APOE4 and chronic health risk factors are associated with sex-specific preclinical Alzheimer’s disease neuroimaging biomarkers by Genna M. Losinski, Mickeal N. Key, Eric D. Vidoni, Jonathan Clutton, Jill K. Morris, Jeffrey M. Burns, Amber Watts, Amber Watts

“…We did not observe sex differences in amyloid-β levels. Higher than optimal waist to hip ratio was most strongly associated with lower volume among female participants.DiscussionFindings suggest genetic and chronic health risk factors are associated with sex-specific AD neuroimaging biomarkers. …”
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Fractional-order SIR model for ADHD as a neurobiological and genetic disorder by Zeeshan Afzal, Mansoor Alshehri

“…Numerical simulations are carried out using the Laplace Residue Power Series (LRPS) and Runge-Kutta 4th Order (RK4) methods for different values of the fractional-order parameter $$\alpha$$ . …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…The 0-1 Knapsack Problem (KP) and Bin Packing Problem (BPP) are NP-hard combinatorial optimization challenges often tackled using metaheuristics. …”
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Hot deformation behavior of micro-alloyed steel using processing maps developed with different constitutive equations by Thakur S.K., Das A.K., Jha B.K.

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Node selection method in federated learning based on deep reinforcement learning by Wenchen HE, Shaoyong GUO, Xuesong QIU, Liandong CHEN, Suxiang ZHANG

“…To cope with the impact of different device computing capabilities and non-independent uniformly distributed data on federated learning performance, and to efficiently schedule terminal devices to complete model aggregation, a method of node selection based on deep reinforcement learning was proposed.It considered training quality and efficiency of heterogeneous terminal devices, and filtrate malicious nodes to guarantee higher model accuracy and shorter training delay of federated learning.Firstly, according to characteristics of model distributed training in federated learning, a node selection system model based on deep reinforcement learning was constructed.Secondly, considering such factors as device training delay, model transmission delay and accuracy, an optimization model of accuracy for node selection was proposed.Finally, the problem model was constructed as a Markov decision process and a node selection algorithm based on distributed proximal strategy optimization was designed to obtain a reasonable set of devices before each training iteration to complete model aggregation.Simulation results demonstrate that the proposed method significantly improves the accuracy and training speed of federated learning, and its convergence and robustness are also well.…”
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Node selection method in federated learning based on deep reinforcement learning by Wenchen HE, Shaoyong GUO, Xuesong QIU, Liandong CHEN, Suxiang ZHANG

“…To cope with the impact of different device computing capabilities and non-independent uniformly distributed data on federated learning performance, and to efficiently schedule terminal devices to complete model aggregation, a method of node selection based on deep reinforcement learning was proposed.It considered training quality and efficiency of heterogeneous terminal devices, and filtrate malicious nodes to guarantee higher model accuracy and shorter training delay of federated learning.Firstly, according to characteristics of model distributed training in federated learning, a node selection system model based on deep reinforcement learning was constructed.Secondly, considering such factors as device training delay, model transmission delay and accuracy, an optimization model of accuracy for node selection was proposed.Finally, the problem model was constructed as a Markov decision process and a node selection algorithm based on distributed proximal strategy optimization was designed to obtain a reasonable set of devices before each training iteration to complete model aggregation.Simulation results demonstrate that the proposed method significantly improves the accuracy and training speed of federated learning, and its convergence and robustness are also well.…”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…This study explores optimizing Artificial Neural Network (ANN) parameters using meta-heuristic algorithms instead of traditional gradient-based methods to predict residential electricity consumption across different seasons. …”
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Cryopreservation of Noble Scallop Mimachlamys nobilis sperm: Optimization study of cooling rate and thawing temperature by Minghao Li, Zhengyi Fu, Gang Yu, Zhenhua Ma

“…This study examined the effects of freezing protocols and thawing methods on the cryopreservation of Mimachlamys nobilis sperm. …”
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Propionyl Carnitine Metabolic Profile: Optimizing the Newborn Screening Strategy Through Customized Cut-Offs by Maria Lucia Tommolini, Maria Concetta Cufaro, Silvia Valentinuzzi, Ilaria Cicalini, Mirco Zucchelli, Alberto Frisco, Simonetta Simonetti, Michela Perrone Donnorso, Sara Moccia, Ines Bucci, Maurizio Aricò, Vincenzo De Laurenzi, Luca Federici, Damiana Pieragostino, Claudia Rossi

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APPLICATION OF HYBRID RANDOM SEARCH METHOD TO OPTIMISATION OF ENGINEERING SYSTEMS’ PARAMETERS by A. V. Panteleev, D. A. Rodionova

“…The obtained method is applied to the optimization of parameters of different engineering systems. …”
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Effects of Mathematical Model of MR Damper on Its Control Performance; A Nonlinear Comparative Study by R. Karami Mohammadi, H. Ghamari

“…Using different modelling methods can lead to different voltages for the MR damper, which subsequently results in changes to the responses of the controlled structure. …”
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Study of the protective properties of immunodominant proteins of orthopoxviruses in various methods of immunization by Denis I. Zrelkin, Olga V. Zubkova, Tatiana A. Ozharovskaia, Olga Popova, Daria V. Voronina, Polina P. Goldovskaya, Irina V. Vavilova, Anastasia S. Chugunova, Inna V. Dolzhikova, Dmitry N. Shcherbinin, Dmitry V. Shcheblyakov, Denis Y. Logunov, Alexander L. Gintsburg

“…This method could be used for development of new multivalent preparations against various viral infections.…”
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Microscopic Remaining Oil Classification Method and Utilization Based on Kinetic Mechanism by Yuhang He, Xianbao Zheng, Jiayi Wu, Zhiqiang Wang, Jiawen Wu, Qingyu Wang, Wenbo Gong, Xuecong Gai

“…Therefore, this study aims to investigate the state, classification method and utilization mechanism of the microscopic remaining oil in the late period of the ultra-high water cut. …”
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A Distributed Conjugate Gradient Online Learning Method over Networks by Cuixia Xu, Junlong Zhu, Youlin Shang, Qingtao Wu

“…To accelerate the convergence speed of the algorithm, we present a distributed online conjugate gradient algorithm, different from a gradient method, in which the search directions are a set of vectors that are conjugated to each other and the step sizes are obtained through an accurate line search. …”
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Soil moisture variation and affecting factors analysis in the Zhangjiakou–Chengde district based on modified temperature vegetation dryness index by Jintao Zheng, Xiaomei Jin, Qing Li, Jie Lang, Xiulan Yin

“…Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Global Land Data Assimilation System (GLDAS) datasets, the spatiotemporal variation in surface soil moisture in the ZC was simulated from 2001 to 2021 using the temperature vegetation dryness index (TVDI) model. The optimal parameter geographical detector (OPGD) method was used to identify the contributions of 10 factors affecting soil moisture. …”
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A Methodical Review on Carbon-Based Nanomaterials in Energy-Related Applications by Robert Birundu Onyancha, Kingsley Eghonghon Ukhurebor, Uyiosa Osagie Aigbe, Otolorin Adelaja Osibote, Heri Septya Kusuma, Handoko Darmokoesoemo

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Research Progress in the Effect of Vanillin Production Methods on Its Flavor Quality by TIAN Huaixiang, HANG Shuyang, HUANG Ningwei, CHEN Chen, YU Haiyan, GE Chang

“…By utilizing enzymes, genes and metabolic engineering, biosynthesis can effectively increase the yield of vanillin and has the capability to control the generation of by-products with natural characteristic flavors, which demonstrates a broad prospect for industrialization and flavor quality optimization. This review summarizes the major production methods of vanillin, analyzes the effects of different production methods on its flavor quality, and discusses the future development direction of vanillin, with a view to providing new technical support and ideas for the sustainable development of the vanillin industry.…”
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Modeling of Complex Integrated Photonic Resonators Using the Scattering Matrix Method by Di Jin, Sian Ren, Junkai Hu, Duan Huang, David J. Moss, Jiayang Wu

“…Our approach is universal across different integrated platforms, providing a useful tool for designing and optimizing integrated photonic devices with complex configurations.…”
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Evaluation method of shale reservoir fracability based on double sweet spots by SHI Can, LIN Botao, XIE Bobo, PAN Yuting, ZHANG Jiahao

“…This method can provide effective scientific guidance for optimizing the well trajectory, increasing the drilling encounter rate with high-quality reservoirs, and optimizing the construction plan of reservoir fracturing.…”
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Modified Morphological Component Analysis Method for SAR Image Clutter Suppression by Shuangying Xiao, Huaping Xu, Bing Sun, Wei Liu

“…To overcome the problem, a modified MCA method is proposed in this paper. The proposed method formulates clutter suppression as a constraint optimization problem that combines MCA with incoherence constraint and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>0</mn></msub></semantics></math></inline-formula> gradient minimization, and it presents an effective solution to the optimization problem. …”
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