bluuebunny/crossref_metadata_2025 huggingface dataset:
Interactions of periodic birth and shearing induce outbreak of Brucellosis in Inner Mongolia
Authors: Ma Xia , Li Mingtao , Zhang Juan , Luo Xiaofeng , Sun Gui-Quan
Published: March 2022

Brucellosis, a zoonotic disease, has brought about enormous human suffering and tremendous economic burden to animal husbandry in China. However, Inner Mongolia is the hardest hit area of brucellosis in China. A total of 132,037 human cases have been reported from 2010 to 2020. Endogenous mechanisms of brucellosis spreading across Inner Mongolia till remains to be revealed. We propose a periodic epidemic model to investigate the effect of periodic parameter changes on brucellosis epidemics. Then we evaluate the basic reproduction number [Formula: see text] and analyze the global dynamics of the model. Furthermore, key parameters related to periodic transmission are estimated based on the monthly data of human brucellosis cases and the trend of newly infected human brucellosis cases are predicted in Inner Mongolia. Our modeling results illustrate that periodical birth and sheep shearing play a significant role in inducing periodical outbreak of brucellosis in Inner Mongolia. Moreover, it is exhibited that the annual peak number and the final scale of human brucellosis cases will be reduced dramatically with the delayed peak time of sheep birth. While the annual peak time will be lagged and the annual peak number will be decreased as the peak time of sheep shearing is postponed. In addition, we discover that it is difficult to stem brucellosis even if all sheep are vaccinated besides ewes. Nevertheless, the detection rate exceed a certain value 0.032 or the decaying rate of Brucella surpass a critical value 0.585, the human brucellosis can be regulated in Inner Mongolia according to the sensitivity analysis of [Formula: see text]. The insights shed herein may contribute to the careful implementation of brucellosis control strategies in other regions.
Vandermonde determinant for a certain Sakaguchi type function in Limaçon domain
Authors: Vijayalakshmi S. P. , Bulut Serap , Sudharsan T. V.
Published: March 2022

In this paper, we define the [Formula: see text]th Vandermonde determinant and determine the coefficient bounds for the second- and third-order Vandermonde determinant for a Sakaguchi type function [Formula: see text] and [Formula: see text] which map open unit disc onto the region bounded by Limaçon [Formula: see text] Sharp upper bounds are obtained for second-order Vandermonde determinant.
Voltammetric Detection of Inositol Using a Platinum Based Electrode
Authors: Bandyopadhyay Dipan , Nag Shreya , Das Debangana , Acharya Srikanta , Tudu Bipan , Pramanik Panchanan , Bandyopadhyay Rajib , Roy Runu Banerjee
Published: March 2022

An electrochemical detection of inositol content using platinum (Pt)-based noble metal electrode is investigated. In this work, the electrochemical behavior of the platinum electrode has been studied and analyzed using a three-electrode system against a silver–silver chloride (Ag/AgCl) reference electrode and a steel counter electrode. Differential pulse voltammetry technique has been employed for this experimental study. A satisfactory linear range of operation was obtained from 50 to 400[Formula: see text][Formula: see text]M with [Formula: see text]M. Electrochemical responses for several inositol concentrations 50, 80, 100, 200, 300 and 400[Formula: see text][Formula: see text]M have also been analyzed using principal component analysis (PCA) with effective data clustering. A good class separability index (SI) was found to be 142.91. In addition, a prediction estimation of inositol contents using partial least square regression (PLSR) and principal component regression (PCR) algorithms were also evaluated and prediction accuracies of 93.69% and 93.71% were obtained, respectively. Moreover, the application of the Pt electrode over real orange juice sample extracts revealed satisfactory recovery rate of 96.18%. Thus, this technique of electrochemical system may be subjected for inositol detection in our daily-life food (especially juice, beverages) consumption.
Evaluating the Impact of WEA 2.0 Regulations on WEA Message Content Accessibility
Authors: LaForce Salimah , Bright Dara
Published: March 2022

Policy is ever-changing and evolving to address the needs of the population it serves. The conversation surrounding emergency preparedness often excludes vulnerable populations such as people with disabilities. Therefore, policies and regulations must address existing gaps with inclusive emergency communications. As the Federal Communications Commission (FCC) re-examines and modifies regulations for the Emergency Alert System (EAS) and the Wireless Emergency Alert (WEA), it is invaluable to evaluate whether these regulatory policies have accomplished their intended effect to become more accessible and inclusive. Thus, this paper explores the impact of WEA 2.0 regulations implemented in December of 2019 on the accessibility of WEA message content and provides a comparative analysis on the accessibility of these messages before the regulation and after.
Ultralow-Platinum Supported Polyaniline-MXene via Facile Electrochemical Strategy for Efficient Hydrogen Evolution
Authors: Jian Xuan , Li Tan , Guo Shanshan , Fu Feng , Tian Yue , Tian Bining , Wu Yucheng
Published: March 2022

The design of ultralow-platinum electrocatalyst with a superior performance is of great interest for hydrogen evolution reaction (HER). Herein, we developed a facile approach of electrochemical deposition that is applicable to construct ultralow-Pt supported polyaniline-Ti3C2T
x
MXene electrocatalyst (denoted as Pt/PANI-Ti3C2T
x
). It is found that the aniline monomers and Ti3C2T
x
nanoflakes were simultaneously electrodeposited on the surface of carbon paper and formed ordered nanostructures, which efficiently immobilizes more Pt species and promotes the H* conversion. The Pt loadings in the as-designed electrocatalyst is determined to be 2.2 μg cm‒2, which is around two-order of magnification lower than that in the state-of-the-art Pt/C catalyst. While it exhibits excellent HER performance with low applied overpotential of 52 mV at a current density of 10 mA cm‒2, a high turnover frequency of 14.13 H2 s‒1 and high mass activity of 14 A mgPt
‒1, as well as excellent long-term durability. Additionally, density functional theory calculations reveal more favorable H adsorption-desorption by the synergistic effect between Pt and PANI-Ti3C2T
x
facilitating hydrogen production.
Understanding Li Plating and Stripping Behavior in Zero-Excess Li Metal Batteries Using Operando Dilatometry
Authors: Lohrberg Oliver , Maletti Sebastian , Heubner Christian , Schneider Michael , Michaelis Alexander
Published: March 2022

Zero-excess Li metal batteries (ZELMB), in which the Li-metal anode is plated in situ on the anode current collector during initial charging, have received considerable attention in recent years. Such batteries hold enormous potential for increasing energy density and simplifying battery production, thus reducing costs, material, and energy requirements. However, transfer into application has so far been limited by challenges related to the non-uniform deposition behavior of lithium, which leads to inadequate performance and safety concerns. To meet these challenges, the electrochemical deposition behavior of lithium must be very well understood to derive and evaluate knowledge-based optimization approaches. For this purpose, advanced characterization methods are urgently needed. Herein the use of operando electrochemical dilatometry (OED) to study Li deposition and dissolution in ZELMB is demonstrated. We show how OED not only provides information on thickness changes during Li deposition and stripping, but also allows insights regarding morphology evolution and quantification of dead Li. The present work is intended to serve as an example to demonstrate the valuable insights that can be gained with OED and to encourage the scientific community to use it to support the development of advanced Li-, Na-, or K-metal batteries.
Lung resistance and elastance are different in ex vivo sheep lungs ventilated by positive and negative pressures
Authors: Dong Shou-Jin , Wang Lu , Chitano Pasquale , Coxson Harvey O. , Vasilescu Dragoş M. , Paré Peter D. , Seow Chun Y.
Published: March 2022

Lung resistance ( RL) and elastance ( EL) can be measured during positive or negative pressure ventilation. Whether the different modes of ventilation produce different RL and EL is still being debated. Although negative pressure ventilation (NPV) is more physiological, positive pressure ventilation (PPV) is more commonly used for treating respiratory failure. In the present study, we measured lung volume, airway diameter, and airway volume, as well as RL and EL with PPV and NPV in explanted sheep lungs. We found that lung volume under a static pressure, either positive or negative, was not different. However, RL and EL were significantly higher in NPV at high inflation pressures. Interestingly, diameters of smaller airways (diameters <3.5 mm) and total airway volume were significantly greater at high negative inflation pressures compared with those at high positive inflation pressures. This suggests that NPV is more effective in distending the peripheral airways, likely due to the fact that negative pressure is applied through the pleural membrane and reaches the central airways via the peripheral airways, whereas positive pressure is applied in the opposite direction. More distension of lung periphery could explain why RL is higher in NPV (vs. PPV), because the peripheral parenchyma is a major source of tissue resistance, which is a part of the RL that increases with pressure. This explanation is consistent with the finding that during high frequency ventilation (>1 Hz, where RL reflects airway resistance more than tissue resistance), the difference in RL between NPV and PPV disappeared.
PTPN18 Stimulates the Development of Ovarian Cancer by Activating the PI3K/AKT Signaling
Authors: Mao Nan , Li Hu , Yang Hui , Su Jianfen , Liang Zhimin , He Guansheng
Published: March 2022

Objective. To illustrate the functions of protein tyrosine phosphatase nonreceptor type 18 (PTPN18) in the progression of ovarian cancer and the potential molecular mechanism. Methods. Differential PTPN18 expression in ovarian cancer samples was determined. Following PTPN18 knockdown, changes in proliferation and migration in ovarian cancer cells were detected. Nude mice with ovarian cancer were used to uncover the effects of PTPN18 on ovarian cancer growth in vivo. Results. PTPN18 was significantly upregulated in ovarian cancer samples and linked to pathological staging and metastasis rate. PTPN18 displayed prognostic and diagnostic potentials in ovarian cancer. Knockdown of PTPN18 and treatment of the PI3K inhibitor could inhibit proliferative and migratory abilities in ovarian cancer cells. Moreover, PTPN18 was capable of inactivating PI3K/AKT signaling. In vivo knockdown of PTPN18 suppressed ovarian cancer growth in nude mice. Conclusions. PTPN18 is upregulated in ovarian cancer, which stimulates the malignant development by activating PI3K/AKT signaling. The PTPN18 level is also associated with pathological staging and metastasis in ovarian cancer patients, which may be utilized as a hallmark predicting the malignant level.
Prognostic Value of Creatine Phosphate and Inflammatory Markers for Mitral Valve Replacement: A Systematic Review and Meta-Analysis
Authors: Zhu Yanhui , Zou Chengwei , Zhang Jun , Chen Lei , Jia Yanting
Published: March 2022

Purpose. The prognosis of mitral valve replacement is an important clinical issue and may produce unexpected mortality rates if not properly addressed. The postoperative examination results have important prognostic implications. This study was designed to determine the prognostic value of phosphocreatine and inflammatory markers after mitral valve replacement. Method. Comparison and analysis of the data obtained using SPSS software. The computer retrieved PubMed, Science Citation Index (SCI), Embase, VIP, CNKI, CBM, and Wanfang database and manually retrieved randomized controlled trials (RCTs) published at home and abroad on the central muscle protection role of creatine phosphate in heart valve replacement, and the search period was established until February 2018. Two random literature reviewers independently screened the literature and extracted data, using Review Manager (RevMan) (Computer program), version 5.3 (The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, 2014). RevMan software version 5.0 assesses the risk of bias for inclusion in studies. The software performs a meta-analysis of the obtained data. Results. Ten RCTs with a total of 464 participants were enrolled. The meta-analysis results showed that (1) elevated creatine kinase levels often predict a better prognosis after mitral valve replacement (

RR
=
1.36

, 95% CI: 1.22 to 1.52,

P
<
0.00001

), (2) the creatine kinase isoenzyme level in the venous blood of the phosphocreatine group after 24 h of aortic blocking was significantly lower than that in the control group (

SMD
=
−
2.90

, 95% CI: -5.19 to -0.60,

P
=
0.01

), and (3) Troponin I levels were significantly lower in the intravenous creatine group than in the control group 24 h after opening of the aortic block (

SMD
=
−
1.49

, 95% CI: -2.02 to -0.97,

P
<
0.00001

). Conclusions. Creatine phosphate and inflammatory factor have good predictive value for the prognosis of mitral valve replacement.
Maritime Intelligent Monitoring System Based on Wireless Sensor Network and Construction of Shipping Legal System
Authors: Fang Hong
Published: March 2022

With the continuous advancement of the rule of law in society, the pace of global integration is accelerating, and all countries are actively expanding the development of sea areas. The previous maritime navigation management model cannot meet the conditions for active ocean development in the new era. The state must manage ships. My country has established a series of legal systems for ship management, including ship inspection systems, ship registration systems, and ship safety inspection systems. New management models, new service concepts, and prospects have gradually become the focus of attention of domestic and foreign waterway managers. With the continuous advancement of the rule of law in our country, the law enforcement requirements of maritime navigation management are also getting higher and higher. It is very important to create a good legal environment. This article is aimed at studying how to play the role of wireless local area network in maritime navigation management and how to establish a relatively complete legal system. This paper proposes a gray fuzzy comprehensive algorithm. If the fuzzy subset method is used to determine the membership matrix in the fuzzy comprehensive evaluation, then there will be a sudden drop in the degree of membership due to a slight change in the critical value of the index level. Based on this algorithm, a set of preliminary models of maritime channel management is established. The experimental data in this article mentions that in 2017-2020, the percentage of a certain maritime management’s attention to the legal system has clearly shown an upward trend. In 2020, the attention to the legal system is even as high as 69%. It can be seen that supervision improving the legal system is an effective measure. From the data, we can see that the rule of law score in 2018 was about 1.5 points lower than that in 2019, and the rule of law score in 2019 was 7.5 points. The results show that administration according to law puts forward higher requirements on the ability and service level of administrative agencies and their administrative law enforcement personnel, especially in the process of law enforcement, dealing with affairs related to administrative counterparts. Therefore, it is very necessary to establish a complete legal system.
A Forecast Model of City Natural Gas Daily Load Based on Data Mining
Authors: Chen Liang , Zhang Jijun
Published: March 2022

Data mining technology is more and more widely used in the daily load forecasting of natural gas systems. It is still difficult to carry out high-precision, timely intraday load forecasting and intraday load dynamic characteristics clustering for natural gas systems. Based on data mining technology, this paper proposes a stable intraday load forecasting method for the natural gas flow state-space model. The load sensitivity under the current operating conditions of the system is obtained by calculation; the sample space of the state space is established through data processing; the partitions under different clustering radii are calculated; and the best intraday load flow is obtained through the state space effectiveness evaluation method. The experimental results show that the model load forecasting accuracy and relative error reached 98.5% and 0.026, respectively, which solved the problem of processing the long-term accumulated historical data of gas intra-day load. At the same time, the amount of data calculation was reduced by 33.6%, which effectively promoted the quantification of intraday load influencing factors and qualitative analysis.
Effect of the Addition of Different Levels of Chard on the Dough Properties and Physicochemical and Sensory Characteristics of Pan Breads
Authors: Alsuhaibani Amnah Mohammed , Alshawi Amal Hassan
Published: March 2022

Background. Chard is a valuable vegetable and is considered a beneficial functional food. Fortification of bread with chard could increase the nutraceutical and functional food consumption. Objective. In this study, we performed a chemical analysis of chard and performed rheological analyses and sensory attribute evaluations of pan breads fortified with 5% and 10% chard powder. Design. The gross chemical composition of chard, some minerals, vitamin C, and total phenolic and flavonoid compounds were estimated. The rheological properties of doughs fortified with 5% and 10% chard powder and the chemical composition and sensory attributes of control, 5% chard and 10% chard pan bread samples were determined. Results. Chard contains carbohydrate, protein, and ash in addition to essential minerals and antioxidants such as vitamin C, phenols, and flavonoids. The chemical composition of 5% chard pan bread was significantly higher in ash and fiber, while the chemical composition of 10% chard pan bread was significantly higher in protein, ash, fiber, and moisture and significantly lower in fat, carbohydrate, and energy level than that of control pan breads. Compared with the control pan bread, the pan bread with increased chard powder content (10%) had significantly increased water absorption percentage, arrival time, dough development, elasticity, and proportional number ratio but significantly decreased stability time, softening degree, and extensibility. Pan bread fortified with 10% chard had the lowest specific volume among the tested breads. Sensory attribute evaluation further showed that increasing the amount of chard to 10% in the bread dough formulation produced lower overall acceptability scores. Conclusions. Pan bread containing 5% chard had better rheological scores and sensory attributes than the other formulations, in addition to good nutritional quality values.
Optimization of FDM Printing Process Parameters on Surface Finish, Thickness, and Outer Dimension with ABS Polymer Specimens Using Taguchi Orthogonal Array and Genetic Algorithms
Authors: Chohan Jasgurpreet Singh , Kumar Raman , Yadav Aniket , Chauhan Piyush , Singh Sandeep , Sharma Shubham , Li Changhe , Dwivedi Shashi Prakash , Rajkumar S.
Published: March 2022

Fused deposition modelling (FDM) is a technique of additive manufacturing used to fabricate a 3D (three-dimensional) model with layer-by-layer deposition of required materials with less material wastage. FDM is used to make any objects with a meager cost, but also there are some negative points related to less strength, less accuracy, and less surface finish. In this study, acrylonitrile butadiene styrene (ABS) is printed using an FDM printer to investigate the effects of various changing parameters like nozzle temperature (°C), infill pattern, and printing speed (mm/s) on surface roughness and thickness measurement. Experiments are designed using the Taguchi L9 orthogonal array method and ANOVA method. For obtaining an increase in surface roughness, the most influencing factor is printing speed with 83.41% contribution, and the effect of nozzle temperature is 9.04%. Lesser printing speed enhances the surface finish and, in the case of thickness and outer dimension of all the printed samples, results are almost constant. Regression analysis is performed to formulate the single-objective equations, and a genetic algorithm (GA) is applied to optimize the values of process parameters.
Low-Rank Matrix Denoising Algorithm-Based MRI Image Diagnosis of Uterine Malignant Tumor and Postoperative Care
Authors: Cao Liqiong , Zhang Huiting , Liu Yanling
Published: March 2022

This paper aimed to discuss regarding diagnosis and postoperative care of uterine malignant tumor, the effect of MRI image based on low-rank matrix denoising algorithm in diagnosis, and postoperative care of uterine malignant tumor. 100 patients with uterine malignant tumor are selected for MRI examination and the MRI examination based on low-rank matrix denoising algorithm. The accuracy, sensitivity, and specificity of the two kinds of MRI are evaluated and compared by three or more experienced doctors through a double-blind method. At the same time, under the guidance of MRI image after denoising, relevant postoperative care is carried out. The results are compared with the previous results in our hospital. The results showed that the sensitivity, specificity, and accuracy of denoised MRI images in the diagnosis of uterine malignant tumors are higher than those of ordinary MRI. After denoising, the postoperative nursing guided by the MRI image effectively reduces the occurrence of postoperative complications. In postoperative nursing, the overall satisfaction of patients with nursing increases by 10.9%. Conclusion. The MRI image based on the low-rank matrix denoising algorithm has an obvious effect on diagnosis and postoperative care of uterine malignant tumor.
The Optimization Function of Computer Image Technology in Processing Oil Painting Creation
Authors: Zhu Hong
Published: March 2022

In terms of processing methods, machine learning mainly takes the network as the core and uses the network as a medium to provide services such as computing and delivery. The “cloud” is mainly composed of computers and servers, and the Internet is used to provide network services. With the continuous progress and development of computer technology, digital image processing technology based on machine learning is widely used in production and life. Machine learning uses its own storage and computing capabilities to make the development space of image processing technology broader and effectively realize the rational allocation of resources. This article mainly analyzes the basic knowledge of machine learning, the construction of image processing cloud platforms, and the image fusion system. Then, we aim to optimize the oil painting creation. Through a simple explanation of the basic connotation of images, it is clear that digital image technology and oil painting creation are closely related and complementary. The impact of education and focusing on the application of computer graphics technology to some of the techniques often used in oil painting creation makes the created works more beautiful and artistic and puts forward the application of image processing technology and computer-aided technology in oil painting creation.
Software Requirements Engineer’s Ability Assessment Method Based on Empirical Software Engineering
Authors: Tian Jingbai , Yin Jianghao , Xiao Liang
Published: March 2022

With the expansion of the scale and complexity of modern software systems, the failure rate of software projects remains high. One of the main reasons for the failure of software projects is the defects in processing software requirements. This paper proposes a software requirements engineer’s ability assessment method based on empirical software engineering to measure the matching degree between the software requirements engineer’s ability and industry expectations. First, collect the recruitment information of software requirements engineers from mainstream recruitment websites. Through natural language processing, the words related to the abilities of the software requirements engineer are counted. These words are summarized in the requirements acquisition, requirements analysis, and other SRE activities, then the industry expectations for various abilities are obtained. Later on, the authors collect the teaching settings of representative SRE courses, reflecting the software requirements engineer’s ability to learn the course. After that, this article defines the ratio of the industry expectation weight to the weight of each SRE activity in teaching as the software requirements engineer’s ability coefficient, which can intuitively reflect the matching degree between the software requirements engineer’s ability and industry expectations. Finally, take the national first-class undergraduate course “SRE” of Jinling Institute of Technology as an example to verify the method’s practicality to a certain extent.
The Cooperation among Participants of Chinese Agricultural Machinery Insurance Based on Game Analysis
Authors: Han Ke , Wang Yawei
Published: March 2022

As the insurance for agricultural machinery features the attributes of quasi-public goods, its participants not only include farmers and insurance companies but also the government. The role played by the government will impose a direct impact on the development of the insurance for agricultural machinery. This paper sheds light on the behavior of the participants in agricultural machinery insurance from the aspects of economics and management. The game analysis is carried out on the participants to elaborate on the collaborative conditions for the long-term and stable development of agricultural machinery insurance. On this basis, the study provides policy recommendations on the role to be played by the government in agricultural machinery insurance.
Ruscogenins Improve CD-Like Enteritis by Inhibiting Apoptosis of Intestinal Epithelial Cells and Activating Nrf2/NQO1 Pathway
Authors: Wen Hexin , Zhang Xiaofeng , Li Qingqing , Huang Ju , Liu Guangyong , Zhao Jingyue , Liu Yiran , Shen Li , Li Yuyang , Yang Kun , Zuo Lugen , Li Jing , Nian Jing , Xiang Ping , Zhao Hao , Yu Liang , Liu Mulin , Geng Zhijun , Song Xue
Published: March 2022

Interaction of intestinal barrier dysfunction and intestinal inflammation promotes the progression of Crohn’s disease (CD). A more recent study has suggested that ruscogenins (RUS) can exert anti-inflammatory effects through activation of the Nrf2/NQO1 pathway. The current study is aimed at determining the functionalization of RUS on CD-like colitis. Wild-type (WT) mice induced with trinitrobenzene sulfonic acid (TNBS) exhibit a significant inflammation in their colon and are hence widely used for CD models. In the current study, the mice were treated with the Nrf-2 antagonist (ML385) or ruscogenin (RUS) whereas normal WT mice were kept as the negative control. Comparative analysis was then performed on the inflammation and barrier function of the colons. In vitro analysis of mouse colonic organoid systems revealed the influence of RUS on LPS-induced apoptosis, cytokine, and chemokine expressions in the intestinal epithelium. It was found that RUS ameliorates murine colitis through activation of the Nrf2/NQO1 pathway which was presented as a decrease in inflammation score and downregulated levels of cytokine and chemokine synthesis, as well as increased intestinal permeability. Further, it was noted that RUS alleviated LPS-induced apoptosis in the intestinal epithelium cells through upregulation of the Nrf2/NQO1 signaling pathway in the mouse colonic organoids. In addition, ruscogenin (RUS) attenuated the levels of Bax and C-caspase-3 through activation of the Nrf2/HO1 signaling pathway both in vivo and in vitro. Therefore, it was evident that RUS can be applied as a potential alternative therapeutic agent in CD based on its protective effects on the barrier function and anti-inflammatory activity.
Clinical Outcome and Fracture Risk Prediction of Benign Bone Tumors on the Acetabular Dome: 7-Year Clinical Experience and a Finite Element Analysis
Authors: Yang Hongsheng , Banskota Nishant , Fang Xiang , Xiong Yan , Zhang Wenli , Duan Hong
Published: March 2022

The treatment of benign pelvic lesions and tumors is still a challenge in clinical orthopedics. The surgical procedure was complicated and the postoperative complication was hard to avoid usually. The purpose of this study is to analyze the clinical outcome and predict the fracture risk of benign bone tumors on acetabular dome by finite element analysis. In our research, clinical data of 25 patients were collected from January 2010 to January 2017, including basic information of patients, reconstruction methods, complications, and postoperative MSTS function scores. Finite element analysis (FEA) was used to predict the fracture risk when a benign tumor involved an acetabular dome. 25 patients were followed up for 37.5 ± 5.6 (ranging from 24 to 78) months. Intraoperative bleeding was 100–3000 ml (mean 858.3 ml). The postoperative MSTS93 score was 19.61 ± 7.32 before operation and 26.28 ± 15.59 at the last follow-up. The results of finite element analysis suggest that there was a high risk for pathological fracture in the following: both columns were damaged by tumors; the anterior column and 50% of the posterior column were affected. Other cases were in the low fracture risk group. Based on this study, we believe that, according to the risk assessment results of tumor cavity fracture suggested by the FEA results, combined with the nature of tumor, it may become a useful tool which is a great significance to guide the operation plan, select the operation time, and guide the postoperative functional exercise.
Personalized Recommendation Algorithm for University Civics Courses with Multiple User Interests
Authors: Liang Hanyin , Li Wanwan
Published: March 2022

In response to the problems of unity, lack of relevance, lack of synergy, and inability to form a personalized collaborative education mechanism in the current curriculum setting of university thinking and politics education, a personalized recommendation system for university thinking and politics courses based on the multiple interests of users was developed. The system of interests is divided into two parts: first is initial interest guidance, in which the N meta-model is used to learn the context of known course processes; second is user interest extraction; at the end of creating the recommendation process, facing the diversity of user interests, probabilistic latent semantic analysis trains the interest-service-flow distribution of students to recommend the civics course that matches the current interest for students. A good recommendation algorithm can simulate learners’ enthusiasm and give full play to different learners’ learning personalities. The simulation experiments show that the system is stable in operation, complete in function, and has strong practicality and robustness, which is of positive significance in creating a win-win, diverse, and innovative atmosphere for students’ and teachers’ thinking education in colleges and universities.
Analysis of Distributions of HPV Infection in Females with Cervical Lesions in the Western District of Beijing Chaoyang Hospital
Authors: Gong Meili , Chen Chen , Zhao Huirong , Guo Liyuan , Sun Mingxia , Song Meiyu
Published: March 2022

Objective. To analyze the distribution of human papilloma virus (HPV) infection in women with cervical lesions of different grades and analyze the relationship of high-risk HPV and cervical lesions in order to facilitate targeted prevention. Methods. The infection status of HPV subtype was statistically analyzed in patients who underwent colposcopy examination from April 2017 to June 2019. Results. The infection rate of HPV was 81.4% in chronic cervicitis, 82.9% in 1ow-grade squamous intraepithelial lesion (LSIL), 63.7% in HSIL (high-grade squamous intraepithelial lesion), and 50% in cervical squamous cell carcinoma (CSCC). Among the 16 high-risk HPV types, the top six HPV types with the comprehensive infection rates were HPV16 > HPV52 > HPV58 > HPV18 > HPV51 > HPV53 in turn, and the infection rates were 23.3%, 14.8%, 13.3%, 9.8%, 9.2%, and 8.8%, respectively. The infection rates of HPV16 in chronic cervicitis group, LSIL group, and HSIL group were significantly different. There was no significant difference in the injection rates of HPV52, HPV58, and HPV18 among the three groups. HPV infection rates were highest in the 31–40 years old group, followed by the 41–50 years old group. Conclusion. The distribution of different types of HPV varies in different tissue types, which can be used to develop relevant vaccines to achieve better prevention and treatment of cervical cancer.
Post-Surface Processing and Virtual Simulation Analysis of Ball-Punch Test on CP-Ti Material
Authors: Vemula Ananda Mohan , Chandra Mohan Reddy G. , Manzoor Hussain M. , Kumar Atul , Kumar Naresh , Allasi Haiter Lenin
Published: March 2022

The titanium alloy is one of the prime materials for many engineering applications. It has been recommended for the components in automotive engines, power sector, biomedical industries, and more applications. It is due to the unique properties of the material with good strength and corrosion resistance. However, it is very challenging to handle Ti-based materials in manufacturing sectors without damaging the metallurgical quality. Thus, an attempt made to study the deformability of the CP-Ti material through ball–punch test to represent the stress, strain, and formability limit during mechanical loading and plastic deformation. The experiments are conducted following the ASTM E643 standards to study the material behavior. The maximum cupping reached to a height of 8.69 mm and got teared at the peak of doom. The separation has induced grain detachment due to tensile loading. The same condition is used to simulate with PAM STAMP™ software and 8.48 mm is the maximum cupping height achieved. The different is 0.21 mm. The results are interesting with similar observations and found acceptable to study the deformation.
Acrylated Biopolymers Derived via Epoxidation and Subsequent Acrylation of Vegetable Oils
Authors: Ho Yee Heng , Parthiban Anupreetha , Thian Min Chyong , Ban Zhen Hong , Siwayanan Parthiban
Published: March 2022

Chemically modified vegetable oils have become commercially attractive nowadays because they can be utilized as specialized components for the production of bioplasticizers and biopolymers due to their characteristics as being inexpensive, nontoxic, biodegradable, and renewable products. Due to the presence of unsaturation sites in the vegetable oils, they can be chemically modified and transformed into polymeric monomers such as acrylated epoxidized vegetable oils through well-known processes like epoxidation and acrylation processes. Acrylated epoxidized vegetable oil is a biopolymer that has a multitude of applications and is used mainly as a coating material for plastic, paper, and wood. There is an enormous demand for this biopolymer, and the market growth prospects are huge in some regions of the world. However, there are some challenges in the synthesis of acrylated epoxidized vegetable oils in achieving the performance of similar acrylated polymer derived from petroleum sources. In this paper, the chemical structure, properties, and chemical modifications of different types of vegetable oils were reviewed where the emphasis was given on epoxidation and its subsequent acrylation processes. This paper also highlights four types of epoxidation and their subsequent acrylation processes involving five different vegetable oils.
The Novel Role of Cytomorphology from Ultrasound-Guided Fine Needle Aspiration Cytology in Evaluating the Status of Prognostic Factors including Estrogen Receptor, Progesterone Receptor and HER2 in Breast Cancer
Authors: Li Yunzhu , Jia Shijun , Yao Yuqi , Zhou Yehan , Li Shurong , Li Jiayu , Liu Yang
Published: March 2022

It is well established that estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2) could be regarded as prognostic factors in breast cancer. Ultrasound-guided fine needle aspiration cytology (FNAC) has revolutionized the management of cancers, providing less invasive and quick diagnostic method. There are hardly any studies on the correlation between cytomorphology and prognostic biomarkers. We retrospectively analyzed the immunohistochemistry and the fluorescence in situ hybridization of breast cancer specimens from 252 patients, who have been diagnosed as breast cancer at our hospital. Morphological features of cytology smears were scored. The relationship between cytological features and three biomarkers were analyzed. Based on this, we developed a system to predict the status of biomarkers. The results indicated that some cytological parameters, especially the features of nucleoli, were distinctively related to the makers’ expression. In the novel scoring system, a cutoff of 12.0 provided a statistical discrimination for cytological grading. We concluded that cytomorphological features were associated with prognostic factors. The HR+ neoplasms showed scattered micronucleoli, while HER2+ neoplasms demonstrated centered macronucleoli. We summarized a scoring system to predict the status of three factors. This may help us to broaden the application of breast cancer cytology.
An Improved Secure Key Generation Using Enhanced Identity-Based Encryption for Cloud Computing in Large-Scale 5G
Authors: Gupta Rajeev Kumar , Almuzaini Khalid K. , Pateriya R. K. , Shah Kaushal , Shukla Piyush Kumar , Akwafo Reynah
Published: March 2022

The demand of cloud computing and 5G networks has increased in the current scenario due to their attractive features and also the security related to the data over the cloud. In the context of cloud security, there is a number of computationally hard methods available. One of the most popular methods used to secure data over the cloud is the identity-based encryption (IBE). It is an access policy that allows only authorized users to access legible data in order to avoid a malicious attack. IBE comprises of four stages, namely, setup, key generation or extract, encryption, and decryption. Key generation is one of the important and time-consuming phases in which a security key is generated. It is a computational and decisional hard problem for generating unbreakable and nonderivable secure keys. This paper proposes an enhanced identity-based encryption approach where a secure key is generated using part of an identity bit string in order to avoid leakage of users’ identity even if an adversary or attacker decodes the key or encrypted data. Experiment results show that the prosed algorithm takes less time in the encryption and decryption as compared to the competitive approach named efficient selective-ID secure identity-based encryption approach. One of the most important features of the proposed approach is that it hides the user’s identity by using the Lagrange coefficient, which consists of a polynomial interpolation function. The security of the system depends on the hardness of computing the bilinear Diffie-Hellman problem.
Electron Transfer Flavoprotein (ETF) α Controls Blood Vessel Development by Regulating Endothelial Mitochondrial Bioenergetics and Oxygen Consumption
Authors: Yan Yi , Xu Yingyi , Yang Xuewen , Li Zhonghao , Niu Kaiyuan , Liu Chenxin , Zhao Ming , Xiao Qingzhong , Wu Wei
Published: March 2022

While impairment of vascular homeostasis induced by hypercholesterolemia is the first step of cardiovascular diseases, the molecular mechanism behind such impairment is not well known. Here, we reported that high-cholesterol diet (HCD) induced defective vessel sprouting in zebrafish larvae. Electron transfer flavoprotein subunit α (ETFα) (encoded by the ETFA gene), a protein that mediates transfer of electrons from a series of mitochondrial flavoenzymes to the respiratory chain, was downregulated in HCD-fed zebrafish and in endothelial cells treated with oxidized low-density lipoprotein. Knockdown of ETFα with morpholino antisense oligonucleotides reproduced vascular sprouting defects in zebrafish larvae, while replenishing with exogeneous ETFA mRNA could successfully rescue these defects. ETFA knockdown in endothelial cells reduces cell migration, proliferation, and tube formation in vitro. Finally, knockdown of ETFA in endothelial cells also reduced fatty acid oxidation, oxygen consumption rate, and hypoxia-inducible factor-1α (HIF1α) protein levels. Taken together, we demonstrate that downregulation of ETFα is involved in hypercholesterolemia-induced defective vessel sprouting in zebrafish larvae via inhibition of endothelial proliferation and migration. The molecular mechanism behind this phenomenon is the decrease of HIF1α induced by downregulation of ETFα in endothelial cells. This work suggests that disturbance of ETFα-mediated oxygen homeostasis is one of the mechanisms behind hypercholesterolemia-induced vascular dysfunction.
Lagrange Multivariate Polynomial Interpolation: A Random Algorithmic Approach
Authors: Essanhaji A. , Errachid M.
Published: March 2022

The problems of polynomial interpolation with several variables present more difficulties than those of one-dimensional interpolation. The first problem is to study the regularity of the interpolation schemes. In fact, it is well-known that, in contrast to the univariate case, there is no universal space of polynomials which admits unique Lagrange interpolation for all point sets of a given cardinality, and so the interpolation space will depend on the set

Z

of interpolation points. Techniques of univariate Newton interpolating polynomials are extended to multivariate data points by different generalizations and practical algorithms. The Newton basis format, with divided-difference algorithm for coefficients, generalizes in a straightforward way when interpolating at nodes on a grid within certain schemes. In this work, we propose a random algorithm for computing several interpolating multivariate Lagrange polynomials, called RLMVPIA (Random Lagrange Multivariate Polynomial Interpolation Algorithm), for any finite interpolation set. We will use a Newton-type polynomials basis, and we will introduce a new concept called

Z
,
z

-partition. All the given algorithms are tested on examples. RLMVPIA is easy to implement and requires no storage.
Monitoring and Visualization of Physical Exercise Physiological Indicators Driven by Discrete Data
Authors: Tang Ying
Published: March 2022

Physical exercise physiological index monitoring has a wide range of applications in the fields of physiological index planning and design and organizational network evolution. Among the existing analysis methods for monitoring data points of physical exercise physiological indicators, the analysis error of point events under linear constraints is relatively large. Based on discrete data-driven datasets, this paper realizes the monitoring and visualization of sports physiological indicators. First, the principal component analysis of multivariate discrete data is used for dimensionality reduction. Second, the clustering of discrete physical exercise data uses the BIC criterion to preset the number of clusters, and the R software is used to visually realize the clustering results of physical exercise physiological indicators in each region in the text. The experiment solves the problem of mismatch of model parameter combinations when the physical exercise index monitoring quantity is used for the auxiliary analysis of the clustering results. Through the ARI index monitoring, the accuracy of the clustering physical exercise results of the method is increased to 89.7%, and the error rate is controlled within 4.3%. It promotes the superiority and effectiveness of multivariate discrete data-driven model clustering methods.
A Set of Comprehensive Evaluation System for Different Data Augmentation Methods
Authors: Zhang Can , Zhang Xu , Tu Dawei
Published: March 2022

Data augmentation is an effective method to prevent model overfitting in deep learning, especially in medical image classification where data samples are small and difficult to obtain. In recent years, different data augmentation methods, such as those based on single data transformation, multiple data mixing, and learning data distribution, have been proposed one after another, but there has never been a systematic system to evaluate various data augmentation methods. An impartial and comprehensive data augmentation evaluation system not only can assess the benefits and drawbacks of existing augmentation approaches in a specific medical image classification but also can provide an effective research direction for the subsequent proposal of new medical image data augmentation methods, thereby advancing the development of auxiliary diagnosis technology based on medical images. Therefore, this paper proposes an objective and universal evaluation system for different data augmentation methods. In this method, different augmented methods are evaluated objectively and comprehensively in terms of classification accuracy and data diversity by using existing large public data sets. The method is universal and easy to operate. To imitate the prevalent small-sized data sets in deep learning, an equal-interval sampling technique based on similarity ranking is presented to select samples from large public data sets and construct a subset that can fully reflect the original set. The augmented data sets are then created using various data augmentation approaches based on the small-sized data sets. Finally, different data augmentation strategies are objectively and fully evaluated based on the comprehensive scores of classification accuracy and data diversity following data augmentation. The validity and feasibility of the suggested sampling method and assessment system in this study are demonstrated by experimental findings on numerous data sets.
In Vitro Comparison of the Effect of Three Types of Heat-Curing Acrylic Resins on the Amount of Formaldehyde and Monomer Release as well as Biocompatibility
Authors: Ansari lari Homeira , Jahed Saman Hakimi , Abbasi Kamyar , Alam Mostafa , Alihemmati Mohammad , Ghomi Ali Jamali , Rahbar Mahdi , Mosaddad Seyed Ali , Soufdoost Reza Sayyad , Ashtiani Reza Eftekhar
Published: March 2022

Background/Purpose. The biocompatibility and cytotoxicity of formaldehyde and monomer are essential in resin-based denture’s byproducts. This present study was performed to compare the release of formaldehyde and monomer and biocompatibility of three brands of heat-curing acrylic resins, including Ivoclar, Bayer, and Acropars, with different mixing properties and the same processing methods. Materials and Methods. In this experimental in vitro study, 18 samples were fabricated from Ivoclar, Bayer, and Acropars heat-curing acrylic resins (each group consisting of 6 samples). The released formaldehyde and monomer level were measured and registered for 1, 7, and 30 days. Also, methyl methacrylate release from samples was used to test cell cytotoxicity using L-929 murine fibroblast. The data were analyzed with repeated measures, one-way ANOVA, and Kruskal–Wallis tests. Results. For formaldehyde release of 1 day, Ivoclar acrylic resin showed the lowest level, followed by Bayer and Acropars acrylic resins (

P
<
0.05

). On 7 and 30 days, Bayer acrylic resin released the lowest formaldehyde, followed by Ivoclar and Acropars acrylic resins (

P
<
0.05

). Acropars showed the weakest and most significant results regarding biocompatibility and monomer release in all three points of time, respectively (

P
<
0.05

). Conclusion. Acropars acrylic resin showed the most significant formaldehyde and monomer release and least biocompatibility compared to Bayer and Ivoclar for 1, 7, and 30 days; however, after 30 days, all three resins displayed the same amount of formaldehyde release.