Stochastic Demand-Side Management for Residential Off-Grid PV Systems Considering Battery, Fuel Cell, and PEM Electrolyzer Degradation by Mohamed A. Hendy, Mohamed A. Nayel, Mohamed Abdelrahem

“…The simulation results indicate that the proposed method achieved total degradation cost reductions of 16.66% and 42.6% for typical summer and winter days, respectively, in addition to a reduction of the levelized cost of energy (LCOE) by about 22.5% compared to the average performance of 10,000 random operation scenarios.…”
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Integrated analysis of single-cell and bulk transcriptomics reveals cellular subtypes and molecular features associated with osteosarcoma prognosis by Feng Liu, Tingting Zhang, Yongqiang Yang, Kailun Wang, Jinlan Wei, Ji-Hua Shi, Dong Zhang, Xia Sheng, Yi Zhang, Jing Zhou, Faming Zhao

“…Multiple machine learning algorithms were applied to develop tumor purity prediction models based on transcriptomic profile of OS. …”
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Prospects of artificial intelligence for the sustainability of sugarcane production in the modern era of climate change: An overview of related global findings by Rajan Bhatt, Akbar Hossain, Debjyoti Majumder, Mandapelli Sharath Chandra, Rajiv Ghimire, Muhammad Faisal Shahzad, Krishan K. Verma, Amarinder Singh Riar, Vishnu D. Rajput, Mauro Wagner Oliveira, Adel Nisi, Riyadh S. Almalki, Viliam Bárek, Marian Brestic, Sagar Maitra

“…This study discusses the latest research on artificial intelligence (AI) in sugarcane farming, with particular attention given to soil biochemistry, disease detection, climate-smart technology for greenhouse gas emissions, yield and water productivity prediction, and cane juice biochemistry. Artificial intelligence (AI) tools, such as machine learning algorithms, can optimize irrigation, increase yields, save water, and properly estimate sugarcane production. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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Performance analysis of advanced deep learning technics: Application to solar energy forecasting and management in several cities in Chad by Osée Mounkang, Claude Vidal Aloyem Kaze, Nzoko Tayo Dieudonné, Ghislain Junior Bangoup Ntegmi, Duclair Paul Edouard Pountounynyi, Hervice Roméo Fogno Fotso, Armel Zambou Kenfack, Germaine Kenmoe Djuidje, René Tchinda

“…This study proposes a hybrid artificial intelligence model that combines LLM and LSTM methods, utilizing the Adam optimization algorithm to make hourly solar radiation predictions over a seven-day period. …”
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Machine learning-based characterization of stemness features and construction of a stemness subtype classifier for bladder cancer by Heping Qiu, Xiaolin Deng, Jing Zha, Lihua Wu, Haonan Liu, Yichen Lu, Xinji Zhang

“…Methods We used bladder cancer datasets from the TCGA and GEO databases, based on stemness gene sets from the StemChecker database, to identify stemness subtypes using the consensus clustering algorithm. We calculated the mRNA expression-based stemness index (mRNAsi) using the OCLR algorithm. …”
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A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway by Jun-luan Mo, Xi Li, Lin Lei, Ji Peng, Xiong-shun Liang, Hong-hao Zhou, Zhao-qian Liu, Wen-xu Hong, Ji-ye Yin

“…Finally, target gene prediction and functional enrichment analysis were performed on these key RNAs. …”
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Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis by Lijuan Feng, Kaiyong Bai, Limeng He, Hao Wang, Wei Zhang

“…Additionally, a nomogram model was employed to predict the diagnostic ability of biomarkers for RA. …”
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Marine soundscape forecasting: A deep learning-based approach by Shashidhar Siddagangaiah

“…Despite the rapid development of anomaly detection algorithms and deep-learning models for forecasting, their application to marine soundscapes remains unexplored. …”
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Unraveling the oxidative stress landscape in diabetic foot ulcers: insights from bulk RNA and single-cell RNA sequencing data by Jialiang Lin, Linjuan Huang, Weiming Li, Haijun Xiao, Mingmang Pan

“…Machine learning algorithms (SVM-RFE, LASSO and RF) identified BCL2 and 和FOXP2 as candidate hub DORGs for DFU diagnosis. …”
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Analysis and Validation of Autophagy-Related Gene Biomarkers and Immune Cell Infiltration Characteristic in Bronchopulmonary Dysplasia by Integrating Bioinformatics and Machine Lea... by Xiao S, Ding Y, Du C, Lv Y, Yang S, Zheng Q, Wang Z, Zheng Q, Huang M, Xiao Q, Ren Z, Bi G, Yang J

“…Subsequently, the hub genes were identified by Lasso and Cytoscape with three machine-learning algorithms (MCC, Degree and MCODE). In addition, hub genes were validated with ROC, single-cell sequence and IHC in hyperoxia mice. …”
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SUDDEN DEATH IN HYPERTROPHIC CARDIOMYOPATHY: SEARCH FOR NEW RISK FACTORS by N. S. Krylova, E. A. Kovalevskaya, N. G. Poteshkina, A. E. Demkina, F. M. Khashieva

“…The issue for prediction of SCD in this pathology does not lose its importance.Aim. …”
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Multiobjective optimization of CO2 injection under geomechanical risk in high water cut oil reservoirs using artificial intelligence approaches by Fankun Meng, Jia Liu, Gang Tong, Hui Zhao, Chengyue Wen, Yuhui Zhou, Vamegh Rasouli, Minou Rabiei

“…Therefore, a hybrid optimization framework was designed that combines artificial intelligence methods (Support Vector Regression with the Gaussian kernel, Gaussian-SVR or Long Short-Term Memory, LSTM) and multi-objective optimization algorithms (multiple objective particle swarm optimization, MOPSO or Non-dominated Sorting Genetic Algorithm II, NSGA-II) to find the optimal CO2 injection and production strategies under different water cut. …”
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Formation of a heterogeneous group of UAVS with a reasonable number of false and real drones by Volodymyr Prymirenko, Andrii Demianiuk, Roman Shevtsov, Serhii Bazilo, Andrey Pilipenko, Mykola Vovchanskyi

“…The availability of the developed mathematical model, algorithm, and program code makes it possible to predict the possible results of the combat use of heterogeneous groups of UAVs based on the initial parameters and to substantiate recommendations for a possible composition of such groups.…”
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Color-Sensitive Sensor Array Combined with Machine Learning for Non-Destructive Detection of AFB₁ in Corn Silage by Daqian Wan, Haiqing Tian, Lina Guo, Kai Zhao, Yang Yu, Xinglu Zheng, Haijun Li, Jianying Sun

“…The combined 1st D-PCA-KNN model showed optimal prediction performance, with determination coefficient (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>R</mi><mi>p</mi><mn>2</mn></msubsup></mrow></semantics></math></inline-formula> = 0.87), root mean square error (<i>RMSEP</i> = 0.057), and relative prediction deviation (<i>RPD</i> = 2.773). …”
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Estimation of Canopy Chlorophyll Content of Apple Trees Based on UAV Multispectral Remote Sensing Images by Juxia Wang, Yu Zhang, Fei Han, Zhenpeng Shi, Fu Zhao, Fengzi Zhang, Weizheng Pan, Zhiyong Zhang, Qingliang Cui

“…The RF model, which outperforms the other models in terms of the prediction effect in multiple growth stages, can effectively predict the SPAD value in the leaves of apple trees and provide a reference for the growth status monitoring and precise management of orchards.…”
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Estimating Winter Canola Aboveground Biomass from Hyperspectral Images Using Narrowband Spectra-Texture Features and Machine Learning by Xia Liu, Ruiqi Du, Youzhen Xiang, Junying Chen, Fucang Zhang, Hongzhao Shi, Zijun Tang, Xin Wang

“…Subsequently, machine learning algorithms were applied to develop estimation models for winter canola biomass. …”
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Pilot Protection of New Energy Transmission Line in Active Distribution Network Based on 5G Communication by Tiecheng LI, Hui FAN, Weiming ZHANG, Xianzhi WANG, Yihong ZHANG, Zhihui DAI

“…Traditional pilot differential protection will have the problem of reliability reduction or even failure to operate after the access of new energy stations. …”
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Quantitative Analysis of Structural Parameters Importance of Helical Temperature Microfiber Sensor by Artificial Neural Network by Juan Liu, Minghui Chen, Hang Yu, Jinjin Han, Hongyi Jia, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, Hao Dai

“…The relative output intensities of HMF sensor at different temperatures are predicted by the BPNN with the HMF&#x2019;s structural parameters as the input variables. …”
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In Silico Analysis of Coding/Noncoding SNPs of Human RETN Gene and Characterization of Their Impact on Resistin Stability and Structure by Lamiae Elkhattabi, Imane Morjane, Hicham Charoute, Soumaya Amghar, Hind Bouafi, Zouhair Elkarhat, Rachid Saile, Hassan Rouba, Abdelhamid Barakat

“…Stability analysis predicted 9 nsSNPs (I32S, C51Y, G58E, G58R, C78S, G79C, W98C, C103G, and C104Y) which can decrease protein stability with at least three out of the four algorithms used in this study. …”
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