bluuebunny/crossref_metadata_2025 huggingface dataset:
Hereditary hypomagnesemias in children: pathogenesis, clinical picture and treatment approaches
Authors:   Russian Children's Clinical Hospital with the Pirogov Russian National Research Medical University of the Ministry of Healthcare of Russia, Moscow, Russia, Mikhailova S.V. ,   Academician N.P. Bochkov Research Centre of Medical Genetics (RCMG) of the Ministry of Science and Higher Education of the Russian Federation, Moscow, Russia, Zakharova E.Yu. ,   Academician N.P. Bochkov Research Centre of Medical Genetics (RCMG) of the Ministry of Science and Higher Education of the Russian Federation, Moscow, Russia, Yurasova Yu.B. ,   N.N. Priorov National Medical Center of Traumatology and Orthopedics of the Ministry of Healthcare of Russia, Moscow, Russia, Petryaykina E.E. ,   Russian Children's Clinical Hospital with the Pirogov Russian National Research Medical University of the Ministry of Healthcare of Russia, Moscow, Russia
Published: December 2023

Hypomagnesaemias are the diseases characterized by the reduced level of magnesium in the body. The first mention of them appeared in the early XX century when cases in children were initially described as conditions accompanied by painful twitching in the muscles, weakness and heart rhythm disturbances, the reasons for which remained unknown for a long time. The scientific research in recent decades has only made it possible to decipher the diseases’ pathogenesis mechanisms. Primary hypomagnesaemias are hereditary monogenic diseases in which, as a result of a violation of magnesium metabolism in the body, its concentration decreases and the main clinical manifestations of the disease develop. The clinical picture of hypomagnesemia in children can be diverse and nonspecific. Early symptoms are manifested in the form of short-term involuntary painful contractions of muscles or muscle groups, weakness, cardiac arrhythmia and fatigue. As the disease progresses, more rather serious symptoms such as stunted growth, psychomotor development and epileptic seizures may occur. The severity of clinical manifestations of hereditary hypomagnesaemias correlates with the degree and duration of magnesium deficiency: from general weakness and crumpy syndrome to the development of depression of consciousness and in some cases of an unfavorable outcome. The main methods for confirmatory diagnosis of genetically determined hypomagnesaemias are molecular genetic methods. Authors represent bibliographical review and recent updates on known primary hypomagnesaemias in terms of mechanisms of pathogenesis and clinical presentation as well as their own familial case description of hypomagnesaemia in children.
ANTI-FACTOR H ANTIBODY ASSOCIATED ATYPICAL HEMOLYTIC-UREMIC SYNDROME IN CHILDREN: CLINICAL PROFILE, DIAGNOSIS AND TREATMENT
Authors:   Department of Children's Diseases No. 1 of the Belarusian State Medical University, Minsk, Republic of Belarus, Baiko S.V.
Published: December 2023

Atypical hemolytic uremic syndrome (aHUS) refers to one of the forms of thrombotic microangiopathy occurring with preferred damage to the kidneys. About 10% of all cases of aHUS in children are aHUS associated with antibodies to complement factor H (CFH-Ab-aHUS). In 90% of cases CFH-Ab-aHUS is represented by DEAP-HUS (Deficiency of Complement Factor H Related (CFHR) plasma proteins and Autoantibody Positive Hemolytic Uremic Syndrome) with a predominant deficiency of CFHR1, most often due to a homozygous deletion of CFHR3/CFHR1. CFH-Ab-aHUS is characterized by the age of onset of the disease of 4 to 12 years old; the presence of a prodrome, more often associated with gastrointestinal disorders such as vomiting and abdominal pain, less often diarrhea; relapsing course with a high risk in the first 6 months from the onset of the disease, a high proportion of adverse outcomes: death of the patient or development of end stage chronic kidney disease (CKD). Determination of the CFH-Ab titer should be performed in all children with HUS, and in case of their increase, regularly monitored during treatment. Treatment begins with eculizumab or its biosimilar until a CFH-Ab titer is obtained and, if CFH-Ab-aHUS is confirmed, it is necessary to switch to intensive plasma exchanges in combination with immunosuppressive therapy. If there are contraindications to immunosuppressive therapy or if there is no effect from it, if plasma exchanges are impossible or ineffective, if significant mutations in complement regulator genes are detected, it is necessary to continue or return to complement blocking therapy. After achieving remission of the disease, long-term monitoring of patients is required to control residual effects on the kidneys (hematuria, proteinuria, CKD) and the cardiovascular system (arterial hypertension, left ventricular myocardial hypertrophy). In patients who have reached the end stage of CKD, it is mandatory to determine the anti-CFH titer and conduct a molecular genetic research in order to determine the risks of the disease returning to the kidney graft and the need for prophylactic therapy with eculizumab or its biosimilar before and after the surgical intervention.
Vyhodnocení kolekce nálezů z hradu Pustohradu u Hořic v Podkrkonoší. Příspěvek k problematice doby provozu sídla a jeho sídelním souvislostem
Authors:   Katedra archeologie Filozofické fakulty Univerzity Hradec Králové, Drnovský Pavel
Published: December 2023

The study deals with an aristocratic residence located near the village of Lhota Svatogothardská near Hořice in the Podkrkonoší region. The original name of the castle is unknown and is referred to by its folk name – Pustohrad. In the past, undocumented excavations and a series of surface surveys were carried out on the site. The subject of the work is the evaluation of available archaeological finds. Ceramic finds make it possible to chronologically determine up to the course of the 14th century with possible overlaps into the previous and following century. Documented arrowheads correspond to this determination. The site can likely be associated with the numerous written references to members of the lower nobility, who used the name of the village Lhota as a part of their surnames.
Orthogonal wind power plants for oil and gas field facilities on land and offshore
Authors: Shishkin Nickolai Dmitrievich , Marysheva Marina Aleksandrovna
Published: December 2023

Wind and solar power plants for autonomous power supply of small oil and gas facilities with a capacity of no more than 20 kW, wind power plants in their composition – 10 kW with a power factor (energy efficiency) of no more than 0.35–0.45 are considered. An improved design of an orbital wind power plant based on a combined H-Darye-Savonius rotor has been developed. Experiments on the laboratory installation showed that the maximum values of the power factor reached 0.60, which is much higher than that of the rotors of known types of wind turbines. The values of the CRDS power factor are calculated for various geometric dimensions of the N-Darye and Savonius rotors included in its composition. With an increase in wind speed to the nominal value of 9.0 m/s for small and medium power wind turbines and a rotor diameter of 15.0 m, the combined rotor power reaches almost 60 kW. The proposed orthogonal wind power plants with a nominal capacity of up to 60 kW will be able to be used together with other power plants for autonomous power supply at oil and gas field facilities on land and at sea, and in the future at intelligent fields.
La promoción de tecnologías 4.0 para las Pequeñas y Medianas Empresas argentinas
Authors: Versino Mariana , Guido Luciana , Gorenstein Silvia , Vidosa Regina
Published: December 2023

La adopción de las nuevas tecnologías 4.0 -inteligencia artificial, Big Data, computación en la nube, Internet de las cosas, robótica avanzada, entre otras- está transformando radicalmente los sistemas productivos de los países centrales. Sin embargo, los alcances de la difusión de estas tecnologías en países periféricos como la Argentina no son homogéneos. Su impacto sobre las Pequeñas y Medianas Empresas (PyME) se caracteriza por un escaso conocimiento de las nuevas tecnologías, insuficientes recursos financieros para adoptarlas, y una baja disponibilidad de fuerza de trabajo capacitada. En este trabajo se analizan las principales políticas nacionales y provinciales orientadas a la difusión de las tecnologías 4.0, en particular aquellas que se centran en la promoción de organizaciones intermedias orientadas a las PyME, tales como los Centros Tecnológicos (CT).
Experimental Studies on the Operation of Agricultural Crops Mowing Unit with Simultaneous Chopping and Incorporation of Stubble Into the Soil
Authors: Nadykto Volodymyr , Kiurchev Sergey , Chorna Tatiana , Hutsol Taras , Mudryk Krzysztof , Głowacki Szymon , Rud Anatoliy , Shevtsova Alona , Ryabov Igor , Szwedziak Katarzyna
Published: December 2023

For harvesting crops, one-phase and two-phase methods are most often used. When implementing the second one, mounted and trailed units are used. The latter is becoming less and less used due to the problems with movement stability in the horizontal plane because of the asymmetric layout. A stubble background, which is susceptible to solar and wind influences, is formed as a consequence of application of the mounted harvesting unit, As a result, the field’s soil in the inter-swath space intensively loses moisture. A harvesting unit based on a tractor with rear steerable wheels has been designed to eliminate this shortcoming. A header is mounted on its front hitch linkage system, and a disc harrow is mounted on the rear one. During the working movement, such a harvesting unit mows the crop into swaths, chops the stubble in the inter-swath space, and simultaneously incorporates it into the soil. This article presents the operation results of such a unit for harvesting winter wheat, oats, and sudan grass. Research has established that oscillations in the deviations of the mowed crops’ swaths from a straight line are of low frequency. The variances spectra of this process, as follows from the Analysis of normalized spectral densities, are concentrated in the frequency range of 0-0.5 m−1. The mean value velocities of the harvesting unit are 2.13-2.61 m·s−1, which is 0.17-0.21 Hz. The variances of oscillations in the header operating width, the cut crop’s swath width, and the disc harrow’s width are concentrated in approximately the same low-frequency range, the maximum value of which is small and does not exceed 0.9 m−1 or 0.37 Hz. The oscillation processes of the mowed crops’ stubble height have a higher frequency. The cutoff frequency of their normalized spectral densities is at the level of 3.0 m−1. In terms of time, considering the harvesting unit movement velocity of 2.13-2.61 m·s−1, this is 1.02-1.25 Hz. At the same time, oscillations in the stubble height of mowed crops are characterized by small variances, the maximum value of which does not exceed 11 cm2.
Heavy Metal Content in Substrates in Agricultural Biogas Plants
Authors: Derehajło Stanislaw , Tymińska Magdalena , Skibko Zbigniew , Borusiewicz Andrzej , Romaniuk Waclaw , Kuboń Maciej , Olech Elżbieta , Koszel Milan
Published: December 2023

The content of heavy metals in soil should be continuously monitored, especially in organic crops. Exceeding the permissible concentrations of these elements may lead not only to inhibition of plant growth but also to ingestion into the organisms of animals that feed on these plants.

Heavy metals usually enter the soil via precipitation or manure. There is a noticeable increase in interest in digestate for fields fertilization. Therefore, the authors decided to test the heavy metal content in substrates (slurry and solid input) and digestate. The 15x3 samples tested showed that only trace amounts of heavy metals were present. The study shows that the content of these elements in the digestate is not the sum of the elements supplied to the digester with the substrates. In most of the samples tested, lead concentrations did not exceed 5 mg‧kg−1. The lowest amounts of cadmium (an average of 0.28 mg‧kg−1) were observed in the slurry, and the highest (an average of 0.34 mg‧kg−1) in the solid substrate fed to the digester. Slurry had the lowest mercury and cadmium contents (average 0.012 mg‧kg−1and 5.8 mg‧kg−1). The highest concentration of chromium was registered in the digestate (average 3 mg‧kg−1) and this was on average 0.3 mg‧kg−1 higher than the feedstock and 0.5 mg‧kg−1 than the slurry
Using Time Series Analysis to Study the Changing Trend of Business English Teaching Effectiveness in Colleges and Universities
Authors: Ye Chunling
Published: December 2023

This paper analyzes the characteristics and changes of influence on college business English teaching in the context of the new era, constructs a multimodal college business English teaching model based on vision and hearing, and carries out a multimodal fusion of graphics, text and audio through deep learning. To solve this problem, the time series analysis problem is easily affected by noise. On the basis of the basic time series algorithm, the GBDT-KF algorithm based on the Kalman filter is designed. It also predicts the effectiveness of college business English teaching. The results show that listening ability is improved by 0.3, speaking ability by 0.25, writing ability by 0.21, and reading ability by 0.18; the effect of college business English teaching has also been improved in different degrees.
The Development Trend of Innovative Teaching of Dance in Colleges and Universities Based on Clustering Algorithm in the Context of Big Data
Authors: Zhang Cong
Published: December 2023

This paper establishes a model for teaching dance innovation in colleges and universities based on big data. Using a clustering algorithm to obtain the characteristics of dance teaching using affiliation assignment calculation to maximize the fuzzy indicators, the dance innovation teaching indicators are divided to improve the assessment accuracy. The optimization of dance teaching assessment indicators is normalized to complete the data processing and clustering in the teaching system and combined with the user preference to divide the student group based on similar characteristics. The results show that 45.00% of the student’s performance ability of physical balance is excellent, and the dance teaching classroom question score is 93. Big data technology can effectively integrate and categorize the existing dance teaching resources in colleges and universities, thus improving the quality of dance teaching.
Economic Policy Uncertainty, Accounting Robustness and Commercial Credit Supply - An Analysis Based on Accounts Receivable
Authors: Ren Xiufeng
Published: December 2023

This paper constructs a commercial credit supply decision-making model based on the analysis of corporate accounts receivable. The regression analysis algorithm is used to categorize and calculate the variable parameters affecting credit supply, and the expectations of suppliers and vendors are used as the predicted value for decision-making. The BP neural network is used to assess the risk of business accounts receivable from the horizontal as well as vertical perspectives, respectively, and to enhance the security quality of credit supply decision-making. The results show that strengthening the management of accounts receivable enhances the robustness of corporate accounting, keeps the rate of change in surplus around 0.4% per year, and the accounts receivable turnover rate reaches a maximum of 15.9 times/year so that the business credit supply decision will be more prudent.
Digital leisure sports help to revitalise the culture of beautiful villages
Authors: Wu Jiafa , Dusaran Mariphe M.
Published: December 2023

In this paper, a platform for digital leisure sports services is built using digital information technology in the context of the new economy. Plain Bayesian classification is used to classify sports information based on its features, and the target value is assigned based on the feature vector. The RBF algorithm is introduced to transform the information into measurable data, and the target weights are updated using the energy function. The results indicate that the villagers exercised for 5 hours each day on the platform, and the BMI pass rate of villagers of different age groups exceeded 70%. The digital innovation of leisure sports has a greater effect on the psychology and physiology of villagers and is a strong fit for the prosperity and revitalization of rural culture.
Intercultural Communication Paths in Chinese International Education Based on Multiple Regression Models
Authors: Lu Jialin
Published: December 2023

In this paper, we first studied the demand for Chinese language communication, explored the mode of Chinese language communication, the process of Chinese language communication and the mode of interaction, and constructed a multivariate and three-dimensional communication path of Chinese language and culture. Then, a multiple linear regression model was established, the generalization error of the model was calculated, and the least squares method was used to find the optimal solution of the model parameters. Finally, the effect of cross-cultural communication in Chinese international education was evaluated, and the level of Chinese cultural awareness, Chinese cultural identity and Chinese cultural communication of the research participants were analyzed. The results show that the overall cultural awareness dimension of the survey respondents scored a total of 186 points, with an average score of 138.65 points, which is a medium level, indicating that Chinese intercultural communication and dissemination are more effective. This study promotes the development of international education and the in-depth development of international communication and cooperation.
Transforming Numerical Efficacy of Civics Curriculum Development in Colleges and Universities by Combining Matrix Modeling
Authors: Long Boyu
Published: December 2023

In this paper, firstly, on the basis of the digital construction of the Civics course, we propose to construct a Civics course teaching system to realize the transformation of digital type effectiveness of the Civics course and design the functional module and database module of Civics course teaching system according to the connection between students, teaching content and teachers. Secondly, on the basis of the matrix model, the subordination degree function of the Civics course is determined according to the subordination relationship of the Civics course features, and then the contribution degree of the variable factors of the Civics course is calculated by using the segmented subordination function, and the contribution degree of each factor is combined to construct the matrix model of the Civics course teaching system. Then, set the set of evaluation factors of the course Civics teaching system, calculate the evaluation factor scores of the Civics teaching system by using the multi-factor synthesis method, and evaluate and analyze the digital construction of Civics courses in colleges and universities. The results show that on the matrix model, the comprehensive score of Chengdu University’s curriculum Civics system construction is calculated to be 88, which also verifies that the teaching system of Civics courses runs well. On the sense of teacher efficacy, the significant probability value of P less than 0.05 for teaching age, title, and education indicates a significant relationship with the sense of teacher efficacy.
Analysis of Linguistic and Cultural Differences in Japanese Translation Based on Differential Equation Modeling in the Perspective of PMC Assessment
Authors: Chen Yicai , Li Xianrui
Published: December 2023

This paper focuses on the differences in grammar rules and syntactic structures between Japanese passive and probable tenses and labels the corresponding sentences in the corpus according to their grammatical features. A statistical method is employed to categorize the corpus by linking dependency trees and morphological information. Differential equation modeling is used to construct a classification model, and the important features and extraction processes for distinguishing sentence structure are defined. In conclusion, the impact of language and cultural differences on the machine translation of Japanese passive sentences is examined. The results show that the significant values of manual translation and machine translation are 0.158 and 0.203, respectively, which are greater than 0.05, indicating that they conform to the normal distribution and there are obvious differences between them. The mean score of the total score of manual translation is 4.62, and the mean score of the total score of machine translation is 2.85, indicating that there is a significant effect of language and cultural differences on machine translation. This paper provides useful guidance and insights for improving the quality of Japanese translation and promoting cross-cultural communication and understanding.
Application of Digital Health Concepts in Dance Culture Dissemination and Promotion Based on Predictive Modelling of Information Dissemination
Authors: Mei Xue
Published: December 2023

The purpose of this paper is to analyze the dissemination effect of digital health concepts in dance culture by constructing a prediction model for dance culture information dissemination. It focuses on analyzing the main paths and forms of Internet+dance culture dissemination and constructing the cultural dissemination process of Internet+dance health. The LSTM method is used to extract the states in information dissemination, and the dissemination characteristics of digital health in dance culture are deduced by analyzing the characteristics of the information dissemination sequence. The association between digital health concepts and dance culture dissemination was determined through the trajectory characteristics of information dissemination. The results show that the spreading range of the four types of models rises in an upward trend and is faster when the spreading time round is in the interval of (0,125). The spread range in models in the (150,300) interval is generally higher than the SI model and SEI model. The factor value of whether the video is top or not affects the amount of playback is 0.771***, and the factor value of whether it carries a topic or not is 0.051.
A Comparison of Chinese-English News Metaphors for Corpus Analysis in the Context of Big Data Technology
Authors: Li Daiju
Published: December 2023

In this paper, firstly, the Chinese-English news corpus is constructed using crawler technology, and a distributed retrieval system is designed to search the Chinese-English data in the corpus. Secondly, the potential semantic analysis algorithm is improved to extract semantic information from the Chinese-English corpus and realize the semantic search data source. Finally, by designing the experimental environment as well as the samples of the Chinese-English news corpus, the performance of the corpus as well as the distribution retrieval performance are analyzed, and the comparison of Chinese-English news metaphors is explored. The results show that the system’s word-level accuracy is 96.32% when the training corpus size reaches 100,000 word-level, the F-value is 96.08, and the latency of 1Mb/s is higher than the latency of 3Mb/s and the latency time of 5M/s, and the corresponding latency is always stabilized within 1.0. The proportion of conceptual metaphors in Chinese news is above 0.5, while in English news, the proportion is mostly around 0.3. Most of the Chinese news is conceptual metaphors, while most English news is interpersonal metaphors.
Dynamic Interactive Design of Graphic Design Elements Based on Image Feature Extraction Algorithm
Authors: Li Shanshan
Published: December 2023

This paper first analyzes the use and expression of line and surface, color, and text as graphic design composition elements. Secondly, it analyzes the relationship between interaction design and other disciplines and constructs a dynamic interactive design model for graphic design. Then, the features of color, texture, shape and spatial relationship of the image are extracted by the feature extraction algorithm, and the gesture recognition algorithm is used to determine the operation requested by the user and execute it. Finally, data analysis was conducted on 32 randomly selected students from the design school of University H who applied the dynamic interactive design model. The results show that the dynamic interactive design has the highest rating in terms of smooth operation, with an average score of 6.893, and the lowest rating is in terms of low learning cost, with an average score of 5.087. This shows that the dynamic interactive design model of graphic elements can improve the smoothness of operation, thus improving the dynamic interactive experience of students and providing direction for the development of the field of graphic design.
Application and Development of Traditional Elements in Rural Revitalization Design under New Media Perspective
Authors: Liu Yan
Published: December 2023

This paper firstly studies the “three-step” strategy of rural revitalization at this stage and proposes to help consumers recommend suitable rural cultural and creative products through the FMIST model based on the dilemma of the development of cultural and creative products in rural revitalization. Then, it explores the role of traditional culture in the cultural and creative products of rural revitalization, as well as in the planning and architectural layout. Finally, the development status of rural cultural and creative products and architectural planning layout, as well as the association between cultural and creative products and architectural planning layout and influencing factors, are analyzed by entropy value method and grey correlation degree, respectively. The correlation between cultural and creative products and rural revitalization is all higher than 0.55, and the correlation between rural revitalization and cultural and creative products on rural revitalization is high. They can be injected with traditional elements and designed as portable cell phone cases and daily-use mugs, leaving behind traditional cultural elements that belong to the unique characteristics of the countryside.
Optimisation and Quality Evaluation of Teaching Models in Primary and Secondary Schools Based on Deep Learning
Authors: Qin Yongxian
Published: December 2023

This paper examines the concept of deep learning and evaluates the quality of teaching models in primary and secondary schools. Based on the comprehensive evaluation application of fuzzy theory, the fuzzy model is established, the evaluation index scheme is selected, and the quality evaluation model of primary and secondary school teaching mode is constructed. The evaluation index system is divided into indexes, and the weights of indexes are calculated, and the first-level indexes are divided into teaching content, teaching management, teaching effect, and teaching attitude. Calculate the fuzzy comprehensive evaluation score of primary and secondary school teaching mode and adjust the primary and secondary school teaching mode based on the score. The final score of a comprehensive evaluation of teaching mode is 4.32, teaching content Q
1 = 4.33, teaching attitude Q
2 = 4.26, teaching management Q
3 = 4.43, and teaching effect Q
4 = 4.05. In the quality evaluation of primary and secondary school teaching mode, teaching management > teaching content > teaching attitude > teaching effect.
Digital Resource Management and Sharing for Teaching and Learning in Higher Education by Integrating Multiple Data Chain Networks
Authors: Yan Xiaojing
Published: December 2023

In this paper, we construct a GCCP multivariate datalink network for teaching and learning resource sharing through the Generalized Control Chaining Primary Protocol (GCCP) combined with mutual cooperative services among the physical, data link and network layers for resource sharing. The solution set is mapped to the distributed dynamic self-organizing network data links through Nash equilibrium. Attribute descriptions for the necessary digital teaching resources are provided in a P2P system for sharing resources in large-scale heterogeneous teaching environments. Finally, simulations are conducted under the Group Service Control Protocol (GCCP) for teaching resource sharing to verify the effectiveness of the scheduling and management model for digital teaching resources. According to the results, the system with a multivariate datalink network maintains an average cluster size of 5 nodes. The response time of the system increases significantly with the increase of scale when RP(k)C-Grid takes k as 10,20,30,40,50 respectively. This paper effectively manages and maintains the entire digital resource management system for teaching and learning in universities, making it more stable and efficient.
Professional Quality Development of English Teachers in Colleges and Universities Based on Network Learning Community
Authors: Geng Yanmei , Liu Lei
Published: December 2023

In this paper, we first construct an online learning community using the social network cascade model, giving the specific structure and specific roles of the model. Secondly, the social network cascade model is constructed by utilizing multi-sequence temporal coding, temporal bi-directional graph convolutional network and GRU encoder with an attention mechanism. Finally, the effectiveness of the model in the development of English teachers’ professional quality in colleges and universities is verified through the comparative validation of the model and the practical application of the network learning community. The results show that English teachers’ professional quality development scores are high, with a mean score of 5.554. The English posttest scores of the experimental class in the comparison experiment increased by 2.12 points compared with the previous test, with two-tailed Sig.=0.024>0.05. This shows that the network learning community can effectively improve the professional quality development of English teachers and further enhance the student’s English learning performance.
Professional identity of grid workers based on SPSS 22.0
Authors: Hou Zhenjiang , Kang Juan
Published: December 2023

The professional identity of grid workers is a significant expression of social service consciousness, and this paper utilizes statistical analysis methods to study its related factors. Under the framework of SPSS 22.0, the non-robust paradigm square of traditional PCA is replaced by a robust measure, and the AWL-RPCA model is constructed by combining the introduced data adaptive learning. Meanwhile, to address the data smoothness problem of quantile regression, the PDQR model was proposed by using the method of constructing panel data to optimize the control of individual heterogeneity. Taking the gridmen in L street of a city as the research object, the related factors of occupational identity were mined based on the AWL-RPCA model, and then the regression equation was obtained by the PDQR model. The degree of influence of the independent variables on the occupational identity of the gridmen from the highest to the lowest is the working status, the level of education, the pressure of helping and teaching, the appraisal satisfaction, the support and coordination satisfaction, and the propaganda satisfaction, and the regression coefficients are 8.36, 3.14, 5.08, 3.60, -4.35, and 3.32, respectively. Under the guidance of the statistical analysis of the SPSS, the construction of the gridmen team can be optimized in a better way.
Exploring the reform of live e-commerce talent training based on the four-way collaboration of “government, industry, enterprise and school”
Authors: Wang Xin
Published: December 2023

This paper takes universities and enterprises as the basic game subjects of collaborative innovation of live e-commerce talent cultivation and defines the involved interest subjects as government, school, enterprise and industry to construct a multi-party evolutionary game model. The model’s evolutionary stable equilibrium point can be calculated using the replicated dynamic equations of multiple parties. MATLAB was used to analyze the numerical simulation to explore the sensitivity of the relevant parameters for the three parties. Finally, according to the game results, a four-point practical path to optimize the live e-commerce talent training program is proposed. The results show that under the satisfaction of the equilibrium point (0, 0, 0), the critical value of the active participation willingness of the four parties is between 0.4 and 0.5, and the final equilibrium point tends to (1, 1, 1). In this paper, the cooperation between schools and enterprises is prompted to change from limited rationality to full rationality in order to realize the Pareto optimal equilibrium of the final game.
The Integration and Development of Ideological and Political Education and Student Management in Universities Based on Data Fusion Models under the Background of Three Comprehensive Education
Authors: Feng Ranjun , Zhang Lingyong
Published: December 2023

Mental health management of college students is a crucial aspect of college student management. To this end, this paper extracts the characteristic sequences of consumption behaviors, including the number of consumption per week, the number of times of use breakfast, the number of times of deviating from the normal time of using breakfast and the number of times fetching water from the daily consumption records of students. Then, the best model MLSTM-FCN is selected from the different existing time series classification models. Aiming at the problem that the FCN branch has a small sensory field and can only run in one direction in the network structure of the MLSTM-FCN two-branch splicing, it is proposed to use a Transformer to replace the FCN branch so as to put forward a Trans-LSTM students’ psychological abnormality early warning model based on the classification of time series. Model. According to the model comparison, the Trans-LSTM fusion model F1 has the highest mean value. The value is 0.8245. Finally, in the psychological intervention based on ideology and politics for students with psychological problems identified by the early warning model, the results show that the individual’s pressure t=8.163, df=6, p<0.001, and the social environment pressure t=9.872, df=6, p<0.001, indicating that the subject’s mental anomalies can be classified based on the time series. 0.001, indicating a significant difference between before and after the intervention for the subjects.
Exploring the construction of business management model in the context of big data
Authors: Ran Junwei
Published: December 2023

Big data has made it necessary for business administration to be more intelligent and informationized. This paper introduces data mining technology, explains the specific steps of data mining, and analyzes commonly used data mining algorithms. The rule mining of the C4.5 algorithm is illustrated by using information entropy, the XGBoost model is used as the base learner of Stacking integrated learning and model fusion is carried out. The regional economic prediction model was constructed using the C4.5 rule mining algorithm, while the enterprise credit rating classification model was established using the Stacking algorithm. The empirical evidence shows that the regional economy will be affected by the main body of the enterprise, the industrial structure and the development of the enterprise, in which the industrial structure and the development of the enterprise showed exponential growth in 2007-2018, and their growth rates are all around 30%. Using the Stacking algorithm for enterprise credit rating classification, the recall rate of the weighted fusion model with GRU network as a meta-learner has improved by 2.4%. By analyzing the application of big data technology in business administration data, we illustrate its role in business administration decision-making so as to provide a certain reference for the construction of the business administration informatization model.
Research on the development of AloT sensing module for new energy power information collection
Authors: Jing Zhen , Li Congcong , Zhu Hongxia , Wang Pingxin , Chen Zhiru
Published: December 2023

In order to improve the ability of power communication technology to support large-scale and massive services of smart electricity consumption, this paper designs a sensing model to collect information on new energy electricity consumption. Using the arrival rate calculation method of intelligent IoT, the information on new energy electricity users is collected, and the environmental measurement data is collected with the help of intelligent sensors. Monitoring the concurrency factor of all sensors in the operation state, collecting queuing theory packet loss rate through utilization maximization objective function, and setting the average queuing length of communication nodes. On this basis, the voltage amplitude of the electrical energy sampling point is measured, and the Gaussian perceptual loss vector with non-zero mean and heteroskedasticity is performed to iteratively converge the constraint matrix and error covariance. The results show that the maximum relative errors for service delay and packet loss rate are 16.8% and 7.0%, respectively. As bandwidth increases, the queuing delay and packet loss rate decrease. The broadband power line carrier can reach up to 210 Mbps, and the micropower wireless rate can reach 38.5 kbps. The annual cycle characteristics fluctuate widely, but the cumulative error of electricity load prediction results is lower, and the prediction accuracy is high. It shows that the electricity consumption information collection sensing model provides an important reference for building a new communication network with low cost, high speed and reliability for smart electricity consumption.
Distributed Power High Dynamic Group Control Technology and Grid Connection Demonstration
Authors: Wang Qing , Li Guimin , Chen Zhiru , Jing Zhen , Zhang Zhi
Published: December 2023

Currently, high penetration distributed power generation group control technology makes it difficult to effectively regulate complex power grids. Therefore, on the ground of the division of distributed photovoltaic power generation clusters, this study proposes a dual-layer control model for distribution networks that integrates the cuckoo particle swarm algorithm and verifies its effectiveness. The experiment showcases that the standard deviations of the research algorithm on the four benchmark functions under the 50 dimension are 2.95e-02, 6.73e+02, 6.48e-04, and 6.45e-06, respectively, most of which are lower than the comparison algorithm. On the basis of connecting to the photovoltaic system, the voltage amplitude fluctuation of the double-layer control model designed through research using control algorithms is relatively small, basically maintaining around 1.05. In addition, after implementing control in practical applications, the actual line loss of the distribution network decreased from the maximum of 15.3% to 8.9%, meeting the line loss requirements of the actual distribution network, indicating the effectiveness of the double-layer control model.

Meanwhile, after applying the double-layer control model, the voltage fluctuation of node 42 significantly decreased, and the numerical value remained at 1.05 p.u., achieving a good voltage condition effect. The voltage fluctuation of grid connection in distributed power generation has been significantly improved when applied to the actual grid connection. Overall, the proposed dual-layer control model for the distribution network is effective and practical, which can effectively promote the construction of practical grid connection demonstration projects.
The Effect of External and Internal Factors on Management Effectiveness Within Indian Construction Companies
Authors: Sanchaniya Rashmi Jaymin , Kundziņa Antra , Thomas Cijo George , Geipele Ineta , Naimavičienė Jurga
Published: December 2023

The aim of this study is to define and clarify the idea of improving management effectiveness within Indian construction companies. We conducted an online survey with an Indian construction company and used correlation analysis to thoroughly examine how both external and internal factors affect management effectiveness. The survey includes demographic questions, ratings on a scale of 1 to 5 for management aspects, ratings on a similar scale for internal and external factors, and ratings on a similar scale for potential improvement suggestions. With the help of descriptive statistics and frequencies, the mean efficiency values were calculated using SPSS and Excel to analyse the collected data. To establish links between the variables and the effectiveness of the company, correlation analysis was also carried out. The primary conclusions of the study highlight the critical importance of focussing on employee relations, meticulous tracking of work output, integration of technology, and adherence to established protocols as key factors in improving management effectiveness. The research also reveals significant problems with the management system, such as a preference for sanctions over incentives. It establishes that internal and external factors have equal weight in influencing management effectiveness, emphasising the need for an all-encompassing strategy that is flexible enough to support long-term advancement in construction company management practices.
Optimization Models and Strategy Approaches Dealing with Economic Crises, Natural Disasters, and Pandemics – An Overview
Authors: Guliashki Vassil , Kirilov Leoneed , Nuzi Alsa
Published: December 2023

The occurrence of large-scale crises is a great challenge for people. In such cases, many levels of public life are affected and recovery takes time and considerable resources. Therefore, approaches and tools for predicting and preventing crises, as well as models and methods for crisis management and crisis overcoming, are necessary. In this review, we present approaches, models, and methods that support decision-making in relation to the prevention and resolution of large-scale crises. We divide crises into three types: natural disasters, pandemics, and economic crises. For each type of crisis situation, the types of applied tasks that are solved and the corresponding models and methods that are used to support decision-makers in overcoming the crises are discussed. Conclusions are drawn on the state of the art in this area and some directions for future work are outlined.
Hybridized Cryptographic Encryption and Decryption Using Advanced Encryption Standard and Data Encryption Standard
Authors: Kanshi Avaneesh , Soundrapandiyan Rajkumar , Anita Sofia V. S. , Rajasekar V. R.
Published: December 2023

This research proposes an efficient hybridized approach for symmetrical encryption of image files in bitmap formats. Due to the heavy use of lightweight encryption in fields such as military and corporate workplaces, intruders try to intercept communication through illegal means and gain access to classified information. This can result in heavy losses if the leaked image data is misused. The proposed enhances the security and efficiency of one of the most used standard symmetric algorithms, Advanced Encryption Standard (AES). In the proposed method, the AES architecture has been modified using a less intensive algorithm, Data Encryption Standard (DES). DES carries a sub-process of permuting data columns rather than the AES’s mixing feature. The proposed algorithm is analyzed using a set of 16 bitmap images of varying memory sizes and resolutions. The effectiveness of the algorithm is evaluated solely in terms of perceptual invisibility as per the main objective of the research.
Robust Email Spam Filtering Using a Hybrid of Grey Wolf Optimiser and Naive Bayes Classifier
Authors: Zraqou Jamal , Al-Helali Adnan H. , Maqableh Waleed , Fakhouri Hussam , Alkhadour Wesam
Published: December 2023

Effective spam filtering plays a crucial role in enhancing user experience by sparing them from unwanted messages. This imperative underscores the importance of safeguarding email systems, prompting scholars across diverse fields to delve deeper into this subject. The primary objective of this research is to mitigate the disruptive effects of spam on email usage by introducing improved security measures compared to existing methods. This goal can be accomplished through the development of a novel spam filtering technique designed to prevent spam from infiltrating users’ inboxes. Consequently, a hybrid filtering approach that combines an information gain philter and a Wrapper Grey Wolf Optimizer feature selection algorithm with a Naive Bayes Classifier, is proposed, denoted as GWO-NBC. This research is rigorously tested using the WEKA software and the SPAMBASE dataset. Thorough performance evaluations demonstrated that the proposed approach surpasses existing solutions in terms of both security and accuracy.
A Novel Self-Exploration Scheme for Learning Optimal Policies against Dynamic Jamming Attacks in Cognitive Radio Networks
Authors: Sudha Y. , Sarasvathi V.
Published: December 2023

Cognitive Radio Networks (CRNs) present a compelling possibility to enable secondary users to take advantage of unused frequency bands in constrained spectrum resources. However, the network is vulnerable to a wide range of jamming attacks, which adversely affect its performance. Several countermeasures proposed in the literature require prior knowledge of the communication network and jamming strategy that are computationally intensive. These solutions may not be suitable for many real-world critical applications of the Internet of Things (IoT). Therefore, a novel self-exploration approach based on deep reinforcement learning is proposed to learn an optimal policy against dynamic attacks in CRN-based IoT applications. This method reduces computational complexity, without prior knowledge of the communication network or jamming strategy. A simulation of the proposed scheme eliminates interference effectively, consumes less power, and has a better Signal-to-Noise Ratio (SNR) than other algorithms. A platform-agnostic and efficient anti-jamming solution is provided to improve CRN’s performance when jamming occurs.
Exploring the Performance and Characteristics of Single Linkage and Complete Linkage Hierarchical Clustering Methods for IoT Sensor Networks
Authors: Bajaber Fuad
Published: December 2023

The research explores applying hierarchical clustering methods, namely single linkage and complete linkage, in IoT Sensor Networks (ISNs). ISNs are distributed systems comprising numerous sensor nodes that collect data from the environment and communicate with each other to transmit the data to a base station. Hierarchical clustering is a technique that groups nodes into clusters based on proximity and similarity. This paper implements and compares the performance of single linkage and complete linkage methods in terms of cluster size, network lifetime, and cluster quality. The study’s findings provide guidance for ISN researchers and designers in selecting the appropriate clustering method that meets their specific requirements.