Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…The results reveal the following: (1) NTU and EER levels steadily improved from 2004 to 2022, although coordination between cities still requires enhancement; (2) CCD exhibited a temporal pattern of “progressive escalation and continuous optimization,” and a spatial pattern of “dual-core leadership and regional diffusion,” with most cities shifting from NTU-lagged to synchronized development; (3) environmental regulations (MAR) and fixed asset investment (FIX) emerged as the most influential CCD drivers, and significant nonlinear interactions were observed, particularly those involving population size (HUM); (4) CCD drivers exhibited complex spatiotemporal heterogeneity, characterized by “stage dominance—marginal variation—spatial mismatch.” …”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…Different element quantitative models were constructed for each rock type. The kNN algorithm was selected using cross-validation to determine the optimal k value, and the key punishment parameter C and RBF width parameter γ of the SVM algorithm were determined using a grid search method. …”
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Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach by Gideon Addo, Bismark Amponsah Yeboah, Michael Obuobi, Raphael Doh-Nani, Seidu Mohammed, David Kojo Amakye

“…Chi-square tests assessed diabetes-symptom associations, and the Boruta algorithm examined feature influence. Seven ML classification models were evaluated for predictive accuracy. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…Through rigorous analysis, the properties with the most significant influence on solubility were identified and subsequently used as input features for four ensemble machine learning algorithms: Random Forest, Extra Trees, XGBoost, and Gradient Boosting. …”
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Blockchain-Assisted Verifiable and Multi-User Fuzzy Search Encryption Scheme by Xixi Yan, Pengyu Cheng, Yongli Tang, Jing Zhang

“…Locality-sensitive hashing and bloom filters are used to realize multi-keyword fuzzy search, and the bigram segmentation algorithm is optimized for keyword conversion to improve search accuracy. …”
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Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

“…This study employed multiple machine learning models to perform risk prediction and result exploration for first-trimester Down syndrome in East Asian populations, aiming to identify an optimal risk prediction model that will enhance future predictions of Down syndrome risk and improve the efficiency of the screening process.Patients and Methods: This study collected data from the Down syndrome screening database at Taipei Chang Gung Memorial Hospital from May 1, 2018, to February 29, 2024. …”
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Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. …”
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Frequency Regulation Provided by Doubly Fed Induction Generator Based Variable-Speed Wind Turbines Using Inertial Emulation and Droop Control in Hybrid Wind–Diesel Power Systems by Muhammad Asad, José Ángel Sánchez-Fernández

“…To achieve such goals, we used the above-mentioned proposed controls (EI&P and PC) and optimally tuned them using the Student-Psychology-Based Algorithm (SPBA). …”
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“Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

“…The correction has the most significant impact in northwestern Zhejiang, while its effects are less pronounced in the northeastern coastal areas. (2) Both overall correction and regional correction improve forecast accuracy across various precipitation thresholds. …”
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Unsupervised Anomaly Detection on Metal Surfaces Based on Frequency Domain Information Fusion by Wenfei Wu, Tao Tao, Jinsheng Xiao, Yichu Yao, Jianfeng Yang

“…In addition, a feature selection module is designed to improve the anomaly detection capability and reduce the computational redundancy by selecting the most representative subset of features. …”
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Spatiotemporal Correlation Based Fault-Tolerant Event Detection in Wireless Sensor Networks by Kezhong Liu, Yang Zhuang, Zhibo Wang, Jie Ma

“…Reliable event detection is one of the most important objectives in wireless sensor networks (WSNs), especially in the presence of faulty nodes. …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

“…The Back Propagation Nondominated Sorting Genetic Algorithm-II (BP-NGA) model consistently yielded positive results for most WQI. (2) Water quality in Dianchi varied significantly by region and season. (3) It was recommended to build wetlands and ecological parks on the southwest side of Dianchi and improve sewage interception pipelines on the northeast side to lessen the risk of eutrophication by reducing the inflow of nitrogen and phosphorus.…”
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Enhanced engine misfire diagnosis through integration of vibration and acoustic emission signals using artificial neural networks by Mohamed H. Abdelati, M. Mourad, Al-Hussein Matar, M. Rabie

“…After all the features were put into a complete matrix, the selection algorithms chose the most essential ones for classifying the data. …”
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Novel method for robust bilateral filtering point cloud denoising by Huan Yang, Wei Wang, Yue Wang, Peng Wang

“…Moreover, when compared to algebraic point set surfaces (APSS), robust implicit moving least squares (RIMLS), anisotropic weighted locally optimal projection (AWLOP), bilateral filtering, and guided filtering point cloud denoising algorithms, the proposed method consistently achieved the smallest MSE and the highest SNR in most cases on the dataset used in this study.…”
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Proteomics mapping of cord blood identifies haptoglobin "switch-on" pattern as biomarker of early-onset neonatal sepsis in preterm newborns. by Catalin S Buhimschi, Vineet Bhandari, Antonette T Dulay, Unzila A Nayeri, Sonya S Abdel-Razeq, Christian M Pettker, Stephen Thung, Guomao Zhao, Yiping W Han, Matthew Bizzarro, Irina A Buhimschi

“…This was then subjected to 2(nd)-level validation against indicators of adverse short-term neonatal outcome. The optimal LCA algorithm combined Hp&HpRP switch pattern (most input), interleukin-6 and neonatal hematological indices yielding two non-overlapping newborn clusters with low (≤20%) versus high (≥70%) probability of IAI exposure. …”
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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…IntroductionMachine learning (ML) models have been increasingly applied to predict post-heart transplantation (HT) mortality, aiming to improve decision-making and optimize outcomes. This systematic review and meta-analysis evaluates the performance of ML algorithms in predicting mortality and explores factors contributing to model accuracy.MethodA systematic search of PubMed, Scopus, Web of Science, and Embase identified relevant studies, with 17 studies included in the review and 12 in the meta-analysis. …”
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Accelerating RRT* convergence with novel nonuniform and uniform sampling approach by Sivasankar Ganesan, Mohanraj Thangamuthu, Balakrishnan Ramalingam, Madan Mohan Rayguru, Sethu Narayanan Tamilselvan

“…Due to its asymptotic optimality, the optimal rapidly-exploring random tree (RRT*) algorithm is the most widely used among these. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…In treatment planning, AI could improve approaches by optimizing surgical resection, radiotherapy regimen, and chemotherapy protocols. …”
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A survey on resource allocation in backscatter communication networks by Yongjun XU, Haoke YANG, Yinghui YE, Qianbin CHEN, Guangyue LU

“…With the development of Internet of things (IoT) technology, wireless networks have the characteristics of massive user access, high power consumption, and high capacity requirements.In order to meet the transmission requirements and reduce energy consumption, backscatter communication technology was considered to be one of the most effective solutions to the above problems.In the fact of complex network scenarios, the improvement of spectrum efficiency, system capacity, and energy management has become an urgent problem of resource allocation areas in backscatter communications.For this problem, resource allocation algorithms in backscatter communications were surveyed.Firstly, the basic concept and different network architectures of backscatter communication were introduced.Then, resource allocation algorithms in backscatter communication networks were analyzed according to different network types, optimization objectives, and the number of antennas.Finally, the challenges and future research trends of resource allocation problems in backscatter communication networks were prospected.…”
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Development of a machine learning model for predicting renal damage in children with closed spinal dysraphism by Yu He, Wan-liang Guo, Ming-chang Zhang

“…The Shapley additive explanations (SHAP) algorithm and Local Interpretable Model-Agnostic Explanations (LIME) were used to interpret the optimal model. …”
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