bluuebunny/crossref_metadata_2025 huggingface dataset:
Creep Properties of Mudstone Interlayer in Bedded Salt Rock Energy Storage Based on Multistage Creep Test: A Case Study of Huai’an Salt Mine, Jiangsu Province
Authors: Chen Jie , Chen He , Wu Fei , Jiang Deyi , Zhang Hao , Gao Renbo , Ding Bowen
Published: August 2022

Salt rock is internationally recognized as an excellent medium for energy storage. However, most of the domestic salt mines are lacustrine laminated formations with mudstone interlayers, which have different creep characteristics to pure salt rocks. Therefore, in this paper, uniaxial compression creep tests were carried out on a mudstone interlayer in Huai’an, Jiangsu, China, and the multistage creep mechanical behavior of the mudstone interlayer was investigated using acoustic emission (AE) technology. The results show that at low stress levels, the axial deformation of the interlayer is greater than the lateral deformation. As the increase of the stress level, the lateral deformation becomes more significant, and the corresponding axial and lateral steady-state creep rates both exhibit nonlinear acceleration with the increase of the loading stress. In the initial loading stage of each stress level, the mudstone interlayer releases a large number of AE signals. After the creep stabilization, the AE signals decreased obviously, and a large number of AE signals were released at the last stress level. Based on the creep test data, an improved fractional viscoelastic-plastic model was fitted to it and compared with the Nishihara model. The applicability of the model was also tested, and the model was found to be a good description of the mudstone interlayer after oil erosion. The research results reflected the creep law of the mudstone interlayer to a certain extent and are expected to serve as a reference to studies on the long-term stability of the surrounding rock of a bedded salt rock energy storage.
Design and Development of Smart Wearable Products for Basketball Dribble Teaching Training Posture Monitoring
Authors: Zhang Shubing , Zhang Jianhua , Zhou Xiaomin
Published: August 2022

Basketball is one of the most popular sports, but apart from a small number of sports specialties, ordinary people rarely have the opportunity to receive professional basketball training, let alone coaches who provide one-on-one dribbling posture guidance. Dribbling is a very basic and important technique in basketball. Mastering the correct dribbling posture can help people further improve their basketball skills. In response to this problem, this article designed a smart wearable product to monitor the user’s posture in basketball dribbling training. If the user has a wrong dribble posture, the product will automatically prompt and give relevant suggestions. This article focuses on user demand research, product conceptual design, prototype development, and dribbling posture determination experiments and elaborates the design and development process of the product. Based on the experimental data, this article believes that the optimal parameters of the monitoring standard for the “head down too long” during basketball dribbling are the

x

-axis angle value of the motion sensor is critical for -120°, and the duration of exceeding the critical value is 1 second. The optimal parameters of the “dribbling wrist flip” monitoring standard are the

x

-axis angle value of the motion sensor has a critical value of 105°, and the duration of exceeding the critical value is 0.4 seconds. Judging from the end user’s experience and rating of the product’s trial experience, it can be seen that the smart product can indeed play a very good auxiliary effect in the field of dribbling posture monitoring. Popularizing it in the daily training of basketball players can effectively promote the full informatization and intelligent development of sports.
Some Improved Classes of Estimators in Stratified Sampling Using Bivariate Auxiliary Information
Authors: Bhushan Shashi , Kumar Anoop , Onyango Ronald , Singh Saurabh
Published: August 2022

This manuscript considers some improved combined and separate classes of estimators of population mean using bivariate auxiliary information under stratified simple random sampling. The expressions of bias and mean square error of the proposed classes of estimators are determined to the first order of approximation. It is exhibited that under some particular conditions, the proposed classes of estimators dominate the existing prominent estimators. The theoretical findings are supported by a simulation study performed over a hypothetically generated population.
Epimorphisms, Dominions, and Various Classes of Saturated Semigroups
Authors: Alam N. , Khan N.M. , Obeidat S. , Kirmani S.A.K. , Ahmad Jawed
Published: August 2022

In this paper, we discussed some saturated classes of ℋ‐commutative semigroups, left (right) regular semigroups, medial semigroups, and paramedial semigroups. The results of this paper significantly extend the long standing result about normal bands that normal bands were saturated and, thus, significantly broaden the class of saturated semigroups.
[Retracted] A Certain Investigation of Nanomaterial‐Based Li‐Ion Batteries for Electrical Vehicles
Authors: Sivaramkrishnan M. , Agenya R. , Santhi Mary Antony A. , Baskar Radhika , Prakash R. B. R. , Ramya D. , Sabarimuthu M. , Golie Wondalem Misganaw , Brucely Y.
Published: August 2022

Nowadays, the transports vehicles are required improvement or alternative source for fuel requirement, because of fuel shortage and reducing the global warming. Due to this reason, the electrical vehicle is more concentrated now. The electrical vehicle reduces the carbon emission and reduces the global warming. The main drawback for electrical vehicle is charging time and battery size. To overcome this problem, we use nanomaterial using batteries (like Li‐ion battery and Li‐based batteries). The nanomaterial particles increase the performance and storage battery capacity and reduce the size of the batteries.
Some Developments in the Field of Homological Algebra by Defining New Class of Modules over Nonassociative Rings
Authors: Razzaque Asima , Rehman Inayatur
Published: August 2022

The LA‐module is a nonassociative structure that extends modules over a nonassociative ring known as left almost rings (LA‐rings). Because of peculiar characteristics of LA‐ring and its inception into noncommutative and nonassociative theory, drew the attention of many researchers over the last decade. In this study, the ideas of projective and injective LA‐modules, LA‐vector space, as well as examples and findings, are discussed. We construct a nontrivial example in which it is proved that if the LA‐module is not free, then it cannot be a projective LA‐module. We also construct free LA‐modules, create a split sequence in LA‐modules, and show several outcomes that are connected to them. We have proved the projective basis theorem for LA‐modules. Also, split sequences in projective and injective LA‐modules are discussed with the help of various propositions and theorems.
Study on Bond Defect Detection in Grouted Rock Bolt Systems under Pullout Loads
Authors: Yu Shuisheng , Niu Leilei , Chen Jin , Wang Yawei , Yang Honghao
Published: August 2022

In grouted rock bolt systems, bond defects often occur, which seriously affects the safety of rock mass structures. Therefore, in this study, based on the existence of bond defects, laboratory tests were conducted to detect the location and length of bond defects and study the guided wave propagation in grouted rock bolt systems under different pullout loads. The guided wave signal was analysed in the time domain and frequency domain. In addition to the laboratory test, a numerical simulation of the effect of different bond defect locations on ultrasonic guided wave propagation in rock bolts was conducted using a damage-based model. The influence mechanism of bond defects on guided wave propagation under different pullout loads was explored. The study confirmed that there existed a stress platform in the rock bolt at the bond defect under a pullout load. The location and length of the bond defect could be detected by the stress platform and guided wave. The debonding length increased exponentially with the amplitude ratio (Q) of low frequency to high frequency, and the Q value could be used as the quantitative index of debonding length. As the pullout load increased, the impedance mismatch between the rock bolt and cement mortar (defect) increased, and the guided wave propagation in grouted rock bolt systems was irregular. The pullout load weakened the guided wave propagation law. The larger the pullout load is, the greater the weakening effect is.
Clinical Value Analysis of Hepatectomy Based on Minimally Invasive Surgical Imaging for Hepatolithiasis
Authors: Zhang Shubin , Xing Zhongqiang , Zhou Xinbo , Hu Zixuan , Liu Jianhua
Published: August 2022

Objective. To investigate the clinical value of hepatectomy based on minimally invasive surgical images in the treatment of hepatolithiasis. Methods. The clinical data of 87 patients with hepatolithiasis who received treatment in the Department of General Surgery of our hospital from February 2020 to September 2021 were retrospectively analyzed. According to different surgical methods, the patients were divided into minimally invasive group (n = 43) and laparotomy group (n = 44). Perioperative conditions and stone clearance rate were compared. Results. The preoperative conditions of patients in the two groups were comparable, and the average operation time in the minimally invasive group was significantly longer than that in the laparotomy group (t = 18.783,

P
<
0
.
0
0
1

). There was no significant difference in intraoperative bleeding, postoperative fasting time, postoperative complications, and stone clearance between the two groups (

P
>
0
.
0
5

). Postoperative hospital stay was significantly lower in the minimally invasive group than that in the laparotomy group (t = −0.486,

P
<
0
.
0
0
1

). Conclusion. Hepatectomy based on minimally invasive surgical imaging for hepatolithiasis is safe and feasible, has high clinical value, and can achieve similar short-term clinical efficacy to laparotomy and reduce the postoperative hospital stay of patients, reflecting its minimally invasive advantages, and it is worthy of clinical application.
Data-Driven versus Köppen–Geiger Systems of Climate Classification
Authors: Lasantha Vajira , Oki Taikan , Tokuda Daisuke
Published: August 2022

Climate zone classification promotes our understanding of the climate and provides a framework for analyzing a range of environmental and socioeconomic data and phenomena. The Köppen–Geiger classification system is the most widely used climate classification scheme. In this study, we compared the climate zones objectively defined using data-driven methods with Köppen–Geiger rule-based classification. Cluster analysis was used to objectively delineate the world’s climatic regions. We applied three clustering algorithms—k-means, ISODATA, and unsupervised random forest classification—to a dataset comprising 10 climatic variables and elevation; we then compared the obtained results with those from the Köppen–Geiger classification system. Results from both the systems were similar for some climatic regions, especially extreme temperature ones such as the tropics, deserts, and polar regions. Data-driven classification identified novel climatic regions that the Köppen–Geiger classification could not. Refinements to the Köppen–Geiger classification, such as precipitation-based subdivisions to existing Köppen–Geiger climate classes like tropical rainforest (Af) and warm summer continental (Dfb), have been suggested based on clustering results. Climatic regions objectively defined by data-driven methods can further the current understanding of climate divisions. On the other hand, rule-based systems, such as the Köppen–Geiger classification, have an advantage in characterizing individual climates. In conclusion, these two approaches can complement each other to form a more objective climate classification system, wherein finer details can be provided by data-driven classification and supported by the intuitive structure of rule-based classification.
Validation of a 1H-NMR Spectroscopy Quantitative Method to Quantify Trimethylamine Content and K-Index Value in Different Species of Fish
Authors: Ciampa Alessandra , Laghi Luca , Picone Gianfranco
Published: August 2022

The chemical analysis that is frequently employed for the evaluation of the freshness of fish includes (i) the quantification of trimethylamine (TMA) and (ii) the estimation of the K-Index, based on the ratio between the concentrations of adenosine triphosphate (ATP) and its breakdown products. TMA is quantified using a colorimetric reference method (AOAC), while the K-Index is usually determined by HPLC. The present work proposes a method for the above freshness biomarkers based on HR 1H-NMR as an alternative method able to assess both indexes simultaneously on aqueous fish extracts. To validate the proposed 1H-NMR method, a large set of validation checks has been addressed, such as accuracy, precision, specificity, limits of detection, linearity, and range of linearity and quantification according to EuroChem guidelines. The results show that the methodology satisfies all the validation requirements at the same level as the most frequently used methods, with the advantage of being faster and more repeatable, avoiding the use of solvents, such as toluene and formaldehyde, or dangerous reagents such as picric acid.
BERT-Embedding-Based JSP Webshell Detection on Bytecode Level Using XGBoost
Authors: Pu Ao , Feng Xia , Zhang Yuhan , Wan Xuelin , Han Jiaxuan , Huang Cheng
Published: August 2022

Webshell is a malicious program that might result in data theft, file modification, or other damaging behaviors once uploaded to a server. Detecting webshells is a key security concern for website administrators. In recent years, techniques such as obfuscation and encryption have been deployed on webshell technology, and classic detection approaches such as static feature matching are gradually underperforming on webshell detection. Meanwhile, there are variations between languages such as JSP and PHP, and researchers have proposed webshell detection methods primarily for languages such as PHP. At the same time, there are fewer detection techniques for JSP webshells. In this case, a detection approach for the JSP webshells is needed. This paper provides a novel webshell detection model for the JSP language. The model’s fundamental premise is that it introduces the BERT-based word vector extraction method, which has been shown in experiments to be more effective at detecting obfuscation, encryption, and other means of evading detection than the traditional Word2vec word vector extraction method. Meanwhile, we introduce the XGBoost algorithm as the model classifier. The experimental results reveal that present model has achieved 99.14% accuracy, 98.68% precision, 98.03% recall, and 98.35% f1 score, and the overall effect is better than the already existing JSP webshell detection approaches.
Necroptosis-Related Prognostic Signature and Nomogram Model for Predicting the Overall Survival of Patients with Lung Cancer
Authors: Xuan Yunpeng , Jin Xiangfeng , Wang Mingzhao , Wang Zizong
Published: August 2022

Background. Necroptosis is a type of programmed cell death mode and it serves an important role in the tumorigenesis and tumor metastasis. The purpose of this study is to develop a prognostic model based on necroptosis-related genes and nomogram for predicting the overall survival of patients with lung cancer. Method. Differentially expressed necroptosis-related genes (NRDs) between lung cancer and normal samples were identified. Univariate and LASSO regression analyses were performed to establish a risk score (RS) model, followed by validation within TCGA and GSE37745. The correlation between RS model and tumor microenvironment, mutation status, or drug susceptibility was analyzed. By combining clinical factors, nomogram was developed to predict 1-, 3-, and 5-year survival probability of an individual. The biological function involved by different risk groups was conducted by GSEA. Results. A RS model containing six NRDs (FLNC, PLK1, ID1, MYO1C, SERTAD1, and LEF1) was constructed, and patients were divieded into low-risk (LR) and high-risk (HR) groups. Patients in HR group were associated with shorter survival time than those in the LR group; this model had better prognostic performance. Nomogram based on necroptosis score, T stage, and stage had been confirmed to predict survival of patients. The number of resting NK cells and M0 macrophages was higher in HR group. In addition, higher tumor mutational burden and drug sensitivity were observed in the HR group. Patients in HR group were involved in p53 signaling pathway and cell cycle. Conclusion. This study constructed a robust six-NRDs signature and established a prognostic nomogram for survival prediction of lung cancer.
Evaluation Model Construction of Competitiveness of Sports Tourism Characteristic Towns through IoT Applications
Authors: Shi Yong
Published: August 2022

As the development of sports industry, new business type is also a breakthrough in the development of new urbanization, and it will become a new economic point to promote economic development in the future. In this paper, the “Jewel” model is utilized to dissect the records that influence the center competitiveness of humble communities with sports characteristics, and the loads of the files are examined, and the principal component analysis (PAC) is utilized to build the evaluation model of the center competitiveness of unassuming communities. Finally, a “factor model” is constructed for evaluation. Through the quantitative analysis of the influencing factors, the index system is formed, which is composed of 6 first-level indicators, 23 second-level indicators, and 45 third-level indicators, including environmental resources, characteristic industry competitiveness, infrastructure competitiveness, overall layout, government support, and funding sources. Furthermore, this carries on the weight examination to the list, as per the investigation result advances the idea for the future improvement of the games trademark town, and gives the premise to the improvement of the games trademark town.
Influence of Electrochemical Anticorrosion Technology on Concrete Structure and Performance
Authors: Yang Qin
Published: August 2022

In order to solve the problem of steel bar desensitization in island concrete, which leads to steel bar corrosion and greatly reduces the service life of structures, this work studies the influence of electrochemical corrosion prevention technology on the structure and performance of concrete. Through linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS), the reinforcement in seawater sand concrete and ordinary concrete under two different chloride ion erosion modes was tested electrochemically, and then, its polarization curve and electrochemical impedance spectrum were obtained and analyzed. The experimental results show that the slope ratio of anode Tafel decreases significantly under the condition of steel bar passivation. The self-corrosion potential of reinforcement is −204 MV, which is much higher than −480 MV obtained from early testing. The self-corrosion potential obtained from the L3 polarization test tends to be stable after 84 days. As the test continues, the capacitive reactance arc in L1 and L2 medium-frequency region will gradually disappear with the continuous development of corrosion. Conclusion. This study explains the electrochemical mechanism and rate of reinforcement corrosion in seawater and sea sand concrete.
Vulnerability and Structural Capacity Assessment of Historic Glass Facades under Bird-Strike
Authors: Bedon Chiara , Santi Maria Vittoria
Published: August 2022

Bird-strike analysis is of particular relevance for aircraft engineering applications, where major wing or fuselage components may suffer for possible collision during flying stage and result in serious structural damage. To this aim, the Federal Aviation Regulations requires dedicated bird-strike resistance assessment tests and certifications. In building applications, glass is also largely used for vertical and horizontal load-bearing components. In such a kind of structural design context, major attention is given to wind pressure, seismic loads, impact due to crowd and human body (i.e., to prevent falling out), or even explosions, and rather null consideration is posed for bird-strike analysis, due to their expected limited impact forces and effects on glass. This paper investigates such a topic giving evidence of the dynamic response of an existing glass facade built in 60 s as a part of a museum in Italy. The vulnerability analysis is carried out with computationally efficient Finite Element (FE) numerical models of consolidated use for bird-strike, based also on preliminary mechanical characterization from in-field geometrical inspection and Operational Modal Analysis (OMA) experiments. Local and global dynamic effects due to localized bird-strike on the examined glass facade are discussed based on parametric numerical analysis from Coupled Eulerian Lagrangian (CEL) method.
Intelligent Network Teaching of Product Design Specialty Based on Video Image Processing
Authors: Gao Zhimin , Lee Seungjin
Published: August 2022

The product design major was formally established in 2011 and has been an important part of Chinese art education since then. At the same time, it has laid a solid foundation for the development of China’s higher education. Therefore, the product design major occupies an important position in China’s higher education and plays an irreplaceable role in cultivating industrial design talents for the country. With the continuous development and progress of national education, the teaching of product design is also constantly innovating, in order to better improve the teaching effect of product design and cultivate more product design professionals for the country. The purpose of this paper is to study the teaching of product design major based on intelligent network teaching, establish an intelligent network teaching system, and carry out intelligent network teaching experiment of product design major based on this system. The experiment concluded that the overall satisfaction of the students majoring in product design on the intelligent network teaching reached 82%, and the intelligent network teaching mode also increased the outstanding performance rate of the students majoring in product design by 30%.
A Novel Outlier Detection Method of Long-Term Dam Monitoring Data Based on SSA-NAR
Authors: Song Jintao , Chen Yongchao , Yang Jie
Published: August 2022

Outlier generally exists in dam monitoring data which may seriously affect the accuracy of dam safety evaluation results. Aiming at the outlier detection of dam monitoring data, a novel dynamic detection method of dam outlier data based on SSA-NAR is proposed. This combined method does not depend on the effect quantity and influence quantity relationship of traditional dam safety theory and only uses the time series of effect quantity to mine the variation, which can avoid the impact of missing or abnormal of the influence quantity. The Nonlinear Autoregression (NAR) is a classical time series neural network widely used in engineering field. However, the prediction accuracy of NAR is greatly affected by the selection of model parameters, the Sparrow Search Algorithm (SSA) which is a novel model parameter solution method and can be combined with NAR to derive the optimal parameters of NAR prediction model. The outlier is identified through the analysis of the residual distribution between the predicted data and the measured data. The case study shows that when the original data does not contain outliers, the prediction accuracy of the model is high. When the outlier is included, the proposed model has good robustness which the outlier has little influence on the prediction effect. It can effectively detect the outlier in the original dam monitoring data and provide a reliable data basis for dam safety evaluation.
SEC61G Promotes Cervical Cancer Proliferation by Activating MAPK Signaling Pathway
Authors: Fan Yangyang , Wang Ying , Liu Feifei , Wang Haili , Li Qiumin
Published: August 2022

Objective. The abnormal expression of SEC61G plays an important role in the development of various tumors. This study explored the effects of SEC61G on MAPK signaling pathway and proliferation of cervical cancer (CC) cells. Methods. shRNA was used to inhibit the expression of SEC61G and EdU to observe its effect on the proliferation of CC cell SiHa. The effect of SEC61G on invasion was evaluated by Transwell assay. TCGA database was used to analyze the influence of high or low SEC61G expression level on the overall survival of CC patients. Western blot was used to detect the expressions of SEC61G, p-RAF1, Raf1, p-MEK1/2, MEK1/2, and p-ERK1/2 in cells. SiHa cells overexpressing SEC61G (SiHa-SEC61G) and control group (SiHa-mock) were subcutaneously implanted in nude mice. The tumor growth curve was measured at the specified time points between SiHa-SEC61G and SiHa-mock. The inhibitory effect of gefitinib on SEC61G was further evaluated. Results. In patients with CC, high SEC61G expression predicted poor prognosis. Silencing SEC61G inhibited proliferation and invasion of CC cells in vitro. Overexpression of SEC61G can promote the proliferation and invasion of CC cells in vitro. Meanwhile, overexpression of SEC61G promoted the proliferation of CC xenografts. Knocking down SEC61G can inhibit MAPK signaling pathway. Gefitinib can inhibit CC proliferation and tumor growth by SEC61G. Conclusion. SEC61G is highly expressed in CC and has poor prognosis. Inhibition of SEC61G expression can effectively inhibit the growth and proliferation of human CC cells. The mechanism may be related to the inhibition of MAPK signaling pathway.
Prevalence and Risk Factors for Adult Cataract in the Jingan District of Shanghai
Authors: Hong Yingying , Sun Yang , Ye Xiaofang , Lu Yi , Xu Jianjiang , Xu Jianming , Ji Yinghong
Published: August 2022

Purpose. We report the prevalence of age-related cataract (ARC) in the Jingan district of Shanghai and analyze the risk factors for ARC to be better prepared for the increasing burden of cataracts as a significant cause of visual impairment worldwide. Methods. From March to June 2010, a population-based, cross-sectional study was conducted in a community selected by stratified cluster sampling in the Jingan district of Shanghai. Residents aged 40 and older were recruited and investigated by questionnaires and ophthalmic examination. Univariate and multivariate logistic regression models were used to evaluate the association of these risk factors with any cataract. Results. A total of 2894 subjects aged 40 years and above were included in our study. Nine hundred forty-eight people (32.8%) were diagnosed with cataract, including 845 with bilateral cataracts (29.2%) and 292 with moderate and severe visual impairment (low vision, 10.1%). There were significant differences in low vision among different age groups and gender (Χ2age = 84.420,

P

age < 0.001, Χ2gender = 7.696,

P

gender = 0.021). For any cataract, we found age (OR = 1.107, 95% CI: 1.094–1.120) and refractive error (OR = 1.352, 95% CI: 1.127–1.622) were independent risk factors. Conclusion. The prevalence of cataract is estimated to be nearly one-third of the sample, increasing with age. We provided further evidence that age and refractive error are independent cataract risk factors.
Application of Neural Networks in Financial Time Series Forecasting Models
Authors: Li Xinhui
Published: August 2022

At present, the economic development of the world’s major economies is showing a positive and positive state. Driven by the development of related industries, the development of the financial field is also changing with each passing day. Various activities in the financial industry are in full swing, and the forecasts of related prospects are also full of uncertainties. Summarizing the laws of financial activities through technical means and making accurate predictions of future trends and trends is a hot research direction that relevant researchers pay attention to. Accurate financial forecasts can provide reference for financial activities and decision-making to a certain extent, promote the steady development of the market, and improve the conversion rate of financial profits. As an algorithm model that can simulate the biological visual system, the convolutional neural network can predict the numerical trend of the next period of time based on known data. Therefore, this paper integrates the support vector machine with the established model by establishing a convolutional neural network model and applies the prediction model to the prediction of financial time series data. The experimental results show that the model proposed in this paper can more accurately predict the trend of the stock index.
Electric Kickboard Demand Prediction in Spatiotemporal Dimension Using Clustering-Aided Bagging Regressor
Authors: Khan Prince Waqas , Park Se-Joon , Lee Sang-Joon , Byun Yung-Cheol
Published: August 2022

Demand for electric kickboards is increasing specifically in tourist-centric regions worldwide. In order to gain a competitive edge and to provide quality service to customers, it is essential to properly deploy rental electric kickboards (e-kickboards) at the time and place customers want. However, it is necessary to study how to divide the region to predict electric mobility demand by region. Therefore, this study is made to more accurately predict future demand based on past regional customers’ electric mobility demand data. We have proposed a novel electric kickboard demand prediction in spatiotemporal dimension using clustering-aided bagging regressor. We have used electric kickboard usage data from a Jeju, South Korea-based company. As a result of the experiment, it was found that the accuracy before using clustering-based bagging regressor and when the region was divided by the clustering method, the performance was improved, and we have achieved a regression score

R

2

of 93.42 using our proposed approach. We have compared our proposed approach with other state-of-the-art models, and we have also compared our model with different other combinations of bagging regressors. This study can be helpful for companies to meet the user’s demand for a better quality of service.
Disruption Management Approaches for Berth Scheduling in Bulk Terminals
Authors: Dávila de León Alan , Lalla-Ruiz Eduardo , Melián-Batista Belén
Published: August 2022

Maritime terminals are complex transportation systems sensitive to several sources of uncertainty. An alteration in the baseline planning, as a consequence of one or more disruptive events, can lead terminals to a lower quality of the service provided. Therefore, in a context where a terminal strives to maintain or increase competitiveness, it is necessary to consider the uncertainty in the planning and define actions capable of efficiently and effectively mitigating disruptive events. This paper addresses berthing operations at bulk terminals, considering the arrival and handling times as stochastic variables. Hybrid approaches (i.e., proactive-reactive) are proposed in order to provide the port terminal with robust planning capable of reducing the impact of disruptive events by defining uncertainty-tolerant schedules and reactive actions capable of restoring the performance of the terminal when disruptive events arise. Finally, the solution approaches are evaluated together with and without the incorporation of buffer-time management. The computational results corroborate the effectiveness of integrating proactive and reactive approaches in order to maximize the performance of the terminal and reduce the penalty costs derived from alterations in the baseline schedule, with the consequent increase in the terminal competitiveness.
Comparison of the Effect of EMLA™ Cream and the Valsalva Maneuver on Pain Severity during Vascular Needle Insertion in Hemodialysis Patients: A Controlled, Randomized, Clinical Trial
Authors: Babamohamadi Hassan , Ameri Zahra , Asadi Ilia , Asgari Mohammad Reza
Published: August 2022

Background. Pain due to vascular needle insertion has been reported in 40–60% of hemodialysis (HD) patients. Evidence suggests that there is typically no single method for relieving the pain of inserting vascular needles in HD patients. This study aimed to compare the effectiveness of EMLA cream and Valsalva maneuver (VM) on pain severity during vascular needle insertion in HD patients. Methods. This randomized, controlled, clinical trial was conducted on 90 patients undergoing hemodialysis in the hemodialysis unit of Kowsar Hospital, affiliated with Semnan University of Medical Sciences, in Semnan, Iran. Patients were selected via convenience sampling and were randomly assigned to one of the three groups (EMLA, VM, and control groups). For the patients in the EMLA group, 2.5 g of EMLA cream was applied 60 minutes before the start of dialysis. For patients in the VM group, a maneuver was performed for 16–20 seconds before the needle was inserted. Patients in the control group received only routine care without any additional interventions. The pain severity in the three groups was measured using the visual analog scale (VAS) two minutes after vascular needle insertion. Results. The results showed that the mean pain severity during cannulation was 2.06 ± 2.19 in the EMLA group, 3.2 ± 30.42 in the VM group, and 6.20 ± 1.49 in the control group, suggesting a significant difference between the groups (

P
<
0.001

). Pairwise comparison of the mean pain severity showed that it differed significantly in the EMLA and VM groups from the control group (

P
<
0.001

), but no significant difference was found between the EMLA and VM groups (

P
=
0.067

). Conclusion. According to the results, EMLA cream was as effective as VM in reducing the pain severity caused by arteriovenous fistula (AVF) cannulation. Therefore, the use of EMLA cream and VM is recommended for reducing the severity of AVF cannulation pain. Trial Registration. Iranian Registry of Clinical Trials, Trial No : IRCT20120109008665N12, registered on 3 June 2020.
Psychological Impact and Influence of Animation on Viewer’s Visual Attention and Cognition: A Systematic Literature Review, Open Challenges, and Future Research Directions
Authors: Praveen C. K. , Srinivasan Kathiravan
Published: August 2022

Animation is an excellent method to associate with the audience in a fun and innovative manner. In recent span, animation has been employed in various fields to enhance knowledge, marketing, advertisement, and age groups from infants to adults. The present communication expounds the systematic review on the impact created by animation on the viewer’s visual attention. For this review, a database such as Google Scholar, ScienceDirect, Taylor & Francis, and IEEE Xplore were pursued for publications on the impact of animation on viewer’s visual attention from January 2015 to December 2021. The search results showcased 175 titles with 114 full articles, out of which 35 were related to viewers’ visual attention towards animation. These reviewed studies comprised of physical outcome (

n
=
9

), psychological outcome (

n
=
15

), and cognitive outcome (

n
=
11

) from which the attention-related factors, physical effects, and cognitive effects of animation were assessed. The animation has influenced the viewer’s visual attention through the integration of the different stimuli and the highly organized presentation. Furthermore, the animation has also aided the viewer in attaining greater conceptual understanding, thereby facilitating their cognitive response. As a result, the animation was found to be helpful in enhancing learning skills, food marketing, and teaching strategy. Furthermore, the drawbacks and future recommendations of the studies were elaborated. In addition, challenges and open issues faced during the studies were discussed. Finally, the priority areas in animation identified for promising future directions to visualize large pool data, provide smart communication, and design 3D modeling structures were highlighted.
[Retracted] Herpes Simplex Virus Infection Increases Beta‐Amyloid Production and Induces the Development of Alzheimer’s Disease
Authors: Ge Tianfang , Yuan Yufei
Published: August 2022

Background. Alzheimer’s disease, a neurodegenerative memory disease, primarily results from the formation of amyloid plaques (Aβ) that gradually inhibit neuron communications. The entire mechanism of Aβ production remains unclear to date, and it is of particular interest among scientists to find out the exact mechanism that leads to amyloid precursor protein (APP) cleavage through the amyloidogenic pathway so that effective treatments can be developed. Method. 2 sets of experiments with the use of human H4‐N cell lines are proposed to fully investigate the validity of the hypothesis. All of the experiments would involve immunoblotting of Aβ using an anti‐Aβ antibody, and the results would be analyzed with the assistance of an image analyzer. A significant amount of Aβ would be expected to be present in the cytoplasm of cells with herpes simplex virus (HSV‐1) applied, as APP endocytosis would be induced by HSV‐1, which leads to higher Aβ levels inside the cell. Results. In this paper, a new hypothesis is presented on how HSV‐1 infection initiates APP endocytosis and causes an increase in APP cleavage and Aβ production inside the cells. It is also hypothesized that increased Aβ peptides exit the cell via exocytosis, therefore, leading to the development of Alzheimer’s disease. The findings will support the hypothesis if intracellular Aβ concentration is significantly higher after the introduction of dHSV‐1 and subsequently if extracellular Aβ concentration becomes higher without TeNT exocytosis inhibition. Conclusion. The results of this study would provide valuable insights into the mechanisms underlying Alzheimer’s disease and open new scopes of research for its potential treatments. Further studies on virus infection and the development of memory diseases should be conducted to investigate possible correlations.
Synchronising Bus Bunching to the Spikes in Service Demand Reduces Commuters’ Waiting Time
Authors: Vismara Luca , Saw Vee-Liem , Chew Lock Yue
Published: August 2022

Bus bunching is ostensibly regarded as a detrimental phenomenon in bus systems. We study a bus loop with two bus stops, one regular bus stop and one spike bus stop, where bunched buses can outperform staggered buses. The spike bus stop models a bus stop connected to a train or metro service, where passengers arrive in groups at periodic intervals (spikes). We introduce the configuration of synchronised bunched buses, where bunched buses wait for the spike in demand. For a wide range of parameters, synchronised bunched buses outperform perfectly staggered buses in terms of minimising the waiting time of commuters. We present an analytical formulation of the average waiting time in the case of bunched buses, synchronised bunched buses, and perfectly staggered buses with the consideration of different passenger demands, number of buses, and bus capacity. We demonstrate the validity of our analytical results through an agent‐based simulation of the bus loop system.
Rating Batters in Test Cricket
Authors: Akhtar Sohail , Awais Muhammad , Hussain Ibrar , Ali Gauhar , Ahmad Sadique , Khan Muhammad Imran , Qureshi Humera , ElAffendi Mohammed
Published: August 2022

In test cricket, we rated batters’ performance. We have proposed rating criteria as introduced by Scarf, Akhtar, and Rasool in 2014 with additional explanatory variables on the updated data set. The newly added covariates that we included in our research are the home factor and the ground influence. The same rating system is applied in the previous study. Using multinomial logistic regression, sessions from all days of a test match are modeled to determine match outcome probabilities at the end of each session. These models are based on all of the factors that can influence the outcome of a match. It is discovered that the predictors of home factor and pitch quality have a significant impact on the outcome of the test match. We used multinomial logistic regression to model data and estimate the parameters in the models. We forecasted match outcomes using these models at the end of each session and measured batters’ performances by using these probabilities. This process is repeated in a test match at the end of a session, and batters’ contributions to their team score are accumulated. Both teams’ batters are then ranked based on their rating points. The batsmen are rated based on their performance in the match by adding new factors (pitch effect and home advantage) in the models. The proposed ranking is compared with the ICC’s traditional ranking of batters in the test cricket series.
Clinical Analysis on the Effects of Tandospirone Citrate Assisted by Drawing Therapy on Medication Compliance and Sleep Quality in Patients with Anxiety Disorders
Authors: Hou Jichong , Zhang Ruifang
Published: August 2022

Objective. To explore the clinical effects of tandospirone citrate assisted by drawing therapy (DT) on medication compliance and sleep quality in patients with anxiety disorders. Methods. A total of 128 patients with anxiety disorders treated in the hospital were enrolled between January 2020 and January 2022. According to the random number table method, they were divided into the observation group (n = 64) and the control group (n = 64). The control group was treated with tandospirone citrate, while the observation group was additionally treated with DT. The clinical curative effect and medication compliance after treatment, scores of Hamilton Anxiety Scale (HAMA), Pittsburgh Sleep Quality Index (PSQI), and the World Health Organization’s Quality of Life Questionnaire-Brief Version (WHOQOL-BREF) before and after treatment were compared between the two groups. The occurrence of adverse reactions during treatment was recorded. Results. After treatment, the total response rate in the observation group was higher than that in the control group (96.88% vs 86.94%) (

P
<
0.05

). After treatment, scores of HAMA and PSQI in both groups were decreased, which were lower in the observation group than in the control group (

P
<
0.05

). After treatment, medication compliance in the observation group was higher than that in the control group (

P
<
0.05

). After treatment, scores of environmental factors, social relations, physiological function, and psychological status in both groups were increased, which were higher in the observation group than in the control group (

P
<
0.05

). During treatment, there was no significant difference in the incidence of adverse reactions between the two groups (

P
>
0.05

). Conclusion. DT-assisted tandospirone citrate can effectively improve the clinical symptoms of patients with anxiety disorders, improve medication compliance, sleep quality, and quality of life, and have a certain degree of safety.
Application of Medical-Nursing Integration Multidisciplinary-Assisted Surgical Wound Nursing Mode in Improving the Quality of Wound Treatment
Authors: Wang Jinyan , Yuan Ting , Shi Jun
Published: August 2022

Surgical treatment is a common clinical intervention for trauma, but postoperative pain and poor nursing lead to slow wound recovery and wound infection. Therefore, it is extremely important to select effective nursing intervention methods to improve the quality of wound treatment. This study explored the application value of the wound care model of medical integration and multidisciplinary-assisted surgery in improving the quality of wound treatment. The results show that medical-nursing integration in multidisciplinary-assisted surgical wound nursing mode can improve the quality of wound treatment and pain level in patients, which is beneficial to improving team cohesion of medical staff and satisfaction evaluation of patients.
[Retracted] Comprehensive Intervention and Effect of Martial Arts Routines on Children with Autism
Authors: Li Li , Li Hui , Zhao Zhe , Xu Shijie
Published: August 2022

Autism in children is a representative disease of pervasive developmental disorder, and there is currently no matching treatment. In the course of treatment, people generally use special education training, but this training mode cannot meet the comprehensive development of children. The traditional treatment mode cannot meet the changing new situation due to its poor adaptability. Martial arts routine movements are the soul of martial arts training, which can lay the foundation for movement training. Based on this, this article takes children with autism as research objects and aims to analyze the comprehensive intervention effect of martial arts routines on autism so as to provide some references for the treatment of children with autism. The article first analyzes the intervention forms of martial arts routine movements and realizes the combination of martial arts routine movements and children’s autism intervention treatment from a theoretical point of view. Then, the article randomly divides the experimental subjects into the experimental group and the control group and conducts an evaluation and analysis of various indicators before and after the training of children with autism. Finally, the article falls back from the experimental results to related theories, aiming to provide a scientific basis for the comprehensive intervention treatment of children with autism. The experimental results showed that the scale evaluation results of the experimental group are different from those of the control group, and various indicators have been improved and improved, including language, perception, and social skills. Among them, the language and behavior of children with autism increased by 19.1%. The perception ability increased by 20.7%, and the social ability increased by 5.9%. The above experiments and analysis fully demonstrated that martial arts routines have a good effect in the intervention and treatment of children with autism, which can well improve the comprehensive quality of patients.