bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Pathogen Characteristics and Nursing Factors of Tonsil Infection Based on Regression Equation
Authors: Zhang Longfang , Yang Yuanyuan
Published: June 2022

In order to meet the needs of the analysis and application of regression equation in clinical medicine of tonsil infection, this paper focuses on the semiparametric regression model method, cross-validation method, empirical method, and multiple regression equation analysis of atypical data using regression equation. The general method of analyzing this kind of data is given, and the parameter estimation and hypothesis testing of the model are systematically studied. The experimental results showed that among the 90 paraffin-embedded tissue specimens of chronic tonsillitis and adenoid hypertrophy in this study, 26 out of 49 male children were EBERs positive, accounting for 53.06% of male children (26/49 cases). 28 of the 41 female children were positive, accounting for 68.29 of the female children (28/41 cases). There were 14 cases in infant group, 20 cases in preschool age group, 25 cases in school-age group, and 31 cases in adolescence group; the EBERs-positive rate was 42.86% (6/14 cases) in early childhood and 55.00% in early school-age (11/20 cases), and the EBERs-positive rate was 60.00% in school-age group (15/20 cases) and 70.97% in adolescent group. The results showed that the latent infection rate of adenoid hypertrophy EBV in children with chronic tonsillitis showed no significant difference between genders. It is proved that the regression equation method can meet the needs of clinical analysis and application of tonsil infection.
Clinical Efficacy of PEG-IFNα-2a and PEG-IFNα-2b in the Treatment of Hepatitis B e Antigen-Positive Hepatitis B and Their Value in Improving Inflammatory Factors and Hemodynamics in Patients: A Comparative Study
Authors: Jia Nina , Gao Wei , Fan Xiaohong , Gao Hong , Li Xueqing , Mi Biantao , Yang Jie
Published: June 2022

Objective. To compare the merits and demerits of PEG-IFNα-2a and PEG-IFNα-2b for the treatment of hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB). Methods. Clinical files from eighty-four CHB patients admitted to the Second Hospital of Shanxi Medical University between January 2018 and January 2019 were retrospectively analyzed and assigned to two groups: group 2a treated with PEG-IFNα-2a and group 2b treated with PEG-IFNα-2b. The clinical efficacy was compared between the above two arms, and the liver function (ALT, AST, HA, LN, and IV-C), HBV-DNA, HBsAg, HBeAg, and inflammatory factors (IFs, IL-1β, IL-6, IL-8, and TNF-α) were tested at 12 weeks (T1), 24 weeks (T2), and 48 weeks (T3). The alterations of hemodynamics (SBP, DBP, MAP, and CVP), cardiac function (LVEF and BNP), and the incidence of adverse reactions (ARs) during treatment were recorded. Finally, the patients were followed up for 2 years to investigate the quality of life (QOL) as well as the positive seroconversion rate of HBsAg and HBeAg. Results. The overall response rate was similar in the two arms (

P
>
0.05

). After treatment, the liver function, HBV-DNA, HBsAg, HBeAg, IFs, hemodynamics, and cardiac function were enormously improved (

P
<
0.05

), with faster improvement in group 2b compared with group 2a (

P
<
0.05

). The investigation of ARs identified notably lower incidence rates of alopecia, thrombocytopenia, and granulocytopenia in group 2a as compared to group 2b (

P
<
0.05

). The prognostic follow-up results revealed no distinct difference in the QOL score and the positive seroconversion rate of HBsAg and HBeAg (

P
>
0.05

); however, the quantitative results of HBV-DNA, HBsAg, and HBeAg in group 2b were lower than those in group 2a (

P
<
0.05

). Conclusions. Both PEG-IFNα-2a and PEG-IFNα-2b have excellent and stable therapeutic effects on HBeAg-positive CHB, among which PEG-IFNα-2b renders a faster treatment process but higher side effects, which can provide valuable references when choosing a treatment plan for CHB.
Feature Extraction Method of Electronic Information Based on Statistical Correlation
Authors: Sun Zhengkai , Yang Haidong
Published: June 2022

Since the society enters the information age, science and technology have changed with each passing day. Electronic information has deeply affected social development and people’s life. Based on the statistical correlation algorithm, this study analyzes the establishment model of statistical correlation algorithm. Then, the feature extraction technology of electronic information is obtained according to the statistical correlation algorithm, which promotes the development of electronic information., Afterwards, the feature extraction methods of electronic information among four cities of Beijing, Shanghai, Chongqing and Tianjin are compared and analyzed in detail. The experimental results show that the electronic information feature extraction method based on statistical correlation can be well applied in four municipalities directly under the central government, which provides some theoretical and experimental support for the electronic information feature extraction method in our country.
The Effect of Powder Detergent Water on Shrinkage Cracks of Soil Due to Drying
Authors: Zhang Shaowei , Li Dongdong
Published: June 2022

In this study, the effect of powdered detergent content in grey water on the evaporation and cracking characteristics of soils used in agricultural irrigation was investigated. Soil samples treated with different concentrations of detergent solutions (mass of powder detergent to soil mass of 0, 0.2%, 0.4%, 0.8%, 1.6%, and 3.2%) were used in laboratory evaporation testing to obtain the variation water content and cracking images during the evaporation process. Through image processing technology, the crack ratio and fractal dimensions of the cracks were used as evaluation indexes to quantitatively analyze the crack development of samples during the evaporation process. The results show that the water content of the soil samples treated with the detergent solution slightly increases compared to the control soil sample with no detergent. The maximum difference in water content between the samples with and without 0.8% detergent is 7.8%. The total time of the appearance of initial cracks of soil samples treated with detergent was shorter at a higher water content. The final crack ratio and fractal dimensions of the samples treated with different detergent solutions were all larger than the control sample. The soil samples with 1.6% and 3.2% detergent have precipitation of the grains during the evaporation process and form a flocculent layer on the surface of the sample. The dispersion of the soil samples was enhanced significantly after testing. The purpose of this study is to provide some valuable insights into application and management of grey water irrigation in arid and semi-arid areas.
Model Parameter Estimation Method on Multichannel Structural Response from Turbulence Flutter Test
Authors: Duan Shiqiang , Zheng Hua , Zhang Ziwei , Wang Jianzhu , Fang Guanyu
Published: June 2022

Flutter design is important for the design of new aircraft types, for which flutter tests are an important verification measure. Atmospheric turbulence excitation is a common form of excitation in flutter flight tests. The modal parameter estimation of the turbulence response is a key aspect to ensure accurate data processing of flutter test results. Atmospheric turbulence excitation acts on the structural system, and the turbulence response thus simultaneously contains both the randomness of the excitation signal and the determinism of the structure system. In view of the turbulence response characteristics, this paper addresses the incoherence of atmospheric turbulence excitation and the orthogonality of the frequency domain from a multichannel response. The turbulence response is used to perform modal parameter identification in the frequency domain. The power spectral density matrix can be calculated from the multichannel turbulence response using the periodogram method. Singular value decomposition is then performed on the power spectral density matrix at each spectral pin based on the orthogonality of the frequency domain. The maximum singular value of each spectral pin forms a curve over the entire frequency band, which is the autopower spectral density function of the system, the system is directly identified at the frequency domain using the polynomial fitting in the frequency domain, and the modal parameters (frequency, damping ratio) are calculated according to the fitted transfer function. This paper verifies the theoretical feasibility of the proposed method using simulation data. The engineering applicability is verified based on the turbulence response from the flutter flight test of a certain aircraft type.
Research on Optimization Strategy of Task Scheduling Software Based on Genetic Algorithm in Cloud Computing Environment
Authors: Yu Zhuoyuan
Published: June 2022

In order to improve the task scheduling strategy, a method based on genetic algorithm in cloud computing environment was proposed. First, the independent task scheduling algorithm and associated task scheduling algorithm commonly used in cloud computing are studied and compared, respectively, and their application characteristics, advantages, and disadvantages are analyzed in detail. Second, an independent task scheduling strategy based on multipopulation genetic algorithm is proposed for independent task scheduling in cloud environment, considering the scheduling time, scheduling cost, and system resource utilization of task set. The implementation steps of the algorithm are given in detail. Finally, the simulation experiment is carried out on Cloud Sim platform. The experimental results show that computing resource

M

is 10, subtask

N

is 2000, population size

S

is 80, and ETC matrix and RCU array are randomly generated by the system. As the number of iterations increases, the scheduling scheme formed by MCGA and CGA is more obvious and close to the subtask execution cost optimization. Finally, the optimized scheme is basically formed. However, the scheduling scheme formed by TGA has no obvious optimization effect on the subtask execution cost. It is proved that the algorithm proposed in this paper can effectively optimize the task scheduling efficiency and improve the utilization of cloud computing resources at the same time, providing a feasible idea and method for task scheduling in the cloud computing environment.
The Influence of Sports Dance on the Physical and Mental Development of Contemporary College Students Based on Health Detection
Authors: Huang Huali
Published: June 2022

The healthy growth of college students is related to the future development of the country and the prosperity of the nation. Under fierce social competition, college students are faced with academic pressure and employment pressure, resulting in the failure to improve their physical and mental health and their low self-acceptance level. Faced with such a situation, it is an important subject to solve the problem of the physical and mental health development of contemporary college students. As a sport that integrates sports and art, sports dance is worthy of in-depth discussion on the physical and mental development of college students. To analyze the impact of sports dance on the physical and mental development of contemporary college students, this paper uses an intelligent health monitoring system to monitor the health status of college students before and after physical dance exercise. It analyzes the influence of sports dance on the physical and mental development of college students from the aspects of cardiorespiratory endurance, muscular endurance, flexibility, and happiness. Finally, the results are obtained by conducting experiments with 10 college students. The experimental results show that the psychological well-being of college students who take physical dance exercise increases by 7.8%. Cardiorespiratory endurance and flexibility are both improved accordingly. Physical dance exercise promotes the physical and mental development of contemporary college students.
Spatial‐Temporal Evolution and Influencing Factors of Urban Green Innovation Efficiency in China
Authors: Lu Chengwu , Chen Min , Tian Guixian
Published: June 2022

Promoting green urban development has become a common consensus to address environmental pollution and ecological damage, but we know little about the measurement and drivers of urban green innovation efficiency (GIE). In this article, firstly, we established a framework for assessing urban green innovation efficiency through multidimensional data, then used the spatial econometric model to reveal the spatiotemporal evolutionary characteristics of urban GIE, and, finally, analyzed the influencing factors and spatial spillover effects of urban GIE. The results show the following: (1) The overall urban GIE in China was low and had significant spatial agglomeration, mainly concentrated in the Yangtze River Delta and Pearl River Delta regions with spatial locking characteristics, while the GIE of cities in undeveloped regions does not change much. (3) There was much room for improvement in the input‐output system of green innovation, considering that the sources of inefficiency in most cities were insufficient investment in scientific and technological innovation personnel and innovation environment, excessive environmental pollution, and limited technological output. (4) Foreign direct investment, financial development, and manufacturing industry agglomeration had positive effects on urban GIE. These research findings and policy implications are of certain reference value for other emerging developing countries to implement urban governance and green development.
Enhancing Text Generation via Parse Tree Embedding
Authors: Duan Dagao , Zhang Qiuli , Han Zhongming , Xiong Haitao
Published: June 2022

Natural language generation (NLG) is a core component of machine translation, dialogue systems, speech recognition, summarization, and so forth. The existing text generation methods tend to be based on recurrent neural language models (NLMs), which generate sentences from encoding vector. However, most of these models lack explicit structured representation for text generation. In this work, we introduce a new generative model for NLG, called Tree-VAE. First it samples a sentence from the training corpus and then generates a new sentence based on the corresponding parse tree embedding vector. Tree-LSTM is used in collaboration with the Stanford Parser to retrieve sentence construction data, which is then used to train a conditional discretization autoencoder generator based on the embeddings of sentence patterns. The proposed model is extensively evaluated on three different datasets. The experimental results proved that the proposed model can generate substantially more diverse and coherent text than existing baseline methods.
Weighted Mean Annual Rain Height Applied to Rain Attenuation Prediction on Earth-Space Links
Authors: Lin Leke , Zhang Shoubao , Zhang Xin , Hao Xiaojing , Zhao Zhenwei , Zhu Qinglin , zhang Rui
Published: June 2022

Rain height is crucial for rain attenuation prediction along slant paths, such as Earth-space links. The global digital map of the mean annual rain height is given in Recommendation ITU-R P.839-4. The disadvantage of this model is that heavy rainfall in most regions of the middle and high latitudes of the world is typically concentrated over a few months, such as summer in North China, and the mean rain height during these months and the mean annual rain height are often significantly different. In this study, a new weighted mean annual rain height is proposed by using the ratio of the mean monthly rainfall to the mean annual rainfall as the weight. The analysis shows that the weighted mean annual rain heights have been closer to the statistical rain heights during heavy rainfall in general. On the other hand, the work of this paper helps to improve the accuracy of the rain attenuation prediction model on Earth-space links in China. However, the weighted mean annual rain heights have different characteristics for different rainfall climate zones. This study will contribute to the research of rain attenuation modelling on Earth-space links.
Analytical Solutions to Two-Dimensional Nonlinear Telegraph Equations Using the Conformable Triple Laplace Transform Iterative Method
Authors: Deresse Alemayehu Tamirie
Published: June 2022

The conformable fractional triple Laplace transform approach, in conjunction with the new Iterative method, is used to examine the exact analytical solutions of the (2 + 1)-dimensional nonlinear conformable fractional Telegraph equation. All the fractional derivatives are in a conformable sense. Some basic properties and theorems for conformable triple Laplace transform are presented and proved. The linear part of the considered problem is solved using the conformable fractional triple Laplace transform method, while the noise terms of the nonlinear part of the equation are removed using the novel Iterative method’s consecutive iteration procedure, and a single iteration yields the exact solution. As a result, the proposed method has the benefit of giving an exact solution that can be applied analytically to the presented issues. To confirm the performance, correctness, and efficiency of the provided technique, two test modeling problems from mathematical physics, nonlinear conformable fractional Telegraph equations, are used. According to the findings, the proposed method is being used to solve additional forms of nonlinear fractional partial differential equation systems. Moreover, the conformable fractional triple Laplace transform iterative method has a small computational size as compared to other methods.
Application of Neuroengineering Based on EEG Features in the Industrial Design of Comfort
Authors: Zhou Xiaojun , Ruhaizin S. , Zhu Wei , Shen Cheng , He Xiaobo
Published: June 2022

The smart wheelchair is a service robot that can be used as a means of transportation for the elderly and the disabled. The patients were given an intelligent wheelchair designed by electroencephalogram (EEG), which was used for more than 8 hours and tested continuously for 1 month. By ridit analysis, the difference between the two groups was statistically significant (U = 3.72,

P
<
0.01

). The scores of visual analogue scale (VAS) and joint ground visuality (JGV) in the observation group were significantly better than those in the control group. The modules of physiological function (PF), physical pain (PP), overall health (OH), vitality (VT), social function (SF), emotional function (EF), and mental health (MH) in the SF-36 scores of the two groups were significantly improved (

P
<
0.05

), and the improvement of each module in the observation group was significantly better than that in the control group (

P
<
0.05

). The levels of serum IL-6, IL-10, and superoxide dismutase (SOD) in the two groups were significantly improved (

P
<
0.05

), and the improvement of serum IL-6, IL-10, and SOD in the observation group was significantly better than that in the control group (

P
<
0.05

). It is suggested that neural engineering based on EEG characteristics can be well applied in comfort industrial design.
Effect of Sample Sources on Heavy Metal Concentration Measured in Beta Vulgaris Organs
Authors: Rodríguez Oscar E. , Hernández Diana R. , Andrade William A. , Celis Crispín A. , Pombo Luis M. , Teherán Aníbal A. , Forero Sandra P. , Velandia Javier R. , Díaz Fabio E.
Published: June 2022

Aim. Heavy metal concentration [mg/dL, MP] in soil and the transfer to vegetable organs may have a sampling effect. We compared the [MP] in soil and organ samples of Beta vulgaris collected in sites with socioeconomic differences potentially inducing phytotoxicity. Materials and Methods. Samples of Beta vulgaris and soils (n = 4 per sample of soil and plant material) were randomly collected from two distant geographic areas (Mosquera and Sibaté, Cundinamarca, Colombia). We determined the [MP] using acid digestion of HCl : HNO3 [1 : 1]; the [MP] was obtained by atomic absorption in Varian AA‐140 and Shimadzu AA‐7000 equipment. A two‐way ANOVA estimated the effect (partial η2) of the sampling site and metal type on the [MP] and transfer to the vegetable. Results. In Sibaté, the means (SD) of As_1.44 (0.18), Co_1.09 (0.51), Cr_6.21 (0.33), Ni_0.22 (0.02), and Pb_4.17 (0.87) were higher than in Mosquera (As_1.06 (0.21), Co_0.81 (0.19), Cr_3.72 (0.51), Ni_0.13 (0.04), and Pb_1.69 (0.40)) (p value <0.05). The effect of the interaction between the metal type and Beta vulgaris organs on the [MP] (0.801) in Sibaté was more meaningful than in Mosquera (0.430). Additionally, there was a strong correlation (Spearman’s ρ > 0.8, p value <0.001) between [MP_soil] and [MP_plants] and between the transfer of metals to the plant and to the leaves. Discussion. The sampling location has a differential effect on the [MP] in soil and the transfer to Beta vulgaris. Given the differential effect described, the monitoring and phytoremediation strategies must be adjusted to scenarios with potentially phytotoxic conditions.
Comparative Study of Macular Vascular Density and Retinal Thickness in Myopia Children with Different Microscope Diopters Based on OCTA
Authors: Chen Meiling , Zhao Fanning
Published: June 2022

In order to study the vascular density and retinal thickness of myopic children, a depth study was carried out on the basis of OCTA microscope. Through the methods of prospective cross-sectional research, statistical analysis, and basic data comparison, the research examination of myopia children under OCTA was successfully analyzed. There were significant differences in the density of superficial capillaries in the whole macular region, inner ring, temporal side of inner ring, and nasal side (

P
=
0.033

, 0.024, 0.018, 0.032), and there was no significant difference in other ranges (

P
>
0.05

). Macular fovea, as the most sensitive part of the retina, has pathological changes, which will also lead to serious negative effects on vision. The limitations of cross-sectional studies include the results of a relatively small sample size. After the study of OCTA in the macular region of children with myopia, it is related to the progressive atrophy of the retina and choroid in the macular region. When there are obvious pathological changes in the macular region, the thickness of the macular region becomes significantly thinner. We found that there was a positive correlation between retinal vascular density and retinal thickness in the fovea and above of myopia. The retinal thickness of the whole macular region, the inner ring and its four quadrants, and the outer ring and its four quadrants were positively correlated with SE (standard error) (all

P
<
0.05

); Foveal ring retinal thickness was not associated with SE.
Credibility Analysis of Accounting Cloud Service Based on Complex Network
Authors: Chen Xinyou , Guang Cheng , Hua Du
Published: June 2022

Compared with the previous accounting information system (hereinafter referred to as AIS), the dynamic and changing environment of accounting cloud service, cloud storage away from enterprise entities, service modules selected for purchase, and seamless dynamic configuration. With the emergence of new situations such as the reconstruction of accounting information processing process, the emergence of new features increases the information risk of enterprises. Therefore, taking reasonable and effective measures can enable enterprises to intuitively understand whether AIS is credible in the accounting cloud service environment. Referring to the existing research system in the field of reliability evaluation, this paper analyzes the current situation of accounting cloud service and its characteristics compared with the previous AIS and divides it into four parts: normative inspection, index calculation, and reliability calculation to illustrate the method system for measuring the reliability of accounting cloud service. This paper analyzes the reliability requirements and reliability attributes of accounting cloud services and constructs a reliability evaluation grade model combined with fuzzy comprehensive evaluation to guide the selection of users and the quality management of cloud accounting suppliers. Considering the complexity and dynamics of AIS reliability evaluation in accounting cloud service environment, the reliability of AIS is also affected by the complex call relationship between modules; combined with the complex network theory, a reliability analysis and evaluation method of accounting cloud service based on complex network are proposed.
Spatial Pattern and Evolution of Global Innovation Network from 2000 to 2019: Global Patent Dataset Perspective
Authors: Di Yuna , Zhou Yi , Zhang Lu , Indraprahasta Galuh Syahbana , Cao Jinjin
Published: June 2022

In the era of the knowledge economy, the improvement of national innovation systems is playing a significant role in the global entrepreneurship ecosystem. Entrepreneurs are accelerating international intellectual property applications to be competitive. What remains to be explored is the evolution of international intellectual property network in the globe. With the application of social network analysis and intellectual property application database, the global innovation network structure from 2000 to 2019 is explored. Results showed that (1) in the period 2000–2019, the global innovation network has been expanding rapidly from a sparse network to a dense and complex one. (2) Patent application is unevenly distributed in the globe. Countries such as the US, China, and Canada have been the top countries flowing in, while Japan, Korea, EU, and Switzerland have been the main countries flowing out. (3) Global innovation network shows an obvious “core‐periphery” pattern. The distribution pattern presents a quadrilateral structure with the four core regions of “US, Japan, EU, and China” as the apex. This analysis contributes to the visualization of the global layout of intellectual property and the evolution trend by analyzing intellectual property application networks. This can provide important experience reference for enterprises to study the global entrepreneurship ecosystem.
Major Challenges and Future Approaches in the Employment of Blockchain and Machine Learning Techniques in the Health and Medicine
Authors: UmaMaheswaran S. K. , Prasad G. Lakshmi Vara , Omarov Batyrkhan , Abdul-Zahra Dalael Saad , Vashistha Piyush , Pant Bhasker , Kaliyaperumal Karthikeyan
Published: June 2022

According to the benefits in safeguarding and transferring medical information, illness assessment, evaluation of “Magnetic Resonance Mapping” images, and certain other disciplines, blockchain and machine learning (ML) technology has significantly piqued attention in the healthcare domains. Formerly, those chores have been performed out along with individuals; eventually, individuals acquired attraction because to its precision and efficiency. The proposed study will examine the activities and possible capabilities of learning algorithms and blockchain in the healthcare professions focusing on these fascinating facts. Primary and secondary data analysis has been executed, with primary analysis method consisting of a survey of 150 randomly picked medicine professionals with expertise in machine learning and blockchain. They gave their answers that were being subsequently transferred to figures and employed as response variable in SPSS examining. The length of time where learning and blockchain have been used in medicine is really the independent factor. To better understand the primary and small hurdles of integrating machine learning and blockchain, a correlation investigation was done. Thereafter, secondary methodology is employed to validate the primary study results.
5G-Telecommunication Allocation Network Using IoT Enabled Improved Machine Learning Technique
Authors: Alzaidi Mohammed S. , Subbalakshmi Chatti , Roshini T. V. , Shukla Piyush Kumar , Shukla Surendra Kumar , Dutta Papiya , Alhassan Musah
Published: June 2022

Recent improvements in communication technology have undergone a significant shift over the last two decades, with state-of-the-art communication equipment, standards, and protocols simplifying the lives of consumers everywhere. For more than a decade, advancements in communication technology have mostly focused on increasing the speed with which information can be delivered and retrieved from anywhere in the globe at any time of day or night, regardless of location. Four-generation (4G) communication technologies, which have already been developed and implemented, are used to offer users with seamless access to multimedia content at transmission rates of 100 megabits per second (Mbps). It is becoming more vital to create new technologies in order to meet the growing need for faster speed as well as a variety of other advanced features. 5G networks have just recently been built as a result of extensive research and development. This has resulted in the gradual replacement of existing 4G services with new 5G networks, which are capable of transmitting multimedia content such as audio-video and high definition images, among other things, at data transmission rates in the gigabyte range or higher (up to several gigabits per second). Further recent development, in addition to the Internet of Things (IoT), which was made possible by future communication technology, is the Internet of Things-based social network. Aspects of this include the ability to connect and expanding Internet connectivity to all physical devices that consumers use to access common commercial and industrial services available on the Internet. In spite of this, with the advancement of existing high-speed communication networks, the effective interaction of devices with their inputs and responses via the Internet may be made possible through 5G Internet of Things networks. This new generation of automation and communication systems has emerged as innovative platforms for the next generation of automation and communication systems to be developed further in the future. M2M data may be utilised to more efficiently distribute resources if machine learning (ML) and optimum cell clustering are applied to the situation. It is because of this heterogeneity that the ML is able to make the best use of the remaining resources of the M2M network in order to optimise efficiency. Over the last several years, the shortage of radio frequency spectrum has proven to be the most challenging hindrance to wireless communication. This has occurred from the large number of high-frequency devices that need significant amounts of bandwidth allowance. Cognitive radio networks have been designed to meet this higher demand as a result of this increased demand.
Variability-Weighted Interpolation Algorithm Based on Fixed-Frame Sampling of Data
Authors: Cheng Bo , Zhang Mingnan , Hu Xiaomei
Published: June 2022

A spatial data interpolation algorithm is a method to transform scattered and sparse measurement data into regular and continuous applicable data. This algorithm can make the display results smooth and continuous without changing the data characteristics, which is closer to the real acquisition object. In response to the low interpolation accuracy of the inverse distance weighting (IDW) algorithm and the poor interpolation efficiency of the ordinary kriging (OK) algorithm, this study proposes a variational-weighted (VW) interpolation algorithm based on data fixed-frame sampling. By introducing the variational function of OK into IDW and taking different weight coefficients from OK, a new computational model is constructed to improve the interpolation accuracy and adapt to different types of data characteristics. In the whole interpolation process, the data are sampled in a fixed frame and a new sampling point search method is proposed to improve the computational efficiency. The study not only compares the accuracy and efficiency of the algorithm using two types of data but also tests the stability of the new algorithm for different data volumes. It is shown that VW based on a fixed-grid sampling of the data is more accurate than the inverse distance interpolation algorithm for both data types. The VW interpolation algorithm based on data lattice sampling improves the computational efficiency for featureless data and exhibits better performance in terms of accuracy and computational efficiency for data with features, compared to the common kriging interpolation algorithm. In addition, the VW interpolation algorithm based on a fixed-grid sampling of data has a more stable performance for different amounts of data.
Experimental Study on Damage and Degradation of Structure Plane in Rock Mass under Cyclic Shear Load
Authors: Hong Rubao , Jian Wenbin , Zhang Deng , Chen Ruimin
Published: June 2022

By summarizing the generalized model of the structural plane in a rock mass under a cyclic shear load and influencing factors of dynamic mechanical properties of the structural plane, the mechanism of structural plane damage and degradation is discussed, and the evolution of damage to the structural plane is ascertained from cyclic shear tests by using structural planes with different undulating angles. Based on model tests and previous studies, nonlinear constitutive equations considering the effect of structural plane damage and degradation are presented. The effects of the initial undulating angle, amplitude of the cyclic shear load, and cycle times on the strength of the structural plane, as well as the degeneration process of structural plane stiffness under a cyclic shear load, are taken into consideration in the equations. The applicability of the above-mentioned constitutive equations is analyzed with a corresponding program compiled in the FISH language in the Universal Distinct Element Code (UDEC). The UDEC numerical simulation results are verified with ones from the model test. The achievements presented in this paper are of great significance to theoretical study of the mechanical behaviors of rock masses under cyclic shear loads and to project practice.
Text Feature Extraction for Public English Vocabulary Based on Wavelet Transform
Authors: Ye Di , Shi Xiaojing
Published: June 2022

Text interpretation of public English vocabulary is a critical task in the subject of natural language processing, which uses technology to allow humans and computers to communicate effectively using natural language. Text feature extraction is one of the most fundamental and crucial elements in allowing computers to effectively grasp and read text. This paper proposes a text feature extraction method based on wavelet analysis that performs fast discrete wavelet transform and inverse discrete wavelet transform on the feature vectors under the traditional TF-IDF vector space model to address the problem of low feature differentiation of high-dimensional data in text feature extraction. In particular, due to the design of the Mallat algorithm, there is frequency aliasing in the signal decomposition process. This phenomenon is a problem that cannot be ignored when using wavelet analysis for feature extraction. Therefore, this paper proposes an improved inverse discrete wavelet transform method, in which the signal is decomposed by Mallat algorithm to obtain wavelet coefficients at each scale and then reconstructed to the required wavelet space coefficients according to the reconstruction method, and the reconstructed coefficients are used to analyze the signal at that scale instead of the wavelet coefficients obtained at the corresponding scale. Experiments on the public English vocabulary dataset reveal that the wavelet transform-based strategy suggested in this research outperforms existing feature extraction methods while maintaining greater classification accuracy while reducing the dimensionality of the TF-IDF vector space model.
Security Analysis of Smart Grids
Authors: Ibrahim Mariam , Elhafiz Ruba
Published: June 2022

An attack graph is a beneficial tool to network defenders, demonstrating the routes that an attacker can utilize to acquire entry to a target network. Cyber-attacks endanger the security of smart grids as a result of the presence of vulnerabilities in the diversified structural units establishing it. This paper introduces a new tool built using Python language and Jupyter Notebook to enumerate an attack graph for a smart grid. The smart grid is formally presented and implemented, determining system design, links, weaknesses, resources, potential attack instances, and their pre- and post-conditions. The tool is utilized to automatically determine an attack sequence in the form of a counterexample. It constructs the counterexamples, encodes those for requirement loosening, and iterates up until all attack sequences are disclosed. Then, the attack graph causing disruption of the smart grid’s workflow is graphically visualized.
Grey Relational Analysis Method for Probabilistic Double Hierarchy Linguistic Multiple Attribute Group Decision Making and Its Application to College Tennis Classroom Teaching Effect Evaluation
Authors: Wang Lihua , Li Huiming , Zhang Jianpeng , Yang Jin
Published: June 2022

The college tennis classroom teaching effect evaluation is viewed as the multiattribute group decision making (MAGDM). The probabilistic double hierarchy linguistic term set (PDHLTS) not only conforms to people’s language expression habit of “adverb + adjective” but also can accurately depict its importance in real MAGDM. Therefore, this paper comes up with the probabilistic double hierarchy linguistic grey relational analysis (PDHL-GRA) method based on the grey relational analysis (GRA) process for MAGDM based on PDHLTS environment and applies it to the college tennis classroom teaching effect evaluation. Finally, a practical case for college tennis classroom teaching effect evaluation is presented to demonstrate the steps of our method, and a comparison analysis illustrates its feasibility and effectiveness.
Influence of Aerobic Exercise Load Intensity on Children’s Mental Health
Authors: Zhao Sihong
Published: June 2022

As people have become more aware in recent years, aerobic physical exercise plays an important role in alleviating people’s mental health problems. However, traditionally, it is believed that young children do not have mental health problems. To help people change this fixed idea, and to study how to correctly adjust the load intensity of aerobic physical exercise under the condition of limited physical fitness of young children, and accurately help children’s mental health development, this paper studies the influence of aerobic physical exercise load intensity on children’s mental health. In this paper, the detection and tracking technology of video moving objects is used to analyze the data of the research object. This technique includes several commonly used and improved video analysis algorithms. The use of moving target and tracking technology and algorithms can completely extract moving targets, eliminate the phenomenon of void and nothingness, and improve data acquisition and analysis capabilities. The results show that taking part in aerobic exercise with appropriate intensity is beneficial to regulating children’s emotional state, reducing their psychological burden, enhancing their negative energy resistance, and arousing their positive participation. Compared with before aerobic exercise, the learning efficiency was improved by 6.36%.
The Use of Big Data Combined with Artificial Intelligence Neural Network Technology in Urban Spatial Evaluation System
Authors: Wang Lei , Liang Yujie , Shang Gaizhen , Song Zhiyong , Gao Peng
Published: June 2022

This exploration aims to promote the development of urbanization in China and improve the utilization rate of urban resources. First, intensive theory and spatial economics are studied. Next, an input-output urban spatial evaluation system is established based on intensive theory and data envelopment analysis (DEA). Then, deep learning (DL) is adopted for optimization, and an urban space evaluation system based on DL is proposed. Finally, the reliability level of the urban space evaluation system is tested. The results show that the model’s input and output index α values are above 0.9, and the overall reliability level is higher than 0.9, indicating that the urban space evaluation system has a high reliability. The training results of the DL model show that the mean absolute error (MAE) of model prediction decreases gradually with the increase of training time and training times. When the training lasts for 5 min, each index’ MAE is basically stable between 0.22 and 0.23, and the evaluation accuracy is obvious. The urban space evaluation system based on DL has higher evaluation accuracy, reaching 83.40%. Therefore, this exploration can provide research experience for promoting the effective utilization of urban resources and provide a reference for formulating an urbanization evaluation index system suitable for China’s national conditions.
Study on Reasonable Formation Pressure Maintenance Level for Middle-Deep Reservoirs in the Bohai Sea
Authors: Hui Cai , Xiaoyan Yang , Shujian Xie , Zhanhua Zhang , Long Wang , Yue Gao
Published: June 2022

Reasonable formation pressure maintenance level is significant to high-efficient development of oilfields. In order to study the effects of overlying strata pressure on permeability, oil-water phase permeability curve, and oil displacement efficiency, a physical simulation experiment is designed. Based on the experimental results and the oil-water phase flow theory, the production equation and the mathematical model of oil displacement efficiency considering stress sensitivity are established. And the productivity changes with pressure drop under different permeability are plotted. Then, the permeability coefficients calculated by quantitative characterization of stress sensitivity under different formation pressures are introduced into the numerical simulation model to quantitatively determine the reasonable formation pressure maintenance level of different reservoir properties. Experimental and theoretical studies show that the permeability decreases continuously with the increase in effective overlying strata pressure. In a low permeability reservoir, the more permeability decrease is caused by the increase in effective overlying strata pressure. When reservoir pressure is restored by water injection, the permeability loss is irreversible. With the increase in effective overlying strata pressure, the producer productivity decreases obviously, and the effective seepage capacity and oil displacement efficiency decrease. For reservoirs with permeability below 100 mD and high stress sensitivity, high formation pressure level should be maintained. For reservoirs with permeability of more than 300 mD, lower formation pressure is acceptable in the initial stage. The results are consistent with the actual production characteristics, which effectively guide the establishing of reasonable oilfield development strategy. It has important guiding significance to the oilfield development plans and development of the middle-deep oilfields.
Investigation of the Law of Natural Gas Phase Behavior during the Migration and Reservoir Formation
Authors: Li Longlong , Ye Jiaren , Li Minqi , Pan Lin
Published: June 2022

It is of great significance to understand the phase regime of natural gas migration under high temperature and high pressure in the DF1-1 structure of Yinggehai Basin, South China Sea, to predict natural gas accumulation and evaluate resource reserves. However, the existing methane solubility models are not suitable for the higher temperature and pressure range required under current geological conditions. Through a self-designed experimental equipment with high precision, the solubility of CH4 in deionized water can be measured in a wide range of temperatures (313.15-473.15 K) and pressures (5-200 MPa), and a reliable pressure-temperature-solubility segmented model is obtained by fitting. Using this model, we found that if the free-phase natural gas accumulated in the DF1-1 structural reservoir is completely dissolved in the water-soluble phase, the required formation water volume is much higher than the actual calculated formation water storage. Therefore, it can be inferred that the natural gas generated from the source rock of the DF13-1 structure mainly migrated and accumulated in the form of the free phase.
Exogenous H2S Protects against Septic Cardiomyopathy by Inhibiting Autophagy through the AMPK/mTOR Pathway
Authors: Zhao YuHan , Cheng QingHong
Published: June 2022

Background. Given the cardioprotective role of autophagy, this study aimed to investigate the protective effect of exogenous H2S (NaHS) on infectious cardiomyopathy through the inhibition of the AMPK/mTOR pathway. Methods. In this study, sepsis models were established by cecal ligation and puncture (CLP) induction in vivo and intraperitoneal injection of NaHS was performed. Autophagy‐ and apoptosis‐related proteins were observed by western blot, isolated myocardial tissue morphology was observed by hematoxylin‐eosin (H&E) staining, and myocardial apoptosis was evaluated by the tunnel method. The ultrastructure of autophagy was observed by using an electron transmission electron microscope. Results. In an SD rat model of cecum ligation puncture‐induced sepsis, the level of autophagy‐related proteins was significantly increased, and hematoxylin and eosin staining showed irregular myocardial bands and swollen cardiomyocytes. Following NaHS treatment, the level of autophagy‐related proteins decreased, and electron transmission microscopy revealed decreased autophagosomes. Echocardiography suggested an increase in ejection fraction and significant relief of myocardial inhibition. Conclusions. Our results suggest that NaHS treatment can attenuate the cellular damage caused by excessive autophagy through the AMPK/mTOR pathway.
Correlation Analysis of CML, sRAGE, and esRAGE and the Measure of Atherosclerosis of Coronary Heart Disease
Authors: Liu Wenjun , Ji Yuqiang , Zhang Weiwei , Fang Fei , Cai Qin , Li Ying
Published: June 2022

Objective. To investigate the correlation between CML, sRAGE, and esRAGE and the measure of atherosclerosis of coronary heart disease. Methods. From June 2019 to December 2021, there were 100 patients in all suffering from coronary heart disease (CHD) selected as the observation group. On the basis of Gensini score, they were divided into mild group (Gensini score < 12 points), moderate group (12 points ≤ Gensini score ≤60 points), and severe group (Gensini score > 60). Apart from that, 50 normal people staying in our hospital for physical examination were chosen as the control group in the meantime. N in each group was detected and compared ε-Carboxymethyl lysine (CML), soluble advanced glycation end product receptor (sRAGE), and endogenous secretory advanced glycation end product receptor (esRAGE). Pearson correlation coefficient was adapted to assay the relevance between CML, sRAGE, and esRAGE, as well as the degree of atherosclerosis in CHD. Receiver operator characteristic (ROC) curve was applied to during the evaluation of the diagnosis of CML, sRAGE, and esRAGE, as well as their combined detection of severe atherosclerosis in CHD. Results. In contrast with the control group, the level of serum CML together with sRAGE in the observation group was considerably elevated, while the level of esRAGE appeared in a downward trend (

P

 < 0.05). The level of serum CML and sRAGE was directly proportional to the measure of atherosclerosis in CHD, while the level of esRAGE was inversely proportional to the measure of atherosclerosis in CHD (

P

 < 0.05). That is to say that serum CML and sRAGE were positive in matter of the measure of atherosclerosis in CHD, while esRAGE negatively appertains to the measure of atherosclerosis in CHD (

P

 < 0.05). Serum CML, sRAGE, and esRAGE could effectively diagnose severe atherosclerosis in CHD, and the combined detection sensitivity (89.79%), specificity (77.16%), accuracy (86.12%), positive predictive value (86.63%), negative predictive value (88.59%), and area under ROC curve (AUC) (0.924) were higher (

P

 < 0.05). Conclusion. CML and sRAGE, as well as esRAGE, are bound up with the degree of atherosclerosis in CHD, which is conducive to clinical diagnosis and treatment.