检索结果-内蒙古大学图书馆

Prediction of miRNA-disease association based on multisource inductive matrix completion

SCIENTIFIC REPORTS 2024年第1期14卷 1-15页

作者： Wang, Yawei Yin, Zhixiang Shanghai Univ Enginneering Sci Inst Frontier Med Technol Ctr Intelligent Comp & Appl Stat Sch Math Phys & Stat Shanghai 201620 Peoples R China

MicroRNAs (miRNAs) are endogenous non-coding RNAs approximately 23 nucleotides in length, playing significant roles in various cellular processes. Numerous studies have shown that miRNAs are involved in the regulation of many human diseases. Accurate prediction of miRNA-disease associations is crucial for early diagnosis, treatment, and prognosis assessment of diseases. In this paper, we propose the Autoencoder Inductive Matrix Completion (AEIMC) model to identify potential miRNA-disease associations. The model captures interaction features from multiple similarity networks, including miRNA functional similarity, miRNA sequence similarity, disease semantic similarity, disease ontology similarity, and Gaussian interaction kernel similarity between miRNAs and diseases. Autoencoders are used to extract more complex and abstract data representations, which are then input into the inductive matrix completion model for association prediction. The effectiveness of the model is validated through cross-validation, stratified threshold evaluation, and case studies, while ablation experiments further confirm the necessity of introducing sequence and ontology similarities for the first time.

关键词： miRNA-disease association Multi-source information Autoencoder Inductive matrix completion Ablation experiment optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Integrating socio-psychological factors in the SEIR model optimized by a genetic algorithm for COVID-19 trend analysis

引用

SCIENTIFIC REPORTS 2024年第1期14卷 1-12页

作者： Wang, Haonan Wu, Danhong Luo, Jie Zhang, Junhui Southwest Med Univ Sch Publ Hlth 1Sect 1Xianglin Rd Luzhou 646000 Sichuan Peoples R China Chengdu Univ Informat Technol Dept Appl Math Chengdu 610225 Sichuan Peoples R China Univ Durham Dept Psychol Durham DH1 3LE England

The global spread of COVID-19 has profoundly affected health and economies, highlighting the need for precise epidemic trend predictions for effective interventions. In this study, we used infectious disease models to simulate and predict the trajectory of COVID-19. An SEIR (susceptible, exposed, infected, removed) model was established using Wuhan data to reflect the pandemic. We then trained a genetic algorithm-based SEIR (GA-SEIR) model using data from a specific U.S. region and focused on individual susceptibility and infection dynamics. By integrating socio-psychological factors, we achieved a significant enhancement to the GA-SEIR model, leading to the development of an optimized version. This refined GA-SEIR model significantly improved our ability to simulate the spread and control of the epidemic and to effectively track trends. Remarkably, it successfully predicted the resurgence of COVID-19 in mainland China in April 2023, demonstrating its robustness and reliability. The refined GA-SEIR model provides crucial insights for public health authorities, enabling them to design and implement proactive strategies for outbreak containment and mitigation. Its substantial contributions to epidemic modelling and public health planning are invaluable, particularly in managing and controlling respiratory infectious diseases such as COVID-19.

关键词： COVID-19 Dynamic model GA-SEIR model Epidemic forecasting Socio-psychological factors optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Efficiency, optimality, and selection in a rigid actuation system with matching capabilities for an assistive robotic exoskeleton

引用

ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH 2024年 51卷

作者： Ghaffar, Asim Rahman, Muhammad Zia Ur Leiva, Victor Martin-Barreiro, Carlos Ali, Imran Cabezas, Xavier Castro, Cecilia Univ Engn & Technol Lahore Dept Mech Mechatron & Mfg Engn Faisalabad Campus Faisalabad Pakistan Pontificia Univ Catolica Valparaiso Escuela Ingn Ind Valparaiso Chile ESPOL Escuela Super Politecn Litoral Fac Ciencias Nat & Matemat Guayaquil Ecuador Univ Espiritu Santo Fac Ingn Samborondon Ecuador Escuela Super Politecn Litoral ESPOL Ctr Estudios Invest Estadist Guayaquil Ecuador Univ Minho Ctr Math Braga Portugal

Selecting the right actuator for a portable exoskeleton involves a comprehensive evaluation of various design characteristics. In this study, we introduce a methodology for actuator selection based on specific tasks, enhancing the practical adoption of portable exoskeletons. By examining a range of candidate actuators designed for lower limb exoskeletons, our objective is to engineer a system that is both lightweight and power-efficient. These candidate actuators, developed by integrating diverse motors and transmission systems, were rigorously tested against defined tasks. Our methodology, applied to an assistive exoskeleton catered to the elderly, showed its potential in tailoring an efficient system with matching capabilities. The obtained results indicated that the ideal configuration achieved reductions in weight and power requirements by 35% and 80%, respectively. The present research delineates a strategic approach for actuator selection in portable exoskeletons, contributing to the evolution of high-performing assistive devices.

关键词： Actuators Assistive robotics Dynamic modeling Mathematical simulation MATLAB software optimization algorithm Rehabilitation

来源：评论

学校读者我要写书评

暂无评论

Parameter optimization of an electrochemical and thermal model for a lithium-ion commercial battery

引用

JOURNAL OF ENERGY STORAGE 2020年 32卷

作者： Munoz, P. M. Humana, R. M. Falaguerra, T. Correa, G. aa CONICET UNCA Ctr Invest & Transferencia Catamarca CITCA Prado 366K4700BDH San Fernando Valle Catam Catamarca Argentina CONICET UNCA Fac Ciencias Exactas & Nat Ave Belgrano 300K4700AAP San Fernando Valle Catam Catamarca Argentina

In this work, a LiFePO4/C commercial cylindrical battery cell is modeled with a P2D model coupled with a 2D axisymmetric heat transfer model to adequately represent the electrochemical and thermal responses of a battery. Charge and discharge tests at different C-rates with a controlled environment temperature are used to validate the parameters selected for the model. Some relevant parameters were obtained from literature and by opening the battery and testing the electrodes with charge and discharge protocols and SEM images. The parameters for which no direct measurement can be done and have no consensus in literature, were obtained through an optimization process using the BOBYQA optimization algorithm, which allows a substantial reduction in calculation time compared to other methods. Model simulations and experimental battery measures show good agreement with maximum RMSE of 62 mV and 0.68 degrees C, and mean relative errors of 1.76% and 2.36% for the voltage and temperature profiles in different discharge cycles.

关键词： Battery modelling P2D model Thermal modelling LiFePO4 optimization algorithm Parameter identification

来源：评论

学校读者我要写书评

暂无评论

Robust optimal control of nonlinear fractional systems

引用

CHAOS SOLITONS & FRACTALS 2023年第Part1期175卷

作者： Liu, Chongyang Zhou, Tuo Gong, Zhaohua Yi, Xiaopeng Teo, Kok Lay Wang, Song Shandong Technol & Business Univ Sch Math & Informat Sci Yantai 264005 Peoples R China Shandong Technol & Business Univ Sch Informat & Elect Engn Yantai 264005 Peoples R China Sunway Univ Sch Math Sci Kuala Lumpur 47500 Malaysia Curtin Univ Sch Elect Engn Comp & Math Sci Perth 6845 Australia

Parameter uncertainty is inevitably found in almost every system and, if is ignored, it could jeopardize the effectiveness of control method. Motivated by this issue, we consider a robust optimal control problem governed by a nonlinear fractional system with uncertain parameters, where the system sensitivity with respect to the uncertain parameters is explicitly included in the cost functional. For this problem, we first prove that the system sensitivity can be expressed as the solution of an auxiliary fractional system. Then, we propose a numerical scheme for discretizing both the original and auxiliary fractional systems, resulting in a finite dimensional optimization problem. Furthermore, a numerical solution algorithm based on gradients of the cost functional is developed for the resulting optimization problem. Finally, numerical results for two example problems are given to demonstrate the validity and applicability of the proposed algorithm.

关键词： Robust optimal control Fractional system Discretization scheme optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Predicting the small strain shear modulus of sands and sand-fines binary mixtures using machine learning algorithms

引用

TRANSPORTATION GEOTECHNICS 2024年 44卷

作者： Khodkari, Naser Hamidian, Pouria Khodkari, Homayoun Payan, Meghdad Behnood, Ali Univ Tehran Coll Engn Sch Civil Engn Tehran Iran Amirkabir Univ Technol Tehran Polytech Turbulence Lab Tehran Iran Univ Guilan Fac Engn Dept Civil Engn Rasht Iran Univ Mississippi Dept Civil Engn Oxford MS USA

This study aims to develop several novel machine learning (ML) evolutionary algorithms for the prediction of small strain shear modulus (Gmax) of clean sands and sand-fines binary mixtures. To this end, five key features of isotropic confining pressure (p), void ratio (e), uniformity coefficient (Cu), particle shape descriptor (rho), and non plastic fines content (FC) are adopted as the inputs to artificial neural network (ANN) models as well as genetic programming (GP) algorithm so as to render the maximum shear modulus of granular soils as the output. Accordingly, a comprehensive dataset containing 1055 Gmax data points is exploited to develop ML simulations. The validity of ML-based models in estimating the Gmax of clean sands and sand-silt mixtures is rigorously examined through various statistical indices and measurement criteria. The results show that a novel ML model utilizing ANN-Levenberg Marquardt (LM) in conjunction with an evolutionary optimization method named Success History-based Adaptive Differential Evolution with Linear population size reduction (LSHADE) is capable of predicting Gmax data with a very high precision rendering R2 values of 0.9833, 0.9841, 0.9802, and 0.9835 for the whole, training, validation, and test datasets, respectively. Meanwhile, using the well-established GP algorithm, a new practical model is proposed to predict the Gmax of clean sands and sand-fines mixtures containing non-cohesive silt inclusion with R2 values of 0.9323, 0.9351, and 0.9312 for the whole, training, and test datasets, respectively. Finally, the proposed models of ANN-LSHADE-LM and GP are shown to be appreciably superior, in terms of accuracy, to all commonly used empirical correlations in the literature for Gmax estimation.

关键词： Small strain shear modulus Artificial neural network (ANN) optimization algorithm Differential evolution (DE) Genetic programming (GP) Sand-silt mixtures

来源：评论

学校读者我要写书评

暂无评论

Research on factor analysis and method for evaluating grouting effects using machine learning

引用

SCIENTIFIC REPORTS 2024年第1期14卷 1-19页

作者： Li, Wenxin Chen, Juntao Zhu, Jun Ji, Xinbo Fu, Ziqun Shandong Univ Sci & Technol Coll Energy & Min Engn Qingdao Peoples R China Shandong Energy Xinwen Min Grp Suncun Coal Mine Tai An 271219 Peoples R China

The evaluation of grouting effects constitutes a critical aspect of grouting engineering. With the maturity of the grouting project, the workload and empirical characteristics of grouting effect evaluation are gradually revealed. In the context of the Qiuji coal mine's directional drilling and grouting to limestone aquifer reformation, this study thoroughly analyzes the influencing factors of grouting effects from geological and engineering perspectives, comparing these with various engineering indices associated with drilling and grouting. This led to the establishment of a "dual-process, multi-parameter, and multi-factor" system, employing correlation analysis to validate the selected indices' reasonableness and scientific merit. Utilizing the chosen indices, eight high-performing machine learning models and three parameter optimization algorithms were employed to develop a model for assessing the effectiveness of directional grouting in limestone aquifers. The model's efficacy was evaluated based on accuracy, recall, precision, and F-score metrics, followed by practical engineering validation. Results indicate that the "dual-process, multi-parameter, multi-factor" system elucidates the relationship between influencing factors and engineering parameters, demonstrating the intricacy of evaluating grouting effects. Analysis revealed that the correlation among the eight selected indicators-including the proportion of boreholes in the target rock strata, drilling length, leakage, water level, pressure of grouting, mass of slurry injected, permeability properties of limestone aquifers before being grouted, permeability properties of limestone aquifers after being grouted-is not substantial, underscoring their viability as independent indicators for grouting effect evaluation. Comparative analysis showed that the Adaboost machine learning model, optimized via a genetic algorithm, demonstrated superior performance and more accurate evaluation results. Engineering validat

关键词： Grouting effect evaluation Correlation analysis optimization algorithm Machine learning

来源：评论

学校读者我要写书评

暂无评论

When to sleep and consume caffeine to boost alertness

引用

SLEEP 2024年第10期47卷 zsae133页

作者： Vital-Lopez, Francisco G. Doty, Tracy J. Reifman, Jaques US Army Biotechnol High Performance Comp Software Applicat Telemed & Adv Technol Res Ctr Dept DefMed Res & Dev Command ATTN FCMR TT504 Scott St Ft Detrick MD 21702 USA Henry M Jackson Fdn Advancement Mil Med Inc Bethesda MD USA Walter Reed Army Inst Res Behav Biol Branch Silver Spring MD USA

Study Objectives Sleep loss can cause cognitive impairments that increase the risk of mistakes and accidents. However, existing guidelines to counteract the effects of sleep loss are generic and are not designed to address individual-specific conditions, leading to suboptimal alertness levels. Here, we developed an optimization algorithm that automatically identifies sleep schedules and caffeine-dosing strategies to minimize alertness impairment due to sleep loss for desired times of the *** We combined our previous algorithms that separately optimize sleep or caffeine to simultaneously identify the best sleep schedules and caffeine doses that minimize alertness impairment at desired times. The optimization algorithm uses the predictions of the well-validated Unified Model of Performance to estimate the effectiveness and physiological feasibility of a large number of possible solutions and identify the best one. To assess the optimization algorithm, we used it to identify the best sleep schedules and caffeine-dosing strategies for four studies that exemplify common sleep-loss conditions and compared the predicted alertness-impairment reduction achieved by using the algorithm's recommendations against that achieved by following the U.S. Army caffeine *** Compared to the alertness-impairment levels in the original studies, the algorithm's recommendations reduced alertness impairment on average by 63%, an improvement of 24 percentage points over the U.S. Army caffeine *** We provide an optimization algorithm that simultaneously identifies effective and safe sleep schedules and caffeine-dosing strategies to minimize alertness impairment at user-specified times. Graphical Abstract

关键词： alertness caffeine fatigue management optimization algorithm sleep schedules

来源：评论

学校读者我要写书评

暂无评论

Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm

引用

SCIENTIFIC REPORTS 2024年第1期14卷 1-21页

作者： Wu, Yanmin Wang, Lu Wan, Zhenjie Liu, Jiaqi Fu, Dongpeng An, Yanjun Zhang, Xiaofeng Zhengzhou Univ Light Ind Coll Bldg Environm Engn Zhengzhou 450002 Peoples R China Naval Univ Engn Coll Elect Engn Wuhan 430033 Peoples R China Henan Univ Engn Sch Accounting Zhengzhou 451191 Peoples R China

To address the challenges related to active power dissipation and node voltage fluctuation in the practical transformation of power grids in the field of new energy such as wind and photovoltaic power generation, an improved Dung Beetle optimization algorithm Based on a Hybrid Strategy of Levy Flight and Differential Evolution (LDEDBO) is proposed. This paper systematically addresses this issue from three aspects: firstly, optimizing the DBO algorithm using Chebyshev chaotic mapping, Levy flight strategy, and differential evolution algorithm;secondly, validating the algorithm's feasibility through real-time network reconfiguration at random time points within a 24-h period;and finally, applying the LDEDBO to address the dynamic reconfiguration problems of the IEEE-33 and IEEE-69 node bus. The simulation indicates that the power dissipation of the IEEE-33 node bus is decreased by 28.94% and the minimum node voltage is elevated from 0.9273 p.u to 0.9447 p.u after the reconstruction with LDEDBO. The power dissipation of the IEEE-69 node bus is reduced by 36.45%, and the minimum node voltage is increased from 0.9224 p.u to 0.9481 p.u. The LDEDBO enhances both the pace of convergence and the precision of the optimization model, leading to a superior solution for the switching combination.

关键词： Distribution network reconfiguration LDEDBO algorithm optimization algorithm Dynamic reconfiguration Time-varying load

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based inversion of soil and rock compaction density utilizing Falling Weight Deflectometer (FWD) and Surface Waves

引用

TRANSPORTATION GEOTECHNICS 2024年 49卷

作者： Li, Chen Gao, Guozhong Shen, Pengtian Wang, Yanling Wang, Yunsheng Wuhan Business Univ Coll Informat Engn Wuhan 430100 Hubei Peoples R China VGP Serv LLC Houston TX 77406 USA Wuhan 99 Future Intelligent Tech Co Ltd Intelligent Geophys Res Wuhan 430000 Hubei Peoples R China Yunnan Jiaohang Engn Technol Co Ltd Anning 650300 Yunnan Peoples R China

Methods relying on a single dynamic parameter to estimate the material density for the compaction quality testing of earth-rock dams and roadbed projects, present certain limitations in terms of applicability, testing accuracy, and work efficiency. The theory of elastic wave propagation reveals that the compaction density of the medium results from the combined interaction of multiple material properties. This study proposes a method that utilizes the transient surface wave method and a vehicle-mounted Falling Weight Deflectometer (FWD) to jointly enhance the accuracy of soil and rock material compaction detection. The transient surface wave method is employed to extract surface wave velocity and compressional wave velocity. The analysis of the FWD signal involves extracting dynamic parameters closely related to material density, including stiffness coefficients, central frequencies, and stiffness impedances, from time-domain, frequency-domain, and mechanical impedance analyses. A fully connected deep neural network is introduced to intelligently estimate the compaction density. The deep learning model is optimized by selecting the optimal activation function and optimization algorithm, as well as additional tuning. Extensive testing shows that deep learning model produce results closely approximating the true compaction density values. The average relative errors for the wet density and the dry density are 2.9% and 2.85%, respectively, meeting the quality control requirements for density testing. The proposed approach enables rapid detection and control of the compaction quality of soil and rock materials, providing a new method for the in-situ rapid detection of compaction quality.

关键词： Transient Surface Wave FWD Compaction density Characteristic parameters Deep learning optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：