dP/dtmax: An underestimated prognostic factor in large animal infarction model by Rita Garamvölgyi, Dénes Kőrösi, Ottó Tátrai, Emőke Bodor, Dániel Fajtai, Kornélia Farkas, András Vorobcsuk

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Applicability of a computer retinal model for scale-dependent investigation of legibility problems by Gábor Dömötör, András Horváth

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Improvement of modeling on the Pidgeon process for magnesium production by introducing the variable thermophysical properties by Li R.-B., Wang C., Wang Z., Yang P.-X., Xue F., Liu F.-Q., Zhang S.-J.

“…The variable thermophysical properties were introduced into the coupling model of heat transfer and reduction reaction in the Pidgeon process to improve the accuracy of the numerical calculation. …”
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Study on Colloidal Model of Petroleum Residues through the Attraction Potential between Colloids by Long-li Zhang, Guo-hua Yang, Chao-he Yang, Guo-he Que

“…The Van der Waals attractive potential energy between colloids corresponding to various models could be calculated from the fractional composition and the Hamaker constants of every component. …”
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Review of Digital Construction of UHV Projects Based on Building Information Modeling Technology by QI Lizhong, LIU Ding, ZHANG Zhuoqun, XIE Rongzhen, RONG Jingguo, ZHANG Su, YUAN Bo, SUN Yi

Subjects: “…uhv project|new type of power system|digital transformation|building information modeling （bim）|smart construction sites…”
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Theories, models and strategies in developing an effective HIV/AIDS campaign in South Africa by Mpine Qakisa

“…Another problem may be that most health programme interventions have not been based on theories and models. Theories play a pivotal role in planning and implementing campaign strategies. …”
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Epigenetic Research of Neurodegenerative Disorders Using Patient iPSC-Based Models by Rubén Fernández-Santiago, Mario Ezquerra

“…Current in vitro systems of induced pluripotent stem cells (iPSCs) generated by cell reprogramming of somatic cells from patients have provided valuable disease models recapitulating key pathological molecular events. …”
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Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects by Miaojie Xia, Yuqi Zhang, Ruiqin Tian

“…This paper studies the variable selection of high-dimensional spatial autoregressive panel models with fixed effects in which a matrix transformation method is applied to eliminate the fixed effects. …”
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Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model by Nhat-Duc Hoang, Anh-Duc Pham, Quoc-Lam Nguyen, Quang-Nhat Pham

“…This research carries out a comparative study to investigate a machine learning solution that employs the Gaussian Process Regression (GPR) for modeling compressive strength of high-performance concrete (HPC). …”
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Social Force Model Calibration for Preschool Children Evacuations Based on Multiscenario Experiments by Qingjie Qi, Ruifeng She, Han Liu, Jingwen Zhang, Yue Zhang

“…The social force model has been widely used in simulating and analyzing pedestrian behavior. …”
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Exploring Deep Learning–Based Models for Sociocultural African Food Recognition System by Grace Ataguba, Mona Alhasani, James Daniel, Emeka Ogbuju, Rita Orji

“…We present the design and evaluation of a sociocultural app for African food recognition using deep learning models such as transfer learning. Deep learning models have multiple processing layers that make them robust in image recognition. …”
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Multiple-Modal-Coupling Modeling and Stability Analysis of Cold Rolling Mill Vibration by Lingqiang Zeng, Yong Zang, Zhiying Gao

“…An effective dynamic model is the basis for studying rolling mill vibration. …”
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Multiperiod Coordination Models of Coal-Electricity Supply Chain with Double Price Regulations by Hongjun Peng, Meihua Zhou, Fudong Wang

“…Using game models, we study multiperiod coordination contract and model of coal-electricity supply chain under the condition of double price regulations to alleviate the price conflicts of coal and electricity enterprises. …”
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MODELING OF THE SAND BLEND PREPARATION PROCESS IN HIGH-SPEED MIXER OF BATCH OPERATION by A. P. Melnikov

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A Semi-Stochastic Propagation Model for the Study of Beam Tilting in Cellular Systems by Konstantinos B. Baltzis

“…A semi-stochastic propagation model is presented and applied to the study of the impact of the base station beam tilting in cellular communications. …”
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Limiting the development of anti-cancer drug resistance in a spatial model of micrometastases by Ami B. Shah, Katarzyna A. Rejniak, Jana L. Gevertz

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Mood Detection from Physical and Neurophysical Data Using Deep Learning Models by Zeynep Hilal Kilimci, Aykut Güven, Mitat Uysal, Selim Akyokus

“…A wide range of comparative and extensive experiments shows that the proposed model exhibits noteworthy results compared to the state-of-art studies.…”
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Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management by Zhuojie Li

“…According to the BP neural network algorithm, for the problem that the input variables of the BP network cannot be automatically optimized during the modeling process of the multivariable complex system, it is used to establish a neural network optimization algorithm according to the gray correlation analysis (GM2 BPANN). …”
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Optimal control of a mathematical model for cancer chemotherapy under tumor heterogeneity by Shuo Wang, Heinz Schättler

“…We consider cancer chemotherapy as an optimal control problem with the aim to minimize a combination of the tumor volume and side effects over an a priori specified therapy horizon when the tumor consists of a heterogeneous agglomeration of many subpopulations. The mathematical model, which accounts for different growth and apoptosis rates in the presence of cell densities, is a finite-dimensional approximation of a model originally formulated by Lorz et al. [18,19] and Greene et al. [10,11] with a continuum of possible traits. …”
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Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning by Won Joong Kim, Gunho Jung, Sun-Yong Choi

“…Additionally, we demonstrate that machine-learning models, namely, SVR, RNN, LSTM, and GMDH, outperform the model-driven methods (in this case, the Nelson–Siegel model). …”
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