bluuebunny/crossref_metadata_2025 huggingface dataset:
Virtual Screening of PotentialIn SilicoHits for the Prevention of Neuroinflammation: Arylalkanoic Acid Derivatives of NSAIDs as Selective Dual Inhibitors of Microsomal Prostaglandin E Synthase-2 (mPGES-2) and 5-Lipoxygenase-Activating Protein (FLAP)
Authors: Nedeljković Nikola V. , Bojović Dijana N. , Živanović Ana S. , Mijajlović Marina Ž. , Nikolić Miloš V.
Published: June 2022

The aim of this in silico study was the identification of NSAID’s amides with ability to bypass the COX inhibition and selectively target mPGES-2 and FLAP. Molecular binding analysis was conducted on selected compounds using molecular docking, MD simulations and MM/GBSA calculations to assess their potential in the prevention of neuroinflammation. Ligand-based virtual screening was performed in the ChEMBL database, thereby 196 compounds were obtained. Resulting compounds were passed through the BBB permeability and druglikeness filters, and six compounds were selected for further analysis. Molecular docking analysis showed that compounds 4 and 6 can avoid the COX inhibition and simultaneously target mPGES-2 and FLAP. These two top docked compounds were subjected to MD simulations, which indicated that complexes of compound 4 with mPGES-2 and FLAP have shown conformational stability throughout the simulation. Calculated MM/GBSA binding energies confirmed that compound 4 demonstrated dual binding affinity against mPGES-2 and FLAP. Based on the docking score, MM/GBSA average binding energy and MD results, compound 4 emerged as the best in silico hit for the prevention of neuroinflammation.
A Novel Assistive Glove to Convert Arabic Sign Language into Speech
Authors: Alzubaidi Mohammad A. , Otoom Mwaffaq , Abu Rwaq Areen M.
Published: June 2022

People with speech disorders often communicate through special gestures and sign language gestures. However, other people around them might not understand the meaning of those gestures. The research described in this article is aimed at providing an assistive device to help those people communicate with others by translating their gestures into a spoken voice that others can understand. The proposed device includes an electronic glove that is worn on the hand. It employs an MPU6050 accelerometer/gyro with 6 degrees of freedom to continuously monitor hand orientation and movement, plus a potentiometer for each finger, to monitor changes in finger posture. The signals from the MPU6050 and the potentiometers are routed to an Arduino board, where they are processed to determine the meaning of each gesture, which is then voiced using the audio streams stored in an SD memory card. The audio output drives a speaker, allowing the listener to understand the meaning of each gesture. We built a database with the help of 10 deaf people who cannot speak. We asked them to wear the glove while performing a set of 40 Arabic sign language words and recorded the resulting data stream from the glove. That data was then used to train seven different learning algorithms. The results showed that the Decision Tree learning algorithm achieved the highest accuracy of 98%. A usability study was then conducted to determine the usefulness of the assistive device in real-time.
Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes
Authors: Gupta Vinayak , Bedathur Srikanta , Bhattacharya Sourangshu , De Abir
Published: June 2022

A large fraction of data generated via human activities such as online purchases, health records, spatial mobility, etc. can be represented as a sequence of events over a continuous-time. Learning deep learning models over these continuous-time event sequences is a non-trivial task as it involves modeling the ever-increasing event timestamps, inter-event time gaps, event types, and the influences between different events within and across different sequences. In recent years, neural enhancements to
marked temporal point processes (MTPP)
have emerged as a powerful framework to model the underlying generative mechanism of asynchronous events localized in continuous time. However, most existing models and inference methods in the MTPP framework consider only the complete observation scenario i.e., the event sequence being modeled is completely observed with no missing events – an ideal setting that is rarely applicable in real-world applications. A recent line of work which considers missing events while training MTPP utilizes supervised learning techniques that require additional knowledge of
missing
or
observed
label for each event in a sequence, which further restricts its practicability as in several scenarios the details of missing events is not known
a priori
. In this work, we provide a novel unsupervised model and inference method for learning MTPP in presence of event sequences with missing events. Specifically, we first model the generative processes of observed events and missing events using two MTPP, where the missing events are represented as latent random variables. Then, we devise an unsupervised training method that jointly learns both the MTPP by means of variational inference. Such a formulation can effectively impute the missing data among the observed events, which in turn enhances its predictive prowess, and can identify the optimal position of missing events in a sequence. Experiments with eight real-world datasets show that
IMTPP
outperforms the state-of-the-art MTPP frameworks for event prediction and missing data imputation, and provides stable optimization.
Obesity-related vascular dysfunction persists after weight loss and is associated with decreased vascular glucagon-like peptide receptor in female rats
Authors: Kiernan Risa , Persand Dhandevi , Maddie Nicole , Cai Weikang , Carrillo-Sepulveda Maria Alicia
Published: June 2022

Although short-term weight loss successfully improved metabolic parameters, it failed to correct vascular dysfunction present in obese female rats. Vascular GLP-1/Akt signaling was decreased in both obese rats and those with short-term weight loss, suggesting it may be a potential target for therapeutic intervention in obesity-related persistent vascular dysfunction in obese females.
Reevaluating methods reporting practices to improve reproducibility: an analysis of methodological rigor for the Langendorff whole heart technique
Authors: King D. Ryan , Hardin Kathryn M. , Hoeker Gregory S. , Poelzing Steven
Published: June 2022

In recent decades, the scientific community has seen an increased interest in rigor and reproducibility. In 2017, concerns about methodological thoroughness and reporting practices were implicated as significant barriers to reproducibility within the preclinical cardiovascular literature, particularly in studies using animal research. The Langendorff, whole heart technique has proven to be an invaluable research tool, being modified in a myriad of ways to probe questions across the spectrum of physiological and pathophysiological functions of the heart. As a result, significant variability in the application of the Langendorff technique exists. This literature review quantifies the different methods employed in the implementation of the Langendorff technique and provides brief examples of how individual parametric differences can impact the outcomes and interpretation of studies. From 2017 to 2020, significant variability of animal models, anesthesia, cannulation time, perfusate composition, pH, and temperature demonstrate that the technique has diversified to meet new challenges and answer different scientific questions. The review also reveals which individual methods are most frequently reported, even if there is no explicit agreement upon which parameters should be reported. The analysis of methods related to the Langendorff technique suggests a framework for considering methodological approach when interpreting seemingly contradictory results, rather than concluding that results are irreproducible.
Quercetin Inhibits KBM7R Cell Proliferation through Wnt/β-Catenin Signaling
Authors: Li Wei , Yu Yang , Cheng Huanchen , Liu Shengwei , Gong Tiejun , Ma Jun , Tang Qinghua
Published: June 2022

Background. Tyrosine kinase inhibitors could treat chronic myelogenous leukemia (CML) effectively, but they have no effect on patients with T315I mutation. It is necessary to find drugs to overcome the resistance. Quercetin (Qu) is a kind of bioflavonoid with an antitumor effect. In this study, we observed the effect of Qu on proliferation and Wnt/β-catenin pathway in KBM7R cells, an imatinib-resistant cell with T315I mutation. Methods. The IC50 of Qu was detected by trypan blue staining. The KBM7R cell apoptosis and cycle were detected through the method of flow cytometry (FCM). The expression of the related mRNA and protein was evaluated by means of an RT-PCR assay and western blot in KBM7 (sensitive to IM) and KBM7R cells. Results. These results showed that in the KBM7R cell, the proliferation inhibition effect was increased after 48 h administration with different Qu concentrations. The IC50 to Qu was 241.7 μmol/L. The different doses of Qu (50, 100, and 200 μmol/L) would raise apoptosis and depress the cell cycle at the G1 phase. Dealing with a median Qu concentration (100 μmol/L) for 48 h, the mRNA and the protein level of caspase-3, caspase-8, and caspase-9 along with p21 and p27 raised compared with the control. The median concentration of Qu could inhibit both the mRNA and protein levels of GSK-3β, β-catenin, and Lef-1 in the Wnt/β-catenin signal pathway and also the downstream targets PPAR-δ and cyclin D1 in both KBM7 and KBM7R cells. Conclusions. Our findings suggest that Qu could inhibit proliferation, induce apoptosis, and arrest the cell cycle on IM-resistant KBM7R cells with T315I mutation. And this effect could be related with the inhibition of the Wnt/β-catenin signal pathway and downstream targets.
Knowledge, Attitude, and Practice of Community towards an Onchocerciasis Elimination Program from South West Ethiopia
Authors: Worku Haile , Mola Misganaw , Alemu Bizuwork Derebew , Jemal Sebwedin Surur , Ayiza Aklilu , Getachew Samuel , Chauhan Nitin Mahendra , Tulshiram Hajare Sunil , Chandra Singh Suresh , Kuddus Mohammed , Upadhye Vijay J.
Published: June 2022

Onchocerciasis is a neglected tropical disease that is prevalent throughout Africa, including developing countries such as Ethiopia. It affects around 37 million people, the majority of whom are from Africa. As a result, the study was designed to look into the community’s knowledge, attitude, and practice about the onchocerciasis elimination campaign. Four communities from Gesha town, Southwest Ethiopia, were chosen. The population was selected using a basic random selection procedure, and 312 people were identified for the study based on the eligibility requirements, with 302 (96.79%) of them responding correctly. The data were analyzed using the descriptive method with the SPSS program version 20. It was discovered that the majority of communities (89.4%) are aware of onchocerciasis. They also have a good awareness of the severity, preventability, therapy, and mode of transmission, yet they have certain misunderstandings. The communities attitude towards community directed therapy (CDT) using Ivermectin is positive (68.5%). According to 56% of the community, offering incentives for community drug distributors (CDD) has the potential to make the elimination campaign more successful. Different measures, such as avoiding any activities near the river, are important in the process of eradicating this disease at the community level. As a result, the respondent demonstrates that covering the lower body part lessens the black fly’s vulnerability because they may attack below the knee. In general, community awareness and attitude are required to eradicate this disease from the district. In addition, increased stakeholder participation and offering motivating rewards for CDT are required to make the elimination program a success.
[Retracted] MIP‐1α Level and Its Correlation with the Risk of Left Atrial Remodeling in Patients with Atrial Fibrillation
Authors: Bai Chen , Ye Qing , Zhao Yichen , Liu Yang , Wang Jiangang
Published: June 2022

The aim of this study is to investigate the expression level of macrophage inflammatory protein‐1α (MIP‐1α) in atrial fibrillation patients and its correlation with the risk of left atrial remodeling. A total of 64 atrial fibrillation patients admitted to our hospital from April 2020 to December 2021 were prospectively selected as the case group and 61 healthy subjects who received physical examination during the same period were selected as the control group. Serum MIP‐1α level was determined by a double‐antibody sandwich enzyme‐linked immunosorbent assay. Serum MIP‐1α expression levels were compared between the case and the control groups. The case group was divided into high‐level and low‐level groups according to the serum MIP‐1α median. Simultaneously, the sociodemographic data, clinical data, and left atrial remodeling indexes of the patients were collected in the case group. The Pearson correlation analysis was applied to analyze the correlation between the serum MIP‐1α level and the risk of left atrial remodeling in patients with atrial fibrillation. The serum MIP‐1α level was significantly higher in the case group than that in the control group (P < 0.05), high‐level group (≥2.14 pg/mL, 32 cases), and low‐level group (<2.14 pg/mL, 32 cases). There were significant differences in the anteroposterior diameter, upper and lower diameter, left and right diameter of the left atrium, left atrial volume, volume index, left atrial global ejection fraction, and sphericity between the low‐level and high‐level groups (P < 0.05). The Pearson correlation analysis showed that serum MIP‐1α level was positively correlated with the left atrial anteroposterior diameter (r = 0.745), left atrial left and right diameter (r = 0.759), left atrial upper and lower diameter (r = 0.810), left atrial volume (r = 0.837), left atrial volume index (r = 0.813), and left atrial sphericity (r = 0.785) but negatively correlated with the left atrial global ejection fraction (r = ‐0.731) (P < 0.05). The expression level of serum MIP‐1α is high in atrial fibrillation patients and is associated with the risk of left atrial remodeling.
Performance Appraisal System and Its Optimization Method for Enterprise Management Employees Based on the KPI Index
Authors: Peng Jin
Published: June 2022

Enterprise human resources management plays an important role in enterprise development, and it is an important support for the resisting the risk of market competition. The quality of enterprise managers and whether the performance appraisal is reasonable and effective directly affect the operation status and overall benefits of enterprises. Therefore, in order to enhance the competitiveness and achieve the development goals of the enterprise, the enterprise needs a set of scientific performance appraisal systems for enterprise management personnel. By combining the characteristics and research status of enterprise managers’ performance evaluation, the shortcomings of the current popular enterprise managers’ performance evaluation system were analyzed and pointed out in this paper, and the optimization method of enterprise managers’ performance evaluation system based on KPI indicators was studied and put forward, which can provide a certain theoretical support for enterprises to improve their management level and market competitiveness.
Efficacy of the Whole-Course Case Management Model on Compliance and Satisfaction of Breast Cancer Patients with Whole-Course Standardized Treatment
Authors: Jin Lijun , Zhao Yunyan , Wang Peng , Zhu Ran , Bai Jie , Li Jie , Jia Xue , Wang Zunyi
Published: June 2022

Objective. To explore the influence of the whole-course case management model on the compliance and satisfaction of breast cancer patients with the whole-course standardized treatment. Methods. Eighty breast cancer patients admitted to our hospital between April 2020 and June 2021 were assigned to receive either conventional nursing (routine group, n = 40) or whole-process case management (experimental group, n = 40) according to different nursing methods. Outcome measures included self-rating anxiety scale (SAS) scores, self-rating depression scale (SDS) scores, adverse reactions, treatment compliance, and nursing satisfaction. Results. After nursing, the SAS and SDS scores of the experimental group were significantly lower than those of the routine group

P
<
0.05

. The whole case management mode was associated with a significantly lower incidence of adverse reactions versus routine nursing

P
<
0.05

. The whole case management resulted in higher compliance of patients versus routine nursing

P
<
0.05

. The experimental group had a significantly higher nursing satisfaction versus the routine group

P
<
0.05

. Conclusion. The whole-process case management mitigates patients’ negative emotions, strengthens their treatment compliance, lowers the incidence of postoperative adverse reactions, and improves nursing satisfaction, which may provide a viable nursing alternative for patients with breast cancer.
Loquat Leaf Extract Enhances Muscle Contraction-Induced Activation of Protein Synthesis Signaling in Rat Skeletal Muscle
Authors: Hung Yung-Li , Kosugi Riki , Natsume Toshiharu , Machida Shuichi
Published: June 2022

Loquat (Eriobotrya japonica (Thunb.) Lindl.) leaves are traditionally used to improve muscle weakness, but their effects on muscle protein synthesis require further research. Therefore, we aimed to investigate whether loquat leaf extract (LLE) enhances muscle contraction-induced activation of muscle protein synthesis signaling. Male Wistar rats (12 weeks old, n = 6/group) were categorized into water treatment (CON) and LLE treatment (LLE) groups. The rats were administered distilled water or LLE (1.5 g/kg/day) once a day by oral gavage for 7 days. On day 7, at 3 h post-LLE administration, the gastrocnemius muscle in the right leg of each rat was stimulated by electrical muscle stimulation (EMS) (100 Hz, 30 V) through five sets of 10 isometric contractions (7 s contraction, 3 s rest) with 3 min interset intervals. The rats were then sacrificed, and the gastrocnemius muscles of both legs were excised at 3 h post-EMS. The phosphorylation levels of mammalian target of rapamycin complex 1 (mTORC1) signaling pathway molecules (Akt, mTOR, and p70S6K) were determined by Western blotting. Regarding the muscle contraction-induced protein synthesis signaling pathway, Akt phosphorylation at Ser473 was not significantly different between the CON and LLE groups. mTOR phosphorylation at Ser2448 was increased by EMS but did not show a significant difference between the CON and LLE groups. p70S6K phosphorylation at Thr389 was significantly increased in response to EMS, whereas the LLE group showed significantly higher p70S6K phosphorylation at Thr389 than that in the CON group. This suggests that LLE enhances muscle contraction-induced activation of p70S6K phosphorylation in rat skeletal muscles.
Jujuboside A Ameliorates Myocardial Apoptosis and Inflammation in Rats with Coronary Heart Disease by Inhibiting PPAR-α Signaling Pathway
Authors: Hu Chunfang , Zhang Zhiyuan , Song Guixian , Zhu Li , Wang Ruzhu , Ruan Zhongbao
Published: June 2022

Background. Coronary heart disease (CHD) is a chronic disease caused by atherosclerosis (AS), which can cause myocardial ischemia, hypoxia, or necrosis, seriously threatening human health. There is an urgent need for effective treatments and drugs to reduce the various risk factors for coronary heart disease and relieve symptoms of angina pectoris and myocardial infarction in patients. Jujuboside A (JuA) is a triterpenoid saponin extracted from jujube seeds, which has various biological activities such as antioxidant, anti-inflammatory, antiapoptotic, and neuroprotective effects. We study the function of JuA in myocardial injury, dyslipidemia, and inflammation in the CHD rat model, to explore its potential mechanism of improving CHD. Methods. A rat model of CHD was established by feeding a high-fat diet. The rats were randomly divided into 5 groups (n = 6): control group, CHD group, JuA 25 mg/kg group, JuA 50 mg/kg group, and JuA 75 mg/kg group. Echocardiography was used to detect the cardiac function parameters of rats in each group, and then, hematoxylin and eosin staining was used to assess the histopathological injury in myocardial tissues. Levels of blood lipids, myocardial injury indexes, and inflammatory factors of rats in each group were measured by biochemical tests and enzyme linked immunosorbent assay, and the levels of Bax, Bcl-2, c-caspase-3, PPAR-α, p65, p-p65, IκBα, and p-IκBα protein expression in myocardial tissues were detected by western blot. Results. Compared with the CHD group, JuA therapy significantly improved injury in myocardial tissue and endothelial tissue. It also strengthened cardiac function, while decreasing total cholesterol, triacylglycerol, and low-density lipoprotein cholesterol levels in the serum and increasing high-density lipoprotein cholesterol levels. In addition, JuA also restrained cardiomyocytes apoptosis and inhibited the inflammatory reaction by reducing TNF-α, IL-1β, and IL-6 expression in myocardial tissues. Furthermore, administration of JuA inhibited the activation of PPAR-α pathway by preventing the phosphorylation of p65 and IκBα in myocardial tissues of CHD rats. Conclusion. JuA may improve cardiac function, alleviate myocardial and endothelial injury, and also ameliorate dyslipidemia and inflammatory reaction in rats with CHD, where JuA probably plays a protective role by inhibiting the activation of PPAR-α pathway.
Effect Evaluation of Perioperative Fast‐Track Surgery Nursing for Tibial Fracture Patients with Computerized Tomography Images under Intelligent Algorithm
Authors: Zhang Mengmeng , Li Chuanbo , Rao Fulan
Published: June 2022

This study aimed to study the application value of computerized tomography (CT) images under the graph cut algorithm in the effect evaluation of perioperative fast‐track surgery (FTS) nursing in tibial fracture. In this study, 80 tibial fracture patients in the perioperative period were selected as the research objects. These objects were randomly divided into two groups according to the examination method. In group A, routine CT examination was performed; in group B, CT examination under the graph cut algorithm was applied. The imaging results showed that there were still 16 cases with collapse of group A and 34 cases with collapse of group B; the difference was statistically significant (P < 0.05). As for 16 cases with collapse in both groups, the average collapse shown in group A was about 2.79 ± 1.31 mm, while that in group B was 5.51 ± 1.88 mm, with a statistically significant difference (P < 0.05). The average broadening in the images of group A was 3.17 ± 1.41 mm and that of group B was 5.72 ± 1.83 mm, suggesting that the difference was statistically significant (P < 0.05). The broadening distance of 3‐4 mm was mainly shown in the images of group A and that of 5‐8 mm was shown in group B, with a statistical difference (P < 0.05). In terms of the total score, there were 26, 44, 8, and 2 cases that were assessed as excellent, good, common, and bad, respectively, in group A, while 44 cases were assessed as good and 36 cases were assessed as common in group B, which were significantly different (P < 0.05). In summary, the graph cut algorithm not only had a good segmentation effect and segmentation efficiency but also could improve the evaluation of CT images for perioperative FTS nursing effect in patients with tibial fracture.
Abnormal Data Monitoring and Analysis Based on Data Mining and Neural Network
Authors: Chen Yanyan
Published: June 2022

In order to solve the problems of low efficiency, high consumption of human and time resources, and low degree of intelligence in the current financial abnormal data detection system in computerized accounting, this paper proposes a financial abnormal data monitoring and analysis algorithm based on data mining and neural network. The analysis algorithm uses the method of data mining to process the original financial data, remove invalid information, retain valuable information, and standardize the data to solve the problem of large labor and time consumption. Then, neural network-related algorithms are used to identify the anomalies of standardized data, so as to realize the intelligent early warning of financial abnormal data. Compared with the financial audit algorithm in traditional accounting computerization, this algorithm has the advantages of high efficiency, low energy consumption, and high intelligence. The test results show that the classification accuracy of the proposed algorithm for abnormal data can reach more than 90%. It is proved that the algorithm is effective and improves the efficiency at the same time. The classification error rate of the classifier designed in this paper is 22.5%, and the accuracy rate is 77.5%. Both estimated and actual values represent the number of times, and there is no physical unit. The experiment shows that the main reason for the error rate is the delay of the inspection results of financial abnormalities. Through the example analysis, it can be concluded that the proposed intelligent analysis method of financial abnormal data based on deep learning has good effectiveness and accuracy and has a certain practical value.
Situation Awareness of Electric Vehicle Charging Load Based on Random Forest Algorithm
Authors: Bo Wen , Wang Donglai , Zhao Yan , Li Quanzheng , Zhang Zhen
Published: June 2022

Due to the important characteristics of energy saving and carbon reduction, electric vehicles have attracted worldwide attention. It can be predicted that the power grid will be faced with the access problem of large-scale electric vehicles. In order to master the user behavior characteristics of electric vehicle load, it is necessary to establish the model based on electric vehicle charging behavior. In this paper, combined with the electric vehicle charging demand and the situational awareness results of the dispatchable resources in the station area, the characteristic indicators of the electric vehicle load are quantitatively analyzed. Situational prediction of electric vehicle load based on random forest algorithm is proposed, and the sample set is divided and trained. A simulation example is used to verify the effectiveness of the method provided in load forecasting.
An Empirical Study on the Relationship between Craftsman’s Spirit and Economic Growth of Construction Industry
Authors: Bai Furong , Wang Huanru
Published: June 2022

This exploration aims to explore the relationship between craftsman’s spirit and the economic growth of the construction industry and discuss the heterogeneity of different regions to provide a reference for the development of the construction industry in each region. The annual data from 2011 to 2018 of China’s 30 provinces (autonomous regions and municipalities) (except Tibet) is used as the research object. Based on defining the craftsman’s spirit of the construction industry and constructing its comprehensive evaluation index system, a panel data model is established to analyze the relationship between the craftsman’s spirit and the economic growth of the construction industry and regional differences. The empirical results show that the level of craftsman’s spirit in China’s construction industry is increasing year by year, showing a “gradient decreasing” trend in the east, the middle, and the west. Specific data show that, from 2011 to 2018, the craftsman’s spirit of the construction industry in 30 provinces increased from 0.154 to 0.256. Among them, the craftsman’s spirit index in Beijing in 2018 was 2.19 times higher than that in 2011, an increase of 119.38%, with the fastest growth rate. The growth rate of Shaanxi Province in recent 8 years is only 11.4%, which is relatively low. The craftsman’s spirit has a positive impact on the economic growth of the construction industry, and there are regional differences. The promotion effect is more obvious in the central region, followed by the eastern region, and weaker in the western region. The research content has important reference value for improving the construction industry’ attention to cultivating the craftsman’s spirit of employees and promoting the coordinated development of regions.
Euler‐Lagrange Equation in Free Coordinates
Authors: Alotaibi Mastourah M. , Altoum Sami H.
Published: June 2022

In this paper, we introduce different equivalent formulations of variational principle. The language of differential forms and manifold has been utilized to deduce Euler–Lagrange equations in free coordinates. Thus, the expression is simple and global.
SROBR: Semantic Representation of Obfuscation-Resilient Binary Code
Authors: Tang Ke , Shan Zheng , Liu Fudong , Huang Yizhao , Sun Rongbo , Qiao Meng , Zhang Chunyan , Wang Jue , Gui Hairen
Published: June 2022

With the rapid development of information technology, the scale of software has increased exponentially. Binary code similarity detection technology plays an important role in many fields, such as detecting software plagiarism, vulnerabilities discovery, and copyright solution issues. Nevertheless, what cannot be ignored is that a variety of approaches to binary code semantic representation have been introduced recently, but few can catch up with existing code obfuscation techniques due to their maturing and extensive development. In order to solve this problem, we propose a new neural network model, named SROBR, which is a deep integration of natural language processing model and graph neural network. In SROBR, BERT is applied to capture sequence information of the binary code at the first place, and then GAT is utilized to capture the structural information. It combines natural language processing and graph neural network, which can capture the semantic information of binary programs while resisting obfuscation options in a more efficient way. Through binary code similarity detection task and obfuscated option classification task, the experimental results demonstrate that SROBR outperforms existing binary similarity detection methods in resisting obfuscation techniques.
Investigation of Dendrimer Structures by Means of K‐Banhatti Invariants
Authors: Huo Cheng-Gang , Azhar Fozia , Virk Abaid Ur Rehman , Ismaeel Tariq
Published: June 2022

Dendrimers are highly branched macromolecules. The structural chemistry of dendrimers could be shaped by their topological invariants to target the particular design with appropriate properties to bring the drugs to mark a carrier vehicle. This study is about some new topological indices of dendrimer generations. Here, we calculate K Banhatti indices for five generations of dendrimers. Precisely speaking, we computed the 1st K Banhatti redefined Zagreb index, 2nd K Banhatti redefined Zagreb indices, and 3rd K Banhatti redefined Zagreb index for the dendrimers Di(p) for i = 1,2,3,4,5.
Data Fusion Model for Muscle Proteomics in Sports Applications
Authors: Xie Chunsheng , Li Xian , Cui Congying
Published: June 2022

Proteome is a cell, tissue, or organism to express all the floorboard of the protein; proteomics is the study of proteomics is an emerging discipline; the research on the law of occurrence of sports fatigue and its mechanism is an important and challenging subject in the field of sports medicine. Exercise-induced fatigue refers to the physiological process in which the body’s functional ability or work efficiency declines and cannot be maintained at a specific level during exercise. With the improvement of the modern competitive sports level and the increasingly fierce competition, the athletes have to bear more and more loads in sports training, and the probability of sports fatigue is also higher. Appropriate sports fatigue and reasonable recovery methods can promote the improvement of athletes’ functional level; on the contrary, excessive fatigue not only affects the training effect but may also cause various dysfunctions, which may damage the athletes’ health. Therefore, understanding the mechanism of sports fatigue is of positive significance for accelerating the elimination of sports fatigue. The purpose of this paper is to study the progress of muscle proteomics in sports. Since each athlete has individual differences, different levels of muscle function corresponding to the left lower limb will produce different EMG signals. Static experiments and random visual stimulation evaluation experiments were performed on the left lower limbs of athletes, and they were coordinated with the right lower limbs, and then the left and right lower limbs were compared with the same muscle-weighted RMS (Recipe Management System) and IEMG (Comprehensive electromyography). Experimental results show that using the statistical method of single-factor variance analysis to the same muscles in two states of RMS was analyzed, respectively, under the two states of differences between muscle electromyography IEMG were analyzed, finally, the muscle integral electrical values on the contribution rate of extent of each muscle under the two states are analyzed. For one-way ANOVA, this study defined the significance level of the difference analysis between groups as

P
<
0.05

.

P
<
0.05

is a small probability event, indicating that the possibility of an event occurring is very small, so it is considered that the event is unlikely to occur. A low-probability event is an event that has a low probability of occurring. Then, it is almost impossible to happen in one experiment, but it is bound to happen in many repeated experiments. With the continuous improvement of existing technologies and the emergence of more new technologies, proteomics research will make greater contributions to elucidate the mechanism of exercise on skeletal muscle remodeling and its improvement on health.
Swin-YOLOv5: Research and Application of Fire and Smoke Detection Algorithm Based on YOLOv5
Authors: Zhang Shangjie Ge , Zhang Fengxi , Ding Yuyang , Li Yu
Published: June 2022

Accurate monitoring of fire and smoke plays an irreplaceable role in preventing fires and safeguarding the safety of citizens' lives and property. The network structure of YOLOv5 is simple, but using convolution to extract features will lead to some problems such as limited receptive field, poor feature extraction ability, and insufficient feature integration. In view of the current defects of YOLOv5 target detection algorithm, a new algorithm model named Swin-YOLOv5 was proposed in this work. Swin transformation mechanism was introduced into YOLOv5 network, which enhanced the receptive field and feature extraction ability of the model without changing the depth of the model. In order to enrich the feature map splicing method of weighted Concat and enhance the feature fusion ability of model pairs, the feature splicing method of three output heads of feature fusion layer network was improved. The feature fusion module was further modified, and the weighted feature splicing method was introduced to improve the network feature fusion ability. Experiments showed that, compared with the original algorithm, the rising rate of mAP@0.5 (mean average precision, IoU=0.5) of the improved algorithm was 0.7%, the mAP@0.5:0.95 was increased by 4.5%, and the target detection speed with high accuracy was accelerated by 1.8 FPS (frames per second) under the same experimental dataset. The improved algorithm could more accurately detect the targets that were not detected or detected inaccurately by the original algorithm, which embodied the adaptability of real scene detection and had practical significance. This work provided an opportunity for the application of fire-smoke detection in forest and indoor scenes and also developed a feasible idea for feature extraction and fusion of YOLOv5.
Teaching Design of Mathematics Application Based on Naive Bayes
Authors: Ling Huanzhang
Published: June 2022

There is a huge amount of mathematical information in the world, and mathematics is everywhere and nowhere. Bayesian theory is based on a process of statistical inference that requires the calculation of general and prior information to obtain a posteriori information. Its main features are the use of probabilities to represent all forms of uncertainty and the use of probabilistic rules to enable learning and inference, estimating the probability of future occurrences by calculating the probability of a past time. In order to bring mathematics closer to life, this paper explores the teaching of mathematical applications in terms of material selection, teaching arrangement, and professional integration. At the same time, in order to better realize mathematics application teaching, effectively improve the classroom effect of mathematics application teaching, and make students better accept mathematical knowledge and apply it to practical applications, the design of mathematics application teaching in this paper is also based on Naive Bayes.
Rehabilitation of a Child with Denari Prosthesis after Dental Avulsion
Authors: Arcos-López César Sebastián , Parise-Vasco Juan Marcos , Armas-Vega Ana , Carrillo-Azuero Yecenia
Published: June 2022

Prosthetic rehabilitation in cases of premature loss of temporary teeth always is a procedure that must be carried out in a planned and integral manner. The avoidance of opposing tooth extrusion, loss of horizontal space, and acquisition of bad oral habits are fundamental to not trigger alterations in the child’s occlusal development and psychological development. The purpose of this document is to report the clinical case of a 4-year-old patient with avulsion of the anterior primary teeth secondary to severe automobile trauma. In this case, we describe the use of a Denari-type fixed partial prosthesis. This prosthesis can recover the function and aesthetics of the superior anterior sector of the oral cavity, thus preventing lingual interposition. The treatment with the Denari prosthesis allowed satisfactory results relating to the transverse growth of the maxillary bone in this case report.
Monitoring of Nitrogen Transport in Pear Trees Based on Ground Hyperspectral Remote Sensing and Digital Image Information
Authors: Fan Zehua , Wang Desheng , Zhang Nannan , Zhou Baoping
Published: June 2022

To study nitrogen transport monitoring in pear trees based on ground-based hyperspectral remote sensing and digital image information. First, based on ground hyperspectral remote sensing and digital image information, combined with the characteristics of visible and near-infrared spectral data and digital image data, a beet nitrogen nutrition diagnosis model based on visible and near-infrared spectral and digital image information was established. The results showed that under water and nitrogen management conditions, the marked nitrogen use efficiency at soil profiles 15, 45, and 75 cm was 28.2%, 22.3%, and 16.3%, respectively. From the analysis of soil and plant nitrogen measured in this experiment, it can be seen that nitrogen nitrate fertilizer should be properly applied to pear trees in the future.
Morbidity of the Donor Site and Complication Rates of Breast Reconstruction with Autologous Abdominal Flaps: A Systematic Review and Meta-Analysis
Authors: Mortada Hatan , AlNojaidi Taif Fawaz , AlRabah Razan , Almohammadi Yousif , AlKhashan Raghad , Aljaaly Hattan
Published: June 2022

Background. Numerous studies have evaluated the use of autologous abdominal tissue for breast reconstruction; nevertheless, complications and donor site morbidity rates vary significantly. The study aims to compare the literature regarding morbidity of the donor site and complication rates of breast reconstruction with autologous abdominal flaps. Methods. The databases of MEDLINE, EBSCO, Scopus, Wiley Library, and Web of Sciences were searched for studies that compared different flaps in terms of complications and donor site morbidity. The procedures studied included pedicled transverse rectus abdominis myocutaneous ﬂap (pTRAM), free TRAM (fTRAM), deep inferior epigastric perforator (DIEP), and superﬁcial inferior epigastric artery perforator (SIEA) flaps. A total of 34 studies were included. Of these, 28 were retrospective studies and 9 were prospective cohort studies. Results. When compared to DIEP, fTRAM flaps were found to have a decreased incidence of flap fat necrosis, hematoma, and total thrombotic events, yet a higher risk of donor site hernia/bulging. pTRAM flaps were also associated with an increased risk of hernia/bulging at the donor site, as well as wound infection, yet flap hematoma was less common. On the other hand, SIEA flaps showed the lowest risk of donor site hernia/bulging while still having a high risk of wound infection. Conclusion. fTRAM procedures comparatively had the least complications. However, regarding flap choice, patients would benefit most from a case-by-case analysis, taking into consideration individual risk factors and preferences.
Multidrug-Resistant Acinetobacter baumannii May Cause Patients to Develop Polymicrobial Bloodstream Infection
Authors: Chen Qingqing , Zheng Zhencang , Shi Qingxin , Wu Huijuan , Li Yuping , Zheng Cheng
Published: June 2022

Background. The incidence of polymicrobial bloodstream infections is increasing, the clinical characteristics of polymicrobial Acinetobacter baumannii bloodstream infections (AB-BSI) are unclear, and there are no reports of polymicrobial AB-BSI in mainland China. Therefore, our objective was to identify the clinical characteristics, risk factors, and outcomes of polymicrobial AB-BSI versus monomicrobial AB-BSI. Methods. A retrospective survey of all patients with AB-BSI from January 1, 2015, to December 31, 2019, and their clinical data were collected and analyzed by reviewing electronic medical records. All data were compared and analyzed between groups of monomicrobial and polymicrobial AB-BSI. Risk factors for polymicrobial AB-BSI were assessed using multivariable logistic regression analysis. Results. A total of 204 patients were included, of which 39 (19.1%) were patients with polymicrobial AB-BSI. The main sources of the pathogenicity of polymicrobial Acinetobacter baumannii bloodstream infections were skin and soft tissue (38.5% vs. 16.4%,

p
=
0.002

). Resistance to piperacillin/tazobactam as an independent factor for polymicrobial AB-BSI was found in multivariate analysis. Patients with polymicrobial AB-BSI had longer hospital stays compared to those with monomicrobial AB-BSI. However, there was no significant difference in mortality between the two groups. Conclusions. Polymicrobial AB-BSI accounted for a significant proportion among all AB-BSI, and it did not influence mortality but was related to slightly longer total hospital stays. Multidrug resistance was associated with the development of polymicrobial AB-BSI but does not directly lead to polymicrobial AB-BSI, whereas resistance to piperacillin/tazobactam was highly correlated with polymicrobial AB-BSI. Therefore, while treating A. baumannii bloodstream infections, clinicians cannot ignore the multidrug-resistant A. baumannii, especially piperacillin/tazobactam-resistant A. baumannii, which may predispose to the development of polymicrobial AB-BSI.
Construction of Sports Training Management Information System Using AI Action Recognition
Authors: Cheng Dali , Wang Hong , Li Min
Published: June 2022

With the development of science and technology, more and more fields have begun to use AI to provide convenient services for humans. Artificial intelligence (AI) refers to a new technology that uses human thinking to respond accordingly through computers and robots to assist human beings. Action recognition is an important research project that needs to be broken through in many industries, such as security system, martial arts instruction, and dance training. This paper aims to study a method for action recognition using AI technology and to build a sports training management information system. In this paper, a recognition model and related algorithms using a convolutional neural network (CNN) are proposed, and an intelligent sports training management information system is constructed. The system and the model are tested, the action recognition effect of 60 athletes in a university is tested, and the comparison with the traditional recognition algorithm is carried out. The results show that the CNN recognition accuracy test results used in this paper are generally more than 90%, while the traditional recognition accuracy rate is only about 75%, and the highest is not more than 86%; the training management information system of this paper takes about 15.7 s, and the maximum time is not more than 10 s, while the traditional recognition system takes about 15.7 s, which is about twice the time of the system in this paper. Therefore, it shows that the CNN recognition method in this paper has a significantly better effect on the recognition of athletes’ movements, and the sports training management information system constructed in this paper is less time-consuming and faster and has certain feasibility.
Solution of a Fractional Integral Equation Using the Darbo Fixed Point Theorem
Authors: Chandra Deuri Bhuban , V. Paunović Marija , Das Anupam , Parvaneh Vahid
Published: June 2022

The concept of measure of noncompactness in a Banach space is used in this paper to extend some tripled fixed point theorems. We prove the existence of fractional integral equation solutions using a generalized Darbo fixed point theorem. To demonstrate the validity of the main result, an example is provided.
Aircraft Failure Rate Prediction Method Based on CEEMD and Combined Model
Authors: Li Wenqiang , Hou Ning
Published: June 2022

Accurate prediction of aircraft failure rate can improve flight safety and spare parts supply efficiency and effectively provide good maintenance and maintenance decisions and health management guidance. In order to achieve accurate prediction of non-linear and non-stationary aircraft failure rate, an aircraft failure rate prediction method based on the fusion of complementary ensemble empirical mode decomposition (CEEMD) and combined model is proposed. Firstly, the complementary set empirical mode is used to decompose the failure rate into multiple components with different frequencies, then the integrated moving average autoregressive model (ARIMA) model and grey Verhulst model are selected to predict different components, the entropy weight method is used to solve the coefficients of the combined model, and finally the prediction results of each prediction model are multiplied by their respective weight coefficients to obtain the final prediction results. The experiment was carried out by taking the actual case application of the failure rate data of the aircraft fuel control system as an example. Seven evaluation functions are used as evaluation criteria to evaluate the performance of the combined model. Experimental results show that the developed combined model is better than other models such as sum of squared error (SSE) and mean absolute error (MAE), which can significantly improve the prediction accuracy of aircraft failure rate. It is proved that the model can improve the accuracy and effectiveness of aircraft failure rate prediction. At the same time, the stability of the model has certain advantages over other models and has a good application prospect.