bluuebunny/crossref_metadata_2025 huggingface dataset:
Axisymmetric Postbuckling of Functionally Graded Graphene Platelets Reinforced Composite Annular Plate on Nonlinear Elastic Medium in Thermal Environment
Authors: Allahkarami Farshid , Tohidi Hasan
Published: August 2022

This study investigates the axisymmetric postbuckling of functionally graded graphene platelets reinforced composite (FG-GPLRC) annular plates resting on nonlinear elastic medium in thermal environment. Five kinds of graphene platelets (GPLs) distribution patterns including [Formula: see text]-pattern, [Formula: see text]-pattern, [Formula: see text]-pattern, [Formula: see text]-pattern, and [Formula: see text]-pattern have been considered. The nonlinear equilibrium equations and associated boundary conditions are obtained based upon the Mindlin plate theory. The governing equations are solved via the generalized differential quadrature method (GDQM). Afterwards, the direct iterative method is implemented to accomplish postbuckling loads using the buckling mode deflection. In order to confirm the accuracy of the present model, comparisons between our data with those published in the available literature are put forth. Eventually, this paper emphasizes the impact of diverse parameters such as geometrical parameters of the structure, GPLs patterns and their geometric, GPLs weight fraction, boundary conditions, elastic medium’s parameters and temperature change on the buckling and postbuckling response of nanocomposite annular plates. It can be found that elastic medium overshadows the applicability of distribution patterns and weight fraction of GPLs.
A Framework to Assess Seismic Resilience of Self-Centering Steel Frame Buildings
Authors: Li Yiming , Tan Ping , Fu Zhijun
Published: August 2022

Resilience can be treated as an integrated measure to assess the seismic performance of buildings. Available methods to assess the seismic performance of self-centering structures mainly consider inter-story drift ratios, peak floor accelerations, and energy dissipative capacities, however, their seismic resilience is poorly understood. This paper proposes a framework to estimate the seismic resilience of self-centering energy dissipative braced steel frame office buildings. In this context, a new damage ratio assessment model is presented to assess functionality. Unlike the traditional method that only considers the economic loss or repair time in the functionality assessment, the proposed model accounts for the contribution of four performance measures such as downtime. To estimate the repair cost, repair time, casualties, and unsafe placarding, the FEMA P58 methodology is used. Based on the proposed model, the new damage ratios and recovery times of the self-centering structure are estimated. Obtained damage ratios are combined with fragility analysis to calculate the functionality loss. After considering an appropriate recovery model, seismic resilience is assessed. For comparison, the traditional method (i.e. HAZUS) is also used to assess seismic resilience. The whole framework is applied to a three-story self-centering energy dissipative braced steel frame, and the results show that the traditional method often underestimates the seismic resilience, and the proposed method may be more suitable for predicting the seismic resilience of self-centering energy dissipative braced steel frame office building. Sensitivity analysis is performed to identify uncertain parameters to which seismic resilience is most sensitive, and the result indicates that the control time and damage ratio at the extensive damage state have a major influence on seismic resilience. The framework can be modified and extended to assess the seismic resilience of ordinary building structures and other complex structural systems such as isolated structures.
Computational design and experimental confirmation of conformationally constrained peptides to compete with coactivators for pediatric PPARα by minimizing indirect readout effect
Authors: Gao Caijie , Zhao Xu , Fan Jianrong
Published: August 2022

The peroxisome proliferator-activated receptor-[Formula: see text] (PPAR[Formula: see text]) is a member of PPAR nuclear receptor family, and its antagonists have been widely used to treat pediatric metabolic disorders. Traditional type-1 and type-2 PPAR[Formula: see text] antagonists are all small-molecule compounds that have been developed to target the ligand-binding site (LBS) of PPAR[Formula: see text], which is not overlapped with the coactivator-interacting site (CIS) of PPAR[Formula: see text]. In this study, we described the rational design of type-3 peptidic antagonists that can directly disrupt PPAR[Formula: see text]–coactivator interaction by physically competing with coactivator proteins for the CIS site. In the procedure, seven reported PPAR[Formula: see text] coactivator proteins were collected and eight 11-mer helical peptide segments that contain the core PPAR[Formula: see text]-binding LXXLL motif were identified in these coactivators, which, however, possessed a large flexibility and intrinsic disorder when splitting from coactivator protein context, and thus would incur a considerable entropy penalty (i.e. indirect readout) upon binding to PPAR[Formula: see text] CIS site. By carefully examining the natively folded conformation of these helical peptides in their parent protein context and in their interaction mode with the CIS site, we rationally designed a hydrocarbon bridge across the solvent-exposed, ([Formula: see text], [Formula: see text]+ 4) residues to constrain their helical conformation, thus largely minimizing the unfavorable indirect readout effect but having only a moderate influence on favorable enthalpy contribution (i.e. direct readout) upon PPAR[Formula: see text]–peptide binding. The computational findings were further substantiated by fluorescence competition assays.
Task-Oriented Real-Time Optimization Method of Dynamic Force Distribution for Multi-Fingered Grasping
Authors: Liu Ziqi , Jiang Li , Yang Bin
Published: August 2022

The dynamic force distribution is significant in multi-fingered hand operation. It is essential to choose the appropriate contact force between fingers and object to ensure both stability and power consumption requirements corresponding to the specific task. We describe nonlinear contact force distribution problems as smooth manifold optimization problems corresponding to a linearly constrained positive definite matrix. A quadratic index gradient flow approach is presented to optimize the contact force based on a low-dimensional description matrix. And, a task-oriented contact stability criterion is proposed to evaluate contact stability. A simple selection method of the weight parameters of the objective function is provided for the specified contact stability criterion. The proposed algorithm has better force optimization results and fewer iterations than the traditional gradient flow optimization algorithm under the same stability condition. Numerical examples demonstrate the correctness and effectiveness of the algorithm. The proposed method of dynamic force distribution can be used for the real-time application of multi-fingered grasping and manipulation.
Stability analysis of an SIR epidemic model with homestead-isolation on the susceptible and infectious, immunity, relapse and general incidence rate
Authors: Bernoussi Amine
Published: August 2022

In this paper, we propose the global dynamics of an SIR epidemic model with distributed latent period, immunity, relapse, homestead-isolation of the susceptible and infectious individuals and general incidence rate. The resulting model has a disease-free equilibrium and if [Formula: see text] then the SIR epidemic model admits a unique endemic equilibrium. By using suitable Lyapunov functionals and LaSalle’s invariance principle, the global stability of the disease-free equilibrium and the endemic equilibrium is established, under suitable monotonicity conditions on the incidence function.
Physical Modeling, Simulation and Validation of Small Fixed-Wing UAV
Authors: Kapeel Ebrahim H. , Safwat Ehab , Kamel Ahmed M. , Khalil Mohamed K. , Elhalwagy Yehia Z. , Hendy Hossam
Published: August 2022

The flight dynamics of small Unmanned Aerial Vehicles (UAVs) exhibits substantial nonlinear features which should not be ignored in simulation or analysis. In this work, a complete six degrees of freedom (6DOF) and high-fidelity simulation model of a case study of a small fixed-wing UAV is developed. To accurately estimate the nonlinear UAV’s mathematical model, the mass-inertia properties are investigated through experiments. Moreover, the aerodynamic model characteristics are estimated using a semi-empirical technique to estimate the aerodynamic coefficients and derivatives. The propulsion system’s physical characteristics are estimated and analyzed through experimental measurements. The International Standard Atmosphere (ISA) tables are used to develop the atmospheric model. Furthermore, the actuation model is estimated and validated experimentally through system identification techniques. These estimated sub-model data are integrated to complete the nonlinear flight dynamics model in MATLAB® (Simulink). The UAV trim calculations are graphically derived and then the developed model is tested and verified. The open loop simulation results have proved the superiority of the utilized model techniques to describe the UAV motion. Moreover, it gives very optimistic results to test the flight dynamics of the UAV and design a consistent flight control and guidance system.
Proposal of a Self-Assessment Competency Framework for Transdisciplinary Engineering
Authors: Sajdakova J. , Carey E. , Dhokia V. , Newnes L. , Parry G.
Published: August 2022

Transdisciplinary (TD) working is claimed to be critical to meet future societal needs, with engineers being at the core to provide solutions to these challenges. However, there is little available that enables one to assess whether they or their team have the competencies required. Within this paper, we propose a self-assessment framework to ascertain whether design engineers have the competencies which enable TD working. We describe how the competencies were identified using a systematic literature review (SLR), we then describe how we utilized coded decision trees to classify which disciplinary level a particular competency can enable. In total, 76 competencies were classified; the results of the analysis show 20 of these displaying TD attributes as defined by Jantsch. The novelty of the approach is as follows: (1) In this paper, we propose a novel way to map the identified competencies against the levels of Jantsch’s hierarchical framework. (2) The proposed framework enables self-assessment of individual or team competencies to assess whether they have the competencies which enable TD working. (3) It enables a move towards incorporating TD practices in engineering projects.
Exploiting Constant Trace Property in Large-scale Polynomial Optimization
Authors: Mai Ngoc Hoang Anh , Lasserre J. B. , Magron Victor , Wang Jie
Published: August 2022

We prove that every semidefinite moment relaxation of a polynomial optimization problem (POP) with a ball constraint can be reformulated as a semidefinite program involving a matrix with constant trace property (CTP). As a result, such moment relaxations can be solved efficiently by first-order methods that exploit CTP, e.g., the conditional gradient-based augmented Lagrangian method. We also extend this CTP-exploiting framework to large-scale POPs with different sparsity structures. The efficiency and scalability of our framework are illustrated on some moment relaxations for various randomly generated POPs, especially second-order moment relaxations for quadratically constrained quadratic programs.
Consistent Individual Behavioral Variation: What Do We Know and Where Are We Going?
Authors: Laskowski Kate L. , Chang Chia-Chen , Sheehy Kirsten , Aguiñaga Jonathan
Published: August 2022

The study of individual behavioral variation, sometimes called animal personalities or behavioral types, is now a well-established area of research in behavioral ecology and evolution. Considerable theoretical work has developed predictions about its ecological and evolutionary causes and consequences, and studies testing these theories continue to grow. Here, we synthesize the current empirical work to shed light on which theories are well supported and which need further refinement. We find that the major frameworks explaining the existence of individual behavioral variation, the pace-of-life syndrome hypothesis and state-dependent feedbacks models, have mixed support. The consequences of individual behavioral variation are well studied at the individual level but less is known about consequences at higher levels such as among species and communities. The focus of this review is to reevaluate and reestablish the foundation of individual behavioral variation research: What do we know? What questions remain? And where are we going next?
Private Finance of Public Infrastructure
Authors: Engel Eduardo , Fischer Ronald , Galetovic Alexander
Published: August 2022

Public-private partnerships (PPPs) have emerged as an organizational form to provide public infrastructure. A key characteristic of PPPs is that private investors participate directly in individual infrastructure projects. The advantage of private finance is that it may improve incentives. However, private finance typically neither frees public funds nor enlarges the pool of viable projects.

Private finance improves risk allocation if exogenous demand risk is assigned to the public, while endogenous risks are assigned to the private parties (PPPs and financiers), which provides strong incentives for efficiency. When funding for the project relies on user fees, variable term contracts can allocate risks efficiently, in contrast to allocation under fixed term contracts.

The exploration of alternative financial contracts that allocate endogenous risks to private parties and determination of the optimal allocation of these risks among borrowers and lenders are potentially fruitful areas for future research. This line of research is probably relevant beyond infrastructure finance.
The Electrolytic Reduction of MoO3 in CaCl2-NaCl Molten Salt
Authors: Ji Nan , Jiang Feng , Peng Hao , Chen Hao , Huang Wei , Gong Yu
Published: August 2022

Electro-deoxidation reduction technology is a very attractive method used to treat oxides in metallurgical industry. In this paper, cyclic voltammetry, square wave voltammetry and open circuit chronopotentiometry were applied to study the electrochemical behavior of MoO3 cathode in the CaCl2-NaCl melt at 873 K. Through the electrolytic reduction of MoO3 at different potentials (−1.15 V, −1.45 V and −1.75 V, vs Ag/AgCl) and XRD analysis, MoO3 was found to be transformed into several intermediate compounds (CaMoO4, MoO2 and Na1.4Mo2O4) and finally reduced to metallic Mo. When the electrolysis time was increased from 3 to 18.5 h and the employed potential was reduced from −1.75 V to −2.30 V (vs Ag/AgCl), the intermediate compounds could be completely reduced to metallic Mo, and the reduction ratio of MoO3 was calculated to be 93.7%.
Characterization of TRPV4-mediated signaling pathways in an optimized human choroid plexus epithelial cell line
Authors: Hulme Louise , Hochstetler Alexandra , Schwerk Christian , Schroten Horst , Ishikawa Hiroshi , Tung Chun-Yu , Perrin Benjamin , Blazer-Yost Bonnie
Published: August 2022

The objectives of these studies were twofold: 1) to characterize the human choroid plexus papilloma (HIBCPP) cell line as a model of the blood-cerebrospinal fluid barrier (BCSFB) via morphology, tightness, and polarization of transporters in choroid plexus epithelia (CPe), and 2) to utilize Ussing-style electrophysiology to elucidate signaling pathways associated with the activation of the transient receptor potential vanilloid 4 (TRPV4) channel involved in cerebrospinal fluid (CSF) secretion. RT-PCR was implemented to determine gene expression of cell fate markers, junctional complex proteins, and transporters of interest. Scanning electron microscopy and confocal three-dimensional renderings of cultures grown on permeable supports were utilized to delineate the morphology of the brush border, junctional complexes, and polarization of key transporters. Electrophysiology was used to understand and explore TRPV4-mediated signaling in the HIBCPP cell line, considering both short-circuit current ( Isc) and conductance responses. HIBCPP cells grown under optimized culture conditions exhibited minimal multilayering, developed an intermediate resistance monolayer, retained differentiation properties, and expressed, and correctly localized, junctional proteins and native transporters. We found that activation of TRPV4 resulted in a robust, multiphasic change in electrogenic ion flux and increase in conductance accompanied by substantial fluid secretion. This response appears to be modulated by a number of different effectors, implicating phospholipase C (PLC), protein kinase C (PKC), and phosphoinositide 3-kinase (PI3K) in TRPV4-mediated ion flux. The HIBCPP cell line is a representative model of the human BCSFB, which can be utilized for studies of transporter function, intracellular signaling, and regulation of CSF production.
Hear the sounds: the role of G protein-coupled receptors in the cochlea
Authors: Zhang Zhong , Chai Renjie
Published: August 2022

Sound is converted by hair cells in the cochlea into electrical signals, which are transmitted by spiral ganglion neurons (SGNs) and heard by the auditory cortex. G protein-coupled receptors (GPCRs) are crucial receptors that regulate a wide range of physiological functions in different organ and tissues. The research of GPCRs in the cochlea is essential for the understanding of the cochlea development, hearing disorders, and the treatment for hearing loss. Recently, several GPCRs have been found to play important roles in the cochlea. Frizzleds and Lgrs are dominant GPCRs that regulate stem cell self-renew abilities. Moreover, Frizzleds and Celsrs have been demonstrated to play core roles in the modulation of cochlear planar cell polarity (PCP). In addition, hearing loss can be caused by mutations of certain GPCRs, such as Vlgr1, Gpr156, S1P2, and Gpr126. And A1, A2A, and CB2 activation by agonists has protective functions on noise- or drug-induced hearing loss. Here, we review the key findings of GPCR in the cochlea and discuss the role of GPCR in the cochlea, such as stem cell fate, PCP, hearing loss, and hearing protection.
Sphingolipidome of plasma, liver, and adipose tissues and its association with insulin response to oral glucose testing in Icelandic horses
Authors: Jorge-Smeding Ezequiel , Warnken Tobias , Grob Anne Julia , Feige Karsten , Pudert Tanja , Leung Yue Hei , Go Yun Young , Kenéz Ákos
Published: August 2022

Insulin dysregulation (ID) is a determinant of equine metabolic syndrome. Among the sphingolipids, ceramides contribute to the development of ID; however, the cross talk between the liver and adipose tissue (AT) depots and the variation among AT depots in terms of ceramide metabolism are not well understood. We aimed to characterize the sphingolipidome of plasma, liver, and AT (nuchal, NUAT; subcutaneous, SCAT; omental, OMAT; retroperitoneal, RPAT) and their associations with insulin response to oral glucose testing (OGT) in normoinsulinemic and hyperinsulinemic horses. Plasma, liver, and AT samples were collected from 12 Icelandic horses upon euthanasia and analyzed by liquid chromatography-mass spectrometry. Eighty-four targeted compounds were effectively quantified. Comparing the AT depots, greater (false discovery rate, FDR < 0.05) ceramide, dihydroceramide, and sphingomyelin concentrations and lower glucosyl- and galactosyl-ceramides were found in RPAT and OMAT than in NUAT and SCAT. Hyperinsulinemic response to OGT was associated with sphingolipidome alterations primarily in the RPAT and OMAT, whereas the NUAT sphingolipidome did not show signs of ceramide accumulation, which was inconsistent with the previously proposed role of nuchal adiposity in ID. The plasma sphingolipidome was not significantly associated with the liver or AT sphingolipidomes, indicating that plasma profiles are determined by an interplay of various organs. Furthermore, hepatic sphingolipid profiles were not correlated with the profiles of AT depots. Finally, statistically valid partial least square regression models predicting insulin response were found in the plasma ( Q2 = 0.58, R2 = 0.98), liver ( Q2 = 0.64, R2 = 0.74), and RPAT ( Q2 = 0.68, R2 = 0.79) sphingolipidome, but not in the other adipose tissues.
UHPLC‐Q‐TOF‐MS/MS Dereplication to Identify Chemical Constituents of Hedera helix Leaves in Vietnam
Authors: Pham Hong Ngoc , Tran Chieu An , Trinh Thi Diep , Nguyen Thi Ngoc Lan , Tran Phan Huynh Nhu , Le Van Nhan , Le Ngoc Hung , Phung Van Trung
Published: August 2022

Hedera helix has been reported to contain a wide range of metabolites and produce many pharmacological effects. This research demonstrates the determination and evaluation of the phytochemical profiling of H. helix grown in central Vietnam. Methanolic extract of ivy had been analyzed by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC‐Q‐TOF‐MS/MS). MS, and MS/MS experiments were manipulated using both negative and positive ionization modes to provide molecular mass information and production spectra for the structural elucidation of compounds. A total of 46 compounds including 24 triterpene saponins and other compounds were successfully identified of which four established saponin structures have been reported for the first time. This study has provided a base for building a quality control of the raw materials according to the profile of triterpene saponins and assessment of pharmaceutical ingredients of H. helix planted in Vietnam.
Architecture, Integrated Gateway Design, And Performance Evaluation for High Concurrency Access of Power Internet of Things
Authors: Yu Fei , Rao Wei , Liu Chang , Wang Jin , Zhou Liang
Published: August 2022

Power Internet of things (IoT) is deemed as a promising network platform with widely deployed infrastructure to boost efficient information delivery in the power grid. Due to the long history of the mature power grid and increased requirements from various industries, the architecture of power IoT should be carefully investigated. Specifically, a large number of end devices in the power grid are required to simultaneously report their sensed information to the management side. However, there are few works related to the uniform communication mechanism to support various devices made by different manufacturers. In this paper, we study the architecture of power IoT for high concurrency access. For each layer of power IoT, we study its fundamental structure and functionality. Moreover, according to the architecture of power IoT, we propose an integrated gateway to support multiple end device simultaneous access. The simulation results verify that the proposed gateway can work well in different network traffic and communication protocols.
Sine-Weibull Geometric Mixture and Nonmixture Cure Rate Models with Applications to Lifetime Data
Authors: Angbing Irene Dekomwine , Nasiru Suleman , Jakperik Dioggban
Published: August 2022

In this study, two new distributions are developed by compounding Sine-Weibull and zero-truncated geometric distributions. The quantile and ordinary moments of the distributions are obtained. Plots of the hazard rate functions of the distributions show that the distributions exhibit nonmonotonic failure rates. Also, plots of the densities of the distributions show that they exhibit decreasing, skewed, and approximately symmetric shapes, among others. Mixture and nonmixture cure rate models based on these distributions are also developed. The estimators of the parameters of the cure rate models are shown to be consistent via simulation studies. Covariates are introduced into the cure rate models via the logit link function. Finally, the performance of the distributions and the cure rate and regression models is demonstrated using real datasets. The results show that the developed distributions can serve as alternatives to existing models for survival data analyses.
A Robust Convolutional Neural Network for 6D Object Pose Estimation from RGB Image with Distance Regularization Voting Loss
Authors: Ullah Faheem , Wei Wu , Daradkeh Yousef Ibrahim , Javed Muhammad , Rabbi Ihsan , Al Juaid Hanan
Published: August 2022

Six-degree (6D) pose estimation of objects is important for robot manipulation but at the same time challenging when dealing with occluded and textureless objects. To overcome this challenge, the proposed method presents an end-to-end robust network for real-time 6D pose estimation of rigid objects using the RGB image. In this proposed method, a fully convolutional network with a features pyramid is developed that effectively boosts the accuracy of pixelwise labeling and direction unit vector field that take part in the voting process for object keypoints estimation. The network further takes into account measuring the distance between pixel and keypoint, which aims to help select accurate hypotheses in the RANSAC process. This avoids hypothesis deviations caused by the errors due to direction unit vectors in cases of distant pixels from keypoints. A vectorial distance regularization loss function is used to help Perspective-n-Point find 2D-3D correspondences between 3D object keypoints and their estimated corresponding 2D counterparts. Experiments are performed on widely used LINEMOD and occlusion LINEMOD datasets with ADD (-S) and 2D projection evaluation metrics. The results show that our method improves pose estimation performance compared to the state-of-the-art while still achieving real-time efficiency.
Pigeon Inspired Optimization with Encryption Based Secure Medical Image Management System
Authors: Geetha B. T. , Mohan Prakash , Mayuri A. V. R. , Jackulin T. , Aldo Stalin J. L. , Anitha Varagantham
Published: August 2022

Presently, technological advancements in the healthcare sector pose a challenging problem relevant to the security and privacy of health-related applications. Medical images can be considered significant and sensitive data in the medical informatics system. In order to transmit medical images in an open medium, the design of secure encryption algorithms becomes essential. Encryption can be considered one of the effective solutions for accomplishing security. Although numerous models have existed in the literature, they could not adaptable to the rising number of medicinal images in the health sector. At the same time, the optimal key generation process acts as a vital part in defining the performance of the encryption techniques. Therefore, this article presents a Pigeon Inspired Optimization with Encryption-based Secure Medical Image Management (PIOE-SMIM) technique. The proposed PIOE-SMIM approach majorly concentrates on the development of secret share creation (SSC) and the encryption process. At the initial stage, the medical images are converted into a collection of 12 shares using the SSC approach. In addition, an elliptic curve cryptography (ECC) scheme is employed for the encryption process. In order to optimum key creation procedure in the ECC model, the PIO technique is exploited with the aim of maximizing PSNR. Finally, on the receiver side, the decryption and share reconstruction processes are performed to construct the original images. The PIOE-SMIM model displayed an enhanced PSNR of 59.37 dB in image 1. Improved PSNR of 59.53 dB is given for image 5 using the PIOE-SMIM model. For demonstrating an enhanced performance of the PIOE-SMIM method, a widespread experimental study is made and the results highlighted the supremacy of the PIOE-SMIM model over other techniques.
Medical Social Security System Considering Multisensor Data Fusion and Online Analysis
Authors: An Ying
Published: August 2022

At present, multi-sensor data fusion technology has been applied in many fields, and we have to understand the algorithm principle of multisensor data fusion technology, master the basic theory of multisensor data fusion technology, and analyze the application field of multisensor data fusion technology. The technical challenges of its application area should be understood. The discussion on its development direction has promoted the wide application of multisensor data fusion technology. By improving the query planning, query interpretation, and cache query optimization mechanism of different data organization models, a scalable and efficient distributed hybrid online analytical processing system is designed and implemented. With the opening of the medical system reform, the construction of the medical security system will be continuously improved. The in-depth reform of the medical security system will affect the medical treatment of more than one billion people, involving thousands of households, and it is a great cause for the welfare of the people. In this paper, exploration and research are carried out, combined with the basic algorithm and typical application of data fusion, and the construction of urban residents’ medical insurance is studied. The experimental results show that the Cavani index of medical expenses generally shows a downward trend in urban and rural areas, and the urban area has decreased from −0.1916 in 2012 to −0.2995 in 2020. This paper focuses on the in-depth study of the development process, actual situation, and existing problems of the social medical insurance system for urban residents, compares the development models of urban medical insurance in other places, and tries to put forward valuable and constructive countermeasures for the medical insurance system for urban residents.
Time Series Anomaly Detection Model Based on Multi-Features
Authors: Tang Hengyao , Wang Qingdong , Jiang Guosong
Published: August 2022

For Internet information services, it is very important to closely monitor a large number of key time series data generated by core business for anomaly detection. Although there have been many anomaly detection models in recent years, its practical application is still a big challenge. The model usually needs repeated iteration and parameter adjustment; and for different types of time series data, we need to select different models. Therefore, this paper proposes an anomaly detection model based on time series. The model first designs the statistical features, fitting features, and time-frequency domain features for the time series, and then uses the random forest integration model to automatically select the appropriate features for anomaly classification. In addition, this paper presents an anomaly evaluation index ADC score with timeliness window, which adds the time delay factor of anomaly detection on the basis of F1-score. We use the KPI time series, a representative key performance index in the industry, as the experimental data. It is found that the ADC score of the anomaly detection model in this paper reaches the level of 0.7–0.8, which can meet the needs of practical application.
[Retracted] A PCA‐DEA‐Based Model for Assessing the Sustainability of Marine Economy
Authors: Yao Haihui , Huang Jianping , Li Junhua
Published: August 2022

One of the most important and continuously growing research areas in marine ecology is assessing the sustainability of ecosystems. The concept is traditionally approached by quantifying different anthropogenic pressures, such as top‐down effects, overexploitation, invasive species, overfishing, and pollution. However, this perspective has been criticized for its inability to capture the complex interactions between natural factors (such as climate change), human factors, and sociopolitical factors that shape ecosystems. In this paper, we present a new structural model for assessing the sustainability of marine ecosystems, PCA‐DEA‐based model, as an extension to current models that incorporates these key interfaces into dynamic system modeling by including trade‐offs on horizontal scales (e.g., decision making).
Review of Digital Economy Research in China: A Framework Analysis Based on Bibliometrics
Authors: Xu Yanmin , Tao Yitao , Zhang Chunjiong , Xie Mingxing , Li Wengang , Tai Jianjiang
Published: August 2022

This article combs the present situation and future development trend of digital economy research in China by means of literature measurement. On the one hand, China’s digital economy presents a framework system of industrial digitization, digital industrialization, digital governance, and data value. On the other hand, digital economics has gradually become a dominant science and is constantly challenging the traditional economic research framework. Data are no longer the traditional data, and the data-driven economic and social innovation development model is the future trend. Data privacy, data protection, data ethics, data assets, and so on will become the focus of academic research.
Information Security Risk Management Model for Big Data
Authors: Yang Min
Published: August 2022

In the current society of rapid expansion of information, big data have achieved vigorous development in all walks of life, considerably promoting data transmission and information sharing. Meanwhile, individuals are becoming increasingly reliant on big data and the Internet, but at the same time, the threat of information security posed by big data is becoming increasingly visible. As a result, how to protect the information security of big data has piqued the interest of both government and businesses. The essence of information security management is risk management, which is closely related to each other. Therefore, this study focuses on the following two aspects of research work. On the one hand, most existing risk management models merely describe risk management in the abstract from a macro-level, and they lack research on risk assessment, making them ineffective. This research builds a novel information security risk management model on the basis of existing risk management models based on the concept of multidimensional risk management. To achieve multidimensional dynamic management of big data risks and to keep them within an acceptable range as much as possible, the model is divided into five levels and two dimensions. On the other hand, this research also optimizes and improves the fuzzy mathematical analysis method and proposes a fuzzy comprehensive assessment method as the core algorithm for the risk assessment layer in the model. As a post-event risk assessment method, the advantage of this method is that it can comprehensively consider factors affecting risk and can quantify some assessment factors in the real network to achieve an effective combination of qualitative and quantitative, thereby providing a basis for decision-making in risk analysis and risk control. Finally, the effectiveness of the risk model in the real application is verified by example analysis, and it is intended that the study work would provide assistance and assurance for big data information security management.
[Retracted] Analysis of the Influence of Rural Family Education Environment on School‐Age Children’s Social Behavior and Patterns
Authors: Yao Wenwen , Zhen Ying , Zhang Yu
Published: August 2022

Family education will have an important impact on children’s body and psychology. It is different from social education and school education. It is mainly based on parents’ words and deeds. Children enhance their life experience through the family’s living atmosphere. Restricted by geographical conditions and economic level, family education is not given enough attention, and children’s social behavior is more prone to problems. Therefore, rural primary more needed to pay attention to the impact of family education on children and promote the healthy development of children’s physical health. Children’s social disorder behavior is currently the most common phenomenon that hinders the normal development of children’s interpersonal relationships in the physical and mental development of children in my country. This problem is not only reflected in the psychology of children with social disabilities, but also in normal children and children with social disabilities in daily social interactions. In the current product design market, a single product cannot comprehensively solve the practical problems encountered by children with social disabilities. Therefore, it is necessary to explore the possibility of experience design with multidimensional perspectives and multidisciplinary integration. This paper analyzes the current situation of children’s social behavior in a rural family education environment and expounds the problems existing in rural family education and the impact of rural family education on children’s social behavior. To provide a reference for improving children’s social behavior in my country.
The Relationship between Body Mass Index and Physical Activity Participation Rate Design Based on Fuzzy Breakpoint Regression Design
Authors: Wu Jinhao , He Lixin
Published: August 2022

Obesity is a global public health problem in modern society. Body mass index (BMI) can measure whether a person’s body is in obesity and health. Body mass is the quality of human body, which is a comprehensive and relatively stable characteristic of human body structure, physiological function, and psychological factors, and body mass is the basis of heredity and acquisition. Physical exercise is a kind of physical activity that people do in their spare time in order to exercise their body and mind. In this paper, we take the physical health problem of obesity as the background and combine the fuzzy breakpoint regression method to design the body mass index and physical exercise participation rate. The relationship between the body mass index and physical exercise participation rate design based on fuzzy breakpoint regression in this paper is mainly discussed as follows: background: the obesity rate is rising and chronic diseases caused by obesity affect health; results: jumps were observed for body health indices above 24.9 kg/m2, while participation rates in physical activity decreased compared to the normal weight range; and conclusion: the greater the weight of the group, the less willingness to participate in physical activity and the lower the rate of participation in physical activity.
Effect of Phyto‐Assisted Synthesis of Magnesium Oxide Nanoparticles (MgO‐NPs) on Bacteria and the Root‐Knot Nematode
Authors: Khan Azhar U. , Khan Masudulla , Khan Azmat Ali , Parveen Aiman , Ansari Sajid , Alam Mahboob
Published: August 2022

The root‐knot nematode was examined using magnesium oxide nanoparticles (MgO‐NPs) made from strawberries. The biologically synthesized MgO‐NPs were characterized by UV, SEM, FTIR, EDS, TEM, and dynamic light scattering (DLS). Nanoparticles (NPs) were examined using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) and shown to be spherical to hexagonal nanoparticles with an average size of 100 nm. MgO‐NPs were tested on the root‐knot nematode M. incognita (Meloidogynidae) and the plant pathogenic bacteria Ralstonia solanacearum. The synthesized MgO‐NPs showed a signiﬁcant inhibition of R. solanacearum and the root‐knot nematode. MgO‐NPs cause mortality and inhibit egg hatching of second‐stage juveniles (J2) of M. incognita under the in vitro assay. This study aims to examine the biological activity of biogenic MgO‐NPs. The findings marked that MgO‐NPs may be utilized to manage R. solanacearum and M. incognita and develop effective nematicides. In addition, the antioxidant capacity of MgO‐NPs was determined by using 2, 2‐diphenyl‐1‐picryl‐hydrazyl‐hydrate (DPPH).
SARS‐CoV‐2 Transmission by Arthropod Vectors: A Scoping Review
Authors: Nekoei Shahin , Khamesipour Faham , Benchimol Marlene , Bueno-Marí Rubén , Ommi Davood
Published: August 2022

COVID‐19 is a respiratory disease of worldwide importance as it has brought enormous health problems to the world’s population. The best‐known way of transmission of the virus is through aerosolization. However, research is needed to explore other transmission routes. Researchers hypothesized that arthropods could transmit SARs‐CoV‐2. This study is aimed at reviewing research on arthropods as possible reservoirs and/or vectors of SARS‐CoV‐2, the causative agent of COVID‐19. Following PRISMA guidelines, we conducted a systematic review using several electronic databases/academic searches with the search terms “arthropods,” “coronavirus,” and “transmission.” A total of 64 unique articles were identified, of which 58 were included in the review. The SARS‐CoV‐2 virus is tiny and invisible to the naked eye, and its presence in stools, droplets, and surfaces was detected. One doubt is whether insects can transmit the virus from one place to another. Thus, a healthy carrier of the COVID‐19 virus can be at the root of the contamination of their community or their family through the transport of the virus by insects from the interior (flies, cockroaches, etc.) from their feces and food surfaces. Hygiene care within communities and families becomes a prime factor. Coronavirus infection is a significant public health problem around the world. The prevention and control of outbreaks remain very important, even with the production of new vaccines. The main option to achieve this is the proper management of the transmission of the virus. The registry of infected people is currently the basis for the transmission of COVID‐19. However, questions about the possibility of infection from other sources and its prevention are not receiving adequate attention. Numerous studies have shown the possibility that SARS‐COV‐2 fragments could have a longer life than shed respiratory droplets. Also, this virus is larger than those of other coronavirus families.
Knowledge Sharing Motivation, Behavior, and Creativity of Knowledge Workers in Virtual Organizations
Authors: Jin Jian , Suntrayuth Sid
Published: August 2022

Focusing on the basic research subject of “seeking effective ways to enhance knowledge workers’ creativity,” this paper has surveyed a total of 208 employees from 11 Chinese high‐tech enterprises. Based on review and analysis of relevant literature, this paper has constructed a moderating effect model including mediating factors relying on the social cognitive theory and tested the model by hierarchical multiple regression. The results show that there is a significant positive correlation between knowledge sharing motivation and creativity of members in a virtual organization. Knowledge sharing behavior plays a partial mediating role between knowledge sharing motivation and creativity, and self‐efficacy moderates the complete mediating effect of knowledge sharing behavior on the relationship between knowledge sharing motivation and creativity. These conclusions enrich the theory of the relationship between knowledge sharing motivation and creativity, and enable enterprises to understand the importance of employees’ knowledge sharing motivation and the ways to stimulate employees’ creativity by activating their knowledge sharing behavior.
Access Control Model Scheme based on Policy Grading in Natural Language Processing Blockchain Environment
Authors: Huang Jie , Wu Dehua
Published: August 2022

In order to solve many problems such as secure storage of access policies and distrust of third parties in complex and dynamic big data environment, a hierarchical access control model under block chain environment (BP-ABAC) is proposed. Access control policies are stored in blockchain in the form of smart contracts, and access control policies are classified in contract design. Users can obtain the access permission of the corresponding policy set according to the rating evaluation. Access to a resource is obtained when the request attribute matches the policy in the policy set. The simulation results show that the model can grant corresponding access control permissions according to different users’ access requests, improve the time efficiency and accuracy of the access control process, and improve the security and privacy of the storage of access policies and the interaction of data sharing.
Effectiveness of a Community Health Worker-Led Intervention on Knowledge, Perception, and Prostate Cancer Screening among Men in Rural Kenya
Authors: Mbugua Ruth Gathoni , Karanja Simon , Oluchina Sherry
Published: August 2022

Background. Globally, an increase in mortality from prostate cancer (PC) remains a big challenge with disparities existing with a slight preponderance among men in low and middle-income countries. Prostate cancer is a leading cause of mortality among men in sub-Saharan Africa. In Kenya, despite the majority of men presenting with advanced prostate cancer for treatment, knowledge and screening for prostate cancer is low. The study aimed to examine the effectiveness of a community health worker-led education intervention on knowledge, perception, and PC screening. Methods. This was a quasiexperimental study among Kenyan men aged 40–69 years. The intervention site was Gatundu North subcounty and the control site was Kiambu subcounty in Kiambu County. Stratified random sampling was applied to select 288 respondents per arm of the study. We used a pretested interviewer-administered questionnaire to collect data at baseline and 6 months postintervention. Pearson’s chi-square test was used for data analysis. Results. Awareness of prostate cancer significantly increased postintervention

P
<
0.05

. The proportion of respondents who had good knowledge of prostate cancer increased significantly from 49% to 76.4%

P
<
0.05

in the intervention arm. The proportion of respondents with a high perception of self-vulnerability increased significantly from 26% to 42.1%

P
<
0.05

. The proportion of men who had undergone PC screening significantly increased from 4.5% to 20.4%

P

<

0.05

in the intervention arm. In postintervention, there was a statistically significant difference in the proportion of men screened for prostate cancer in the intervention and control arm

P
<
0.05

. Conclusion. Health education by community health workers during household visits increased awareness and knowledge, perception, and uptake of PC screening. Utilization of community health worker delivered education is an effective strategy that requires to be adopted to enhance screening.
Internet of Things Remote Piano Information Teaching System and Its Control Method
Authors: Fan Yangjie
Published: August 2022

In order to change the current piano teaching mode and develop towards digitalization, this paper puts forward the Internet of Things remote piano information teaching system. The digital electric piano teaching system is controlled by multimedia computer. It is a kind of music teaching form composed of electric piano and other electronic keyboard instruments, music auxiliary teaching system, and music production software. It integrates viewing, listening, and practicing and changes the traditional one-to-one teaching mode. Its core structure adopts professional audio processing chip and processor to realize controllable digital audio communication channel, which solves the interference problem well, and realizes classroom simulation functions such as centralized teaching, personal guidance, personal demonstration, group demonstration, and group practice. The application results show that the average learning time of the students who pass the intelligent digital electric piano teaching system is reduced by 14%; After two months of study, 46 students still like the piano through the intelligent digital electric piano teaching system, with a retention rate of 92%, which is significantly higher than the 38 students who study the traditional piano, with a retention rate of 76%. Conclusion. The system makes teaching easier and more efficient.