INVARIANTS OF GENERALIZED RAPOPORT-LEAS EQUATIONS by E. N. Kushner

“…For the generalized Rapoport-Leas equations, algebra of differential invariants is constructed with respect to point transformations, that is, transformations of independent and dependent variables. The finding of a general transformation of this type reduces to solving an extremely complicated functional equation. …”
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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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Bayesian inference for peak feature extraction and prediction of material property in X-ray diffraction data by Ryo Murakami, Taisuke T. Sasaki, Hideki Yoshikawa, Yoshitaka Matsushita, Keitaro Sodeyama, Tadakatsu Ohkubo, Hiroshi Shinotsuka, Kenji Nagata

“…We challenge peak feature extraction in the situation where only the peak function profile is known a priori, without knowledge of the measurement material or crystal structure factor. …”
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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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Fast 3D localization of nano-objects in wide-field interferometric scattering microscopy via vectorial diffraction model-derived analytical fitting by Liaoliao Wei, Caroline Livan Anyi, Huakun Li, Haitao Nie, Bihan Wen, Tong Ling

“…The simplified analytic function includes a quadratically scaling amplitude term and a linearly scaling phase term, both of which change with the nano-object’s axial position. …”
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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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Decoding the role of serum cholinesterase among type 2 diabetes mellitus patients at RIMS, Ranchi – A hospital-based study by Avijit Saha, Abha Kumari, Santosh Kumar, Abhay Kumar, Chandrakanta Munni

“…This condition is characterized by variable levels of insulin resistance, impaired insulin secretion, and elevated glucose production. …”
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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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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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Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…In recent years, the use of machine learning techniques (ML) has become widespread for analysing the effects of operational factors on anaerobic digestion efficiency. Among these, Support Vector Regression (SVR) with a Radial Basis Function (RBF) kernel has been used to predict biogas yield based on diverse operating parameters. …”
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Multi-objective optimal scheduling of cascade reservoirs in complex basin systems: Case study of the Jinsha River-Yalong River confluence basin in China by Zhaocai Wang, Zhihua Zhu, Hualong Luan, Tunhua Wu

“…Benchmark function tests demonstrate that IMOSSA outperforms others in terms of optimization capability and stability. …”
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Shunt active power filter using model predictive control with stability guarantee by Jhon Pérez-Ramírez, Diego Montoya-Acevedo, Walter Gil-González, Oscar Danilo Montoya, Carlos Restrepo

“…The cost function exhibits convex characteristics, ensuring a unique control law. …”
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Prediction of Soil Carbon Sequestration in Rangelands Regarding the Depth and Elevation of Sample Locations using Adaptive Neuro-Fuzzy Inference System (ANFIS) (Case Study: Lar Wat... by zeinab jafarian, zhila ghorbani

“…This system is based on the combination of three components: membership functions of input and output variables (fuzzification), fuzzy rules (rule base), mechanism inference (a combination of rules with fuzzy input), output characteristics, and results of the system (de-fuzzification). …”
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The potential habitat of Phlomoides rotata in Tibet was based on an optimized MaxEnt model by Jun-Wei Wang, Jun-Wei Wang, Min Xu, Norbu Ngawang, Yonghao Chen, Ngawang Bonjor, Xiaoyan Jia, Zhefei Zeng, Zhefei Zeng, La Qiong, La Qiong

“…IntroductionPhlomoides rotata, an important Tibetan medicinal plant, has garnered significant attention due to its remarkable medicinal value and ecological functions. However, overharvesting and climate change have progressively reduced its distribution range, threatening its survival.MethodsThis study employed an optimized MaxEnt model, integrating field survey data and multiple environmental variables, to predict and analyze the potential suitable distribution of P. rotata in Tibet.ResultsThe model achieved high predictive accuracy, with Ture skill statistic (TSS) = 0.87 and Cohen’s Kappa Coefficient (Kappa) = 0.81. …”
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Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework by Xinyu Guo, Faying Gu, Hongxu Liu, Yongcheng Yu, Runjie Li, Juan Wang

“…First, a precise nonlinear model of the PHS microgrid is established and the logic variables are introduced to capture the hydrogen devices’ short-term properties, i.e., the start-up/shut-down of electrolyzers and fuel cells. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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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

“…Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. …”
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True amplitude migration in constant gradient velocity media by Castillo López Luis Antonio

“…<p class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 0pt; mso-layout-grid-align: none;"><span style="font-family: ";Arial";,";sans-serif";; font-size: 12pt; mso-ansi-language: EN-US;" lang="EN-US">The kirchhoff conventional algorithm using ray tracing is based on a constant velocity function. This solution, where is incorporated ray path information into conventional algorithm, can be extended to a variable velocity medium. …”
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