bluuebunny/crossref_metadata_2025 huggingface dataset:
Thymosin β4 Protects against Cardiac Damage and Subsequent Cardiac Fibrosis in Mice with Myocardial Infarction
Authors: Wang Fei , He Yajuan , Yao Naijuan , Ruan Litao , Tian Zhen
Published: June 2022

Background. Inflammation is a critical factor in the development and progression of myocardial infarction and cardiac fibrosis. Thymosin β4 (Tβ4) alleviates the disease process via protective antioxidant and anti-inflammatory mechanisms. Although Tβ4 has been shown to have a protective effect in myocardial infarction, its impact on cardiac fibrosis has not been well reported. In this study, we evaluated the influence of exogenous Tβ4 on myocardial infarction and cardiac fibrosis and explored the possible underlying mechanism. Methods. Real-time quantitative reverse-transcription PCR (qRT-PCR), immunohistochemistry (IHC), and Western blot were used to analyze Tβ4 expression in acute myocardial infarction (AMI) cardiac tissues. The effects of intraperitoneal adeno-associated virus-Tβ4 (AAV-Tβ4) on ligation-induced AMI in mice were studied using cardiac function parameters, and RT-PCR, Western blot, HE staining, Masson staining, and IHC were used to assess the degree of myocardial fibrosis. The effects of Tβ4 were confirmed in vitro using mouse cardiac myocytes and myofibroblasts. Results. Tβ4 was shown to be significantly elevated in mice AMI cardiac tissues. In mice, AAV-Tβ4 induced exogenous expression of Tβ4 significantly reduced oxidative damage, inflammation, cardiac dysfunction, and fibrosis. H2O2 inhibited mitophagy and increased inflammation in mouse cardiac myocytes via oxidative stress, and Tβ4 substantially reduced mitophagy inhibition and inflammasome activation in myocytes caused by H2O2. Furthermore, Tβ4 decreased cardiac myofibroblast growth and reduced TGF-β1-induced activation. Conclusions. AAV-Tβ4 induced expression of Tβ4 reduced inflammation, heart damage, and eventual fibrosis in vivo. Tβ4 helped to reduce oxidative stress, promote mitophagy, and alleviate inflammation and fibrosis. Exogenous supplementation of Tβ4 might be a promising therapeutic agent for treating myocardial infarction as well as cardiac fibrosis.
Research on the Role and Mechanism of Digital Finance in Improving the Performance of Industrial Green Innovation
Authors: Wang Haojie
Published: June 2022

The slack-based measure–Malmquist index model (SBM Malmquist) including unexpected output was used to calculate the performance of China’s provincial industrial green innovation from 2011 to 2019, and a systematic general moment method (GMM) with a dynamic panel model was constructed to empirically test the effect and mechanism of digital finance on the performance of industrial green innovation. The results show that the performance of China’s industrial green innovation has shown an upward trend in recent years, mainly due to improvements in technical efficiency. Digital finance can significantly promote the performance of industrial green innovation, and the improvement of technical efficiency is greater than that of technological progress. From the perspective of structure, the coverage, use depth, and digitization degree have significantly promoted the performance of industrial green innovation, and the digitization degree has the greatest effect. In areas with backward and traditional financial development, digital finance can better promote the improvement in the performance of industrial green innovation and technical efficiency, and the role of the universal benefit is obvious. The mechanism test found that financial efficiency played a partial intermediary effect in the process of digital finance, affecting the performance of industrial green innovation, while residents’ consumption mainly played a masking role. This provides a useful reference for the development and optimization of digital finance and the realization of the drive towards regional industrial green innovation.
Random Walk Algorithm-Based Computer Tomography (CT) Image Segmentation Analysis Effect of Spiriva Combined with Symbicort on Immunologic Function of Non-Small-Cell Lung Cancer
Authors: Li Xiaodan , Liu Wei , Liang Mianjie , Sun Zengtao
Published: June 2022

The objective of this research was to explore the effect of the treatment regimen of Spiriva combined with Symbicort on the immune function of non-small-cell lung cancer (NSCLC) based on computed tomography (CT) imaging features. An automatic CT image segmentation algorithm (RW-CT) was constructed based on random walk (RW) and image segmentation technology. The image segmentation algorithm based on the Toboggan method (C-CT) was introduced to compare with the traditional RW algorithm. 60 subjects were divided into four groups: a Chinese combined with Western medicine group (treated with Spiriva combined with Symbicort, group C+W), a Chinese medicine group (treated with Spiriva, group C), a Western medicine group (treated with Symbicort, group W), and a model group for control (group M). The results show that the Dice coefficient of the RW-CT algorithm was obviously larger than that of the C-CT algorithm and the RW algorithm, while the Hausdorff distance (HD) of the RW-CT algorithm was much smaller than that of the other two algorithms (

P
<
0.05

). The proportion of positive cells of hypoxia-inducible factor-1α (HIF-1α) in group C+W was the least (15%-23%), followed by the group W (21%-29%) and the group C (28%-37%), and that in the group M was the highest (39%-49%). There was a remarkable difference in the immunohistochemical scores (HIS) of vascular endothelial growth factor (VEGF) in the tumor tissues between group C+W and the group M (

H
=
14.200

,

P
=
0.001

), but there was no great difference from the group C and the group W (

P
>
0.05

). There was a notable difference in the IHS of vascular endothelial factor recepto-2 (VEGFR-2) between the group C+W medication group and the group M (

H
=
12.800

,

P
=
0.002

), and there was no statistical difference between the group C and W (

P
>
0.05

). In short, the RW-CT constructed based on RW was better than the traditional algorithms for CT image segmentation. The Spiriva combined with Symbicort could effectively inhibit the expression of VEGF, VEGFR-2, and HIF-1α in NSCLC and promote the immunologic function of the body.
Dengue Risk Forecast with Mosquito Vector: A Multicomponent Fusion Approach Based on Spatiotemporal Analysis
Authors: Li Linlin , Fang Zhiyi , Zhou Hongning , Tang Yerong , Wang Xin , Liang Geng , Zhang Fengjun
Published: June 2022

Dengue as an acute infectious disease threatens global public health and has sparked broad research interest. However, existing studies generally ignore the spatial dependencies involved in dengue forecast, and consideration of temporal periodicity is absent. In this work, we propose a spatiotemporal component fusion model (STCFM) to solve the dengue risk forecast issue. Considering that mosquitoes are an important vector of dengue transmission, we introduce feature factors involving mosquito abundance and spatiotemporal lags to model temporal trends and spatial distributions separately on the basis of statistical properties. Specifically, we conduct multiscale modeling of temporal dependencies to enhance the forecast capability of relevant periods by capturing the historical variation patterns of the data across different segments in the temporal dimension. In the spatial dimension, we quantify the multivariate spatial correlation analysis as additional features to strengthen the spatial feature representation and adopt the ConvLSTM model to learn spatial dependencies adequately. The final forecast results are obtained by stacking strategy fusion in ensemble learning. We conduct experiments on real dengue datasets. The results indicate that STCFM improves prediction accuracy through effective spatiotemporal feature representations and outperforms candidate models with a reasonable component construction strategy.
A Path-Planning Approach Based on Potential and Dynamic Q-Learning for Mobile Robots in Unknown Environment
Authors: Hao Bing , Du He , Zhao Jianshuo , Zhang Jiamin , Wang Qi
Published: June 2022

The path-planning approach plays an important role in determining how long the mobile robots can travel. To solve the path-planning problem of mobile robots in an unknown environment, a potential and dynamic Q-learning (PDQL) approach is proposed, which combines Q-learning with the artificial potential field and dynamic reward function to generate a feasible path. The proposed algorithm has a significant improvement in computing time and convergence speed compared to its classical counterpart. Experiments undertaken on simulated maps confirm that the PDQL when used for the path-planning problem of mobile robots in an unknown environment outperforms the state-of-the-art algorithms with respect to two metrics: path length and turning angle. The simulation results show the effectiveness and practicality of the proposal for mobile robot path planning.
Optical Microstructure, FESEM, Microtensile, and Microhardness Properties of LM 25-B4Cnp-Grnp Hybrid Composites Manufactured by Selective Laser Melting
Authors: Babu M. , Venkataraman S.R. , Rao Putta Nageswara , Rao Venkateswara , Kaliappan S. , Patil Pravin P , Sekar S. , Yuvaraj K.P. , Murugan Arundeep
Published: June 2022

The current investigation, nano-multi-powder particles, 5 and 10 wt.% boron carbide (B4C) and graphite (Gr) are utilized as a reinforcement, and aluminium LM 25 alloy is used as a matrix. These hybrid nanocomposites were fabricated by a novel additive manufacturing method—selective laser melting. The specimen was carried out in a cylindrical size having 2 circular slots of dimension 14 and length 50 mm. The diverse SLM specimens focused on tribological properties of impact, creep, tensile, and hardness were carried out for the three specimens with same weight percentage of nanoparticles. The consequence of the reinforcement has been performed through microtensile and microhardness tests. The microtensile and microhardness properties are evaluated by microtensile test machine and Vickers hardness tester, and the specimen has been prepared as per ASTM E8 and ASTM E18 standards. Microtensile strength and hardness were augmented by the addition of B4C and graphite nanoparticles. The tensile strength and hardness values are 668.93 MPa and 739.16 MPa, and 193VHN and 206.79VHN, respectively. The result of the microstructure study shows homogeneous dispersion of B4Cnp-Grnp in the matrix material of the LM25 alloy. The FESEM image results of the ruined surface illustrate the addition performance of ductile fracture, brittle fracture, and ploughing of reinforced material. The consequences of the research enhanced tensile and hardness properties of composite with reinforcement added.
The Impact of Emotional Intelligence on Cognitive Strategy Uses of Saudi English Foreign Language Students’ Vocabulary Knowledge
Authors: Tilwani Shouket Ahmad , Asif Muhammad , Hussain Zahida , Patra Indrajit , Sarabani Leeda
Published: June 2022

It is becoming increasingly difficult to ignore the connection between emotional intelligence, strategy use, and vocabulary knowledge. However, very little attention has been paid to this subject, to the best of researchers’ knowledge. To this end, intermediate students were considered through the Cambridge English: Key English Test (KET). After taking the test, 50 male students with a mean age of 16 whose grades equaled (between 45 and 69) were chosen for this research sample. Adopting a correlational design, the researchers gathered three types of scores: an emotional intelligence questionnaire, cognitive strategy use questionnaire, and a vocabulary knowledge test. The data were checked for linearity of the relationship and normality of the distribution. Finally, Pearson product-moment correlation was conducted to identify any possible correlation between the variables. The results showed a significant relationship between emotional intelligence and cognitive strategy use. The data analysis also indicated a relationship between emotional intelligence and vocabulary knowledge. Moreover, the data analysis showed that in comparison with cognitive strategy use, vocabulary knowledge has a higher correlation with emotional intelligence. The findings have some pedagogical implications for instructors of proficiency courses, writing textbook developers, EFL learners, and language teachers who can benefit from this research results.
Construction of a Multimedia Education Resource Security Model Based on Multistage Integration
Authors: Yuan Lina
Published: June 2022

A security model of multimedia education resource fusion based on multistage integration of multimedia educational resources is constructed in this paper in the context of smart education. First, the teaching model of multimedia education resource fusion is analyzed and the IoT communication evolution model and functional architecture model are constructed accordingly, based on which the realization path of IoT intelligent sensing, intelligent management, emotional computing, device sharing, and vision simulation functions for smart education are discussed. The security model uses a decentralized cryptographic data security sharing method based on blockchain for protection and supports blockchain to record user attributes to ensure the confidentiality and integrity of data. The experimental and analytical results indicate that the scheme can effectively reduce the computational overhead of smart devices while ensuring the security of data sharing. Moreover, the proposed model in the paper achieves better performance than other methods in terms of security strength, encryption, and decryption time.
Effect of Sandplay Therapy on the Mental Health Level of College Students
Authors: Li Gaoyong , Wu Xue
Published: June 2022

To analyze the effect of sandplay (SP) therapy on the mental health level of college students. 500 college students were openly recruited, using the University Student Mental Health Questionnaire (UPI) to screen out 76 students in the UPI category. 34 college students were randomly selected and divided into two groups, 17 in the control group and 17 in the SP therapy group (experimental group); the control group received no treatment, and the experimental group was treated with SP therapy, to analyze the differences between groups before and after the intervention of SCL-90 and self-made group self-reflection questionnaire. (1) With a detection rate of 15.2 percent, 76 of the 500 college students solicited openly were identified as UPI students; (2) except for the terror factor, there were significant differences in other aspects and overall scores for the experimental group following SP therapy intervention, and the scores reduced. There were no significant differences in the total scores and scores of all factors in the control group (

P
>
0.05

). The overall score, somatization, interpersonal connection, depression, paranoia, and psychosis were all significantly different between the experimental and control groups in the independent sample

t

-test (

P
<
0.05

).
An Information Granulated Based SVM Approach for Anomaly Detection of Main Transformers in Nuclear Power Plants
Authors: Yu Wenmin , Yu Ren , Li Cheng
Published: June 2022

The main transformer is critical equipment for economically generating electricity in nuclear power plants (NPPs). Dissolved gas analysis (DGA) is an effective means of monitoring the transformer condition, and its parameters can reflect the transformer operating condition. This study introduces a framework for main transformer predictive-based maintenance management. A condition prediction method based on the online support vector machine (SVM) regression model is proposed, with the input data being preprocessed using the information granulation method, and the parameters of the model are optimized using the particle swarm optimization (PSO) algorithm. Using DGA data from the NPP data acquisition system, two experiments are designed to verify the trend tracing and prediction envelope ability of main transformers installed in NPPs with different operating ages of the proposed model. Finally, how to use this framework to benefit the maintenance plan of the main transformer is summarized.
Cycle Performance of Aerated Lightweight Concrete Windowed and Windowless Wall Panel from the Perspective of Lightweight Deep Learning
Authors: Yuan Xing , Zhang Yao , Lu Qinggang , Zhang Shuhang , Liu Hua , Jin Mingchang , Xu Feng
Published: June 2022

This paper aims to explore the seismic mechanical properties of newly developed fabricated aerated lightweight concrete (ALC) wall panels to clarify the interaction mechanism between wall panels and structures. It first introduces the lightweight deep learning object detection algorithm and constructs a network model with faster operation speed based on the convolutional neural network. Secondly, combined with the deep learning object detection algorithm, the quasi-static loading system is adopted to conduct the repeated loading test on two fabricated ALC wall panels. Finally, the hysteresis load-displacement curve of each test is recorded. The experimental results show that the proposed deep learning algorithm greatly improves the operation speed and compresses the model size without reducing the accuracy. The lightweight deep learning algorithm is applied to the study of the slip performance of the wall plate. The pretightening force of the connecting screw characterizes the slip performance between the wall plate and the structural beam, thereby affecting the deformation response of the wall plate when the interstory displacement increases. The hysteresis curve of the ALC wall panel has obvious squeezing effect, indicating that the slip of the connector can unload part of the external load and delay the damage of the wall panel. The skeleton curve suggests that the fabricated windowless ALC wall panel has higher positive and negative initial stiffness and bearing capacity than the fabricated windowed wall panel. However, the degradation analysis of the stiffness curve reveals that the lateral stiffness deviation of the fabricated windowless ALC wall panel is more obvious. It confirms that the proposed connection method based on the lightweight deep learning model can improve the seismic performance of ALC wall panels and provide reference for the structural analysis of embedding fabricated ALC wall panels. This work shows the important practical value for exploring the application effect of embedded ALC wall panels.
Detection of Cannabinoid Receptor Expression by Endometriotic Lesions in Women with Endometriosis as an Alternative to Opioid-Based Pain Medication
Authors: Allam Sarah , Paris Elizabeth , Lazcano Itzel , Bitterman Pincas , Basu Sanjib , O’Donnell James , Barua Animesh
Published: June 2022

Emerging information suggests a potential role of medicinal cannabis in pain medication in addition to enhancing immune functions. Endometriosis is a disease of women of reproductive age associated with infertility and reproductive failure as well as chronic pain of varying degrees depending on the stage of the disease. Currently, opioids are being preferred over nonsteroidal anti-inflammatory drugs (NSAID) due to the latter’s side effects. However, as the opioids are becoming a source of addiction, additional pain medication is urgently needed. Cannabis offers an alternative therapy for treating the pain associated with endometriosis. Information on the use and effectiveness of cannabis against endometriotic pain is lacking. Moreover, expression of receptors for endocannabinoids by the ovarian endometriotic lesions is not known. The goal of this study was to examine whether cannabinoid receptors 1 and 2 (CB1 and CB2) are expressed by ovarian endometriotic lesions. Archived normal ovarian tissues, ovaries with endometriotic lesions, and normal endometrial tissues were examined for the presence of endometrial stromal cells using CD10 (a marker of endometrial stromal cells). Expression of CB1 and CB2 were determined by immunohistochemistry, immunoblotting, and gene expression studies. Intense expression for CB1 and CB2 was detected in the epithelial cells in ovarian endometriotic lesions. Compared with stroma in ovaries with endometriotic lesions, the expression of CB1 and CB2 was significantly higher in the epithelial cells in endometriotic lesions in the ovary (

P
<
0.0001

and

P
<
0.05

, respectively). Immunoblotting and gene expression assays showed similar patterns for CB1 and CB2 protein and CNR1 (gene encoding CB1) and CNR2 (gene encoding CB2) gene expression. These results suggest that ovarian endometriotic lesions express CB1 and CB2 receptors, and these lesions may respond to cannabinoids as pain medication. These results will form a foundation for a clinical study with larger cohorts.
The Risk of Developing Lymphoma among Autoimmune Thyroid Disorder Patients: A Cross-Section Study
Authors: Al-Mansour Mubarak , Maglan Alaa Fawzi , Altayeb Meral Khalid , Faraj Laila Ali , Felimban Esraa Aman , Aga Syed Sameer , Khan Mohammad Anwar
Published: June 2022

Background. Graves’ disease (GD) and Hashimoto’s thyroiditis (HT) are the most common types of autoimmune thyroid diseases (AITD), and both are characterized by the infiltration of lymphocytes into the thyroid gland. Moreover, autoimmune diseases like HT have a higher risk of developing lymphoma. This study is aimed at assessing the prevalence and association of lymphoma in patients with AITD. Methods. This cross-sectional study was conducted in King Abdulaziz Medical City, Jeddah, Saudi Arabia. Data were gathered from the medical records of patients aged 18 years or older who developed AITD. A total number of 140 medical records were collected, and 72 patients were included after applying in exclusion criteria. Data on the subtype, clinical-stage, treatment modality, patient status, remission, and relapse were collected for patients who developed lymphoma. Results. Among 72 patients who developed AITD, HT was diagnosed in 58 (80.6%) patients and GD in 14 (19.4%). Five (7%) patients were diagnosed with lymphoma all of whom had a history of HT. The subtypes of lymphoma were diffuse large B-cell lymphoma (DLBCL 3; 4.2%), follicular lymphoma 1 (1.4%), and Hodgkin’s lymphoma 1 (1.4%). Conclusion. The prevalence of PTL in patients with AITD, specifically HT, was 7%. Most patients developed NHL, with DLBCL being the most common subtype. The onset of lymphoma in this study was lower than reported in the literature. All patients with PTL had HT in their backgrounds. Further national studies are warranted to explore the relationship between the two diseases to provide more insight into the comprehension of this association.
miR-214 Modulates the Growth and Migration of Oral Cancer before and after Chemotherapy through Mediating ULK1
Authors: Yang Yongtao , Sun Xiaolan , Li Minghua , Li Limei , Wang Shanshan , Zhu Yaomin
Published: June 2022

The role of miRNAs as crucial components in carcinogenesis has been well documented. However, whether and how miR-214 influences oral cancer cells’ drug resistance remains to be elucidated, and its downstream targets are still under investigation. Hence, this research is aimed at determining miR-214 and ULK1 expression in oral cancer before and after chemotherapy and their correlations with cancer cell growth. Human oral normal epithelial cells and human tongue squamous cell carcinoma CAL-27 cells were cultured to detect miR-214 and ULK1 levels. It was found that before chemotherapy, miR-214 was higher, while ULK1 was underexpressed in CAL-27 cells, versus normal epithelial cells. After chemotherapy, miR-214 decreased obviously in CAL-27 cells, while ULK1 level increased significantly. In addition, autophagy-related genes (Beclin 1, mTOR, and P53) in CAL-27 cells were found to be significantly inhibited before chemotherapy and were obviously increased after chemotherapy. Moreover, to further determine the impacts of miR-214 and ULK1 on oral cancer cell growth after chemotherapy, the two were overexpressed or silenced in CAL-27 cells after transfection. We found that ULK1 could effectively decrease the activity and invasion of CAL-27 cells and increase their apoptosis level, while miR-214 could antagonize its antitumor effect. Therefore, miR-214 can be used as an early prognostic biomarker for oral cancer, and ULK1 is a new candidate therapeutic target.
Dynamic Resource Allocation and Forecast of Snow Tourism Demand Based on Multiobjective Optimization Algorithm
Authors: Feng Mingfen , Zhang Xiaomei , Dong Shuqi
Published: June 2022

This paper aims to map the task of reliable transmission of wireless sensor networks. At the same time, this paper transforms the mapping problem of wireless sensor networks into a problem of reducing the energy consumption of mapping under many constraints such as reliability and scheduling length and uses discrete particle swarm optimization algorithm to map. For optimization, the algorithm performs iterative calculations to obtain the best mapping node for each operation so that the inertia coefficient of the existing particle swarm optimization algorithm is improved and linearly minimized with the number of iterations. When resource-demanding tasks need to allocate dynamic resources to multiple nodes to complete collaboratively, adding the mapping principle of the nearest node in the discrete particle swarm optimization mapping reduces the energy consumption of communication between tasks. An in-depth analysis of the influencing factors of the ice and snow tourism market shows that the per capita disposable income of urban residents and the number of urban residents have a significant impact on the ice and snow tourism market demand. In addition, regression analysis and demand-based forecasting are important methods to analyze the scale and development trend of tourism. At the same time, it shows an important position in the purpose of urban tourism and regional market share so as to provide a basis for decision-making in tourism destination marketing. This paper mainly studies and analyzes the wireless sensor network and further introduces it into dynamic resource allocation and ice and snow tourism, which can promote the continuous development of dynamic resource allocation and ice and snow tourism.
Nanotube Combined Rehabilitation Therapy in the Treatment of Knee Arthritis in Basketball Players
Authors: Zheng Yi
Published: June 2022

With the improvement of people’s attention to health, basketball is a sport that can strengthen the body and deeply loved by people. However, basketball involves a lot of physical activity and a quick stop technique, which increases the risk of arthritis. The reason for this paper is to concentrate on the utilization of nanotube joined restoration treatment in the treatment of knee joint pain in basketball players. This paper first introduces the structure and properties of carbon nanotubes, analyzes the pathology of knee arthritis and the causes of knee arthritis in basketball players, and discussed the knee arthritis rehabilitation treatment method. According to the diagnostic criteria of osteoarthritis and the significant incorporation and rejection measures, a sum of 50 patients with knee osteoarthritis were chosen as the review subjects and separated into test gathering and control bunch. The benchmark group was treated with conventional electroacupuncture, and the exploratory gathering was treated with nanotubes as repair materials for knee arthritis. The experimental results show that the application of nanotube combined rehabilitation therapy in the treatment of knee arthritis in basketball players is practical to a certain extent. The total score of WOMAC in the two groups after treatment decreased to a certain extent compared with that before treatment, but the difference in the experimental group was more obvious, and the difference was significant after statistical analysis (P < 0.05).
On Nonlocal Vertical and Horizontal Bending of a Micro-Beam
Authors: Zhu Chengxiu , Chen Yingting , Zhao Jingbo , Li Cheng , Lei Zuxiang
Published: June 2022

The vertical and horizontal bending of micro-beams subjected to axial compressive and transverse concentrated loadings is a common lateral deformation in micro-/nano-engineering that plays a significant role in the design and optimization of micro-/nano-devices. The present study aims to investigate it using the nonlocal theory. For this purpose, the simplified mathematical model is developed, and the nonlocal differential constitutive equation is applied. Since the mechanical properties of micro-beams are different from those of macro-beams, the non-classical nonlocal bending moment is introduced to improve the classical bending formulation in order to adapt to the vertical and horizontal bending of micro-beams. The effects of the external load, external size, structural stiffness, and internal characteristic scale on the vertical and horizontal bending deformation including the midpoint deflection and critical compression are presented. The present analytical model and results are validated by the finite element method. It is shown that the critical compression decreases with increasing the internal characteristic scale. Moreover, the midpoint deflection varies remarkably with respect to the axial and transverse loadings, structural stiffness, internal characteristic scale, and external size. An obvious nonlocal scale effect is found, in which the internal characteristic scale cannot be neglected compared with the external size. Besides, a threshold value of the structural stiffness is determined, and the connotation of the nonlocal interaction requires that the structural stiffness shall not be lower than that threshold. A mutual restriction between structural stiffness and external loadings is observed in the vertical and horizontal bending. In particular, it is further proved that the classical continuum mechanics can not be used in micro-/nano-scaled mechanics through a strange phenomenon that is contrary to mechanical common sense in the calculation example. The study is expected to be beneficial to the design and application of micro-beams subjected to the vertical and horizontal bending.
Elite Oppositional Farmland Fertility Optimization Based Node Localization Technique for Wireless Networks
Authors: Bharathiraja N. , Padmaja Pydimarri , Rajeshwari S. B. , Kallimani Jagadish S. , Buttar Ahmed Mateen , Lingaiah T. Bheema
Published: June 2022

Wireless networks include a set of nodes which are connected to one another via wireless links for communication purposes. Wireless sensor networks (WSN) are a type of wireless network, which utilizes sensor nodes to collect and communicate data. Node localization is a challenging problem in WSN which intends to determine the geographical coordinates of the sensors in WSN. It can be considered an optimization problem and can be addressed via metaheuristic algorithms. This study introduces an elite oppositional farmland fertility optimization-based node localization method for radio communication networks, called EOFFO-NLWN technique. It is the goal of the proposed EOFFO-NLWN technique to locate unknown nodes in the network by using anchor nodes as a starting point. As a result of merging the principles of elite oppositional-based learning (EOBL) and the agricultural fertility optimization algorithm (FFO), we have developed the EOFFO-NLWN approach, which is described in detail below. The EOBL concept makes it easier to populate the FFO algorithm’s population initialization, which results in an increase in the exploration rate. Various BNs and CRs were tested, and the findings revealed that the EOFFO-NLWN technique outperformed all other known techniques in all cases. A comprehensive experimental result analysis of the EOFFO-NLWN technique is performed under several measures, and the results described the sovereignty of the EOFFO-NLWN method associated to existing techniques.
Lag Synchronization of Noisy and Nonnoisy Multiple Neurobiological Coupled FitzHugh–Nagumo Networks with and without Delayed Coupling
Authors: Ibrahim Malik Muhammad , Iram Shazia , Kamran Muhammad Ahmad , Naeem Mannan Malik Muhammad , Ali Muhammad Umair , Jung Il Hyo , Kim Sangil
Published: June 2022

This paper presents a methodology for synchronizing noisy and nonnoisy multiple coupled neurobiological FitzHugh–Nagumo (FHN) drive and slave neural networks with and without delayed coupling, under external electrical stimulation (EES), external disturbance, and variable parameters for each state of both FHN networks. Each network of neurons was configured by considering all aspects of real neurons communications in the brain, i.e., synapse and gap junctions. Novel adaptive control laws were developed and proposed that guarantee the synchronization of FHN neural networks in different configurations. The Lyapunov stability theory was utilized to analytically derive the sufficient conditions that ensure the synchronization of the FHN networks. The effectiveness and robustness of the proposed control laws were shown through different numerical simulations.
Global Occupational Exposure to Blood and Body Fluids among Healthcare Workers: Systematic Review and Meta-Analysis
Authors: Mengistu Dechasa Adare , Dirirsa Gebisa , Mati Elsai , Ayele Dinku Mekbib , Bayu Kefelegn , Deriba Wegene , Alemu Fekade Ketema , Demmu Yohannes Mulugeta , Asefa Yohanis Alemeshet , Geremew Abraham
Published: June 2022

Background. Occupational exposure to blood and body fluids has become a serious public health problem for healthcare workers and is a major risk for the transmission of various infections such as human immune-deficiency virus, hepatitis B virus, and hepatitis C virus. This systematic review and meta-analysis aims to determine the career time and previous one-year global pooled prevalence of occupational exposure to blood and body fluids among healthcare workers. Methods. For the review, the articles published in English were searched using the electronic databases (SCOPUS/Science Direct, PubMed, Web of Science, Google Scholar, CINAHL, MEDLINE, Cochrane Library, DOAJ, and MedNar) with a combination of Boolean logic operators (AND, OR, and NOT), Medical Subject Headings (MeSH), and keywords. A quality assessment was conducted to determine the relevance of the articles using JBI critical appraisal tools. Furthermore, several steps of assessment and evaluation were taken to select and analyze the relevant articles. Results. Of the 3912 articles identified through the electronic database search, 33 that met the inclusion criteria were included in the final analysis. The current study found that the global pooled prevalence of blood and body fluids among healthcare workers during career time and in the previous one year accounted for 56.6% (95% CI: 47.3, 65.4) and 39.0% (95% CI: 32.7, 45.7), respectively. Based on subgroup analysis by publication year, survey year, and World Health Organization regions, the highest prevalence of blood and body fluid exposure in the last 12 months was observed among articles published between 2004 and 2008 (66.3%), conducted between 2003 and 2008 (66.6%), and conducted in the Southeast Asia Region (46.9%). The highest career time prevalence was 60.6%, 71.0%, and 68.4% for articles published between 2015 and 2020, conducted between 2015 and 2019, and reported in the African region, respectively. Conclusion. The current study revealed a high prevalence of occupational exposure to blood and body fluids among healthcare workers and suggests the need to improve occupational health and safety services in healthcare systems globally.
Coupled Fixed Point Theorems in Topological Spaces with Size Function Topology
Authors: Sunyeekhan Gun
Published: June 2022

Regarding the concept of size function topology, this allows us to view the topological space

X

as a metric-like space. We prove the existence and uniqueness for a coupled fixed point of the map

F
:
X
×
X
⟶
X

satisfying some certain contractive conditions.
Resource Management and Optimization Method of Music Audio-Visual Archives under the Background of Big Data
Authors: Deng Chongbo
Published: June 2022

With the development of music and video, music and video management has been in a relatively backward state. This study uses the logistic regression algorithm based on sigmoid functions to analyze and process the music audio-visual library of a music software and establishes the logistic regression dynamic model, which provides a scientific research method for this complex system. The LPC characteristic coefficient is extracted, and then the logistic regression model of music audio-visual archives resources is established. After completing the model, this study obtains the logistic regression model through a series of experiments, which effectively optimizes the management of music audio-visual archives. The specific experimental conclusions are as follows: through genre classification and emotion classification, users can search more music audio-visual archives resources. The comparison shows that the recommendation effect after filtering by the logistic regression model is better than that of the nonstandard collaborative filtering recommendation system. Finally, after practical applications, it is concluded that the model based on the logistic regression algorithm has made a good optimization conclusion for the resource management of music audio-visual archives.
Immunotherapy and Antivascular Targeted Therapy in Patients’ Treatment with Concurrent Malignant Tumors after Organ Transplantation: Opportunity or Challenge
Authors: Shen Bairu , Guo Zi , Huang Peng , Tan Minghua , Zhang Xiaoshen , Lin Siyao , Song Changshan , Wang Jiaqing , Huang Minqian
Published: June 2022

Objective. To analyze the therapeutic effects and organ rejection of anti-PD-1 immunotherapy or antivascular targeting therapy on patients with combined malignancies after organ transplantation. Methods. We collected retrospective studies on “post-transplantation, cancer, immunotherapy, and vascular targeting therapy” in Embase, Wanfang database, Cochrane Library, VIP databases, CNKI, and PubMed, and the case data were organized and analyzed. Results. Data from only 40 papers met our requirements, which included 2 literature reviews, 4 original researches, and 34 case reports from 2016 to 2020. A total of 40 studies involving 66 patients were included, who were divided into 3 groups (patients using CTLA-4 inhibitors, group 1; patients who received sequential or concurrent anti-PD-1 and anti-CTLA-4 therapy, group 2; and patients using PD-1/PD-L1 inhibitors, group 3). There was no statistical difference in patients’ DCR between the three groups (

P
>
0.05

). Also, compared with group 2, there was no statistically significant difference in recipient organ rejection in group 1 and group 3 (

P
>
0.05

). The DCR rate for antivascular targeted therapy is approximately 60%. Conclusions. Immunotherapy should be carefully selected for patients with combined malignancies after organ transplantation. Antivascular targeted therapy is one of the options worth considering; the risk of side effects of drug therapy is something that needs to be closely monitored when combined with immunotherapy.
Cost-Sharing Mechanism of Water Pollution Control in Main and Subbasins Based on Stackelberg Game Model
Authors: Yang Yaohong , Liu Ying , Dai Jing , Zeng Yi
Published: June 2022

Faced with goal to improve ecological environment, water pollution treatment in river basins has been one of research focuses in recent years. Based on the basic characteristics of the river basins including main stream and multiple or multilevel tributaries, considering competitive relationship and cost-sharing mechanism of water pollution control, a differential game model of pollution elimination including main stream government and two tributary governments was constructed, and the equilibrium strategies under two situations of noncooperation mechanism and cost-sharing mechanism were discussed. The results show that Stackelberg game model based on cost-sharing mechanism can improve the pollution elimination effect and achieve Pareto improvement of the environment and economy. Then, through numerical analysis, influence of factors such as competition coefficient on pollutant elimination effect, tripartite effort, and optimal cost-sharing ratio were discussed. The results show that, in order to effectively reduce pollutant and improve environmental benefits, the greater pressure on tributary governments to develop the economy and the smaller degree of pollution treatment efforts, the more cost-sharing mechanism needed, and the higher main stream government’s cost-sharing proportion to the tributary government. When the pollution eliminating-quantity on unit effort of one tributary government increases, the revenue of main stream and tributary governments will increase; simultaneously, when the effort degree of the tributary government increases, the other decreases. The optimal cost-sharing proportions of main stream government to two tributaries are different which is influenced by many factors, and the influence rule presents stable monotonic increase or decrease. The research conclusions can provide reference for the governments to negotiate and determine cost-sharing mechanism.
A Review on Deep Sequential Models for Forecasting Time Series Data
Authors: Ahmed Dozdar Mahdi , Hassan Masoud Muhammed , Mstafa Ramadhan J.
Published: June 2022

Deep sequential (DS) models are extensively employed for forecasting time series data since the dawn of the deep learning era, and they provide forecasts for the values required in subsequent time steps. DS models, unlike other traditional statistical models for forecasting time series data, can learn hidden patterns in temporal sequences and have the memorizing data from prior time points. Given the widespread usage of deep sequential models in several domains, a comprehensive study describing their applications is necessary. This work presents a comprehensive review of contemporary deep learning time series models, their performance in diverse domains, and an investigation of the models that were employed in various applications. Three deep sequential models, namely, artificial neural network (ANN), long short-term memory (LSTM), and temporal-conventional neural network (TCNN) along with their applications for forecasting time series data, are elaborated. We showed a comprehensive comparison between such models in terms of application fields, model structure and activation functions, optimizers, and implementation, with a goal of learning more about the optimal model used. Furthermore, the challenges and perspectives of future development of deep sequential models are presented and discussed. We conclude that the LSTM model is widely employed, particularly in the form of a hybrid model, in which the most accurate predictions are made when the shape of hybrids is used as the model.
Construction of Cross-Cultural College English Teaching System Based on Computer Simulation Technology
Authors: Xiang Jiangshui
Published: June 2022

For a long time, college English instruction has emphasised language skills training and information transfer while neglecting to emphasise the development of cross-cultural communication skills. Theoretical study on cross-cultural communication ability, on the other hand, has grown in various dimensions and lacks empirical research methodologies. Meanwhile, in real teaching, a cross-cultural communicative competence training framework that is adequate for Chinese college English teaching practise and has a high degree of recognition and operability has yet to be constructed. This paper uses computer simulation technology to construct the teaching system of college English cross-cultural knowledge. At the same time, this paper proposes a cross-cultural communicative competence training model suitable for Chinese college English teaching based on the Chinese language communication environment and foreign language teaching environment. Finally, this paper constructs a cross-cultural university English teaching system model through computer simulation. Through teaching experiments, we can see that the system constructed in this paper has a certain effect.
Investigation on Reinforcement Effects of Nanocellulose on the Mechanical Properties, Water Absorption Capacity, Biodegradability, Optical Properties, and Thermal Stability of a Polyvinyl Alcohol Nanocomposite Film
Authors: Bacha Ebise Getacho , Demsash Hundessa Dessalegn , Shumi Lema Deme , Debesa Bune Erre
Published: June 2022

This paper presents the reinforcement of nanocellulose (NC) in polyvinyl alcohol (PVA) to examine the effect of the amount of reinforcement on the properties of PVA. The nanocellulose was successfully extracted by sulfuric acid hydrolysis method and ultrasonication, and successively reinforced with polyvinyl alcohol by the solvent-casting method. After incorporating nanocellulose into the PVA matrix, the effect of nanocellulose on the tensile strength, elongation at break, water absorption capacity, transmittance, thermal stability, and biodegradability of PVA was investigated. The tensile strength increased from

24.5
±
0.53
 
MPa

to

35.5
±
0.55
 
MPa

and

40.6
±
0.73
 
MPa

with the addition of 2%NC and 5%NC, respectively. The elongation at break increased from

40
±
0.53
%

to

45.7
±
0.53
%

with 2%NC, and after the reinforcement of 7%NC, it decreased to

32.2
±
0.75
%

. The water absorption capacity result reveals that neat PVA absorbs the highest amount of water which is

84.6
±
0.56
%

and is reduced to

73
±
0.78
%

by adding 2%NC. By increasing the nanocellulose loading to 7%, the water intake capacity was reduced to

61
±
0.59
%

which illustrates the water intake was reduced linearly with the increment of NC. The ultraviolet-visible (UV-Vis) result implies that the transmittance of neat PVA and PVA-2%NC composite film was 85.4% and 78.2% at 600 nm, respectively, which indicates the decrement in transmittance. The thermogravimetry analysis (TGA) reveals that the thermal stability of polyvinyl alcohol after incorporating nanocellulose particles was reduced. The weight loss of neat PVA is

70.7
±
1.7
%

after 90 days while the weight loss of the PVA composite films reinforced with 1%, 3%, 5%, 7%, and 9% was

65
±
1.85
%

,

57
±
1.57
%

,

55.6
±
0.64
%

,

52
±
1.73
%

, and

53.1
±
1.72
%

, respectively. The scanning electron microscopy micrograph for the PVA-6%NC nanocomposite film reveals a dispersion of nanocellulose in a matrix.