Monitoring the Concentrations of Na, Mg, Ca, Cu, Fe, and K in <i>Sargassum fusiforme</i> at Different Growth Stages by NIR Spectroscopy Coupled with Chemometrics by Sisi Wei, Jing Huang, Ying Niu, Haibin Tong, Laijin Su, Xu Zhang, Mingjiang Wu, Yue Yang

“…Superior CARS-PLS models were established for Na, Mg, Ca, Cu, Fe, and K with root mean square error of prediction (<i>RMSEP</i>) values of 0.8196 × 10³ mg kg⁻¹, 0.4370 × 10³ mg kg⁻¹, 1.544 × 10³ mg kg⁻¹, 0.9745 mg kg⁻¹, 49.88 mg kg⁻¹, and 7.762 × 10³ mg kg⁻¹, respectively, and coefficient of determination of prediction (<i>R_P</i>²) values of 0.9787, 0.9371, 0.9913, 0.9909, 0.9874, and 0.9265, respectively. …”
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COOPERATIVE MODEL FOR OPTIMIZATION OF EXECUTION OF THREADS ON MULTI-CORE SYSTEM by A. A. Prihozhy, O. N. Karasik

“…It optimizes the execution order of the  computational operations and the operations of data exchange, decreases the overall time of the multithread application  execution by means of the reduction of the critical path in the concurrent algorithm graph, increases the application throughput at the growth of the number of threads, and excludes the competition among threads that is specific for preemptive multitasking...............................…”
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A prospective cluster randomized trial of an interventions bundle to reduce inappropriate antibiotic use for upper respiratory tract infections in the outpatient setting by Adeel A. Butt, Sherin Shams, Atika Jabeen, Asma Ali Al-Nuaimi, Jeyaram Illiayaraja Krishnan, Aimon B. Malik, Samah Saleem, Maryam Hassan Abdulaziz, Naheel Ismail Seyam, Kamran Aziz, Dalia Kandil, Anil G. Thomas, Hanaa Nafady-Hego, Muzna I. Lone, Jameela Al Ajmi, Zain A. Bhutta, Noora AlSulaiti, Wael E. Said Hussein, Sandy Semaan, Samya Ahmad Al-Abdulla, Mohamed Ghaith Al-Kuwari, Abdul-Badi Abou-Samra

“…The relative reduction was 20.9% (44.9% vs. 35.5%; p < 0.001) between the two groups. …”
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AgriChainSync: A Scalable and Secure Blockchain-Enabled Framework for IoT-Driven Precision Agriculture by Hassam Ahmed Tahir, Walaa Alayed, Waqar Ul Hassan, Fahad Nabi, Truong X. Tran

“…The rapid advancement of precision farming, automated irrigation systems, and predictive analytics has revolutionized agriculture, but these innovations also introduce new challenges, particularly in data integrity and security. …”
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SHapley Additive exPlanations (SHAP) for Landslide Susceptibility Models: Shedding Light on Explainable AI by H. Al-Najjar, B. Kalantar, B. Pradhan, G. Beydoun, N. Ueda

“…Various evaluation metrics, including overall accuracy and precision-recall, are employed to assess the predictive capabilities of each model. The findings reveal the strengths and limitations of both models, providing valuable insights for stakeholders and decision-makers involved in land use planning and disaster preparedness. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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Variable Speed Limit Strategies Based on the Macro Hierarchical Control Traffic Flow Model by Shubin Li, Tao Wang, Hualing Ren, Baiying Shi, Xiangke Kong, Jianyong Chai, Xuejuan Wang

“…The dynamic OD estimation model is used to produce the real traffic information, which is loaded to the traffic network. Then, the prediction information of traffic variables and the VSL strategy are introduced to macro hierarchical control traffic flow model. …”
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Dispatching strategy of shared bicycles for morning peak tidal travel based on spatial distribution by Xiangyu Lei, Jiaqi Yang

“…The study identifies the spatial distribution characteristics of the tidal phenomenon by analyzing the riding order and electronic fence data and combining them with the KD-Tree algorithm; subsequently, a demand prediction model based on the XGBoost algorithm and a hierarchical scheduling model based on the greedy algorithm are constructed to dynamically optimize the spatial distribution of the bicycle resources with the demand fluctuation as the guide. …”
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Servo Control of Shunt-Active Power Filters Using Kalman Filter With DC-Link Reference by Vijay Kumar C. V., Srinivasa Rao Gundala, Sri Kavya G., Pavan K., Murali R., Meerimatha G.

“…This reference approach may autonomously regulate adapting dc-link voltage anticipating current at most permissible source reference under varying load circumstances. Predictive modelling does this. MATLAB/Simulink integrates SAPF with the control algorithm. …”
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Signature of pre-pregnancy microbiome in infertile women undergoing frozen embryo transfer with gestational diabetes mellitus by Wenzheng Guan, Tian Zhou, Jiao Jiao, Liwen Xiao, Zhen Wang, Siyuan Liu, Fujie Yan, Fangqing Zhao, Xiuxia Wang

“…A model based on ten bacteria and ten metabolites simultaneously was used to predict the risk of GDM developing in the pre-pregnancy state with the ROC value of 0.712. …”
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Intelligent design of mixture proportions of manufactured sand concrete from environmental, economical and mechanical perspectives by Junfei Zhang, Changhai Xu, Lei Zhang, Ling Wang

“…This study proposes a multi-objective optimization (MOO) method based on machine learning (ML) and the non-dominated sorting genetic algorithm II (NSGA-II) to optimize MSC mixtures. The results indicate that the extremely randomized trees (ERT) model exhibits the best predictive performance for UCS, with an R value of 0.988 on the test set. …”
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An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…This approach provides a valuable reference for predictive maintenance and fault detection systems in industrial applications.…”
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A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy by Muhammad Aurangzeb, Yifei Wang, Sheeraz Iqbal, Md Shafiullah, Sultan Alghamdi, Zahid Ullah

“…The ring seal search (RSS) algorithm ensures the optimum compatibility of the EV charging and discharging profiles revolving around multiple objectives, such as cost of charging, peak load demand reduction, and grid stability. …”
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Comparative effects of metformin and varying intensities of exercise on miR-133a expression in diabetic rats: Insights from machine learning analysis by Elahe Alivaisi, Sabrieh Amini, Karimeh Haghani, Hori Ghaneialvar, Fatemeh Keshavarzi

“…We used the CatBoost algorithm to develop a predictive model for miR-133a expression based on metabolic parameters. …”
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A Distributed Energy Optimized Routing Using Virtual Potential Field in Wireless Sensor Networks by Haifeng Jiang, Yanjing Sun, Renke Sun, Wei Chen, Shanshan Ma, Jing Gao

“…We adopt the social welfare function from social sciences to predict equality of residual energy of neighbors after selecting different next nodes, which is used to compute the potential value in energy balance potential field. …”
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3D Volumetric Strain Distribution of the Cerro Prieto Geothermal Field Inferred From Inverse Modeling of InSAR and Leveling Data by Luis A. Gallardo, Olga Sarychikhina, Ewa Glowacka, Braulio Robles

“…We present and release a conjugate‐gradient inversion code that searches for the three‐dimensional distribution of the volumetric strain that predicts simultaneously any observed InSAR, leveling and GPS surface displacement. …”
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Local Entropy Optimization–Adaptive Demodulation Reassignment Transform for Advanced Analysis of Non-Stationary Mechanical Signals by Yuli Niu, Zhongchao Liang, Hengshan Wu, Jianxin Tan, Tianyang Wang, Fulei Chu

“…This method provides strong support for mechanical fault diagnosis, condition monitoring, and predictive maintenance, making it particularly suitable for real-time analysis of multi-component and cross-frequency signals.…”
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Artificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency by Yaling Hew, Duygu Kutuk, Tuba Duzcu, Yagmur Ergun, Murat Basar

“…AI’s data analysis and pattern recognition capabilities offer valuable predictive insights, enhancing personalized treatment plans and increasing success rates in fertility treatments. …”
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Integrating Multiple Hierarchical Parameters to Achieve the Self-Compensation of Scale Factor in a Micro-Electromechanical System Gyroscope by Rui Zhou, Rang Cui, Daren An, Chong Shen, Yu Bai, Huiliang Cao

“…This is achieved by integrating the primary and secondary relevant parameters of the scale factor using the partial least squares regression (PLSR) algorithm. In this paper, a scale factor prediction model is presented. …”
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Distributed OPGW abnormal vibration monitoring and forewarning based on LSTM by Tianlong Bu, Hanpeng Kou, Dapei Zhang, Zhenhua Feng, Helen Law, Bin Wang

“…In addition, the abnormal vibration forewarning method is analyzed by correlating predicted data with historical data. Experimental results in Hulunbuir demonstrate that the LSTM algorithm performs well in predictions over a 22-h period, evidenced by a root mean square error of 0.8729 and a determination coefficient (R2) of 0.9938 for the fitting curve with actual results. …”
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