Efficiency-Centered Fault Diagnosis of In-Service Induction Motors for Digital Twin Applications: A Case Study on Broken Rotor Bars by Adamou Amadou Adamou, Chakib Alaoui

“…The uninterrupted operation of induction motors is crucial for industries, ensuring reliability and continuous functionality. To achieve this, we propose an innovative approach that utilizes an efficiency model-based digital shadow system for in situ failure detection and diagnosis (FDD) in induction motors (IMs). …”
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Cross-dimensional adaptivity research on a 3D earth observation data cube model by Yu Jinsongdi, Cui Zhanying, Baumann Peter, Tong Ruiju, Wei Dandan, Luo Yuan

“…However, a significant challenge in their utilization is the interoperability among EO data cubes with varying dimensionalities. …”
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Optimizing SVC placement for enhanced voltage stability using a novel index and hybrid ABC-PSO algorithm by Hafizur Rahman, Roman Mia, Mustafizur Rahman, Md. Faiyaj Ahmed Limon, Md. Shahid Iqbal, Md. Fahad Jubayer, Md. Rabiul Karim, Md. Janibul Alam Soeb

“…It integrates FVSI with a Novel Collapse Prediction Index (NCPI) with the help of a switching function. Unlike conventional indices such as the Fast Voltage Stability Index (FVSI) and Line Stability Index (Lmn), which rely predominantly on reactive power-based predictions, MCPI relies on both active and reactive power, providing an improved indication of system stability and is utilized as the objective function for the optimal placement of SVCs. …”
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Investigating SMYD3 role during oocyte maturation in a 3D follicle-enclosed oocyte in vitro model in sheep by Chiara Camerano Spelta Rapini, Alessia Peserico, Chiara Di Berardino, Giulia Capacchietti, Camila Rojo-Fleming, Andrada-Ioana Damian-Buda, Irem Unalan, Aldo Roberto Boccaccini, Valentina Grossi, Mauro Mattioli, Barbara Barboni

“…This study aimed to elucidate the function of SMYD3 in regulating oocyte meiotic progression and developmental competence using sheep as a mono-ovulatory model.ResultsUtilizing a 3D follicle-enclosed in vitro maturation (FEO-IVM) system, the study examined the impact of SMYD3 inhibition on oocyte maturation within Early Antral follicles In the absence of human chorionic gonadotropin oocytes remained arrested at the germinal vesicle (GV) stage. …”
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Estimation of Positive‐, Negative‐, and Zero‐Sequence Current and Voltage Phasors of UIPC VSCs for Short‐Circuit Faults in Transmission Lines by Babak Bahadori, Ali Nahavandi, Mahyar Abasi

“…ABSTRACT FACTS devices, functioning as controlled series voltage and parallel current source converters in transmission lines, can enhance network flexibility. …”
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The association between serum albumin–globulin ratio and overactive bladder in American adults: a cross-sectional study by Yuan-Zhuo Du, Jia-Hao Liu, Fu-Chun Zheng, Qiang Zhou, Ju Guo

“…Abstract Objectives The albumin–globulin ratio (AGR) is considered an important indicator reflecting an individual’s immune function and nutritional status, and it is closely associated with various health conditions. …”
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Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

“…By utilizing the 1-norm and ∞-norm to characterize the uncertainty sets between sources and loads, this strategy effectively minimizes operational costs while ensuring robust performance. …”
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Research and Application of A Comprehensive Monitoring Platform for Coal Conveyor Gallery Based on Multi-Dimensional Information Fusion by CUI Xiaohui, MA Xiaodong, LIU Mingsheng, CHEN Xiaodong, ZHANG Hanqing

“…It encompasses functions such as accessing multi-source heterogeneous data, load balancing, intelligent analysis, and decision fusion based on multiple data models. …”
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A MODEL FOR ASSESSING SHIPPING SAFETY WITHIN PROJECT-ORIENTATED RISK MANAGEMENT BASED ON HUMAN ELEMENT by Svitlana ONYSHCHENKO, Yuriy BYCHKOVSKY, Oleksiy MELNYK, Oleg ONISHCHENKO, Martin JURKOVIČ, Viacheslav RUBSKYI, Kostiantyn LIASHENKO

“…The proposed methodology can effectively identify, analyse and manage safety risks, which can contribute to the success and safety of shipping projects. The study also discusses the importance of dividing the crew into functional groups based on the operations performed, which helps to better identify the safety risk for each group. …”
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Reactualizing Classical Islamic Power: Reinterpreting Al-Mawardi in Post-Reform Indonesian Democracy by Jafar Ahmad

“…Al-Mawardi, through the institution of ahl al-halli wa al-‘aqdi, provides a theoretical foundation for community representation in the leadership selection process, which functionally resembles elections in a democratic system. …”
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Antalya Kaleiçi and Its Surroundings on the 1905 Maps by Evren Dayar

“…This article aims to evaluate two maps of Antalya prepared on March 27, 1905, utilizing archival documents, inscriptions, and various visual sources. …”
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Machine learning-based model for CD4+ conventional T cell genes to predict survival and immune responses in colorectal cancer by Zijing Wang, Zhanyuan Sun, Hengyi Lv, Wenjun Wu, Hai Li, Tao Jiang

“…The immunological responses to cancer heavily rely on the function of CD4Tconv. Despite this critical role, prognostic studies on CRC-related CD4Tconv remain insufficient. …”
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Eeg-based detection of epileptic seizures in patients with disabilities using a novel attention-driven deep learning framework with SHAP interpretability by Tawfeeq Shawly, Ahmed A. Alsheikhy

“…We articulate the mathematical characteristics of feature selection driven by NAM, delineate the convergence attributes of the loss function, and present measures of explainability through Shapley Additive Explanations (SHAP). …”
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µID-TIMS: spatially resolved high-precision U–Pb zircon geochronology by S. Markovic, J.-F. Wotzlaw, D. Szymanowski, J. Reuteler, P. Zeng, C. Chelle-Michou

“…The accuracy and precision of <span class="inline-formula">µ</span>ID-TIMS dates for zircon of any given age depend, as for non-microsampled zircon, on the available mass of U and radiogenic Pb – both a function of sample size. Our accompanying open-source code can aid researchers in estimating the necessary microsample size needed to obtain accurate dates at precision sufficient to resolve the processes under study. …”
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A Multiscale Convolution SAR Image Target Recognition Method Based on Complex-Valued Neural Networks by Guangyu Hou, Zhihui Xin, Guisheng Liao, Penghui Huang, Yuhao Huang, Rui Zou

“…Recent advances in deep learning have driven significant success in synthetic aperture radar (SAR) automatic target recognition, particularly through convolutional neural network (CNN) based classification algorithms. …”
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Social Confrontation with Menstruation: A Feminist Ethnography of Menstrual Experience among Female Instagram Users by Rana Mohammad Taghinejad Esfahani, Majid Movahed, Halimeh Enayat, Aliyar Ahmadi

“…Materials & MethodsThis research employed feminist ethnography, utilizing Charmaz Grounded Theory for data analysis. …”
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Real-World Robot Control Based on Contrastive Deep Active Inference With Demonstrations by Kentaro Fujii, Takuya Isomura, Shingo Murata

“…To bridge this gap, we utilize active inference, a framework based on the free-energy principle that accounts for various human brain functions. …”
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Reducing dependence of modeled resuspended volcanic ash on meteorological grid resolution by Alice M. Crawford, Christopher P. Loughner, Daniel Q. Tong, Ariel F. Stein

“…Similar schemes have been used successfully for dust emissions. Reducing or eliminating this dependence is important in order to assess and compare the success of different emission schemes, threshold friction velocities, and calibration factors.…”
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WearMoCap: multimodal pose tracking for ubiquitous robot control using a smartwatch by Fabian C. Weigend, Neelesh Kumar, Oya Aran, Heni Ben Amor

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Prediction of Water Quality in Agricultural Watersheds Based on VMD-GA-LSTM Model by Yuxuan Luo, Xianglan Meng, Yutong Zhai, Dongqing Zhang, Kaiping Ma

“…The VMD-GA-LSTM model utilizes the variational mode decomposition technique to decompose the time series data into multiple intrinsic mode functions and then uses the optimized LSTM network to predict each component to improve the accuracy of water quality prediction. …”
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