Explainable Model Prediction of Memristor by Sruthi Pallathuvalappil, Rahul Kottappuzhackal, Alex James

“…The accurate memristor model prediction becomes critical to decipher the overall circuit function in a wide range of nonideal and practical conditions. …”
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Non-convex optimization with using positive-negative moment estimation and its application for skin cancer recognition with a neural network by P.A. Lyakhov, U.A. Lyakhova, R.I. Abdulkadirov

“…Standard methods are based on the square roots of exponential estimates of the moments of the squares of past gradients and do not use the local variation in gradients. …”
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SGD-TripleQNet: An Integrated Deep Reinforcement Learning Model for Vehicle Lane-Change Decision by Yang Liu, Tianxing Yang, Liwei Tian, Jianbiao Pei

“…This dynamic weight adjustment process fine-tunes the weights based on gradient information to minimize the target loss function. …”
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Perceptual Error Logarithm: An Efficient and Effective Analytical Method for Full-Reference Image Quality Assessment by Sergio A. C. Bezerra, Sergio A. C. Bezerra Junior, Jose L. De S. Pio, Jose R. H. Carvalho, Keiko V. O. Fonseca

“…Finally, to calculate the PEL score, a logarithmic function is applied to the perceptual error map, which combines the simple and special maps, besides adjusts this combination based on the weight of the superpixel similarity and local energy maps. …”
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Seasonal Analysis of Planetary Boundary Layer and Turbulence in Warsaw, Poland Through Lidar and LES Simulations by Rayonil G. Carneiro, Maciej Karasewicz, Camilla K. Borges, Lucja Janicka, Dongxiang Wang, Gilberto Fisch, Iwona S. Stachlewska

“…The PBLH diurnal cycles showed pronounced changes in their vertical structure as a function of the season: the winter heights were shallow (~0.7 km), while summer heights were deeper (~1.7 km). …”
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Identification and validation of an explainable machine learning model for vascular depression diagnosis in the older adults: a multicenter cohort study by Ran Zhang, Tian Li, Fan Fan, Haoying He, Liuyi Lan, Dong Sun, Zhipeng Xu, Sisi Peng, Jing Cao, Juan Xu, Xiaoxiang Peng, Ming Lei, Hao Song, Junjian Zhang

“…Abstract Background Vascular depression (VaDep) is a prevalent affective disorder in older adults that significantly impacts functional status and quality of life. Early identification and intervention are crucial but largely insufficient in clinical practice due to inconspicuous depressive symptoms mostly, heterogeneous imaging manifestations, and the lack of definitive peripheral biomarkers. …”
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Autobiographical memory in Alzheimer’s disease: a systematic review by Chiara Stramba-Badiale, Fabio Frisone, Fabio Frisone, Fabio Frisone, Fabio Frisone, Diana Biondi, Giuseppe Riva, Giuseppe Riva

“…The studies demonstrated altered temporal gradients, with remote memories showing better preservation than recent ones, supporting Ribot’s law. …”
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Climate and human activities alter coupling of soil macro- and micronutrients: Evidence from a long-term experiment in typical steppes by Yi Zhou, Shenghua Chang, Xiaojuan Huang, Wenjun Wang, Fujiang Hou, Yanrong Wang, Zhibiao Nan

“…Soil nutrients are essential for ecosystem function and food production. However, the long-term dynamics and ecological drivers of soil macro- and microelements, as well as their relationships, remain virtually unknown, especially in varying precipitation contexts. …”
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Spatially Explicit Analysis of Landscape Structures, Urban Growth, and Economic Dynamics in Metropolitan Regions by Ioannis Vardopoulos, Marco Maialetti, Donato Scarpitta, Luca Salvati

“…Assuming that settlement morphologies and landscape structures are the result of economic transformations, the present study illustrates a statistical framework investigating metropolitan growth due to the inherent changes in landscape configurations <i>vis à vis</i> socio-demographic functions. Focusing on the evolution of their spatial drivers over time, metropolitan development was studied by adopting land parcels (or ‘patches’, as they are referred to in the ecological literature) as the elementary analysis unit—with the individual surface area and a specific shape indicator as the dependent variables and background socioeconomic attributes as predictors of landscape change over time. …”
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Reinforcement Learning-Based Safe Path Planning for a 3R Planar Robot by Mustafa Can Bingol

“…Later, state, action, reward, and terminate functions were determined. Lastly, actor and critic artificial neural networks (ANN), which are basic components of deep deterministic policy gradients (DDPG), were formed in order to generate a safe path. …”
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Variational method of numerical solution of the inverse problem of gas lift oil production process by N.M. Temirbekov, A.K. Turarov

“…The inverse problem is formulated as an optimal control problem, where the minimization of the objective functional is carried out using the gradient method. …”
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Numerical Solution of the Direct and Inverse Problems in the Gas Lift Process of Oil Production Using the Conjugate Equations Method by Nurlan M. Temirbekov, Amankeldy K. Turarov, Syrym E. Kasenov

“…To minimize the quadratic objective functional, the gradient method is used, in which the gradient is determined using the conjugate equation method. …”
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Spatiotemporal evolutionary patterns and influencing factors of urban carbon emissions in China by Qifeng Meng, Chunyi Li

“…This research initially used the Gradient Boost Regression Tree (GBRT) model to construct the urban carbon emission dataset from 1992 to 2021. …”
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Construction of multifunctional composite networks and resilience evaluation under multiple attack scenarios: A case study of the Yangtze river delta by Jianshen Qu, Hao Wang, ZiWei Zhang, Zhili Xu, Yuexia Han, Bin Dong

“…Existing studies often address ecological connectivity or thermal mitigation in isolation, lacking a comprehensive framework integrating ecological, thermal, and economic functions. This study integrates the gradient source model and circuit theory to optimize a multi-functional composite network linking ecological services, thermal environment diffusion, and economic interactions in the YRD. …”
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Control of Overfitting with Physics by Sergei V. Kozyrev, Ilya A. Lopatin, Alexander N. Pechen

“…In this work, overfitting control (or generalization property) in machine learning is explained using analogies from physics and biology. For stochastic gradient Langevin dynamics, we show that the Eyring formula of kinetic theory allows to control overfitting in the algorithmic stability approach—when wide minima of the risk function with low free energy correspond to low overfitting. …”
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Retinoic acid regulates the proliferation, differentiation, and cell death of limb skeletal progenitors, contributing to establish the size and identity of the digits by Cristina Duarte-Olivenza, Goretti Moran, Juan M. Hurle, Juan A. Montero, Carlos I. Lorda-Diez

“…RA gain- and loss-of-function experiments via pharmacological approaches confirmed a close correlation between interdigital RA and digit size. …”
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A Reinforcement Learning-Based Generative Approach for Event Temporal Relation Extraction by Zhonghua Wu, Wenzhong Yang, Meng Zhang, Fuyuan Wei, Xinfang Liu

“…To bridge the gap between the optimization objective and task performance metrics, we employ the REINFORCE algorithm to optimize our generative model, designing a novel reward function to simultaneously capture the accuracy of temporal prediction and the quality of generation. …”
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Nitrogen sensitivity of soil microorganism community in alpine desert steppe is not always higher than that in alpine steppe by Zhishu Wang, Jianyu Xiao, Fusong Han, Shaolin Huang, Chengqun Yu

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The Conditioned Environmental Center‐Periphery Hypothesis of Biogeography: Statistical Evidence From Tree Species by Pablo Antúnez, Martin Ricker

“…The aim here is to analyze for each environmental gradient separately the ecological niche of 12 Mexican tree species and 16 abiotic environmental gradients, in the form of statistical probability density functions. …”
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AI-enabled Barilai–Borwein–Blinder–Oaxaca–Bernoulli Deep Classifier for Enhanced Crop Yield Prediction by Rajesh Kumar Dhanaraj, Nithya Rekha Sivakumar, Firoz Khan, Mahmoud Ahmad Al-Khasawneh

“…The study of innovative AI method integrated with Min–max Normalization, Barilai–Borwein gradient, Blinder–Oaxaca decomposition function, Deep Belief Network, Xavier Initialization function, Bernoulli distribution function, and Principal Components for achieving better performance in crop yield prediction.…”
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