The global burden of depression attributable to childhood sexual abuse, intimate partner violence, and bullying victimization from 1990 to 2021: an analysis based on the global bur... by Zhuo Liu, Guo Mao

“…This study quantifies trends in depression burden attributable specifically to CSA, IPV, and bullying from 1990 to 2021. Methods We extracted age-standardized rates and disability-adjusted life years (DALYs) attributable to CSA, IPV, and bullying for 204 countries and territories from the GBD 2021 database (1990–2021). …”
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Short-term Load Forecasting Based on DTW K-medoids and VMD Multi-branch Neural Network for Multiple Users by Yufei WANG, Tong DU, Weiguo BIAN, Zhao ZHANG, Huiting LIU, Lijun YANG

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Spatio-Temporal Joint Planning for Integrated Energy Systems with Internet Data Center Considering Privacy Preservation by WU Chengbang, CHENG Zhijiang, LU Haifeng, YANG Handi

“…Based on the Karush-Kuhn-Tucker （KKT） conditions of the IDC and IES operational models， the operational models were transformed into additional constraints for the planning model， which were linearized using the big-M method. …”
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Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm by Jingui YI, Ziwei ZHU, Qing XIE

“…Finally, the proposed method and model are analyzed and verified by typical examples. …”
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Short-Term Wind Speed Predicting Based on Legendre Multiwavelet Transform and GRU-ENN by Xiaoyang Zheng, Xiaoheng Luo, Dezhi Liu

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Multi-Objective Optimal Power Flow of Integrated Transmission and Distribution Network Considering Node Carbon Emission Intensity by ZHANG Xianglong, YUAN Zhaoxiang, DONG Shufeng, LIU Ying, XIAO Zhihong, TIAN Yuzhou

“…[Methods] To address these challenges， a collaborative distributed optimal power flow model based on a heterogeneous decomposition algorithm was proposed. …”
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Short-term residential load forecasting via transfer learning and multi-attention fusion for EVs’ coordinated charging by Shuhua Gao, Yuanbin Liu, Jing Wang, Zhengfang Wang, Xu Wenjun, Renfeng Yue, Ruipeng Cui, Yong Liu, Xuezhong Fan

“…Although many load forecasting methods have emerged in recent years, these methods face two significant challenges: effectively capturing the impact of special events on load and requiring a substantial amount of historical data for model training. …”
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<italic>H</italic>∞ -LS Current Control Strategy for Single-Phase ANPC Rectifiers Considering Grid-Voltage Harmonics by MEI Wenqing, HU Liang, LIU Haoran

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Coordinated Scheduling of Distribution Networks and Microgrids Considering Heat Pump Load and Distributed Photovoltaic by Shihui LI, Qi WANG, Xiaobo JIA, Wenchuan WU, Huayang LIANG, Lin ZHU

“…However, the strong randomness and volatility of distributed photovoltaics also bring many challenges to the operation of the power systems and make the power grids face such problems as severe power flow fluctuations and voltage violations. Firstly, a decomposition and coordination model is constructed for distribution networks and microgrids considering heat pumps, photovoltaics and energy storage systems , in which the heat pumps are described by the equivalent state space model. …”
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Efficient contingency analysis of power systems using linear power flow with generalized warm-start compensation by Jinyu Yu, Zhigang Li, Jiahui Zhang, Xiang Bai, Huaichang Ge, J.H. Zheng, Q.H. Wu

“…To efficiently calculate the inversion of a perturbed coefficient matrix in LPF models, a generalized decomposition method is devised based on the matrix inverse lemma and full rank decomposition. …”
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Optimization research on UAV semantic communication system based on SVD-MADRL by Yibo Yang, Yahe Tan, Liu Liu

“…The effectiveness of the two models designed for research is relatively high, both superior to traditional methods, providing a theoretical basis for optimizing the overall performance of unmanned aerial vehicle communication. …”
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Financial Market Prediction and Simulation Based on the FEPA Model by Dehui Zhou

“…When predicting the closing price of Australian stock index, the hit rate (DS) of the FEPA model decomposition method is 72.22%, 10.86% higher than the EMD-BPNN model and 3.23% higher than the EMD-LPP-BPNN model. …”
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Multi-objective design optimization of a transonic axial fan stage using sparse active subspaces by Richard Amankwa Adjei, Chengwei Fan

“…Active subspace was used to compute the active variables via singular value decomposition and a hybrid polynomial correlated function expansion was used to construct a surrogate model on the active subspace. …”
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Deep Learning Algorithm-Based Financial Prediction Models by Helin Jia

“…In this paper, a new FEPA portfolio forecasting model is based on the EMD decomposition method. The model is based on the special empirical modal decomposition of financial time series, principal component analysis, and artificial neural network to model and forecast for nonlinear, nonstationary, multiscale complex financial time series to predict stock market indices and foreign exchange rates and empirically investigate this hot area in financial market research. …”
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Modeling and Predicting Time Series with Non-stationarity and Volatility by FENG Qiang, ZHAO Jianguang, YANG Rong, NIU Baoning

“…When dealing with non-stationarity, existing deep learning models adopt a method of stabilizing the input sequences before training, which has problems of weak ability to eliminate non-stationarity or loss of information. …”
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Testing the Performance of Large-Scale Atmospheric Indices in Estimating Precipitation in the Danube Basin by Constantin Mares, Venera Dobrica, Ileana Mares, Crisan Demetrescu

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Implementation of Du Pont Model in Non-Financial Corporations by Sylvia Jencova, Eva Litavcova, Petra Vasanicova

“…In this paper, the practical application of the dynamic decomposition of the return on equity is used on the basis of the ratio indicators. …”
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DCT-Based White Blood Cell Image Enhancement for Recognition Using Deep Learning by Anh Quynh Vu, Hoan Quoc Bui, Long Tuan Nguyen, Tuyen Ngoc Le

“…Experimental results show that our method dramatically improves deep learning-based WBC recognition accuracy.…”
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MODELING OF ANISOTROPIC GROWTH AND RESIDUAL STRESSES IN ARTERIAL WALLS by Anna Zahn, Daniel Balzani

“…A method for the imitation of opening angle experiments in numerically simulated arterial segments, visualizing the deformations related to residual stresses, is presented and illustrated in a numerical example.…”
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MODELING THE TRANSFER EFFECT OF EXCHANGE RATE ON PRICES IN RUSSIA by M. G. Tiunova

“…The study is based on the apparatus of structural vector autoregressions, evaluated using Bayesian methods. The structural identifcation of the model is carried out by the recursive ranking of variables and decomposition of structural shocks elaborated by André-Louis Cholesky. …”
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