Parkinson's disease screening using a fusion of gait point cloud and silhouette features. by Tee Connie, Timilehin B Aderinola, Jia You Ong, Thian Song Ong, Michael Kah Ong Goh, Bayu Erfianto, Bedy Purnama, Ming De Lim, Nor Izzati Saedon

“…Therefore, we propose a fusion of appearance-based and model-based gait features for PD prediction. First, we extracted keypoint coordinates from gait captured in videos and modeled these keypoints as a point cloud. …”
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A simple and efficient eight node finite element for multilayer sandwich composite plates bending behavior analysis by Khmissi Belkaid, Nadir Boutasseta, Hamza Aouaichia, Djamel Eddine Gaagaia, Badreddine Boubir, Adel Deliou

“…The governing equations of the element (constitutive, virtual work and equilibrium equations) are implemented for the prediction of approximate solutions of deflections and stresses of sandwich plates linear elastic problems. …”
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MicroRNAs as Prognostic Biomarkers for Atrial Fibrillation Recurrence After Catheter Ablation: Current Evidence and Future Directions by Emmanouil P. Vardas, Evangelos Oikonomou, Panos E. Vardas, Dimitris Tousoulis

“…This review presents the existing evidence on the prognostic role of microRNAs (miRNAs) in the prediction of AF recurrence after catheter ablation. …”
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Optimization of Process Parameters for Vertical-Faced Polypropylene Bottle Injection Molding by Youmin Wang, Zhichao Yan, Xuejun Shan

“…By finding the best combination of process parameters, the orthogonal experiment was completed, the results were analyzed by range analysis, and the order of influence of each process parameter on each direction of optimization was obtained. The prediction dates of the infusion bottle were gained under various parameters, a comprehensive quality evaluation index of the bottle was formulated, and the multiobjective optimization problem of injection molding process was transformed into a single-objective optimization problem by the integrated weighted score method. …”
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Civilizational Analysis in Historical Sociology and Explanations of the “Soviet Collapse" by M. V. Maslovskiy

“…The article considers the prediction of disintegration of the USSR offered by Randall Collins and Johann Arnason's analysis of the Soviet version of modernity. …”
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StreetSurfaceVis: a dataset of crowdsourced street-level imagery annotated by road surface type and quality by Alexandra Kapp, Edith Hoffmann, Esther Weigmann, Helena Mihaljević

“…As the frequency distribution of road surface types and qualities is highly imbalanced, we propose a sampling strategy incorporating various external label prediction resources to ensure sufficient images per class while reducing manual annotation. …”
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Study on the Deformation Mechanism of Soft Rock Roadway under Blasting Disturbance in Baoguo Iron Mine by Hong-di Jing, Yuan-hui Li, Kun-meng Li

“…Afterwards, according to monitoring data of mining blasting vibration, a suitable safety blasting prediction model for Baoguo Iron Mine was determined. …”
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Optimization of Hydraulic Machinery Bladings by Multilevel CFD Techniques by Susanne Thum, Rudolf Schilling

“…After having got a convergent solution, the optimization process is repeated on the second level using a full 3D Euler code yielding a more accurate flow prediction. Finally, a 3D Navier-Stokes code is applied on the third level to search for the optimum optimorum by means of a fine-tuning of the geometrical parameters. …”
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SUPPRESSION OF SUBGENOMIC HEPATITIS C VIRUS RNA REPLICON REPLICATION IN Huh-7 CELLS BY THE NS3 PROTEASE INHIBITOR SCH5030334: A STOCHASTIC MATHEMATICAL MODEL by E. L. Mishchenko, N. V. Ivanisenko, I. R. Akberdin, P. S. Demenkov, V. A. Likhoshvai, N. A. Kolchanov, V. A. Ivanisenko

“…Thus, it is pertinent to applymathematical modelingto prediction ofthe efficiencyofnew candidate pharmaceuticals. …”
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A Study of English Informative Teaching Strategies Based on Deep Learning by Yaojun Guo

“…In this paper, we study and design a deep learning-based English informatics teaching system to develop a deep learning-based scoring prediction model. The model incorporates deep learning models based on word embedding and text convolutional networks, which can uncover the hidden interest features of academics for English. …”
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Analysis of Shunted Screen Gravel Pack Process and Calculation of Friction in Deepwater Horizontal Wells by Fei Xu, Shengtian Zhou, Chong Zhang, Yi Yu, Zhao Dong

“…The model and software can provide technical support for the prediction and optimization of gravel packing parameters in the future.…”
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Performance of Geosynthetic-Reinforced and Cement-Fly Ash-Gravel Pile-Supported Embankments over Completely Decomposed Granite Soil: A Case Study by Lijun Wu

“…Five methods widely adopted in current designing were used to calculate the pile efficacy. The prediction for pile efficacy by the Nordic method, BS8006, and its modified version is significantly higher than measured values. …”
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State of Health Estimation of Li-Ion Batteries Based on Differential Thermal Voltammetry and Gaussian Process Regression by ZHU Haoran, CHEN Ziqiang, YANG Deqing

“…The results show that the established model can better approximate the experimental value and shorten the training and prediction time. The average absolute error of SOH estimation is 0.67%—0.97%, which is 20%—30% lower than that of single-step GPR. …”
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Crack propagation in fracture mechanical graded structures by B. Schramm, H.A. Richard

“…In this context, the developed TSSR-concept is presented which allows the prediction of crack propagation in fracture mechanical graded structures considering the loading situation (Mode I, Mode II and plane Mixed Mode) and the material gradation. …”
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Generalized cue reactivity in rat dopamine neurons after opioids by Collin M. Lehmann, Nora E. Miller, Varun S. Nair, Kauê M. Costa, Geoffrey Schoenbaum, Khaled Moussawi

“…A widely accepted assumption is that drugs of abuse result in disparate dopamine responses to cues that predict drug vs. natural rewards. The leading hypothesis is that drug-induced dopamine release represents a persistently positive reward prediction error that causes runaway enhancement of dopamine responses to drug cues, leading to their pathological overvaluation. …”
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Comprehensive genome annotation of Trilocha varians, a new model species of Lepidopteran insects by Jung Lee, Toshiaki Fujimoto, Katsushi Yamaguchi, Shuji Shigenobu, Ken Sahara, Toru Shimada

“…To facilitate further use of T. varians, we developed genome annotation information on the chromosome-scale assembly of T. varians previously published by our group. 9 RNA-seq datasets and 2 Iso-seq datasets were submitted for transcriptome-based gene prediction. As a result, 16,266 protein-coding genes were predicted on the latest genome assembly, and 98.6% of BUSCO sequences were present in our gene models. …”
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Compressive sensing based data gathering algorithm over unreliable links in WSN by Ce ZHANG, Xia ZHANG, Ou LI, Guan-lin MEI, Zhe HAN, Da-long ZHANG, Guang-yi LIU

“…To solve the problem that the ubiquitous unreliable links in the WSN influence the performance of the compressive sensing (CS) based data gathering,first the relationship between the reconstruction SNR of CS-based data gathering algorithm and the bit-error-ratio (BER) were simulated quantitatively.Then classify two cases were classified,namely light-payload and heavy-payload,relying on the analysis of wireless link packet loss characteristics.The random packet loss model was conceived to describe the packet loss under light-payload scenario.Further the neighbor topology spatial correlation prediction-based CS data gathering (CS-NTSC) algorithm was proposed,which utilized the nodes spatial correlation to reduce the impact of error.Additionally,the node pseudo-failure model was conceived to describe the packet loss occurred in network congestion,and then the sparse schedule-aided CS data gathering (CS-SSDG) algorithm were conceived,for the purpose of changing the sparsity of measurement matrix and avoiding measurements amongst the nodes affected by unreliable links,thus weakening the impact of error/loss on data reconstruction.Simulation analysis indicates that the proposed algorithms are not only capable of improving the accuracy of the data reconstruction without extra energy,but also effectively reducing the impact affected by the unreliable links imposed on CS-based data gathering.…”
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Research on 2.4 GHz Wireless Channel Propagation Characteristics in a Steel Ship Cabin by Wanli Tu, Hong Xu, Yiqun Xu, Qiubo Ye, Mingxian Shen

“…A 3D ray-tracing model of 2.4 GHz wave propagation in the ship cabin is established, a multipath propagation prediction is carried on, and receiving power is calculated. …”
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Leakage Analysis of PEMFC Sealing System Considering Temperature Cycling by Zhi Chen, Yanfeng Xing, Juyong Cao, Fuyong Yang, Xiaobing Zhang

“…Addressing the leakage rate prediction problem of the PEMFC sealing system is of great importance for its stable operation. …”
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An Improved Deep Learning Model for Electricity Price Forecasting by Rashed Iqbal, Hazlie Mokhlis, Anis Salwa Mohd Khairuddin, Munir Azam Muhammad

“…Then, an improved LSTM prediction module is proposed to forecast electricity prices where LiSHT layer is adopted to optimize the parameters of the heterogeneous LSTM. …”
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