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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Transcriptome profiling of Hyacinthus orientalis L. cultivars in floral pigmentation by Kwan-Ho Wong, Hoi-Yan Wu, Cheryl Wood-Yee Shum, Jerome Ho-Lam Hui, Pang-Chui Shaw, David Tai-Wai Lau

“…In addition, the usability of the dataset was demonstrated by the identification of differentially expressed genes, functional annotation and functional enrichment analysis. …”
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Bioactive compounds from tropical fruit by-products: Extraction, characterization and therapeutic potential by Niza Otero-Guzman, Ricardo Andrade-Pizarro

“…However, there are several challenges associted with the efficient extraction and accurate characterization of these compounds, including the complexity of plant matrices, variability in compound polarity, and the need for scalable, eco-friendly methods that preserve their bioactivity. …”
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Optimized Blade Design of Counter-Rotating-Type Pump-Turbine Unit Operating in Pump and Turbine Modes by Jin-Woo Kim, Jun-Won Suh, Young-Seok Choi, Kyoung-Yong Lee, Toshiaki Kanemoto, Jin-Hyuk Kim

“…The pump and turbine mode efficiencies of the unit were selected as the objective functions and they combined into a single specific objective function with the weighting factors. …”
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Order assignment mechanism based on hierarchical decomposition and element matching by ZHANG Xinyue, LYU Weimin, WEI Dingjiang, YANG Dongsheng

“…This is achieved through the utilization of the flexibility of edge command nodes, which enables them to cope with unexpected situations and guarantee the continuity of the operational command link, thus facilitating the efficient achievement of operational goals.…”
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Land-Cover Semantic Segmentation for Very-High-Resolution Remote Sensing Imagery Using Deep Transfer Learning and Active Contour Loss by Miguel Chicchon, Francisco James Leon Trujillo, Ivan Sipiran, Ricardo Madrid

“…We assessed the U-Net-scSE, FT-U-NetFormer, and DC-Swin architectures, incorporating transfer learning and active contour loss functions to improve performance on semantic segmentation tasks. …”
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Advanced microfluidic strategies for core-shell nanoparticles: the next-generation of polymeric and lipid-based drug nanocarriers by Giuseppe Nunziata, Alessandro Borroni, Filippo Rossi

“…Microfluidic technology has transformed the synthesis of core-shell nanoparticles (CSNPs), providing an unprecedented level of control over their structural and functional properties. This review critically evaluates recent advancements, highlighting the superiority of microfluidic methods over conventional batch techniques, which often suffer from variability and scalability issues. …”
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Exploring the Impact of School-Based Physical and Perceived Environments on Students’ Physical Activity During Recess: A Case Study of Four Schools in Xi’an, China by Qing Wang, Yan Wang, Lan Zhou, Yong Nan

“…The study’s results confirmed previous findings from a social–ecological perspective and provide a comprehensive assessment framework that includes the spatial organization/spatial quality of the school and the perceived variables of safety, comfort, aesthetics, accessibility and functionality. …”
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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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Dimensions-Reduced Volterra Digital Pre-Distortion Based On Orthogonal Basis for Band-Limited Nonlinear Opto-Electronic Components by Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

“…Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. The orthogonal basis enables the estimation of each coefficient separately, which provides a significant computational gain. …”
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Sustainable forest management: success and challenges in Ethiopia by Rusha Begna Wakweya

“…The outcomes of local-level forest governance depend on the quality, efficiency, and effectiveness of local policymaking and decision-making processes, as well as how power and authority are exercised locally. …”
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Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive D... by Duc Nam Nguyen, Thanh-Phong Dao, Ngoc Le Chau, Van Anh Dang

“…The optimization problem considers three design variables and two objective functions. An efficient hybrid optimization approach of central composite design (CDD), finite element method (FEM), Kigring metamodel, and multiobjective genetic algorithm (MOGA) is developed. …”
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Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures by Nishchal K. Verma

“…The main contribution of this paper is the estimation of fuzzy measures efficiently and directly from covariance matrices found in GMM, avoiding the computational burden greatly while learning them iteratively and solving polynomial equations of order of the number of input-output variables.…”
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Binary composite crossover genetic algorithm for locating critical slip surface by Wei Qin, Jiancheng Zhao

“…A reasonable combination of parameters for the binary composite crossover (BCC) operator in the RGA-BCC is determined through six benchmark function experiments. On this basis, the stability of five soil slopes from the literature was analysed using the RGA-BCC in combination with the Morgenstern and Price method, and the results obtained were compared with those in the published literature to demonstrate that the RGA-BCC is able to efficiently determine the CSSs of slopes and their minimum factors of safety. …”
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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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Leveraging artificial intelligence for diagnosis of children autism through facial expressions by Mahmood A. Mahmood, Leila Jamel, Nazik Alturki, Medhat A. Tawfeek

“…Using autism spectrum disorder (ASD) diagnosed child RGB images data, researchers evaluated six prevalent deep learning structures: DenseNet201, ResNet152, VGG16, VGG19, MobileNetV2, and EfficientNet-B0. ResNet152 reached the highest accuracy rate of 89% when functioning independently. …”
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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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Exploring the nexus of many-body theories through neural network techniques: the tangent model by Senwei Liang, Karol Kowalski, Chao Yang, Nicholas P Bauman

“…The NN representation not only allows us to evaluate the effective interactions efficiently for various geometrical configurations of chemical systems corresponding to various levels of complexity of the underlying wave functions, but also reveals that the bare and effective interactions are related by a tangent function of some latent variables. …”
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