Using Compact 1H NMR, NIR, and Raman Spectroscopy Combined with Multivariate Data Analysis to Monitor a Biocatalyzed Reaction in a Microreaction System by Robin Legner, Alexander Wirtz, Martin Jaeger

“…Process analytical technology aims at process knowledge and process improvement, efficiency, and sustainability. A prerequisite is process monitoring. …”
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Challenges of sustainable food security in Iran by Sharareh Asadi, Azadeh Noorollah Noorivandi, Ahmad Reza Ommani, Mohammad Sadegh Sabouri

“…The most important problem of the research is the lack of in-depth identification of sustainable food security challenges and their prioritization in Iran. …”
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A Review on Covid-19 Detection Using Artificial Intelligence from Chest CT Scan Slices by Dhanshri M. Mali, S. A. Patil

“…According to studies, COVID-19 is frequently accompanied by coughing. Therefore, the identification and classification of cough sounds can be a promising method for rapidly and efficiently diagnosing the disease. …”
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Psychometric properties of the short mood and feelings scale among Chinese adolescents using item response theory by Fang Wang, Xuliang Gao

“…This study aimed to assess the SMFQ using Item Response Theory (IRT) in adolescents and determine optimal cutoff points for a revised version.MethodsUsing IRT and the Graded Response Model (GRM), we evaluated the SMFQ in 906 Chinese adolescents (average age 15 years). …”
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Enhancement of dicoumarol production by Aspergillus fumigatus using methanolic extract of Gliricidia sepium leaves: Insights into fermentation kinetics parameters by Siti Zalina Yaacob, Luqman Chuah Abdullah, Chuan Li Lee, Nor Hafizah Abdullah, Kit Ling Chin

“…The Monod kinetic model effectively described the relationship between growth rate, substrate concentration, and biomass production. …”
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An airport apron ground service surveillance algorithm based on improved YOLO network by Yaxi Xu, Yi Liu, Ke Shi, Xin Wang, Yi Li, Jizong Chen

“…At the same time, the original model was converted to TensorRT and OpenVINO format models, which increased the inference efficiency of the GPU and CPU by 55.3 and 137.1%, respectively.…”
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Active Hard Sample Learning for Violation Action Recognition in Power Grid Operation by Lingwen Meng, Di He, Guobang Ban, Guanghui Xi, Anjun Li, Xinshan Zhu

“…Experimental results show significant improvements in model performance and training efficiency, demonstrating the method’s effectiveness in complex power grid environments. …”
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Multi-Terminal Coordinated Frequency Support Strategy for Alternating Current/Direct Current Hybrid Voltage Source Converter-Based Multi-Terminal Direct Current System by Xilin Zhao, Maoyuan Du

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Maize Classification in Arid Regions via Spatiotemporal Feature Optimization and Multi-Source Remote Sensing Integration by Guang Yang, Jun Wang, Zhengyuan Qi

“…This study addresses the challenges of redundant crop identification features and low computational efficiency in complex agricultural environments, particularly in arid regions. …”
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Seasonal Analysis of Silicon Photovoltaic Technology Module by Krupali Kanekar, Prakash Burade, Dhiraj Magare

“…Three main stages must be taken into account while modeling a PV cell: the right selection of analogous models, the mathematical formulation of the model, and the precise identification of parameter values in the models. …”
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Detecting Galactic Rings in the DESI Legacy Imaging Surveys with Semisupervised Deep Learning by Jianzhen Chen, Zhijian Luo, Cheng Cheng, Jun Hou, Shaohua Zhang, Chenggang Shu

“…However, due to the scarcity of ringed galaxies and challenges in their identification, traditional methods often struggle to efficiently obtain statistically significant samples. …”
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Deep learning-based computational approach for predicting ncRNAs-disease associations in metaplastic breast cancer diagnosis by Saleem Ahmad, Imran Zafar, Shaista Shafiq, Laila Sehar, Hafsa Khalil, Nida Matloob, Mehvish Hina, Sidra Tul Muntaha, Hamid Khan, Najeeb Ullah Khan, Samreen Rana, Ahsanullah Unar, Muhammad Azmat, Muhammad Shafiq, Yousef A. Bin Jardan, Musaab Dauelbait, Mohammed Bourhia

“…Feature selection and optimization reduced dimensionality by 42.5% (4,430 to 2,545 features) while maintaining high accuracy, demonstrating computational efficiency. External validation confirmed model specificity to breast cancer subtypes (87–96.5% accuracy) and minimal cross-reactivity with unrelated diseases like Alzheimer’s (8–9% accuracy), ensuring robustness. …”
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An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

“…AEMGO is designed to overcome common issues in traditional meta-heuristic algorithms, such as premature convergence and the exploration–exploitation imbalance, thus enabling the effective identification of key prognostic features. The efficiency of AEMGO is validated against the IEEE CEC 2017 benchmark suite, demonstrating its ability to optimize solution stability and diversity. …”
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Meta-YOLOv8: multi-scale few-shot object detection for Chinese medicinal decoction pieces by Kai Hu, Chu-he Lin, Xing Jin, Hangjuan Lin

“…We tested the proposed Meta-YOLOv8 model on two common image datasets, VOC and COCO, as well as a self-built CMDP image dataset. …”
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Enhanced Blade Fault Diagnosis Using Hybrid Deep Learning: A Comparative Analysis of Traditional Machine Learning and 1D Convolutional Transformer Architecture by Syed Asad Imam, Meng Hee Lim, Ahmed Mohammed Abdelrhman, Iftikhar Ahmad, Mohd Salman Leong

“…Tested on an in‐house fabricated multistage rotor, the hybrid model demonstrated exceptional diagnostic accuracy, exceeding 93% for various fault scenarios. …”
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GaitCSF: Multi-Modal Gait Recognition Network Based on Channel Shuffle Regulation and Spatial-Frequency Joint Learning by Siwei Wei, Xiangyuan Xu, Dewen Liu, Chunzhi Wang, Lingyu Yan, Wangyu Wu

“…Concurrently, the spatial domain processing branch balances the contributions of frequency and spatial domain information through an adaptive weighting mechanism, maintaining computational efficiency while enhancing features. Experimental results demonstrate that the proposed GaitCSF model achieves significant performance improvements on mainstream datasets including GREW, Gait3D, and SUSTech1k, breaking through the performance bottlenecks of traditional methods. …”
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A Novel MoCo-Based Self-Supervised Learning Framework for Solar Panel Defect Detection by Jun Huang, Shamsul Arrieya Ariffin, Yongqiang Chen, Jinghui Lin, Wanting Xu

“…Additionally, our model achieved 99.44% accuracy on the EL dataset, underscoring its adaptability and robustness across different environments. …”
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Tracking Oral Nanoparticle Uptake in Mouse Gastrointestinal Tract by Fluorescent Labeling and t-SNE Flow Cytometry by Rabeya Mow, Michal Kuczma, Xiaodi Shi, Didier Merlin, Chunhua Yang

“…This protocol presents a refined approach for fluorescent labeling and flow cytometric analysis of colonic cells following oral lipid nanoparticle (LNP) treatment, focusing on LNP uptake in colonic cell subpopulations in a DSS-induced colitis mouse model. By integrating optimized fluorochrome selection and gating strategies with advanced t-distributed stochastic neighbor embedding (t-SNE) analysis, this method enables precise identification and multidimensional visualization of LNP-targeted epithelial and macrophage populations under the complex conditions of inflamed colon tissue. …”
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Nonlinear Vibrations of Low Pressure Turbine Bladed Disks: Tests and Simulations by Umidjon Usmanov, Giuseppe Battiato, Christian Maria Firrone, Marta Conte, Emanuele Rosso, Antonio Giuseppe D’Ettole

“…This study presents a novel approach combining experimental Blade Tip Timing (BTT) with numerical simulations using Policontact (ver. 3.0) software and a model update based on experimental evidence to validate nonlinear dynamic responses. …”
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Personalized Drug Recommendation System Using Wasserstein Auto-encoders and Adverse Drug Reaction Detection with Weighted Feed Forward Neural Network (WAES-ADR) in Healthcare by J Omana, P. N Jeipratha, K Devi, S Benila, K Revathi

“…WAEs' capacity to manage complex data distributions and develop meaningful latent representations makes them ideal for modeling heterogeneous healthcare data. This study intends to improvise the precision and efficiency of drug recommendation systems while also improving patient safety by combining WAEs and early ADR detection strategies. …”
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