bluuebunny/crossref_metadata_2025 huggingface dataset:
Folic acid and methotrexate use and their association with COVID-19 diagnosis and mortality: a case–control analysis from the UK Biobank
Authors: Topless Ruth , Green Ralph , Morgan Sarah L , Robinson Philip , Merriman Tony , Gaffo Angelo L
Published: August 2022

Objective

To determine if methotrexate or folic acid prescription was associated with differential risk for COVID-19 diagnosis or mortality.

Design

Case–control analysis.

Setting

The population-based UK Biobank (UKBB) cohort.

Participants

Data from 380 380 UKBB participants with general practice prescription data for 2019–2021. Updated medical information was retrieved on 13 December 2021.

Primary and secondary outcome measures

The outcomes of COVID-19 diagnosis and COVID-19-related mortality were analysed by multivariable logistic regression. Exposures evaluated were prescription of folic acid and/or methotrexate. Criteria for COVID-19 diagnosis were (1) a positive SARS-CoV-2 test or (2) ICD-10 code for confirmed COVID-19 (U07.1) or probable COVID-19 (U07.2) in hospital records, or death records. By these criteria, 26 003 individuals were identified with COVID-19 of whom 820 were known to have died from COVID-19. Logistic regression statistical models were adjusted for age sex, ethnicity, Townsend deprivation index, body mass index, smoking status, presence of rheumatoid arthritis, sickle cell disease, use of anticonvulsants, statins and iron supplements.

Results

Compared with people prescribed neither folic acid nor methotrexate, people prescribed folic acid supplementation had increased risk of diagnosis of COVID-19 (OR 1.51 (1.42–1.61)). The prescription of methotrexate with or without folic acid was not associated with COVID-19 diagnosis (p≥0.18). People prescribed folic acid supplementation had positive association with death after a diagnosis of COVID-19 (OR 2.64 (2.15–3.24)) in a fully adjusted model. The prescription of methotrexate in combination with folic acid was not associated with an increased risk for COVID-19-related death (1.07 (0.57–1.98)).

Conclusions

We report an association of increased risk for COVID-19 diagnosis and COVID-19-related death in people prescribed folic acid supplementation. Our results also suggest that methotrexate might attenuate these associations.
Impact of the macro-environment on the reporting of occupational injuries and illnesses by low-income workers compared to middle-income workers in South Africa: a mixed-methods study protocol
Authors: Mudenha Wellington Farai , Naicker Nisha , Singh Tanusha
Published: August 2022

Introduction

Construction workers, mineworkers and manufacturing employees in South Africa must report occupational injuries and illnesses to their employer as stipulated in section 14 of the Occupational Health and Safety Act and section 22 of the Mine Health and Safety Act. However, under-reporting of workplace injuries and illnesses is common globally.

This protocol seeks to ascertain if macro-environment factors impact reporting of workplace injuries and illnesses and compare reporting between low-income and middle-income workers.

Methods and analysis

To achieve the objectives of the study, a sequential mixed-methods research design will be adopted. A questionnaire will be distributed among low-income and middle-income workers from nine companies in Gauteng from the construction, mining and manufacturing sectors to establish macro-environment factors that impact their reporting. In addition, a data extraction sheet will be submitted to compensation fund administrators who receive and process workers’ compensation claims to determine reporting patterns by low-income and middle-income workers. In-depth interviews will be conducted with occupational health and safety subject matter experts in South Africa to ascertain their opinion regarding factors that impact reporting. Data will be analysed using SPSS V.27.

Ethics and dissemination

Prior to the commencement of the study, ethical approval and permission will be obtained from the University of Johannesburg Faculty of Health Sciences Research Ethics Committee. The researcher intends to publish the results of the study in peer-reviewed journals and present research papers at scientific conferences and provide feedback to employers and employees across all three industries. The study shall determine associations in reporting between the manufacturing, mining and construction sectors and establish interventions employers can implement for workers to report injuries and illnesses.
Pessary or progesterone to prevent preterm birth in women with short cervical length: protocol of the 4–6 year follow-up of a randomised controlled trial (Quadruple-P)
Authors: van Limburg Stirum Emilie V J , van der Windt Larissa I , van Dijk Charlotte E , van Baar Anneloes L , Leemhuis Aleid G , van Wely Madelon , de Boer Marjon A , van 't Hooft Janneke , Oudijk Martijn A , Pajkrt Eva
Published: August 2022

Introduction

Vaginal progesterone and a cervical pessary are both interventions that are investigated for the prevention of preterm birth (PTB). Thus far, beneficial or harmful effects of these interventions on long-term child health and development are described, but evidence is not robust enough to draw firm conclusions. With this follow-up study, we intent to investigate if progesterone or a pessary is superior for the prevention of PTB considering the child’s health at 4–6 years of corrected age.

Methods and analysis

This study is a follow-up study of the Quadruple-P trial; a multicentre, randomised clinical trial (NL42926.018.13, Eudractnumber 2013-002884-24) which randomises women with an asymptomatic midtrimester short cervix to daily progesterone or a pessary for the prevention of PTB. All children born to mothers who participated in the Quadruple-P study (n=628 singletons and n=332 multiples) will be eligible for follow-up at 4–6 years of corrected age. Children will be assessed using parental questionnaires. Main outcomes are child (neuro)development and behaviour. Other outcomes include child mortality, growth and general health. A composite of adverse child outcomes will be compared between the progesterone and pessary groups reporting OR and the corresponding 95% CI. Analyses will be performed separately for singletons and multiples and using the intention-to-treat approach.

Ethics and dissemination

The Medical Research Ethics Committee from Amsterdam UMC confirmed that de Medical Research Involving Human Subjects Act (WMO) did not apply to our study (W20_481 #20.531). Results will be published in a peer-reviewed journal and shared with stakeholders and participants. This protocol is published before analysis of the results.

Trial registration number

Dutch Trial Register (NL9646).
An automation solution for evaluating school capital projects based on fuzzy expert system
Authors: Hasan Monjurul , Newton Ross
Published: August 2022

Evaluating the priority of any school capital project is still considered unique because of its attachment to the fundamental human right, “the right to education”, and the prioritization methodology for school infrastructure projects has yet to be formalized. This paper presents a comprehensive framework and enhances the prioritization process of school infrastructure projects by quantifying project needs. The proposed “school project needs evaluation framework” consists of two parts. The first part describes the input selection process and integration of the fuzzy expert system to evaluate the school project's need as a quantitative term. The fuzzy rule-based system was developed in consultation with domain experts. The second part leverages the fuzzy expert system designed in the first part and quantifies the new school capacity and construction project type. The application steps of the automation solution developed based on the proposed framework are presented using examples.
The second law of thermodynamics as a deterministic theorem for quantum spin systems
Authors: Wreszinski Walter F.
Published: August 2022

We review our approach to the second law of thermodynamics as a theorem asserting the growth of the mean (Gibbs–von Neumann) entropy of quantum spin systems undergoing automorphic (unitary) adiabatic transformations. Non-automorphic interactions with the environment, although known to produce on the average a strict reduction of the entropy of systems with finite number of degrees of freedom, are proved to conserve the mean entropy on the average. The results depend crucially on two properties of the mean entropy, proved by Robinson and Ruelle for classical systems and Lanford and Robinson for quantum lattice systems: upper semicontinuity and affinity.
Ternary hybrid nanofluid near a stretching/ shrinking sheet with heat generation/ absorption and velocity slip on unsteady stagnation point flow
Authors: Mahmood Zafar , Ahammad N. Ameer , Alhazmi Sharifah E. , Khan Umar , Bani-Fwaz Mutasem Z.
Published: August 2022

For practical purposes, the study of ternary hybrid nanofluid flows near stretching/ shrinking surfaces, including heat generation/ absorption and velocity slip, has enormous value. It is crucial to understand how fluid mechanics deals with stagnation point flow, which is a common phenomenon in both engineering and scientific domains. In the evaporation process, the polymer enterprises, and the aircraft counter jet, the stagnation point flow may be found. An unsteady stagnation point flow is used to explore a ternary hybrid nanofluid (Cu–TiO2–Al2O3/ polymer) in relation to a convectively heated stretching/ shrinking sheet. This research also considers the velocity slip condition in addition to the traditional surface under no-slip conditions. The differential equations and their partial derivatives are changed to ordinary differential equations by applying approved similarity transformations. The MATHEMATICA operating system employs the Shooting with Runge–Kutta-IV process to explain the reduced mathematical model. When preliminary assumptions are appropriate, the technique may provide solutions. According to the data, nanoparticle volume fraction has an effect on the skin friction coefficient and local Nusselt number. The coefficient of skin friction decreases when velocity slip occurs at the border, while the rate of heat transfer increases. According to the research, increasing the unstable parameter led to large increases in the coefficient of skin friction and heat transfer as opposed to just altering velocity slip. The outcomes show that ternary fluid has a greater skin fraction and heat transmission profile than hybrid and traditional nanofluids for all parameters. The recent evidence and published results for a particular case were contrasted to validate the findings, and good agreement was established.
Artificial intelligence knacks-based stochastic paradigm to study lie group analysis with the impact of electric field on MHD Prandtl–Eyring fluid flow system
Authors: Shoaib M. , Naz Iqra , Khan M. Ijaz , Raja M. Asif Zahoor , Zubair Ghania , Nisar K. S. , Guedri Kamel
Published: August 2022

In this research paper, we observed the Prandtl–Eyring magneto hydrodynamic fluid model (PE-MHDFM) by applying the Bayesian regularization scheme as backpropagated artificial neural networks (BRS-BANNs). Effect of suction/injection at the wall is the source of convective steady flow. The nonlinear partial differential equations (PDEs) of PE-MHDFM are converted into ordinary differential equations (ODE) by applying some suitable similarity transformation. These ODEs are solved by utilizing Lobatto IIIA numerical procedure to acquire the reference dataset for different scenarios of BRS-BANN. The reference dataset is used to design the solver BRS-BANN. Further, the performance of BRS-BANN is clarified by MSE results, error analysis plots, regression and error histogram. Moreover, the solution of PE-MHDFM is observed through the validation, training and testing procedures. It is observed that the best correlation between the targeted values outcomes of the study is matched effectively, which definitely authenticates the validity and reliability of the designed solver. Furthermore, the impacts on the velocity profile and temperature profile are examined by the variation of different physical quantities along with their comparison with state-of-the-art Lobatto IIIA numerical approach.
Challenges of Agile–Crowd Software Development: A Systematic Literature Review
Authors: Qayyum Shamaila , Imtiaz Salma , Khan Huma Hayat
Published: August 2022

Crowdsourcing is an emerging approach in software development, where software is developed by unknown, heterogeneous people around the globe, via an open call by the employer. Crowdsourcing, when used with agile, faces challenges because of the different development methodologies. Agile development methodology has practices that involve face-to-face frequent interaction, whereas crowdsourcing is a distributed development with no or limited face-to-face interaction. Both concepts are actively being used in the software development industry due to their benefits. However, there is a need to explore the integration of both methodologies for an effective and efficient software development. In this regard, the first step is to identify the challenges of integrating crowdsourcing and agile. In this paper, we intend to identify the possible challenges that may be faced while executing agile along with crowdsourcing. For this, we have conducted a Systematic Literature Review. Five main categories of challenges are presented which are: team issues, coordination and communication issues, organizational issues, project-related issues and task-related issues. A list of possible challenges of Agile–Crowd Software Development (ACSD) is presented in this study.
Kinetic modeling of coupled epidemic and behavior dynamics: The social impact of public policies
Authors: Kontorovsky Natalia Lucía , Ferrari Carlo Giambiagi , Pinasco Juan Pablo , Saintier Nicolas
Published: August 2022

We study the propagation of a disease in a population where agents are characterized by their awareness level, representing the measures they take to avoid the infection. We introduce another agent, the government, which is constantly sending a message to the population trying to steer the mean awareness to a value which should ensure the extinction of the disease. We propose three levels to analyze this model. First, an agent-based model, which we use later to derive a mean-field system of ordinary differential equations; and finally, we propose a kinetic approach to model the evolution of the distribution of agents on the awareness levels. We obtain nonlinear systems of different dimension, first an ODE-Boltzmann system and later an ODEs-PDE system, where a Boltzmann or a first order, non-local partial differential equation are coupled with two ordinary differential equations that describe the evolution of the epidemic and the response of the government. We prove the existence and uniqueness of solutions in an abstract setting. Finally, we consider stubborn agents that are not willing to apply protection measures.
Comment on: “Aharonov–Bohm effect for bound states in relativistic scalar particle systems in a spacetime with spacelike dislocation”
Authors: Fernández Francisco M.
Published: August 2022

Here, we argue that the results shown in [L. L. Vitória and K. Bakke, Int. J. Mod. Phys. D 27 (2018) 1850005] are not correct. The truncation of the Frobenius method only yields some particular bound states from which one cannot derive any sound physical conclusion. The existence of allowed model parameters is an artifact of such procedure. Besides, the authors failed to obtain most of the solutions given by the truncation of the Frobenius series as well as their connection with the actual eigenvalues of the problem.
Modelling Predictability of Airbnb Rental Prices in Post COVID-19 Regime: An Integrated Framework of Transfer Learning, PSO-Based Ensemble Machine Learning and Explainable AI
Authors: Ghosh Indranil , Sanyal Manas K. , Pamucar Dragan
Published: August 2022

In this research, an effort has been put to develop an integrated predictive modeling framework to automatically estimate the rental price of Airbnb units based on listed descriptions and several accommodation-related utilities. This paper considers approximately 0.2 million listings of Airbnb units across seven European cities, Amsterdam, Barcelona, Brussels, Geneva, Istanbul, London, and Milan, after the COVID-19 pandemic for predictive analysis. RoBERTa, a transfer learning framework in conjunction with [Formula: see text]-means-based unsupervised text clustering, was used to form a homogeneous grouping of Airbnb units across the cities. Subsequently, particle swarm optimization (PSO) driven advanced ensemble machine learning frameworks have been utilized for predicting rental prices across the formed clusters of respective cities using 32 offer-related features. Additionally, explainable artificial intelligence (AI), an emerging field of AI, has been utilized to interpret the high-end predictive modeling to infer deeper insights into the nature and direction of influence of explanatory features on rental prices at respective locations. The rental prices of Airbnb units in Geneva and Brussels have appeared to be highly predictable, while the units in London and Milan have been found to be less predictable. Different types of amenity offerings largely explain the variation in rental prices across the cities.
Existence of photon sphere at or outside the throat of stable wormholes
Authors: Godani Nisha
Published: August 2022

In this paper, the effects of strong gravitational lensing are explored in the context of traversable wormholes by determining the existence of photon spheres. The redshift function is defined as [Formula: see text], where [Formula: see text] and [Formula: see text] are constants. Using this redshift function, the points of maximum potentials are determined which consequently gives the radius of photon spheres. It is obtained that either the throat itself can act as an effective photon sphere or the photon sphere exists outside the throat of the wormhole. Further, the nature of matter supporting the wormhole solutions is examined by analyzing the energy conditions, and the stability of solutions is tested with the help of the TOV (Tolman–Oppenheimer–Volkoff) equation.
Efficiency Concerns of Groundwater Irrigation in Green Revolution States of India: Data Envelopment Analysis (DEA) Approach
Authors: Khara Deepratan Singh , Ghuman Ranjit Singh
Published: August 2022

Increased reliance on groundwater for irrigation in India has resulted in its overexploitation, raising concerns about its long-term sustainability. The groundwater situation is severe particularly in the Northern–Western Green Revolution states of Punjab and Haryana. The provision of free (in Punjab) and heavily subsidized (in Haryana) electricity for tube-wells has resulted in the inefficient use of groundwater, which has contributed to its overexploitation. The primary objective of this study is to analyze the technical and groundwater irrigation efficiency of rice and wheat crops on sample farms in both states, as well as to determine the key factors impacting efficiency. This was accomplished using a non-parametric DEA model using cross-sectional data from 400 farms in Punjab and Haryana. The findings demonstrated disparities in both technical and groundwater consumption efficiency levels in both inter-state and intra-state scenarios. In both states, groundwater irrigation efficiency was found to be lower than technical efficiency. The mean technical efficiency for both crops has been found to be over 80% in both states, with irrigation efficiency being around 70%. Tube-well accessibility status, agriculture extension service access, fragmented landholdings, and adherence to standard crop irrigation practices were found to have a positive impact on technical and irrigation efficiency levels in both states.
DiVA: A Scalable, Interactive and Customizable Visual Analytics Platform for Information Diffusion on Large Networks
Authors: Sehnan Dhruv , Goel Vasu , Masud Sarah , Jain Chhavi , Goyal Vikram , Chakraborty Tanmoy
Published: August 2022

With an increasing outreach of digital platforms in our lives, researchers have taken a keen interest in studying different facets of social interactions. Analyzing the spread of information (
aka
diffusion) has brought forth multiple research areas such as modelling user engagement, determining emerging topics, forecasting the virality of online posts and predicting information cascades. Despite such ever-increasing interest, there remains a vacuum among easy-to-use interfaces for large-scale visualization of diffusion models. In this article, we introduce

DiVA

—
Di
ffusion
V
isualization and
A
nalysis, a tool that provides a scalable web interface and extendable APIs to analyze various diffusion trends on networks.
DiVA
uniquely offers support for simultaneous comparison of two competing diffusion models and even the comparison with the ground-truth results, which help develop a coherent understanding of real-world scenarios. Along with performing an exhaustive feature comparison and system evaluation of
DiVA
against publicly-available web interfaces for information diffusion, we conducted a user study to understand the strengths and limitations of
DiVA
. We noticed that evaluators had a seamless user experience, especially when analyzing diffusion on
large
networks.
The Influence of Personality Traits on User Interaction with Recommendation Interfaces
Authors: Yan Dongning , Chen Li
Published: August 2022

Users’ personality traits can take an active role in affecting their behavior when they interact with a computer interface. However, in the area of
recommender systems (RS)
, though
personality-based RS
has been extensively studied, most works focus on algorithm design, with little attention paid to studying
whether
and
how
the personality may influence users’ interaction with the recommendation interface. In this manuscript, we report the results of a user study (with 108 participants) that not only measured the influence of users’ personality traits on their perception and performance when using the recommendation interface but also employed an eye-tracker to in-depth reveal how personality may influence users’ eye-movement behavior. Moreover, being different from related work that has mainly been conducted in a single product domain, our user study was performed in three typical application domains (i.e., electronics like smartphones, entertainment like movies, and tourism like hotels). Our results show that mainly three personality traits, i.e.,
Openness to experience
,
Conscientiousness
, and
Agreeableness
, significantly influence users’ perception and eye-movement behavior, but the exact influences vary across the domains. Finally, we provide a set of guidelines that might be constructive for designing a more effective recommendation interface based on user personality.
Ultrasound Detection of Portomesenteric Venous Gas Is an Early Sign of Bowel Ischaemia in Non-Traumatic Abdominal Pain: Old Dogs, New Tricks—Four Cases Report
Authors: Di Capua Mirko , Tonani Michela , Paglia Stefano
Published: August 2022

Acute bowel ischemia is a severe disease often with a poor outcome. Early diagnosis can improve outcome, but atypical clinical manifestations and nonspecific laboratory and instrumental diagnostic findings may delay computed tomographic angiography (CTA). Portomesenteric venous gas (PVG), indirect sign of pneumatosis intestinalis, is considered a late finding with poor prognosis. We report four cases where PVG, easily identified through point-of-care ultrasonography (POCUS), was an early sign of bowel ischemia leading to a precocious diagnosis confirmed at CTA. In acute non-traumatic abdominal pain, an evidence of PVG could be an early ultrasonographic finding of bowel ischemia in the emergency department.
Microblog Emotion Analysis Method Using Deep Learning in Spark Big Data Environment
Authors: Yan Junya , Ma Xiaohui
Published: August 2022

Aiming at the problem that the existing methods in the big data environment cannot extract the emotional features of microblog sufficiently and the average accuracy of analysis results is low, a microblog emotion analysis method using deep learning in spark big data environment is proposed. First, the Jieba word segmentation method is used to process text comments, so as to reduce the interference of irregular grammar and nonstandard words on the emotion analysis task of microblog text. Then, features based on affective rules, unary word features, syntactic features, and dependent word collocation features are selected. In order to prevent the dimension disaster caused by excessive feature dimensions, the feature selection method of information gain is used to reduce the dimension of features. Finally, a microblog emotion analysis method based on deep belief network (DBN) is established, and the DBN is parallelized through spark cluster to shorten the training time. Experiments show that when the feature set is composed of TOP2000 features, the classification accuracy of the fusion of four features is 90.94%, which is higher than that of the comparison method. In addition, the training time of DBN algorithm parallelized by spark cluster is only 27.78% of that of single machine. Therefore, compared with the comparison method, the proposed method can significantly improve the performance of the microblog emotion analysis system.
Brain Magnetic Resonance Imaging Features of Nicotine‐Dependent Individuals and Its Correlation with Polymorphisms of Dopamine D Receptor Gene
Authors: Liu Hongfeng , Guan Lixin , Nie Ying , Li Qi , Xue Jiting , Yang Yong , Rong Shengzhong , Liang Jun , Guan Yanzhong , Zhai Fengguo , Ren Yanhai , An Ziyi , Dong Zesong , Han Zhixue
Published: August 2022

The aim of this research was developed to provide a scientific basis for individualized prevention, clinical diagnosis, and corrective treatment of nicotine addiction. The objects were 214 cases in the smoke group and 43 cases in the control group. According to the Fagerstrom Nicotine Dependence Test (FTND), the smokers were divided into mild nicotine dependence group (FTND < 6 points, 138 cases) and nicotine severe dependence group (≥6 points, 76 cases). The brain structure in long‐term smokers was evaluated by using magnetic resonance imaging (MRI). The nicotine dependence was further analyzed by grouping the included individuals, and some candidate genes related to nicotine addiction were screened by combining with bioinformatics analysis. The family research strategy was adopted to detect nicotine addiction susceptibility genes and their polymorphisms. The MRI imaging results showed that the bilateral thalamus, right parietal, and left lens gram‐molecule volume (GMV) were negatively correlated with smoking index and smoking years in the smoking group. The GMV of the posterior cingulate cortex in the severe nicotine dependence group was lower than that of the control group, and the GMVs of bilateral thalamus and bilateral superior limbic gyrus in the mild nicotine dependence group were lower than those of the control group. The gene polymorphism detection showed that rs6275 was highly polymorphic in the target population and the frequency of rs6275‐C allele was 53.26%. Therefore, the MRI imaging characteristics suggested that the affected brain regions of smokers and people with varying degrees of nicotine dependence were mainly concentrated in response‐related pathways and the limbic system and had cumulative effects on the central nervous system. In addition, the M6275 polymorphism of DRD2 gene was associated with susceptibility to nicotine addiction in Chinese population, and the M6275‐C allele had a protective effect on susceptibility to nicotine addiction and smoking initiation.
A Multiobjective Model for Optimizing Green Closed‐Loop Supply Chain Network under Uncertain Environment by NSGA‐II Metaheuristic Algorithm
Authors: Hassangaviar Babak , Naderi Bahman , Etebari Farhad , Vahdani Behnam
Published: August 2022

Nowadays, due to growing development and competitiveness in global markets of products, companies are forced to make significant efforts for supply procurement, production, and goods distribution in order to survive in the market and be able to respond to their customers’ needs as quickly and cost‐efficiently as possible. In this regard, supply chain management is considered a crucial indicator. This study presents a multiobjective, multifacility, closed‐loop supply chain under uncertain environments considering green supply chain aspects. The model is designed with multiple products, periods, plants, customer markets, collection centers, recycle centers, distribution centers, return facilities, product recovery facilities, and suppliers. After modeling the study, the model is solved by the Nondominated Sorting Genetic Algorithms (NSGA‐II) in order to rank the optimum solutions. The efficiency of the research model is indicated by the results and depicted graphs in the present study. Results show that the exact value of the triple objective functions is calculated. Also, the problem is solved in small, medium, and large dimensions. Then, the accuracy of the proposed model compared to the metaheuristic method is shown. Finally, by performing sensitivity analysis, we showed that target functions are less sensitive to reducing the capacity of centers.
Metachronous Liver Metastasis from Alpha-Fetoprotein-Producing Gastric Cancer Successfully Treated with Capecitabine/Oxaliplatin Combination Chemotherapy
Authors: Furukawa Soichi , Kobayashi Takashi , Shiono Saori , Nishinakagawa Shuta
Published: August 2022

A consensus regarding the treatment of recurrent alpha-fetoprotein-producing gastric carcinoma due to its rarity is lacking. We herein describe a case of such a carcinoma that was associated with metachronous liver metastasis. A 73-year-old man was referred for the surgical treatment of a type 2 gastric tumor that extended from the greater curvature of the gastric corpus to the pylorus. As no remote metastases were detected, the patient underwent open total gastrectomy with lymphadenectomy and Roux-en-Y reconstruction. Histopathological examination revealed regional lymph node metastasis and the invasion of the muscularis propria by a moderately differentiated adenocarcinoma. Immunostaining of the primary tumor was positive for alpha-fetoprotein and negative for human epidermal growth factor receptor 2. Serum alpha-fetoprotein levels decreased to within normal limits after eight courses of S-1 monotherapy; however, levels started to increase, and a hypovascular nodule in segment 5/6 of the liver was detected 3.5 years later. Serum alpha-fetoprotein levels returned to the normal range, and the tumor was undetectable after four courses of capecitabine and oxaliplatin therapy. No recurrence was detected at 1.5-year follow-up. This case demonstrates that combined capecitabine and oxaliplatin therapy can successfully treat metachronous liver metastasis from alpha-fetoprotein-producing gastric carcinoma.
[Retracted] An Analysis of the Cultivation Methods of Visual Communication Design in New Media Environment
Authors: Qi Meng
Published: August 2022

In order to better adapt to the teaching development needs of visual communication design in the new media environment, a method of visual communication design training based on the ecological environment of the new media environment is proposed. This method constructs a web‐based professional course network teaching platform by cultivating practical design talents under the new platform, new environment, and new technology, starting from the perspective of practical application, starting from the teaching process of visual communication design specialty, combined with the needs of social development for students’ creative needs, so as to provide rich visual communication design cases, design practice, and exchange and discussion platform for professional teaching. The results show that the local display time of the system page is too long. It takes 3.3 seconds to enter the query page manually, and the script test time is 0.3 seconds, so the page display time takes about 3 seconds. The system basically meets the functional requirements, but from the perspective of resource occupation, the program requirements are further optimized to reduce the utilization of CRU. From the analysis of memory usage, it is suggested to optimize the memory recycling mechanism.
Audio and Video Matching Zero‐Watermarking Algorithm Based on NSCT
Authors: Fan Di , Sun Wenxue , Zhao Huiyuan , Kang Wenshuo , Lv Changzhi
Published: August 2022

In the Internet age, information security is threatened anytime and anywhere and the copyright protection of audio and video as well as the need for matching detection is increasingly strong. In view of this need, this paper proposes a zero‐watermarking algorithm for audio and video matching based on NSCT. The algorithm uses NSCT, DCT, SVD, and Schur decomposition to extract video features and audio features and generates zero‐watermark stream through synthesis, which is stored in a third‐party organization for detection and identification. The detection algorithm can obtain zero watermark from the audio and video to be tested and judge and locate tampering by comparing with the zero watermark of the third party. From the experimental results, this algorithm can not only detect whether the audio and video are mismatched due to tampering attacks but also locate the mismatched audio and video segments and protect the copyright.
Research on an Artificial Intelligence-Based Professional Ability Evaluation System from the Perspective of Industry-Education Integration
Authors: Bian Yijie , Lu Yanchi , Li Jingqi
Published: August 2022

The rapid development of artificial intelligence technology demands higher requirements for employment and talent training. The integration of industry and education is an important way to solve the mismatch between industrial demand and talent supply. Therefore, this study starts from the perspective of the integration of industry and education. We collect recruitment texts from the perspective of “industry” and mine the specific requirements of the artificial intelligence post system through the LDA topic model and the combination of Word2Vec and K-means. We then conduct expert consultations and adjust the selected indicators from the perspective of “education.” Finally, we construct a four-dimensional vocational ability grade evaluation index system, including basic vocational skills of artificial intelligence, database, network skills, algorithm and design skills, and research and practice skills. The intuitionistic fuzzy analytic hierarchy process, which can eliminate the subjective uncertainty of experts in the scoring process, is applied to calculate the index weights. We find that the weight of algorithm and design skill is the highest, which is an important criterion for artificial intelligence professional ability evaluation. Among the second-level indicators, practical indicators such as team spirit, innovation ability, and communication ability are the focus of investigation from the perspective of industry, while in education, the cultivation of knowledge and skills such as programming ability, applied mathematics ability, data structures, and algorithms are more important.
Analysis of Cross-Cultural Communication in English Subjects and the Realization of Deep Learning Teaching
Authors: Niu Jianing , Liu Yang
Published: August 2022

In subject teaching, subject characteristics are the logical starting point for teaching development, and a deep understanding of subject characteristics is the basis for effective teaching. In practice, due to ignoring the cross-cultural understanding of middle school English subjects, there has been a long-term dilemma of “emphasizing knowledge and neglecting culture,” and overemphasis on the instrumental nature of middle school English has caused middle school English teaching to lose cultural self-cultivation and obscured the due education human value. Under the background of globalization and diversification, it is more and more important to develop students’ cross-cultural awareness. How to realize cross-culturalism in middle school English teaching has become an important subject of teaching reform and development. From the perspective of English subject, this research constructs a scientific and implementable English listening and speaking teaching mode that promotes students’ in-depth learning, provides specific and operational teaching implementation plans for English subject teachers in front-line teaching, and improves classroom teaching. It can promote students’ construction of the meaning of language knowledge, stimulate their learning motivation, and finally achieve the common development of teachers and students.
Resource Cache Sharing System of Education Information Center Network Based on Internet of Things
Authors: Juan Wang
Published: August 2022

The development of the internet of things has spawned new information concepts such as educational information sharing. Due to the openness of the internet of things, all kinds of mobile terminal devices can rely on the internet of things for data communication, information interaction, and resource sharing. Although the development of the internet of things has brought convenience to people’s lives, the internet of things is facing severe challenges in the fields of internal data sharing and cache sharing of educational information. The existing resource sharing systems do not fully consider the problems of privacy, shared data security, and data access control. This paper mainly studies the network integrated resource cache sharing system of the education information center based on internet of things. The data management system of the network education information center is developed on the basis of the school teaching management system and lifelong education public service platform, combined with the actual situation of student information. This paper combines the enrollment and information workflow of the student information management website, analyzes the problems existing in the current workflow, and then uses computer technology to standardize and transform the workflow, realize the information of the built-in resources in the data management, and solve the problems of data cache sharing and data statistics in the management of the education information center. The simulation results show that with the increase in the number of concurrent threads, the average response time of the edge cloud system deployed with two servers is smaller than that of the edge cloud system deployed with a single server, and the cloud system has good scalability.
Evaluation of the Inferior Vena Cava Diameter in Dehydrated Children Using Bedside Ultrasonography
Authors: Özkan Esra Akyüz , Kılıç Mahmut , Çalışkan Fatih , Baydın Ahmet
Published: August 2022

Objective. Bedside ultrasonography (US) is a new imaging modality that has begun to be used in the Pediatric Emergency Unit to evaluate inferior vena cava (IVC) diameter for intravascular volume status. In this article, we aimed to evaluate IVC diameter with bedside US before and after the fluid therapy in dehydrated children. Methods. A total of 124 dehydrated patients were enrolled, aged 8 months to 17 years. The maximum diameters of the IVC and aorta (AO) were measured. IVC/AO ratio and IVC collapsibility index IVC–CI were calculated before and after the fluid therapy and correlation with the degree of dehydration and laboratory parameters was investigated. Results. Of the 124 patients, 49.2% (n = 61) were male, the mean age was 7.5 ± 4.94 years. The IVC/AOs ratio was increased in mild and moderate/severe groups after fluid therapy compared to before fluid administration. While the mean rate of heart rate, blood urea nitrogen (BUN), creatinine, and uric acid values were higher in the moderate/severe group, potassium and HCO3 were lower. There was no significant change in AO diameter and IVC–CI after fluid therapy in all groups. When the factors affecting the IVC/AOs ratio were analyzed with the logistic regression backward model; the IVC/AO ratio was found to increase as the degree of dehydration decreased (Adj.β = −0.318) and as the age (Adj.β = 0.242) and CRP (Adj.β = 0.186) value increased. Conclusion. The IVC/AO ratio can be a promising index for the assessment and grading of dehydration in children, and cutoff values that vary according to age are necessary for a more objective assessment of dehydration.
The Construction of University English Translation Teaching Model Based on Fuzzy Comprehensive Assessment
Authors: Li Zhe
Published: August 2022

With the deepening of economic globalization, the communication between countries is getting closer and closer. The common topic of communication between people of different cultures and environments is English. Since the country has established English as a subject, the importance of English has become one of the main factors for the all-round development of students. In recent years, higher vocational education in China has once again developed towards high quality, all-round diversification, and innovation. According to the continuous reform and innovation and independent innovation, college English has been proved to be an important part of higher vocational education and an important measure to promote the development trend of higher vocational education all over the country. With the progress of science and technology and the development of economy, the level of education in China is still improving. People have put forward stronger teaching standards and regulations for English, a course with strong adaptability and practicality. Part of Chinese translation in college English shows its comprehensive ability and high-level thinking ability. In order to integrate this trend, this paper proposes the formulation and use of college English translation teaching model. The experiment proves that the accuracy of the traditional fuzzy evaluation method in the comment module design of college English translation teaching mode is low, only 82% at most. In order to solve this problem, BP optimization algorithm is introduced. The precision and reliability of BP optimization algorithm are improved. Because of the learning effect of the college English translation teaching mode based on the fuzzy evaluation BP optimization algorithm proposed in the certification paper, the certification is carried out according to the questionnaire and the final evaluation method. The students’ satisfaction and favoritism at the assessment level and the final results of their classmates have proved the proposed college English translation teaching model. The article has excellent learning effect.
Analysis and Prediction of Cross-Border e-Commerce Scale of China Based on the Machine Learning Model
Authors: Chen Qiaoping
Published: August 2022

In the context of the rapid development of Internet technology, the integration of the world economy has been strengthened, and the continuous innovation of technology and foreign trade business forms has promoted the rapid development of cross-border e-commerce. Due to the lack of relevant data on cross-border logistics empirical research, this paper conducts a prediction study on the scale of China’s cross-border e-commerce market based on machine learning models and combines the relevant financial reports of listed companies to determine the proportion of performance costs to turnover. Forecast of the scale of cross-border e-commerce in China. Combined with the total economic volume, industrial structure, domestic and foreign trade, online shopping development, people’s life, and express development, the index system is established, and 11 indicators are initially established with reference to the selection principle of indicators. Combined with the research object, multiple regression and gray prediction methods are established. The relevant prediction model is tested, and the established model is tested to ensure the prediction accuracy. The forecast results show that by 2027, the size of China’s cross-border e-commerce market will reach 30.8133 trillion yuan.
Artificial Intelligence of Internet of Things Based on Machine Learning and College Student Management
Authors: Qiu Zhiqi , Han Jiwei
Published: August 2022

Under the background of the development of higher education, according to the characteristics of college student management, after analyzing its background and practical significance, this study constructs an intelligent college student management system of Internet of things based on machine learning. The data volume of the Internet of things is huge, so ensuring the normal and efficient operation of the system is the primary goal. In this study, the data management model of the system is constructed with the help of cyclic neural network in machine learning algorithm to predict the data and optimize the computer program. At the same time, the system data are filled and classified by the k-nearest neighbor model, and the data are trained and simulated by constructing a safe bilstm neural network system. Because the information related to students in the university database involves personal privacy, in order to ensure the security of the system and avoid relevant data leakage, in the judgment standard of configuration error data flow, this study calculates the monitoring abnormal data and loss function through the dark network flow and ip2vec algorithm, so as to establish the system abnormal monitoring model and identify the system error data flow. Finally, it constructs the college student management system and expounds on the basic requirements of the system use cases. After a series of tests of system performance, capacity, and stability, the results meet the basic requirements of system operation, which provides a certain reference for the application of college student management in the future.
Ordinary AV Nodal Reentry Tachycardia-Unusual Ablation: A Case Report and Review of the Literature
Authors: Haertel Franz , Schulze P. Christian , Große Anett , Prochnau Dirk , Surber Ralf
Published: August 2022

A 72-year-old woman was referred to us with typical symptoms of paroxysmal supraventricular tachycardia for electrophysiological diagnostics and catheter ablation. During the first session of catheter ablation, a probing of the right ventricle was not successful. Therefore, an angiography of the central veins was performed. A rare anatomical variation with atresia of the inferior vena cava below the hepatic veins with azygos persistence was detected. The blood of the lower half of the body was drained via the dilated azygos into the superior vena cava; the blood of the liver veins enters into the right atrium directly. By atypical catheter placement over the azygos vein in the right ventricle and coronary sinus, an AV nodal reentry tachycardia (AVNRT) could be confirmed as the mechanism of tachycardia. However, a stable position of the ablation catheter could not be achieved by the femoral approach, so the successful AV node modulation with ablation of the slow pathway was performed via jugular access.