bluuebunny/crossref_metadata_2025 huggingface dataset:
A Personalized Recommendation Technique for Travel Route Based on Fuzzy Consistent Matrix
Authors: Huiling Yang , Jing Jiang
Published: August 2022

Recommending travel routes for tourists has become a research hotspot in the present tourism industry. Various machine learning methods have been well studied for recommendation systems. However, the accuracy of these systems is not up to the expected levels. In order to increase the ranking accuracy, as well as, the recall rate of the recommended routes by the personalized travel recommendation algorithm, in this paper, a fuzzy consistent matrix technique is introduced for personalized travel recommendation systems. First of all, the user’s travel interest data are obtained through the fuzzy consistency matrix. Next, the user’s travel interest data are de-noised to determine the user’s preferred interest points and the coverage of the user’s interest points. Besides this, the constraints of the route recommendation systems have also become a research topic. Therefore, the proposed method also uses the fuzzy consistent matrix technology to determine the users’ similarity and classifies the personalized recommendation algorithm. Finally, a personalized travel recommendation model is constructed to comprehend the personalized travel route recommendation. The investigational outcomes, using real datasets, illustrate that when the number of routes is 5000, then the accuracy rate of the proposed method is approximately 97.21%, and the accuracy rate of the recommendation ranking is 97.54%. We also observed that when using 60 GB of data, the recall rate of the proposed method, for personalized travel recommendation routes, can reach as high as 97.59%.
New Class of Close‐to‐Convex Harmonic Functions Defined by a Fourth‐Order Differential Inequality
Authors: Khan Mohammad Faisal , Matarneh Khaled , Khan Shahid , Hussain Saqib , Darus Maslina
Published: August 2022

In the recent past, various new subclasses of normalized harmonic functions have been defined in open unit disk U which satisfy second‐order and third‐order differential inequalities. Here, in this study, we define a new class of normalized harmonic functions in open unit disk U which is satisfying a fourth‐order differential inequality. We investigate some useful results such as close‐to‐convexity, coefficient bounds, growth estimates, sufficient coefficient condition, and convolution for the functions belonging to this new class of harmonic functions. In addition, under convex combination and convolution of its members, we prove that this new class is closed, and we also give some lemmas to prove our main results.
On Topological Analysis of Niobium (II) Oxide Network via Curve Fitting and Entropy Measures
Authors: Siddiqui Muhammad Kamran , Javed Sana , Khalid Sadia , Hussain Mazhar , Shahbaz Muhammad , Fufa Samuel Asefa
Published: August 2022

The remarkable optical features of metallic nanoparticles have extensively developed the interest of scientists and researchers. The generated heat overwhelms cancer tissue incident to nanoparticles with no damage to sound tissues. Niobium nanoparticles have the ability of easy ligands connection so they are very suitable in treating cancer optothermally. A modern field of applied chemistry is chemical graph theory. With the use of combinatorial methods, such as vertex and edge partitions, we explore the connection between atoms and bonds. Topological indices play a vital part in equipping directions to treat cancers or tumors. These indices might be derived experimentally or computed numerically. Although experimental results are worthful but they are expensive as well, so computational analysis provides an economical and rapid way. A topological index is a numerical value that is only determined by the graph. In this paper, we will discuss the chemical graph of niobium (II) oxide. Additionally, each topological index is related with thermodynamical properties of niobium (II) oxide, including entropy and enthalpy. This has been done in MATLAB software, using rational built‐in method.
Life Cycle Ecological Footprint Reduction for a Tropical Building
Authors: Husain Dilawar , Prakash Ravi , Ahmad Akbar
Published: August 2022

Rapid urbanization significantly impacts natural resource demands and waste management in the construction sector. In this study, a novel methodology has been developed that could assess the overall environmental impact of a building during its lifespan by considering resources such as building materials, energy use, emissions, water, manpower, and wastes. The proposed method can estimate the life cycle ecological footprint (EFT) of a building. The result indicates that 957.07 global hectares (gha) of bioproductive land are required during the lifespan of the case building. The CO2 absorption land is the most significant bioproductive land in the EFT of the building. The low environmental impact of building materials may reduce the ecological footprint (EF) of buildings, and using renewable energy can also reduce the operational EF of a building. The proposed building materials and solar PV systems have the potential to reduce the building’s life cycle environmental impact by up to two‐thirds. The EF assessment of all existing and proposed buildings may be examined in order to execute strategies for a sustainable construction sector.
Deconstruction of the Optimal Design of Urban Road Interchange Based on the Integration of Smart Transportation and Big Data
Authors: Zhang Jiyong , Yang Yukui , Chu Lijing , Chen Shiliang , Bian Wenchao , Ling Meining , Li Shengfu
Published: August 2022

Urban interchange is the core hub connecting various regions, and it is of great significance for alleviating the problem of traffic congestion. In the process of urban interchange design, it is impossible to strictly control the traffic volume, interchange types, and standards by relying on traditional technologies. Smart transportation and big data are emerging technologies based on data, which can provide technical support for design and decision making. Based on this, this paper first uses smart transportation and big data technology to predict the traffic volume of Nancheng New District, so as to calculate the future development trend of the target area. Then, on the basis of traffic volume, the article uses smart transportation and big data technology to optimize the original urban interchange design scheme from the aspects of traffic capacity, safety, economic benefits, and environmental benefits. Finally, the article evaluates the optimized urban interchange scheme by means of comprehensive quantitative indicators and evaluation methods. Experiments show that the traffic capacity of the interchange on the outer ring road optimized by smart transportation and big data has increased to 72.6%, and the environmental coordination has increased from 45.2% to 55.2%. Moreover, the design aesthetics of the urban interchange after optimized design based on smart transportation and big data has increased to 65.9%. In addition, the comprehensive evaluation value of the urban interchange after optimization of smart transportation and big data reached 82.6. This fully shows that the optimal design of urban interchange based on the integration of smart transportation and big data can greatly improve the traffic capacity of urban roads.
High Systemic Immune-Inflammation Index and Body Mass Index Are Independent Risk Factors of the Thoracic Ossification of the Ligamentum Flavum
Authors: Zhao Yongzhao , Xiang Qian , Lin Jialiang , Jiang Shuai , Li Weishi
Published: August 2022

Background. Inflammation has been considered to play an important role in the pathogenesis of the thoracic ossification of the ligamentum flavum (OLF). However, the inflammation-related risk factors of thoracic OLF have not been fully investigated to date. Methods. A total of 95 patients (48 in the OLF group and 47 in the control group) were included in this retrospective study to explore the independent risk factors of thoracic OLF. The following demographic and clinical variables were compared between the two groups: gender, age, body mass index (BMI), coexistence of hypertension or diabetes, and inflammation-related variables. Multivariate logistic regression analysis was utilized to determine the independent risk factors. Results. High systemic immune-inflammation index (SII) (≥621) (odds ratioOR=12.16, 95% confidence intervalCI=2.95–50.17,p<0.01) and BMI (≥25 kg/m2) (OR=9.17,95%CI=3.22–26.08,p<0.01) were independent risk factors of thoracic OLF. SII (R=0.38,p<0.01) and BMI (R=0.46,p<0.01) were positively associated with OLF score. Conclusion. High SII and BMI were the independent risk factors of thoracic OLF. Multicenter prospective studies with a large population should be conducted in the future to verify our findings.
Multi-Kernel Fuzzy Clustering-Based Sporting Consumption Behavior Study
Authors: L Yingying , Wang Zhonghua , Li Ying
Published: August 2022

Cluster analysis plays a very important role in the field of unsupervised learning. The multikernel function is used to transform the low-dimensional nonlinear relationship of the influencing factors of consumption behavior into a high-dimensional linear problem, thereby improving the aggregation ability of clustering for multidimensional spatial data. In this study, a multikernel fuzzy clustering method is proposed to handle sporting consumption behavior problems. In the clustering process, the weight coefficients of different kernel functions are automatically adjusted based on fuzzy criteria to improve the feature learning ability of the combined kernel function and the generalization ability of the system after clustering. Extensive experimental results show the promising performance of the proposed multikernel clustering method.
Simulation Path of Network Microvideo Personalized Recommendation Based on Improved Ant Colony Algorithm
Authors: Liu Dequn
Published: August 2022

With the rapid development of Internet technology, network information not only brings many conveniences to the majority of users but also brings about the problem of information overload. It is increasingly difficult for users to accurately obtain the information they need from the vast ocean of information. This problem has led to the research of recommendation technology, especially the simulation path of online microvideo personalized recommendations. The video recommendation model in this study adopts the idea of an ant colony algorithm. The evaluation data and browsing record data generated by users are the basis of video recommendation, and the microvideo feature model and user preference model are abstracted from the original data by improving the ant colony algorithm. The recommendation algorithm is then used to recommend online microvideos that meet users’ preferences. There are two recommendation methods, one is to find similar students through the user preference model of each student, and find the microvideo content that the students have not learned; the other is to use the user preference model and the content feature model to match the content that conforms to the user’s preference. Compared with the traditional BP neural network algorithm, GA-BP algorithm, and PSO-BP algorithm, the mean square error MSE value of the ACO algorithm for microvideo scoring classification is reduced by 11.41%, 5.93%, and 2.41%, respectively. It can be seen that the classification of video ratings by the improved ACO algorithm has lower average errors than other algorithms. The network microvideo personalized recommendation scheme designed in this study has very practical significance.
[Retracted] Progesterone Reduces ATP‐Induced Pyroptosis of SH‐SY5Y Cells
Authors: Cui Chang , Wang Xiaona , Zhang Siyu , Wu Hui , Li Meijie , Dong Luoxiao , Yan Chongshuai , Li Dongliang
Published: August 2022

Aim. To investigate the mechanism of progesterone inhibiting the scorch death of SH‐SY5Y cells induced by exogenous adenosine triphosphate (ATP). Methods. SH‐SY5Y cells with good logarithmic growth were used in the experiment. The cells were randomly divided into 5 groups: normal control group, DMSO group, BBG group, ATP group, and ATP+progesterone group. The cell survival rate of each group was measured by CCK‐8 method. The expressions of P2X7 receptor, caspase‐1, caspase‐11, and IL‐1β were detected by western blotting. Results. (1) After SH‐SY5Y cells were treated with ATP at different concentrations (1, 3, 6, and 9 mmol/L) for 2 hours, the cell survival rate decreased in a concentration‐dependent manner compared with the normal blank group. The results showed that the optimal lethal concentration of ATP was 6 mmol/L. SH‐SY5Y cells were preincubated with progesterone at different concentrations (3, 10, 30, and 100 nmol/L) for 30 minutes and then incubated with 6 mmol/L ATP. The cell survival rate of this group was significantly improved (P < 0.01). The optimal concentration of progesterone to improve cell survival and inhibit cell death was 30 nmol/L. (2) Compared to the control group, there was no significant difference (P > 0.05) in P2X7 receptor, caspase‐1, caspase‐11, and IL‐1β with the DMSO group (0.001% DMSO, 24 h) and BBG group (bbg1 mmol/L, 24 h). (3) In the ATP group, the expression of P2X7 receptor and caspase‐1 (the key protein of classical cell death pathway) increased significantly (P < 0.01), which was related to inflammatory factor IL‐1β with consistent performance (P < 0.01). There was no significant change in caspase‐11 (the key protein of nonclassical focal death pathway) (P > 0.05). (4) The expression of P2X7 receptor, caspase‐1, and inflammatory factor IL‐1β in the progesterone+ATP group was significantly downregulated (P < 0.01). There was no significant change in caspase‐11 (P > 0.05). Conclusion. Certain dose of progesterone can inhibit the focal death of SH‐SY5Y cells induced by extracellular high concentration ATP. It can reduce the expression of P2X7 receptor, inhibit the conduction pathway of cell death, reduce the release of inflammatory factor IL‐1β, and improve cell survival.
The Efficacy of Chinese Herbal Medicine in Animal Models of Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis
Authors: Zhang Jiacheng , Xin Xiyan , Zhang Haolin , Zhu Yutian , Ye Yang , Li Dong
Published: August 2022

Objective. This study aimed to evaluate the efficacy of Chinese herbal medicine (CHM) on ovarian mass, weight, sex hormone disorders, and insulin resistance in animal models of polycystic ovary syndrome (PCOS). Methods. This systematic review and meta-analysis was conducted through a comprehensive search in three databases to find studies testing CHM in animal models of PCOS. Two researchers independently reviewed the retrieval, extraction, and quality assessment of the dataset. The pooled effects were calculated using random-effect models; heterogeneity was explored through subgroup analysis; and stability was assessed through sensitivity analysis. In addition, publication bias was assessed using the Egger’s bias test. Results. Fifteen studies with twelve mice and 463 rats published from 2016 to 2021 met the inclusion criteria. The results of primary outcomes revealed that CHM therapy was significantly different with control animals in ovarian mass and testosterone (SMD, −1.01 (95% CI, −1.58, −1.45); SMD, −1.62 (95% CI, −2.07, −1.16), respectively). The secondary outcomes as well showed an overall positive effect of CHM compared with control animals in weight (SMD, −1.02 (95% CI, −1.39, −0.65)), follicle-stimulating hormone (FSH) (SMD, 0.58 (95% CI, 0.19, 0.97)), luteinizing hormone (LH) (SMD, −0.94 [95% CI, −1.25, −0.64)), homeostasis model assessment-insulin resistance (HOMA-IR) (SMD, −1.24 (95% CI, −1.57, −0.92)). Subgroup analyses indicated that PCOS induction drug, formula composition, random allocation, and assessment of model establishment were relevant factors that influenced the effects of interventions. The stability of the meta-analysis was showed robust through sensitivity analysis. The publication bias was substantial. Conclusions. Administration with CHM revealed a statistically positive effect on ovarian mass, weight, sex hormone disorders, and insulin resistance. Moreover, these data call for further high-quality studies investigating the underlying mechanism in more depth.
Moment-to-Moment Observation of Parental Media Use and Parent-Child Interaction: Quality and Media Multitasking
Authors: Linder Lisa , McDaniel Brandon T. , Jaffe Heather
Published: August 2022

Mobile media proliferation throughout society has infused and complicated environments that formerly were interaction rich (e.g., waiting rooms, restaurants, and playgrounds) with the presence of smart devices. Ethnographic studies have indicated that parental use negatively impacts parent-child interaction quality. The current study reviews and expands on previous research through observing systematically parent-child interaction quality throughout the course of an entire meal (30-140 minutes). Utilizing five-minute intervals, across 93 parent-child dyads, we assessed both within- and between-person moment-to-moment changes in parenting quality (i.e., parental positivity, negativity, and engagement) in the context of parental media use. Between-person, only positivity appeared to decrease when comparing low and high parental media use. Within-person findings indicated that when the parent demonstrated higher than their typical media use, we noted a significant decrease in the quality of engagement and positivity. Differing from ethnographic studies, no change in negativity was identified within-person. Utilizing a lagged interval analysis, we identified a pattern of increased parental engagement with their child following intervals with parental media use, identifying a pattern of parental media multitasking heretofore only observed in ethnographic studies. Implications of findings in the context of previous research and future directions are discussed.
Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning
Authors: Ramesh S. , Rajalakshmi R. , Dwivedi Jaiprakash Narain , Selvakanmani S. , Pant Bhaskar , Bharath Kumar N. , Fissiha Demssie Zelalem
Published: August 2022

The Wireless Sensor Network is a network formed in areas human beings cannot access. The data need to be sensed by the sensor and transferred to the sink node. Many routing protocols are designed to route data from a single node to the sink node. One of the routing protocols is the hierarchical routing protocol, which passes on the sensed data hierarchically. The Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the hierarchical methods in which communication happens in two steps: the setup phase and the steady-state phase. The efficiency of the LEACH has to be optimized to improve the network lifetime. Therefore, the k-means clustering algorithm, which comes under the unsupervised machine learning method, is incorporated with the LEACH algorithm and has shown better results. But the selection of cluster head needs to improvise because it will transfer the summed-up data to the sink node, so it is to be efficient enough. So, this paper proposes the modified k-means algorithm with LEACH protocol for optimizing the Wireless Sensor Network. In the modified k-means algorithm, the weight of the cluster head is tested and elected, and the clusters are formed using the Euclidean distance formula. The proposed work yields 48.85% efficiency compared to the existing protocol. It is also proven that the proposed work showed more successful data transfer to the sink node. The cluster head selection process elects the more efficient node as the head with less failure rate. The proposed work optimistically balanced the whole network in terms of energy and successful data transfer.
Present Evidence of Determinants to Predict the Efficacy of Renal Denervation
Authors: Zhou Hao , Xu Yanping , Chen Weijie , Wang Liang , Du Huaan , Liu Hang , Ling Zhiyu , Yin Yuehui
Published: August 2022

Sympathetic overactivation is one of the main contributors to development and progress of hypertension. Renal denervation (RDN) has been evidenced by series of clinical trials for its efficacy and safety to treat overactivated sympathetic nervous system induced diseases. However, the results were inconsistent and not all patients benefited from RDN. Appropriate patient selection and intraoperative factors to improve the efficacy of RDN need to be solved urgently. Over the decade, research studies on the correlations between indicators and the antihypertensive effects have been conducted and made a fairly well progress. Herein, we comprehensively reviewed the research studies on how to make RDN more predictable or improve the efficacy of RDN and summarized these potential indicators or devices which might be applied in clinical settings.
Investigation on the Mechanical Properties of Flax/False Banana Hybrid Fiber-Reinforced Polymer Composite
Authors: Zelalem Biresaw Alelign , Sirahbizu Yigezu Belete
Published: August 2022

The intent of this research is to develop new material from flax and false banana fiber hybrid reinforced polymer composite using polyester resin as a matrix to replace synthetic fiber-reinforced polymer composites for automotive interior bodies. The composite samples were fabricated based on the weight percentage of fibers/matrix and the orientation of the fibers that were combined with Taguchi’s experimental design using the hand layup fabrication process. And also, single flax and single false banana fiber-reinforced polymer composite was fabricated with the same composition and orientation alone. The composite was tested for tensile and flexural strength properties, and it had been discussed and specimens were prepared according to ASTM standards. As a result, false banana showed better flexural strength than false banana fiber-reinforced composite for tensile strength, whereas the hybrid composites of 25% of flax, 15% of false banana, and unidirectional orientation have shown the maximum tensile and flexural strength with a value of 113.4 MPa and 167.88 MPa, respectively.
Comparison of Curative Effect between PFNA and PCCP in the Treatment of Femoral Intertrochanteric Fractures
Authors: Fan Buxin , Xiao Hansen , Wu Peng , Du Yao
Published: August 2022

Objective. To compare and analyze the clinical efficacy of proximal femoral nail anti-rotation (PFNA) and percutaneous compression plate (PCCP) for minimally invasive treatment of femoral intertrochanteric fractures. Methods. A retrospective analysis of 98 patients with femoral intertrochanteric fractures admitted to our hospital from January 2019 to December 2020 was used as the research object, and they were divided into PFNA group and PCCP group according to different treatment methods, with 51 cases and 47 cases. The intraoperative and postoperative indicators were compared between the two groups of patients. Results. There was no significant difference in the operative time, postoperative fracture healing time, and Harris score of hip joint function between the two groups (t = −1.43, 1.86, 1.63;

P
>
0.05

). Compared with the PFNA group, the intraoperative blood loss and postoperative drainage volume in the PCCP group were lower than those in the PFNA group (t = 11.38, 9.66;

P
<
0.05

). Compared with the PFNA group, the time of weight-bearing in the PCCP group was longer than that in the PFNA group (t = −2.23,

P
<
0.05

). The total incidence of postoperative complications was 7.84% in the PFNA group and 10.64% in the PCCP group, and there was no significant difference between the two groups (

P
>
0.05

). Conclusion. The PFNA and PCCP are both effective measures for the clinical treatment of intertrochanteric fractures, and internal fixation should be reasonably selected according to the specific conditions of the patients.
Japanese Kampo Medicine Juzentaihoto Improves Antiviral Cellular Immunity in Tumour-Bearing Hosts
Authors: Takaku Shun , Shimizu Masumi , Morita Rimpei
Published: August 2022

Global and antigen-independent immunosuppression by growing tumours can cause life-threating damage when concurrent with an infection in tumour-bearing hosts. In the present study, we investigated whether the oral administration of the Japanese traditional herbal (Kampo) medicine, juzentaihoto (JTT), plays a role in the improvement of antiviral cellular immunity in tumour-bearing hosts. Female BALB/c mice subcutaneously injected with murine colorectal cancer CT26 cells fed a control or JTT diet were inoculated with recombinant vaccinia virus expressing human immunodeficiency virus-1 glycoprotein 160 (vSC25). At 7 days postinfection, anti-vSC25 cellular immunity was evaluated by measuring the abundance of splenic virus-specific CD8+ T cells. JTT had no impact on CT26 tumour growth in vivo. Surprisingly, JTT augmented anti-vSC25 cellular immunity in CT26-bearing mice. Depletion of either CD25+ regulatory T (Treg) cells or myeloid-derived suppressor cells (MDSCs) also enhanced anti-vSC25 cellular immunity in tumour-bearing mice but had no therapeutic benefit against tumour growth. However, JTT had no impact on the abundance of these immunosuppressive cells. Overall, our data indicates that JTT contributes to the improvement of anti-vSC25 cellular immunity in tumour-bearing hosts possibly via a mechanism independent of CD25+ Treg cells and MDSCs, suggesting that this Kampo medicine can act as a promising antiviral adjuvant in an immunosuppressive state caused by tumours.
[Retracted] Model of the Integration of the Building Interior with the Natural Environment Based on Nanomaterials and I.M. Pei’s Design Concept
Authors: Gu Yu , Wang Yiyun , Li Jiangtao
Published: August 2022

The current pair of fusion models for fusing the information of building interior and natural environment treats the two separately due to a large amount of computation, which leads to low efficiency and poor results of fusion. Regarding the above‐discussed problems, the study constructs a fusion model of building interior and the natural environment under I.M. Pei’s design idea. Following an examination of how the interior of the building and the natural environment relate to one another by I.M. Pei’s design concept, information about the natural environment and the interior of the building is obtained through the use of remote sensing technology and 3D modeling technology. To finish the development of the model, the neural network model is used after the training of the parameters, and then, feature‐level and information‐level fusion of the obtained data is carried out. The validation data of the model showed that the fusion efficiency of the constructed model was improved by about 58.9%, and the fusion effect was significantly improved.
Analysis of the Influence of Slope Sliding on the Stability of Underground Diaphragm Wall Bridge Foundation Based on Wireless Sensor Network
Authors: Wang Lijuan , Zhao Qihua
Published: August 2022

Real-time monitoring, condition assessment, early warning processing, and damage identification of underground diaphragm wall bridge structures are the current research trends. Based on the wireless sensor network theory, this paper constructs the stability model of the slope sliding on the underground diaphragm wall bridge foundation. The model builds a complete set of underground diaphragm wall bridge vibration signal acquisition and monitoring platform through wireless sensor network node data acquisition and solves the problem of data accuracy measurement by using theoretical analysis, software and hardware design, software simulation, and experimental verification methods. During the simulation process, experiments were designed such as slope sliding vibration signal acquisition data accuracy test, sensor node wireless charging power test and modeling, lithium battery charging power test and modeling, wireless rechargeable sensor node system work test, and other experiments. The experimental results show that the accuracy of the collected vibration signals of the underground diaphragm wall bridge is high, the main working frequency bands are 868 MHz, 915 MHz, and 2.4 GHz, the maximum data transmission rate is 250 Kbps, and the communication distance reaches 100 m, which can meet the requirements of the underground diaphragm wall. The power of wireless charging of lithium batteries reaches 4.5 mW, which effectively improves the stability measurement accuracy of underground diaphragm wall bridge foundations.
Determinants of Pelvic Floor Disorders among Women Visiting the Gynecology Outpatient Department in Wolkite University Specialized Center, Wolkite, Ethiopia
Authors: Benti Terefe Ayana , Gemeda Gudeta Tolesa , Teferi Mengistu Girma , Abebe Sori Seboka
Published: August 2022

Background. Pelvic floor disorders encompass a broad range of interrelated clinical conditions. Pelvic floor disorders are a common public health concern that affects the lives of millions of adult females. This disorder is expected to be more widespread and probably more severe among women in low-income countries. However, there is limited knowledge about pelvic floor disorders and their determinants among women in Ethiopia. Objective. The purpose of the study was to assess the determinants of pelvic floor disorders among women who visited the gynecology outpatient service at the Wolkite University Specialized Hospital, Wolkite, Ethiopia, in 2021. Methods. A cross-sectional hospital study was conducted on 275 randomly chosen women from June 1 to July 1, 2021. A systematic sampling technique was used when selecting the study subjects. The data were gathered using interviewer administered structured questionnaires. The data collected was entered in version 3.1 of EpiData, and version 23 of Statistical Package for Social Sciences was used for the analysis. The variables with a

P

-value <0.25 in the bivariate analysis were considered for a subsequently built multivariable model, and factors with

P
<
0.05

in the final model were statistically significant. The results were presented in an adjusted odds ratio with a 95% confidence interval. Result. The prevalence of pelvic floor disorder was reported to be 17.8% with 9.3% of the women experiencing urinary incontinence, 8.9% experiencing pelvic organ prolapse, and 5.9% experiencing anal incontinence. Two hundred thirty-two (85.9%) were currently married, while 110 (40.7%) were housewives. Statistically, a significant association was found between age at first pregnancy (AOR = 5.193; 95% CI = 1.905–14.157), many vaginal deliveries (AOR = 15.858; 95% CI = 5.305–47.400), history of episiotomy (AOR = 7.508 95% CI = 1.556–36.224), and menopause (AOR = 7.665; 95% CI = 2.440–24.078) when analyzed with a multivariate logistic regression model. Conclusion. In this study, age at first pregnancy, number of vaginal births, history of episiotomy, and menopause were independently associated with pelvic floor disorder. Therefore, educating women about the year of their first pregnancy, promoting family planning, and advice on the prevention of routine episiotomy by a health professional is recommended.
Design of Chinese Opera Cultural Platform Based on Digital Twins and Research on International Cultural Communication Strategies
Authors: Ma Li
Published: August 2022

As an important part of a country’s diplomatic strategy, international cultural communication is increasingly valued by countries. But the traditional way of communication has been unable to keep up with the pace of the times. Digital twin technology can realize virtual reality, which can be applied to the design and dissemination of opera cultural platforms. The influence of a country’s culture not only depends on whether its content has unique charm but also depends on whether it has advanced means of communication and strong communication ability. The purpose of this paper is to study how to design an opera cultural platform based on digital twins. This paper proposes a three-dimensional transformation algorithm based on digital twin, which can play a good role in the design of the opera culture platform. The experimental results in this paper are shown in Table 1. In 2016, the economic benefits brought by international cultural communication to China were 35.889 billion yuan. It increased by 3.735 billion yuan year-on-year, with a growth rate of 10.4%. By 2019, the economic benefits brought by international cultural communication to China were 50.730 billion yuan, with an increase of 49.66% over the previous year and a growth rate of 9.7%. It can be seen that, through continuous external communication, this aspect shows the cultural strength of the country and obtains an excellent international reputation and social benefits. On the other hand, it reaped considerable economic benefits. Therefore, it is very necessary to study the strategies of international cultural communication.
Water Retention Behaviour and Fracture Toughness of Coir/Pineapple Leaf Fibre with Addition of Al2O3 Hybrid Composites under Ambient Conditions
Authors: Natrayan L. , Kumar P. V. Arul , Baskara Sethupathy S. , Sekar S. , Patil Pravin P. , Velmurugan G. , Thanappan Subash
Published: August 2022

Due to their high mechanical and physical properties, natural fibre-based composite materials have been important in many fields of application for four to five years. The chief intention of the current study is to determine the mechanical and water retention features of composite materials under ambient conditions. Coir and pineapple leaf fibre were used as a reinforcement, aluminium oxide as additives, and polyester as a matrix. The hybrid resources were laminated by the manual hand lay-up method. The mechanical characteristics like tensile, flexural, and fracture toughness properties were tested as per the ASTM standard. Nanoparticle weight ratio and its size variation significantly impact mechanical qualities. The hybrid composite’s water retention behaviour was tested for two types of water levels: ordinary tab water and nanofluid. The moisture uptake of the composites rose as the fibre volume increased, and after 640 hours, all of the composites had reached equilibrium. According to the results, the following combinations have the maximum mechanical strength: 15% wt.% coir, 15% wt.% pineapple, 10% wt.% nanofiller, and 60% wt.% polyester resin. The combinations mentioned above withstand the most load during the tests. Compared to 20% filler, 10% Al2O3 filler produces good interfacial adhesion in the current study. The fractured specimens were analyzed using scanning electron microscopic (SEM) pictures to recognize better the failure process of composites during mechanical testing.
Stock Market Reaction to the Announcement of the COVID‐19 Lockdown: Evidence from Healthcare Companies in Malaysia
Authors: Xie Yi , Zhou Lingke
Published: August 2022

The sudden global pandemic of COVID‐19 occurred in Malaysia at the beginning of new 2020, which increased the uncertainty of the economy. As a highly demanded industry during diseases, COVID‐19‐related news had a mixed influence on investors’ confidence in the healthcare industry, so the short‐term market reaction of the Malaysian healthcare industry is investigated during this unfolding event. This paper examines whether the “lockdown” suppressed the influence of COVID‐19 pandemic on stock performance in 12 listed healthcare companies in Malaysia. We consider the “lockdown” order has different impacts on samples. The hardest hit among the four events is the first announcement of lockdown, whose cumulative average abnormal return (CAAR) is negative (CAAR<0), for its strict movement control. However, the impacts of the following three lockdown events are positive and less severe as the market gradually digest these kinds of news and the deregulation of movement control. Previous studies have justified the influence of disease outbreaks on the stock market; however, this study compensates for other studies by employing the event study methodology (ESM) approach to provide the first empirical evidence of the unprecedented influence of “lockdown” on Malaysian healthcare stock market. This study has practical implications for Malaysian financial markets that the lockdown orders matter for the Malaysian healthcare industry. The empirical results show that the stock market has positively affected the lockdown announcement after the first event. In turn, the policymakers could draw on these results related to stock performance to modify the regulations in the healthcare industry.
Deep Learning-Based CT Imaging in the Diagnosis of Treatment Effect of Pulmonary Nodules and Radiofrequency Ablation
Authors: Zhou Chengwei , Zhao Xiaodong , Zhao Lili , Liu Jiayuan , Chen Zixuan , Fang Shuai
Published: August 2022

To study the effect of computerized tomography (CT) images based on deep learning algorithms on the diagnosis of pulmonary nodules and the effect of radiofrequency ablation (RFA), the U-shaped fully convolutional neural network (FCNN) (U-Net) was enhanced. The convolutional neural network (CNN) algorithm was compared with the U-Net algorithm, and segmentation performances were analyzed. Then, it was applied to the CT image diagnosis of 110 lung cancer patients admitted to hospital. The patients in the observation group (55 cases) were diagnosed based on the improved U-Net algorithm, while those in the control group (55 cases) were diagnosed by traditional methods and then treated with RFA. The Dice coefficient (0.8753) and intersection over union (IOU) (0.8788) obtained by the proposed algorithm were remarkably higher than the Dice coefficient (0.7212) and IOU (0.7231) obtained by the CNN algorithm, and the differences were considerable (

P
<
0.05

). The boundary of the pulmonary nodule can be segmented more accurately by the proposed algorithm, which had the segmentation result closest to the gold standard among the three algorithms. The diagnostic accuracy of the pulmonary nodule in the observation group (95.3%) was superior to that of the control group (90.7%). The long diameter, volume, and maximum area of the pulmonary nodule of the observation group were significantly higher than those of the control group, with substantial differences (

P
<
0.05

). Patients were reexamined after one, three, and six months of treatment, and 71 patients (64.55%) had complete remission, 32 patients (29.10%) had partial remission, 6 patients (5.45%) had stable disease, and 1 patient (0.90%) had disease progression. The remission rate (complete remission + partial remission) was 93.65%. The improved U-NET algorithm had good image segmentation performance and ideal segmentation effect. It can clearly display the shape of pulmonary nodules, locate the lesions, and accurately evaluate the therapeutic effect of RFA, which had clinical application value.
UHRF1 Induces Metastasis in Thyroid Cancer
Authors: Kuang Bo-Hua , Lin Guo-He , Liu Quentin , Wang Bi-Cheng
Published: August 2022

Background. Ubiquitin-like with PHD and ring-finger domain 1 (UHRF1) has been defined as an oncogene in tumor cells. However, the role of UHRF1 in mediating metastasis in thyroid cancer remains unexplored. In this study, we aimed to investigate the metastatic function and the potential mechanisms of UHRF1 in thyroid cancer. Methods. Transwell assays were used to detect the metastatic capability of thyroid cancer. Dual-luciferase reporter assays were applied to examine the activation of transcription factors. Coimmunoprecipitation assays and immunofluorescence staining assays were used to elucidate the potential mechanisms of UHRF1 in promoting the metastasis of thyroid cancer. Results. In this study, we found that overexpression of UHRF1 promoted the metastasis of papillary thyroid cancer cells, and suppression of UHRF1 decreased the metastasis of anaplastic thyroid cancer cells. Regarding the signaling pathway in regulating metastasis, UHRF1 directly combined and activated the transcription factor c-Jun/AP-1 in the nucleus, subsequently increasing the transcription of IL-6 and MIF. Conclusion. Our results suggest that UHRF1 could induce the metastasis of thyroid cancer, and the potential signaling pathway might be that UHRF1 activates c-Jun/AP-1 to increase the expression of IL-6 and MIF. These findings provide a novel mechanism of UHRF1 and illustrate that UHRF1/AP-1 complex could be a potential therapeutic target for patients with thyroid cancer.
Housing Price Appreciation Effects of Elevator Installation in Old Residential Areas: Empirical Evidence Based on a Multiperiod DID Model
Authors: Ma Shichang , Li Tingting , Yang Yunfan
Published: August 2022

Scientific measurement of the appreciation effect of house prices after the installation of elevators in old residential areas would help build a reasonable urban renewal investment mechanism. Based on the transaction data of second‐hand houses in old residential areas with elevators installed in Beijing from 2016 to 2021, a multiperiod DID model is constructed to measure the appreciation effect, dynamic effect, and heterogeneity effect brought by the installation of elevators and to explore the mechanism of the appreciation effect. The research results show that, overall, the installation of elevators boosts the house prices of the entire community, and the appreciation effect appears in advance due to good market expectations. However, the effect of house prices varies by floor. The higher the floor, the greater the appreciation of house prices, while low‐rise residential buildings are depreciated by the installation of elevators. Mechanistic research shows that the appreciation of house prices on high floors is mainly due to the improvement in the living environment, and factors such as noise and poor lighting lead to depreciation on lower floors. The results of quantile regression analysis show that the appreciation effect brought by the installation of elevators increases with the increase in the residential value.
The Role of the Key Differentially Mutated Gene FGFR3 in the Immune Microenvironment of Bladder Cancer
Authors: Jiang Jun , Zhan Yan , Li Jun
Published: August 2022

The tumor microenvironment (TME) has been a major focus of research in recent years as a crucial factor in the development and progression of bladder cancer. Unfortunately, the precise composition of TME, particularly the immunological and stromal components, remains unknown. In this work, we downloaded the RNA-seq expression profiles and somatic mutation data of 433 bladder cancer cases from The Cancer Genome Atlas (TCGA) and then employed a comprehensive bioinformatics approach to evaluate them. Firstly, the expression profiles were used to predict the scores and then the content of immune and stromal cells via the estimate package in R software. We then identified differentially expressed genes (DEGs) and differentially mutated genes (DMGs) according to the high-stromal score cohort and low-stromal score cohort. Finally, fibroblast growth factor receptor 3 (FGFR3) was the main differentially mutated gene in bladder carcinoma that we discovered after conducting a cross-study on DEGs and DMGs. Follow-up investigation revealed that FGFR3, whose expression correlated inversely with cancer progression stage, appeared to be a protective factor in bladder cancer. The method of Gene Set Enrichment Analysis (GSEA) was employed to, respectively, interpret the expression data of FGFR3 in high and low expression lists. We observed that the genes in the low FGFR3 expression list were strongly enriched in the biological processes associated with transplantation and cell adhesion, suggesting the possible role of FGFR3 in predicting TME metastasis status in bladder cancer. Therefore, this study is aimed at investigating whether FGFR3 is promising as a biomarker of TME remodeling to explain underlying mechanisms involved in tumorigenesis and metastasis, which may help to make decisions on treatments for bladder cancer.
Dynamic Evaluation of Transformation Ability for Emergency Scientific Research Achievements Based on an Improved Minimum Distance-Maximum Entropy Combination Weighting Method: A Case Study of COVID-19 Epidemic Data
Authors: Tan Qingmei , Hui Juan
Published: August 2022

In the process of responding to major public health emergencies, the transformation of emergency scientific research results often faces many unfavourable factors such as limited resources, tight time, changes in needs, and lack of results. It is necessary to evaluate and analyze the ability to transform emergency scientific research results under public health emergencies, so as to rationally allocate emergency scientific research resources between subjects and regions, improve the efficiency of emergency results transformation, enhance emergency scientific research capabilities, and efficiently support incident prevention, control, and treatment. Starting from the patent level, this paper constructs an indicator system to evaluate the transformation ability of emergency scientific research results under major public health emergencies. It improves the minimum distance-maximum entropy combination weighting method to realize the static evaluation of transformation ability for emergency scientific research results from the perspective of patents, then constructs the dynamic evaluation model of transformation ability for emergency scientific research results in public health emergencies from the perspective of patents, and carries out the dynamic evaluation of the emergency scientific research achievements transformation ability of different subjects and different regions. We also improve the ER index, measure the static polarization effect of the transformation ability for regional emergency scientific research results, and consider the time factor to construct a dynamic polarization effect measurement model for the transformation ability of emergency scientific research achievement. Furthermore, this paper improves the measurement model of contribution degree to the polarization effect, and analyzes the contribution degree to polarization of the transformation ability for regional emergency scientific research results.