bluuebunny/crossref_metadata_2025 huggingface dataset:
Fuzzy Testing Method of CAN Bus of Charging Pile Based on Genetic Algorithm
Authors: Liu Chang , Wang Xueqiong , Tian Li , Mei Song , Zhang Zhendong
Published: April 2022

With the guidance of the new energy policy and the continuous expansion of the new energy market, electric vehicles are the development direction of the automotive industry in the future, and the electric vehicle charging infrastructure is an important guarantee for the use of electric vehicles, which plays a positive role in promoting the popularity of electric vehicles. CAN bus protocol is the communication protocol between charging pile and electric vehicle, and its security concerns the safety of electric vehicles. In this article, a CAN bus fuzzy testing method based on genetic algorithm is proposed to solve the security problem of charging pile CAN bus. In this method, genetic algorithm is added in the fuzzy testing process of CAN bus protocol, that is, genetic algorithm is introduced in the generation of fuzzy data to search the test case that best conforms to CAN bus protocol, so as to greatly improve the detection efficiency of CAN bus protocol.
Orderings of Extreme Claim Amounts from Heterogeneous and Dependent Weibull‐G Insurance Portfolios
Authors: Liu Ling , Yan Rongfang
Published: April 2022

In the context of insurance, the smallest and largest claim amounts become increasingly important in the context of insurance analysis, which provides crucial and key information for setting an annual premium. We first give some sufficient conditions for comparing the largest claim amounts arising from two sets of dependent heterogeneous Weibull‐G insurance portfolios with respect to the usual stochastic order under Archimedean copula dependence. Second, we establish some sufficient conditions to compare the smallest claim amounts in the sense of the usual stochastic and hazard rate orders when the claim severities are independent or dependent heterogeneous Weibull‐G insurance portfolios. Finally, to illustrate the key theoretical insights, some numerical examples are offered.
Decision-Making with Risk under Interval Uncertainty Based on Area Metrics
Authors: Yan Ying , Suo Bin
Published: April 2022

From the perspective of D-S evidence theory and area measurement, a risk-based comprehensive decision-making method that considers both the expected utility and the uncertainty of the scheme is proposed under the interval uncertainty environment of attribute values. The upper and lower bounds of the synthetic probability distribution of attributes values in different natural states are constructed based on the belief measure and plausibility measure. Based on the area measurement, a method for calculating the expected utility of each scheme is proposed. To reflect the influence of the uncertainty in the evaluation value of each scheme attribute on the final decision result, two indexes are defined: the evaluation uncertainty of attributes (EUA) and the uncertainty of the expected utility of scheme (UEU). Finally, considering the expected value of the expected utility and its uncertainty, three decision methods, namely, risk-neutral, risk-averse, and risk-preference, are constructed. An example is considered to show that the proposed method is effective and practical, and the uncertainty of the expected utility has a significant impact on the result of risky decisions. The new method can solve the problems of existing methods that overlook the impact of epistemic uncertainty on the decision-making process.
Integrated Network Pharmacology and UPLC/Q-TOF-MS Screen System to Exploring Anti-Inflammatory Active Components and Mechanism of Shunaoxin Pills
Authors: Chang Nianwei , Wang Yu , Jiang Min , Bai Gang
Published: April 2022

Background. Chronic cerebral ischemia (CCI) is a pathological condition associated with a variety of cerebrovascular diseases. Shunaoxin pills (SNX) are a traditional Chinese medicine (TCM) used to improve blood circulation. However, its multicomponent and multitarget features make it difficult to decipher the molecular mechanisms. Objective. Thus, in this study, we aimed to identify the key anti-inflammatory components of SNX as markers for standardization and quality control and the potential pharmacological mechanisms of SNX in the treatment of CCI by network pharmacology to provide scientific evidence of its clinical efficacy. Methods. We evaluated the anti-inflammatory effect of SNX using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectroscopy (UPLC/Q-TOF-MS) combined with a dual-luciferase reporter assay for nuclear factor kappa B (NF-κB) inhibition to identify the active components in SNX. In addition, key pathways involved in the anti-inflammatory effect of SNX were predicted using a network pharmacology approach, and some crucial proteins and pathways were further validated by Western blotting. Results. Shunaoxin pills inhibited NF-κB through tumor necrosis factor-α (TNF-α) stimulation in 293T cells. The therapeutic effect may be related to 10 pathways regulated by ligustilide, ferulic acid, ligustrazine, and senkyunolide I. It was further confirmed that ligustilide could reduce the inflammatory response by inhibiting the phosphorylation of p38 and 3-phosphoinositide-dependent kinase 1 (PDK1). Conclusions. Ligustilide, senkyunolide I, ferulic acid, and ligustrazine could be used as anti-inflammatory Q-markers to control the quality of SNX, and p38 and PDK1 might be potential targets of SNX in the treatment of CCI.
Intervention Mechanism of Hunag-Lian Jie-Du Decoction on Canonical Wnt/β-Catenin Signaling Pathway in Psoriasis Mouse Model
Authors: Yang Xuesong , Luo Guangyun , Fu Lan , Huang Hong , Wang Lifen , Yin Lihua , Zhang Xuelian , Wang Tingting , Ma Xuan , Feng Tianyu , Ye Jianzhou
Published: April 2022

Background. Psoriasis is a common chronic inflammatory skin disease with multifactor etiology, characterized by abnormal proliferation and differentiation of keratinocytes. Huang-Lian Jie-Du decoction (HLJDD) is a traditional Chinese medicine prescription with good clinical curative effect on psoriasis. However, its therapeutic mechanisms are still unclear. Methods. The psoriasis model of SKH-1 nude mice was established by imiquimod-induced and HLJDD gavage was given. Hematoxylin and eosin staining were used to evaluate pathological morphologies, and immunohistochemistry was used to detect the expressions of Wnt1, β-catenin, and c-Myc in psoriasis mice. Western blot was used to examine the expressions of Frizzled-2, LRP5/6, GSK-3β, APC, Axin2, TCF4, LEF1, cyclin D1, TBX3, EPHB2, and NOTUM enzyme. Results. In this study, HLJDD reduced skin erythema and lesions, decreased the thickness of epidermal and downregulated the expressions of Wnt1, β-catenin, and c-Myc. Western blot results showed that HLJDD reduced the expressions of Wnt receptors Frizzled-2 and LRP5/6, and Wnt downstream target genes TCF4, LEF1, cyclin D1, TBX3, and EPHB2, while upregulated destruction complex proteins GSK-3β, APC, and Axin2. Conclusions. HLJDD can effectively treat psoriasis and inhibit the Wnt/β-catenin signaling pathway at multiple stages.
Investigation on Forestry Wood Wastes: Pyrolysis and Thermal Characteristics of Ficus religiosa for Energy Recovery System
Authors: Rao Yarrapragada K. S. S. , Dhanalakshmi C. Sowmya , Vairavel Dinesh Kumar , Surakasi Raviteja , Kaliappan S. , Patil Pravin P. , Socrates S. , Lalvani J. Isaac JoshuaRamesh
Published: April 2022

Pyrolysis is the most important thermochemical process that can be used for the production of biofuel, from wood and wood-based lignocellulosic materials. In this study, bio-oil is produced from the bio-weed named Ficus religiosa by the thermal pyrolysis process by utilizing laboratory-scale fluidized bed reactor. This study deals with the production of maximum bio-oil by optimizing process parameters such as process temperature, particle size, and sweep gas flow rate. Further different analytical techniques were used to describe the properties of bio-oil for different applications. Wood and wood barks of Ficus religiosa were chosen as the raw material due to their higher volatile content (72.4%). The maximum yield of 47.5 wt% bio-oil was collected at the optimized operating conditions of 450°C temperature, 1.0 mm particle size, and 2.0 m3/h sweep gas flow rate. Compared with other operating parameters, temperature is observed as the most significant one to determine the product yield. Through chromatographic analysis, it was identified that the bio-oil is found with the variety of chemical compounds including alcohols, alkenes, phenols, saturated fatty acids, and esters.
Fuzzy Analysis for Thin-Film Flow of a Third-Grade Fluid Down an Inclined Plane
Authors: Siddique Imran , Jamil Raja Noshad , Nadeem Muhammad , Abd El-Wahed Khalifa Hamiden , Alotaibi Fakhirah , Khan Ilyas , Andualem Mulugeta
Published: April 2022

We examined the thin-film flow problem of a third-grade fluid on an inclined plane under a fuzzy environment. The highly nonlinear flow governing differential equations (DEs) with the boundary conditions are fuzzified using the triangular fuzzy numbers (TFNs) developed by

α

-cut

α
∈

0,1

.

The fuzzy perturbation (FPM) method is adopted to calculate the fuzzified form of the governing equations as well as the fuzzified boundary conditions. For the validation, the present work is in good agreement as compared to existing work in the literature under the crisp form. For various values of the fluid parameter

λ
,

inclined parameter

γ

and fuzzy parameter

α

-cut is presented in graphical form. The

α

-cut controls TFNs, and the variability of uncertainty is investigated using a triangular membership function (MF). Using TFNs, the middle (crisp), left, and right values of the fuzzy velocity profile are used for fuzzy linear regression analysis. The outcome of this study and the fuzzy velocity profile have the maximum rate of flow as compared to the crisp velocity profile (mid values).
The Current Status of SSRP1 in Cancer: Tribulation and Road Ahead
Authors: Jia Shengnan , Guo Baofeng , Wang Lihui , Peng Liping , Zhang Ling
Published: April 2022

Background and Objectives. Owing to the complexity and heterogeneity of tumors, cancer’s early diagnoses and treatment have become a provocation. Structure-specific recognition protein-1 (SSRP1) is a histone (H3-H4 or H2A-H2B) chaperone in chromatin-related processes such as transcription, cell cycle control, and DNA replication, reported in various tumor tissues. It may also be used as a biomarker. This study aimed to highlight the role of SSRP1 in cancer with a focus on the current progress and future perspective. Methods. We search PubMed and Web of Sciences with keywords “SSRP1” and “Cancer.” Only English literature was included, and conference papers and abstract were all excluded. Results. Transcription factors are classified into three groups based on their DNA binding motifs: simple helix-loop-helix (bHLH), classical zinc fingers (ZF-TFs), and homeodomains. The tumor-suppressive miR-497 (microRNA-497) acted as an undesirable regulator of SSRP1 upregulation, which led to tumor growth. The siRNA (small interfering RNA) knockdown of SSRP1 hindered cell proliferation along with incursion and glioma cell migration. Through the AKT (also known as protein kinase B) signaling pathway, SSRP1 silencing affected cancer apoptosis and cell proliferation. Conclusion. The MAPK (mitogen-activated protein kinase) signaling pathway’s phosphorylation was suppressed when SSRP1 was depleted. The effect of curaxins on p53 and NF-B (nuclear factor-κB), and their toxicity to cancer cells, is attributable to the FACT (facilitates chromatin transcription) complex’s chromatin trapping.
[Retracted] Effects of Treadmill Exercise on Mitochondrial DNA Damage and Cardiomyocyte Telomerase Activity in Aging Model Rats Based on Classical Apoptosis Signaling Pathway
Authors: Liang Chao , Zhou Xiaoli , Li Meiling , Song Zhengpeng , Lan Jinyan
Published: April 2022

In order to explore the effect of treadmill exercise on mitochondrial DNA damage and myocardial telomerase activity in aging model rats based on the classical apoptosis signaling pathway, a total of 36 clean‐grade male SD rats are selected. After modeling, the rats are randomly divided into groups, namely, control and 3 times/w and 6 times/w exercise rats, with 12 rats in each group. After the rats of each group are modeled, the myocardial tissue and cells are collected, the apoptosis of myocardial cells is detected by TUNEL method, and the protein expressions of Bax and Bcl‐2 in myocardial tissue are detected by western blotting. The mtDNA content of the control rats is the highest, which is significantly higher than that of the exercise group (P < 0.05); the expression of mtDNA content in the heart of the rats exercising 3 times/w is significantly higher than that of the rats exercising 6 times/w (P < 0.05); cardiomyocyte apoptosis AI value, Bcl‐2, and Bax expressions of the control rats is the highest and significantly higher than those in the exercise group (P < 0.05); Bcl‐2/Bax in the control rats is the lowest and is significantly lower than that in the exercise group (P < 0.05). The AI value, Bcl‐2, and Bax expression of myocardial cell apoptosis in 3 times/w exercise rats are significantly higher than those in 6 times/w exercise rats (P < 0.05); Bcl‐2/Bax of 3 times/w exercise rats is significantly lower than that in 6 times/w exercise rats (P < 0.05); by observing the rats that completed treadmill exercise, Akt2 protein of 3 times/w exercise rats and 6 times/w exercise rats is observed and analyzed. Compared with the control rats, the expressions of the two proteins are increased in 3 times/w exercise rats and 6 times/w exercise rats, and the upregulation in 6 times/w exercise rats is significantly increased and higher than that in 3 times/w exercise rats (P < 0.05). For aging rats, treadmill exercise can reduce the body Bcl‐2 and Bax values, improve the mitochondrial DNA damage and myocardial cell telomerase activity in aging model rats, and slow down the aging process.
5G-Based Information Platform Design of Tourist Attractions in the Context of Mobile Big Data
Authors: Fang Shuo
Published: April 2022

This article aims to study the design of a tourist attraction information platform architecture based on 5G transmission technology in the context of mobile big data. It introduces the NOMA technology and the B/S mode. When introducing the nonorthogonal multiple access (NOMA) technology, it discusses the introduction and technical advantages of NOMA and puts forward the K-means algorithm, focusing on the selection of K value and distance measurement. How to measure the principle of K value NOMA technology is explained and analyzed. It can be seen that NOMA technology can effectively improve the capacity and spectrum efficiency of 5G communication system, and B/S function can reduce the cost of system maintenance and upgrade and the cost of users. In the experimental part of the article, starting from the overall design of the platform architecture, the overall design of the database, and the software and hardware platform, a tourist attraction information platform architecture based on 5G transmission technology is designed. The experimental results of this article show that people of different occupations are significantly more satisfied with the tourist attraction information platform proposed in this article than other platforms and the satisfaction is as high as 76.8%.
Research on Data Mining of Sports Wearable Intelligent Devices Based on Big Data Analysis
Authors: Zong Xing , Zhang Chenfei , Wu Dengpan
Published: April 2022

Traditional motion data mining models have some problems, such as poor dynamic data capture effect, low information classification effect rate, poor quantitative representation effect, and so on. Based on this, this paper studies the mining method of dynamic motion data based on neural network, constructs a data mining model based on discrete dynamic modeling technology, and realizes the collection of data information from the aspects of motion characteristics and types combined with multilayer sensors. Neural network algorithm is used for comprehensive analysis to realize multivariate analysis and objective evaluation of all data of dynamic motion process and accurate analysis and evaluation according to different data characteristics of different types of motion data. The results show that the data mining model based on discrete dynamic modeling technology and wearable sensor technology has the advantages of high feasibility, high intelligence, and wide application range.
IoT-Based Water Quality Assessment System for Industrial Waste WaterHealthcare Perspective
Authors: Dhruba Abdur Rab , Alam Kazi Nabiul , Khan Md. Shakib , Saha Sananda , Khan Mohammad Monirujjaman , Baz Mohammed , Masud Mehedi , AlZain Mohammed A.
Published: April 2022

The environment, especially water, gets polluted due to industrialization and urbanization. Pollution due to industrialization and urbanization has harmful effects on both the environment and the lives on Earth. This polluted water can cause food poisoning, diarrhea, short-term gastrointestinal problems, respiratory diseases, skin problems, and other serious health complications. In a developing country like Bangladesh, where ready-made garments sector is one of the major sources of the total Gross Domestic Product (GDP), most of the wastes released from the garment factories are dumped into the nearest rivers or canals. Hence, the quality of the water of these bodies become very incompatible for the living beings, and so, it has become one of the major threats to the environment and human health. In addition, the amount of fish in the rivers and canals in Bangladesh is decreasing day by day as a result of water pollution. Therefore, to save fish and other water animals and the environment, we need to monitor the quality of the water and find out the reasons for the pollution. Real-time monitoring of the quality of water is vital for controlling water pollution. Most of the approaches for controlling water pollution are mainly biological and lab-based, which takes a lot of time and resources. To address this issue, we developed an Internet of Things (IoT)-based real-time water quality monitoring system, integrated with a mobile application. The proposed system in this research measures some of the most important indexes of water, including the potential of hydrogen (pH), total dissolved solids (TDS), and turbidity, and temperature of water. The proposed system results will be very helpful in saving the environment, and thus, improving the health of living creatures on Earth.
Determination of Constitutive Parameters of Crystalline Limestone Based on Improved RHT Model
Authors: Tian Hao-Fan , Bao Tai , Li Zhuo , Peng Hao , You Shuai , Xiao Shi-li
Published: April 2022

This study improves the RHT constitutive model based on some shortcomings, and the main improvements work are as follows: (1) hyperbolic function is used to make up for the deficiency of tensile strain rate enhancement factor of RHT constitutive model at high strain rate; (2) considering the constant change of hydrostatic pressure, the initial damage value of rock is introduced into the constitutive model, and the improved damage accumulation expression is derived based on this value. (3) In the equation of residual failure surface, the influence of the Lode angle factor is considered, the RHT constitutive parameters of crystalline limestone are determined by the SHPB experiment, and the difference in rock failure forms before and after the correction of constitutive parameters is simulated by ANSYS/LS-DYNA software. The results show that the improved constitutive parameters can effectively represent the yield strength surface and residual strength surface of the rock, which verifies the rationality of the improved RHT constitutive model, and also shows that it is an effective and simple method to obtain RHT constitutive parameters by SHPB experiment.
Platform Firm’s IT Capabilities, External Informal Knowledge Governance, and Green Knowledge Integration in Low-Carbon Economy
Authors: Fu Guanghua , Li Bencheng
Published: April 2022

Platform ecosystem provides internal firms with an abundant source of green technology knowledge for sustainable development. In a low-carbon economy, green technology could be accumulated via platform, thus utilized to achieve energy conservation and emission reduction. From firm’s social capital perspective, this study explores the effects of platform firm’s IT capabilities and external informal knowledge governance on green knowledge integration. A theoretical model is constructed about their direct and interactive effects. Based on 372 samples of platform firms, the empirical test results show that IT capabilities have a significant positive impact on collaborative and sysematic green knowledge integration; external informal knowledge governance has a significant positive impact on socialized and collaborative green knowledge integration; and their interactive effects pose significant positive impact on socialized, collaborative, and systematic green knowledge integration.
Cancer Burden in China during 1990–2019: Analysis of the Global Burden of Disease
Authors: Zhang Shu-Zhen , Zhang Li , Xie Long
Published: April 2022

This study reports the risk factors, trends, and burden of cancer in China from 1990 to 2019 from the Global Burden of Diseases. The incidence, mortality, and DALY of all cancers in China for the past 30 years were analyzed. In 2019, the age‐standardized rates (ASRs) of cancer incidence, mortality, and DALY in China were 232.42/100 000, 136.72/100 000, and 3288.22/100 000, respectively. The five cancers with the highest age‐standardized incidence rates were lung, stomach, colorectal, breast, and prostate cancers. From 1990 to 2019, the number of new cancer cases, deaths, and DALY increased by 168.78%, 86.89%, and 51.20%, respectively. The ASR increased by 22.21% for incidence and decreased by 19.01% and 27.19% for mortality and DALY, respectively, and their corresponding average annual percent change values were 0.71, ‐0.80, and ‐1.26, respectively. The main risk factors for cancer in China were smoking, air pollution, dietary factors, and alcohol use. From 1990 to 2019, the cancer incidence rate was on the rise, and cancer mortality and DALY rates were declining; however, these characteristics vary by cancer site. Therefore, current prevention strategies should be reoriented, and specific strategies for cancers in different sites should be established to prevent the increase in cancer cases.
Effects of Lipolysis‐Stimulated Lipoprotein Receptor on Tight Junctions of Pancreatic Ductal Epithelial Cells in Hypertriglyceridemic Acute Pancreatitis
Authors: Wang Jie , Qin Mengbin , Wu Qing , Yang Huiying , Wei Biwei , Xie Jinlian , Qin Yingying , Liang Zhihai , Huang Jiean
Published: April 2022

Objective. We investigated the effects of lipolysis‐stimulated lipoprotein receptor (LSR) on the tight junctions (TJs) of pancreatic ductal epithelial cells (PDECs) in hypertriglyceridemic acute pancreatitis (HTGAP). Methods. Sprague‐Dawley rats were fed standard rat chow or a high‐fat diet and injected with sodium taurocholate to obtain normal and HTGAP rats, respectively. Serum triglyceride (TG) levels, pathological changes, TJ proteins in the pancreas, and TJ ultrastructure of PDECs were assessed. LSR overexpression (OE) and knockdown (KD) HPDE6‐C7 models were designed and cultured in a high‐fat environment. Protein levels were quantified by Western blotting. Cell monolayer permeability was detected using FITC‐Dextran. Results. Serum TG concentration and pancreatic scores were higher in the HTGAP group than in the normal group. Among the TJ proteins, LSR protein expression was significantly lower in the HTGAP group than in the acute pancreatitis (AP) group. Tricellulin (TRIC) expression in the pancreatic ductal epithelia was higher in the HTGAP group than in the AP group. The HTGAP group had lower TJ protein levels, wider intercellular space, and widespread cellular necrosis with disappearance of cell junction structures. In the cell study, TJ proteins were downregulated and the cellular barrier was impaired by palmitic acid (PA), which was reversed by LSR‐OE, whereas LSR‐KD downregulated the TJ proteins and aggravated PA‐induced cellular barrier impairment. Conclusions. Hypertriglyceridemia downregulates the TJ proteins in PDECs, which may impair the pancreatic ductal mucosal barrier function. LSR regulation can change the effects of HTG on cellular barrier function by upregulating the TJ proteins.
Study on the Influence of Wuthering Heights Characters Based on Web Analysis and Text Mining
Authors: Wang Rui , Deng Lin
Published: April 2022

The rapid development of network technology and the popularity of the Internet have made people rely more and more on the exchange and sharing of network information, and the demand for obtaining information about people from the Internet has gradually increased, but the massive amount of network data has made the information about people fragmented and disorganized, and the existing work on portraits has mainly focused on the extraction of people’s attributes. In this paper, we examine the artistic construction and characterization of Wuthering Heights on the basis of a tasting of the book, with the aim of presenting the “alienated personalities” hidden in the depths of the characters’ consciousness and showing the author’s unique creative art through an analysis of thematic ideas, the use of temporal elements, and the tracing of the creation of the characters’ original forms. In the aspect of character social relationship extraction, first, the method of expanding the seed dictionary by means of synonym word forest is used to build a character relationship lexicon, which avoids the inefficiency caused by manual lexicon collection; second, a character relationship extraction algorithm based on the combination of rule matching and syntactic tree is proposed, which effectively overcomes the disadvantage of low recall rate caused by rule matching, and the average F-value of this algorithm reaches 82.61% in the experiment The algorithm achieves an average F-value of 82.61% in the experiment, which is a significant advantage over other methods.
Migrasomes: From Biogenesis, Release, Uptake, Rupture to Homeostasis and Diseases
Authors: Zhang Yaxing , Guo Wenhai , Bi Mingmin , Liu Wei , Zhou Lequan , Liu Haimei , Yan Fuman , Guan Li , Zhang Jiongshan , Xu Jinwen
Published: April 2022

Migrasomes are migration-dependent membrane-bound vesicular structures that contain cellular contents and small vesicles. Migrasomes grow on the tips or intersections of the retraction fibers after cells migrate away. The process of releasing migrasomes into the extracellular space is named as “migracytosis”. After releasing, they can be taken up by the surrounding cells, or rupture and further release their contents into the extracellular environment. Physiologically, migrasomes provide regional cues for organ morphogenesis during zebrafish gastrulation and discard the damaged mitochondria in response to mild mitochondrial stresses. Pathologically, migrasomes are released from podocyte during early podocyte stress and/or damage, from platelets after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), from microglia/macrophages of the ischemic brain, and from tumor necrosis factor α (TNFα)-activated endothelial cells (ECs); thus, this newly discovered extracellular vesicle is involved in all these pathological processes. Moreover, migrasomes can modulate the proliferation of cancer cell via lateral transferring mRNA and protein. In this review, we will summarize the biogenesis, release, uptake, and rupture of migrasomes and discuss its biological roles in development, redox signalling, innate immunity and COVID-19, cardio-cerebrovascular diseases, renal diseases, and cancer biology, all of these highlight the importance of migrasomes in modulating body homeostasis and diseases.
Efficacy of Drug-Eluting Bead Transarterial Chemoembolization in the Treatment of Colorectal Cancer Liver Metastasis
Authors: Chen Sipan , Yang Yaobo , Jiao Yang , Hou Lei , Chang Hulin , Liu Sida , Yan Zhaoyong
Published: April 2022

We aimed to investigate the efficacy and safety of drug-eluting bead transarterial chemoembolization (DEB-TACE) in the treatment of colorectal cancer liver metastasis. A total of 120 patients with colorectal cancer liver metastasis were divided into the TACE group (receiving TACE treatment, n = 60) and the DEB-TACE group (receiving DEB-TACE treatment, n = 60). At 1 month after treatment, the objective response rate (ORR) in the TACE group and DEB-TACE group were 65.0% (39/60) and 78.3% (47/60), respectively, and the disease control rate (DCR) was 78.3% (47/60) and 85.0% (51/60), respectively. Three months later, the ORRs in TACE and DEB-TACE groups were 63.3% (38/60) and 75.0% (45/60), and the DCRs were 76.7% (46/60) and 81.7% (49/60). We showed that the 1-year overall survival (OS) in TACE and DEB-TACE groups were 100% (60/60) and 88.3% (53/60), respectively, and the 2-year OS were 78.3% (47/60) and 61.7% (37/60). Further analysis indicated that the OS in the DEB-TACE group was significantly longer than that in the TACE group (P = 0.045). DEB-TACE is effective, safe, and feasible in the treatment of colorectal cancer liver metastasis, which can effectively improve the survival of patients.
Environmental Healthcare Assessment via Daily-Scale Drought Monitoring
Authors: Yuan Huizhou , Huang Qiang , Lu Qiongling , Yang Haiyan , Lu Wei Jie
Published: April 2022

Precipitation is the most important factor in determining the drought condition. In addition, the drought condition is also affected by the hydrological process such as evaporation, leakage, runoff, and groundwater. Based on a simple physical model of water income and recession, the effective precipitation index (WAP) can reflect the drought condition in a region on a short time scale. Using a water decline equation to describe the process of preliminary soil moisture, evaporation, runoff, and groundwater, the WAP can be used for the quantitative study of drought. This paper improves the calculation program of WAP with reference to the calculation model of the standardized index. The improved WAP (called SWAP) effectively solves the problem of seasonality in drought. The results showed that SWAP has the ability to capture the drought processes of occurrence, development, peak, and regression in a short time scale, and the SWAP can be used as an effective tool for drought identification, assessment, and prevention.
Evaluation of Relationship between Serum Liver Enzymes and Hypertension: A Cross-Sectional Study Based on Data from Rafsanjan Cohort Study
Authors: Khalili Parvin , Abdollahpoor Saeedeh , Ayoobi Fatemeh , Vakilian Alireza , Hakimi Hamid , Rajabi Zohreh , Jamali Zahra
Published: April 2022

Background. Hypertension as a major risk factor for cardiovascular diseases is among the leading causes of death worldwide. The relationship between elevated serum levels of liver enzymes and hypertension has been reported in limited studies, and to the best of our knowledge, there are no previous reports in the literature on this issue in the southeast of Iran. Our investigation aimed at evaluating the relation between ALT, AST, GGT, and ALP with hypertension in the Rafsanjan Cohort Study, a city in Kerman Province, Iran. Methods. In this cross-sectional study, we used data obtained from the Rafsanjan Cohort Study (RCS), as a part of the prospective epidemiological research studies in Iran (PERSIAN). The association of the liver enzymes levels with hypertension was investigated using the multivariable logistic regression models. Results. Among 9930 participants, the mean age (±SD) was 49.94 (±9.56) years, and 46.56% were men. The odds of abnormal blood pressure significantly increased along with the higher levels of ALT, GGT, and ALP which remained significant only for ALP after adjustment for all confounding variables in both males and females (OR in males: 1.36, 95% CI = 1.09–1.69, OR in females: 1.25, 95% CI = 1.01–1.54). In subjects with normal levels of ALT, AST, GGT, and ALP, dose-response increases were observed for abnormal blood pressure in both genders. Finally, we found that, among liver enzymes, only elevated ALP was significantly correlated with the odds of stage 1 hypertension and stage 2 hypertension for both genders. Conclusions. In subjects with normal levels of ALT, AST, GGT, and ALP, dose-response increases were observed for abnormal blood pressure in both genders. Increased serum ALP activity was positively associated with increased odds of hypertension in males and females. Therefore, increased ALP could be an early indicator of hypertension.
OTO-Net: An Automated MRA Image Segmentation Network for Intracranial Aneurysms
Authors: Ye Jianming , Xu Xiaomei , Li Liuyi , Zhao Jialu , Lai Weiling , Zhou Wenting , Zheng Chong , Wang Xiangcai , Lai Xiaobo
Published: April 2022

Intracranial aneurysms are local dilations of the cerebral blood vessels; people with intracranial aneurysms have a high risk to cause bleeding in the brain, which is related to high mortality and morbidity rates. Accurate detection and segmentation of intracranial aneurysms from Magnetic Resonance Angiography (MRA) images are essential in the clinical routine. Manual annotations used to assess the intracranial aneurysms on MRA images are substantial interobserver variability for both aneurysm detection and assessment of aneurysm size and growth. Many prior automated segmentation works have focused their efforts on tackling the problem, but there is still room for performance improvement due to the significant variability of lesions in the location, size, structure, and morphological appearance. To address these challenges, we propose a novel One-Two-One Fully Convolutional Networks (OTO-Net) for intracranial aneurysms automated segmentation in MRA images. The OTO-Net uses full convolution to achieve intracranial aneurysms automated segmentation through the combination of downsampling, upsampling, and skip connection. In addition, loss ensemble is used as the objective function to steadily improve the backpropagation efficiency of the network structure during the training process. We evaluated the proposed OTO-Net on one public benchmark dataset and one private dataset. Our proposed model can achieve the automated segmentation accuracy with 98.37% and 97.86%, average surface distances with 1.081 and 0.753, dice similarity coefficients with 0.9721 and 0.9813, and Hausdorff distance with 0.578 and 0.642 on these two datasets, respectively.
Application of Optimized Convolution Neural Network Model in Mural Segmentation
Authors: Chen Zhiqiang , Rajamanickam Leelavathi , Tian Xiaodong , Cao Jianfang
Published: April 2022

To address the problems of blurred target boundaries and inefficient image segmentation in ancient mural image segmentation, a multi-classification image segmentation model MC-DM (Multi-class DeeplabV3+ MobileNetV2) that fuses lightweight convolutional neural networks is proposed. The model combines the Deeplabv3+ structure and MobileNetV2 network and adopts the unique spatial pyramid structure of DeeplabV3+ to process convolutional features for multi-scale fusion, which reduces the loss of detail in the mural segmentation images. Firstly, the features calculated at any resolution in MobileNetV2 network are extracted by hole convolution, the input step is expressed as the ratio between the input image resolution and the final resolution, and the density of encoder features is controlled according to the budget of computing resources. Then, the spatial pyramid pool structure is used to fuse the previously calculated features at multiple scales to enrich the semantic information of the feature image. Finally, the same convolution network is used to reduce the number of channels and filter the density feature map. The filtered features are fused with the features after multi-scale fusion again to obtain the final output. In total, 1000 scanned images of murals were adopted as datasets for testing under the JetBrains PyCharm Community Edition 2019 environment. The obtained experimental results indicate that MC-DM improves the training accuracy by 1 percentage point compared with the conventional SegNet-based image segmentation model, and by 2 percentage points compared with the PspNet network-based image segmentation model. The PSNR (peak signal-to-noise ratio) of the MC-DM model is improved by 3–8 dB on average compared with the experimental model. This confirms the effectiveness of the model in mural segmentation and provides a novel method for ancient mural image segmentation.
RIP3 Contributes to Cardiac Hypertrophy by Influencing MLKL-Mediated Calcium Influx
Authors: Xue Honghong , Shi Hongtao , Zhang Fan , Li Hao , Li Chao , Han Qinghua
Published: April 2022

Receptor-interacting protein 3(RIP3), a RIP family member, has been reported as a critical regulator of necroptosis and involves in the pathogenesis of various heart diseases. However, its role in the development of myocardial hypertrophy after pressure overload is unclear. We aimed to investigate the roles of RIP3 in pathological cardiac hypertrophy. A rat model of myocardial hypertrophy induced by the aortic banding method was used in this study. Neonatal rat cardiomyocytes (NRCMs) were stimulated with angiotensin II (Ang-II) or phenylephrine (PE) to induce neurohumoral stress. Our results showed that RIP3 level was significantly elevated in the hypertrophic myocardium tissues from patients, rats subjected to AB surgery, and NRCMs treated with Ang-II or PE. After downregulation of RIP3 expression in NRCMs, the phenotypes of myocardial hypertrophy were obviously alleviated. In mechanism, we demonstrated that RIP3 interacts with mixed lineage kinase domain-like protein (MLKL) and promotes its cell membrane localization to increase the influx of calcium within cells, thereby mediating the development of myocardial hypertrophy. More interestingly, we found the blockage of calcium influx by 2-aminoethoxydiphenyl borate, and lanthanum chloride efficiently reverses RIP3-induced cardiac remodeling in NRCMs. Taken together, our findings indicate a key role of the RIP3-MLKL signaling pathway in myocardial hypertrophy, which may be a novel promising treatment strategy for myocardial hypertrophy.
Structural Effects of pH Variation and Calcium Amount on the Microencapsulation of Glutathione in Alginate Polymers
Authors: Bustos Daniel , Hernández-Rodríguez Erix W. , Castro Ricardo I. , Morales-Quintana Luis
Published: April 2022

Reduced glutathione (GSH) has a high antioxidant capacity and is present in nearly every cell in the body, playing important roles in nutrient metabolism, antioxidant defense, and regulation of cellular events. Conversely, alginate is a macromolecule that has been widely used in the food, pharmaceutical, biomedical, and textile industries due to its biocompatibility, biodegradability, nontoxicity, and nonimmunogenicity as well as for its capabilities of retaining water and stabilizing emulsions. The primary goal of this study was to characterize and optimize the formation of a molecular complex of calcium alginate with GSH using a computational approach. As methods, we evaluated the influence of varying the amount of calcium cations at two different pHs on the structural stability of Ca2+‐alginate complexes and thus on GSH liberation from these types of nanostructures. The results showed that complex stabilization depends on pH, with the system having a lower Ca2+ amount that produces the major GSH release. The systems at pH 2.5 retain more molecules within the calcium‐alginate complex, which release GSH more slowly when embedded in more acidic media. In conclusions, this study demonstrates the dependence of the amount of calcium and the stabilizing effect of pH on the formation and subsequent maintenance of an alginate nanostructure. The results presented in this study can help to develop better methodological frameworks in industries where the release or capture of compounds, such as GSH in this case, depends on the conditions of the alginate nanoparticle.
Construction of COVID-19 Epidemic Prevention and Control and Public Health Emergency Response System Based on Discrete Stochastic Mathematical Model
Authors: Yang Ying , Dong Liming , Rong Hua , HongyuYang  , Liu Bingxin
Published: April 2022

This research was aimed at exploring the construction and evaluation method of the comprehensive emergency response system for public health emergencies under the COVID-19 (coronavirus disease 2019) epidemic situation based on discrete stochastic mathematical model. The response of the Centers for Disease Control and Prevention (CDCP) of Taiyuan city in the COVID-19 epidemic situation was taken as an example. A new discrete stochastic COVID-19 epidemic spread mathematical model which integrated public health intervention and input cases was proposed. The model was parameterized by multisource data, and the impact of different flow patterns on the risk of secondary outbreak was analyzed. The advantages and disadvantages of its emergency system construction were analyzed. Additionally, the improvement measures and suggestions for the existing problems were proposed. Results suggested that there was only one specialized disease prevention and control institution in Taiyuan, and there were only 11 centers for disease prevention and control, accounting for 6.2% (11/177) of the total in Shanxi Province. Through the analysis, it was found that the current public health emergency response system in Taiyuan city had imperfect management coordination mechanism, incomplete plan type, serious shortage of public health personnel, poor information communication efficiency, insufficient early warning efficiency of the epidemic detection system, and weak logistics material security links. Therefore, it was proposed to establish a sound coordination system of emergency health management and vigorously promote the construction of emergency health management institutions. Thus, a public health emergency management system integrating management coordination system, plan system, emergency team building system, material reserve management, and other functions was formed. The application of discrete stochastic mathematical model suggests that intermittent population flow and effective isolation of infected people in transient population can effectively reduce the risk of secondary outbreak. The system analysis here also provides theoretical basis for improving the construction of public health emergency response system in Taiyuan.
Strain Measuring of Composite Grid Using Digital Image Correlation
Authors: Lim Chhoung , Jeong Yeongseok , Limkantanyu Suchart , Kwon Minho
Published: April 2022

Digital Image Correlation (DIC) is a new advanced technique for measuring the deformation of a specimen using high-resolution images. It has been used by numerous researchers since it can measure the deformation of specimens without interference because it is contactless. Moreover, the DIC technique can be applied to any materials to which normal measuring equipment is difficult to attach such as Fiber-Reinforced Polymer (FRP) grid in this paper, undulated and small surfaces. The DIC technique is easy to set up and provides reliable results compared to conventional equipment like a strain gauge. Although it is good, its associated equipment is too expensive to be readily affordable. Hence, this paper uses an open-source DIC program called Ncorr that works in MATLAB to analyze deformations of six FRP grids from direct tensile tests by comparing their results to the results from a strain gauge. Young’s modulus—calculated from ASTM 3039, ACI 440-3R-04, and regression analysis—of each specimen will be used for comparison. The results show that the difference between Young’s modulus from DIC and strain gauge is <5% if the stress–strain graph of data from the strain gauge is perfectly linear without straying.
Design of a Treatment Method for Patients with Anxiety Disorders Based on Ball Games and Digital Technology Assistance
Authors: Chang Shuzhi
Published: April 2022

Patients with anxiety disorders often have a long and often recurring course of the disease, which negatively affects all aspects of the patient’s work life while also causing a significant economic burden. Psychotherapy and medication are common treatments for anxiety disorders, but they are ineffective, especially in cases of chronic anxiety, having a high relapse rate and often causing adverse side effects. Ball games are important sports that have been widely used in training and sports activities. Physical activity has been discovered to be good not only for physical health but also for the treatment of anxiety disorders, according to recent medical studies. Therefore, there is an urgent need to investigate the rehabilitation effects of ball games on anxiety disorder patients and to develop novel training methods. Meanwhile, in recent years, the use of computers for digital technology-assisted mental illness treatment has received widespread attention. In this paper, a new treatment strategy for anxiety patients is proposed by combining ball games with support vector machine algorithm as digital assisted technology. This research examines the shortcomings in the classic support vector machine technique first and then proposes an improved FSVM algorithm for data processing and analysis. The results of the experiments reveal that the proposed technique has a significant impact on the treatment of anxiety disorders and creates the foundation for the study of anxiety patients’ exercise therapy.
Detection of Multicamera Pedestrian Trajectory Outliers in Geographic Scene
Authors: Wang Wei , Xie Yujia , Wang Xiaozhi
Published: April 2022

The abnormal detection of moving objects in intelligent video surveillance system plays an important role in early warning for man-made disasters. However, the current abnormal detection methods cannot effectively perceive the cross-camera abnormal movements of video objects. The main reason is that the existing methods ignore the spatial relationship between the fields of view of different cameras and blind areas among the fields of view. This condition prevents them to effectively infer and analyze the cross-camera movements of video objects combined with geospatial information. This paper proposes the detection of multicamera pedestrian trajectory outliers in geographic scene to address this problem. This approach first spatializes the video object trajectory and then realizes trajectory vectorization by extracting trajectory points with equal time difference. The position trajectory outliers are detected by constructing isolation forest and scoring trajectory vectors, and the velocity trajectory outliers are identified through vectors’ neighborhood comparison. Related experiments show that our method can effectively improve the efficiency and accuracy of detecting trajectory outliers, which can enhance the early warning capability of video surveillance systems for man-made disasters.