Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
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Impedance-based sensitivity analysis for enhanced dynamic stability in DC off-grid hydrogen production systems by Chenguang Zhang, Zhongjian Kang, Bin Li, Hongyang Zhang, Di Zhu

“…DC off-grid hydrogen production systems, employing source–hydrogen interface converters to achieve efficient renewable energy conversion and electrolysis coupling, represent a core technological solution for green hydrogen generation. …”
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Dynamic ensemble-based machine learning models for predicting pest populations by Ankit Kumar Singh, Md Yeasin, Ranjit Kumar Paul, A. K. Paul, Anita Sarkar

“…Advances in machine learning algorithms facilitate the development of efficient pest alert systems. Furthermore, ensemble algorithms help in the utilization of several models rather than being dependent on a single model. …”
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ESTIMATING THE DEMAND FOR RAILWAY FREIGHT TRANSPORTATION: A CASE STUDY IN KAZAKHSTAN by Madiyar SULTANBEK, Nazdana ADILOVA, Aleksander SŁADKOWSKI, Arnur KARIBAYEV

“…Qualitative methods rely on judgments and opinions, while quantitative methods utilize historical data or identify causal relationships between variables. Overall, the present study highlights the critical role of demand forecasting in the railway freight transportation industry and its impact on efficient planning and decision-making processes.…”
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Development of a Data‐Driven Lightning Scheme for Implementation in Global Climate Models by Vincent Verjans, Christian L. E. Franzke

“…Abstract This study proposes a new lightning scheme applicable at the global scale, predicting lightning rates from climatic variables. Using satellite lightning records spanning a period of 29 years, we apply machine learning methods to derive a functional relationship between lightning and climate reanalysis data. …”
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Antigenic characterization of the human immunodeficiency virus (HIV-1) envelope glycoprotein precursor incorporated into nanodiscs. by Kristen C Witt, Luis Castillo-Menendez, Haitao Ding, Nicole Espy, Shijian Zhang, John C Kappes, Joseph Sodroski

“…We identified detergents, as well as lipids similar in composition to the viral lipidome, that allowed efficient formation of Env-nanodiscs (Env-NDs). Env-NDs were created with the full-length Env precursor and with an Env precursor with the majority of the cytoplasmic tail intact. …”
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In vitro study of macro and micro nutrients decline in MS medium on growth and development levels of Acacia tortilis (Forssk.) Hayne. by Seyed Mohammad Hosseini Nasr, Marziyeh Valizadeh, Seyed Ali Razavi

“…Acacia tortilis is one of the valuable species growing in the southern regions of Iran, which is highly considerable for a variety of reasons such as stabilization of quicksand, medicinal uses and ecological functions. Low germination capacity of seeds, hard rooting of cuttings, the value of aesthetics and multiple medicinal uses highlight the importance of further research to explore methods for easy and efficient propagation of this species in vitro. …”
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Some comments on the assessment of students’ knowledge at the University by Darya I. Yareshchenko

“…The parametric approach consists in choosing the form of the function up to a vector of parameters and the subsequent evaluation of these coefficients by a training sample. …”
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HEART AND VESSEL REMODELING IN DIFFERENT AGE GROUPS OF PATIENTS WITH ARTERIAL HYPERTENSION by V. N. Kandilova

“…The Spearman rank correlation coefficient (r) was used to estimate the relationship between these variables. …”
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Empirical Study of the Impact of Unemployment on Political Stability in Iran (1985-2015) by habib samani, robabeh khilkordi

“…Vector regression (VAR), Johansson-Juselius, Vector Error Correction Model (VECM), and variance analysis function were used for this purpose. The results show that in the long run, two variables of unemployment rate and Gini coefficient have a negative and significant relationship with political stability. …”
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Multi-objective optimization of an open-pit mining system to determine safety buffer using the modified NBI method and the meta-model approach by Tahereh Khajvandsany, Hossein Amoozad Khalili, Ramezan Rezaeyan, Kourosh Nemati

“…The central composite design (CCD) method was used to develop the design of experiments (DOE) for the design variables. Results: according to obtained findings, the considered design variables were the number of trucks of 120 tons, 240 tons, 35 tons, and 100 tons. …”
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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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Understanding the Role of Organic Hole Transport Layers on Pinhole Blocking and Performance Improvement in Sb2Se3 Solar Cells by Thomas P. Shalvey, Christopher H. Don, Leon Bowen, Tim D. Veal, Jonathan D. Major

“…After successive record‐efficiencies using a range of device structures, spiro‐OMeTAD has emerged as the default hole transport material (HTM), however, the function of HTM layers remains poorly understood. …”
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Magnetic Field Effects on Convective Heat Transfer of Ferrofluid from a Heated Sphere in Porous Media by Ayesha Aktar, Sharaban Thohura, Md. Mamun Molla

“…For increasing Ha, the figure of streamlines seems to depict functions with more gradual changes, and for isotherms, it represents functions with sharper, exponential-like increases. …”
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Impact of Wall Material Composition (Maltodextrin vs. Inulin vs. Nutriose) and Emulsion Preparation System (Nano- vs. Microemulsion) on Properties of Spray-Dried Linseed Oil by Dorota Ogrodowska, Iwona Zofia Konopka, Grzegorz Dąbrowski, Beata Piłat, Józef Warechowski, Fabian Dajnowiec, Małgorzata Tańska

“…For these independent variables, the properties of the prepared emulsions (flow curves and viscosity) and the resulting powders (encapsulation efficiency, particle size distribution, water activity, bulk and tapped density, Carr’s index, color parameters, and thermal stability) were determined. …”
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An Optimal Hybrid Control Method for Energy-Saving of Chilled Water System in Central Air Conditioning by Yan Zhang, Xiaoli Chu, Yongqiang Liu

“…Here, an optimum control method is proposed with the principle of the minimum, by setting the minimum power consumption as the performance function in fixed time, which realizes variable control of pumps and accurate adjustment of temperature inside room. …”
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The Brain Behind the Grid: A Comprehensive Review on Advanced Control Strategies for Smart Energy Management Systems by Gowthamraj Rajendran, Reiko Raute, Cedric Caruana

“…The integration of digital technologies is catalysing a fundamental transformation of modern energy systems, enhancing operational efficiency, adaptability, and sustainability. Despite significant progress, the existing literature often addresses digital innovations in isolation, with limited consideration of their synergistic potential within Advanced Energy Systems (AES). …”
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Clinical Outcome Prediction Model in Tetralogy of Fallot Without Pulmonary Valve Replacement Using Contraction Fraction From the SCOUT‐TOF Registry by Mark A. Fogel, Jennifer A. Faerber, Abdullah Mahmood, Keerthi Reddy, Xuemei Zhang, Elizabeth Goldmuntz, Matthew A. Harris, David Biko, Sara Partington, Stephen Paridon, Michael Mcbride, Victor Ferrari, Kevin K. Whitehead, Laura Mercer‐Rosa

“…Conclusions In rTOF, RV contraction fraction, a novel biomarker of ventricular efficiency, may be used to possibly improve risk stratification. …”
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Investigation of a chest radiograph-based deep learning model to identify an imaging biomarker for malnutrition in older adults by Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, Takahito Nishihara, Masafumi Haraguchi, Masanori Fukushima, Ryu Sasaki, Satoshi Miuma, Hisamitsu Miyaaki, Kazuhiko Nakao

“…The predicted data were evaluated by computing the correlation coefficients and area under the curve (AUC). Results: As a numerical variables analysis, albumin and hemoglobin predictions were relatively accurate (R=0.71, 0.74). …”
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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Analytical expressions for key QoS indicators (delay, variability, loss, energy consumption) as functions of the shift parameter are derived, and a multi-factor reward function is constructed. …”
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