Correlation of magnetic resonance imaging parameters with montreal cognitive assessment-Indonesian (MOCA-INA) score in dementia patients at Prof. Dr. IGNG Ngoerah General Hospital,... by Made Widhi Asih, Elysanti Dwi Martadiani, I Wayan Gede Artawan Eka Putra, Felicia Nike, Putri Ayu Ratnasari, Nugra Arenz Raturandang, Jessieca Liusen, Anak Agung Parama Swari Khrisna, Luh Dindi Ayu Surya Kanti, Adsel Kartadinata

“…Correlation between variables was evaluated based on the correlation coefficient, which indicates the direction and strength of the correlation. …”
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行星变速器的模糊可靠性多目标优化设计 by 鲁成瑞, 张进生, 王志

“…An objective function for increasing the transmission efficiency and reliability of the planetary system and trying our best to reduce the weight is set up,through the linear weighted function method,the mathematical model of objective function is established.The weighting factors is determined by using the method of design variables normalization.Based on the fuzzy mathematics theory of reliability constraints and geometric constraint,the optimal design is carried out by using optimization toolbox in Matlab.To ensure the optimal parameter to meet the global optimal solution of objective function,stack calculation of the three local optimal solution are carried out.Through an example show that,by using multi-objective optimization method of fuzzy reliability design,the transfer efficiency and stability of the system are improved,the quality of the planet gear train is also reduced.…”
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A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation by Dong Miao, Ying Zhao, Xue Ren, Meng Dou, Yu Yao, Yiran Xu, Yingchao Cui, Ailian Liu

“…To achieve precise Couinaud liver segmentation in preoperative planning for hepatic surgery, accommodating the complex anatomy and significant variations, optimizing surgical approaches, reducing postoperative complications, and preserving liver function.This research presents a novel approach to automating liver segmentation by identifying seven key anatomical landmarks using portal venous phase images from contrast-enhanced magnetic resonance imaging (CE-MRI). …”
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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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MCL-SWT: Mirror Contrastive Learning with Sliding Window Transformer for Subject-Independent EEG Recognition by Qi Mao, Hongke Zhu, Wenyao Yan, Yu Zhao, Xinhong Hei, Jing Luo

“…Inspired by left/right hand motor imagery inducing event-related desynchronization (ERD) in the contralateral sensorimotor cortex, we develop a mirror contrastive loss function. It segregates feature spaces of EEG signals from contralateral ERD locations while curtailing variability in signals sharing similar ERD locations. …”
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Computational studies reveal structural characterization and novel families of Puccinia striiformis f. sp. tritici effectors. by Raheel Asghar, Nan Wu, Noman Ali, Yulei Wang, Mahinur Akkaya

“…However, due to the lack of an efficient genetic transformation system in Pst, progress in effector function studies has been slow. …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

“…The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. …”
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SSR loci potentially associated with high amylopectine content in maize kernel endosperm by S. I. Vakula, O. A. Orlovskaya, L. V. Khotyleva, A. V. Kilchevsky

“…As a component of functional nutrition, maize cultivars with “non-traditional” kernel composition (waxy, oilbearing, sugar, opaque, etc. phenotypic variants) are promising. …”
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Development characteristics and potential of fault-fracture reservoir in southwest margin of Ordos Basin by HE Faqi, LI Junlu, GAO Yilong, WU Jinwei, BAI Xingying, GAO Dun

“…The induced fracture zone's proximity to the fault correlates with higher production capacity, demonstrating the spatial impact of fault structures on reservoir productivity. 3） The production characteristics of fracture wells are categorized into three stages: ① the fracture system acts as the high yield stage; ② the fracture system serves as the storage stage and plays the role of diversion; ③ the fracture's primarily function in diversion. This research significantly increases the proportion of high-yield wells in the fault-fracture reservoir, providing crucial insights for guiding efficient, ongoing exploration and development activities in the Mesozoic reservoirs on the southwest margin of the basin. …”
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Numerical Investigation and Optimization of Transpiration Cooling Plate Structures with Combined Particle Diameter by Dan Wang, Yaxin Liu, Xiang Zhang, Mingliang Kong, Hanchao Liu

“…An optimization analysis of CPD−PS is conducted using response surface methodology (RSM), and the influence of design variables on the objective function (<i>η</i>_ave and <i>p</i>) is analyzed. …”
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Assessment of Matrix Metalloproteinases a Prognostic Indicator in Advanced Fibrotic Lung Disease: A Systematic Review by Mehvish Aqil, Saif Ur Rahman, Muhammad Zeeshan Aslam, Mostafa Ahmed Abdellah Ahmed, Ammar Ahmed, Sidra Javaid, Ehsan Ul Haq

“…The MMP-7 was consistently elevated in 73.3% (n=11) of the studies and correlated with disease severity, lung function decline, and progression. In 46.7% (7) of studies, MMP-9 was associated with imaging severity and functional impairments, and in 26.7% (4) of studies, MMP-7 was found as the strongest biomarker, and the correlation coefficient calculated was from (r = 0.65 to 0.80), for MMP-9 it was (r = 0.4 to 0.6) and for MMP-1 (r = 0.3 to 0.45). …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…Principal Component analysis further highlighted five clusters of health-related variables, identifying age-related metabolic indicators (AGE, HbA1c, BMI), kidney function markers (creatinine (Cr), Urea), cardiovascular lipid profiles (Cholesterol, LDL), lipid transport (VLDL), and protective cardiovascular indicator (HDL). …”
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Quantitative analysis of ocular deviation under eye occlusion: a descriptive study using the ORTe EYENAC eye-tracking system by Shunya Tatara, Yuna Magara, Touko Sasaki, Fumiatsu Maeda, Noriaki Murata, Kazuhiro Itagaki, Tomoya Handa, Haruo Toda

“…Data were fitted to a logistic function to estimate ocular deviations, deviation speed, and stabilization time. …”
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Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

“…During the optimization process, these controlling parameters are used as a design variable whereas the objective function required to me be a maximum is the summation of turbidity removal and salinity removal. …”
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Optimization Design of Fast Neutron Target Station Beam Extraction Based on Genetic Algorithm by QIN Ziqian1, 2, 3, TAN Xinjian2, 3, ZHANG Xiaodong2, 3, PAN Qingquan1, LIU Xiao2, 3

“…Therefore, the aforementioned parameters are used as variables, and the three important indicators are taken as the objective function. …”
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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

“…In this work, we show two machine learning approaches – one with pre-trained language models (PTLM) capturing functional effects of sequence variation, and second, a supervised convolutional neural network (CNN) trained with Rosetta energetic features – to better classify thermostable scFv variants from sequence. …”
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Comparative Genomics of Rhamnolipid Synthesis and Monoaromatic Hydrocarbon Tolerance Genes in Environmental Pseudomonas aeruginosa strains [version 2; peer review: 2 approved] by Sandro B. Martel-Torres, Camila Castillo-Vilcahuaman, ROGER A. PALOMINO HUARCAYA, Susana M. Gutiérrez Moreno, Fernando A. Merino Rafael

“…The BTEX (benzene, toluene, ethylbenzene, and xylene) are toxic hydrocarbons requiring efficient microbial degradation for bioremediation. …”
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Genetically Engineered Bacterial Ghosts as Vaccine Candidates Against <i>Klebsiella pneumoniae</i> Infection by Svetlana V. Dentovskaya, Anastasia S. Vagaiskaya, Alexandra S. Trunyakova, Alena S. Kartseva, Tatiana A. Ivashchenko, Vladimir N. Gerasimov, Mikhail E. Platonov, Victoria V. Firstova, Andrey P. Anisimov

“…Previously, this kit made it possible to generate bacterial cells of <i>Yersinia pestis</i> with varying degrees of hydrolysis and variable protective activity. <b>Results:</b> In the current study, we showed that co-expression of the holin and endolysin genes from the L-413C phage elicited more rapid and efficient <i>K. pneumoniae</i> lysis than lysis mediated by only single gene <i>E</i> or the low functioning holin–endolysin system of λ phage. …”
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Analisis Penerimaan Learning Management System Institut Teknologi Garut Menggunakan Technology Acceptance Model by Asri Mulyani, Dede Kurniadi, Mita Hidayani Putri

“…It is hoped that the results of this research can be used as a reference for developers to continue to optimize the functionality of the Learning Management System so that it can be used optimally. …”
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Synthesis of evasive maneuver control of unmanned aerial vehicle for terminal restrictions by N. Y. Polovinchuk, S. V. Ivanov, L. I. Kotelnitskaya

“…The FV (flying vehicle) control is organized with maximum efficiency. Herewith, the maneuvering FV trajectory must satisfy the requirements of optimality for some given functions of the phase variables at the final time and the conditions of its path through a specified terminal area space. …”
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