bluuebunny/crossref_metadata_2025 huggingface dataset:
Acute Rhabdomyolysis in a Child with Multiple Suspicious Gene Variants
Authors: Murakami Aiko , Lau Rhiana L. , Wallerstein Robert , Zagustin Tamara , Kuwada Garett , Purohit Prashant J.
Published: September 2022

Rhabdomyolysis is diagnosed with creatinine kinase (CK) elevation beyond 1000 U/L or ten times above the normal upper limit. Severe episodes can be fatal from electrolyte imbalance, acute renal failure, and disseminated intravascular coagulation. A 13-month-old child was admitted with a CK of 82,090 U/L in the setting of respiratory tract infection-related hyperthermia of 106.9° farenheit. His medical history was significant for prematurity, dystonia, and recurrent rhabdomyolysis. His home medications clonazepam, clonidine, and baclofen were continued upon admission. He exhibited uncontrolled dystonia despite treatment for dystonia. Therefore, sedative infusions and forced alkaline diuresis were begun to prevent heme pigment-induced renal injury. Despite these interventions, his CK peaked at 145,920 U/L, which is rarely reported in this age group. The patient also developed pulmonary edema despite diuresis and required mechanical ventilation. Sedative infusions were not enough for dystonia management, and he needed the addition of a neuromuscular blocking infusion. He finally responded to these interventions, and the CK normalized after a month. He required a month of mechanical ventilation and two and a half months of hospitalization and extensive rehabilitation. We were able to avert renal replacement therapy despite pulmonary edema and an estimated glomerular filtration rate nadir of 21 mL/min/1.73 m2 based on the bedside Schwartz formula. He made a complete recovery and was discharged home. His growth and development were satisfactory for two years after that event. His extensive diagnostic workup was negative. Unfortunately, he died from septic and cardiogenic shock with mild rhabdomyolysis two years later. Prompt recognition, early institution of appropriate therapies, identification of underlying disease, and triggering events are pivotal in rhabdomyolysis management. Evidence-based guidelines are needed in this context.
An Advanced MPPT Scheme for PV Systems Application with Less Output Ripple Magnitude of the Boost Converter
Authors: Chellakhi Abdelkhalek , El Beid Said , Abouelmahjoub Younes
Published: September 2022

The purpose of this paper is to enhance the performance and tracking efficiency of solar photovoltaic systems. This aim can be achieved by operating the photovoltaic array at its optimum power and reducing the output ripple problem of DC-DC converters that affect and stress sensible electronic loads. In view of that, an advanced maximum power point (MPP) tracking (MPPT) scheme, which can guarantee zero oscillation tracking of the accessible MPP and less ripple magnitude on the output side of the DC-DC boost converter, is used. Various simulations are carried out under three conditions of solar irradiance variation, namely, standard test conditions (STC), rapid, and Sin scenarios, using the MATLAB/Simulink® environment, to assess and benchmark the robustness of the tracking of the new MPPT scheme over the celebrated Increment of Conductance (INC) MPPT scheme. Based on the simulation results, the proposed scheme can significantly improve tracking accuracy and reduce the magnitude of ripples on both sides of the boost converter compared to the INC scheme. Certainly, the proposed scheme can provide a shorter time response (0.011 seconds) to locate and track the expected MPP, which is 2.55 times less than that of the INC scheme; a zero power magnitude oscillation instead of 15.9 watts of the INC scheme; and six-time minimization of the magnitude of output voltage ripples compared to the INC scheme. Furthermore, the suggested MPPT scheme has the better tracking efficiency in all scenarios; 99.86%, 99.60%, and 99.62% in the STC, rapid, and Sin scenarios, respectively, with an average value of 99.69% compared to the INC MPPT scheme, which has 94.23%, 95.28%, and 97.87% in the STC, rapid, and Sin scenarios, respectively, with a moderate average tracking efficiency of 95.79%. Finally, the accuracy and tracking performance of the proposed MPPT scheme are verified by real-time examination using the RT-LAB simulator. According to the results obtained, the proposed scheme provides the highest tracking efficiency of 99.80% and 97.77% under the STC and sudden insolation change scenarios, respectively, compared to the INC scheme, which shows, respectively, 97.8% and 96.5% under both scenarios.
Nanorobots with Hybrid Biomembranes for Simultaneous Degradation of Toxic Microorganism
Authors: Refaai Mohamad Reda A. , Manjunatha M. N. , Radjarejesri S. , Ramesh B. , Subbiah Ram , Adugna Nahom
Published: September 2022

Nanorobotics is a modern technological sector that creates robots with elements that are close to or near the nanoscale scale of such a nanometer. To be more specific, nanorobotics has been the nanotechnology approach to designing and creating nanorobots. Also, with the fast growth of robotics technology, developing biomaterials micro- or nanorobots, which convert biological concepts into a robotic device, grows progressively vital. This proposes the development, manufacturing, and testing of a dual–cell membrane–functionalized nanorobot for multifunctional biological threat component elimination, with a focus on the simultaneous targeted and neutralization of the pathogenic bacteria and toxins. Ultrasound-propelled biomaterials nanorobots comprised of the gold nanostructures wrapped in a combination of platelet (PL) and Red Blood Cell (RBC) layers were developed. Biohybrid micro- and nanorobots were small machines that combine biological and artificial elements. They may benefit from onboard actuators, detection, management, and deployment of a variety in medical functions. These hybrid cell walls consist of a variety of structural proteins involved in living organism RBCs and PLs, which provide nanorobots with either a quantity of the appealing biological functionality, with bonding and adhesion to the PL-adhering pathogenic organisms (for example, staphylococcus bacteria) but also neutralization of the pore-forming toxins (e.g., toxin). Furthermore, the biomaterials nanorobots demonstrated quick and efficient extended sonic propulsion for total blood with really no visible bacterial growth and mirrored the movements of genuine cell separation. This propulsion improved the robots’ bonding and detoxifying efficacy against infections and poisons. Overall, combining this diversified physiological activity of hybrid cellular tissue with the energy propulsion of such robotic systems contributed to the dynamic robotics scheme for effective separation and synchronous elimination of various living risks, a significant step towards to development of a broad-spectrum detoxifying robotic framework.
Endothelial Cells Promote Migration of Mesenchymal Stem Cells via PDGF-BB/PDGFRβ-Src-Akt in the Context of Inflammatory Microenvironment upon Bone Defect
Authors: He Sihao , Hou Tianyong , Zhou Jiangling , Ai Qiuchi , Dou Ce , Luo Fei , Xu Jianzhong , Xing Junchao
Published: September 2022

Homing of mesenchymal stem cells (MSCs) to the defect site is indispensable for bone repair. Local endothelial cells (ECs) can recruit MSCs; however, the mechanism remains unclear, especially in the context of the inflammatory microenvironment. This study was aimed to investigate the role of ECs in MSCs migration during the inflammatory phase of bone repair. The inflammatory microenvironment was mimicked in vitro via adding a cytokine set (IL-1β, IL-6, and TNF-α) to the culture medium of ECs. The production of PDGF-BB from ECs was measured by ELISA. Transwell and wound healing assays were employed to assess MSCs migration toward ECs and evaluate the implication of PDGF-BB/PDGFRβ. A series of shRNA and pathway inhibitors were used to screen signal molecules downstream of PDGF-BB/PDGFRβ. Then, mouse models of femoral defects were fabricated and DBM scaffolds were implanted. GFP+ MSCs were injected via tail vein, and the relevance of PDGF-BB/PDGFRβ, as well as screened signal molecules, in cell homing was further verified during the early phase of bone repair. In the mimicked inflammatory microenvironment, MSCs migration toward ECs was significantly promoted, which could be abrogated by pdgfrb knockout in MSCs. Inhibition of Src or Akt led to negative effects analogous to pdgfrb knockout. Blockade of JNK, MEK, and p38 MAPK had no impact. Meanwhile, the secretion of PDGF-BB from ECs was evidently motivated by the inflammatory microenvironment. Adding recombinant PDGF-BB protein to the culture medium of ECs phenocopied the inflammatory microenvironment with regard to attracting MSCs, which was abolished by pdgfb, src, or akt in MSCs. Moreover, pdgfb knockout suppressed the expression and phosphorylation of Src and Akt in migrating MSCs. Src knockout impaired Akt expression but not vice versa. In vivo, reduced infiltration of CD31+ ECs was correlated with diminished PDGF-BB in local defect sites, and silencing pdgfb, src, or akt in MSCs markedly hampered cell homing. Together, these findings suggest that in the inflammatory microenvironment, MSCs migrate toward ECs via PDGF-BB/PDGFRβ and the downstream Src-Akt signal pathway.
A Convolution‐Based Computational Technique for Subdivision Depth of Doo‐Sabin Subdivision Surface
Authors: Khan Faheem , Shakoor Bushra , Mustafa Ghulam , Razaq Sidra
Published: September 2022

Subdivision surface schemes are used to produce smooth shapes, which are applied for modelling in computer‐aided geometric design. In this paper, a new and efficient numerical technique is presented to estimate the error bound and subdivision depth of the uniform Doo‐Sabin subdivision scheme. In this technique, first, a result for computing bounds between Pk (a polygon at kth level) and P∞ (limit surface) of the Doo‐Sabin scheme is obtained. After this, subdivision depth (the number of iterations) is computed by using the user‐defined error tolerance. In addition, the results of the proposed technique are verified by taking distinct valence numbers of the Doo‐Sabin surface scheme.
Consumption Behavior Prediction Based on Multiobjective Evolutionary Algorithm
Authors: Li Jun , Jaharudin Nor Siahbinti , Song Yu
Published: September 2022

Consumption behavior prediction reveals customer attributes, personal preferences, and intrinsic laws. Organizations would benefit from knowing further about customer needs and business desires by monitoring client behavior to provide more precise recommendations and boost acquisition rates. The economics of the customer, buyer groupings, and product quality are only a few of the numerous variables that influence customer behavior. The key issue that has to be resolved at this time is how to filter out useful information from these vast amounts of data to forecast customer behavior. For customer consumption behavior prediction and analysis with an advanced quantitative research process, we proposed the multiobjective evolutionary algorithm, which significantly boosts the accuracy of consumption behavior predictions. The dataset is initially gathered based on consumer preferences and behaviors as the essential information for the entire prediction model. Min-max normalization is used as a component of the preprocessing of the data to get the elimination of redundant and superfluous data. The Word2vec model is utilized for feature extraction, and boosted ant colony optimization (BACO) is employed to choose the best features. Utilizing the suggested multiobjective evolutionary algorithm (MOEA), the predictions are made. The suggested system’s performance is assessed, and the metrics are contrasted with more established methods. The findings demonstrate that the suggested MOEA technique performs well than the traditional ML, XGB, AI, and HNB algorithm methods in terms of accuracy (95 percent), quality of prediction (97 percent), precision (99 percent), recall (93 percent),

F
1

-score (98 percent), and prediction time (50 seconds). Hence, the outcomes show that the regression model is sustainable. The suggested consumption behavior prediction system has demonstrated its efficiency in boosting profitability.
The Comprehensive Evaluation Model of Business Performance Based on Artificial Neural Network
Authors: Wang Lai-Wang , Chu Fu-Lin , Chang Chien-Hua
Published: September 2022

In recent years, domestic enterprises have shown a strong development trend with rapid growth and wide coverage. The construction and operation of enterprise management models are crucial to the development of enterprises, and a good enterprise management model helps enterprises stand firm in market competition and achieve long-term development. Under the background of the new economic normal, the market environment has seen tremendous changes, which have far-reaching effects on the operation and development of enterprises. In order to cope with the impact of the changing economic situation on enterprises, enterprises need to reasonably improve their management models and promote their sustainable and stable development. Through qualitative and quantitative research, scholars have expressed their views on this issue. Combining the existing studies and analyses by scholars at home and abroad, this paper discusses the necessity of the need for innovation in enterprise management in the context of the big data era, discusses the current situation of enterprise management, reveals the problems from both microaspects and macroaspects of enterprises, uses artificial neural networks to establish an enterprise performance assessment model and related policy recommendations, improves the efficiency of enterprises, and puts forward some constructive suggestions for the innovation of enterprise management models.
Connexin 37 Regulates the Kv1.3 Pathway and Promotes the Development of Atherosclerosis
Authors: Liao Minqi , Chen Lihua , Lu Jiongbin , Liang Guangzhu , Yao Yongzhao , Ouyang Shumin , Yang Yanhua , Jian Zhengwei , Guo Suxia
Published: September 2022

Objective. To investigate the mechanism of Connexin 37 (Cx37) and Kv1.3 pathways in atherosclerosis (AS). Methods. ApoE-/- mice were given a high-fat diet to establish atherosclerosis (AS) model, and macrophages in mice were isolated and extracted to transfect Cx37 vectors with silencing or overexpressing, and Kv1.3 pathway blockers were used to inhibit the pathway activity. The indexes of body weight, blood glucose, and blood lipid of mice were collected. The protein and mRNA expression levels of Cx37 and Kv1.3 were detected by reverse transcription-PCR (RT-PCR), Western blot, and immunofluorescence technique. Oil red O staining was used to observe plaque area. Masson staining was used to detect collagen content. The concentrations of chemokine CCL7 were quantified using the ELISA kits. CCK8 was used to detect cell proliferation. Results. Cx37 and Kv1.3 were highly expressed in macrophages of AS mice, and the expression of Kv1.3 and CCL7 decreased after Cx37 was silenced, and the proliferation of macrophages was also decreased. Wild-type mice and AS model mice were treated with Cx37 overexpression vectors and Kv1.3 pathway blocking, and it was found that Cx37 overexpression could improve the blood lipid and blood glucose levels and increase the area of AS in AS mice. However, blocking the activity of Kv1.3 pathway can reduce the levels of blood lipid and blood glucose, increase the body weight of mice, and reduce the area of AS mice. Blocking the activity of Kv1.3 pathway can slow down the plaque development of AS mice and make its indexes close to wild-type mice. And the use of Kv1.3 pathway blockers on the basis of overexpression of Cx37 indicated that inhibition of Kv1.3 pathway activity did not affect the expression of Cx37, but could inhibit the collagen content in the plaque area of AS mice, inhibit the expression of chemokine CCL7, and reverse the effect of Cx37 overexpression. Conclusion. Cx37 can improve the activity of macrophages by regulating the expression of chemokines and the activity of Kv1.3 pathway in AS mice, and enrich macrophages in inflammatory tissues and expand the area of plaque formation.
A Study on the Usefulness of Stochastic Simulation Algorithms for Teaching and Learning in College Physical Education Classrooms
Authors: Xu Ju
Published: September 2022

In order to address the problem of the absolute nature of the evaluation of superiority and inferiority in the evaluation of physical education classroom in universities and the problem of inconsistency in the conclusion of multiple evaluations, we develop an “autonomous advantage evaluation method to highlight one's own advantages,” which uses a probabilistic stochastic simulation algorithm to evaluate the advantages of the evaluated objects by calculating the degree of superiority among them. The method is based on an innovative “base to top” approach, with a high degree of independence. The method was validated by means of an algorithm, and the conclusions were obtained with probabilistic information.
Efficacy of Laparoscopic Totally Extraperitoneal Repair for Inguinal Hernia
Authors: Pan Zhigang , Zhang Minjie , Wang Ling
Published: September 2022

Objective. To assess the treatment efficacy of laparoscopic totally extraperitoneal repair for inguinal hernia. Methods. Between November 2018 and May 2020, 130 patients with inguinal hernias diagnosed and treated in our hospital were randomly recruited and assigned to receive either tension-free hernia repair (control group) or laparoscopic totally extraperitoneal repair (study group) at the random method. All patients received routine care including external traditional Chinese medicine (TCM) application. Outcome measures included surgical indices, numeric rating scale (NRS) scores, infections, and postoperative complications. Results. Laparoscopic surgery is associated with a shorter operation duration, time-lapse before postoperative off-bed activity, and hospital stay, as well as less intraoperative hemorrhage volume compared to tension-free hernia repair in the control group. Patients in the study group had considerably lower NRS ratings after therapy than those in the control group. (

P
<
0.05

). After treatment, the levels of blood cell count (WBC), C-reactive protein (CRP), and procalcitonin (PCT) in the study group were lower than those in the control group (

P
<
0.05

). In the control group, there were 0 cases of hematoma, 3 cases of subcutaneous effusion, 4 cases of urinary retention, 5 cases of scrotal effusion, and 1 case of bladder injury. In the study group, there were 0 cases of hematoma, 1 case of subcutaneous fluid, 1 case of urinary retention, 0 cases of scrotal fluid, and 0 cases of bladder injury. Laparoscopic surgery resulted in a lower incidence of postoperative complications versus traditional surgery (P <0.05). Conclusion. Laparoscopic totally extraperitoneal repair for inguinal hernia improves the intraoperative indices, mitigates postoperative pain, and reduces the risks of infections and complications, with the advantages of short operation duration, less hemorrhage volume, and shorter hospital stay. It shows great potential for clinical promotion.
Development Trend of Digital Physical Education Teaching by Integrating Intelligent Sensor Technology
Authors: Chen Junfei , Zeng Bosi
Published: September 2022

Digital teaching has gradually banned traditional offline teaching, and its advantages are self-evident, but the current digital teaching has certain limitations. Especially in physical education, the key content of physical education is the changes in physical movements; the process is not only complex; the differences between movements are also extremely small; and ordinary digital cannot accurately teach these complex and subtle movements. In this context, this paper mainly studies the application of digitalization of fusion intelligent sensor technology in physical education teaching and combines the characteristics of high precision and recognizable actions of intelligent sensors with digitalization to improve physical education teaching. This paper mainly selects the students majoring in physical education in the second year of school A as the research object to test the effect of digitalization of fusion intelligent sensor technology in physical education teaching. Before the experiment, the research subjects were divided into groups and the T-test was performed, and it was concluded that there was no significant difference between the experimental group and the control group. On this basis, the experimental group and the control group were respectively taught table tennis, gymnastics, martial arts, football, and 100 meters and then tested and tested. The results showed that the experimental group was higher than the control group in table tennis, gymnastics, martial arts, football, and 100 meters test. In the 100 meter test, the boys in the experimental group were 7.13, 6.94, and 6.93 points higher than the control group, and the girls in the experimental group were 2, 1, and 2 points higher than the control group. Overall, after the improved digital teaching, both boys and girls in the experimental group performed better than the control group in table tennis, gymnastics, martial arts, football, and 100 meters. It shows that the effect of the improved digital physical education is remarkable, and it also provides a certain theoretical basis and guidance for the teaching improvement of other courses.
Method to Study the Importance of Automobile Industry Chain Based on the Input‐Output Model
Authors: Wang Junlei , Zhang Fan , Zhang Zhaozhao , Wang Liangliang , Ayipeh Collins Sam
Published: September 2022

This paper proposes a study based on the importance of the automobile industry chain based on the input‐output model (IOM) to verify the importance of the automobile industry chain in the national economy. The available data shows interdependence among various industrial sectors and the automobile industry chain. The same is reflected in the input‐output table. The input data is taken from the input‐output table (IOTB) of the automobile industry chain. A mathematical model was developed that shows the equilibrium relationship indicating the direct and indirect technical as well as economic links amongst the different sectors. The static model of the IOM was selected. The static model herein reflects the technical and economic correlations amongst the sectors during the same period. The same was applied to analyze and study the contemporaneous production process. 153 fields(variables) were selected to verify multiple economic indicators of the automobile industry chain. The conclusion demonstrates that the auto parts and accessories in the automobile industry chain are in the top 10 among the 153 fields, in terms of their consumption coefficient (CC) and contribution degree. The purpose of the research was to verify the significance of the relationship between various fields which can optimize and upgrade the industrial structure. It also provides a scientific basis for formulating strategies and policies of the relevant industry chain.
Study on the Relationship between the Use of Bisphosphonates for Antiosteoporosis and Vertebral Re-Fracture after Vertebroplasty
Authors: Qian Li , Chen Qian , Wang Dashou , Pan Qi , Jian Qianhong , Ma Yinghong
Published: September 2022

Objective. To explore the effect of bisphosphonates after vertebroplasty in patients with osteoporotic vertebral compression fractures (OVCF), and to analyze the relationship between the use of bisphosphonates and vertebral refracture. Methods. A total of 150 patients with OVCF were selected from the pain department of our hospital from January 2018 to May 2020. All patients received vertebroplasty after admission, and were divided into the surgery group (62 cases) and combined with the bisphosphonates group (combined group, 88 cases) according to whether patients had used bisphosphonates after surgery. Before surgery, 1 month, 3 months, 6 months, and 1 year after surgery, visual analogue scale (VAS), Oswestry disability index (ODI), vertebral body and femoral neck bone mineral density (BMD), and Cobb Angle were collected, and the differences among groups were compared to analyze the treatment effect. After the follow-up, patients were divided into two groups according to whether vertebral refracture occurred during the follow-up period. Clinical characteristics, general information, and surgical indicators of patients in the two groups were collected, and related factors of postoperative vertebral refracture were analyzed. Results. There were no significant differences in preoperative VAS score, ODI index, BMD value, and Cobb angle between the two groups

P
>
0.05

. At 12 months after surgery, VAS score, ODI index, and Cobb angle decreased, while BMD value increased in both groups. The VAS score, ODI index, and Cobb angle in the combined group were lower than those in the operation group, while the BMD value was higher than that in the operation group, and the difference was significant

P
<
0.05

. The results of multivariate regression analysis showed that in BMD, no postoperative antiosteoporosis treatment, bone cement leakage, and poor cement diffusion were independent risk factors for vertebral refracture after vertebroplasty in patients with vertebral compression fractures. Conclusion. In order to avoid recurrent fractures in OVCF patients, attention should be paid to BMD, whether patients take antiosteoporosis drugs, whether bone cement permeation occurs and the diffusion of bone cement, etc. The above factors are the main influencing factors leading to recurrent fractures after PKP and PVP in the clinic.
Investigation on the Correlation of Anxiety Degree with Family Atmosphere in Children with Precocious Puberty
Authors: Xiao Yongbei , Li Yamin , Cai Zhengrong , Xie Jiao
Published: September 2022

Objective. This research sets out to explore the correlation of anxiety degree with family atmosphere in children with precocious puberty (PP), so as to provide a reference for future treatment of PP. Methods. Eighty-one cases of PP were visited between January 2021 and March 2021, and their direct relatives were selected as the research population for retrospective analysis. After admission, children and their direct relatives completed a questionnaire survey on the quality of life and social anxiety of children with PP. Children were assigned to the research group and the control group based on their anxiety scores. The intergroup differences in daily activities, diet, and family status, as well as children’s and parents’ psychological status, were identified, and the relationship between anxiety degree in PP children and family atmosphere was discussed. Results. The children’s anxiety score was (6.17 ± 4.26), and they were divided into groups according to the median, with 30 cases in the research group and 51 cases in the control group. The two cohorts were similar in dietary status and children’s physiological status (

P
>
0.05

); however, the research group exhibited a greater number of cases who used electronic products for 2-3 h daily and watched romantic TV series (movies). The daily exercise time of the research group is lower than that of the control group (

P
<
0.05

). In the research group, the monthly family income and the number of family companions and very harmonious families were significantly lower, while the number of divorces or remarriages increased (

P
<
0.05

). The survey results on parents’ psychological status also showed better psychological states in patients in the control group (

P
<
0.05

). Conclusion. The anxiety level of PP children is closely related to the family atmosphere. In future clinical treatment of children with PP, it will also be necessary to pay attention to and adjust the family relationship of the children, which is of great significance for relieving PP-associated anxiety.
Network Pharmacology and Molecular Docking to Explore the Mechanism of Kangxian Decoction for Epilepsy
Authors: Wang Weitao , Zhang Yongquan , Yang Yibing , Gu Lian
Published: September 2022

Purpose. Kangxian decoction (KXD) has been used in clinical practice to treat epilepsy. The purpose of this study was to explore the active components of KXD and clarify its antiepileptic mechanism through network pharmacology and molecular docking. Methods. The components of KXD were collected from the Encyclopedia of Traditional Chinese Medicine (ETCM) database and the literature was searched. Then, active ingredients were screened by SwissADME and potential targets were predicted by the SwissTargetPrediction database. Epilepsy-related differentially expressed genes were downloaded from the Gene Expression Omnibus database. A component-target-pathway network was constructed with Cytoscape. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein‒protein interaction network analysis revealed the potential mechanism and critical targets. Receiver operating characteristic (ROC) curves and box plots in microarray data validated the good diagnostic value and significant differential expression of these critical genes. Molecular docking verified the association between active ingredients and essential target proteins. Results. In our study, we screened the important compounds of KXD for epilepsy, including quercetin, baicalin, kaempferol, yohimbine, geissoschizine methyl ether, baicalein, etc. KXD may exert its therapeutic effect on epilepsy through the following targets: PTGS2, MMP9, CXCL8, ERBB2, and ARG1, acting on the following pathways: neuroactive ligand-receptor interactions, arachidonic acid metabolism, IL-17, TNF, NF-kappa B, and MAPK signaling pathways. The molecular docking results showed that the active ingredients in KXD exhibited good binding ability to the key targets. Conclusion. In this study, we explored the possibility that KXD for epilepsy may act on multiple targets through multiple active ingredients, involving neurotransmitters and neuroinflammatory pathways, providing a theoretical basis for subsequent clinical and experimental studies that will help develop effective new drugs to treat epilepsy.
[Retracted] Prediction of Changes in Tumor Regression during Radiotherapy for Nasopharyngeal Carcinoma by Using the Computed Tomography‐Based Radiomics
Authors: Yang Yu , Wu Jiayang , Mai Wenfeng , Li Hengguo
Published: September 2022

This work aimed to explore the application value of computed tomography (CT)‐based radiomics in predicting changes in tumor regression during radiotherapy for nasopharyngeal carcinoma. In this work, 144 patients with nasopharyngeal carcinoma who underwent concurrent chemoradiotherapy (CCRT) in our hospital from January 2015 to December 2021 were selected. The patients were divided into a radiosensitive group (79 cases) and an insensitive group (65 cases) according to the tumor volume shrinkage during radiotherapy. The 3D Slicer 4.10.2 software was used to delineate the tumor region of interest (ROI), and a total of 1223 radiomics features were extracted using the radiomics module under the software. After between‐group and within‐group consistency tests, one‐way ANOVA, and LASSO dimensionality reduction, three omics features were finally selected for the establishment of predictive models. At the same time, the age, gender, tumor T stage and N stage, hemoglobin, and albumin of the patients were collected to establish a clinical prediction model. The results showed that compared with logistic regression, decision tree, random forest, and AdaBoost models, the SVM model based on CT radiomics features had the best performance in predicting tumor regression changes during tumor radiotherapy (training group area under the receiver operating characteristic curve (AUC): 0.840 (95% confidence interval (CI): 0.764–0.916); validation group: AUC: 0.810 (95% CI: 0.676–0.944)). Compared with the supported vector machine (SVM) prediction model based on clinical features, the SVM model based on radiomics features had better performance in predicting the change of retraction during tumor radiotherapy (training group: omics feature SVM model AUC: 0.84, clinical feature SVM model: 0.78; validation group: omics feature SVM model AUC: 0.8, clinical feature SVM model: 0.58, P = 0.044). Based on the radiomics characteristics and clinical characteristics of patients, a nomo prediction map was established, and the calibration curve shows good consistency, which can be visualized to assist clinical judgment. In this work, the prediction model composed of CT‐based radiomic features combined with clinical features can accurately predict withdrawal changes during tumor radiotherapy, ensuring the accuracy of treatment planning, and minimizing the number of CT scans during radiotherapy.
Application of β-Wollastonite on Bulk Density and Ignition Loss of Clay-Based Ceramic Materials
Authors: Zenebe Chirotaw Getem
Published: September 2022

This work focuses on the effect of β-wollastonite percentage with different particle sizes on the bulk density and weight loss of clay-based ceramics. The ceramic bodies were prepared by mixing clay with a synthesized β-wollastonite (5%, 15%, and 25%) using a solid slip casting method. The clay (75 µm) and β-wollastonite (63, 75, and 125 µm) were mixed and fired at 950°C, 1000°C, and 1050°C of firing temperatures. The fabricated ceramic material exhibited a maximum bulk density of 2.35 g/cm3 on 25% content of β-wollastonite, 63 µm particle size of β-wollastonite, and 1050°C of firing temperature. However, a minimum bulk density of 1.87 g/cm3 was found on 25% content of β-wollastonite, 125 µm particle size of β-wollastonite, and 950°C firing temperature. A minimum of 2.32% ignition loss was recorded on a ceramic specimen that contained 25% of β-wollastonite with a particle size of 125 µm and fired at 950°C of firing temperature. In contrast, a maximum of 4.37% ignition loss was observed at a ceramic body made up of 5% of β-wollastonite content with 63 µm particle sizes and fired at 1050°C. In general, the result shows that the firing temperature, the particle size of β–wollastonite, and the addition of β–wollastonite have a great effect on the bulk density and ignition loss of the clay ceramic materials.
Signal Optimization of Electronic Communication Network Based on Internet of Things
Authors: Feng Bo , Li Wei , Wang Lina
Published: September 2022

In order to solve the problem that many people communicate at the same time, there are many external interference factors, and the signal is prone to instability in the process of electronic communication, the author proposes a signal optimization method for electronic communication network based on the Internet of Things. The method takes the cloud trust mechanism as the dynamic evolution trust relationship between various Internet of Things electronic communication services, performs explicit and implicit uncertainty conversion, calculates the objective function of data communication network performance, and confirms the control strategy. The positioning information of the network nodes in the communication is added to the communication data packet, and the most stable electronic communication path in the network is obtained to form the network topology structure. The Krasovsky method is adopted, and the working state of the nodes of the communication network is divided into the congested state and the normal state, the probability of the two is calculated, and the range of the transition balance is determined, so as to realize the optimization of the stability of the network topology. Experimental results show that the transmission rate of this method has been maintained at about 180 Kb/s; although there is fluctuation, the fluctuation value is small and the transmission rate is very stable. Conclusion. It can improve the accuracy of electronic communication of the Internet of Things and is less affected by external interference factors, and the communication transmission rate is faster.
Axial Compression Behavior of Recycled Concrete Filled Steel Tubular Short Columns after High Temperature
Authors: Liu Xiao , Liu Siying , Hui Yanchuan , Zhang Xuexin , Wang Bing , Zhao Lei
Published: September 2022

This article is devoted to study the axial compression behaviour of recycled concrete‐filled steel tubular (RCFST) columns after high temperature. Several axial compression members’ internal mechanisms are analyzed by combining experimental and finite element analysis (FEA). Firstly, the failure mode of axial compression members is studied by experiments. Then, based on the correct constitutive relationship between recycled concrete and steel, the finite element model is established by ABAQUS software, and theoretical analysis and experimental verification are carried out, which are in good agreement. The effects of different parameters such as temperature, substitution rate, and bond strength of the coefficient on the whole load‐strain curve are compared. The results show that the bearing capacity of recycled concrete‐filled steel tubular columns decreases with the increase in temperature and replacement rate. The bond coefficient between steel tubular and core concrete has little effect on the specimen’s overall axial compressive mechanical properties. The interaction force P rises slightly along the height after the high temperature at the peak load, as it gradually moves away from the cover. In the square section, corners show stress concentration, and bulge deformation occurs first under the condition of axial compression.
Expression of TLR4 Is Upregulated in Patients with Sporadic Acute Stanford Type A Aortic Dissection
Authors: Liu Xinyi , Zhang Ai , Dong Nianguo , Wang Zhiwen
Published: September 2022

Sporadic acute Stanford type A aortic dissection (TAAD) is a serious condition that requires urgent treatment to avoid catastrophic consequences. The purpose of the present study was to explore, firstly, whether TLR4-regulated immune signalling molecules were activated in TAAD patients and, secondly, whether TLR4-regulated inflammatory products interleukin-1β (IL-1β) and CC chemokine ligand 5 (CCL5) could be a promising biomarker for diagnosis in patients with TAAD. Full-thickness ascending aortic wall specimens from TAAD patients (n = 12) and control donors (n = 12) were examined for the expression of TLR4 and its major signalling molecules, in terms of immunity and inflammation. Blood samples from TAAD (n = 49) and control patients (n = 53) were collected to detect the circulating plasma cytokine levels of IL-1β and CCL5. We demonstrated that expression levels of TLR4 and its downstream signalling cascade molecules were significantly elevated. Furthermore, receiver operating characteristic curve analyses showed that elevated IL-1β levels and decreased plasma CCL5 may have diagnostic value for TAAD. In summary, this current study suggests a more generalized pattern of inflammation in TAAD. In addition, TLR4-mediated inflammatory product, such as IL-1β and CCL5, could be novel and promising biomarkers with important diagnostic and predictive value in the identification of sporadic TAAD diseases.
Evaluation System of Mobile English Learning Platform by Using Deep Learning Algorithm
Authors: Cui Yu , Li Hao
Published: September 2022

At present, China’s economic development continues to progress and foreign exchanges are also increasingly frequent. Learning to master the world’s universal pronunciation, English, has become a more important link. However, people’s living habits make it difficult to carry heavy desktop devices for a long time, so mobile English learning platform meets the development needs of people’s English teaching. Based on the existing English mobile learning platform, this paper puts forward the concept of integrating artificial intelligence and deep learning technology into it. Through deep learning, the learning status and learning situation of students in the process of English learning are extracted, so as to analyze the needs and learning interests of each student in English learning and then push corresponding English materials to each student, which improves the efficiency of English learning. In addition, deep learning can also model the data of students’ behaviors and build a language vector feature extraction mechanism and translation quality evaluation model, so as to carry out certain intelligent auxiliary correction and correction on students’ English grammatical expressions and spoken English. The research in this paper has achieved good results through practice. The practice results show that the integration of deep learning into the existing mobile English teaching platform can optimize the functions of the existing platform, provide more ideas for the development of online English learning, and has good theoretical and practical value.
Model for Evaluating the Technical and Tactical Effectiveness of Tennis Matches Based on Machine Learning
Authors: Liu Lei
Published: September 2022

As the level of tennis improves, the ability and strategy to play in the game determine the responsibility for the outcome of the game. It is committed to improving the professional and strategic level of Asian tennis players and narrowing the gap with high-level European and American tennis players. The purpose of this paper is to study the application of machine learning in the study of the evaluation model of the technical and tactical effectiveness of tennis matches, and proposes the decision tree algorithm, artificial neural network, reinforcement learning algorithm, and related concepts of tennis matches. Therefore, this paper selects Federer’s technical and tactical games from 2013 to 2017 as the research object. And by paying attention to the application characteristics of Federer’s methods and strategies in each stage, a detailed statistical analysis of the data is carried out point by point. The exploratory outcomes show that through the AI calculation, it is found that the incredible skill and vital sufficiency of Federer’s hard court game change around 0.600, and the typical worth is 0.594. Particular and vital efficiency showed a sluggish recuperation in 2017.
Application of Artificial Intelligence-Based Sensor Technology in the Recommendation Model of Cultural Tourism Resources
Authors: Hou Shuang , Zhang Shihui
Published: September 2022

Aiming at the lack of theoretical basis for the development of cultural tourism resources, an application method of artificial intelligence-based sensor technology in the recommendation model of cultural tourism resources is proposed. Sensor network is an application-based network. Compared with traditional wireless communication network, it has the characteristics of large node scale, self-organized multihop, unattended, and no communication infrastructure. Combined with artificial intelligence sensor technology, this paper attempts to construct an evaluation index system and evaluation model for cultural tourism resources, and uses this model to conduct a comprehensive evaluation of cultural ecotourism resources in the western region. The experimental results show that theEvalue of the evaluation result of cultural tourism resources in the western region is 6.346, which has a good development value. Secondly, from the specific evaluation results of each level, the western region has the highest cultural tourism standard, which has 6.605. Cultural tourism resources, landscape resources, and development conditions scored lower. Among them, cultural tourism resources and landscape resources have the highest score (7.186), and the economic and cultural field has the lowest score (6.092). Among the cultural tourism development conditions, the policy conditions are high (6.823), but the location conditions are very low, only 4.879 points. Therefore, it is found that the model takes cultural tourism landscape resources, cultural tourism environment resources, and cultural tourism development conditions as the content of cultural tourism resources evaluation, which is comprehensive and has strong hierarchy and pertinence; fuzzy comprehensive evaluation method has strong objectivity to determine the weight and the value classification; and weighting evaluation model of cultural tourism resources has rationality and generalizability and can provide a scientific basis for the classification and evaluation of cultural tourism resources and the planning and development of cultural tourism.
Potential Molecular Mechanism of Guishen Huoxue Decoction against Intrauterine Adhesion Based on Network Pharmacology
Authors: Zhang Wenyan , Yuan Yuan , Huang Guangrong , Xiao Jing
Published: September 2022

Objective. Intrauterine adhesion (IUA) represents an endometrial repair disorder that is associated with menstrual disorders, recurrent pregnancy loss, and infertility. This study aimed to explore the underlying biological mechanisms of Guishen Huoxue decoction for the treatment of IUA based on network pharmacology. Methods. The selection of active compounds for Guishen Huoxue decoction and prediction of relevant targets were performed by the TCMSP and Swiss Target Prediction databases, respectively. The targets of IUA were obtained by three databases, including Online Mendelian Inheritance in Man (OMIM), DisGeNET, and GeneCards. The drug-disease regulatory network was constructed via Cytoscape software, following the acquisition of common genes of active compounds of drug Guishen Huoxue decoction and disease IUA, which was carried out through Venny software. Protein-protein interaction (PPI) network and function enrichment analyses were performed. Results. According to the data obtained from TCMSP, a total of 200 potential active compounds of Guishen Huoxue decoction and their related targets (1068) were screened by the Swiss Target Prediction database. 1303 disease targets and 134 common targets were identified. The drug-disease regulatory network showed that 165 active compounds were found to be involved in the treatment of IUA. Among 134 common targets, AKT1, SRC, TP53, VEGFA, and IL-6 were predicted as core genes against IUA. PI3K-Akt, Rap1, Ras, and AGE-RAGE were the main signaling pathways that participated in the treatment of Guishen Huoxue decoction for IUA. Conclusion. The active compounds of Guishen Huoxue decoction confer therapeutic effects against IUA by regulating fibrosis, inflammation, and oxidative stress through major signaling pathways such as PI3K-Akt and AGE-RAGE.