bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation and Analysis of Regional Economic Growth Factors in Digital Economy Based on the Deep Neural Network
Authors: Cheng Caijun , Huang Huazhen
Published: August 2022

With the rise of deep learning technology, due to the superior performance of the deep neural network, its application in the digital economy has attracted extensive attention of scholars. Since the beginning of the 21st century, my country’s digital economy has developed rapidly, and its universalization and other characteristics have created favorable conditions for the optimal allocation of resources in underdeveloped regions and the exertion of comparative advantages. The digital economy will play a key role in poverty alleviation, promoting coordinated regional development, narrowing regional gaps, and improving the spatial layout of my country’s reform and opening up. This paper studies the factors that the digital economy based on deep neural networks has on regional economic growth. Simulation experiment conclusions are as follows: (1) the digital economy of Guizhou, Beijing, Chongqing, Anhui, and Tibet is growing rapidly. The central and western regions are in a period of rapid growth. For the gap between major industrial provinces, the coefficient of variation reached about 1 before 2013, then it declined rapidly, and slowed down, and steadily declined after 2019, indicating that the gap in the digital economy in various regions is narrowing in general. (2) From the national level, the digital economy index coefficient is 1.24, that is, for every 1% increase in digital economy investment, GDP will increase by about 0.24%. The labor force increased by 1% and the GDP increased by about 0.22%. This promotion effect is also very obvious. (3) Judging from the above data, the western region urgently needs to promote the construction of the digital economy and introduce high-tech digital economy talents. The talent effect in the Midwest has a significant effect on GDP. (4) From the perspective of the whole country and other regions, the parameter coefficients and signs have not changed significantly, so the original model is robust, and so the conclusion is desirable.
Evaluation Method of the Metacognitive Ability of Chinese Reading Teaching for Junior Middle School Students Based on Dijkstra Algorithm and IoT Applications
Authors: Wen Diyi
Published: August 2022

In view of the poor quality of Chinese Reading Teaching in junior middle school, this paper puts forward the metacognitive ability evaluation method of Chinese Reading Teaching for junior middle school students based on Dijkstra algorithm, constructs the Chinese Reading Teaching management system for junior middle school students, optimizes the Chinese reading evaluation indexes for junior middle school students, and optimizes the metacognitive ability evaluation algorithm of Chinese Reading Teaching for junior middle school students combined with Dijkstra algorithm, Finally, the experiment proves that the metacognitive ability evaluation method of Chinese Reading Teaching for junior middle school students based on Dijkstra algorithm has high practicability in the process of practical application, can better ensure the teaching quality, and can fully meet the research requirements.
Identification of Encrypted Traffic Using Advanced Mathematical Modeling and Computational Intelligence
Authors: Liu Xinlei
Published: August 2022

This paper proposed a hybrid approach for the identification of encrypted traffic based on advanced mathematical modeling and computational intelligence. Network traffic identification is the premise and foundation of improving network management, service quality, and application security. It is also the focus of network behavior analysis, network planning and construction, network anomaly detection, and network traffic model research. With the increase in user and service requirements, many applications use encryption algorithms to encrypt traffic during data transmission. As a result, traditional traffic classification methods classify encrypted traffic on the network, which brings great difficulties and challenges to network monitoring and data mining. In our article, a nonlinear modified DBN method is proposed and applied to encrypted traffic identification. Firstly, based on Deep Belief Networks (DBN), this paper introduces the proposed Eodified Elliott (ME)-DBN model, analyzes the function image, and presents the ME-DBN learning algorithm. Secondly, this article designs an encrypted traffic recognition model based on the ME-DBN model. Feature extraction is carried out by training the ME-DBN model, and finally, classification and recognition are carried out by the classifier. The experimental results on the ISCX VPN-non-VPN database show that the MEDBN method proposed in this article can enhance the classification and recognition rate and has better robustness to encrypt traffic recognition from different software.
A Blockchain Consensus Protocol Based on Quantum Attack Algorithm
Authors: Wang Hui , Yu Jian
Published: August 2022

The blockchain is a distributed storage system of digital assets. This decentralized, non-copyable technology stems from universal standard password algorithm and the consensus mechanism of the game theory. The development of quantum computing poses threat to traditional algorithms of blockchain encryption, including symmetric encryption and hash encryption. Focusing on the traditional blockchain consensus mechanism, this paper designs a new blockchain consensus mechanism, based on the stochasticity, irreversibility, and uncertainty of quantum measurement. In the proposed consensus mechanism, complex calculations and intractability mathematical problems are abandoned. In this way, a huge amount of computing resources is saved, less energy is consumed, the time delay is shortened, and the throughput is increased. The proposed quantum consensus mechanism can withstand 51% attacks.
Transformation Path of Modern Media from the Perspective of Internet of Things
Authors: Zhang Yujie , Yasin Megat Al Imran , Alsagoff Syed Agil Bin Shekh , Hoon Ang Lay
Published: August 2022

The Internet of Things (IoT) is a new technology revolution that aims to link all ordinary physical items to the Internet, creating a massive worldwide network of uniquely connected things that can exchange information and fulfill planned activities, resulting in considerable advantages for consumers. Researchers have started to explore new techniques of technical help in various fields (e.g. health, transport, and education) as the Internet of Things has grown in popularity in recent years. In this research, we present a revolutionary IoT paradigm with an encryption mechanism to establish a kind of network that would allow the more intelligent media-data transfer. Initially, we collected COVID-19-related data and preprocessed the raw data using the median absolute deviation method. The preprocessed data that is to be transferred to the media is then stored in the IoT device using various sensors. To improve the security of the data, we propose Robust Modern Media Data Encryption (RMMDE) algorithm with Enhance Cuckoo Swarm Optimization (ECSO) algorithm. The suggested mechanism is compared to the traditional encryption approaches, and the metrics are evaluated using the OriginPro tool. This proposed methodology could be a start point for better and more efficient media data transmission.
Data Mining-Based Tracking Method for Multisource Target Data of Heterogeneous Networks
Authors: Li Chaofeng
Published: August 2022

In order to solve the problem that the target is easily lost in the process of multisource target data fusion tracking, a multisource target data fusion tracking method based on data mining is proposed. Multisource target data fusion tracking belongs to location level fusion. Firstly, a hybrid heterogeneous network fusion model is established, and then, data features are extracted, and a fusion source big data acquisition algorithm is designed based on compressed sensing to complete data preprocessing to reduce the amount of data acquisition. Based on data mining association multisource fusion target, get the relationship between each measurement and target, and build multisource target data fusion tracking model to ensure the stable state of fusion results. It shows that the proposed method can save the tracking time and improve the tracking accuracy compared with the methods based on NNDA and PDA, which is more conducive to the real-time tracking of multisource targets.
Application of Smart Wearable Fitness Equipment and Smart Health Management Based on the Improved Algorithm
Authors: Cao Haibo
Published: August 2022

IoT technology has scientific, advanced, and practical characteristics in wearable fitness equipment and artificial intelligence health management. On this basis, this paper discusses the intelligent health management system based on IoT technology. By building an IoT health management system, the design principles and algorithm design of wearable fitness equipment are introduced around the device, and various noises that affect the accuracy of the equipment and how to better filter out various noises are also analyzed. The authors selected cloud service platforms and also investigated and analyzed the application prospects of wearable fitness equipment in the community. From the perspective of real-time monitoring, scientific management, and intelligent decision-making, we ensure high-quality, standardized, scientific, efficient, and accurate wearable fitness equipment applications and intelligent health management. In addition to simply viewing IoT technology as an information dissemination platform, IoT technology can also expand many other functions. According to the survey results of this article, 90% of people will use the APP with the function of sports and fitness in social media. One of the most concerned issues in the current society is the application of social media in national fitness activities.
The Application of VR/AR Technology in Graphic Design Based on zSpace
Authors: Liu Lulu , Nhung Minh Tien
Published: August 2022

The arrival of the information age has promoted the rapid development of information technology, and the birth of VR and AR technology has brought many changes to the emerging technology fields. R&D and progress of VR and AR technology highlight outstanding achievements in the information age. In the future, VR and AR technologies will bring huge economic benefits to related industries, and at the same time, they will lead the future of related industries. Virtual reality technology has evolved for decades since its birth. As a new technology, VR has greatly changed people’s daily life. No matter in the field of graphic design or interior design, it can be used as a special technical means to effectively penetrate between abstract thinking and entity, thus promoting the change of people’s design thinking. Therefore, VR technology has been paid more and more attention in recent years, so it is widely used. With the strengthening of China’s national strength, VR/AR technology based on zSpace has been more and more applied to the field of graphic design. Therefore, this paper takes VR/AR technology based on zSpace as the research object, analyzes the application of VR/AR technology in graphic design in detail, sorts out the advantages and existing problems of VR/AR technology in graphic design field, and discusses the role of emerging technologies in graphic design field, hoping to provide reference and help for the improvement of virtual reality technology in graphic design field.
[Retracted] Lung Cancer Classification and Prediction Using Machine Learning and Image Processing
Authors: Nageswaran Sharmila , Arunkumar G. , Bisht Anil Kumar , Mewada Shivlal , Kumar J. N. V. R. Swarup , Jawarneh Malik , Asenso Evans
Published: August 2022

Lung cancer is a potentially lethal illness. Cancer detection continues to be a challenge for medical professionals. The true cause of cancer and its complete treatment have still not been discovered. Cancer that is caught early enough can be treated. Image processing methods such as noise reduction, feature extraction, identification of damaged regions, and maybe a comparison with data on the medical history of lung cancer are used to locate portions of the lung that have been impacted by cancer. This research shows an accurate classification and prediction of lung cancer using technology that is enabled by machine learning and image processing. To begin, photos need to be gathered. In the experimental investigation, 83 CT scans from 70 distinct patients were utilized as the dataset. The geometric mean filter is used during picture preprocessing. As a consequence, image quality is enhanced. The K‐means technique is then used to segment the images. The part of the image may be found using this segmentation. Then, classification methods using machine learning are used. For the classification, ANN, KNN, and RF are some of the machine learning techniques that were used. It is found that the ANN model is producing more accurate results for predicting lung cancer.
A New Probability Heavy‐Tail Model for Stochastic Modeling under Engineering Data
Authors: El-Morshedy M. , Eliwa M. S. , Al-Bossly Afrah , Yousof Haitham M.
Published: August 2022

The main aim of the paper is to propose and study a new heavy‐tail model for stochastic modeling under engineering data. After studying and analyzing its mathematical properties, different classical estimation methods such as the ordinary least square, Cramér‐von Mises, weighted least square, maximum likelihood, and Anderson–Darling estimation along with its corresponding left‐tail and right‐tail estimation methods are considered. Comprehensive numerical simulation studies are performed for comparing estimation methods in terms of some criterions. Three engineering and medical real‐life data sets are considered for measuring the applicability flexibility of the new model and to compare the competitive models under uncensored scheme. Two engineering real‐life data of them are also used to compare the classical methods. A modified Nikulin‐Bagdonavicius goodness‐of‐fit is presented and applied accordingly for validation under censorship case. Finally, right censored lymphoma data set is analyzed under the modified statistic test for checking the validation of the reciprocal Weibull model in modeling the right censored data.
A Joint Model of Natural Language Understanding for Human-Computer Conversation in IoT
Authors: Sun Rui , Rao Lu , Zhou Xingfa
Published: August 2022

Natural language understanding (NLU) technologies for human-computer conversation is becoming a hot topic in the Internet of Things (IoT). Intent detection and slot filling are two fundamental NLU subtasks. Current approaches to these two subtasks include joint training methods and pipeline methods. Whether treating intent detection and slot filling as two separate tasks or training the two tasks as a joint model utilizing neural networks, most methods fail to build a complete correlation between the intent and slots. Some studies indicate that the intent and slots have a strong relationship because slots often highly depend on intent and also give clues to intent. Thus, recent joint models connect the two subtasks by sharing an intermediate network representation, but we argue that precise label information from one task is more helpful in improving the performance of another task. It is difficult to achieve complete information interaction between intent and slots because the extracted features in existing methods do not contain sufficient label information. Therefore, a novel bidirectional information transfer model is proposed in order to create a sufficient interaction between intent detection and slot filling with type-aware information enhancement. Such a framework collects more explicit label information from the network’s top layer and learns discriminative features from labels. According to the experimental results, our model greatly outperforms previous models and achieves the state-of-the-art performance on the two datasets: ATIS and SNIPS.
Prediction of the Height of Water Flowing Fractured Zone Based on the MPSO-BP Neural Network Model
Authors: Xu Xing , Wang Xingzhi , Li Yuanzhi
Published: August 2022

The height of the water flowing fractured zone (HWFFZ) is the key parameter for safe coal mining under water bodies. In order to improve the accuracy of prediction model of the HWFFZ, the grey relational analysis (GRA) is used to quantitatively analyze the influencing factors of the HWFFZ, the main influencing factors of the HWFFZ under the condition of comprehensive mechanized mining and comprehensive top coal caving mining are selected scientifically, and these five factors that include mining depth, mining thickness, inclined length of working face, hard rock lithology proportion coefficient, and coal seam dip angle are selected as the discriminant indexes for predicting the HWFFZ. Nonlinear inertia weight adjustment, linear adjustments of local acceleration factor and global acceleration factor, and Gaussian mutation operation are introduced into particle swarm optimization (PSO) algorithm to improve the performance of PSO algorithm. The modified particle swarm optimization (MPSO) algorithm is used to optimize the initial weights and thresholds of back propagation (BP) neural network, and the prediction model of the HWFFZ based on MPSO-BP neural network algorithm is established according to the measured data. The prediction results are compared with those of PSO-BP neural network model and empirical formulas, the results show that the prediction accuracy of MPSO-BP neural network prediction model is higher than that of PSO-BP neural network prediction model and empirical formulas, and its prediction mean relative error (MRE) is smallest. The model also has good application effect and certain guiding significance for actual production.
Production Scheduling Optimization of Garment Intelligent Manufacturing System Based on Big Data
Authors: Sun Ning , Cao Botao
Published: August 2022

In order to improve the efficiency of cloth laying and cutting integrated production process, this article proposes a method of optimal scheduling of cloth laying and cutting garment production system process based on big data and genetic algorithm. The chromosomes in the algorithm are expressed by real strings. The method of bit string crossover and mutation is used to solve the premature problem of the algorithm. The experimental results show that the actual cutting time of the plan is 736 min, and the total idle time is 113 min. The idle time occurs in processes 25, 28, 34, 35, and 31, respectively. The cutting time of the plan arranged by the genetic algorithm is 627 min, and there is no idle time. Conclusion. This method can effectively solve the optimal scheduling problem of the cloth laying and cutting production process.
Research on the Civic Policy Model and Reform Innovation of Intelligent Sensor Technology Course
Authors: He Zheng Wan
Published: August 2022

Intelligent sensor technology is a professional course of communication, electronics, information, computer, and other related majors and is a course of expansion and extension of computer network (Ministry of Education of the People’s Republic of China, 2001). It is connected with the Internet by using information sensing device to realize the intercommunication of time and space, people, machines, and things. Intelligent sensor technology is an advanced subject; it contains a lot of ideological elements; in teaching, it should be according to the characteristics of the subject, set the goal of ideological education, to design the content of the ideological education, improve the ideological education, to carry on the course of the construction of the ideological practice and exploration, and guide students to set up the correct world outlook, the outlook on life, and values (The State Council of the Central Committee of the Communist Party of China, 2010). Integrating the elements of thinking and politics into the teaching of intelligent sensor technology and organically combining thinking and politics teaching with professional teaching is conducive to realizing the nurturing function of professional teaching and establishing an all-round curriculum system, so that professional and thinking and politics courses can go hand in hand and produce synergy. With the concept of “civic education as the soul, general education as the root, professional education as the foundation,” the strategy of integrating civic education from “point to surface (Wei, 2015), from history to the present, from inside to outside” is summarized, and a system of assessment, evaluation, and continuous improvement is established. It also establishes a system of assessment, evaluation, and continuous improvement. The strategy has proved to be effective in combining ideological and political education with moral education, enabling students to develop theoretical, institutional, and cultural confidence on the road to socialism with Chinese characteristics (Ministry of Education of the People’s Republic of China, 2004).
The Effects of Probiotics Supplementation on Clinical Status and Biomarkers of Oxidative Damage and Inflammation in Children with Brucellosis: A Randomized, Double-Blind, and Placebo-Controlled Trial
Authors: Zamani Noushin , Ganjy Zeinab , Sharif Mohammad Reza , Taghavi Ardakani Abbas , Kheirkhah Davood , Sayyah Mansour , Azimi Ali , Sharif Alireza
Published: August 2022

Background. Increased levels of inflammatory cytokines and oxidative damage may play crucial roles in the pathogenesis of brucellosis. The purpose of this trial was to evaluate the impact of probiotics administration on clinical status and biomarkers of oxidative damage and inflammation in pediatric patients diagnosed with brucellosis. Methods. This randomized, double-blind, and placebo-controlled trial was performed by recruiting 40 patients, 8–15 years of age, who had been diagnosed with brucellosis. Study participants were randomly allocated into two groups to receive either probiotics supplement or placebo (n = 20 each group) for 8 weeks. Blood samples were collected at the onset and after 8 weeks of intervention to quantify biochemical parameters. Clinical status was examined by a pediatric infectious disease specialist. Results. Following 8-week intervention, probiotics supplementation substantially improved total antioxidant capacity (

P
<
0.001

) and malondialdehyde (

P
=
0.002

). Furthermore, the difference between probiotics group and placebo group for the duration of fever (

P
=
0.02

) and musculoskeletal pain (

P
=
0.001

) was statistically significant, though probiotics administration had no significant effects on high-sensitivity C-reactive protein, total glutathione, and other clinical outcomes compared with placebo. Conclusion. Overall, probiotics intake had beneficial impact on clinical status and body antioxidative defense system in pediatric patients with brucellosis.
[Retracted] Regional Differences and Convergence of Urban‐Rural Integration Development from the Perspective of Factor Flow
Authors: Qian Li , Zhang Ke , Song Jun-Xiu , Tang Wei-Yi
Published: August 2022

Based on the panel data of thirty‐one provinces in China from 2003 to 2020, we constructed an evaluation index system of urban‐rural integration development level from the perspective of factor flow. The combined weighting model of GI and CRITIC were used to evaluate the regional urban‐rural integration development. The coefficient of variation and panel fixed effect model was used to explore convergence, absolute convergence, and conditional convergence. The impact of capital, labor, and technology factor flow on the convergence of urban‐rural integration development level was further investigated. In addition, the difference analysis in time scale and impulse response function analysis was performed to explore the regular pattern of factor flow on the convergence of urban‐rural integration development. The main conclusions were as follows: first, the growth of urban‐rural integration development had an absolute convergence trend and tended to conditional convergence faster. Second, the capital flow positively affected the convergence of urban‐rural integration development, while labor and technology flow had a slowing effect on the convergence of urban‐rural integration development at this stage. Third, the impact of factor flow on the convergence of urban‐rural integration development was dissimilar during different phases. The convergence rate of urban‐rural integration development after 2012 was drastically slower than before.
Design and Implementation of an Interactive English Translation System Based on the Information-Assisted Processing Function of the Internet of Things
Authors: Mo Liya
Published: August 2022

As a new type of language expression, interactive translation is widely used in English, and based on the Internet of Things technology, text harmony and glyphs are combined for information exchange. This design adopts B/S mode to realize the relational query of document content. This paper adopts the B/S architecture mode to design, implement, and test its functional modules and related data analysis to provide a friendly interactive English translation system service to the user group. In this paper, the development of the Internet of Things information-assisted translation system mainly focuses on the semantic embedding and correlation analysis based on the Internet of Things as well as the realization of interactive functions. On this basis, an interactive English translation process based on corpus and text data sets is designed and completed. This method can not only effectively solve the problems of large amount of text and high difficulty of expression but also can make the translation more concise and clear to achieve the required expression effect of the original text. At the same time, the system can automatically perform statistical analysis on the translation results to verify the accuracy and completeness of the translation results, providing reference value for subsequent function implementation. In this paper, we mainly study the realization of interactive functions and propose solutions to its existing problems and deficiencies. The experimental results show that the average BLEU of the system in this paper is 0.985, which indicates that the translation quality of the system is good and the interaction with users is improved.
An Intervention Pattern of Family Parent‐Child Physical Activity Based on a Smartphone App for Preschool Children during COVID‐19
Authors: Han Xiaowei , Tian Zhulin , Zhao Meiling , Zhou Zhixiong
Published: August 2022

Objective. Children’s lifestyles, behaviors, and educational activities were affected by COVID‐19. The preschool children struggled with the challenge of learning at home and avoiding a rapid decrease in physical activity (PA). This study tested the effectiveness of a family‐based intervention that integrated the family and preschool based on a smartphone app to improve the moderate‐to‐vigorous PA (MVPA) and physical fitness of preschool children during COVID‐19. Methods. This 8‐week study was conducted using a quasiexperimental pre‐ and posttest design with a comparison group. A total of 66 pairs of preschool children (30 boys) and their parents and 44 preschool children (24 boys) and their parents composed the experimental group (EG) and the control group (CG), respectively. PA was measured using a GENEActiv waveform triaxial accelerometer. Children’s physical fitness was assessed using a battery test from the Chinese National Measurement Standards on People’s Physical Fitness for preschool children. Results. Preschool children and their parents in the EG participated in less sedentary (p < 0.01) and more light PA (p < 0.01) and MVPA (p < 0.01) compared with those in the CG at the late PA assessment. The EG significantly improved the mean performance of tennis ball throw (p < 0.05), balance beam walk (p < 0.01), and continuous jumping on both feet (p < 0.01) compared to the CG. Conclusions. The family parent‐child PA intervention based on a smartphone app can effectively increase the MVPA of preschool children and their parents, reduce sedentary time, and improve preschool children’s physical fitness. Overall, the family parent‐child PA intervention model based on a smartphone app for preschool children designed in this study is feasible and effective.
Providing a Multiproduct and Multiperiodic Model for Closed‐Loop Green Supply Chain under Conditions of Uncertainty Based on a Fuzzy Approach for Solving Problem of Business Market
Authors: Lagzaie Leila , Hamzehee Ali
Published: August 2022

Many organizations must adjust their supply chains and business environments to remain competitive and retain market share. However, despite the benefits of such developments for organizations, they can lead to supply chain disruptions in many cases. An essential aspect of modern organizations is closed‐loop supply chain management, which reduces risk by coordinating processes. This paper presents a mathematical model of a closed‐loop green supply chain under uncertain conditions. A detailed description of the model and current assumptions for a specific industry are provided. Consequently, the model is developed with several relevant objectives for the design of the network. Our proposed model has the following characteristics: being multiobjective, multiproduct, and multiperiodic. Our analysis indicates that the applied model can be used both to increase profitability and to reduce environmental damage. The problem was made more uncertain using fuzzy logic. Torabi and Hassini (TH) method is combined with Jiménez’s proposed method to solve the problem.
Form Specification of Smart Contract for Intellectual Property Transaction Based on Blockchain
Authors: Duan Zhihao , Feng Wenlong , Zhong Wang , Huang Mengxing , Feng Siling
Published: August 2022

In view of the current chaotic structure of smart contracts and no unified definition of smart contracts, the implementation of smart contracts for the same business in the same field is quite different due to different development institutions and operating platforms, resulting in a low level of smart contract sharing and high development costs, hindering the development of smart contracts. Combined with the intellectual property transaction scenario, this paper proposes a blockchain-based intellectual property transaction smart contract form specification, designs the overall structure and process specification of the smart contract in the intellectual property transaction process, formulates a standard for the standardization of smart contract writing in intellectual property transaction scenarios, and solves the current chaotic structure of intellectual property transaction smart contracts, which is conducive to the collaborative development of scholars in various fields.
Study on the Risk Model of the Intelligent Ship Navigation
Authors: Luo Jianan , Geng Xiongfei , Li Yabin , Yu Qiaochan
Published: August 2022

The perception of risks is a prerequisite for establishing an intelligent ship navigation system based on ship-shore cooperation. According to the research conclusions on the ship-shore collaboration, the technical characteristics of the intelligent ship navigation system, and the analysis of the test results of the ship “ZHI FEI” featured with intelligent navigation, we study and construct the conceptual model and mathematical expression model for risk evolution of the intelligent ship navigation. We further explore the unmanned trend, the general law, and the characteristics of risk evolution based on navigation scenarios and chain effects. The present study provides insight into the risk perception, management, and government governance of intelligent ship navigation and the construction of an intelligent ship navigation system based on ship-shore collaboration.
Compilation of 10 Years of MIRU-VNTR Data: Canadian National Tuberculosis Laboratory’s Experience
Authors: Sharma Meenu K. , Janella Debra , McGurran Alisa , Corbett Cindi , Adam Heather , Akochy Pierre-Marie , Haldane David , MacKenzie Hope , Minion Jessica , Needle Robert , Newberry Caroline , Patterson Michael , Sekirov Inna , Tyrrell Gregory , Soualhine Hafid
Published: August 2022

Tuberculosis is a significant cause of morbidity worldwide and is a priority at the provincial and federal levels in Canada. It is known that tuberculosis transmission networks are complex and span many years as well as different jurisdictions and countries. MIRU-VNTR is a universal tuberculosis genotyping method that utilizes a 24-loci pattern and it has shown promise in identifying inter and intrajurisdictional clusters within Canada. MIRU-VNTR data collected over 10 years from the National Reference Centre for Mycobacteriology (NRCM) were analyzed in this study. Some clusters were unique to a single province/territory, while others spanned multiple provinces and/or territories in Canada. The use of a universal laboratory test can enhance contact tracing, provide geographical information on circulating genotypes, and hence, aid in tuberculosis investigation by public health. The housing of all data on one platform, technical ease of the method, easy exchange of data between jurisdictions, and strong collaboration with laboratories and surveillance units at the provincial and federal levels have the potential to identify possible outbreaks in real time.
Effect of Cross Theoretical Model of Behaviour Change and Motivation Interview on Self-Management Behaviour
Authors: Wang Hongxia , Li Dongmei , Xiong Ye , Huang Huijun , Hu Qiongshuang , Zhang Weimei
Published: August 2022

Objective. To evaluate the effects of a trans-theoretical model (TTM) of behavioural change plus motivational interviewing on self-management behavior and quality of life (QoL) in patients with intracranial aneurysm. Methods. A total of 94 patients with intracranial aneurysm treated in the First Affiliated Hospital of Wenzhou Medical University from 2019 to 04/2021-04 were retrospectively analyzed. Among them, 49 patients used TTM + motivational interview as the observation group (Obs group), and 45 patients used the traditional method as the control group (Con group). The Self-Management Behavior Scale for Patients with Intracranial Aneurysm was used for analyzing the changes in the self-management behavior of the two groups of patients, and the MOS 36-item Short Form Health Survey (SF-36) was used to analyze the changes in the QoL of the patients. The incidence of adverse events after 6 months of intervention was counted. In addition, the Barthel Index (BI) and Montreal Cognitive Assessment Scale (MOCA) were used to evaluate the recovery effects of patients. Logistic regression was conducted for analyzing the risk factors of adverse cerebrovascular events. Results. After treatment, the Con group got lower self-management behavior score than the Obs group (

P
<
0.05

), and also got lower SF-36 scores, BI, and MOCA scores than the Obs group (

P
<
0.05

). Age and a history of hypertension were independent risk factors for adverse events. The Hosmer–Lemeshow test was adopted for testing the goodness of fit of the regression equation (

P
=
0.903

). With the established model, the area under the receiver operating characteristic curve for predicting adverse events in patients with intracranial aneurysm was determined to be 0.851, indicating that the model performed well as a risk prediction model. Conclusion. TTM + motivational interviewing can help improve the self-management behavior and QoL of patients with intracranial aneurysm without increasing the occurrence of adverse events.
Research on Mono-Pulse Beam Angle Tracking Algorithm of Phased Array Antenna Based on CKF
Authors: Xuan Liu , Ruo-xin Li , Yi-feng He
Published: August 2022

Phased array antenna beam tracking and communication system based on mono-pulse system is an alternative satellite-to-earth communication technology solution for future planetary spacecraft, which meets the mission requirements of agile scanning, multimode, wide field of view, and small size. This paper firstly outlines the technical scheme of mono-pulse angle tracking based on the planar phased array antenna. A simplified mathematical model of angle measurement is summarized. Secondly, the beam pointing of the spacecraft communication antenna is frequently affected by the attitude and presents a nonlinear dynamic change. A robust two-dimensional angular tracking filtering algorithm based on cubature Kalman filter (CKF) is proposed, in order to solve this complex high-order nonlinear dynamic estimation problem. Finally, the comprehensive performance of the proposed algorithm is simulated and analyzed under two conditions of stable flight and high dynamic flight of the spacecraft. When the angular velocity is within 4°/s, the tracking accuracy can be better than 0.65°, and the tracking accuracy will be better than 1° when the angular velocity is within 8°/s. Compared with the basic CKF algorithm, the robust CKF tracking accuracy is significantly improved, while the resource consumption is slightly reduced. The research results can provide reference for the engineering implementation of related fields in the future.
[Retracted] Vancomycin as an Antibacterial Agent Capped with Silver Nanoparticles: An Experimental Potential Analysis
Authors: Patwekar Mohsina , Patwekar Faheem , Alghamdi Saad , Kamal Mehnaz , Allahyani Mamdouh , Almehmadi Mazen , Kabrah Ahmed , Dablool Anas S. , Alsaiari Ahad Amer , Jawaid Talha , Medikeri Anuradha , Samuel Krupa , Islam Fahadul
Published: August 2022

For the treatment of various infections, a variety of antimicrobial drugs are formulated. Nevertheless, many bacterial infections now exhibit antibiotic resistance due to the widespread utilization antibiotics. Methicillin‐resistant among the most dangerous multidrug‐resistant bacteria is Staphylococcus aureus (MRSA). Vancomycin became a viable therapy option due to MRSA resistance to methicillin medicines. One of the well‐informed antibacterial compounds with wideband antibacterial activity is silver nanoparticles (AgNPs). AgNPs are thus suitable candidates for usage in conjunction alongside vancomycin to increase its antibacterial effect. The goal of the present research work is to boost the antibacterial potency of the glycopeptide antibiotic vancomycin towards Gram‐positive (Staphylococcus aureus) but also Gram‐negative (Escherichia coli) bacteria. The chemical reduction approach is used to create a colloidal solution of silver nanoparticles utilizing silver nitrate as a precursor in the environment of the ionic surfactant trisodium citrate that serves as covering including reducing reagent. Vancomycin was used to functionalize the synthesized nanoparticles and create the nanodrug complex (Van@AgNPs). The synergistic antibacterial potential of silver nanoparticles coated with vancomycin on both test pathogens was investigated using the agar well diffusion technique. The antibacterial potency for both classes of bacteria has significantly increased, according to the well diffusion test. It has been noted that this improvement is synergistic instead of additive.
[Retracted] Meta‐Analysis of Mechanism of Influence of CRY2 on the Differentiation of Mouse Osteoblast through the Regulation of Wnt/Β‐Catenin Signaling Pathway
Authors: Ma Chao , Yang Chaojian , Xie Tong , Dai Wenjuan , Ma Jun
Published: August 2022

Noncoding RNAs were discovered to control a variety of developmental mechanisms, including osteogenesis. According to emerging evidence, cryptochrome circadian‐regulating (CRY) proteins have emerged as essential controllers of osteoblast differentiation. The linked processes, on the other hand, are still unknown. The specific process that underpins osteoblast differentiation and proliferation is yet unknown. This research gives a meta‐analysis of CRY2’s impact on mouse osteoblast differentiation via the control of the WNT/β–catenin signaling pathways. Western blot and quantitative real‐time PCR were used to identify Cry2 expression levels, components in the osteoblast‐associated signaling pathway, and osteoblast transcription markers. The osteogenic condition was measured utilizing alkaline phosphatase (ALP) and alizarin red (AR) staining, whereas cell growth rates were measured using CCK8 assays. An ectopic bone formation experiment was used to determine the osteogenic potential of osteoblasts. Cry2 stimulates the osteogenic development of mouse osteoblasts through canonical Wnt/β‐catenin signaling, according to the findings.
An Analysis of the Influence of Complex Networks in Cross-Cultural Communication
Authors: Meng Yun
Published: August 2022

With the in-depth exchanges in various aspects such as global politics, economy and trade, and cultural exchanges, improving the cultural status of the Chinese nation has become a major strategic goal of the Chinese nation. In order to better pass on Chinese culture and to truly improve the effectiveness and influence of Chinese culture in international publicity, Chinese culture needs to gradually explore effective cross-language cultural communication methods and strategies to comprehensively improve Chinese culture in cross-language cultural exchange strength on the stage of global traditional cultural exchange. On the basis of analyzing the current situation of cross-cultural communication, the article studies the promoting effect of complex networks on cross-cultural communication. The results of the article show that (1) the influence of complex networks on cultural communication is relatively significant, and the complex network communication model is used. After that, the communicative competence of the three groups has been greatly improved, and among them, the group with the rapid growth of cultural level has the greatest room for growth. (2) The point-degree centrality of organizational relationship is 10, which is relatively high, indicating that organizational relationship is in the middle position among the influencing factors, and the value orientation has a strong mediating effect. (3) The propagation efficiency of the complex network model is the highest. With the increase of the time series, the propagation efficiency will also increase. The propagation efficiency of the complex network propagation model can reach 85%. When the number of nodes is 5000, the propagation efficiency of cultural information can reach 80%.
Optimal Time Allocation for Energy Harvesting Cognitive Radio Networks with Multichannel Spectrum Sensing
Authors: Liu Xiaoying , Xia Ming , Hu Ping , Zheng Kechen , Zhang Shubin
Published: August 2022

From the perspective of time domain and frequency domain, we investigate the energy harvesting cognitive radio networks (EH-CRNs) with multichannel, where the secondary transmitter (ST) opportunistically accesses the licensed subchannels to transmit packets by consuming the harvested energy. To explore the spectrum holes and improve the lifetime of the EH-CRNs, the ST scavenges energy from the radio-frequency (RF) signal in the wide band during the energy harvesting (EH) phase and exploits the harvested energy for sequential sensing and packet transmission during the rest of the time slot. Under the energy constraint, the secondary throughput is improved by optimizing the time allocation among the EH phase, sensing phase, and transmission phase. We formulate the secondary throughput with respect to the durations of the three phases, prove the existence of the optimal time allocation, and discuss the secondary throughput in three cases of the EH-CRNs. Finally, numerical results validate the theoretical results about the secondary throughput and explore the impacts of key system parameters.
Analysis on the Development of Smart City of Big Cities in China and Its Effect to Economic Structure Based on Entropy Method
Authors: Liu Yejin , Ye Min
Published: August 2022

This work aims to analyze the construction of smart cities in China’s large cities and its impact on the economic structure. Some developed countries, such as the United States and Europe, have established mature smart city evaluation systems. Therefore, this work draws on the evaluation system of smart cities in developed countries to study the development status of smart cities in large cities in China. An extend linear system evaluation model is established. Besides, five first-level indicators and 24 second-level indicators are established from the five aspects: urban infrastructure, technological innovation, smart economy, human services, and intelligent environment to evaluate the development status of the city. In addition, a susceptible infected system model has been established to study the impact of smart city construction on the industrial structure. The research results demonstrate that the development level of smart cities and smart industries in eastern China is relatively high, and the comprehensive scores of smart city construction in Beijing, Shanghai, Guangzhou, Shenzhen, and Chongqing all exceed 0.082. However, the development level of smart cities and smart industries in the central and western regions is relatively low. The comprehensive evaluation scores of smart cities such as Tianjin, Hangzhou, and Wuhan are between 0.35 and 0.8, and technological innovation still needs to be further developed. In conclusion, the development gap between eastern, central, and western China has further widened with time. This work provides possible research experience for China’s smart city construction and industrial construction.
A Practical Anonymous Voting Scheme Based on Blockchain for Internet of Energy
Authors: Hu Houpeng , Ou Jiaxiang , Qian Bin , Luo Yi , He Peilin , Zhou Mi , Chen Zerui
Published: August 2022

E-voting allows us to build a democratic business in most Internet of things (IoT) systems. For example, we may vote to choose a proper energy broker in a smart grid system. In this study, we focus on e-voting services in an Internet of energy (IoE) system, which is a new-style smart grid. A practical e-voting in IoE may focus on the properties of fairness, decentralization, eligibility, anonymity, compatibility, verifiability, and coercion resistance. It is difficult to fulfil all these properties simultaneously. Traditional voting schemes often use a public bulletin board or administrator in the voting process, which makes them become centralized. Services that offer e-voting via blockchain can make the voting schemes decentralized. However, many of them ignore the complexity of organizing the data of the transactions, which should be confirmed by the miners. Moreover, to the best of the authors’ knowledge, no works have tested the performance in the blockchain while considering practical use cases and constraints. Concerning all the challenges, we propose a practical anonymous voting scheme for IoE called IoEPAV. The proposed scheme fulfils all the mentioned design goals simultaneously. We tested IoEPAV both in different test networks of the Ethereum blockchain to give an overall evaluation. The practical evaluation can show that the proposed scheme is easy to be integrated into a real system like IoE. We also gave a comparison analysis with the state-of-the-art blockchain-based e-voting. All the results show that IoEPAV is decentralized, verifiable, anonymous, and highly efficient.
Relational Quasicontractions and Related Fixed Point Theorems
Authors: Eljaneid Nidal H. E. , Khan Faizan A. , Mohammed Hamid I. A. , Alam Aftab
Published: August 2022

In this article, some results on fixed points under quasicontractions in the framework of metric space endowed with binary relation are proved. Our newly proved results improve and extend several noted fixed point theorems of the existing literature besides their relation‐theoretic analogues. We conclude this article by constructing an example to affirm the efficacy of our results.