Social norms and groups structure safe operating spaces in renewable resource use in a social–ecological multi-layer network model by M. Bechthold, M. Bechthold, M. Bechthold, W. Barfuss, W. Barfuss, A. Butz, J. Breier, J. Breier, S. M. Constantino, J. Heitzig, L. Schwarz, L. Schwarz, L. Schwarz, S. N. Vardag, J. F. Donges, J. F. Donges, J. F. Donges

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Simple model and integral method for simulating the growth of the borided layer FeB/Fe2B on the AISI H13 steel by Youcef Djafri, Bendaoud Mebarek, Guerri Yassine El, Mourad Keddam, Naima Hadjadj

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Business model innovation as a mediator between construction 4.0 and firm performance: Evidence from Turkish construction companies by Omimah Alsaadi, Lutfihak Alpkan, Bora Yildiz

“…This empirical study aims to uncover the complex relations among Construction 4.0, Business Model Innovation (BMI), and firm performance in a developing country context. …”
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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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Olfactory dysfunction and altered cortical excitability in the mouse model of Fragile X Syndrome by Felipe Arancibia, Marcelo Rojas, Diego Becerra, Rocío Fuenzalida, Christian Cea-Del Rio, Jorge Mpodozis, Magdalena Sanhueza, Alexia Nunez-Parra

“…Here, we use a combination of behavioral tests and slice physiology tools to study the neurophysiological alterations underlying aberrant sensory processing in the olfactory system of the FXS mouse model (Fmr1 KO). …”
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FastGEMF: Scalable High-Speed Simulation of Stochastic Spreading Processes Over Complex Multilayer Networks by Mohammad Hossein Samaei, Faryad Darabi Sahneh, Caterina Scoglio

“…This study introduces FastGEMF, a novel, scalable simulation framework for exact, high-speed modeling of Markov chain processes on complex multi-layer networks. …”
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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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GoalBERT: A Lightweight Named-Entity Recognition Model Based on Multiple Fusion by Yingjie Xu, Xiaobo Tan, Mengxuan Wang, Wenbo Zhang

“…This reduces the high computational demand caused by stacking multiple self-attention layers while enhancing the model’s ability to process context information. …”
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Contextual Emotional Transformer-Based Model for Comment Analysis in Mental Health Case Prediction by Ayodeji O. J. Ibitoye, Oladosu O. Oladimeji, Olufade F. W. Onifade

“…Mental health (MH) assessment and prediction have become critical areas of focus in healthcare, leveraging developments in natural language processing (NLP). Recent advancements in machine learning have facilitated the exploration of predictive models for MH based on user-generated comments that overlooked the integration of emotional attention mechanisms. …”
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Ultrastructural sublaminar-specific diversity of excitatory synaptic boutons in layer 1 of the adult human temporal lobe neocortex by Astrid Rollenhagen, Akram Sadeghi, Bernd Walkenfort, Claus C Hilgetag, Kurt Sätzler, Joachim HR Lübke

“…Astrocytic coverage of excitatory SBs suggests both synaptic crosstalk or removal of spilled glutamate by astrocytic processes at synaptic complexes. The structural composition of SBs in L1 may underlie the function of L1 networks that mediate, integrate, and synchronize contextual and cross-modal information, enabling flexible and state-dependent processing of feedforward sensory inputs from other layers of the cortical column.…”
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Advanced neural network-based model for predicting court decisions on child custody by Mohammad Abrar, Abdu Salam, Faizan Ullah, Muhammad Nadeem, Hussain AlSalman, Muaadh Mukred, Farhan Amin

“…In this phase, NLP and transformer-based models were employed and thus processed 3,000 annotated court rulings. …”
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Modelagem da infiltração em solos com encrostamento superficial. Parte I: modelo GAML para solos estratificados Modelling of the soil water infiltration in crusting soil. Part I: G... by João H. Zonta, Mauro A. Martinez, Fernando F. Pruski, Demetrius D. da Silva, Marcelo R. dos Santos

“…<br>ABSTRACT The aim of this study was to evaluate the Green-Ampt-Mein-Larson (GAML) model and GAML model modified by Moore (1981) for layered soils, in the simulation of water infiltration process in crusting soil. …”
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Mathematical modeling, drying kinetics, and economic analysis of a hybrid photovoltaic thermal solar dryer for henna leaves by Abdallah Elshawadfy Elwakeel, Awad Ali Tayoush Oraiath, Tarek Hussien M. Ghanem, Ahmed Elbeltagi, Ali Salem, Ahmed Z. Dewidar, Abdelaziz M. Okasha, Abadeer Habib, Tamer M. El-Messery, Moustapha Eid Moustapha, Khaled A. Metwally

“…Furthermore, Lewis (Newton), Weibullian, and Page were the most appropriate mathematical drying models for Henna leaves at layer thicknesses of approximately 2, 4, and 6 cm, respectively, for dried samples by DDSD. …”
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Mine pressure prediction based on empirical mode decomposition linear model by Yuwei ZHU, Pengfei WANG, Huixian WANG, Qiangqiang NIU, Liang XIN

“…To ensure the safe and efficient extraction of coal mines and reduce sudden roof accidents, this study proposes a novel multivariate long-term sequence mine pressure prediction model—the Empirical Mode Decomposition Linear Model (EMD–Mixer). …”
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Joint Exploitation of Physical-Layer and Artificial Features for Privacy-Preserving Distributed Source Camera Identification by Hui Tian, Haibao Chen, Yuyan Zhao, Jiawei Zhang

“…Specifically, we build a hybrid fingerprint model by combining sensor level hardware fingerprints with artificial tag features to characterize the unique identity of the camera in a digital image. …”
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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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METHOD FOR NUMERICAL MODELING OF UNSTEADY SEPARATED FLOW AROUND AIRFOILS MOVING CLOSE TO FLAT SCREEN by T. V. Pogrebnaya, S. D. Shipilov

“…The algorithm is based on the combination of discrete vortex method and turbulent boundary layer equations. An unsteady flow separation modeling has been used. …”
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Working-memory load decoding model inspired by brain cognition based on cross-frequency coupling by Jing Zhang, Tingyi Tan, Yuhao Jiang, Congming Tan, Liangliang Hu, Daowen Xiong, Yikang Ding, Guowei Huang, Junjie Qin, Yin Tian

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