Multi-objective optimization of a novel control algorithm and scheduling procedure for optimal use of energy storage systems by Amirhossein Hamzeiyan, Armin Ebrahimi

“…Regarding this, 2 hypothesis load demand profiles as well as 5 different scenarios with diverse objective functions, including ESS capacity, standby days of the ESS, etc., were considered for multi-objective optimization, and the control algorithm was applied to them. …”
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Enabling Precision Agriculture through a Web-Based Fertilization Management System for Nawungan Selopamioro Fruit Orchards by Andri Prima Nugroho, Fauzan Edy Wijaya, Ngadisih Ngadisih, Rudiati Evi Masithoh, Lilik Sutiarso

“…Although comprehensive testing confirmed a 100% success rate in functionality, the system currently operates within a limited scope of variables. …”
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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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Cognitive Agent-Based Modeling to Optimize Complex Project Management Under Uncertainty by Liliana M. Pantoja-Rojas, Marco A. Alzate-Monroy, Vactor H. Medina-Garcaa, Luis G. Moreno-Sandoval

“…Overall, the study underscores the importance of organizational continuity and the thoughtful design of collaboration parameters to achieve efficient performance in complex project settings. …”
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Assessment of the Potential of Decentralized Dinance (DeFi) as an Alternative to Traditional Financial Services in the Context of the Development of the Digital Economy and Web3 by Manoilenko Oleksandr V., Kuznetsova Svitlana O., Pysakovskyi Anton O.

“…An analysis of the main characteristics of DeFi protocols, their functional capabilities, and differences from centralized financial institutions has been conducted. …”
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Review: roles of mycorrhizal symbioses and associated soil microbiomes in ecological restoration by Christine Lethielleux-Juge

“…A similar recovery period was observed for fungal communities in forest restoration, where ectomycorrhizal mycorrhizal fungi (EMF) species dominate, and diversity increased with time post-revegetation, influenced by edaphic variables and tree species. Under heavy metal (HM) contamination, microorganism classes, enzymes, and AMF efficiency vary with time, soil parameters, restoration treatments, plant species, and levels of soil contamination, with Proteobacteria and Actinobacteria being often predominant. …”
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Research on Design and Energy-Saving Performance of Gate Rudder by Chunhui Wang, Qian Gao, Lin Li, Feng Gao, Zhiyuan Wang, Chao Wang

“…As a novel energy-saving and maneuvering device for ships, the gate rudder system (GRS) functions similarly to an accelerating duct. While providing additional thrust, its independently controllable rudder blades on either side of the propeller also enhance ship maneuverability. …”
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An Empirical Analysis of Herding Behavior in the Stock Market: Evidence from Various Economic and Social Conditions in Iran by Majid Aghaei

“…This approach models the response of the dependent variable to the independent variable at various quantiles, denoted as "τ," making it an effective tool for analyzing non-normal distributions. …”
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Rehabilitation impact indices and their independent predictors: a systematic review by Amardeep Thind, Gerald Choon-Huat Koh, Robert Petrella, Cynthia Huijun Chen

“…Then, various names of the same formula were used to identify studies, limited to articles in English and up to 31 December 2011, including case–control and cohort studies, and controlled interventional trials where RIIs were outcome variable and matching or multivariate analysis was performed.Results The five RIIs identified were (1) absolute functional gain (AFG)/absolute efficacy/total gain, (2) rehabilitation effectiveness (REs)/Montebello Rehabilitation Factor Score (MRFS)/relative functional gain (RFG), (3) rehabilitation efficiency (REy)/length of stay-efficiency (LOS-EFF)/efficiency, (4) relative functional efficiency (RFE)/MRFS efficiency and (5) revised MRFS (MRFS-R). …”
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Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…The architecture’s efficiency is further demonstrated by its reduced trainable parameters and robust handling of multimodal and variable-length inputs, making it a versatile solution for classification tasks.…”
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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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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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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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Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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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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On the development of a practical Bayesian optimization algorithm for expensive experiments and simulations with changing environmental conditions by Mike Diessner, Kevin J. Wilson, Richard D. Whalley

“…The method is validated on two synthetic test functions, and the effects of the noise level, the number of environmental parameters, the parameter fluctuation, the variability of the uncontrollable parameters, and the effective domain size are investigated. …”
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On the Nonlinear Forced Vibration of the Magnetostrictive Laminated Beam in a Complex Environment by Nicolae Herisanu, Bogdan Marinca, Vasile Marinca

“…The nonlinear differential equations were studied using an original, explicit, and very efficient technique, namely the optimal auxiliary functions method (OAFM). …”
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Advancing the modified face name associative memory exam in cognitive aging research: insights into connectomic correlates and task reliability by Yilin Liu, Yilin Liu, Mark H. Sundman, Mark H. Sundman, Dalen Hinderaker, Allison Yu-Chin Chen, Allison Yu-Chin Chen, Jacob M. Green, Jacob M. Green, Lisbeth G. Haaheim, Lisbeth G. Haaheim, Hannah M. Siu, Hannah M. Siu, Catherine Jezerc, Kaitlyn Lai, Carol Chen, Parker Guss, Ying-hui Chou, Ying-hui Chou, Ying-hui Chou

“…Experiment 2 revealed significant associations between mFNAME performance and network properties like global efficiency, local efficiency, and system segregation in the default mode network (DMN) and medial temporal network (MTN). …”
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