Embedded physical constraints in machine learning to enhance vegetation phenology prediction by Mengying Cao, Qihao Weng

“…The results show that the overall root mean square error (RMSE) with physical constraints is reduced to 12.37 days, higher by 2.6 days than the machine learning method without physical constraints. …”
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Cómo Iniciar el Proceso de Mercadeo en la Empresa by Gerardo Lee Rojas

“…Sin un plan de mercadeo, la posibilidad decometer errores es altísima. En muchos casos, la desesperaciónque causa el avance de la competencia y lareducción del nivel de ventas, provocan que la empresase desenfoque, cometiendo el error de operar en camposque no estaban contemplados en su estrategia comercialbásica, y, por tanto, en los que no tiene suficiente habilidadcompetitiva. …”
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Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests by Muhammad Junaid Ismail, Tika Ram Poudel, Akber Ali, Lingbo Dong

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Time in range prediction using the experimental mobile application in type 1 diabetes by A. N. Rusanov, T. I. Rodionova

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Performance of Large Language Models in the Non-English Context: Qualitative Study of Models Trained on Different Languages in Chinese Medical Examinations by Zhong Yao, Liantan Duan, Shuo Xu, Lingyi Chi, Dongfang Sheng

“… Abstract BackgroundResearch on large language models (LLMs) in the medical field has predominantly focused on models trained with English-language corpora, evaluating their performance within English-speaking contexts. …”
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Influences of intelligent predictive networks on thermal efficiency of radiative magnetohydrodynamics hybrid nanofluid flow considering heat absorption-generation aspects by Muhammad Habib Ullah Khan, Waqar Azeem Khan, Taseer Muhammad, Marei S. Alqarni, Hamid Qureshi, Iftikhar Hussain

“…The research on HNFs is on peak and results revealed the efficient heat transfer properties of these liquids which are working as primary agents for industrial use. …”
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Simulation of landslide dam failure due to overtopping considering wide-graded soil erosion by Gangyong Song, Tianlong Zhao, Penghui Zhao, Changjing Fu, Xiong Hu

“…The calculated results of key dam failure outcomes were compared with actual measurements, showing that the results of this model are largely consistent with actual measurements, with the error controlled within 10%. Additionally, the mathematical model proposed in this article was compared with two other existing dam failure models, revealing that the model proposed here has advantages in controlling the error of key dam failure outcomes, mainly due to the comprehensive consideration of erosion calculation in wide-graded soil. …”
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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

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Multi-Criteria Assessment of Flood Risk on Railroads Using a Machine Learning Approach: A Case Study of Railroads in Minas Gerais by Fernanda Oliveira de Sousa, Victor Andre Ariza Flores, Christhian Santana Cunha, Sandra Oda, Hostilio Xavier Ratton Neto

“…The database required for the machine learning model can be created with these hydrological data. The research regions are situated in the densely rail-networked state of Minas Gerais. …”
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Clinical Application of Xenon in Subanesthetic Concentrations (Review) by M. E. Politov, S. V. Podprugina, E. N. Zolotova, P. V. Nogtev, Yu. S. Agakina, S. G. Zhukova, A. G. Yavorovsky

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A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems by Shuaibo Wang, Xinyuan Xiang, Jie Zhang, Zhuohang Liang, Shufang Li, Peilin Zhong, Jie Zeng, Chenguang Wang

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A Comprehensive Approach to Load Frequency Control in Hybrid Power Systems Incorporating Renewable and Conventional Sources with Electric Vehicles and Superconducting Magnetic Ener... by K. Nagendra, K. Varun, G. Som Pal, K. Santosh, Sunil Semwal, Manoj Badoni, Rajeev Kumar

“…The FOPID-FOID control scheme provides advantages like adaptability/flexibility to system parameter changes and better response time for the current power system. This research is novel because it shows that the FOPID-FOID is an excellent control scheme that can integrate these diverse/renewable sources with modern systems.…”
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Optimizing agricultural yield: a predictive model for profitable crop harvesting based on market dynamics by Nilesh P. Sable, Nilesh P. Sable, Vinod Kumar Shukla, Parikshit N. Mahalle, Vijayshri Khedkar

“…In agriculture, optimizing harvesting schedules is crucial for maximizing profits while minimizing resource waste. This research introduces a novel forecasting model that forecasts the most profitable months to harvest different crops, to optimize agricultural productivity. …”
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Design and Control of a Deformable Trees-Pruning Aerial Robot by Changliang Xu, Zhong Yang, Zhao Zhang, Hao Xu, Jiying Wu, Dongsheng Zhou, Luwei Liao, Qiuyan Zhang

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Mapping and Estimation of Monthly Global Solar Irradiation in Different Zones in Souss-Massa Area, Morocco, Using Artificial Neural Networks by O. Nait Mensour, S. Bouaddi, B. Abnay, B. Hlimi, A. Ihlal

“…Solar radiation data play an important role in solar energy research. However, in regions where the meteorological stations providing these data are unavailable, strong mapping and estimation models are needed. …”
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An improved method for predicting the permeability of Chang 7 shale oil reservoirs based on lithology and hydraulic flow units by Heting Gao, Yanze Sun, Hui Zhao, Fei Zhou, Weichao Tian, Zhigang Wen, Yunpeng Fan, Xiaoyu Chen

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Eddy-induced underwater acoustic field reconstruction and computation based on sound speed classification and B-spline surface fitting by Luochuan Xu, Jian Xu, Xuegang Zhang, Anmin Zhang, Yi Liu, Dan Chen, Linglong Chen, Zhongpeng Wu

“…The results show that this approach reduces computational time and resource consumption by more than 30%, while maintaining a mean transmission loss error of only 1.2 dB over a 20 km range. This work represents an effective integration of acoustic sensing, machine learning, and FEM simulation in oceanographic research, offering a practical and efficient solution for studying subsurface phenomena in ice-covered regions.…”
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Deep learning for predicting porosity in ultra-deep fractured vuggy reservoirs from the Shunbei oilfield in Tarim Basin, China by Ziyan Deng, Dongsheng Zhou, Hezheng Dong, Xiaowei Huang, Shiping Wei, Zhijiang Kang

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Repeatability, reliability, and stability of eye movement measurements in Parkinson’s disease, cerebellar ataxia, and healthy adults by Solveig E. J. Dalbro, Solveig E. J. Dalbro, Ahmed Elsais, Siri Lynne Rydning, Mathias Toft, Mathias Toft, Emilia Kerty, Emilia Kerty, Stig E. Larsen

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Individualized transcranial direct current stimulation combined with foot core exercise improves foot and ankle sensorimotor function and static postural control in individuals wit... by Chuyi Zhang, Songlin Xiao, Bin Shen, Zhen Xu, Jianglong Zhan, Jingjing Li, Junhong Zhou, Weijie Fu

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