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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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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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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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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Optimization of Mangiferin extraction from Mangifera Indica leaves Peruvian Criollo variation using ultrasound assisted surface response methodology by Elena Sofia Espinoza Rodríguez, Stephanie Elena Sosa Pulcha, Naysha Y. M․ Elguera, Abdel Alejandro Portocarrero Banda, Hugo Guillermo Jiménez Pacheco

“…Additionally, FTIR analysis demonstrated that the extracted mangiferin preserved key functional groups such as hydroxyl (-OH), carbonyl (C = O), and aromatic C = C bonds. …”
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Application of machine learning algorithms for predicting the life-long physiological effects of zinc oxide Micro/Nano particles on Carum copticum by Maryam Mazaheri-Tirani, Soleyman Dayani, Majid Iranpour Mobarakeh

“…All ML algorithms showed varied efficiencies in predicting the nonlinear relationships among parameters, with higher efficiency in predicting the behavior of root and shoot dry mass, root fresh weight and number of flowers according to R2 index. …”
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Providing a Roadmap for the Adaption of Agricultural Sector to Water Scarcity Conditions (Case Study: Selected Crops of Tajan Basin, Iran) by H. Fouladi, H. Amirnejad, S. Shirzadi Laskookalayeh

“…For this reason, the void of using an efficient model that can provide all economic and environmental aspects at the same time was completely felt. …”
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ANALYTICAL SOLUTIONS OF NON-LINEAR HEAT CONDUCTION PROBLEMS by V. A. Bondarev

“…An example of calculations in the case of variable coefficients of thermal conductivity and radiative heating transfer on the boundaries is considered in the paper. …”
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Low-frequency rTMS modulates small-world network properties in an AVH-related brain network in schizophrenia by Lin Zhang, Li Guo, Xiaohui Liu, Jing Han, Yuanqiang Zhu, Chaozong Ma, Ye Li, Weiliang Ye

“…Resting-state fMRI data were collected before and after treatment to assess functional connectivity within the predefined 35-region AVH-related network. small-worldness (σ), normalized clustering coefficient (γ), and normalized characteristic path length (λ), as well as functional segregation (clustering coefficient [Cp], local efficiency [El]) and functional integration (global efficiency [Eg], characteristic path length [Lp])—were analyzed before and after rTMS. …”
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The role of digital green accounting and environment performance on forest sustainable development goals: A case study on customary forest in Papu by Otniel Safkaur, Bill Pangayow, Halomoan Hutajulu, Lediana Hanasbe

“…Therefore, Green Accounting is a business concept that focuses on the efficiency and effectiveness of long-term resource use in integrating the customary forest environmental functions and providing social benefits. …”
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On a Solution of a Third Kind Mixed Integro-Differential Equation with Singular Kernel Using Orthogonal Polynomial Method by Ahmad Alalyani, M. A. Abdou, M. Basseem

“…The singular kernel is modified to take a logarithmic form, while the kernels of time are continuous and positive functions. Using the separation of variables technique, we have a system of Fredholm integral equations (FIEs) that can be transformed into an algebraic system after using orthogonal polynomials. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

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Characterization and treatment monitoring of ureagenesis disorders using stable isotopes by Gabriella Allegri, Martin Poms, Nadia Zürcher, Véronique Rüfenacht, Nicole Rimann, Déborah Mathis, Beat Thöny, Matthias Gautschi, Ralf A. Husain, Daniela Karall, Karolina Orchel-Szastak, Francesco Porta, Dominique Roland, Barbara Siri, Carlo Dionisi-Vici, René Santer, Johannes Häberle

“…Thus, the method proved to be safe and efficient to monitor UCD patients of variable severity pre- and post-therapy, being suitable as physiological endpoint for development of therapies.…”
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An Hfq-dependent post-transcriptional mechanism fine tunes RecB expression in Escherichia coli by Irina Kalita, Ira Alexandra Iosub, Lorna McLaren, Louise Goossens, Sander Granneman, Meriem El Karoui

“…This fine-tuning Hfq-mediated mechanism might have the underlying physiological function of maintaining RecB protein levels within an optimal range.…”
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Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography by Ziwei Zhu, Ke Fan, Shuyuan Zhang, Tingting Hu, Jingyi Li, Ze Zhao, Ye Jin, Shuyang Zhang

“…Abstract Cardiomyopathy often alters left ventricular geometry (LVG), impairing cardiac function. We developed a deep learning (DL) model to estimate left ventricular ejection fraction (LVEF) from echocardiographic images while accounting for LVG variability and assessed prognostic factors across LVG subtypes. …”
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Differentiation and correlation of regional uptake heterogeneity with cardiac dysfunction in biopsy-proven transthyretin amyloid cardiomyopathy using quantitative single-photon emi... by Masakazu Tsujimoto, Hideki Kawai, Shingo Tanahashi, Masayoshi Sarai, Yasuki Asada, Hideo Izawa

“…Polar maps were analyzed to assess local SUV distribution in patients with ATTR-CM. The coefficient of variation (COV) of myocardial uptake, difference score between the septum and lateral wall (%DS), base-to-apex variability, and total cardiac SUV were calculated and compared with echocardiographic parameters. …”
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