IRGL-RRI: interpretable graph representation learning for plant RNA–RNA interaction discovery by Qingquan Liao, Xuchong Liu, Wei Zhao, Yu Tong, Fangzheng Xu, Xinxin Liu, Yifan Chen

“…To address this, this study proposes an interpretable graph representation model for accurate plant RRI prediction. The model enriches sample information by extracting features of different bases from plant RNA data and reconstructs these features using an algorithmic hierarchy approach to capture more complex patterns. …”
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A simple and efficient plasticity-fracture constitutive model for confined concrete by Hadi Meidani

“…A plasticity-fracture constitutive model is presented for prediction of the behavior of confined plain concrete. …”
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Advancing agriculture with machine learning: a new frontier in weed management by Mohammad MEHDIZADEH, Duraid K. A. AL-TAEY, Anahita OMIDI, Aljanabi Hadi Yasir ABBOOD, Shavan ASKAR, Soxibjon TOPILDIYEV, Harikumar PALLATHADKA, Renas Rajab ASAAD

“…Validation and refinement of these algorithms are needed for practical application.…”
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Engineering project management technology based on visual simulation module and particle swarm optimization by Hua Tian

“…The particle swarm multi-objective optimization algorithm performed well in reducing project cost prediction errors. …”
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Comparative study on inversion of the unsaturated hydraulic parameters using optimization and Bayesian estimation methods by KE Fengqiao, MAN Jun, ZENG Lingzao, WU Laosheng

“…However, this method is sensitive to the initial guess of parameters, and the obtained predictions occasionally deviate from the measurements. 2) The MCMC algorithm can provide state predictions which better fit measurements. …”
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Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection by J. Pérez-Aracil, C. Peláez-Rodríguez, Ronan McAdam, Antonello Squintu, Cosmin M. Marina, Eugenio Lorente-Ramos, Niklas Luther, Verónica Torralba, Enrico Scoccimarro, Leone Cavicchia, Matteo Giuliani, Eduardo Zorita, Felicitas Hansen, David Barriopedro, Ricardo García-Herrera, Pedro A. Gutiérrez, Jürg Luterbacher, Elena Xoplaki, Andrea Castelletti, S. Salcedo-Sanz

“…This research can potentially enhance our understanding of HW drivers and predictability.…”
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Research on lightweight malware classification method based on image domain by SUN Jingzhang, CHENG Yinan, ZOU Binghui, QIAO Tonghua, FU Sizheng, ZHANG Qi, CAO Chunjie

“…To address the high deployment costs and long prediction times associated with traditional malware classification methods, a lightweight malware visualization classification method was proposed. …”
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HR Management Big Data Mining Based on Computational Intelligence and Deep Learning by Genliang Zhao, Zhe Xue

“…To this end, this paper proposes an end-to-end competency-aware job requirement generation framework to automate the job requirement generation, and the prediction based on competency themes can realize the skill prediction in job requirements. …”
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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

“…<b>Objective:</b> This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. …”
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Research on Identification Technology of Explosive Vibration Based on EEMD Energy Entropy and Multiclassification SVM by Huayuan Ma, Xinghua Li, Qiang Liu, Xie Xingbo, Chong Ji, Changxiao Zhao

“…Taking eigenvector composed of CEE (components of energy entropy) as input, multiclassification SVM algorithm was used for training and prediction. Prediction accuracy was more than 80%. …”
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Energy-efficient strategy for data migration and merging in Storm by Yonglin PU, Jiong YU, Liang LU, Ziyang LI, Chen BIAN, Bin LIAO

“…Storm is suffering the problems of high energy consumption but low efficiency.Aiming at this problem,the resource constraint model,the optimal principle of data reorganization in executors and node voltage reduction principle were proposed based on the analysis of the architecture and topology of Storm,and further the energy-efficient strategy for data migration and merging was put forward in Storm(DMM-Storm),which was composed of resource constraint algorithm,data migration and merging algorithm as well as node voltage reduction algorithm.The resource constraint algorithm estimates whether work nodes are appropriate for data migration according to the resource constraint model.The data migration and merging algorithm designs an optimal method to migrate data according to the the optimal principle of data reorganization in executors.The node voltage reduction algorithm reduces voltage of work nodes according to node voltage reduction principle.The experimental results show that the DMM-Storm can reduce energy consumption efficiently without affecting the performance of cluster compared with the existing researches.…”
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Energy-efficient strategy for data migration and merging in Storm by Yonglin PU, Jiong YU, Liang LU, Ziyang LI, Chen BIAN, Bin LIAO

“…Storm is suffering the problems of high energy consumption but low efficiency.Aiming at this problem,the resource constraint model,the optimal principle of data reorganization in executors and node voltage reduction principle were proposed based on the analysis of the architecture and topology of Storm,and further the energy-efficient strategy for data migration and merging was put forward in Storm(DMM-Storm),which was composed of resource constraint algorithm,data migration and merging algorithm as well as node voltage reduction algorithm.The resource constraint algorithm estimates whether work nodes are appropriate for data migration according to the resource constraint model.The data migration and merging algorithm designs an optimal method to migrate data according to the the optimal principle of data reorganization in executors.The node voltage reduction algorithm reduces voltage of work nodes according to node voltage reduction principle.The experimental results show that the DMM-Storm can reduce energy consumption efficiently without affecting the performance of cluster compared with the existing researches.…”
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Constructing a tumor immune microenvironment-driven prognostic model in acute myeloid leukemia using bioinformatics and validation data by Amir Abbas Navidinia, Ali Keshavarz, Bentol Hoda Kuhestani Dehaghi, Reza Khayami, Najibe Karami, Vahid Amiri, Mehdi Allahbakhshian Farsani

“…ROC analysis demonstrated predictive accuracy (AUC: 63.38–68.5% for 1–5-year survival). …”
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Atrial fibrillation and chronic kidney disease: main clinical characteristics of patients in selected subjects of the Russian Federation by M. A. Druzhilov, T. Yu. Kuznetsova, O. Yu. Druzhilova, U. D. Arustamova, D. V. Gavrilov, A. V. Gusev

“…The information was taken from the Webiomed predictive analytics platform, including 80775 patients with AF (men, 42,5%, mean age, 70,0±14,3 years) who underwent outpatient and/or inpatient treatment in medical organizations in 6 Russian subjects in 2016-2019 with data on blood creatinine levels. …”
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Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification by Zhan Wang, Zhaokai Zhou, Shuai Yang, Zhengrui Li, Run Shi, Ruizhi Wang, Kui Liu, Xiaojuan Tang, Qi Li

“…Lastly, various machine learning algorithms were applied to identify novel potential targets of BLCA, following which their pro-tumorigenic effects were experimentally verified. …”
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Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis by Zhenhui Huo, Chongyi Fan, Kehan Li, Chenyue Xu, Yingzhen Niu, Fei Wang

“…Functional enrichment, drug target prediction, and target gene-related miRNA prediction were performed for these genes. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks by Jhony Andrés Guzmán-Henao, Rubén Iván Bolaños, Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Jesús C. Hernández

“…The results demonstrated the effectiveness of these algorithms. NSGA-II achieved the best performance, with reductions of 32.84% in energy losses and 42.41% in operating costs (with standard deviations of 0.21% and 0.39%, respectively) for the urban system; and reductions of 21.87% in energy losses and 43.36% in operating costs (with standard deviations of 0.07% and 0.24%, respectively) for the rural system. …”
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Optimal Operation Strategy of Cascade Hydro-Wind-Solar-Pumped Storage Complementary System Considering Flexible Regulation Ability by XIA Jinlei, TANG Yijie, WANG Lingling, JIANG Chuanwen, GU Jiu

“…To overcome the limitations of traditional models such as low predictive accuracy and the subjective selection of long short-term memory (LSTM) hyperparameters, the particle swarm optimization (PSO) algorithm is used to optimize the parameters of LSTM and the optimized LSTM model is then used to forecast the output of wind and solar power. …”
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A novel anthropometric method to accurately evaluate tissue deformation by Chongyang Ye, Xiaolu Li, Haiyan Song, Yu Shi, Ruixin Liang, Jun Zhang, Ka Po Lee, Zhaolong Chen, Beibei Zhou, Raymond Kai-Yu Tong, Kit-Lun Yick, Sun-Pui Ng, Joanne Yip

“…However, displacement from movement affects alignment so accurately measuring tissue deformation with different wear conditions becomes challenging.MethodsTo address this issue, an analytical model is constructed to predict tissue deformation by using the Boussinesq solution, which is based on the elastic theory and stress function method. …”
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