Exploring the Potential Regulatory Mechanisms of Mitophagy in Ischemic Cardiomyopathy by Li Z, Kong J, Xi S, Jin Z, Yang F, Zhu Z, Liu L

“…Finally, 45 drugs targeting the biomarkers were predicted, such as Salmeterol, Histamine, Rotavirus vaccine, etc. …”
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Research on the spatial layout of the elderly care industry based on explainable machine learning: A case study of Hangzhou(基于可解释性机器学习的养老产业空间布局研究)... by 曾笑奇(ZENG Xiaoqi), 赵秋皓(ZHAO Qiuhao), 冯友建(FENG Youjian)

“…However, existing research has not sufficiently explored the factors influencing the spatial layout of elderly care facilities or how to optimally predict these layouts. This study uses Hangzhou's urban area as a case study to fill this gap. …”
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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

“…Intervention Bundled 4-component intervention including extensive provider education, a decision support algorithm, option for deferred antibiotics prescription, and monthly feedback on prescription patterns, vs. a single randomly assigned intervention (decision support algorithm). …”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…Progress in artificial intelligence and machine learning has significantly improved the capability to accurately predict the properties of nano-enhanced phase change materials (NePCMs). …”
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Personalized Federated Learning for Heterogeneous Residential Load Forecasting by Xiaodong Qu, Chengcheng Guan, Gang Xie, Zhiyi Tian, Keshav Sood, Chaoli Sun, Lei Cui

“…Based on the principle of generative adversarial network (GAN), the algorithm achieves the balance between privacy and prediction accuracy throughout the game. …”
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Design of nonlinear rubber vibration isolators with low resonant frequency and high load bearing capacity by Xiaoqi Zhang, Xin Li, Fei Du, Fucai Hu, Li Wang, Yongsheng Yu

“…The rubber isolator static and dynamic behavior prediction models suitable for engineering applications are first established, where Yeoh model is adopted for rubber strong nonlinear feature prediction. …”
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Evaluasi Kinerja MLLIB APACHE SPARK pada Klasifikasi Berita Palsu dalam Bahasa Indonesia by Antonius Angga Kurniawan, Metty Mustikasari

“…The result of confusion matrix was also good, because the number of correct predictions was far more than the number of incorrect ones. …”
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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses by Qian L, Fu B, He H, Liu S, Lu R

“…Radiomic features were extracted from the arterial, venous and delayed phases and further analysed by dimensionality reduction and selection. Four mainstream machine learning algorithm training models, namely, support vector machine (SVM), k-nearest neighbour (kNN), light gradient boosting (LightGBM) and logistic regression (LR), were constructed to determine the best classifier model. …”
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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…With the increasing application of machine learning technology in the medical field, algorithm-based diagnostic tools provide new possibilities for early prediction of breast cancer. …”
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Traffic signal active control method for short-distance intersections. by Yulin Tian, Shuqing Liu, Lu Wei, Zhen Li, Shaohu Tang, Yuchen Zhang, Tao Zhu

“…Aiming at the existing problems about the overflow prevention goal and the overall traffic efficiency guarantee being difficult to optimize at the same time in the signal control process of short-distance intersections scenario, this paper proposes a traffic signal active control method based on key state prediction. In order to construct the key state evolution trend of short-distance intersection scenarios, this paper proposes the concept of overflow index for short-distance road sections and designs the prediction method of overflow index. …”
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Parametric Model for Coaxial Cavity Filter with Combined KCCA and MLSSVR by Shengbiao Wu, Huaning Li, Xianpeng Chen

“…First, the low-dimensional tuning data is mapped to the high-dimensional feature space by kernel canonical correlation analysis, and the nonlinear feature vectors are fused by the kernel function; second, the multioutput least squares support vector regression algorithm is used for parametric modeling to solve the problems of low accuracy and poor prediction performance; third, the support vector of the parameter model is optimized by the differential evolution whale algorithm (DWA) to improve the convergence and generalization ability of the model in actual tuning. …”
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Intelligent optimization method of fracturing parameters for shale oil reservoirs in Jimsar Sag, Junggar Basin, NW China by Yunjin WANG, Fujian ZHOU, Hang SU, Leyi ZHENG, Minghui LI, Fuwei YU, Yuan LI, Tianbo LIANG

“…A separated fracturing effect prediction model is proposed, with the fracturing learning curve decomposed into two parts: (1) overall trend, which is predicted by the algorithm combining the convolutional neural network with the characteristics of local connection and parameter sharing and the gated recurrent unit that can solve the gradient disappearance; and (2) local fluctuation, which is predicted by integrating the adaptive boosting algorithm to dynamically adjust the random forest weight. …”
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Learning-based early detection of post-hepatectomy liver failure using temporal perioperative data: a nationwide multicenter retrospective study in ChinaResearch in context by Kai Wang, Qian Yang, Kang Li, Shanhua Tang, Baoluhe Zhang, Xiangyun Liao, Shunda Du, Wenguang Fu, Zhiwei Li, Huanwei Chen, Haorong Xie, Pengxiang Huang, Jieyuan Li, Qiuting Wang, Haiqing Liu, Zhiwei Huang, Pheng Ann Heng, Xueshuai Wan, Chuanjiang Li, Weixin Si

“…Importantly, our model demonstrates a high capacity for predicting clinically relevant PHLF. The clinicians' prediction assisted by our model was substantially improved over the clinician-only predictions (AUC = 0.778 vs. 0.637, P = 0.009). …”
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Efficient search, mapping, and optimization of multi‐protein genetic systems in diverse bacteria by Iman Farasat, Manish Kushwaha, Jason Collens, Michael Easterbrook, Matthew Guido, Howard M Salis

“…We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram‐positive and gram‐negative bacterial hosts. …”
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Intelligent generative design: a transfer learning-enhanced bidirectional mapping framework for customised parametric structural design by Jiajie Hu, Yayun Wang, Hua Tian, Peng Zheng, Liang Chi, Lulu Xue, Qian Su, Qing Jiang, Yong He, Lan Li, Liya Zhu

“…We employ a genetic algorithm to optimise a back-propagation neural network (GA-BPNN) for forward prediction of elastic modulus from structural parameters (porosity, pore size). …”
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Effect of Social Sustainability on Supply Chain Resilience Before, During, and After the COVID-19 Pandemic in Mexico: A Partial Least Squares Structural Equation Modeling and Evolu... by Miguel Reyna-Castillo, Alejandro Santiago, Ana Xóchitl Barrios-del-Ángel, Francisco Manuel García-Reyes, Fausto Balderas, José Ignacio Anchondo-Pérez

“…This work starts from an epistemological premise, in which non-parametric statistical methodologies and mathematical analytics are complementary perspectives to comprehensively understand the same social phenomenon. Second-generation predictive statistics, such as the PLS-SEM algorithm, have demonstrated robustness in treating multivariate social information, making it feasible to prepare data for knowledge transfer with mathematical techniques specialized for fuzzy data. …”
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Informative Path Planning Using Physics-Informed Gaussian Processes for Aerial Mapping of 5G Networks by Jonas F. Gruner, Jan Graßhoff, Carlos Castelar Wembers, Kilian Schweppe, Georg Schildbach, Philipp Rostalski

“…Physics-informed mean functions, including a detailed ray-tracing simulation, are integrated into the GP models to enhance the extrapolation performance of the GP prediction. As a central element of the GP prediction, a quantitative evaluation of different mean functions is conducted. …”
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Investigation on the Temperature Distribution of Asphalt Overlay on the Existing Cement Concrete Pavement in Hot-Humid Climate in Southern China by Zuzhong Li, Yayun Zhang, Chunguang Fa, Xiaoming Zou, Haiwei Xie, Huaxin Chen, Rui He

“…This research is to analyze the impact of meteorological factors on temperature at 2 cm depth in asphalt overlay by ReliefF algorithm and also obtain the temperature prediction model using MATLAB. …”
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FocusDet: an efficient object detector for small object by Yanli Shi, Yi Jia, Xianhe Zhang

“…SIOU multi-dimension accurately locates the prediction box, and SoftNMS uses the Gaussian algorithm to remove redundant prediction boxes. …”
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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…Results demonstrate three key findings: (1) By introducing prototype learning, a meta-learning approach, to guide model updates, we achieved precise assessments with small training samples, attaining an MAE of 1.02, representing 58.5–76.1% error reduction compared to conventional machine learning algorithms. …”
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