bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilization of Flex Controlled Robotics on Prosthetic Hand instead of Damaged Body Parts
Authors: Refaai Mohamad Reda A. , Elfasakhany Ashraf , Rajalakshmy P. , Chandra Saha Bikash , Prakaash A. S. , Basheer Dadapeer
Published: August 2022

Scientists have researched human anatomy and biology to produce human-like prosthetic hands. In the absence of a hand, prosthetics assist in reestablishing independence and confidence. Prosthetic hands are limited in functionality and cost. A low-cost anthropomorphic prosthetic hand was designed. With five independently operated fingers and powered thumb roll movement, the design is unlike anything else on the market. This research aims to provide a cheaper alternative to the market’s robotic prostheses. Inability to use limbs causes psychological and physical issues for amputees. Arduino, an open-source microprocessor, was used to build a prototype prosthetic hand. An Android app allows users to select a hand motion to circumvent myoelectric prosthesis control mechanisms. The Arduino uses this data to power servos that individually trigger each finger.
Study on Layered-Backfill-Based Water Protection Technology of Thick Coal Seam in the Ecologically Fragile Mining Area in Western China
Authors: Zhu Lei , Song Tianqi , Gu Wenzhe , Xu Kai , Liu Zhicheng , Qiu Fengqi , Zhang Xinfu
Published: August 2022

The mining areas in Western China are characterized by water shortage and ecological fragility, and the coal resources in these areas are extracted in a large-scale and highly intensive manner, which is highly likely to induce ecological problems, such as soil erosion and grassland degradation. In addition, there is a secondary protection zone of Hongshixia water source near Guojiatan minefield. If the water resources loss of Salawusu Formation is too large, it will affect the normal water supply of Yulin city. To reasonably coordinate coal exploitation and water protection, the development characteristics of water-conducted fissures with different backfill ratios are obtained in combination with theoretical analysis, field test, and numerical modelling. The panel layout of the layered-backfill-based water protection working face and the parallel operation of mining and backfilling are designed, and a feedback regulation system integrating hydrological monitoring and backfill ratios is established, which assists in evaluating the effectiveness of water protection. The results indicated that when the slicing mining method was adopted with the roof naturally caving, the maximum development height of the water conducted fracture zone was 220.0 m (developed to the Yan’an Formation), and the water conducted fracture zone could only develop to the Yan’an Formation without crossing the Zhiluo Formation when the backfill ratio reached 80%. The water emission rates in the west of the field testing area reduced from 334.95 m3/h to 60.60 m3/h, dropping by 86.86%. Compared to the scene prior to the layered backfill mining, the shallow water outflow was reduced by 72.74 m3/h, and it helped annually reduce the shallow water loss of 637200 m3, which was equivalent to 1.74% of the actual water supply to Yunli city every year. The results of this study can provide guidance on effectively avoiding the loss of shallow water resources that are regarded as indispensable sources of domestic water.
Feasibility Study of Mass Sports Fitness Program Based on Neural Network Algorithm
Authors: Li Jian , Wu Yejin
Published: August 2022

Mass sports has become a world trend, setting off a new health revolution in the world. Mass fitness programs not only enrich people's lives. It not only relieves the psychological pressure of modern people but also promotes people's health and improves people's quality of life. According to the time-consuming stability of neural network algorithm, this paper proposes a sports video recognition algorithm based on BP neural network. The static and dynamic features are classified by BP neural network, and the basic probability assignment is constructed according to the preliminary recognition results. At the same time, we use evidence theory to fuse the preliminary results and get the results of motion video recognition. It can be applied to the generation model of the feasible scheme of mass sports fitness. Relevant experiments show that the whole model that generates the feasible mass sports fitness scheme can accurately generate the sports fitness scheme of multiple patient users and ensure the rationality and safety of the sports fitness scheme.
Adjuvant Application of Shenmai Injection for Sepsis: A Systematic Review and Meta-Analysis
Authors: Sun Ye , Liu Yilin , Li Li , Xue Bing , Cao Yan
Published: August 2022

Objective. To compare the efficacy and safety of Shenmai injection plus regular treatment versus regular treatment alone in the treatment of sepsis. Methods. Review Manager 5.3 was used. Databases including PubMed, Cochrane Library, Wan-FANG, VIP, CNKI, and CBM were searched for the relative control and randomized studies till June 2022. Primary outcomes were 28-day mortality; case fatality rate; APACHE II score; and levels of procalcitonin, tumor necrosis factor-α, interleukin-6, and C-reaction protein. Secondary outcomes were measurements related to inflammatory reactions, coagulation function, immune function, and organ function. Results. In total 21 studies with 1469 patients were included. Shenmai injection plus regular treatment of sepsis significantly decreased 28-day mortality rate (odds ratio: 0.36 (0.20, 0.63);

p
=
0.0004

) and case fatality rate (odds ratio: 0.32 (0.19, 0.54),

p
<
0.0001

) and significantly further reduced APACHE II score (standard mean deviation: −1.14 (−1.30, 0.99);

p
<
0.00001

). Procalcitonin reduction was similar in the two groups (standard mean deviation: −0.59 (−1.64, 0.46);

p
=
0.27

). Tumor necrosis factor-α (standard mean deviation: −1.96 (−2.79, −1.13);

p
<
0.00001

), interleukin-6 (standard mean deviation: −1.52 (−2.13, −0.91);

p
<
0.00001

), and C-reaction protein (standard mean deviation: −2.37 (−4.26, −0.49);

p
=
0.01

) levels were significantly further decreased in the Shenmai injection group. Most of the measurements related to inflammatory reaction, coagulation function, immune function, and organ function were significantly regulated in the Shenmai injection group. Furthermore, there was no adverse event, and two study groups had similar adverse event rates. Conclusion. Shenmai injection as adjuvant therapy shall be effective and safe in the treatment of sepsis. However, further investigation is still warranted especially regarding safety. Adjuvant application of Shenmai injection in sepsis is worth further investigation.
Abnormal User Detection via Multiview Graph Clustering in the Mobile e-Commerce Network
Authors: Du HangYuan , Li Duo , Wang WenJian
Published: August 2022

In recent years, Internet of Things has not only promoted the continuous development of e-commerce transaction but also brought loop-hole to the fraud gangs who always utilize mobile devices to commit fraud crimes. For example, fraud gangs are usually organized to purchase commodities at low prices in e-commerce promotions. They benefit from the price spread by reselling commodities at high prices. In the past few years, the transaction fraud caused serious financial losses to merchants in e-commerce platform. To detect the fraudulent user and behavior effectively, a multiview graph clustering-based abnormal detection model is developed in this paper. In the proposed model, two fraudulent behavior patterns are proposed by abstracting the e-commerce network as a heterogeneous information graph. On this basis, two user-similarity graphs are reorganized from the heterogeneous graph with the help of different metapaths. Subsequently, in order to capture the corresponding fraudulent behavior patterns, the above two graphs are encoded into user embeddings and assigned to specific clusters in respective views. Finally, the consensus detection result is produced by fusing the complementary information of different views in a joint multiview learning framework. As we know, our work is the first one that uses multiview graph clustering in e-commerce fraud detection, which will provide a new research perspective for fraud detection in e-commerce platform. Extensive experiments are conducted on real and semisynthetic datasets, and the results demonstrate the effectiveness and superiority of the proposed model.
[Retracted] Study on Various Luteal Characteristics Using Doppler Ultrasonography for Early Pregnancy Diagnosis in Nili‐Ravi Buffaloes
Authors: Riaz Umair , Hassan Mubbashar , Khan Muhammad I. , Farooq Umer , Ali Farah , Mehmood Khalid , Shaukat Aftab , Lashari Mushtaq H. , Yang Liguo
Published: August 2022

The objective of current study was to assess the trend in various luteal characteristics viz luteal size (LS), plasma progesterone (P4) concentration, and luteal blood flow (LBF) using color Doppler imaging (CDI) and power Doppler imaging (PDI) modes in pregnant and nonpregnant Nili‐Ravi buffaloes. Lactating, cyclic, and healthy Nili‐Ravi buffaloes (n = 09) without any reproductive abnormality were selected in present study. Buffaloes were synchronized using Ov‐Synch, and fixed‐time artificially insemination was performed (day = 0). Pregnancy was diagnosed on 30‐day post‐AI using B‐mode ultrasonography based on presence or absence of embryonic heartbeat. Ovaries of all animals were scanned from day 5 till 21 post‐AI using both B‐mode and Doppler ultrasonography to measure LS and LBF. After each ovarian ultrasound examination, blood samples were collected via jugular venipuncture to determine plasma P4 concentration. According to results, LBF using CDI and PDI was significantly higher (P ≤ 0.05) in pregnant buffaloes on days 13 and 15 post‐AI, respectively. The mean LS and plasma P4 concentration did not differ (P ≥ 0.05) between pregnant and nonpregnant animals until day 15 post‐AI. However, a significant difference (P ≤ 0.05) was noticed for both on day 17 and onwards. It is concluded that LBF is a more sensitive luteal character as compared to LS and P4 for earlier pregnancy diagnosis in Nili‐Ravi buffaloes when ascertained through CDI.
Association between XRCC3 rs861539 Polymorphism and the Risk of Ovarian Cancer: Meta‐Analysis and Trial Sequential Analysis
Authors: Hu Siya , Jing Yunnan , Liu Fangyuan , Han Fengjuan
Published: August 2022

Background. Current studies on the relationship between XRCC3 rs861539 polymorphism and ovarian cancer risk have been inconsistent. Therefore, we performed a meta‐analysis to explore their association. Methods. Six electronic databases (PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and China Wanfang Database) were searched for relevant studies published before December 2021. Meta‐analysis, subgroup analysis, sensitivity analysis, and publication bias analysis were performed using Stata software 16.0. Trial sequential analysis (TSA) was performed using TSA 0.9.5.10 Beta software. Results. A total of 12 studies were included in 9 literatures, comprising 4,634 cases of ovarian cancer and 7,381 controls. After Bonferroni correction, the meta‐analysis showed an association between XRCC3 rs861539 polymorphism and ovarian cancer risk in the heterozygote model and the dominant model (GA vs. GG: OR = 0.88, 95%CI = 0.81‐0.96, P = 0.003; GG vs. GA+AA: OR = 0.89, 95%CI = 0.82‐0.96, P = 0.004). In an ethnically stratified subgroup analysis, XRCC3 rs861539 was shown to reduce the risk of ovarian cancer in Caucasian in the heterozygote model and the dominant model (GA vs. GG: OR = 0.88, 95%CI = 0.81‐0.96, P = 0.004; GG vs. GA+AA: OR = 0.88, 95%CI = 0.81‐0.96, P = 0.004). In the control source and detection method stratified subgroup analysis, hospital‐based studies and PCR‐RFLP‐based studies were found to increase ovarian cancer risk (GG vs. AA: OR = 1.30, 95%CI = 1.05‐1.62, P = 0.016; GG vs. AA: OR = 1.31, 95%CI = 1.06‐1.62, P = 0.013). Conclusion. This meta‐analysis showed a significant association between XRCC3 rs861539 polymorphism and ovarian cancer risk, especially in Caucasians. Large‐scale multicenter case‐control studies in more different regions will be needed in the future.
Algorithm Model Design of the Aging Transformation Scheme of Computer Intelligent Aided Technology under the Background of Rural Revitalization
Authors: Pan Yan
Published: August 2022

The study is to improve the living environment of the elderly in rural areas, improve the quality of life and well-being of the elderly, and ensure the living environment of the elderly while promoting rural revitalization and development under the policy background of rural revitalization, this study optimizes the aging transformation scheme by integrating computer intelligent auxiliary technology, and analyzes and compares the algorithm model design of the aging transformation scheme through the algorithms of the traditional transformation scheme and computer intelligent auxiliary technology. The results show that compared with the transformation scheme of the traditional algorithm, the transformation scheme after using computer intelligent auxiliary technology has higher accuracy and coupling for the aging transformation scheme, and has a better effect on improving rural development, beautiful rural construction, and improving the life of rural residents.
[Retracted] The Protective Effect of Interval Exercise on Myocardial Ischemia‐Reperfusion Injury in Players
Authors: Wang Wei
Published: August 2022

In recent years, the popularity of sports has been increasing. In the high‐intensity competition, many players have been injured; most of them are myocardial ischemia. With the development of medical science and technology, myocardial ischemia can be reperfusion. However, sometimes, the function of tissues and organs cannot be restored, but the dysfunction and structural damage of tissues and organs can be aggravated. Therefore, it is necessary to actively carry out intermittent exercise to protect players from myocardial ischemia‐reperfusion injury. The purpose of this paper is to explore the protective effect of intermittent exercise on the myocardial ischemia‐reperfusion injury of players. 60 clean male Sprague Dawley (SD) old rats were selected as the research objects, which were divided into control group, ischemia/reperfusion model group, intermittent exercise + model group, and intermittent exercise + control group, and compared the parameters of heart function indexes of each group. The results showed that the creatine kinase (CK) content of control group was 0.577 ± 0.176 u/ml, lactate dehydrogenase (LDH) content was 7.834 ± 1.507 u/ml, model group was 1.257 ± 0.113 u/ml, lactate dehydrogenase (LDH) content was 14.441 ± 1.793 u/ml, intermittent exercise + model group was 0.987 ± 0.127 u/ml, lactate dehydrogenase (LDH) content was 11.714 ± 3.017 u/ml, intermittent exercise + control group was 1.103 ± 0.125 u/ml, and lactate dehydrogenase (LDH) content was 14.647 ± 2.575 u/ml. It can be seen that intermittent exercise has a good protective effect on myocardial ischemia‐reperfusion injury. If the interval exercise method is integrated into the daily training of athletes, it can effectively improve the perfusion injury caused by myocardial ischemia.
Design and Development of Fixed-Frequency Double-Integral SM-Controlled Solar-Integrated Bidirectional Quasi Z-Source DC-DC Converter in Standalone Battery Connected System
Authors: Battula Santhoshkumar , Panda Anup Kumar , Garg Man Mohan
Published: August 2022

DC microgrids have been quite popular in recent times. The operational challenges like control and energy management of the renewable-driven standalone DC microgrids have been an interest of research. This paper presents a bidirectional quasi Z-source DC-DC converter (BQZSDC). This converter topology has been developed based on a conventional buck-boost type bidirectional converter, and it interfaces the storage system and the common DC bus. The challenge, however, lies in effectively managing the uncertain renewable energy sources and the storage system and catering for the loads simultaneously. An effective control strategy is needed for that energy management and to achieve various microgrid objectives. This paper deals with one such effective control strategy implemented for BQZSDC. That is, the fixed-frequency double-integral sliding mode control (FF-DISMC) controls the converter to regulate the DC bus voltage and battery current. A detailed analysis of the controller is conducted, and its performance is evaluated for both charging (buck) and discharging (boost) modes. Simulations have been performed in MATLAB, showing that the controller performs satisfactorily in achieving the objectives of voltage regulation and battery current regulation. Finally, the performance of the proposed controller is validated with the hardware setup.
[Retracted] Comprehensive and Integrated Analysis Identifies ZEB1 as a Key Novel Gene in Oral Squamous Cell Carcinoma
Authors: Ma Jie , Yao Yu , Tao De-tao , Yin Jia-yi , Chen Liang , Cui Yong , Wang Ying , Hu Cong-lin , Tian Ming-xing , Wang Qiong
Published: August 2022

Oral squamous cell carcinoma (OSCC) is the most common head and neck cancer with a poor prognosis. Therefore, it is crucial to explore molecular prognostic biomarkers for OSCC. ZEB1 (also known as δEF1) is a member of the zinc finger E‐box binding protein family of transcription factors involved in various biological processes, including tumorigenesis, progression, and metastasis. Recent evidence suggests that ZEB1 has a role in the tumorigenicity of oral epithelial cells, although its mode of action needs to be investigated further. To better understand the relationship between ZEB1 and OSCC, we transfected the ZEB1‐overexpressing oral squamous cell lines SCC9 and SCC25 with lentivirus and then extracted RNA from the cells for gene expression analysis. Furthermore, the GSE30784 dataset was downloaded from the Gene Expression Omnibus (GEO) database to identify potential biomarkers of OSCC and to assess the potential mechanisms. The criteria for identification of their DEGs were |logFC| > 1 and P < 0.05. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were also carried out. Integrating the data from the PPI network and survival analysis identified that ZEB1 might be an independent prognostic biomarker in OSCC. In conclusion, integrated bioinformatics and microarray analysis identified the critical gene ZEB1 linked to the overall survival (OS) of patients with OSCC. ZEB1 could be applied as a prognostic biomarker to forecast the survival of patients with OSCC and might indicate innovative therapeutic indicators for OSCC.
Effect of Roxadustat on Factors Associated with Renal Fibrosis and Efficacy
Authors: Zheng Fangfang , Zhang Peng , Zhao Mingzuo , Wang Jinna , Xu Xiaohong , Zhang Chi , Zhang Li
Published: August 2022

Objective. We investigated the effect of roxadustat on factors associated with renal fibrosis and efficacy. Methods. Sixty patients meeting the inclusion criteria between January 2021 and October 2021 were equally distributed into observation (roxadustat) group and control (Erythropoietin) group. Then, the expression of serum hypoxia-inducible factor 1-alpha (HIF-1α), transforming growth factor-β (TGF-β1), vascular endothelial growth factor (VEGF), fibronectin (FN), and collagen Ⅳ (C-IV) was compared at different time points (baseline, 2-week follow-up, and 4-week follow-up). The improvement degree of hemoglobin (Hb) and the change level of iron parameters and hepcidin were also compared between the two groups. Results. In the roxadustat group, the expression of HIF-1α at 2 weeks was significantly higher than the baseline and approached the baseline value at 4 weeks. At 4 weeks, TGF-β1 and FN expression was significantly lower than baseline. In addition, the improvement of Hb in the roxadustat group was significantly higher than that in the control group at 4 weeks, and the change of ferritin, transferrin, and hepcidin indexes from baseline was better than in the control group. Conclusion. After giving roxadustat, it can change the expression of HIF-1α, TGF-β1, and FN. Its efficacy is superior to EPO, which is worthy of clinical application.
A Study on Exploring the Path of Psychology and Civics Teaching Reform in Universities Based on Artificial Intelligence
Authors: Han Liang , Gong Jijuan
Published: August 2022

The development of precise teaching of civics with artificial intelligence not only is the realistic need of the development of the times and technological innovation but also provides a new picture to solve the problem of the relevance of civics, so it is the inevitable requirement for the quality and efficiency of civics teaching. Curriculum Civics is an important support for the cultivation of innovation ability of college students. To effectively identify the state categories of college students’ psychology and civics and to fully consider the emotional factors between teachers and college students, this paper proposes a psychological civics teaching model based on graphical convolutional neural network. First, the dialog texts of psychology and civics teaching between teachers and students are coded in sequence context using Bi-GRU to obtain discourse text representations; then, a directed graph is constructed based on the order of the dialog between teachers and students in psychology and civics teaching, and a new text representation vector for each discourse text is obtained using graph convolutional neural network; finally, the two discourse representation vectors obtained are connected, and a similarity-based attention mechanism is used. Finally, the final discourse text representation is obtained using an attention-based mechanism to perform psychological and ideological state. The proposed method is conducive to the implementation of the teaching practice exploration of organic integration of ideals and beliefs with the cultivation of innovation ability in colleges and universities.
Performance evaluation of agricultural financial funds based on smart big data analysis
Authors: Kuang Min
Published: August 2022

This paper attempts to build a performance evaluation system for agricultural financial project expenditures to make the performance evaluation of financial support for agriculture more maneuverable and provide a reference for the management of agricultural funds. Moreover, this paper combines the intelligent big data technology to construct the agricultural financial fund performance evaluation system, and describes the characteristics of the relevance of geographic elements in the entire spatial region through global spatial autocorrelation. Simultaneously, this paper uses different spatial weight matrices to examine the rationality and robustness of the results. In addition, this paper introduces covariates and removes trends through regression methods. Further, taking into account the characteristics, scientificity and operability of agricultural financial funds, the dimensions and structure of the performance evaluation of agricultural financial expenditures are drawn up. Finally, this paper verifies the effectiveness of this method through case studies, and gives several targeted suggestions.
On English Courses and Teaching Strategies in Compound Application-Oriented Talents Training Based on the Education Ideas of CDIO in the Construction of Smart Cities
Authors: Xie Zhengyan
Published: August 2022

To improve the level of English education in China and promote the cultivation of compound application-oriented talents in colleges and universities, this research integrates the concept of conceive design implement operate (CDIO) into college English education. First, the CDIO educational concept is introduced in detail. Second, the moth-flame optimization (MFO) algorithm and the support vector machine (SVM) model by the MFO algorithm are presented, and they are applied to teaching evaluation, and then the teaching plan is proposed by the CDIO concept. The teaching evaluation model is applied to the English teaching of students in class A with ordinary learning levels in a university in Hengyang City. The implementation method of the teaching plan is explained in detail by taking “Unit 2 Charlie Chaplin” in the textbook “New Horizons College English” as an example. Finally, the accuracy of the MFO-SVM model for teaching evaluation is verified by simulation analysis, and the corresponding teaching strategies are summarized through teaching evaluation and customization of teaching plans. The experimental results reveal that the MFO-SVM model has an accuracy of 96.43% in teaching evaluation, while the extreme learning machine (ELM), SVM, and back propagation neural network (BPNN) models have an accuracy of 92.27%, 90.45%, and 86.36%, respectively in the evaluation results of the teaching quality. The summarized teaching strategies are mainly divided into four parts, namely, autonomous learning, project-based teaching, dynamic generation and information feedback, and production teaching. This research has a certain reference for the current reform of English education in China and the cultivation of compound application-oriented talents.
Repeated Low‐Dose Streptozotocin and Alloxan Induced Long‐Term and Stable Type 1 Diabetes Model in Beagle Dogs
Authors: Han Qingyue , Sun Jie , Xie Wenting , Bai Yuman , Wang Shuzhou , Huang Jianjia , Zhou Shuilian , Li Quanwei , Zhang Hui , Tang Zhaoxin
Published: August 2022

Type 1 diabetes mellitus (T1DM) is a chronic disease represented by insulin‐causing pancreatic β‐cell disruption and hyperglycemia. Therefore, it is necessary to establish a variety of animal models of diabetes to study the pathogenesis and pathophysiology of it. However, there are few reports on the use of beagle dogs to establish an animal model of type 1 diabetes. This study aimed to explore a simple and feasible modeling method to establish a long‐term and stable type 1 diabetes model in beagle dogs. Forty adult beagle dogs were randomly divided into control group and model group. After 24 h of fasting, streptozotocin (20 mg/kg) and alloxan (20 mg/kg) were injected through the cephalic vein. The second intravenous injection was given on the 4th day after the first injection. Insulin release testing was performed on the 7th day after the last intravenous injection. Fasting blood glucose and body weight were recorded monthly. Four months after the last injection, the serum fructosamine content and the ratio of glycated hemoglobin were detected. Then, the pancreatic tissue was harvested for histopathological examination. The results showed that the level of fasting blood glucose of the 16 dogs in the model group was consistently higher than 11.1 mmol/L for 4 consecutive months. Moreover, compared with the control group, the insulin release curve of the model group was flat with no increase. The body weight of the model group was significantly reduced, and the ratios of blood glucose, fructosamine, and glycosylated hemoglobin were significantly higher than those in the control group. Meanwhile, histopathological examination of the pancreas showed that the islet beta cells appeared to have vacuoles or even necrosis. In the model group, pancreatic β‐cells were damaged and insulin release was reduced. These results suggest that the above modeling methods can induce long‐term and stable type 1 diabetes models in beagle dogs.
Minimum Flexural Reinforcement Steel Ratios of High‐Strength Concrete Beams
Authors: Salih Ameer M. , Mohammed Azad A.
Published: August 2022

Considering that most studies depend on theoretical equations to determine the minimum reinforcement ratio, only a few studies on this ratio are available. Therefore, a more defined limit should be suggested to design codes by performing additional investigations and experimental studies on this limit. This study examines the behavior of high‐strength concrete (HSC) beams with low reinforcing steel ratios to establish a limit for the lowest flexural reinforcement ratio that will ensure ductility. Experiments were performed on 12 reinforced HSC beams with a concrete compressive strength of 99 MPa, which were divided into three categories depending on their size. Each category comprised four beam reinforcement ratios (0%, 0.13%, 0.33%, and 0.65%), and two main parameters (beam size and reinforcement ratio) were investigated. Furthermore, to ensure flexural failure at the middle‐span, adequate web reinforcing was used in all the beams and tested under a four‐point load until they exhibited failure. Based on regression analysis, an equation was proposed for the rupture modulus of reinforced beams. The findings suggest that, in addition to the yielding strength of the reinforcements and the compressive strength of the concrete, the depth of the beams should be considered when computing the minimum flexural reinforcement of beams.
Jellyfish Collagen Hydrolysate Alleviates Inflammation and Oxidative Stress and Improves Gut Microbe Composition in High-Fat Diet-Fed Mice
Authors: Lv Zhe , Zhang Chongyang , Song Wei , Chen Qingsong , Wang Yaohui
Published: August 2022

The collagen from jellyfish has many beneficial effects, including antioxidant, anti-inflammatory and immune-modulatory activities. However, whether jellyfish collagen hydrolysate (JCH) has any effects on high-fat diet-induced obesity remains unknown. Consequently, we in the present study orally administrated JCH in high-fat diet-fed mice to explore its effects on body weight gain, inflammatory and oxidative status, and cecum microbe composition. The results showed that oral administration of JCH prevented the body weight gain in high-fat diet-treated mice. Meanwhile, glucose, triglycerides, and total cholesterol level in serum were maintained by JCH administration. Furthermore, JCH administration alleviated oxidative stress by increasing the GSH content and decreasing the level reactive oxygen species in the liver and improved inflammatory response by decreasing the expression of TNF-α, IL-1β, and IL-8 gene in the liver and ileum. Importantly, JCH administration helps recover the alteration of microbiota composition induced by high-fat diet, and the genus Romboutsia may critically involve in the beneficial effects of JCH administration. In conclusion, our results indicated that JCH could be potentially used for the prevention and treatment of diet-induced obesity.
Nasolabial Ulcerated Placard Revealing a Primary Cutaneous Aggressive Epidermotropic CD8+ T-cell Lymphoma
Authors: Ntihebuwayo J. B. , Hali F. , Kerouach A. , Rachadi H. , Chiheb S. , Marnissi F.
Published: August 2022

Primary cutaneous aggressive epidermotropic CD8+ T-cell lymphoma is a rare entity representing less than 1% of cutaneous lymphomas. It has an aggressive clinical manifestation with a poor prognosis. It is characterized by cytotoxic and epidermotropic CD8+ proliferation. It also expresses the TIA-1 marker. We report a new case for its display and aggressive character, diagnostic difficulty, and good therapeutic response to chemotherapy. This is a 62-year-old female patient admitted to the hospital for a nasolabial ulcerated placard evolving for two years. Clinical examination revealed submandibular lymph nodes. The specimen analysis associated with anatomoclinical manifestation was concluded for a primary cutaneous aggressive epidermotropic CD8+ T-cell lymphoma. Tumor extent assessment did not show any secondary localization. The blood tests and serology were unremarkable. The patient had benefited from a CHOEP-type multidrug therapy protocol with complete healing of the lesion after three courses of chemotherapy.
[Retracted] Influence of Oxytocin Usage and Dose Difference During Delivery on Pregnancy Outcome of VBAC Pregnant Women
Authors: Yuan Zhuo , Hu Lei , Li Wanying , Zhou Shuo , Zhu Nana , Lv Qi
Published: August 2022

In order to explore the influence of oxytocin usage and dose difference during delivery on the pregnancy outcome of VBAC pregnant women, the clinical data of 166 VBAC pregnant women from January 2017 to March 2020 are retrospectively analyzed. All women are divided into different groups according to the usage of oxytocin during delivery and the oxytocin dose difference. Binary logistic regression is used to analyze the factors affecting the pregnancy outcome of pregnant women with VBAC. The gestational weeks and the thickness of the lower uterine segment in the oxytocin group are significantly more than those in the nonoxytocin group (P < 0.05). The time of the first stage of labor, second stage of labor, and total stage of labor in the oxytocin group are significantly longer than the nonoxytocin group (P < 0.05). The proportion of entering NICU in the oxytocin group is significantly lower than the nonoxytocin group (P < 0.05). There is no significant difference in labor duration and pregnancy outcome between low‐dose and medium‐dose oxytocin groups. Binary logistic regression analysis shows that prenatal BMI <30 kg/cm2, gestational age ≤40 weeks, history of vaginal delivery, uterine expansion, and admission to hospital are the influencing factors for pregnancy success of pregnant women with VBAC. The usage of oxytocin in VBAC pregnant women during delivery may increase the duration of labor. For those with poor uterine contraction, oxytocin can be increased to 4∼18 mU/min to speed up the labor process, without increasing the risk of adverse pregnancy outcomes.
Recent Advances on Electroconductive Hydrogels Used in Heart Repair and Regeneration
Authors: Yan Xu , Sun Huan , Yang Ping
Published: August 2022

Myocardial infarction (MI) permanently damages cardiac tissue. Tissue engineering exhibits tremendous potential as a strategy for developing engineered tissue to repair congenital abnormalities in the heart and/or cardiovascular tissue. Electroconductive hydrogels (EHs) are prepared from synthetic or natural biodegradable polymers and conductive components that could partially restore the myocardial/ventricular electromechanical coupling and synchronized heartbeats. Also, EHs are ideal materials for the preparation of cell culture and induction carriers, engineered scaffolds, and patches, as well as cell and gene delivery carriers, all of which aid in tissue formation. Except for a brief introduction to the classification and synthesis of EHs, this review discussed the recent progress and challenges of EHs applied in cardiac repair and regeneration to provide a reference for the further application of EHs in treating cardiovascular diseases. Figure abstract: the EHs categorization and the potential application of heart repair and regeneration in this review.
Study on Activation Behavior of Complex Fracture Network in Weak-Planar Rock
Authors: Chen Jin , Ran Lingbo , Zhou Peiyao , Chen Wenbin , Tang Meirong , Wang Qiang
Published: August 2022

Aiming at the problem of quantifying the composition of complex fracture network and fracture activation after fracturing, a complex fracture network model of weak plane with prefabricated structure is established based on finite element method, global embedded cohesive zone model (CZM), and real shale outcrop. Considering the influence of fully coupled stress/fluid, the effects of weak plane azimuth, horizontal stress difference, fracturing fluid viscosity, and injection rate on fracture network composition, geometry, and stimulated reservoir volume (SRV) are studied. The concept of fracture relative activation rate, which can quantitatively analyze fracture network composition and fracture activation, is proposed. The results show that the fracture geometry of the two kinds of conjugated shale after fracturing is controlled by the most weak mechanical plane, and the fracture network is, respectively, axisymmetric and centrosymmetric. The fracture network is composed of the weak plane fractures with the dominant free gas transport and the matrix microfractures with the dominant adsorbed gas transport. The effects of weak plane azimuth, horizontal stress difference, and fracturing fluid viscosity on SRV length are not monotonous, while the increase of the azimuth, horizontal stress difference, fracturing fluid viscosity, and the reduction of appropriate injection rate will lead to the increase of SRV width. The effect of horizontal stress difference on the relative activation rate of fractures does not change monotonically, while the increase of weak plane azimuth, fracturing fluid viscosity, and injection rate will lead to the increase of the relative activation rate of matrix microfractures, the increase of the total length of activated fractures, and the decrease of the relative activation rate of weak plane fractures.
Morphological Variations of the Posterior Superior Iliac Spine in Chinese Population: Potential Effects on the Reliability of Palpation
Authors: Qi Ji , Li Jing , Wang Haizhou , Ping Ruiyue , Li Yikai , Chen Haiyun , Zhan Jiheng , Chen Ping , Yang Bing , Yu Xiubing , Zhang Qing , Lin Dingkun
Published: August 2022

Objectives. The posterior superior iliac spine (PSIS) is an important anatomical landmark often involved in spinal manipulation and surgical bone harvest. Hence, knowledge of variations in the PSIS may be predictive and valuable in clinical settings. Taking the complex morphology into account, the study is aimed at proposing a classification of PSIS in the Chinese population. Methods. An anatomical study was undertaken on 288 human ilia. First, the morphological features of variations in the PSIS were noted following visual inspection. Then, 12 variable anatomical parameters were measured in order to determine the differences based on morphology, side, and sex. Results. Overall, four types of PSIS were found among 288 bones, including type I “V‐shape” (106, 36.8%), type II “U‐shape” (121, 42.0%), type III “W‐shape” (36, 12.5%), and type IV “ossification‐shape” (25, 8.7%). There were no significant sex or bilateral differences in the morphological distribution of the PSIS (p > 0.05). Furthermore, the measurements showed that type I was the narrowest and type III the broadest (p < 0.05). Moreover, female specimens had an overall larger distance and width of surrounding landmarks (p < 0.05), and a significant difference was found in the width of the PSIS between the left and right sides (p < 0.05). Conclusion. The PSIS samples displayed multiple morphological variations and could be classified into four types. In addition, sex‐based or bilateral differences existed in the size and relative positions. It is thus likely that differences in the morphology and asymmetry of the PSIS provide references for palpation, bone harvest, and other clinical settings.
Quality Evaluation and Satisfaction Analysis of Online Learning of College Students Based on Artificial Intelligence
Authors: Yun Shangzi , Bai Yongfeng , Jongnam Baek
Published: August 2022

In order to better study the quality and satisfaction of online learning of college students, this paper analyzes and researches online learning of college students based on relevant theories of artificial intelligence. Through the traditional machine learning method to evaluate the quality of online learning, the deep learning theory is applied to the satisfaction analysis of college students'’ online learning. The results show that different statistical indexes have different influences on traditional machine learning, but they all show a gradually decreasing trend. The main reason for the different degrees of influence is that the emphasis of different statistical indexes is different, and the order from large to small is MAE > RMSE > MAPE > TIC. Statistical indicators can better describe the first stage of test data, while the corresponding quality indicators can better characterize the second stage of test data. It indicates that statistical and quality indexes should be considered comprehensively to analyze the test data accurately. The increase of evaluation indexes based on traditional machine learning can improve the evaluation indexes of online learning quality of college students. And the improvement of statistical indicators and evaluation factors can promote the accuracy of online learning quality evaluation of college students. Based on the theory of artificial intelligence, the quality and satisfaction of online learning of college students are analyzed and evaluated by using the traditional machine learning method and deep learning method, respectively. Relevant research can provide a research basis for artificial intelligence in online learning methods of college students.
Power Metering Automation System Based on Internet of Things
Authors: Dai Xiangrong
Published: August 2022

In order to solve the problems of poor stability and low operation efficiency of the traditional power marketing metering production automatic scheduling system, this paper proposes a power metering automation system based on the Internet of Things. In this paper, the hardware and software of the system are designed under the environment of the Internet of Things. The hardware part is mainly divided into three platforms: basic resource layer, platform business layer, and interface presentation layer. The normal operation is realized through the network topology, and the load balancing server and business subsystem are emphatically designed. The software is completed in four steps: coding, scheduling, backup, and display. The experimental results show that the integrity rate of the electric quantity data collected by this system in the experiment with the traditional system is as high as 99%. Compared with the traditional dispatching system, the power information dispatching system designed under the Internet of Things has better stability and higher operation efficiency.
Copyright Protection and Data Reliability of AI-Written Literary Creations in Smart City
Authors: Wei Chenlin
Published: August 2022

The purpose is to solve copyright disputes over artificial intelligence (AI)-written literary creations and protect copyright by legislation through data reliability research. Accordingly, this work makes a detailed study of the criteria for the copyright protection of AI-written literary creation and the creation process. It constructs the model of swarm intelligence (SI) perception. Then, the Preservation Trustworthiness Incentives Sense (PTISense) scheme is designed based on the encryption algorithm for the SI perception model. The performance of the proposed PTISense scheme is verified and analyzed through experiments. Mainly, it analyzes the impact of PTISense on the accuracy of the reputation model, its robustness against malicious users, and the actual feasibility. The results show that when users complete 50 tasks, the false-positive rate is only 0.1, and the corresponding false-negative rate approximates 0. After each task, the user reputation will be updated, and the data will be evaluated for trust. The trust model of the proposed PTISense scheme based on encryption technology is more accurate. When η (the number of malicious users) is small, the more tasks are performed, the faster the reputation value decreases and tends to zero. The proposed PTISense scheme-based reputation evaluation model can better protect the data submitted by good users. It is robust against malicious users and protects the data and privacy of good users. Further, entities’ computing overhead in different SI perception stages is calculated. It is found that the proposed PTISense scheme is feasible for user data privacy protection. Compared with other schemes, it can achieve a safe and reliable SI perception process with a lower computing overhead. It can better ensure the authenticity and reliability of data.
Establishment of a Big Data Monitoring Platform for Cinema Opening in the Postepidemic Era from the Perspective of Public Health
Authors: Wei Qi , Zhao Nan
Published: August 2022

The emergence of COVID‐19 has had a huge impact on people’s lives around the world. With the vaccine and the effective policies of the government, the spread of the epidemic has been effectively contained. However, in the postepidemic era, public health and epidemic protection policies have forced the transformation of public places such as movie theaters. The cinema box office monitored by the traditional monitoring platform can no longer effectively reflect the opening of the transformed cinema. To make up for the shortcomings of the traditional monitoring platform, considering the large amount of data generated by the cinemas’ online and offline platforms and public place codes, this study establishes an intelligent monitoring platform based on big data technology to monitor the opening of cinemas. The established intelligent monitoring platform can fully extract the feature information contained in numerous data collected from cinemas and output quantitative indicators that characterize the opening of cinemas based on the feature information. The performance of the established intelligent monitoring platform is analyzed through a case study. The research results show that the average relative error between the cinema opening indicators predicted by the intelligent monitoring platform and the real results is within 2%, which indicates that the intelligent monitoring platform has good prediction accuracy. In addition, the statistical analysis results show that the linear correlation coefficient between the predicted and real results is 0.9802 > 0.95, which further indicates the feasibility of the established intelligent monitoring platform to monitor the opening of cinemas in the postepidemic era.
Research on Kinetic Energy Recovery of Energy Vehicle ABS Solenoid Valve Based on the ELM Deep Learning Model
Authors: Tu Chaoqun , Zhang Lingli
Published: August 2022

Aiming at the energy vehicle ABS kinetic energy recovery, this study optimizes the ABS system through the IPSO-ELM model, so that the energy vehicle can recover the energy generated by the ABS system to the greatest extent, so as to achieve the purpose of kinetic energy recovery and reduce energy consumption and vehicle cost. Based on the PSO-ELM model, a linear decreasing weighting method is introduced, and then, an IPSO-ELM model is proposed for the optimization analysis of ABS brake kinetic energy recovery. The results show that compared with the simple ELM model and PSO-ELM model, the simulation mean square error and relative error are significantly smaller, the generalization ability and prediction accuracy are higher, and the maximum relative error of the prediction result is 5.43% and the average relative error is 2.72%. The results confirm that the use of IPSO-ELM for ABS kinetic energy recovery optimization is extremely effective, and the study of ABS kinetic energy recovery for energy vehicles based on IPSO-ELM model optimization has strong application prospects and application potential.
A Reinforcement Learning-Based Basketball Player Activity Recognition Method Using Multisensors
Authors: Bo Yang
Published: August 2022

It is an effective means to use a computer auxiliary system to assist athletes in training. In this paper, we design a technical activity recognition system for basketball players. The system uses the sensing module bound to the basketball player to collect the activity data and uses the proposed Multilayer Parallel Long Short Term Memory (MP-LSTM) algorithm to recognize the activity. Moreover, in order to extend the working time of the system and reduce the energy consumption of the sensing module, we also utilize the classical reinforcement learning algorithm DQN to adaptively control the sampling frequency of the sensing module for making a trade-off between recognition accuracy and energy consumption. Experiment results show that the recognition accuracy of the proposed MP-LSTM algorithm reaches 94%, while the recognition accuracy of the system remains at about 90% after applying the DQN algorithm, and the energy consumption is reduced by 76%.