Retinal Nerve Fiber Layer and Macular Ganglion Cell Layer Thickness in Subjects Suffering from Diabetes Mellitus: An Observational Study by Anujja Gharat, Nayana Anil Potdar, Salma Mohd Iqbal Tabani, Burhanuddin Kaidjoher Fakhri, Darshana B. Rathod, Twinkle Choksi

“…Purpose: The purpose of this study was to investigate the relationship of retinal nerve fiber layer (RNFL) and ganglion cell–inner plexiform layer (GCIPL) thickness in between normal healthy eyes and those affected by diabetes mellitus (DM) and also associate it with the extent of the disease. …”
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A performance-driven hybrid text-image classification model for multimodal data by Swati Gupta, Bal Kishan

“…Abstract Deep learning is transformed by a hybrid model combining text and image processing in a transforming approach to categorization chores. …”
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A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance by Pedro Juan Rivera Torres, Chen Chen, Sara Rodríguez González, Orestes Llanes Santiago

“…This concept was tested using a PBN model of an ultrasound welding process and its machines. …”
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Modeling of thermophysical processes with moderate cryogenic effect on the periodontal zone using a thermoelectric cooling system by O. V. Evdulov, S. G. Magomedova, E. A. Dzhabrailova

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Hydrodynamic Processes of Incipient Meander Chute Cutoffs: Laboratory Experiments With Implications for Morphodynamics and Depth‐Averaged Modeling by Jason T.‐Y. Lin, Esteban Lacunza, Roberto Fernández, Marcelo H. García, Bruce Rhoads, Jim Best, Jessica Z. LeRoy, Gary Parker

“…This paper investigates three‐dimensional mean flow structure, turbulent flow structure, and bed shear stress distribution from high‐resolution flow velocity data in a fixed‐bed, sediment‐free physical model. The results show that (a) the chute channel conveys around 1.4 times the unit‐width flow discharge as the cutoff bend; (b) mean flow structure is highly three‐dimensional, with strong convective acceleration throughout the bends and pronounced flow separation zones in both the chute channel and the cutoff bend; (c) turbulent kinetic energy is intense at shear layers bounding the flow separation zones at several locations in the channel; and (d) bed shear stress is elevated due to strong turbulence in the chute channel and is low in the cutoff bend. …”
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Theoretical investigations on analysis and optimization of freeze drying of pharmaceutical powder using machine learning modeling of temperature distribution by Turki Al Hagbani, Jawaher Abdullah Alamoudi, Majed A. Bajaber, Huda Ibrahim Alsayed, Halah Jawad Al-fanhrawi

“…Abstract This study investigates the application of various neural network-based models for predicting temperature distribution in freeze drying process of biopharmaceuticals. …”
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Release Control of Biologically Active Substances from Simulation Model of Silicone Liners by S. V. Gribanova, I. L. Udyanskaya, V. G. Yankova, T. K. Slonskaya, N. B. Epshtein, A. A. Zhukova, O. N. Plakhotnaya, V. N. Kuzina

“…Silicone disks (SDs), impregnated with BAS (0,2 % of the volume) were used as a simulation model of silicone liners. The BAS release from silicone liner models was assessed using highly sensitive chromatographic methods of thin-layer and gas-liquid chromatography.Results and discussion. …”
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One developed finite element model used in nano-layered flaky Ti2AlC MAX ceramic particles reinforced magnesium composite by Wantong Chen, Jingyu Yang, Wenbo Yu, Yishi Su, Ang Zhang, Chaosheng Ma, Yihu Ma

“…To improve the accuracy, matrix ductile damage, particle internal delamination deformation behaviors, and particle-matrix interfacial behaviors were respectively introduced into this model. The visual deformation processes of crack generation and propagation were carefully presented and discussed. …”
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Evaluation of Combined Effect of Zero Flux and Convective Boundary Conditions on Magnetohydrodynamic Boundary-Layer Flow of Nanofluid over Moving Surface Using Buongiorno’s Model by Purnima Rai, Upendra Mishra

“…This study explores the synergistic impact of zero flux and convective boundary conditions on the magnetohydrodynamic (MHD) boundary-layer slip flow of nanofluid over a moving surface, utilizing Buongiorno’s model. …”
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Anomaly Field Extraction Based on Layered-Earth Model and Equivalent Eddy Current Inversion: A Case Study of Borehole zk506 in Baishiquan, Xinjiang by Yi Yang, Jie Zhang, Qingquan Zhi, Yang Ou, Xingchun Wang, Lei Wang, Junjie Wu, Xiaohong Deng

“…It demonstrates the effectiveness and significance of the pure anomaly extraction based on the layered-earth model and equivalent eddy current inversion in the exploration of high-conductivity sulfide ores.…”
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Protein sequence classification using natural language processing techniques by Huma Perveen, Julie Weeds

“…Abstract Purpose This study aimed to enhance protein sequence classification using natural language processing (NLP) techniques while addressing the impact of sequence similarity on model performance. …”
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Modeling and Simulation for Predicting Thermo-Mechanical Behavior of Wafer-Level Cu-PI RDLs During Manufacturing by Xianglong Chu, Shitao Wang, Chunlei Li, Zhizhen Wang, Shenglin Ma, Daowei Wu, Hai Yuan, Bin You

“…The fineness and complexity of structures, combined with the temperature-dependent and viscoelastic properties of organic materials, make it increasingly difficult to predict the thermo-mechanical behavior of wafer-level Cu-PI RDL structures, posing a severe challenge in warpage prediction. This study models and simulates the thermo-mechanical response during the manufacturing process of Cu-PI RDL at the wafer level. …”
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Modeling of Optical Processes in Thin-Film IR Light-Emitting Diode Based on Colloidal PbS Quantum Dots by U. Y. Turavets

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A Theoretical Model for the Hydraulic Permeability of Clayey Sediments Considering the Impact of Pore Fluid Chemistry by Lixue Cao, Hang Zhao, Baokai Yang, Jian Zhang, Hongzhi Song, Xiaomin Fu, Lele Liu

“…The chemistry of the pore fluid within clayey sediments frequently changes in various processes. However, the impacts of pore fluid chemistry have not been well included in the hydraulic permeability model, and the physical bases behind the salinity sensitivity of the hydraulic permeability remains elusive. …”
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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

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Simulating characteristics of Si/Ge tandem monolithic solar cell with Si1-xGex buffer layer by A. B. Gnilenko, Ju. N. Lavrich, S. V. Plaksin

“…The cascades are commutated by the use of the germanium tunnel diode between the bottom sub-cell and the buffer layer. For the solar cell modeling, the physically-based device simulator ATLAS of Silvaco TCAD software is employed to predict the electrical behavior of the semiconductor structure and to provide a deep insight into the internal physical processes. …”
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ElHBiAt: Electra Pre-Training Network Hybrid of BiLSTM, the Attention Layer to Aspect-Based Sentiment Analysis by Amin Ghanee Nezhad, Kia Jahanbin, Abolfazl Razzaghi Yamchi

“…In this model, two layers of attention are used to extract the essential aspects of the text, and the deep neural network BiLSMT is used to process the text in a two-way. …”
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NUMERICAL MODELING OF THE CINDER FORMATION PROCESS WITH APPLICATION OF SYMMETRICAL IMPLICIT SCHEMA IN MOVING HEATED INGOT OF CHROMIUM STEEL by A. N. Chichko, A. S. Borozdin

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TECHNIQUE OF DESIGNING OF TECHNOLOGICAL PROCESSES OF CENTRIFUGAL PROCESSING by Yu.A. PROSKORJAKOVA

“…Article is devoted to research of process of centrifugal processing. Theoretical models are developed for definition of an average arithmetic deviation of a structure of the established roughness, depth of the strengthened layer and a degree of hardening. …”
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Recognition of Industrial Spare Parts Using an Optimized Convolutional Neural Network Model by Chandralekha Mohan, Takfarinas Saber, Priyadharshini Jayadurga Nallathambi

“…In this article, a novel Deep Learning-based object recognition model based on a convolutional neural network architecture is proposed and constructed using stacked convolutional layers to extract and learn features of the spare parts efficiently with the goal of improving the effectiveness of the spare part image recognition process. …”
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