohd Zaini, Raja Balqis Raja-Razali, Muhammad Ameer Ushidee-Radzi, Zul Ilham, Wan Abd Al Qadr Imad Wan-Mohtar

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Developing CGMap: Characterizing Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes by Shuzhen Bai, Chu Lin, Xiaoling Cai, Suiyuan Hu, Jing Wu, Ling Chen, Wenjia Yang, Linong Ji

“…However, glucose variability decreased with increased BMI. Meanwhile, greater glycemic variability was associated with worse islet function, higher baseline glucose level, and higher hemoglobin.…”
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Elucidating Genotypic Variation in Quinoa via Multidimensional Agronomic, Physiological, and Biochemical Assessments by Samreen Nazeer, Muhammad Zubair Akram

“…The results revealed that significant variation was observed across all measured parameters, highlighting the diverse adaptive strategies and functional capacities among the tested genotypes. More specifically, genotypes Q4, Q11, Q15, and Q126 demonstrated superior agronomic potential and canopy-level physiological efficiencies, including high biomass accumulation, low infrared canopy temperatures and sustained NDVI values. …”
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XPolypNet: A U-Net-Based Model for Semantic Segmentation of Gastrointestinal Polyps With Explainable AI by Arjun Kumar Bose Arnob, Muhammad Mostafa Monowar, Md. Abdul Hamid, M. F. Mridha

“…Although the model exhibited satisfactory performance, it still faced challenges regarding boundary misclassification and reduced efficacy in datasets with high variability. The next steps of this research will focus on domain adaptation and integration of additional modalities to enhance generalizability. …”
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Validation of an interferon-gamma enzyme-linked immunosorbent spot assay to evaluate cell-mediated immunity against severe acute respiratory syndrome coronavirus 2 by Yunhwa Kim, Eun-Jeong Jang, Ji-Young Hwang, Kyung-Min Lee, Sivilay Xayaheuang, Seok-Tae Choi, Hosun Park

“…The lack of a global standardized protocol and the high variability of intra- and inter-assay precision of the T-cell response made it difficult to compare T-cell assay results with those of other laboratories. …”
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Specific nature of the integrative (complex) effect of environmental factors on hazelnut cultivars in the Russian humid subtropics by T. D. Besedina, A. P. Boyko, Ts. V. Tutberidze, N. S. Kiseleva

“…The expediency of the crop’s large-scale cultivation calls for measuring the parameters of agroclimatic indicators, ranging in variability, intensity, and duration of their impact. …”
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Data-driven modeling and regression analysis on ship resistance of in-service performance by Daehyuk Kim, Shin Hyung Rhee

“…The analysis of added resistance due to waves shows significant, but sometimes inconsistent, transfer function coefficients, suggesting simpler model structures could be more effective. …”
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Automatic detection of optic canal fractures and recognition and segmentation of anatomical structures in the orbital apex based on artificial intelligence by Yu-Lin Li, Yu-Hao Li, Mu-Yang Wei, Guang-Yu Li

“…Timely and accurate diagnosis and treatment are crucial for preserving visual function. However, diagnosing OCF can be challenging for inexperienced clinicians due to atypical OCF changes in imaging studies and variability in optic canal anatomy. …”
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Strong Amplitude Modulation of Hard-band X-Ray Quasiperiodic Oscillation with Soft-band Flux in RE J1034+396 by Ruisong Xia, Hao Liu, Yongquan Xue

“…They are highly correlated, with an average cross-correlation function (CCF) peak coefficient of 0.61 and a lag of approximately 3 ks. …”
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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

“…We investigated the impact of using different feature extraction (spectro‐temporal measurements, linear and Mel‐frequency cepstral coefficients (MFCC), as well as highly comparative time‐series analysis) and classification methods (discriminant function analysis, neural networks, random forests (RF), and support vector machines) on the consistency of caller identity classification accuracy across 16 mammalian datasets. …”
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Advancing geohazard risk assessment – A digital tool for steep slope management by Cherry Rose Godes, One-Bin Lim, Shanelle Aira Rodrigazo, Yongseong Kim, Yongjin Kim, Seungjoo Lee, Jaeheum Yeon

“…Growing climatic variability and rapid urbanization have increased landslide occurrences, posing significant challenges for risk assessment. …”
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Which Metrics Can I Monitor? Test-Retest Reliability of Countermovement Jump and Countermovement Rebound Jump Force-Time Metrics in Youth Soccer Players In-Season by Andrew Badby, Paul Comfort, Nicholas Ripley, Matthew Cuthbert, Francisco Robles-Palazón, Peter Mundy, John McMahon

“…Objective measures provide the most effective means of monitoring the magnitude and time course of changes in neuromuscular function (NMF) resulting from physical activity if measurements are repeatable (reliability). …”
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A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study. by Patrizio Barca, Fabio Paolicchi, Giacomo Aringhieri, Federica Palmas, Daniela Marfisi, Maria Evelina Fantacci, Davide Caramella, Marco Giannelli

“…The analysis of several quality indices showed a non-negligible variability in head CT imaging capabilities across different scanners/acquisition protocols. …”
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Compositional and nutritional value of lupin cultivars: Identifying high-protein seeds for enhanced protein isolate production and phytochemical valorisation by Pau Taberner-Pibernat, Albert Ribas-Agustí, Gisela Quinteros, Gerard Sabeña, Miguel López-Gómez, Rubén Domínguez-Valencia, Ricard Bou

“…The findings revealed significant inter- and intra-species variability in protein, total dietary fibre, and fat content among the studied cultivars. …”
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Application of Post-Occupancy Evaluation in the Design of Collegiatae Educational Space: (Case study: Faculty of Arts and Architecture, Islamic Azad University-Tehran South Branch) by Reza Naghdbishi, Zeinab Gohari

“…This analysis identified the relationship between research variables and evaluated their impact on the design. …”
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Optimizing Load Frequency Control of Multi-Area Power Renewable and Thermal Systems Using Advanced Proportional–Integral–Derivative Controllers and Catch Fish Algorithm by Saleh A. Alnefaie, Abdulaziz Alkuhayli, Abdullah M. Al-Shaalan

“…Additionally, by contrasting the performance of the PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers, the efficiency of the CFA is confirmed. Additionally, a sensitivity analysis that considers simultaneous modifications of the frequency bias coefficient (B) and speed regulation (R) within a range of ±25% validates the efficacy and dependability of the suggested CFA-tuned PI(1+DD). …”
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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…One important modular component of msAbs is the single-chain variable fragment (scFv). Despite the exquisite specificity and affinity of these scFv modules, their relatively poor thermostability often hampers their development as a potential therapeutic drug. …”
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