bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Isothermal Signal Amplification Technique in the Etiological Diagnosis of Gonorrhea and Drug Resistance Gene Detection
Authors: Chen Wei , Zhang Jinling , Li Dongsheng , Wang Yue
Published: July 2022

Background: Isothermal signal amplification technique is developed based on the rolling ring amplification mechanism of cyclic DNA molecules in nature. This technique plays an extremely beneficial role in gonorrhea pathogen identification and drug resistance gene detection. Aims: This study analyzes the isothermal signal amplification techniques in the etiological diagnosis of gonorrhea and drug resistance gene detection. Materials and Methods: Urethral, cervical secretion, or prostatic fluid samples from 322 cases of gonorrhea collected from January 2018 to December 2021 at the STD clinic of our hospital dermatology department were selected for direct smear examination and gonococcal culture examination; DNA was extracted from urethral, cervical secretion, or prostatic fluid samples and then used for pathogen identification by SAT assay and rolling loop nucleic acid amplification technique, smear examination and pathogen culture examination methods, SAT assay, and isothermal signal amplification technique for comparative sensitivity and specificity analysis. Results: The highest rate of gonorrhea positivity was for the urine rolling loop nucleic acid amplification technique, followed by the swab rolling loop nucleic acid amplification technique, and the lowest rate of gonorrhea positivity was for the urine SAT test. The difference in the positivity rate between the two urine testing methods was statistically significant (

P
<
0.05

). The highest sensitivity of the urine rolling loop nucleic acid amplification technique method for the detection of gonorrhea pathogens and the lowest sensitivity of the urine SAT method were statistically significant (

P
<
0.01

). The differences in sensitivity and specificity between the swab rolling loop nucleic acid amplification technique and the swab SAT method were not statistically significant (

P
>
0.05

). ROC curves were plotted based on sensitivity and specificity, with swab SAT assay (

A
U
C
=
0.998

) > rolling loop nucleic acid amplification technique (

A
U
C
=
0.981

). Comparing the negative rates of urine and swab rolling loop nucleic acid amplification technique and urine SAT assay, the differences were not statistically significant (

P
>
0.05

). Conclusion: The isothermal signal amplification technique improves the shortcomings of gonorrhea pathogen identification means and drug resistance gene detection methods, with good detection sensitivity and specificity, simple operation, low price, and easy promotion, which has obvious advantages in clinical applications and epidemiological studies.
SARS-CoV-2 and Subacute Thyroiditis: A Case Report and Literature Review
Authors: Salehi Amir Mohammad , Salehi Hossain , Mohammadi Hossein Ali , Afsar Jamileh
Published: July 2022

Introduction. Subacute thyroiditis (SAT) is an inflammatory disorder of the thyroid gland, usually triggered by a recent viral or bacterial infection of upper respiratory tracts. The disease is characterized by neck pain radiating to the ears and thyroid gland tenderness. In most cases, it is associated with a transient episode of hyperthyroidism, which is followed by euthyroidism. However, sometimes, it manifests itself with hypothyroidism. Case Presentation. The present report described a case of SAT who was a 55-year-old man presenting to an endocrine clinic with tachycardia, tremor, and neck pain radiating to the jaw and ears. His thyroid function test revealed thyrotoxicosis, and thyroid ultrasound findings were consistent with SAT. The patient reported a history of COVID-19 about 15 days before presentation, which was confirmed by a positive PCR test for SARS-CoV-2. Conclusions. It is of great importance for physicians to note that thyrotoxicosis in a patient with a recent history of COVID-19 can be due to SAT. Therefore, they should not begin antithyroid drugs without ordering proper investigations.
Load Balancing in Edge Computing Using Integer Linear Programming Based Genetic Algorithm and Multilevel Control Approach
Authors: Zhang Rui , Shu Hong , Navaei Yahya Dorostkar
Published: July 2022

Due to the proliferation of requests in heterogeneous resources in edge computing, the existence of a large number of tasks and workloads in virtual machines in the edge computing environment is inevitable. Thus, load balancing strives to facilitate an even distribution of workload across available resources. Its purpose is to provide continuous service and to ensure fair load distribution among resources. Load balancing, with the aim of minimizing response time for tasks and improving resource efficiency, tries to do the proper mapping of tasks among virtual machines at a lower cost. Flow scheduling, on the other hand, assigns a task (group of tasks) to computational resources by prioritizing tasks, so that the relationship between them is maintained. Therefore, in this research, a hierarchical control framework for load balancing and assignment of tasks in edge computing services is presented in order to create load balancing. In the proposed method, in the first level, the genetic algorithm receives a set of tasks in a workflow. Genetic algorithm prioritizes and assigns tasks to resources according to time constraints, resource processing power, resource availability, and task cost. For this purpose, the integer linear programming optimization in the evaluation function of the genetic algorithm will be utilized. In the second level, considering the past load distribution in edge resources, we estimate the probability of load distribution among sources according to hidden Markov model (HMM). Finally, in order to optimally map tasks to the virtual machines in each host, we will use game theory with service quality factors as an evaluation function. Previous methods have provided a hierarchical control framework that aims to achieve conflicting goals within a data center, but does not use linear programming. Considering the use of service quality criteria as evaluation function parameters in heuristic and optimization methods in this research, it is expected that the results of this research will improve compared to previous methods.
[Retracted] Maintenance and Management Technology of Medical Imaging Equipment Based on Deep Learning
Authors: Liu Bin , Tong Lingli , Liu Yanmei , Guo Zhizhang
Published: July 2022

Medical equipment maintenance in modern hospital management is an emerging marginal discipline which is one of the important branches of hospital management with the dual function of management and technology. The good or bad management of medical equipment directly affects the quality of hospital work. With the development of science and technology, the scale of hospitals continues to expand and develop; hospitals are equipped with more and more medical equipment and its technical content is getting higher and higher, which makes the medical equipment management and maintenance practitioners more demanding. However, the situation of existing medical equipment management and maintenance personnel is not optimistic. For this reason, this paper designs a good database structure, which can effectively reduce data redundancy and better avoid the problems that may occur during the database operation. As a reference guideline for database design, the three database paradigms can be studied and understood in depth to help software designers design more “robust” databases, enabling effective maintenance and management of medical imaging equipment.
Accident Detection in Autonomous Vehicles Using Modified Restricted Boltzmann Machine
Authors: Roohullah  , Wahid Fazli , Ali Sikandar , Abbasi Irshad Ahmed , Baseer Samad , Khan Habib Ullah
Published: July 2022

Accident detection in autonomous vehicles could save lives by reducing the time it takes for information to reach emergency responder. One of the most common reason for the death of humans is accident. Indeed, it was determined throughout the survey that road accidents are indeed the second greatest cause of death in the United States for people aged 30 to 44 years, representing for 1/3 among all deaths. The transportation industry is increasingly relying on mathematical methods and new data assets to detect injuries. Many machine learning and deep learning models have already been proposed for accident detection but still there is much space for further improvement to be done to save human lives in case of accident detection, if accidents are not identified well. In our present study, we proposed modified restricted Boltzmann machine for accident detection. Our proposed methodology consists of the following steps. In the first step, we took different accidental and nonaccidental images as an input. In the second step, we applied our proposed deep learning technique modified restricted Boltzmann machine. In the third step, when weight acceleration and coefficient adjustments are run as a generalization mechanism, then we check our model performance after applying through multiple procedures. As a result, multiple images are classified as accidental and nonaccidental images of vehicles. Proposed methodology has been applied for data set, and data have been divided into different training and testing ratios. The proposed MRBM model has an accuracy of 98% in classification of both accidental and nonaccidental images of vehicles. The proposed model outperforms the competition significantly than other in which they are compared like artificial neural network, support vector machine, and restricted Boltzmann machine techniques.
Media Content Mining Based on Artificial Intelligence and Network Interaction
Authors: Kang Kai , Wang Zhixue , Zhang Hongwu
Published: July 2022

In recent years, due to the explosive growth of social media information, mining hot information in social media has become a research direction of great concern. In this paper, Python crawler technology is used to crawl the semi-structured text data of food safety news from static web pages and dynamic web pages. After preprocessing, the structured text data required to establish a document clustering algorithm (CASC) based on a convolutional neural network is obtained. Using the feature extraction ability of convolutional neural network and self-encoder, while preserving the internal structure of the original data to the greatest extent, it is embedded into the low-dimensional potential space for clustering. Finally, it is compared with the performance of the K-means algorithm and spectral clustering algorithm. The experimental results show that the CASC algorithm reduces the running time and time complexity of the algorithm on the premise of ensuring clustering accuracy. The CASC algorithm is superior to the k-means algorithm and spectral clustering algorithm in precision, recall, and composite index. At the same time, the running time is 91 seconds faster than the K-Means algorithm and 5 seconds faster than the spectral clustering algorithm.
Comparison of Rapid Rehabilitation after Anterior Cruciate Ligament Reconstruction with Tensioning Technique and Traditional Rehabilitation
Authors: Jin Tianfu , Li Yanlin , Yang Guiran , Liao Xinyu , Wang Guoliang , Wang Fuke
Published: July 2022

To investigate the efficacy of a fast rehabilitation program for the recovery of knee joint function after arthroscopic autologous hamstring tendon transplantation for reconstruction of the anterior cruciate ligament (ACL), from January 1, 2017, to March 31, 2019, a total of 65 patients with ACL injury were randomly divided into a study group and a control group. Both groups were treated with autologous hamstring tendon to reconstruct the anterior cruciate ligament, arthroscopic transplantation, and decompression techniques. The research group was treated with a fast rehabilitation program. The control group was treated with traditional rehabilitation program. Knee flexion angles were measured at 2, 4, and 8 weeks postoperatively. KT-1000 knee anterior stability was measured at 3, 6, and 12 months after operation. Knee function was assessed by subjective knee function assessment scale (IKDC) and Lysholm knee score. The knee curvature, KT-1000 measurement, IKDC score, and Lysholm score were compared between the two groups before and after treatment. KT-1000 measured value, IKDC score, and Lysholm score in 2 groups were significantly improved 3, 6, and 12 months compared with those before treatment, and the difference was statistically significant (

P
<
0.001

). Comparison between the two groups: 2 weeks, 4 weeks, and 8 weeks after treatment, the knee curvature in the study group was better than that in the control group, and the difference was statistically significant (

P
<
0.001

); there was no significant difference in the measured values of KT-1000 between the two groups 3, 6, and 12 months after treatment (

P
>
0.05

); IKDC score and Lysholm score in the study group 3 and 6 months after treatment were significantly better than those in the control group, with statistical significance (

P
<
0.001

); there was no significant difference in IKDC score and Lysholm score between the two groups 12 months after treatment (P >0.05). Autograft hamstring tendon transplantation and tense-reducing technique for anatomical reconstruction of anterior cruciate ligament under arthroscopy combined with rapid rehabilitation program can quickly, safely, and effectively restore the knee function of patients, greatly shortening the rehabilitation period of patients.
Research on Nonlinear Time Series Processing Method for Automatic Building Construction Management
Authors: Liu Yunbing
Published: July 2022

Aiming at the nonlinear time series of automatic building construction management, a neural network prediction model is proposed to analyze and process the nonlinear sequence of deformation monitoring number cutter. The specific content of this method is as follows: for the noise problems existing in deformation monitoring data, a wavelet is used to denoise the preprocessing; for the BP network and RBF network commonly used in neural networks, the performance of the two networks is compared and demonstrated by MATLAB program, which proves that RBF neural network can significantly improve the accuracy of deformation prediction. By comparing the results, the maximum relative error of BP network prediction is 18.59%, while the maximum relative error of RBF network prediction is 29.16%, and the average relative error of 13P network prediction is 7.02%, while the average relative error of RBF network prediction value is 10.5%. The comprehensive error of network prediction is 6.1%, RBF network prediction is 8.52%, the standard deviation RMSE of BP network prediction error is 15.347, and that of RBF network prediction error is 21.401, and it shows that the prediction accuracy of BP network is higher than that of RBF network.
Effect of Proprioception and Balance Training Combined with Continuous Nursing on BBS Score and HSS Score of Patients Undergoing Total Knee Arthroplasty
Authors: Lin Hong , Xu Aihua , Wu Heping , Xu Hanchun , Lu Yifang , Yang Hongping
Published: July 2022

Background. Total knee arthroplasty is one of the most effective methods for the treatment of end-stage knee osteoarthritis, but 10% of patients still show insufficient function, strength, and mobility. Continuous nursing service plays an important role in the rehabilitation of patients undergoing total knee arthroplasty. For discharged and convalescent patients, the traditional follow-up model cannot solve the nursing problems of discharged patients. How to meet the health needs of discharged patients under the limited nursing resources has become an existing problem. Objective. To explore the effect of proprioception and balance training combined with continuous nursing on Berg balance scale (BBS) score and Hospital for Special Surgery (HSS) score of patients undergoing total knee arthroplasty (TKA) is the objective of this study. Methods. Sixty patients undergoing TKA in our hospital from December 2019 to April 2021 were enrolled. The patients were randomly assigned into the control group and the study group. The control group received continuous nursing, and the study group received proprioception and balance training combined with continuous nursing. Results. The nursing satisfaction of the study group was higher than that of the control group (

P
<
0.05

). The HSS scores at discharge, 1 month, 3 months, and 6 months after discharge in the study group were higher than those in the control group (

P
<
0.05

). It was higher in the study group than in the control group at 1 month, 3 months, and 6 months after discharge (

P
<
0.05

). The pain catastrophizing score of the study group at discharge was lower than that of the control group at 1 month, 3 months, and 6 months after discharge (

P
<
0.05

). The BBS scores at discharge, 1 month, 3 months, and 6 months after discharge in the study group were higher than those in the control group (

P
<
0.05

). The Lindmark balance scores at discharge, 1 month, 3 months, and 6 months after discharge in the study group were lower than those in the control group (

P
<
0.05

). Conclusion. Proprioception and balance training combined with continuous nursing can effectively promote the recovery of knee joint function of patients after TKA, enhance patients’ pain catastrophizing grade, enhance patients’ quality of life, effectively promote patients’ knee joint function and BBS score, and promote the improvement of disease.
Study and Analysis on Stress Safety Judgment Method of Heavy Vehicle Rolling on Long-Distance Pipeline
Authors: Shi Ning , Jiang Jinxu , Geng Lin , Zhang Liwen , Niu Yakun , Wang Kaimeng
Published: July 2022

With the rapid increasing mileage of China’s long-distance oil and gas pipelines, the intersection construction with other civil engineering, encroachment by invading the pipeline route, and other third-part problems occurred occasionally. Heavy vehicles rolling the serving pipeline have become one of the inevitable safety risks. The field test method of three in-service long oil and gas pipelines under heavy vehicle rolling is elaborated. The pipeline stress and soil pressure during tests are monitored and analyzed. The parametric model of pipe mechanical response under heavy vehicle rolling and stacking load is established, and the quantitative feedback of each parameter on pipeline stress safety response under heavy vehicle rolling is formed. The results show that the influence factors such as vehicle weight, vehicle speed, buried depth of pipeline, horizontal distance and cover plate on the stress state, vertical displacement state, and contact stress of pipe soil interface are highly consistent with the finite element method and test method, which could be a guideline for the safety assessment at rolling site.
Effect of Vitapex Combined with AH-Plus Paste on Inflammation in Middle-Aged and Elderly Patients with Periodontal-Endodontic Disease
Authors: Hu Rong , Zhang Fulan , Guo Xiangyu , Jing Youren , Lin Xiaowan , Tian Liping
Published: July 2022

Aims. To investigate the effect of Vitapex combined with AH-plus paste on inflammation in middle-aged and elderly patients with periodontal-endodontic disease. Materials and Methods. A total of 80 teeth of middle-aged and elderly patients with the periodontal-endodontic disease who were treated in our hospital from June 2020 to June 2021 were selected as the research objects and were divided into comparison group and treatment group with 40 teeth each according to different treatment methods. Among them, the comparison group was filled with zinc oxide clove oil paste gutta-percha, and the treatment group was filled with Vitapex combined with AH-plus paste. The changes in apical cross-section sealing performance, periodontal pocket depth (PD), and gingival index (GI) of the two groups before treatment and after 6 months of follow-up were observed and compared, and X-ray analysis was performed. Results. There was no significant difference in the level of periodontal indexes and serum inflammatory indexes between the two groups before treatment (

P
>
0.05

). After treatment, the levels of PD, BI, PLI, and GI in the two groups were significantly lower than before treatment (

P
<
0.05

). The differences in IL-6, IL-10, TNF-α, and IL-1β after treatment were significant (

P
<
0.05

). There was no significant difference in the root canal area data of each cross-section between the two groups when the root canal was filled with root filling paste at different positions from the apex (

P
>
0.05

). After root canal filling with root canal paste, the cross-sectional area from different parts of the root canal in the treatment group was significantly smaller than comparison group (

P
<
0.05

). After 6 months of treatment, it was found that CEJ-BD and CEJ-AC in the treatment group were significantly lower than those in the comparison group (

P
<
0.05

). Conclusion. Vitapex combined with AH-plus paste filling can effectively treat middle-aged and elderly periodontal-endodontic disease, which provides a certain reference for the clinical treatment of middle-aged and elderly periodontal-endodontic disease.
Application of Image Processing Sensor and Pattern Recognition in Detection of Bearing Surface Defects
Authors: Wu Qinghong , Zhu Minghui
Published: July 2022

In order to solve the problem that the traditional detection technology can not meet the requirements of online detection, a visual detection device for bearing inner ring defects based on image processing and pattern recognition is proposed in this paper. The device systematically designs an image acquisition device of bearing inner ring based on CCD. In the hardware scheme, the appropriate lens, camera, light source, and other related hardware are selected according to the actual needs, a complete image acquisition platform of bearing inner ring is built, and the software function design is completed. The simulation results show that the qualified rate of machine detection is 98.6%, the missed detection rate is 0, and the false detection rate is 1.4%, which are better than manual detection. Conclusion. The test results show that the bearing inner ring defect detection system can detect the surface defects of bearing inner ring quickly, stably, and reliably, and the detection efficiency and accuracy are higher than the original manual detection method, so it has a good application prospect.
Effect of Moisture on the Macro Failure Characteristics of Weakly Consolidated Mudstone: Mesomechanism
Authors: Xu Jiahui , Li Guichen , Rong Haoyu , Gomah Mohamed Elgharib , Sun Changlun , Li Jinghua , Zhang Suhui
Published: July 2022

Mudstone, whose significant characteristic is water-weakening, widely exists in all kinds of geotechnical engineering, which brings great security risks to engineering safety. In this paper, through a series of macro and meso test methods, the macro and meso action mechanism of water on the weakly consolidated plane of mudstone was studied. In the uniaxial compressive strength test, the mudstone cementation plane was the main part of the fracture derived. Under the moist state, the strength of mudstone would decrease significantly, which was inversely correlated with relative moisture content. In the case of flooding, mudstone cracking occurred only along the cementation plane. Through ESEM+mapping test, results showed the humidification curing caused obvious damage to the cemented plane, where sodium and calcium were lost without a certain cause. The cemented plane was rich in kinds of clay minerals in mesoscale and presented an inhomogeneous state. The surface hardness data obtained from nanoindentation were discrete and difficult to quantitatively evaluate the mesomechanical properties. However, compared with the dry state, the data set of the moist state had a significant decline, showing a weakening effect. The mudstone is prone to fail along these weakly consolidated planes. Moisture intrudes into the bedding plane further deteriorating their consolidation.
Aesthetic Value Evaluation for Digital Cultural and Creative Products with Artificial Intelligence
Authors: Liang Dan
Published: July 2022

The domestic cultural and creative industry has abundant resource advantages and broad development space. The design for cultural and creative products has evolved rapidly with the objective to improve its quality. The cultural and creative industries have seen rapid growth in the recent years wherein digital technologies have been incorporated with the traditional methodologies. The digital cultural and creative aspect acts are extremely important in the dissemination of traditional culture on the network platform. This is also supported by the state vigorously to implement innovative industrial policies. However, the adoption of digital technology in the cultural and creative industry is a novel approach. But there exists lack of understanding in terms of its nature and development protocols. It is thus necessary to study relevant theories to guide the development of digital cultural and creative industry. The increasingly prosperous aesthetic culture, especially development for cultural and creative industries, has comprehensively improved aesthetic value of the cultural and creative products. Therefore, the methods to evaluate and realize the aesthetic value of digital, cultural, and creative products are extremely important and relevant in the present day and age. In this study, neural network is used to design an improved back propagation (BP) network in order to evaluate the aesthetic value of digital cultural and creative products. At the outset, the basic idea, structural characteristics, the learning algorithm, and its flow of functioning in the BP network are analyzed. Then, an aesthetic value evaluation model of digital cultural and creative products with BP network is developed. Next, considering the shortcomings of BP network, a segmentation adaptive strategy is used to improve the view field and step size for artificial fish swarm algorithm (AFSA). Finally, the improvised algorithm is verified wherein the simulation results reveal improvement in algorithm convergence speed as well as improvement in optimal solution accuracy as part of the adaptive improvement approach.
A Validated RP-HPLC Method for Simultaneous Determination of Cefixime and Clavulanic Acid Powder in Pediatric Oral Suspension
Authors: Nepal Utsav , Panthi Vijay Kumar , Chaudhary Namindra Prasad , Chaudhary Samip
Published: July 2022

A new reverse phase high-performance liquid chromatography (RP-HPLC) method was developed and validated for the simultaneous estimation of pediatric oral powder formulation containing cefixime (CFX) and clavulanic acid (CVA). In this research, an analytical C18 (4.6 mm × 25 cm), 5 μm column was used for chromatographic separation with a mixture of methanol and water containing disodium hydrogen phosphate in ratio of 20 : 80 v/v as the mobile phase (pH 5.5 adjusted with orthophosphoric acid) at a flow rate of 1.0 mL/min. The detecting wavelength and run time were 220 nm and 15 min, respectively. Moreover, the column temperature was maintained at 30°C. The analytical method was validated prior to meeting the conditions specified by International Conference on Harmonization (ICH) and the parameters were specificity, linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, robustness, and solution stability. The calibration curve was found to be linear between the concentration ranges of 0.024–0.036 mg/mL and 0.032–0.048 mg/mL for CFX and CVA, respectively. Furthermore, the LOD and LOQ of CFX were 0.0008 and 0.0025 μg/mL, respectively. Accordingly, LOD and LOQ of CVA were 0.0021 and 0.0065 μg/mL, respectively. The accuracy of the optimized method was examined by recovery studies and the mean recovery was observed to be 98.96% and 99.05% for CFX and CVA, respectively, at 100% spiked level. The repeatability testing for both standard and sample solutions revealed that the method is precise within the acceptable range and the %RSD of the precision was <2%. In addition, the findings of specificity, linearity, accuracy, precision, robustness, LOD, LOQ, and solution stability studies of both CFX and CVA were within the criteria of acceptable limit as well.
NAV3 Is a Novel Prognostic Biomarker Affecting the Immune Status of the Tumor Microenvironment in Colorectal Cancer
Authors: Li Menglong , Wang Zhiqiang , Dong Shuai , Xu Yang
Published: July 2022

Colorectal cancer (CRC) is one of the most common malignant tumors in the world. Tumor microenvironment (TME) plays a crucial role in the development of CRC. With the deep understanding of TME function, growing studies have demonstrated that alteration in tumor-infiltrating immune cells (TICs) and gene expressions are associated with clinical outcomes of various tumors. In this study, we aimed to recognize critical prognostic genes involved in immune states in TME of CRC. Hence, the proportion of TICs and the number of immune and stromal components in CRC samples from TCGA datasets were calculated by the use of CIBERSORT and ESTIMATE calculation methods. Different assays were applied to collect differential expression genes (DEGs) shared by the ImmuneScore and StromalScore. DEGs were further analyzed by the use of univariate Cox regression. Our attention focused on neuron navigator 3 (NAV3) which was highly expressed in CRC specimens and associated with an advanced clinical stage and poor prognosis of CRC patients. KEGG assays revealed that NAV3 may be involved in Alzheimer disease, amyotrophic lateral sclerosis, Huntington disease, FoxO signaling pathway, and human papillomavirus infection. Correlation assays showed that macrophage M0 and B cells memory, NK cells activated, dendritic cells resting, T cells CD4 memory activated, and T cells CD8 were correlated with NAV3 expression, indicating that NAV3 may represent the immune status of TME. Finally, RT-PCR confirmed that NAV3 expression was distinctly increased in CRC cells, and its knockdown suppressed the proliferation of CRC cells. Overall, NAV3 could be used as a novel predictor for TME of CRC and might be a novel prognostic biomarker. In the future, drugs targeting NAV3 might be developed as a potential immunotherapy for CRC patients.
Experimental Investigation on Influence of Acidic Dry-Wet Cycles on Karst Limestone Deterioration and Damage
Authors: Zhang Yan , Wang Zicheng , Su Guoshao , Wu Zhekang , Liu Fengtao
Published: July 2022

This study is aimed at the problem of limestone deterioration and damage caused by the combination of acid rain and the dry-wet cycle in Guilin. Samples of limestone were taken to study the influence of acidic dry-wet cycles on limestone deterioration and damage. This was accomplished by performing nuclear magnetic resonance (NMR) measurements and inductively coupled plasma atomic emission spectrometer measurements on the limestone samples. The study found that with an increase in the number of cycles, the

T

2

curve of the rock continuously shifts to the right, but the range of movement still decreases with pH increasing values. The

T

2

spectrum area, rock porosity, porosity deterioration, mass loss rate, and water absorption rate all increase with an increase in the number of cycles, but the growth rate continues to decrease, and the increase is negatively correlated with pH. After the dry-wet cycles, the mass concentration of each element in the beaker is Ca, Mg, and Fe in order from high to low, and the mass concentration of each main element in the reaction solution increases with the increase in the number of acidic dry-wet cycles.
Phytochemical Analysis and Study of Antioxidant and Antimicrobial Activities of Two Parts of Cupressus arizonica Essential Oils
Authors: Cherrad Sara , Jaouadi Imane , Bouyahya Abdelhakim , Koursaoui Loubna , Aouane El Mahjoub , Satrani Badr , Sultan Mujeeb A. , Alotaibi Amal , Ullah Riaz , Ghanmi Mohamed , Chaouch Abdelaziz
Published: July 2022

The present work aimed to determine the difference in the chemical composition of essential oils isolated from two parts of Cupressus arizonica and to evaluate their in vitro antimicrobial and antioxidant effects. The yields of the essential oil obtained by hydrodistillation from the leaves and cones were 0.85% and 1.29%, respectively. The chemical analysis of the constituents of the two essential oils of Cupressus arizonica was carried out by using the GC and GC/MS techniques. The results of this analysis show that the leaves are dominated by cis-muurola-4 (14), 5-diene (21.27%), umbellulone (19.88%), α-pinene (9.39%), and α-muurolene (7.87%7); on the other hand, the cones are rich in α-pinene (51.07%) accompanied by other variable content constituents, myrcene (17.92%), limonene (9.66%), β-pinene (4.92%), meta-cymenene (2.6%), and α-terpineol (2.38%). The antimicrobial activity against four bacterial strains, four wood decay fungi, and three mould strains were determined using the agar-agar dispersion method. The studied essential oils exhibited moderate antimicrobial properties, which demonstrates the sensibility of all strains tested with the exception of wood rot fungi to which they do not have activity against all concentrations tested. The dosage of antioxidant activity was evaluated using DPPH scavenging and ferric ion reducing power (FRAP). The results indicate that the essential oils from cones of Cupressus arizonica possess a strong antioxidant activity (lower IC50) IC50 = 0.098 ± 0.008/EC50 = 0.646 ± 0.02) in comparison with those from the leaves (IC50 = 5.297 ± 0.09/EC50 = 2.335 ± 0.36). The results suggest that both essential oils could be used as a source of treatment for bacterial infections and also as natural antioxidant substances.
Barycentric Rational Collocation Method for Nonlinear Heat Conduction Equation
Authors: Li Jin
Published: July 2022

Nonlinear heat equation solved by the barycentric rational collocation method (BRCM) is presented. Direct linearization method and Newton linearization method are presented to transform the nonlinear heat conduction equation into linear equations. The matrix form of nonlinear heat conduction equation is also obtained. Several numerical examples are provided to valid our schemes.
[Retracted] Peroxisome Proliferator‐Activated Receptor Gene Knockout Promotes Podocyte Injury in Diabetic Mice
Authors: Yan Rui , Zhang Ye , Yang Yuxing , Liu Lingling , Liu Lirong , Guo Ziwei , Yu Haiyan , Wang Yuanyuan , Guo Bing
Published: July 2022

Objective. To investigate the effects of peroxisome proliferator‐activated receptor (PPARγ) expression on renal podocyte in diabetic mice by conditionally knockout mouse PPARγ gene. Methods. Wild‐type C57BL mice and PPARγ gene knockout mice were used as research objects to establish the diabetic mouse model, which was divided into normal control group (NC group), normal glucose PPARγ gene knockout group (NK group), diabetic wild‐type group (DM group), and diabetic PPARγ gene knockout group (DK group), with 8 mice in each group. After 16 weeks, the mice were sacrificed for renal tissue collection. Morphological changes of renal tissue were observed by HE and Masson staining, and ultrastructure of renal tissue was observed by transmission electron microscope. Protein expressions of PPARγ, podocin, nephrin, collagen IV, and fibronectin (FN) in renal tissues were detected by immunohistochemistry and Western blot, and mRNA changes of PPARγ, podocin, and nephrin in renal tissues were detected by qRT‐PCR. Results. Compared with the NC group, the protein and mRNA expressions of PPARγ, podocin, and nephrin decreased in the kidney tissue of mice in the DM group, while the protein expressions of collagen IV and FN increased. The expression of various proteins in kidney tissues of the DK group was consistent with that of the DM group, and the difference was more obvious. The expression of PPARγ protein and mRNA decreased in the NK group, while the expression of podocin, nephrin protein and mRNA, collagen IV, and FN protein showed no significant difference. Conclusion. In diabetic renal tissue, the loss of PPARγ can aggravate podocellular damage and thus promote the occurrence of diabetic renal fibrosis. Increasing the expression of PPARγ may effectively relieve renal podocyte impairment in diabetic patients, which can be used for the treatment of diabetic nephropathy.
An Accurate Heart Disease Prognosis Using Machine Intelligence and IoMT
Authors: Pirgazi Jamshid , Ghanbari Sorkhi Ali , Iranpour Mobarkeh Majid
Published: July 2022

In recent years, Internet of Medical Things (IoMT) and machine learning (ML) have played a major role in the healthcare industry and prediction of in time diagnosis of diseases. Heart disease has long been considered one of the most common and lethal causes of death. Accordingly, in this paper, a multiple-step method using IoMT and ML has been proposed for diagnosis of heart disease based on image and numerical resources. In the first step, transfer learning based on convolutional neural network (CNN) is used for feature extraction. In the second step, three methods of distributed stochastic neighbor embedding (t-SNE), F-score, and correlation-based feature selection (CFS) are utilized to select the best features. In the end, a combination of outputs of three classifiers including Gaussian Bayes (GB), support vector machine (SVM), and random forest (RF) according to the majority voting is employed for diagnosis of the conditions of heart disease patients. The results were evaluated on the two UCI datasets. The results indicate the improvement of performance compared to other methods.
Comparative Removal of Cr(VI) and F− Ions from Water by Freezing Technology
Authors: Melak Fekadu , Asere Tsegaye Girma
Published: July 2022

Trace element ions, such as Cr(VI) and F−, are of particular interest due to their environmental impact. Both ions exhibit an anionic nature in water that can show similar removal tendencies except for their significant differences in ionic radius, speciation forms, and kosmotropic-chaotropic behaviors. Accordingly, partial freezing was performed to examine the comparative freeze separation efficiencies of Cr(VI) and F– from aqueous solutions. Freeze desalination influencing parameters such as initial ion concentration, salt addition, and freeze duration were explored. Under optimal operating conditions, freeze separation efficiencies of 90 ± 0.12 to 95 ± 0.54% and 58 ± 0.23% to 60 ± 0.34% from 5 mg/L of Cr(VI) and F–, respectively, were demonstrated. The salt addition into the F–-containing solutions revealed more F– ion intercalation into the ice, initiating the decrement of freeze separation efficiency. The influences of structuring-destructuring (kosmotropicity-chaotropicity) and the size-exclusion nature of ice crystals were used to explain the plausible mechanism for the difference in freeze separation efficiency between Cr(VI) and F– ions.
Associated Factors of Wasting among Infants and Young Children (IYC) in Kuyu District, Northern Oromia, Ethiopia
Authors: Yazew Tamiru , Daba Agama
Published: July 2022

Wasting among infants and young children in underdeveloped countries including Ethiopia is one of the most serious public health issues. Therefore, this study was designed to assess the magnitude of wasting and the variables that associate with it among infants and young children in the Kuyu district of Northern Oromia, Ethiopia. A community‐based cross‐sectional study of 612 infants and young children aged 6‐23 months was conducted. To select eligible infants and young children from each family in the Kuyu district, a multilevel sampling approach was used. The amount and determinants related to wasting were investigated using the Statistical Package for Social Sciences (SPSS) version 20.0. In the study area, 14.1% of infants and young children were found to be wasting. Maternal educational status (AOR = 1.8, 95% CI; 1.01, 4.32), diarrhoea (AOR = 2.3, 95% CI; 1.98, 4.56), exclusive breastfeeding (AOR = 2.46, 95% CI, 1.4, 4.58), antenatal care visits (AOR = 2.21; 95% CI, 1.32, 3.48), and wealth index (AOR = 1.66, 95% CI; 1.07, 4.47) were significantly associated with wasting. According to the findings of this study, mother educational status, the occurrence of diarrhoea, exclusive breastfeeding, antenatal care visits, and wealth index have an impact on infants and young children’s wasting. Therefore, to lower the burden of wasting among infants and young children in the study, community‐based schooling and nutritional interventions are urgently needed.
A Visual Human-Computer Interaction System Based on Hybrid Visual Model
Authors: Ke Ziyi , Chen Ziqiang , Wang Huanlei , Yin Liang
Published: July 2022

The traditional human-computer interaction is mainly through the mouse, keyboard, remote control, and other peripheral equipment electromagnetic signal transmission. This paper aims to build a visual human-computer interaction system through a series of deep learning and machine vision models, so that people can achieve complete human-computer interaction only through the camera and screen. The established visual human-computer interaction system mainly includes the function modes of three basic peripherals in human-computer interaction: keyboard, mouse (X-Y position indicator), and remote control. The convex hull method was used to switch between these three modes. After issuing the mode command, Gaussian mixture was used to quickly identify the moving human body to narrow the scope of our image processing. Subsequently, finger detection in human body was realized based on the Faster-RCNN-ResNET50-FPN model structure, and realized the function of moving mouse and keyboard through the relationship between different fingers. At the same time, the recognition of human body posture was done by using MediaPipe BlazePose, and the action classification models were established through the Angle between body movements so as to realize the control function of remote control. In order to ensure the real-time performance of the interactive system, according to the characteristics of different data processing processes, CPU and GPU computing power resources are used to cross-process images to ensure the real-time performance. The recognition accuracy of the human-computer interaction system is above 0.9 for the key feature points of human body, and above 0.87 for the recognition accuracy of four kinds of command actions. It is hoped that vision-based human-computer interaction will become a widely used interaction mode in the future.
Effect of Microscope Combined with Wechat Smart Platform on Clinical Efficacy and Gastrointestinal Function of Patients with Cholecystolithiasis Combined with Common Bile Duct Stones
Authors: Xu Xu , Guo Dongmei , Zhang Yan , Yang Dandan , Hou Guangbin , Li Quanfu , Ge Changqing , Qie Zengwang , Zhong Yonggang
Published: July 2022

To explore the clinical efficacy of microscope combined with Wechat smart platform in patients with cholecystolithiasis and choledocholithiasis, this paper proposes the effect of microscope combined with Wechat smart platform intervention after laparoscopic lithotomy and choledocholithotomy on the clinical efficacy and gastrointestinal function of patients with cholecystolithiasis combined with choledocholithiasis. From February 2018 to March 2019, 78 patients with gastric cancer were selected by our clinic and included in the research team. Evaluate the efficacy of endoscopic biliary lithotomy (LBL) + bile duct lithotomy (TBL) + T-tube drainage therapy to provide reliable evidence for improved efficacy and efficacy in order to provide a strong reference for improving the effectiveness and safety of surgical treatment of choledocholithiasis. Safety of surgical treatment of diseases. Gallstone disease. The experiments did not show any significant differences between the two groups during surgery. Diabetes was lower in the control group, and hospital incidence was lower in the control group. There were no significant differences between the two groups for preoperative WHOQOL-100 scores. Two weeks and four weeks after surgery, the man-key-100 score was higher than that of the control group. Endoscopic cholecystectomy + choledocholithotomy + choledochoscopic lithotomy + T-tube fluid have been shown to be effective in promoting rapid intestinal function and improving patient quality of life and are appropriate for therapeutic use.
Socioeconomic and Geographic Predictors of Poor Diet Quality in a Large U.S. Cohort of Adult Men and Women
Authors: McCullough ML , Chantaprasopsuk S , Islami F , Um C , Rees-Punia E , Wang Y , Leach C , Sullivan L , Patel AV
Published: July 2022

Purpose: Poor diet quality is an important determinant of obesity and chronic disease risk. A better understanding of social, economic and geographic factors associated with diet quality can inform public health and policy efforts for advancing health equity. Methods: This cross-sectional analysis of 155,331 adult men and women in the American Cancer Society (ACS) Cancer Prevention Study-3 examined race/ethnicity, socioeconomic (individual-level education and income), and geographic (metropolitan to rural dwelling, residence in food desert) predictors of poor diet quality, mutually adjusted using multivariable logistic regression models. A diet score reflecting concordance with the 2020 ACS dietary recommendations for cancer prevention based on intake of fruit, vegetables, whole grains, red and processed meats, sugar-sweetened beverages (SSBs) and highly processed foods was calculated from responses to a validated food frequency questionnaire, with scores ranging from 0 (worst) to 12 (best) diet quality, and scores 0-3 representing poor diet quality. Results: All socioeconomic and geographic characteristics assessed were statistically significant, independent predictors of poor diet quality. Compared to White participants, Black participants had a 16% higher likelihood of poor diet quality, while Hispanic/Latino and Asian/Native Hawaiian/Pacific Islander participants had 16% and 33% lower risk of poor diet quality, respectively. Higher income and education were linearly associated with better diet quality among White participants, but not among other racial/ethnic groups. Even after controlling for other characteristics, non-metropolitan residence was associated with a 61% higher risk of poor diet quality. Additionally, residence in a food desert was associated with a 17% higher risk. All diet score components contributed to disparities observed, particularly red and processed meat and SSBs. Conclusions: Race/ethnicity, socioeconomic and geographic factors independently predicted risk of poor diet quality among a large, diverse adult U.S. population. These findings contribute information to more effectively target behavioral interventions, programs, and policies to improve diet quality for populations at highest risk.