bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of Cyberchondria among Outpatients with Metabolic Syndrome in a Tertiary Care Hospital in Southern India
Authors: Pawar Priya , Kamat Ashok , Salimath Gavishiddhayya , Jacob Kiran Rose , Kamath Rajesh
Published: September 2022

Background. In today’s world, Internet-based medical information plays a significant role in patient education. There are several accessible health-related websites. It has become common to search Internet before going for a medical consultation. The main objective of this study was to determine the prevalence of cyberchondriasis and its association with demographic variables. Methods. A cross-sectional study was carried out among metabolic syndrome patients attending the cardiology, endocrinology, and neurology outpatient departments of a tertiary care hospital in South India. The prevalence of cyberchondriasis and its constructs were measured using the cyberchondria severity scale (CSS). Inferential statistics revealed no statistically significant difference in the average CSS scores across sociodemographic variables. Spearman correlation was conducted to determine the relationship between the constructs. Results. A total of 379 participants with metabolic syndrome were included in the study. 42.5% of them were severely affected, and 28.0% were moderately affected by cyberchondriasis. Among the constructs studied, compulsion (85.7%), distress (91.8%), excessiveness (96.6%), and reassurance (76.1%) constructs had an impact on a greater number of study participants, compared to mistrust of medical professional construct (33.0%). Cyberchondriasis had a significant relationship with the history of myocardial infarction (p value = 0.03). There was a statistically significant positive linear relationship between mistrust and reassurance (rs = 0.169, p value<0.001). Reassurance had a significant negative linear relationship with distress (rs = −0.147, p value = 0.004). Conclusion. In India, cyberchondriasis is a growing public mental health issue. Awareness among the general population is necessary to minimize the possible outcomes of cyberchondriasis like anxiety and depression. Screening individuals for possible risk factors is recommended.
Logistics Distribution Path Optimization Algorithm Based on Intelligent Management System
Authors: Li Foshang
Published: September 2022

There are three key points in logistics distribution: the distribution vehicle, the amount of goods, and the distribution path. Comprehensive calculation and optimization of these three parameters can plan a reasonable and efficient distribution scheme, especially the distribution path. This study aims to study the method of optimizing the logistics distribution path and strives to find the optimal distribution scheme and the shortest path, which can reduce the distribution error rate, distribution time, and labor costs, thus realizing intelligent management. In this study, intelligent management methods such as radio-frequency identification technology and ant colony algorithm are proposed to optimize the logistics distribution path and realize the safe and efficient logistics distribution. The experimental results of this study show that for the current logistics distribution, the RFID system has a positioning rate of close to 100% when the number of fixed points reaches about 300, and almost all accurate positioning is achieved. The ant colony algorithm can also accurately find the shortest distance after selecting appropriate parameters, which is about 200 meters away from the actual shortest distance.
[Retracted] Deconstruction of Knee Cartilage Injury in Athletes Using MR Images Based on Artificial Intelligence Segmentation Algorithm
Authors: Zhang Yuze , Lian Hao , Liu Yinghai
Published: September 2022

The knee joint is the second largest joint in the human body, with a wide range of functional activities and strong support for the human body. Moreover, the cartilage of the knee joint is hyaline cartilage, which is relatively brittle, so it is most vulnerable to trauma. In clinical work, the damage of articular cartilage is a disease with a high rate of orthopedic visits. In this paper, all the experimental group cases included in the observation were patients with acute articular cartilage injury or OA diagnosed by knee arthroscopy. All experimental groups and control groups did not have any strenuous exercise one day before MRI (magnetic resonance imaging), and they sat for 30 minutes before the examination. Conventional scanning sagittal FSE‐T1WI, FSE‐T2WI, FS‐FSE‐T1WI, FS‐FSE‐T2WI, FS‐PDWI, and coronal FS‐PDWI sequence. In the normal control group, after the T2 color map was generated in the workstation, the articular cartilage was divided on the midsagittal plane, and the patellar cartilage and tibial plateau were roughly divided into upper, middle, lower and anterior, middle, and posterior thirds. In order to ensure the maximum comparability of the results, an artificial intelligence segmentation algorithm is used to divide the region of interest equally, and the central part of each partition is selected as much as possible for measurement. The T2 values of the three partitions of each cartilage were measured one by one and averaged. For the comparison results of T2 value of cartilage in the same part: according to patellar cartilage, femoral cartilage, and tibial cartilage, the P values are 0.973, 0.150, and 0.525, respectively. Therefore, early detection and early treatment of articular cartilage injury are of great significance to the performance of athletes’ competition level and the extension of sports life.
Development and Evaluation of an Artificial Intelligence–Based Cognitive Exercise Game: A Pilot Study
Authors: Eun Sung-Jong , Kim Eun Joung , Kim Jung Yoon
Published: September 2022

Recently, cognitive serious games have successfully been employed to train cognitive abilities in elderly people with mild cognitive impairment, Alzheimer’s disease, and related disorders. However, despite the continuous rehabilitation game design and its applications, the existing cognitive exercise games fall short of user interaction and personalized elements with regard to difficult levels, which leads to users leaving early and losing interests during the gameplay. In this regard, the purpose of the study was to design and develop the serious game inclusive of playful elements for user motivation, the web‐based mobile application system for easy accessibility, and Artificial Intelligence– (AI–) based difficulty level adjustment system for prevention from earlier leaving out in the middle of the play so that the elderly users can feel entertaining and immersed into the cognitive game voluntarily. This study was designed as an eight‐week pilot experiment with thirty‐seven participants in their 60s to 80s for the game’s usability assessment purpose. Results of the study showed that the AI‐based cognitive exercise game was acceptable, interesting, and motivating for the elderly people and the test results before and after the eight‐week training suggest a relationship between longer the training on the game and lower cognitive assessment scores including geriatric quality of life scale, geriatric depression scale, and Korean version of mini‐mental state examination (MMSE). These correlations demonstrate the potential value of serious games in clinical assessment of cognitive status for the elderly users with varying cognitive ability. Based on these results, the elderly‐centered serious game with playful element can be potentially used in clinical settings, allowing the cognitive training to be more enjoyable and more medically effective. Given these promising results, a more focused study can extend to the game system or additional game tools or features to be explored that solely target the elderly by applying AI and advanced visualization devices.
The Exosomal miR-1246 of Laryngeal Squamous Cell Carcinoma Induces Polarization of M2 Type Macrophages and Promotes the Invasiveness of Laryngeal Squamous Cell Carcinoma
Authors: Wu Lifeng , Zuo Na , Pan Shuo , Wang Yue , Wang Qixue , Ma Jun
Published: September 2022

Background. The possible role and detailed mechanisms of Tumor-associated macrophages (TAMs) in laryngeal squamous cell carcinoma (LSCC) have not been revealed. Methods. The expressions of typical markers were evaluated by qRT-PCR. In macrophages cocultured with TU212 cells, CD163, and CD206 protein expressions were detected by western blot analysis; IL-10 and IL-12 expressions were detected by ELISA assay. Exosomes isolated from TU212 cells were characterized by TEM analysis. As for the TU212 cells cocultured with macrophages processed with HOK or TU212 cells derived exosomes, their viability, migration, and invasion were assessed by CCK-8 assay, wounding healing, and Transwell assays, respectively. Results. In this study, macrophages processed with exosomes from human TU212 cells notably advanced LSCC cell viability, migration, and invasion. miR-1246 inhibitor suppressed the M2 polarization of macrophages. Macrophages transfected with miR-1246 inhibitor suppressed LSCC cell viability, migration, and invasion. Conclusion. In summary, our data implied that the exosomal, miR-1246 of LSCC, induced polarization of M2 type macrophages and promoted the progression of LSCC. This trial is registered with 2020-13.
Construction of College Chinese Blended Teaching Mode Based on Decision Tree Classification Model in New Media Context
Authors: Huang Pingge
Published: September 2022

Based on the context of new media and big data, this article uses the decision tree classification model to construct the college Chinese hybrid teaching mode. In order to verify the accuracy of ID3 algorithm prediction, the comparison of the ID3 algorithm, K-means algorithm, and support vector machine classification algorithm was made, and the experimental results show that the ID3 decision tree classification algorithm has better prediction and classification ability, for the construction of college Chinese hybrid teaching mode provides certain practical value and reference basis.
Analysis on the Main Controlling Factors of Oil Accumulation in Putaohua Reservoir of long12 Block in Daqing Longhupao Oilfield
Authors: Li Tianye , Zhang Lei , Zhang Xuejuan , Wang Dandan , Jin Xiangxiong , Yin Qianhao , Wu Yue
Published: September 2022

Long12 block of Longhupao oilfield is located in the western slope area of Qijia-Gulong Sag, which lay in the central depression of Songliao basin. Recent exploration and development shows that Putaohua oil layer has great potential storage. However, the block is located in the ring concave fault zone, with complex geological background and extensive low resistivity oil layers and water layers of high resistivity, resulting in an unclear condition of reservoir forming and oil-water distribution rules of Putaohua oil layer, which deeply restricts the pace of increasing storage and production of the oilfield. In this study, the data of logging, logging, drilling, analysis, and testing are adopted to study carries out a reservoir forming conditions such as source rocks, reservoirs, caprocks, traps, and migration conditions. Meanwhile this study discuss the main controlling factors of Putaohua reservoir formation in combination with the law of oil-water distribution, so as to provide a geological basis for clarifying the reservoir forming law of long 12 block and the prediction of favorable target areas.
QSLT: A Quantum-Based Lightweight Transmission Mechanism against Eavesdropping for IoT Networks
Authors: Liu Gang , Han Jingyuan , Zhou Yi , Liu Tao , Chen Jian
Published: September 2022

Quantum Key Distribution (QKD) is a promising paradigm for Internet of Things (IoT) networks against eavesdropping attacks. However, classical quantum-based mechanisms are overweight and expensive for resource-constrained IoT devices. That is, the devices need to frequently exchange with the QKD controller via an out-band quantum channel. In this paper, we propose a novel Quantum-based Secure and Lightweight Transmission (QSLT) mechanism to ease the overweight pain for IoT devices against eavesdropping. Particularly, the mechanism predistributes quantum keys into IoT devices with SIM cards. Using one of the keys, QSLT encrypts or decrypts IoT sensitive data. It is noting that an in-band key-selection method is used to negotiate the session key between two different devices. For example, on one IoT device, the in-band method inserts a key-selection field at the end of the encrypted data to indicate the key’s sequence number. After another device receives the data, QSLT extracts the key-selection field and decrypts the data with the selected quantum key stored locally. We implement the proposed mechanism and evaluate its security and transmission performances. Experimental results show that QSLT can transmit IoT data with a lower delay while guaranteeing the security performance. Besides, QSLT also decreases power usage by approximately 58.77% compared with state of the art mechanisms.
Association of Red Cell Distribution Width-to-Platelet Ratio and Mortality in Patients with Sepsis
Authors: Liu Jie , Huang Xueying , Yue Suru , Wang Jia , Ye Enlin , Huang Jiasheng , Zhao Yumei , Niu Dongdong , Hou Xuefei , Wu Jiayuan
Published: September 2022

Background. As a novel inflammatory index, the ratio of red cell distribution width (RDW) to platelet count (RPR) may have prognostic value in some critical illnesses. However, studies on the prognostic influence of RPR in patients with sepsis are few. This study is aimed at investigating the association between RPR levels and 28-day mortality in patients with sepsis. Methods. Data of patients with sepsis were obtained from the Medical Information Mart for Intensive Care III database. The best cut-off value was calculated by establishing the receiver operating characteristic curve (ROC), and the predictive ability of different indicators was compared through the area under the curve (AUC). The association between RPR levels and 28-day mortality was assessed using the Cox proportional hazards model. Restrictive cubic spline analysis was applied to the multivariable Cox model to investigate the nonlinear relationship between RPR and 28-day mortality. Results. A total of 3367 patients with sepsis were included in the study. A nonlinear relationship was observed between RPR and 28-day mortality, showing a trend of a first rapid increase and a gradual increase. For the prediction of mortality, the best cut-off value for RPR was 0.109, with an AUC of 0.728 (95% confidence interval [CI]: 0.709–0.747). The predictive capability of RPR was superior to those of RDW, platelet, SOFA score, and SAPS II score. After adjusting for various confounding factors, high RPR was significantly associated with increased mortality with adjusted hazard ratios of 1.210 (95% CI: 1.045–1.400) for categorical variables and 2.826 (95% CI: 2.025–3.944) for continuous variables. Conclusion. Elevated RPR level is significantly correlated with a high risk of 28-day mortality in patients with sepsis and can be a new predictor of patient prognosis.
Mathematical Problems in Engineering Joint Structure Stiffness Analysis of an Automotive Body in White with the Finite Element Method
Authors: Yin Changcheng , Lv Zhangbin , Wang Yangting , Yue Guosheng
Published: September 2022

The finite element model of the seven connection heads of an automotive body in white is established, and the stiffness calculation is carried out by taking the lower joint of the B pillar as an example. Nine stiffness values were obtained for each branch, which can be written as a 3 × 3 symmetric matrix. The front and back bending stiffness, torsional stiffness, and internal and external bending stiffness are obtained with the decoupling method. Based on this, the finite element model for unrigid and rigid joints is established, and the three stiffness ratio coefficients of each branch of the joint are calculated and evaluated. Finally, the effects of the thickness and stiffness of the sheet metal parts on the bending condition, torsion condition, first-order bending, and torsion frequency of the body in white are discussed using the regional sensitivity analysis and strain energy calculation.
Identification of Scientific Research Evaluation Indicators of College Teachers Based on Wireless Communication Network
Authors: Li Zhi , Qi Zhanyong
Published: September 2022

The evaluation indicator of teachers’ scientific research is a very important criterion in the evaluation of teachers’ scientific research in colleges and universities. Generally, indicators are divided into three levels, and each indicator setting must be very precise. Many indicator systems for college teachers have been created at present. However, there are some problems in the identification of indicators in the evaluation process. There will be cross-repetition between indicators, and the quantification of indicators is not detailed enough, resulting in inaccurate results. To solve these problems and make the evaluation results more fair and accurate, this paper took a university as a case, a deeply discussed method based on wireless communication network, and conducts an experimental analysis on the identification of university teachers’ scientific research evaluation indicators. Using the method of wireless communication network, the problem of index identification was analyzed, and the experimental research of index identification was carried out by using wireless communication network. The results showed that the index of engineering teachers’ practical ability was relatively high, and the weight value was 0.38. The liberal arts was relatively low, and the weight value was only 0.26. However, on the cognitive index, the weight value of liberal arts was the highest, with the weight value of 0.33 while that of engineering was only 0.28. It can be seen that the method applied in this paper greatly improved the efficiency of the whole evaluation, and it made the index recognition more rapid and accurate. Therefore, further research on wireless communication networks and index identification can be considered.
A Resource Allocation Scheme for Intelligent Tasks in Vehicular Networks
Authors: Chen Jiujiu , Guo Caili , Feng Chunyan , Liu Chuanhong , Sun Xin , Liu Jun
Published: September 2022

Lots of resource-consuming intelligent tasks need to be handled in vehicular networks, and traditional resource allocation schemes are hard to meet the intelligent demands. Therefore, this paper proposes a task-oriented resource allocation scheme for intelligent tasks in vehicular networks. First, we propose a task-oriented communication system and formulate a resource allocation problem, which is aimed at maximizing the task performance. Second, based on the system model, an intelligent task-oriented resource allocation optimization criterion is proposed, which is formulated as a mathematical model, and its parameters are solved by the proposed gradient descent-based algorithm. Third, to solve resource allocation problem, a multiagent deep

Q

-network- (MADQN-) based algorithm is proposed, whose convergence and complexity are further analyzed. Last, experiments on real datasets verify the performance advantages of our proposed algorithms.
Machine Learning and Reverse Methods for a Deeper Understanding of Public Roadway Improvement Action Impacts during Execution
Authors: Mamdoohi Sohrab , Miller-Hooks Elise
Published: September 2022

The execution of public roadway maintenance, rehabilitation, and restoration activities disturb normal traffic flows, resulting in roadway capacity reduction, inducing travel time delays, and promoting traffic safety concerns. While they improve public roadway performance once complete, the impacts endured in executing these actions is significant. This work seeks a deeper understanding of the effects of improvement actions on traffic by juxtaposing their effects against those arising from traffic incidents that cause similar capacity reductions and related negative externalities. This is accomplished through direct and reverse comparisons with traffic incident impacts. A measure of unit delay that uses observations to determine event location extent, duration, and propagation direction was computed at both facility and corridor-wide levels to establish the degree to which improvement actions and traffic incidents are similar or dissimilar. Alternative hybrid machine-learning methods are proposed to identify and contrast those traffic characteristics that contribute greatest to correct detection of each type of downtime event. These techniques can detect traffic events and accurately distinguish between event types (whether a collision or improvement activity). The techniques were applied on seven months of data obtained from 2019 along three corridors from northern, southern, and western regions of the Commonwealth of Virginia. Those traffic characteristics that contribute greatest to correct event detection of each event type were identified and their similarities and differences were studied. General linear, multivariate regression equations were also developed for more general application.
Rapid Onset and Resolution of Hydroxychloroquine Cardiomyopathy: A Case Report
Authors: Ramahi Ahmad , Heider Amer , Kahlenberg J. Michelle
Published: September 2022

Systemic lupus erythematosus (SLE) is an autoimmune, chronic, and heterogenous disease with organ damage resulting from immune complex deposition and inflammatory infiltrates. Antimalarial drugs, such as hydroxychloroquine (HCQ), are cornerstone immunomodulators for the treatment of SLE. Rarely, HCQ toxicity can occur, leading to devastating outcomes. We report a case of a patient with SLE on HCQ who presented with a rapid onset of large pericardial effusion and a dramatically decreased left ventricular ejection fraction. Endomyocardial biopsy was positive for curvilinear bodies, confirming the diagnosis of hydroxychloroquine cardiotoxicity. Hydroxychloroquine cardiomyopathy is a rare but life-threatening medication side effect. It is important to consider it in any patient taking the medication who presents with a new onset or worsening symptoms of heart failure.
Fast Tensor-Based Joint Estimation for Time Delay and Angle of Arrival in OFDM System
Authors: Du Jinzhi , Cui Weijia , Ba Bin , Jian Chunxiao , Xu Haiyun
Published: September 2022

Nowadays, the joint estimation of time delay (TD) and angle of arrival (AOA) using conventional vector structure suffers from the considerable complexity of multidimensional spectrum search. Therefore, a fast estimation method using orthogonal frequency division multiplexing (OFDM) technology and uniform planar array (UPA) is proposed in this paper, which adopts low-complexity tensor-based operations and spatial-frequency features to reconfigure the channel frequency response. To begin with, the array response is integrated with the OFDM signal characteristics to build an extended array in tensor form. Afterwards, we process the covariance matrix of the tensor structure by CANDECOMP/PARAFAC decomposition (CPD) to separate the respective signal subspaces of TD and AOA estimates. Finally, we conduct a one-dimensional (1-D) spectrum search to locate the TD estimates and a two-dimensional (2-D) spectrum search to locate the AOA estimates. The simulated performance demonstrates that the proposed algorithm offers precise estimates at low signal-to-noise ratios in a multipath environment and outperforms traditional vector-based algorithms with respect to computational complexity.
The Space Conceptual Models and Water Vapor Characteristics of Typical Rainstorms during Plum Rain Season
Authors: Tian Ying , Yao Rong , Zhao Enrong , Yao Qian , Pan Xiaolong
Published: September 2022

Based on conventional observation data from the China Meteorological Administration (CMA) and reanalysis data from the American National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) between 2012 and 2021, combined with the meteorological analysis, composite synthesis, and water vapor trajectory analysis, the weather circulations of typical rainstorms during the 10 years can be divided into 4 categories: Static Front Pattern (SFP), Subtropical High Edge Pattern (SHEP), Northeast Cold Vortex Pattern (NCVP), and Low-Level Vortex and Shear Pattern (LLVSP). The SHEP and SFP rainstorms have the characteristics of long duration and wide range, while the NCVP rainstorms are characterized by mobility and disaster weather accompaniment. The daily precipitation of LLVSP cases has extremity feature. The occurrence and development of rainstorms are well coordinated with the systems on lower levels. The main water vapor channel in lower layers of the SFP cases is from the South China Sea, while it is from Bohai for the NCVP cases and the Bay of Bengal for the SHEP and LLVSP cases. The main water vapor channel in middle layers is from the Bay of Bengal because of the affection of the southwest air flow. The south boundary of the MLYRB is the most important water vapor input boundary, followed by the west boundary, while the East and North boundaries are the outflow boundaries. During the rainstorms, the low-level water vapor is exuberant with low-level water vapor convergence much stronger than the high-level divergence. Among the four types of rainstorms, the NCVP cases provide the most abundant low-level water vapor convergence, resulting in the strongest short-term precipitation among the four types. Combined with water vapor transportation and convergence, the refined spatial conceptual models of the four types of rainstorms can better judge the process intensity and falling area and provide reference for disastrous weather forecast and early warning.
A Near-Optimal Truthful Online Auction for Efficient Crowdsourced Data Trading with Dynamic Data Owners and Dynamic Data Requests
Authors: Feng Zhenni , Zhang Chen , Chen Junchang , Liu Tong
Published: September 2022

Data is an extremely important asset in a modern scientific and commercial society. The life force behind powerful artificial intelligence (AI) or machine learning (ML) algorithms is data, especially lots of data, which makes data trading significantly essential to unlocking the power of AI or ML. Data owners who offer crowdsourced data and data consumers who request data blocks negotiate with each other to make an agreement on data assignment and trading prices via a data trading platform; consequently, both sides gain profit from the process of data trading. A great many existing studies have investigated various kinds of data sharing or trading as well as protecting data privacy or constructing a decentralized data trading platform due to mistrust issues. However, existing studies neglect an important characteristic, i.e., dynamics of both data owners and data requests in trading crowdsourced data collected by IoT devices. To this end, we first construct an auction-based model to formulate the data trading process and then propose a near-optimal online data trading algorithm that not only resolves the problem of matching dynamic data owners and randomly generated data requests but also determines the data trading price of each data block. The proposed algorithm achieves several good properties, such as a constant competitive ratio for near-optimal social efficiency, incentive compatibility, and individual rationality of participants, via rigorous theoretical analysis and extensive simulations. We further design a decentralized data trading platform in order to construct a practical data trading process incorporating the proposed data trading algorithm.
Clinical Curative Effects and Influencing Factors of Uterine Artery Chemoembolization Combined with Uterine Curettage Treating with Cesarean Scar Pregnancy Patients
Authors: Yu Kewen , Zhou Haifeng
Published: September 2022

Objective. To explore the clinical curative effects of uterine arterial chemoembolization (UACE) combined with uterine curettage treating with cesarean scar pregnancy (CSP) patients, and analyze the influencing factors of postoperative efficacy. Methods. A total of 86 patients with CSP from January 2019 to December 2021 in the Gynecology ward of our hospital were selected and divided into the control group (n = 43) and the observation group (n = 43) according to the random number method. The control group was treated with an injection of methotrexate (MTX) combined with uterine curettage, and the observation group was treated with UACE combined with uterine curettage. Two months after the operation, the therapeutic effect, cesarean scar mass, and β-human chorionic gonadotropin (β-HCG) level were observed and compared between the two groups. The general conditions of patients in two groups were recorded, and the influencing factors of surgical efficacy in patients were analyzed using univariate analysis and a multivariate logistic regression model. Results. After treatment, the total effective rate of the observation group was significantly higher than that of the control group (

P

 < 0.05). The volume of intraoperative blood loss, hospitalization period, menstrual recovery time, mass disappearance time, and β-HCG recovery time of the observation group were lower than those of the control group (

P

 < 0.05). Single factor analysis showed that the number of cesarean sections, gestational age, the largest diameter of the gestational sac, the thinnest muscular layer, and the type of CSP can all affect postoperative efficacy (

P

 < 0.05). Multivariate logistic analysis showed that the gestational age, a maximum diameter of a gestational sac, the thinnest muscular layer, and the type of CSP were independent factors influencing the postoperative efficacy of the patients (

P

 < 0.05). Conclusion. UACE combined with uterine curettage for CSP can significantly improve the curative effect, reduce intraoperative bleeding, and improve the recovery time of postoperative-related symptoms. The gestational age of the patient, the maximum diameter of the gestational sac, the thinnest muscular layer, and the type of CSP can independently affect the therapeutic effect of CSP patients. Fully understanding the high-risk factors that affect the efficacy of treatment of CSP, timely preventive measures, and targeted care can effectively improve the prognosis and reduce the risk of CSP.
Resilience Assessment and Risk Prediction in Supply Chain Management Based on Network Analysis
Authors: Zhu Liyi
Published: September 2022

As an important link of enterprise development, supply chain management should cause enterprise managers to attach great importance in order to enhance the competitiveness of enterprises. Based on enterprise supply chain management, this paper analyzes the current situation and risks of enterprise supply chain management and predicts the risks of supply chain management through network analysis. Supply chain management has strong resilience and can cope with greater risks for itself and various risk situations in the industry. The influence weight of risk types is assessed. The top three factors will restrict the supply chain management of enterprises and are factors that cannot be tolerated by management. In management practice, the influence should be avoided or mitigated as far as possible to improve the management level. In addition, corresponding measures are put forward according to the characteristics of enterprises, and scientific suggestions are provided for the development of enterprises. This assessment can be used as the basis of enterprise supply chain management risk control management decisions.
Numerical Simulation of Chemical Storage Tank Area Leakage and Explosion Accident Based on FLACS
Authors: Liu Ruochen , Liu Anqi , Sun Chunfeng
Published: September 2022

The large amount of oil storage tank possesses significant risks of leakage, and once leakage occurs, the combustible gas is prone to fire and explosion accidents. When the combustible gas cloud is exposed to the ignition source, there are possibilities of triggering the domino effect with more serious consequences. As one important kind of protective layers, the combustible gas detectors continuously monitor the leakage of combustible gas, guaranteeing the safety performance of the site. Using the computational fluid dynamics software FLACS as a tool, the impact of the consequences of the raw material leakage with a vapor cloud explosion accident in a large chemical fiber manufacturer's storage tank area is studied, and the risk of domino effect in the tank area during the course of the accident is predicted. The study shows that FLACS can be applied to the simulation study of gas diffusion explosion phenomenon in complex operation and storage areas, with the great capability of the explosion risk quantitative assessment and the reliable prediction to the risk of domino effects.
An Evaluation of the Antibacterial Activity of Pterocarpus tinctorius Bark Extract against Enteric Bacteria That Cause Gastroenteritis
Authors: Mphande Isaac , Kataba Andrew , Muzandu Kaampwe , Gono-Bwalya Angela
Published: September 2022

Enteric bacteria are the leading cause of bacterial gastroenteritis worldwide, particularly in low-income countries. The bark decoction of Pterocarpus tinctorius (Fabaceae) has traditionally been used to treat bacterial gastroenteritis. However, studies reporting the antibacterial activity of Pterocarpus tinctorius are rare. Therefore, this study aimed to evaluate the antibacterial activity of stem bark extract of Pterocarpus tinctorius against Escherichia coli, Salmonella typhi, and Shigella dysenteriae. The powdered bark extract was successively extracted with methanol using the cold continuous maceration method, followed by partitioning the crude methanolic extract to obtain methanolic, hexane, and chloroform subextracts. Three fractions were isolated from the methanolic subextract using ordinary normal phase column chromatography. The antibacterial activity of the extracts and fractions was performed using the agar well diffusion method. The minimum inhibitory concentration (MIC) was determined using the agar well diffusion method. While, minimum bactericidal concentration (MBC) was obtained by the subculturing method. The methanolic subextract was the only extract that showed antibacterial activity against the tested bacteria, and its activity was highest on Shigella dysenteriae followed by Salmonella typhi and was least active on Escherichia coli, with mean inhibition zones of 14.3 ± 0.2, 13.7 ± 0.3, and 12.2 ± 0.1 at 200 mg/mL, respectively. Chloroform subextract showed antibacterial activity only on Shigella dysenteriae, while hexane subextract did not show antibacterial activity against all bacteria tested at 100 mg/mL and 200 mg/mL. Among the three subfractions of methanolic subextract, only one subfraction was active and had both mean minimum inhibitory concentration and a minimum bactericidal concentration against Escherichia coli at 1.25 mg/mL, Salmonella typhi at 1.25 mg/mL, and Shigella dysenteriae at 0.6 mg/mL. The findings of this study support the use of Pterocarpus tinctorius in traditional medicine. Therefore, purification and structural elucidation studies are highly recommended.
Design of Cross-Platform Information Retrieval System of Library Based on Digital Twins
Authors: Shang Shanshan , Yu Zikai , Jiao Kun , Huang Yingshi , Guo Hua , Wang Guozhong
Published: September 2022

In order to improve the library’s ability of cross-platform information retrieval and data scheduling and distribution, a library cross-platform information retrieval system based on digital twin technology is designed. Using data warehouse decision support and data source structured query methods, the spectral characteristics of Library cross-platform information resources are extracted. Using the method of Hadoop data parallel loading, the library cross-platform operation data is divided into decision-making data, computing resource pool data, and Hadoop parallel loading data. A library cross-platform information digital twin parallel retrieval and information fusion feature matching model is established, and the retrieval channels are allocated through multiple complex and balanced task scheduling sequences. According to the queue configuration model of Library cross-platform information retrieval, the optimization design of Library cross-platform information retrieval system is realized. The simulation test results show that the designed system has good recall ability of cross-platform information retrieval data, and improves the utilization rate of cross-platform resources and the dynamic scheduling ability of online resources.
Exploring the Molecular Mechanism of Tong Xie Yao Fang in Treating Ulcerative Colitis Using Network Pharmacology and Molecular Docking
Authors: Zou Menglong , Zhu Ying
Published: September 2022

Objective. The purpose of this study was to investigate the mechanisms of action of Tong Xie Yao Fang (TXYF) against ulcerative colitis (UC) by employing a network pharmacology approach. Methods. The network pharmacology approach, including screening of the active ingredients and targets, construction of the active ingredient-drug target network, the active ingredient-diseasetarget network, the protein–protein interaction (PPI) network, enrichment analyses, molecular docking, and targets validation, was used to explore the mechanisms of TXYF against UC. Results. 34 active ingredients and 129 and 772 targets of TXYF and UC, respectively, were identified. The intersection of the active ingredient-drug target network, the active ingredient-disease target network, and the PPI network suggested that kaempferol, beta-sitosterol, wogonin, and naringenin were the core ingredients and prostaglandin-endoperoxide synthase 2 (PTGS2) was the core target. Enrichment analyses showed that regulation of exogenous protein binding and other functions were of great significance. Nuclear factor-kappa B (NF-κB) signaling pathway, interleukin-17 (IL-17) signaling pathway, and tumor necrosis factor (TNF) signaling pathway were important pathways. Results of molecular docking indicated that the core ingredients and the target molecule had strong binding affinities. We have validated the high levels of expression of PTGS2 in UC by analyzing three additional datasets from the Gene Expression Omnibus (GEO) database. Conclusions. There are multiple ingredients, targets, and pathways involved in TXYF’s effectiveness against UC, and these findings will promote further research and clinical applications.
Bifurcation Analysis of Travelling Waves and Multi-rogue Wave Solutions for a Nonlinear Pseudo-Parabolic Model of Visco-Elastic Kelvin-Voigt Fluid
Authors: Uddin Sabur , Karim Shazia , Alshammari F. S. , Roshid Harun-Or , Noor N. F. M. , Hoque Fazlul , Nadeem Muhammad , Akgül Ali
Published: September 2022

Through this article, we focus on the extension of travelling wave solutions for a prevalent nonlinear pseudo-parabolic physical Oskolkov model for Kevin-Voigt fluids by using two integral techniques. First of all, we explore the bifurcation and phase portraits of the model for different parametric conditions via a dynamical system approach. We derive smooth waves of the bright bell and dark bell, periodic waves, and singular waves of dark and bright cusps, in correspondence to homoclinic, periodic, and open orbits with cusp, respectively. Each orbit of the phase portraits is envisaged through various energy states. Secondly, with the help of a prevalent unified scheme, an inventive version of exact analytic solutions comprising hyperbolic, trigonometric, and rational functions can be invented with some collective parameters. The unified scheme is an excitably auspicious method to procure novel interacting travelling wave solutions and to obtain multipeaked bright and dark solitons, shock waves, bright bell waves with single and double shocks, combo waves of the bright-dark bell and dark-bright bell with a shock, dark bell into a double shock wave, and bright-dark multirogue type wave solutions of the model. The dynamics of the procured nonlinear wave solutions are also presented through 2-D, 3-D, and density plots with specified parameters.
Extreme Gradient Boosting Regressor Solution for Defy in Drilling of Materials
Authors: Elango Sangeetha , Natarajan Elango , Varadaraju Kaviarasan , Abraham Gnanamuthu Ezra Morris , Durairaj R. , Mohanraj Karthikeyan , Osman M. A.
Published: September 2022

Drilling is a quite common operation being performed in the manufacturing of components. Instrumental response in drilling is geometrical accuracy and surface integrity of the drilled parts. For the application where geometrical tolerance is very small, an operation is to be carried out very carefully. If not, rejection of drilled samples will be higher and consequently production loss will be higher. The use of prediction model in this scenario is much more appropriate and cost-effective. This research aimed to apply extreme gradient boosting (XGBoost) regressor to develop a drilling prediction model. Drilling experiments were conducted after developing design of experiments with twenty-seven unique sets. Experimental data analysis was then carried out on experimental data sets that have features such as speed, feed, angle, hole length, and surface roughness. After correlation analysis, the k-fold cross validation method was applied for parameterisation. Hyperparameters estimated from the k-fold cross validation were then applied to train and test the XGBoost regressor-based machine learning (ML) model. It is concluded from the model evaluation metric (R2) that the XGBoost regressor model has resulted 0.89 before tuning and 0.94 after tuning of the model, which is higher than the polynomial regressor and support vector regressor.
A Phase II, Randomized, Double-Blind, Double-Dummy, Active-Controlled Clinical Trial to Investigate the Efficacy and Safety of NW Low-Glu® in Patients Newly Diagnosed with Type 2 Diabetes Mellitus
Authors: Assaad-Khalil Samir , Elkafrawy Nabil , Khaled Mohsen , Mogeib Omneya , Badr Hytham , Rashwan Ahmed , Youssef Mahmoud , Eltamawy Khaled , Mohamed Shahnaz
Published: September 2022

Background. Medicinal plants have long been used for the treatment of type 2 diabetes mellitus (T2DM). This study aimed to investigate the hypoglycemic efficacy and safety of NW Low-Glu® (contents of one capsule are 300 mg Mas Cotek + 100 mg Cinnamomum cassia L. + 250 mg Nigella sativa L. powdered extracts) in treatment-naïve, newly diagnosed T2DM patients. Methods. This was a 12-week, double-blind, double-dummy, randomized, phase 2 clinical trial. A total of 232 male and female patients aged ≥18 and ≤65 years who were newly diagnosed with T2DM and have not received any antidiabetic drugs before and were equally randomized to receive metformin (2000 mg per day), low-dose NW Low-Glu® (content of four capsules per day), or high-dose NW Low-Glu® (content of five capsules per day). Our primary objective was to measure the mean change in HbA1c between each of the experimental arms and the metformin arm. Results. There was a significant reduction in mean HbA1c at 12 weeks compared to baseline in the low-dose (0.6 (1.4)%;p=0.002) and high-dose arms (0.8 (1.7)%;p=0.004). There was also a significant reduction in 2 hr PPG at 12 weeks in the low-dose (35.4 (74.9) mg/dL,p=0.001) and high-dose arms (24.7 (100.8) mg/dL,p=0.04). Weight reduction was significantly higher with both high-dose (1.1 (−1.7) Kg;p=0.005) and low-dose arms (0.9 (−1.5) Kg;p=0.023) compared to metformin (0.8 (−1.8) Kg). No serious AEs or deaths were reported. Conclusions. After 3 months of treatment, NW Low-Glu® was noninferior to metformin in reducing HbA1c and 2 hr PPG, while leading to significantly higher weight reduction in newly diagnosed T2DM patients. It was also safe and well tolerated.
A Systematic Review of Digital Interventions to Improve ART Adherence among Youth Living with HIV in sub-Saharan Africa
Authors: Griffee Kevin , Martin Roxanne , Chory Ashley , Vreeman Rachel
Published: September 2022

An estimated 3.4 million youth aged 15–24 years live with human immunodeficiency virus (HIV), a majority of whom reside in sub-Saharan Africa (SSA). Youth living with HIV (YLHIV) generally maintain lower levels of antiretroviral therapy (ART) adherence compared to other age groups, which has negative impacts on long-term clinical outcomes. Given expanding mobile phone and Internet usage among youth in SSA, and a need for strategies to increase ART adherence, this review systematically assessed whether digital interventions could be used to improve YLHIV ART adherence in SSA. PRISMA 2020 guidelines were followed, and PubMed and Scopus databases were searched using terms to reflect the population of interest and different digital intervention strategies to improve ART adherence. Experimental or quasi-experimental studies in SSA evaluating the quantitative effect of digital interventions on YLHIV ART adherence were included. 3849 articles and abstracts, and 122 full texts were screened by two researchers (KG and RM). A third researcher (AC) resolved conflicts. Data were extracted from six eligible articles published between 2017 and 2021. Interventions from included studies lasted 13–96 weeks and took place in Kenya, Nigeria, Uganda, and Zimbabwe. Two of the six studies found significant intervention-related improvements in viral suppression. Of these two studies, one used short message service (SMS) for appointment and daily adherence reminders, and the other combined weekly SMS reminders with phone calls, support groups, home visits, and clinic-based counseling. The four remaining studies, using SMS and Internet-based interventions, did not find any significant adherence-related improvements. This review provides mixed evidence for using digital interventions to improve ART adherence among YLHIV in SSA. Given the relative novelty of using digital interventions in this context, further research is required to evaluate their effectiveness in improving youth ART adherence.
Effect and Safety of Painless and Conventional Endoscopic Management of Denture Impaction in the Esophagus
Authors: Tian Li li
Published: September 2022

Objective. To improve the level of clinical diagnosis and treatment, reduce the incidence of complications, and provide the basis for clinicians to choose an appropriate treatment, this research explores the removal methods of the impacted denture in the esophagus by endoscopy. Methods. Based on the clinical information, treatment methods and complications of 72 patients with denture impaction in the esophagus admitted to our hospital from January 2016 to March 2021, which were divided into the group treated with painless endoscopy and the group treated with conventional endoscopy, retrospective analysis of the therapeutic effect and complications was conducted. Results. There was no statistically significant difference between the two groups in terms of denture removal rate (

P
>
0.05

). There were statistically significant differences between the two groups in terms of operating time and incidence rates of complications during and after the procedure. The operating time of the group treated with painless endoscopy was significantly shorter than the group treated with conventional endoscopy (

P
<
0.05

). The incidence rates of complications during and after the procedure of the group treated with painless endoscopy were significantly lower than the group treated with conventional endoscopy (

P
<
0.05

). Conclusions. Compared with the conventional endoscopy, painless endoscopic management of denture impaction in the esophagus under general anesthesia with tracheal intubation improves the clinical efficacy and reduces the adverse reactions. Thus, it is worthy of clinical popularization and application.