bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Influence Mechanism of Platform Corporate Social Responsibility on Customer Extra-Role Behavior
Authors: Liu Wenjun , Wang Chenye , Ding Lin , Wang Cuibo
Published: November 2021

Platform enterprises, which are growing in both quantity and scale, have been inseparable from modern life. In China, the laws specific to platform enterprises fall behind their ever-changing business model. Hence, it is an urgent requirement that platform enterprises undertake their social responsibilities, which will influence consumer extra-role behaviors besides bringing reputation advantages to the enterprises. Based on the motivation theory and social exchange theory, this paper divides corporate social responsibility (CSR) into business ethical responsibility and public welfare responsibility using the CSR division method proposed by McWilliams and Siegel, puts forward self-moral restraint as the proxy variable for business ethical responsibility and explains the relationship between CSR and customer extra-role behavior. It is found that customer extra-role behavior is positively influenced by platform enterprises’ social responsibility. The perception of interest consensus exerts a positive influence on extra-role behavior, so does the perception of service identity. The public welfare responsibility is positively influenced by business ethical responsibility.
Withdrawal from Long-Term Use of Unusually High-Dose Oxazepam
Authors: Mustonen Antti , Leijala Juhani , Aronranta Johanna , Lassila Antero , Aalto Mauri , Koskimäki Janne
Published: November 2021

Benzodiazepine (BZD) misuse is a worldwide problem that healthcare professionals encounter in daily practice. High-dose BZD withdrawal is usually a long process that may require referral to an inpatient rehabilitation unit. Relapses after withdrawal are common. BZD withdrawal can cause complications including seizures, suicidal behavior, anxiety, and depression. Guidelines describe tapering protocols for modest doses; however, protocols for exceptionally high-dose BZD withdrawal are not well described. Herein, we describe a BZD tapering protocol for a patient with daily use of high-dose (1800 mg) oxazepam (OXP). The BZD tapering was administered in an inpatient psychiatric hospital, and the outcome was evaluated monthly after discharge for three months. This report describes a unique case of high-dose OXP withdrawal and also outlines an optional protocol to apply when clinicians encounter these unusual cases.
Saphenous Vein Graft Aneurysm after Drug-Eluting Stent Implantation: Treatment by Covered Stent
Authors: Papadopoulos Kyriacos , Avraamides Panayiotis
Published: November 2021

Saphenous vein graft aneurysms (SVGAs) occur as a rare complication of coronary artery bypass graft but increases the risk of morbidity and mortality. Atherosclerosis is considered to be the most common cause of saphenous vein graft aneurysms. Other etiologies include infections, varicosities of vein grafts, and surgical technical issues. These aneurysms usually present as an incidental finding of a mediastinal or cardiac mass on chest radiograph. Symptomatic aneurysms may present with a wide variety of clinical manifestations such as chest pain/angina, shortness of breath, and myocardial infarction. Treatment options of SVG aneurysms include surgery, percutaneous intervention (including vascular plugs, covered stents, and embolization coils), and conservative management. Herein, we describe a case of a saphenous vein graft aneurysm that developed after percutaneous intervention, which has never been described, to our knowledge, in the previous literature. The aneurysm was treated with polytetrafluoroethylene covered stent implantation.
The Deformation Analysis of a Deep Frame Top‐Down Excavation in Downtown Shanghai Based on the 3D FEM
Authors: Bai Ting , Xie Dong
Published: November 2021

The deformation and environmental influence of the pit excavation in downtown is very important. A 3D FEM analysis is conducted to understand the deformation of a 13.9 to 15.2 m deep excavation with an in‐plane dimension of about 189 m width and 251 m length constructed by the frame top‐down method (FTDM) in the soft clay region in the Shanghai metropolitan area. The field monitoring results indicate that the magnitudes of wall deflections and ground settlements, along with the column’s uplift difference, are relatively small, which are below the specified protection levels, and that the FTDM is feasible as one of the extralarge excavation construction methods. It is reasonable to predict wall deflection by 3D FEM simulation with qualitative comparison between the simulated column uplifts and the measured data, yet the prediction of the settlement distribution is of no satisfaction. This project studied in this paper not only serves as a special case study calibrated and verified by numerical tools but also provides insights into the design and construction of an extralarge deep excavation using the frame top‐down method in soft soils and metropolitan environment.
Phenotypic Changes of LncRNA Hotair in Non-Small-Cell Lung Cancer and Its Clinical Application
Authors: Huang Haihua , Wang Jin , Liu Fabing
Published: November 2021

Non-small-cell lung cancer (NSCLC) is one of the main causes of death of malignant tumors of the respiratory system. At present, the clinical demand for biomarkers for predicting and diagnosing the disease is increasing. Overexpression of LncRNA Hotair (Homeobox transcriptional antisense intergenic RNA) has been previously reported to be associated with poor prognosis and high mortality in different malignancies. qRT-PCR results showed that the expression of LncRNA Hotair in tumor tissue and serum of patients with non-small-cell lung cancer was significantly upregulated. Clinicopathological correlation analysis showed that the upregulation of LncRNA Hotair expression was closely related to lymph node metastasis and tumor lymph node metastasis (TNM) stage (

P

 < 0.05). The results showed that transfection of pcDNA3.1-Hotair could promote the expression of LncRNA Hotair in NSCLC, while transfection of Si-Hotair could reduce the expression level of LncRNA Hotair, hinder the migration and invasion of cancer cells, and promote cell apoptosis. After transfection of Si-Hotair, molecular markers related to migration, the level of E-cadherin and Bax, increased and the level of vimentin, Bcl-2, MMP-3, VEGF, Ki-67 and PCNA decreased. This shows that the proliferation and migration of A549 cells are promoted and LncRNA Hotair deletion can inhibit the proliferation and migration of lung cancer cells. These results show that the expression level of LncRNA Hotair of NSCLC cell lines can promote the invasion and migration of NSCLC, and its expression has a significant correlation with Lymph node metastasis, tumor size, and TNM stage. Therefore, this target is of great significance for the clinical diagnosis and treatment of NSCLC.
Research on Intelligent Perception and Cognitive Computing of Information Security System Based on Computer Big Data
Authors: Guan Yi , Chen Qian
Published: November 2021

Since the 21st century, the development of network technology has entered a new stage, and mankind has gradually entered the era of big data with information explosion. Computer big data technology has changed people’s lifestyles. People can obtain information and materials without going out to provide convenience for people’s lives. But it is affected in many ways, but we will also encounter some difficulties in the process of using it. Informatization has had a profound impact on many areas of human social life. Especially in the context of global informationization, the information security (IS) problems encountered by China at this stage are more prominent and obvious than ever before. IS issues have also become a hot topic for many scholars to pay attention to and study. Informatization has gradually penetrated into every aspect of daily production work. However, the flow of enterprise informatization has made the public suffer from IS problems while improving office efficiency. This paper analyzes the shortcomings of current enterprise IS situation awareness; studies the construction of enterprise IS situation awareness system through big data technology, artificial intelligence algorithm, and threat intelligence technology; and puts forward the enterprise level IS situation awareness system model, situation awareness system, architecture, and specific implementation method. After analyzing the system design and deployment, the threats to corporate IS can be discovered in a more timely manner, and based on risk judgment and threat tracking, the company’s detection capabilities against security threats and security attacks can be improved, and effective security incident handling can be provided. Supported by technical means, the security situational awareness system will bring different protection and prevention to our enterprise.
[Retracted] Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm
Authors: Liu Binbin
Published: November 2021

In recent years, more and more attention has been paid to the utilization of data and information in the logistics distribution path optimization system of e‐commerce, but it is difficult to have scientific guarantee in the process of determining the optimal distribution path scheme of e‐commerce. How to realize the optimization and adaptive setting of distribution path by using intelligent algorithm has become a hot spot. To battle these issues, this paper studies the logistics distribution path optimization model based on recursive fuzzy neural network algorithm. This paper analyses the research status of logistics distribution path determination scheme and applies the recursive fuzzy neural network algorithm in the selection of e‐commerce logistics distribution path scheme. The experimental results show that the recursive fuzzy neural network algorithm can realize the optimization of e‐commerce logistics distribution path, and the best distribution route can be made according to the characteristic difference of logistics distribution route, and its distribution accuracy can reach more than 97%.
The Effect of Toric Intraocular Lens Implantation in Irregular Corneal Steep and Flat Meridian
Authors: Hwang Ho Sik , Kim Hyun Seung , Kim Man Soo , Kim Eun Chul
Published: November 2021

Purpose. To evaluate the effect of toric intraocular lens implantation in cataract patients with irregular corneal steep and flat meridian. Methods. Data of 112 eyes of 78 patients who underwent toric intraocular lens implantation were analyzed retrospectively. Steep meridian deviations (not 180°) and steep and flat meridian deviations (not 90°) were classified as 0, 1–9, 10–19, 20–29, 30–39, and over 30°. Meridian deviation was measured with a sagittal map of a rotating Scheimpflug camera (Pentacam®: Oculus, Wetzlar, Germany) using PicPickTools (NGWIN, Seoul, Korea). Results. Residual astigmatism (D) of 0 (0.51 ± 0.13, 0.55 ± 0.15) and 1–9 (0.61 ± 0.16, 0.66 ± 0.19) groups were significantly lower than that of 10–19 (0.92 ± 0.24, 0.90 ± 0.28), 20–29 (0.10 ± 0.32, 1.01 ± 0.35), and over 30° groups (1.12 ± 0.37, 1.14 ± 0.40) both in steep meridian deviations and horizontal and vertical meridian deviations at 6 months (

P
<
0.05

). Postoperative mean UCVA (logMAR) of 0 (0.09 ± 0.04, 0.09 ± 0.05) (logMAR) and 1–9 (0.10 ± 0.04, 0.11 ± 0.08) groups was significantly improved compared to that of 10–19 (0.14 ± 0.05, 0.17 ± 0.10), 20–29 (0.18 ± 0.08, 0.21 ± 0.10), and over 30° groups (0.20 ± 0.09, 0.22 ± 0.11) both in steep meridian deviations and horizontal and vertical meridian deviations at 6 months (

P
<
0.05

). Conclusions. Correction of astigmatism with toric intraocular lens implantation is not accurate in corneas with steep meridian deviations and steep and flat meridian deviations of more than 10°. Therefore, care should be taken when we perform toric intraocular lens implantation in patients with irregular corneal meridian.
The Impact of New-Onset Diabetes Mellitus and Hypertension on All-Cause Mortality in an Apparently Healthy Population: A Ten-Year Follow-Up Study
Authors: Charoensri Suranut , Kritmetapak Kittrawee , Tangpattanasiri Tassanapong , Pongchaiyakul Chatlert
Published: November 2021

Introduction. The comparative effect of new-onset diabetes mellitus (DM) and hypertension (HT) on long-term mortality is a matter of debate. Materials and Methods. From 2007 to 2017, a 10-year longitudinal retrospective cohort study was conducted in Thailand’s tertiary care setting. As baseline data, health check-up data from apparently healthy participants without underlying disease from 2007 were extracted. The vital status of all participants was determined in 2017, ten years after an initial examination. The impact of new-onset DM and HT at baseline on 10-year all-cause mortality was investigated using multivariable logistic regression analysis. Results. The prevalence of new-onset DM and HT was 6.4% and 28.8%, respectively, at baseline. Newly diagnosed diabetes increased the risk of all-cause mortality over 10 years (adjusted OR 4.77 and 95% CI 2.23-9.99). HT, on the other hand, did not increase the risk of death (adjusted OR 1.24 and 95% CI 0.65-2.35). Different HT and DM status combinations were compared to a nondiabetic, nonhypertensive reference. Individuals who were diabetic and hypertensive had a greater risk of death (adjusted OR 6.22 and 95% CI 2.22-17.00). Having DM without HT also increased the risk of death (adjusted OR 4.36 and 95% CI 1.35-12.87). However, having HT without DM did not result in a significant increase in 10-year mortality risk (adjusted OR 1.21 and 95% CI 0.57-2.56). Conclusion. In an apparently healthy population, new-onset DM is more strongly associated with 10-year all-cause mortality than new-onset HT. Having both DM and HT was associated with a greater risk of death when compared to having DM or HT alone.
An Empirical Study on Intelligent Rural Tourism Service by Neural Network Algorithm Models
Authors: Chen Jingzhi , Xue Hongbo , Tsa Sang-Bing
Published: November 2021

With the continuous development of social economy, tourism has become one of the many choices and is becoming more and more popular. However, it should be noted that how to provide high‐quality and efficient tourism services is extremely important. This paper introduces the neural network algorithm and the optimal classification decision function, through unified combing, classification, and coding of scenic spots, to achieve the subclass classification of scenic spots, based on the optimal distribution function of random intelligent selection, and the formation of the corresponding scenic spots traversal clear tourism routes. The corresponding motivation iteration is obtained by using the corresponding travel route transmission, the best travel route is defined, the corresponding auxiliary decision support is provided, and the simulation experiment is carried out. The experimental results show that the neural network algorithm and the optimal classification decision function are effective and can support the intelligent decision assistance of rural tourism service.
On Topological Analysis of Entropy Measures for Silicon Carbides Networks
Authors: Wang Xing-Long , Siddiqui Muhammad Kamran , Kirmani Syed Ajaz K. , Manzoor Shazia , Ahmad Sarfraz , Dhlamini Mlamuli
Published: November 2021

The silicon material has provoked and stimulated significant research concern to a considerable extent taking into account its marvelous mechanical, optical, and electronic properties. Naturally, silicons are semiconductors and are utilized in the formation of various materials. For example, it is used in assembling the electronic based gadgets. In this article, we have studied the 2D structure of silicon carbide Si2C3 − I[m, n] and Si2C3 − II[m, n] and then continued to discuss some degree grounded topological descriptors in association with their corresponding entropy measures. We extend this computation to the quantitative and pictorial comparisons which could be beneficial in the structure amendment for effective implementation.
Early Warning for the Construction Safety Risk of Bridge Projects Using a RS‐SSA‐LSSVM Model
Authors: Li Gang , Ran Ruijiang , Fang Jun , Peng Hao , Wang Shengmin
Published: November 2021

Bridge engineering is an important component of the transportation system, and early warnings of construction safety risks are crucial for bridge engineering construction safety. To solve the challenges faced by early warnings risk and the low early warning accuracy in bridge construction safety, this study proposed a new early‐warning model for bridge construction safety risk. The proposed model integrates a rough set (RS), the sparrow search algorithm (SSA), and the least squares support vector machine (LSSVM). In particular, the initial early warning factors of bridge construction safety risk from five factors (men, machines, methods, materials, and environment) were selected, and the RS was used to reduce the attributes of 20 initial early warning factors to obtain the optimized early warning factor set. This overcame the problem of multiple early warning factors and reduced the complexity of the subsequent prediction model. Then, the LSSVM with the strongest nonlinear modelling ability was selected to build the bridge construction early‐warning model and adopted the SSA to optimize the LSSVM parameter combination, improving the early warning accuracy. The Longlingshan Project in Wuhan and the Shihe Bridge Project in Xinyang, China, were then selected as case studies for empirical research. Results demonstrated a significant improvement in the performance of the early‐warning model following the removal of redundancy or interference factors via the RS. Compared with the standard LSSVM, Back Propagation Neural Network and other traditional early‐warning models, the proposed model exhibited higher computational efficiency and a better early warning performance. The research presented in this article has important theoretical and practical significance for the improvement of the early warning management of bridge construction safety risks.
An Improved Lattice Hydrodynamic Model by considering the Effect of “Backward‐Looking” and Anticipation Behavior
Authors: Wan Jin , Huang Xin , Qin Wenzhi , Gu Xiuge , Zhao Min
Published: November 2021

In order to prevent the occurrence of traffic accidents, drivers always focus on the running conditions of the preceding and rear vehicles to change their driving behavior. By taking into the “backward‐looking” effect and the driver’s anticipation effect of flux difference consideration at the same time, a novel two‐lane lattice hydrodynamic model is proposed to reveal driving characteristics. The corresponding stability conditions are derived through a linear stability analysis. Then, the nonlinear theory is also applied to derive the mKdV equation describing traffic congestion near the critical point. Linear and nonlinear analyses of the proposed model show that how the “backward‐looking” effect and the driver’s anticipation behavior comprehensively affect the traffic flow stability. The results show that the positive constant γ, the driver’s anticipation time τ, and the sensitivity coefficient p play significant roles in the improvement of traffic flow stability and the alleviation of the traffic congestion. Furthermore, the effectiveness of linear stability analysis and nonlinear analysis results is demonstrated by numerical simulations.
Development, Optimization, and Evaluation of Luliconazole Nanoemulgel for the Treatment of Fungal Infection
Authors: Alhakamy Nabil A. , Md Shadab , Alam Md Shoaib , Shaik Rasheed A. , Ahmad Javed , Ahmad Abrar , Kutbi Hussam I. , Noor Ahmad O. , Bagalagel Alaa , Bannan Douha F. , Gorain Bapi , Sivakumar Ponnurengam Malliappan
Published: November 2021

The present study aimed to optimize luliconazole nanoemulsion using Box–Behnken statistical design, which was further incorporated into the polymeric gel of Carbopol 934. The formulation was characterized for its size, entrapment efficiency, ex vivo permeation, and mechanism of release. The size of the dispersed globules of the optimized drug-loaded nanoemulsion was found to be 17 ± 3.67 nm with a polydispersity index (PDI) less than 0.5. Although the surface charge was recorded at –9.53 ± 0.251, the stability was maintained by the polymeric matrix that prevented aggregation and coalescence of the dispersed globules. The luliconazole-nanoemulgel (LUL-NEG) was characterized for drug content analysis, viscosity, pH, and refractive index, where the results were found to be 99.06 ± 0.59%, 9.26 ± 0.08 Pa.s, 5.65 ± 0.17, and 1.31 ± 0.08, respectively. The permeation across the rat skin was found to be significantly higher with LUL-NEG when compared with LUL gel. Furthermore, the skin irritation test performed in experimental animals revealed that the blank NEG, as well as the LUL-NEG, did not produce any signs of erythema following 48 h exposure. In addition, the histopathological findings of the experimental skins reported no abnormal signs at the formulation application site. Finally, the NEG formulation was found to create a statistically significant zone of inhibition (

P

 < 0.05) when compared to all other test groups. Overall, it could be summarized that the nanoemulgel approach of delivering luliconazole across the skin to treat skin fungal infections could be a promising strategy.
Barriers to Maternal and Child Health Care Service Uptake in Assosa Zone, Benishangul Gumuz Region, Ethiopia: A Qualitative Study
Authors: Agajie Mulatu , Abera Solen , Yimer Eshetu , Yaregal Gizachew , Muhidin Amir , Kelbessa Wagari , Ayana Dula , Shaweno Debebe
Published: November 2021

Background. Ethiopia has reduced maternal mortality from 871 to 412 per 100,000 live births between 2000 and 2016. In 2019, under-5 mortality rates in Ethiopia were 55 deaths per 1,000 live births. Benishangul Gumuz was the second-largest region in the under-5 mortality rate (98/1,000 live births) in the country. Maternal and child health care service uptake is an important indicator of health outcomes. This study is aimed at exploring major barriers to maternal and child health care uptake in Assosa Zone. Methods. This study was conducted in the Bambasi, Menge, and Sherkole districts of the Assosa Zone from July 17 to August 31/2019. The study explored the life experience of study participants about MCH services. The sampling technique was purposive, and data collection methods were focus group discussions, key informant interviews, and in-depth interviews. Data were analyzed thematically. Result. The main barriers to child health care services were financial problems, lack of knowledge, preference of traditional medicines for a sick child, women having no time to care for their sick child, poor roads. poor health facility readiness, the poor economy of families, lack of ambulance, cultural and traditional beliefs, providers being male, and unprofessional behaviors which were the major barriers hindering the uptake of maternal health service utilization. Conclusion. Poor health facility readiness, indirect costs, inaccessibility to health facilities, and cultural and traditional practices were among the major barriers to service uptake identified by this research in the study area.
Preventing Scan-Based Side-Channel Attacks by Scan Obfuscating with a Configurable Shift Register
Authors: Wang Weizheng , Chen Yin , Cai Shuo , Peng Yan
Published: November 2021

Scan test is widely used in integrated circuit test. However, the excellent observability and controllability provided by the scan test gives attackers an opportunity to obtain sensitive information by using scan design to threaten circuit security. Hence, the primary motivation of this paper is to improve the existing DFT technique, i.e., to enhance the chip security on the premise of guaranteeing test quality. In this paper, we propose a new scan design method against scan-based side-channel attack. In the proposed method, the encryption structure is adopted, which requires the correct test authorization code to carry out normal test operation. Without the correct test authorization, the attackers cannot obtain the desired scan data, preventing the scan-based side-channel attacks. Furthermore, the test authorization code is determined by the nonvolatile memory built into the chip to realize the inconsistency of the test authorization code for each chip.
The Ability of Hop Extracts to Reduce the Methane Production of Methanobrevibacter ruminantium
Authors: Blaxland J. A. , Watkins A. J. , Baillie L. W. J.
Published: November 2021

Background. Methane emissions from agriculture are responsible for over 40% of the world’s greenhouse gas emissions. In the past, antibiotics were used to control methane production by animals, but concerns over the emergence and spread of antibiotic-resistant bacteria to humans have prompted a search for alternative approaches. Hops are the flowers of the hop plant Humulus lupulus. They have been used to feed cattle for many years and are known to contain antibacterial compounds, and their extracts have been shown to kill members of the Mycobacterium spp including Mycobacterium bovis, the causative agent of bovine tuberculosis as well as a number of human pathogens. In this study, hop extracts were studied for their ability to inhibit methane production from Methanobrevibacter ruminantium, a major methane-producing archaeon found in the rumen of cattle. Methods. Methanobrevibacter ruminantium M1T (DSM 1093) was grown at 37°C for 30 days, and the amount of methane produced at different time points during this period was measured using gas chromatography. The archaeon was exposed to commercial hop extracts (tetra-hydro-iso-alpha acid and beta acid) and to aqueous hop extracts of a range of hop variants, and their effect on methane production was determined. Results. All of the extracts reduced the level of methane production of M. ruminantium over the 30-day period compared to the negative control (sterile distilled water). The commercial hop extracts were the most effective at inhibiting methane production over the course of the experiment in contrast to the aqueous extracts, which showed a gradual reduction of inhibition with time. Conclusions. Hops contain compounds which inhibit methane production. Given that hops can be safely fed to cattle, this raises the possibility of rationally designing a feed strategy which could reduce greenhouse gas emissions and protect against bovine tuberculosis. This study recommends that further research be undertaken to further identifying bioactive components from hops and their efficacy against a range of archaea.
The Upregulation of PLXDC2 Correlates with Immune Microenvironment Characteristics and Predicts Prognosis in Gastric Cancer
Authors: Li Yang , Li Jia-qi , Jiang Hai-ping , Li Xin
Published: November 2021

Tumor microenvironment (TME) has been demonstrated to exhibit a regulatory effect on the progressions of gastric cancer (GC). However, the related functions of stromal and immune components (TME-associated genes) in TME remain largely unclear. From the TCGA dataset, we downloaded the clinical data of 375 GC cases and then estimated the percentage of tumor-infiltrating immunocytes (TICs) and the levels of immune and stromal constituents by the use of CIBERSORT and ESTIMATE tolls. Univariate assays were applied to study the differentially expressed genes. The associations between the clinical information of GC patients and the expressions of the specific genes were analyzed based on the TCGA datasets. The effect of Plexin domain containing 2 (PLXDC2) expression on TICs was conducted. We observed that PLXDC2 expression was distinctly upregulated in GC specimens compared with nontumor gastric specimens. Its upregulation was associated with advanced clinical stages and predicted a shorter overall survival of GC patients. The genes in the group of higher expressing PLXDC2 were primarily enriched in immunity-associated events. By the use of CIBERSORT, we observed that PLXDC2 expressions were related to the proportion of dendritic cells resting, T cell CD4 memory resting, eosinophils, mastocyte resting, mononuclear cells, plasma cells, T cell follicle helper, macrophage M2, and dendritic cells activated. Overall, our discoveries revealed that the expression of PLXDC2 was remarkable in GC, might be a possible biomarker for GC, and provided novel contents regarding immune infiltrates, offering novel insight for treatments of GC.
A Pulmonary Vascular Extraction Algorithm from Chest CT/CTA Images
Authors: Xu Shihui , Zhang Ziming , Zhou Qinghua , Shao Wei , Tan Wenjun
Published: November 2021

Segmentation of pulmonary vessels in CT/CTA images can help physicians better determine the patient’s condition and treatment. However, due to the complexity of CT images, existing methods have limitations in the segmentation of pulmonary vessels. In this paper, a method based on the separation of pulmonary vessels in CT/CTA images is investigated. The method is divided into two steps: in the first step, the lung parenchyma is extracted using the Unet++ algorithm, which can effectively reduce the oversegmentation rate; in the second step, the pulmonary vessels in the lung parenchyma are extracted using nnUnet. According to the obtained lung parenchyma segmentation results, the “AND” operation is performed on the original image and the lung parenchyma segmentation results, and only the blood vessels within the lung parenchyma are segmented, which reduces the interference of external tissues and improves the segmentation accuracy. The experimental data source used CT/CTA images acquired from the partner hospital. After the experiments were performed on a total of 67 sets of images, the accuracy of CT and CTA images reached 85.1% and 87.7%, respectively. The comparison of whether to segment the lung parenchyma and with other conventional methods was also performed, and the experimental results showed that the algorithm in this paper has high accuracy.
Luteolin Confers Cerebroprotection after Subarachnoid Hemorrhage by Suppression of NLPR3 Inflammasome Activation through Nrf2‐Dependent Pathway
Authors: Zhang Zi-Huan , Liu Jia-Qiang , Hu Cheng-Di , Zhao Xin-Tong , Qin Fei-Yun , Zhuang Zong , Zhang Xiang-Sheng
Published: November 2021

Luteolin (LUT) possesses multiple biologic functions and has beneficial effects for cardiovascular and cerebral vascular diseases. Here, we investigated the protective effects of LUT against subarachnoid hemorrhage (SAH) and the involvement of underlying molecular mechanisms. In a rat model of SAH, LUT significantly inhibited SAH‐induced neuroinflammation as evidenced by reduced microglia activation, decreased neutrophil infiltration, and suppressed proinflammatory cytokine release. In addition, LUT markedly ameliorated SAH‐induced oxidative damage and restored the endogenous antioxidant systems. Concomitant with the suppressed oxidative stress and neuroinflammation, LUT significantly improved neurologic function and reduced neuronal cell death after SAH. Mechanistically, LUT treatment significantly enhanced the expression of nuclear factor‐erythroid 2‐related factor 2 (Nrf2), while it downregulated nod‐like receptor pyrin domain‐containing 3 (NLRP3) inflammasome activation. Inhibition of Nrf2 by ML385 dramatically abrogated LUT‐induced Nrf2 activation and NLRP3 suppression and reversed the beneficial effects of LUT against SAH. In neurons and microglia coculture system, LUT also mitigated oxidative stress, inflammatory response, and neuronal degeneration. These beneficial effects were associated with activation of the Nrf2 and inhibitory effects on NLRP3 inflammasome and were reversed by ML385 treatment. Taken together, this present study reveals that LUT confers protection against SAH by inhibiting NLRP3 inflammasome signaling pathway, which may be modulated by Nrf2 activation.
Outage Constraint Robust Cooperative Beamforming and Jamming Design for Secure AF Relay Networks
Authors: Zhu Jinxin , Shao Jun
Published: November 2021

This paper investigates a joint robust scheme in a secrecy relay network where distributed relays perform cooperative beamforming and a friendly jammer transmits jamming signal to enhance the information security. Specifically, we consider the outage constraint secrecy rate maximization design with imperfect channel state information. Through semidefinite relaxation and one-dimensional search, we propose a two-layer optimization method to solve the nonconvex problem. In addition, the Bernstein-type inequality and large deviation inequality are utilized to convert the probabilistic constraint. Simulation results demonstrate the performance of the proposed design.
Evaluation of Antimicrobial Activity of Conyza bonariensis Leaf Extracts against Clinically Isolated Fungi Causing Superficial Infection
Authors: Girma Yidnekachew , Jiru Tamene Milkessa
Published: November 2021

Plants have been used since long time ago to treat infectious diseases and are considered as important sources of new antimicrobial agents. In this study, crude extracts from leaves of Conyza bonariensis were prepared using methanol, ethyl acetate, hexane, and chloroform. Antimicrobial activity of the extracts was evaluated against pathogenic fungi causing superficial infection (Candida albicans, Malassezia globosa, and Malassezia furfur). Results demonstrated that all extracts had different effects against all the tested fungi with the exception of crude extract using hexane which did not show any effect against M. furfur. A strong effect was observed with chloroform and hexane extracts on C. albicans (32.60 ± 4.69 mm and 27.00 ± 1.00 mm), respectively. While, ethyl acetate and methanol extracts showed the best effect against M. furfur (30.80 ± 1.71 mm and 27.00 ± 1.00 mm), respectively. Moreover, the ethyl acetate showed a considerable effect on M. globosa (25.03 ± 1.05 mm). Minimum inhibitory concentration (MIC) of the fractions was also determined by the microbroth dilution method. The results recorded as the MIC values of the tested extracts against fungi varied from 0.19 ± 0.00 to 66.66 ± 2.86 mg/mL. Ethyl acetate was the best and powerful extract with the lowest MIC value of 0.190.19 ± 0.00 mg/mL for all tested fungi followed by chloroform and methanol extracts with the MIC values ranging from 0.19 ± 0.00 to 0.78 ± 0.00 mg/mL and 0.84 ± 0.68 to 1.56 mg/mL, respectively. Concerning minimum bactericidal concentration (MFC), ethyl acetate was the most potent extract with a MFC value of 0.190.19 ± 0.00 mg/mL for C. albicans and M. furfur. Higher (0.39 mg/mL) MFC was recorded against M. globosa by this extract. In conclusion, solvent extracts of some C. bonariensis can be used to treat infections with pathogenic fungi such as C. albicans, M. furfur, and M. globosa. Further studies should consider this plant as one of the best candidates for the discovery of potent antimicrobial compounds that treat superficial infections.
Tree-Based Public Key Encryption with Conjunctive Keyword Search
Authors: Zhang Yu , You Lei , Li Yin
Published: November 2021

Searchable public key encryption supporting conjunctive keyword search is an important technique in today’s cloud environment. Nowadays, previous schemes usually take advantage of forward index structure, which leads to a linear search complexity. In order to obtain better search efficiency, in this paper, we utilize a tree index structure instead of forward index to realize such schemes. To achieve the goal, we first give a set of keyword conversion methods that can convert the index and query keywords into a group of vectors and then present a novel algorithm for building index tree based on these vectors. Finally, by combining an efficient predicate encryption scheme to encrypt the index tree, a tree-based public key encryption with conjunctive keyword search scheme is proposed. The proposed scheme is proven to be secure against chosen plaintext attacks and achieves a sublinear search complexity. Moreover, both theoretical analysis and experimental result show that the proposed scheme is efficient and feasible for practical applications.
[Retracted] Social Recommendation System Based on Hypergraph Attention Network
Authors: Xia Zhongxiu , Zhang Weiyu , Weng Ziqiang
Published: November 2021

In recent years, due to the rise of online social platforms, social networks have more and more influence on our daily life, and social recommendation system has become one of the important research directions of recommendation system research. Because the graph structure in social networks and graph neural networks has strong representation capabilities, the application of graph neural networks in social recommendation systems has become more and more extensive, and it has also shown good results. Although graph neural networks have been successfully applied in social recommendation systems, their performance may still be limited in practical applications. The main reason is that they can only take advantage of pairs of user relations but cannot capture the higher‐order relations between users. We propose a model that applies the hypergraph attention network to the social recommendation system (HASRE) to solve this problem. Specifically, we take the hypergraph’s ability to model high‐order relations to capture high‐order relations between users. However, because the influence of the users’ friends is different, we use the graph attention mechanism to capture the users’ attention to different friends and adaptively model selection information for the user. In order to verify the performance of the recommendation system, this paper carries out analysis experiments on three data sets related to the recommendation system. The experimental results show that HASRE outperforms the state‐of‐the‐art method and can effectively improve the accuracy of recommendation.
Wireless Sensor Network‐Based Mathematical Modeling for Communication Intelligent Monitoring System
Authors: Shen Ying
Published: November 2021

Knowing the behavioral patterns of city residents is of great value in formulating and adjusting urban planning strategies, such as urban road planning, urban commercial development, and urban pedestrian flow control. Based on the high penetration rate of cell phones, it is possible to indirectly understand the behavior of city residents based on the call records of users. However, the behavioral patterns of large‐scale users over a long period of time can present characteristics such as large dispersion, difficult to discover patterns, and difficult to explain behavioral patterns. In this paper, we design and implement a human behavior pattern analysis system based on massive mobile communication data based on serial data modeling method and visual analysis technology. For the problem that it is difficult to capture the behavioral patterns of residents in cities in call records, this paper constructs base station trajectories based on users’ cell phone call records and uses users’ long‐time base station trajectories to mine users’ potential behavioral patterns. Since users with similar activity characteristics will exhibit similar base station trajectories, this paper focuses on the similarity between text sequences and base station trajectory sequences and combines the word embedding method in natural language processing to build a Cell2vec model to identify the semantics of base stations in cities. In order to obtain the group behavior patterns of users from the base station trajectories of group users, a user clustering method based on users’ regional mobile preferences is proposed, and the results are projected using the Stochastic Neighbor Embedding (t‐SNE) algorithm to expose the clustering features of large‐scale cell phone users in the low‐dimensional space. To address the problem that user behavior patterns are difficult to interpret, a visual analysis model with group as well as regional semantics is designed for the spatial and temporal characteristics of user behavior. Among them, the clustering model uses the distance between scatter points to map the similarity between users, which helps analysts to explore the behavioral characteristics of group users.
BDNF Acts as a Prognostic Factor Associated with Tumor-Infiltrating Th2 Cells in Pancreatic Adenocarcinoma
Authors: Zhu Yanan , Zhang Cangang , Zhao Dongyu , Li Wenhua , Zhao Zhe , Yao Shukun , Zhao Dongyan
Published: November 2021

Pancreatic adenocarcinoma (PAAD) is an extremely lethal disease worldwide. Brain-derived neurotrophic factor (BDNF) is a critical member of the neurotrophin polypeptide superfamily that plays an important role in multiple cancers. However, the association among BDNF expression, tumor immunity, and PAAD prognosis remains unclear. BDNF expression and its influence on patient prognosis were explored based on The Cancer Genome Atlas, Cancer Cell Line Encyclopedia, Genotype-Tissue Expression, and Kaplan-Meier plotter. Gene set enrichment analysis was performed to understand the biological roles of BDNF. The role of BDNF in tumor-infiltrating immune cells was determined using the Tumor Immune Estimation Resource database and the single-sample gene set enrichment analysis and xCell algorithm. The correlation among BDNF and chemokines, chemokine receptors, chemotherapeutic efficacy, and immune checkpoints was analyzed based on RStudio. BDNF expression was remarkably higher in PAAD compared to their paired normal tissues, and high BDNF expression was associated with unfavorable prognosis. Enrichment analysis revealed that BDNF was significantly enriched in major oncogenic pathways in PAAD. BDNF expression was positively correlated with immune infiltration, especially Th2 cells. Moreover, BDNF expression was positively correlated with Th2 cell-related chemokine/chemokine receptors, indicating that BDNF might modulate the migration of Th2 cells in PAAD. We also found that BDNF expression was correlated with high chemotherapeutics sensitivity and highly expressed immune checkpoints, making it a valuable biomarker in predicting the therapeutic benefits for chemotherapy and immunotherapy in cancer patients. In summary, BDNF might affect patient prognosis by interacting with tumor-infiltrating Th2 cells, thus serving as a potential prognostic biomarker in PAAD.
Planning and Scheduling Process for a Grid‐Connected Microgrid Based on Renewable Energy Sources by a Novel Fuzzy Method
Authors: Lijun Zhao , Qingsheng Li , Guanhua Ding
Published: November 2021

High growth of the population and developed industries, on the one hand, increased the demanded energy considerably. Growth of the fossil fuel‐based power generation, on the other hand, has high environmental effects. Accordingly, renewable energy sources are mainly interested in the recent years as clean resources. These sources also can be economical cases in long term. Nevertheless, their intermittent feature is a main drawback. Integration of these resources with the rest of the grid can increase their advantages and tackle their main drawbacks. In the present work, a novel programming method is proposed for energy management and optimization of operational expenses over a grid‐connected microgrid (MG). The considered MG contains various renewable resources. Some uncertainties should be considered in the integration of renewable resources with the grid, which can affect the system performance. Main uncertain parameters are studied in this paper such as predicted values for green power sources, maximum capacity for fuel cells (FCs), energy storage sources (ESSs), maximum capacity for transmission line, and also hourly loads, achieving a higher efficiency. This paper utilized fuzzy idea for presentation of mentioned uncertain parameters in the MG. Moreover, this work employed a 3‐stage optimization algorithm for obtaining the best programming for the MG by considering the uncertain parameters. This paper also used a practical test system to validate the proposed method through minimizing the total cost. Additionally, a sensitivity analysis is performed to study the effects of oscillations of all components in the MG and their associated uncertainties over the obtained results.
[Retracted] Observation of the Clinical Correlation between Carotid Artery Intima‐Media Thickness and Cardiovascular Risk Factors in Hypertensive Patients under Microscope Images
Authors: Wu Na
Published: November 2021

With the development of social science and technology and people’s demand for exploring the micro world, digital microscope technology came into being. Microscope image processing technology has been widely used in industrial micromanipulation, biomedicine, and cultural relic identification and preservation. In order to in‐depth study the use of microscope image technology to observe the thickness of the carotid artery intima‐media in hypertensive patients to find out whether it is feasible to explore many risk factors for cardiovascular development, this article uses data analysis, concept analysis, and graphic construction methods to collect samples, analyzed the image, streamlined the algorithm, and created a microscope image that can study its risk factors. The severity of hypertension, diabetes, and other factors affects the thickness of carotid arteries and cardiovascular diseases. The results show that the longer the duration of hypertension, the higher the central and peripheral blood pressure, the higher the height, and the higher the central blood pressure, which is relatively low. The detection rate of elevated central blood pressure is higher (76.8%). The second group (53.6%) and the third group (49.2%) (P < 0.008); older age, the central blood pressure is relatively high, and the detection rate of central blood pressure increases (75.5%). It is higher than normal blood pressure (24.5%), so it can be concluded that hypertension not only affects central blood pressure but also peripheral blood; height and age are independent factors that affect central blood pressure. It is basically realized that starting from the microscope image, many risk factors of cardiovascular disease have been successfully analyzed.
A Novel COVID-19 Diagnosis Support System Using the Stacking Approach and Transfer Learning Technique on Chest X-Ray Images
Authors: Hamida Soufiane , El Gannour Oussama , Cherradi Bouchaib , Raihani Abdelhadi , Moujahid Hicham , Ouajji Hassan
Published: November 2021

COVID-19 is an infectious disease-causing flu-like respiratory problem with various symptoms such as cough or fever, which in severe cases can cause pneumonia. The aim of this paper is to develop a rapid and accurate medical diagnosis support system to detect COVID-19 in chest X-ray images using a stacking approach combining transfer learning techniques and KNN algorithm for selection of the best model. In deep learning, we have multiple approaches for building a classification system for analyzing radiographic images. In this work, we used the transfer learning technique. This approach makes it possible to store and use the knowledge acquired from a pretrained convolutional neural network to solve a new problem. To ensure the robustness of the proposed system for diagnosing patients with COVID-19 using X-ray images, we used a machine learning method called the stacking approach to combine the performances of the many transfer learning-based models. The generated model was trained on a dataset containing four classes, namely, COVID-19, tuberculosis, viral pneumonia, and normal cases. The dataset used was collected from a six-source dataset of X-ray images. To evaluate the performance of the proposed system, we used different common evaluation measures. Our proposed system achieves an extremely good accuracy of 99.23% exceeding many previous related studies.