bluuebunny/crossref_metadata_2025 huggingface dataset:
How do people perceive different labels for rotator cuff disease? A content analysis of data collected in a randomised controlled experiment
Authors: Zadro Joshua R , Michaleff Zoe A , O'Keeffe Mary , Ferreira Giovanni E , Haas Romi , Harris Ian A , Buchbinder Rachelle , Maher Christopher G
Published: December 2021

Objectives

Explore how people perceive different labels for rotator cuff disease in terms of words or feelings evoked by the label and treatments they feel are needed.

Setting

We performed a content analysis of qualitative data collected in a six-arm, online randomised controlled experiment.

Participants

1308 people with and without shoulder pain read a vignette describing a patient with rotator cuff disease and were randomised to one of six labels:subacromial impingement syndrome, rotator cuff tear, bursitis, rotator-cuff-related shoulder pain, shoulder sprainandepisode of shoulder pain.

Primary and secondary outcomes

Participants answered two questions (free-text response) about: (1) words or feelings evoked by the label; (2) what treatments they feel are needed. Two researchers iteratively developed coding frameworks to analyse responses.

Results

1308/1626 (80%) complete responses for each question were analysed. Psychological distress (21%), uncertainty (22%), serious condition (15%) and poor prognosis (9%) were most often expressed by those labelled withsubacromial impingement syndrome. For those labelled with arotator cuff tear,psychological distress (13%), serious condition (9%) and poor prognosis (8%) were relatively common, while minor issue was expressed least often compared with the other labels (5%). Treatment/investigation and surgery were common among those labelled with arotator cuff tear(11% and 19%, respectively) andsubacromial impingement syndrome(9% and 10%) compared withbursitis(7% and 5%).

Conclusions

Words or feelings evoked by certain labels for rotator cuff disease and perceived treatment needs may explain why some labels drive management preferences towards surgery and imaging more than others.
Exploring medical students’ perceptions of the challenges and benefits of volunteering in the intensive care unit during the COVID-19 pandemic: a qualitative study
Authors: Ali Aliya , Staunton Marita , Quinn Adam , Treacy Gordon , Kennelly Patrick , Hill Arnold , Sreenan Seamus , Brennan Marian
Published: December 2021

Objectives

In March 2020, the WHO declared SARS-CoV-2 a pandemic. Hospitals across the world faced staff, bed and supply shortages, with some European hospitals calling on medical students to fill the staffing gaps. This study aimed to document the impact of volunteering during the COVID-19 pandemic on students’ professional development, resilience and future perceived career choices.

Design

This is a retrospective, qualitative study of student reflections, using purposive sampling.

The Royal College of Surgeons in Ireland (RCSI) University of Medicine and Health Sciences recruited 26 medical student volunteers to assist in pronation and supination of ventilated patients affected by SARS-CoV-2. These students were invited to complete an anonymous survey based on their experiences as volunteers. Thematic analysis was performed on these written reflections.

Results

The results showed that volunteering during the COVID-19 pandemic developed key skills from RCSI’s medical curriculum, significantly fostered medical students’ resilience and guided their career choices. Major areas of development included communication, teamwork, compassion and altruism, which are not easily developed through the formal curriculum. A further area that was highlighted was the importance of evidence-based health in a pandemic. Finally, our respondents were early stage medical students with limited clinical exposure. Some found the experience difficult to cope with and therefore supports should be established for students volunteering in such a crisis.

Conclusion

These results suggest that clinical exposure is an important driver in developing students’ resilience and that volunteering during a pandemic has multiple benefits to students’ professional development and professional identity formation.
Taming the chaos: NHS professionals’ perspective of using video consulting during COVID-19 in Wales
Authors: Johns Gemma , Khalil Sara , Ogonovsky Mike , Hesseling Markus , Wardhaugh Allan , Phipps Kerrie , Williams Jessica , Whistance Bethan , Ahuja Alka
Published: December 2021

The use of video consulting (VC) in the UK has expanded rapidly during the COVID-19 pandemic. Technology Enabled Care (TEC) Cymru, the Welsh Government and Local Health boards began implementing the National Health Service (NHS) Wales VC Service in March 2020. This has been robustly evaluated on a large-scale All-Wales basis, across a wide range of NHS Wales specialities.

Aims

To understand the early use of VC in Wales from the perspective of NHS professionals using it. NHS professionals were approached by TEC Cymru to provide early data.

Methods

Using an observational study design with descriptive methods including a cross-sectional survey, TEC Cymru captured data on the use, benefits and challenges of VC from NHS professionals in Wales during August and September 2020. This evidence is based on the rapid adoption of VC in Wales, which mirrors that of other nations.

Results

A total of 1256 NHS professionals shared their VC experience. Overall, responses were positive, and professionals expressed optimistic views regarding the use and benefit of VC, even when faced with challenges on occasions.

Conclusions

This study provides evidence of general positivity, acceptance and the success of the VC service in Wales. Future research studies will now be able to explore and evaluate the implementation methods used within this study, and investigate their effectiveness in being able to achieve better outcomes through VC.
Primer on binary logistic regression
Authors: Harris Jenine K
Published: December 2021

Family medicine has traditionally prioritised patient care over research. However, recent recommendations to strengthen family medicine include calls to focus more on research including improving research methods used in the field. Binary logistic regression is one method frequently used in family medicine research to classify, explain or predict the values of some characteristic, behaviour or outcome. The binary logistic regression model relies on assumptions including independent observations, no perfect multicollinearity and linearity. The model produces ORs, which suggest increased, decreased or no change in odds of being in one category of the outcome with an increase in the value of the predictor. Model significance quantifies whether the model is better than the baseline value (ie, the percentage of people with the outcome) at explaining or predicting whether the observed cases in the data set have the outcome. One model fit measure is the count-R2, which is the percentage of observations where the model correctly predicted the outcome variable value. Related to the count-R2are model sensitivity—the percentage of those with the outcome who were correctly predicted to have the outcome—and specificity—the percentage of those without the outcome who were correctly predicted to not have the outcome. Complete model reporting for binary logistic regression includes descriptive statistics, a statement on whether assumptions were checked and met, ORs and CIs for each predictor, overall model significance and overall model fit.
In silico modeling of combination systemic therapy for advanced renal cell carcinoma
Authors: Kotecha Ritesh R , Hsu Dennis J , Lee Chung-Han , Patil Sujata , Voss Martin H
Published: December 2021

Therapeutic combinations of VEGFR tyrosine kinase inhibitor plus immune checkpoint blockade now represent a standard in the first-line management of patients with advanced renal cell carcinoma. Tumor molecular profiling has shown notable heterogeneity when it comes to activation states of relevant pathways, and it is not clear that concurrent pursuit of two mechanisms of action is needed in all patients. Here, we applied an in silico drug model to simulate combination therapy by integrating previously reported findings from individual monotherapy studies. Clinical data was collected from prospective clinical trials of axitinib, cabozantinib, pembrolizumab and nivolumab. Efficacy of two-drug combination regimens (cabozantinib plus nivolumab, and axitinib plus pembrolizumab) was then modeled assuming independent effects of each partner. Reduction in target lesions, objective response rates (ORR), and progression-free survival (PFS) were projected based on previously reported activity of each agent, randomly pairing efficacy data from two source trials for individual patients and including only the superior effect of each pair in the model. In silico results were then contextualized to register phase III studies of these combinations with similar ORR, PFS, and best tumor response. As increasingly complex therapeutic strategies emerge, computational tools like this could help define benchmarks for trial designs and precision medicine efforts. Summary statement: In silico drug modeling provides meaningful insights into the effects of combination immunotherapy for patients with advanced kidney cancer.
CDH1germline mutations in healthy individuals from families with the hereditary diffuse gastric cancer syndrome
Authors: Corso Giovanni , Magnoni Francesca , Massari Giulia , Trovato Cristina Maria , De Scalzi Alessandra Margherita , Vicini Elisa , Bonanni Bernardo , Veronesi Paolo , Galimberti Viviana , Bagnardi Vincenzo
Published: December 2021

The objective of this study was to determining the frequency of different sub-types of pathogenicCDH1germline mutations in healthy and asymptomatic individuals from families with the hereditary diffuse gastric cancer (HDGC) syndrome. Relevant literature dating from 1998 to 2019 was systematically searched for data onCDH1germline mutations. The collected variants were classified according to their subtype into the following classes: missense, non-sense, splicing, insertions and deletions. The χ2test was used to estimate if the difference observed between patients with gastric cancer (GC) and unaffected individuals was statistically significant.CDH1genetic screening data were retrieved for 224 patients with GC and 289 healthy individuals. Among the subjects that had testedCDH1positive, splicing mutations were found in 30.4% of the healthy individuals and in 15.2% of the patients with GC (p=0.0076). Missense mutations were also found to occur in healthy subjects with higher frequency (22.2%) than in GC-affected individuals (18.3%), but the difference was not significant in this case. In families meeting the clinical criteria for the HDGC syndrome,CDH1splicing and missense germline mutations have been reported to occur with higher frequency in healthy subjects than in patients with cancer. This preliminary observation suggests that not all pathogenicCDH1germline mutations confer the same risk of developing GC.
Mobile stroke care expedites intravenous thrombolysis and endovascular thrombectomy
Authors: Bender Matthew T , Mattingly Thomas K , Rahmani Redi , Proper Diana , Burnett Walter A , Burgett Jason L , LEsperance Joshua , Cushman Jeremy T , Pilcher Webster H , Benesch Curtis G , Kelly Adam G , Bhalla Tarun
Published: December 2021

Background

The number of mobile stroke programmes has increased with evidence, showing they expedite intravenous thrombolysis. Outstanding questions include whether time savings extend to patients eligible for endovascular therapy and impact clinical outcomes.

Objective

Our mobile stroke unit (MSU), based at an academic medical centre in upstate New York, launched in October 2018. We reviewed prospective observational data sets over 26 months to identify MSU and non-MSU emergency medical service (EMS) patients who underwent intravenous thrombolysis or endovascular thrombectomy for comparison of angiographic and clinical outcomes.

Results

Over 568 days in service, the MSU was dispatched 1489 times (2.6/day) and transported 300 patients (20% of dispatches). Intravenous tissue plasminogen activator (tPA) was administered to 57 MSU patients and the average time from 911 call-to-tPA was 42.5 min (±9.2), while EMS transported 73 patients who received tPA at 99.4 min (±35.7) (p<0.001). Seven MSU patients (12%) received tPA from 3.5 hours to 4.5 hours since last known well and would likely have been outside the window with EMS care. Endovascular thrombectomy was performed on 21 MSU patients with an average 911 call-to-groin puncture time of 99.9 min (±18.1), while EMS transported 54 patients who underwent endovascular thrombectomy (ET) at 133.0 min (±37.0) (p=0.0002). There was no difference between MSU and traditional EMS in modified Rankin score at 90-day clinic follow-up for patients undergoing intravenous thrombolysis or endovascular thrombectomy, whether assessed as a dichotomous or ordinal variable.

Conclusions

Mobile stroke care expedited both intravenous thrombolysis and endovascular thrombectomy. There is an ongoing need to show improved functional outcomes with MSU care.
Combinatorics of KP hierarchy structural constants
Authors: Andreev A. , Popolitov A. , Sleptsov A. , Zhabin A.
Published: December 2021

We investigate the structural constants of the KP hierarchy, which appear as universal coefficients in the paper of Natanzon–Zabrodin arXiv:1509.04472. It turns out that these constants have a combinatorial description in terms of transport coefficients in the theory of flow networks. Considering its properties we want to point out three novel directions of KP combinatorial structure research: connection with topological recursion, eigenvalue model for the structural constants and its deformations, possible deformations of KP hierarchy in terms of the structural constants. Firstly, in this paper we study the internal structure of these coefficients which involves: (1) construction of generating functions that have interesting properties by themselves; (2) restrictions on topological recursion initial data; (3) construction of integral representation or matrix model for these coefficients with non-trivial Ward identities. This shows that these coefficients appear in various problems of mathematical physics, which increases their value and significance. Secondly, we discuss their role in integrability of KP hierarchy considering possible deformation of these coefficients without changing the equations on $$\tau $$
τ
-function. We consider several plausible deformations. While most failed even very basic checks, one deformation (involving Macdonald polynomials) passes all the simple checks and requires more thorough study.
Cosmic censorship, massless fermionic test fields, and absorption probabilities
Authors: Düztaş Koray
Published: December 2021

In the conventional approach, fermionic test fields lead to a generic overspinning of black holes resulting in the formation of naked singularities. The absorption of the fermionic test fields with arbitrarily low frequencies is allowed for which the contribution to the angular momentum parameter of the space-time diverges. Recently we have suggested a more subtle treatment of the problem considering the fact that only the fraction of the test fields that is absorbed by the black hole contributes to the space-time parameters. Here, we re-consider the interaction of massless spin (1/2) fields with Kerr and Kerr–Newman black holes, adapting this new approach. We show that the drastic divergence problem disappears when one incorporates the absorption probabilities. Still, there exists a range of parameters for the test fields that can lead to overspinning. We employ backreaction effects due to the self-energy of the test fields which fixes the overspinning problem for fields with relatively large amplitudes, and renders it non-generic for smaller amplitudes. This non-generic overspinning appears likely to be fixed by alternative semi-classical and quantum effects.
Reconstruction of DBI-essence dark energy with f(R) gravity and its effect on black hole and wormhole mass accretion
Authors: Kar Alokananda , Sadhukhan Shouvik , Debnath Ujjal
Published: December 2021

In this paper, we have used the reconstructed Dirac–Born–Infeld (DBI)-essence dark energy density to modify the mass accretions of black holes and wormholes. In general, the black hole mass accretion does not depend on the metric or local Einstein geometry. That is why we have used a generalized mechanism by reconstructing the DBI-essence dark energy reconstruction with [Formula: see text] gravity. We have used some particular forms of the scale factor to analyze the accretion phenomena. We have shown the effect of cosmic evolution in the proper time variation of black hole mass accretion. Finally, we have studied the validity of energy conditions and analyzed the Type I–IV singularities for our reconstructed model.
Remarks on SUq (2) fermions
Authors: Smaldone L.
Published: December 2021

In this paper, we show that several applications of [Formula: see text] fermions to statistical mechanics and quantum field theory, previously discussed in literature, are based on a wrong statement about the connection between deformed and undeformed fermion operators. Then we exclude various classes of ansatz and we put some constraints about the form of such relation.
China’s Energy Financing in Southeast Asia: Examining Its Public Goods Approach
Authors: GONG Xue
Published: December 2021

This article aims to assess the motivations, modifications and impacts of China’s public goods approach by studying its energy financing in Southeast Asia. It argues that China’s public goods approach of energy financing will help improve financing performance through sustainable development and multilateral cooperation. However, the approach is constrained by the lack of trust from the region, incompatible standards between China and other Western practices, and growing securitisation by the United States on Chinese economic activities.
Hong Kong Special Administrative Region after the National Security Legislation: Prospects and Challenges
Authors: TEO Victor
Published: December 2021

The National Security Law has unequivocally clarified that Hong Kong’s “autonomy” is a bestowed privilege rather than an absolute political right. While effective in stabilising Hong Kong politics, the Law has also effectively rolled back democratisation and raised a number of serious questions about Hong Kong’s future. Going forward, the Hong Kong Special Administrative Region faces a difficult task of maintaining its unique identity, lifestyle and exceptionalism as a truly global city while attempting to align with China’s plans and interests.
Fake News Classification: A Quantitative Research Description
Authors: Jain Rachna , Jain Deepak Kumar , Dharana  , Sharma Nitika
Published: December 2021

Social media can render content circulating to reach millions with a knack to influence people, despite the questionable authencity of the facts. Internet sources are the most convenient and easy approach to obtain any information these days. Fake news has become the topic of interest for academicians and the rest of society. This kind of propaganda has the power to influence the general perception, offering political groups the ability to control the results of democratic affairs such as elections. Automatic identification of fake news has emerged as one of the significant problems due to the high risks involved. It is challenging in a way because of the complexity levels of accurately interpreting the data. An extensive search has already been performed on English language news data. Our work presents a comparative analysis of fake news classifiers on the low resource Bengali language ‘ban fake news’ dataset from Kaggle. The analysis presented compares deep learning techniques such as
LSTM (Long short-term Memory)
and
BiLSTM (Bi-directional Long short-term Memory)
and machine learning methods like Naive Bayes,
Passive Aggressive Classifier (PAC),
and Random Forest. The comparison has been drawn based on classification metrics such as accuracy, precision, recall, and F1 score. The deep learning method BiLSTM shows 55.92% accuracy while Random Forest, in contrast, has outperformed all the other methods with an accuracy of 62.37%. The work presented in this paper sets a basis for researchers to select the optimum classifiers for their approach towards fake news detection.
Instant Basketball Defensive Trajectory Generation
Authors: Chen Wen-Cheng , Tsai Wan-Lun , Chang Huan-Hua , Hu Min-Chun , Chu Wei-Ta
Published: December 2021

Tactic learning in virtual reality (VR) has been proven to be effective for basketball training. Endowed with the ability of generating virtual defenders in real time according to the movement of virtual offenders controlled by the user, a VR basketball training system can bring more immersive and realistic experiences for the trainee. In this article, an autoregressive generative model for instantly producing basketball defensive trajectory is introduced. We further focus on the issue of preserving the diversity of the generated trajectories. A differentiable sampling mechanism is adopted to learn the continuous Gaussian distribution of player position. Moreover, several heuristic loss functions based on the domain knowledge of basketball are designed to make the generated trajectories assemble real situations in basketball games. We compare the proposed method with the state-of-the-art works in terms of both objective and subjective manners. The objective manner compares the average position, velocity, and acceleration of the generated defensive trajectories with the real ones to evaluate the fidelity of the results. In addition, more high-level aspects such as the empty space for offender and the defensive pressure of the generated trajectory are also considered in the objective evaluation. As for the subjective manner, visual comparison questionnaires on the proposed and other methods are thoroughly conducted. The experimental results show that the proposed method can achieve better performance than previous basketball defensive trajectory generation works in terms of different evaluation metrics.
Exploring the Risky Travel Area and Behavior of Car-hailing Service
Authors: Niu Hongting , Zhu Hengshu , Sun Ying , Lu Xinjiang , Sun Jing , Zhao Zhiyuan , Xiong Hui , Lang Bo
Published: December 2021

Recent years have witnessed the rapid development of car-hailing services, which provide a convenient approach for connecting passengers and local drivers using their personal vehicles. At the same time, the concern on passenger safety has gradually emerged and attracted more and more attention. While car-hailing service providers have made considerable efforts on developing real-time trajectory tracking systems and alarm mechanisms, most of them only focus on providing rescue-supporting information rather than preventing potential crimes. Recently, the newly available large-scale car-hailing order data have provided an unparalleled chance for researchers to explore the risky travel area and behavior of car-hailing services, which can be used for building an intelligent crime early warning system. To this end, in this article, we propose a Risky Area and Risky Behavior Evaluation System (RARBEs) based on the real-world car-hailing order data. In RARBEs, we first mine massive multi-source urban data and train an effective area risk prediction model, which estimates area risk at the urban block level. Then, we propose a transverse and longitudinal double detection method, which estimates behavior risk based on two aspects, including fraud trajectory recognition and fraud patterns mining. In particular, we creatively propose a bipartite graph-based algorithm to model the implicit relationship between areas and behaviors, which collaboratively adjusts area risk and behavior risk estimation based on random walk regularization. Finally, extensive experiments on multi-source real-world urban data clearly validate the effectiveness and efficiency of our system.
Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: a review from VascAgeNet
Authors: Charlton Peter H. , Paliakaitė Birutė , Pilt Kristjan , Bachler Martin , Zanelli Serena , Kulin Dániel , Allen John , Hallab Magid , Bianchini Elisabetta , Mayer Christopher C. , Terentes-Printzios Dimitrios , Dittrich Verena , Hametner Bernhard , Veerasingam Dave , Žikić Dejan , Marozas Vaidotas
Published: December 2021

The photoplethysmogram (PPG) signal is widely measured by clinical and consumer devices, and it is emerging as a potential tool for assessing vascular age. The shape and timing of the PPG pulse wave are both influenced by normal vascular aging, changes in arterial stiffness and blood pressure, and atherosclerosis. This review summarizes research into assessing vascular age from the PPG. Three categories of approaches are described: 1) those which use a single PPG signal (based on pulse wave analysis), 2) those which use multiple PPG signals (such as pulse transit time measurement), and 3) those which use PPG and other signals (such as pulse arrival time measurement). Evidence is then presented on the performance, repeatability and reproducibility, and clinical utility of PPG-derived parameters of vascular age. Finally, the review outlines key directions for future research to realize the full potential of photoplethysmography for assessing vascular age.
Luseogliflozin, a sodium-glucose cotransporter-2 inhibitor, reverses cerebrovascular dysfunction and cognitive impairments in 18-mo-old diabetic animals
Authors: Wang Shaoxun , Jiao Feng , Border Jane J. , Fang Xing , Crumpler Reece F. , Liu Yedan , Zhang Huawei , Jefferson Joshua , Guo Ya , Elliott Parker S. , Thomas Kirby N. , Strong Luke B. , Urvina Austin H. , Zheng Baoying , Rijal Arjun , Smith Stanley V. , Yu Hongwei , Roman Richard J. , Fan Fan
Published: December 2021

This study demonstrates that luseogliflozin, a sodium-glucose cotransporter-2 inhibitor, improved CBF autoregulation in association with reduced vascular oxidative stress and AGEs production in the cerebrovasculature of 18-mo-old DM rats. SGLT2i also prevented BBB leakage, impaired functional hyperemia, neurodegeneration, and cognitive impairment seen in DM rats. Luseogliflozin did not have direct constrictive effects on VSMCs and MCAs isolated from normal rats. These results provide evidence that normalization of hyperglycemia with an SGLT2i can reverse cerebrovascular dysfunction and cognitive impairments in rats with long-standing hyperglycemia, possibly by ameliorating oxidative stress-caused vascular damage.
Optimization and Design of Hammerheads and Fenders on Scrap Metal Shredders Based on Improved Genetic Algorithm
Authors: Tian He , Wang Guoqiang , Sun Kangkang , Chen Zeren , Yan Chuliang , Cui Da
Published: December 2021

Dynamic unbalance force is an important factor affecting the service life of scrap metal shredders (SMSs) as the product of mass error. Due to the complexity of hammerheads arrangement, it is difficult to take all the parts of the hammerhead into account in the traditional methods. A novel optimization algorithm combining genetic algorithm and simulated annealing algorithm is proposed to improve the dynamic balance of scrap metal shredders. The optimization of hammerheads and fenders on SMS in this paper is considered as a multiple traveling salesman problem (MTSP), which is a kind of NP‐hard problem. To solve this problem, an improved genetic algorithm (IGA) combined with the global optimization characteristics of genetic algorithm (GA) and the local optimal solution of simulated annealing algorithm (SA) is proposed in this paper, which adopts SA in the process of selecting subpopulations. The optimization results show that the resultant force of the shredder central shaft by using IGA is less than the traditional metaheuristic algorithm, which greatly improves the dynamic balance of the SMS. Validated via ADAMS simulation, the results are in good agreement with the theoretical optimization analysis.
A Multi-Scenario Optimization Model for Emergency Cold Chain Logistics Distribution
Authors: Ba Yile , Feng Chenxi , Jia Wenpeng , Liu Xin , Ren Jianwei
Published: December 2021

Cold chain logistics has been playing a more and more crucial role in modern society. As a special professional cold chain logistics, emergency cold chain logistics can provide quality assurance for temperature-sensitive products in emergency situations. Due to the fact that demand is uncertain in emergency situations, the cold chain logistics companies have to deal with the issue of uncertainty. However, there is no literature on the emergency cold chain logistics distribution optimization problem with uncertain demand. This research contributes to solving this problem. To deal with uncertain demand in emergency situations, an emergency cold chain logistics distribution optimization model with time windows is proposed based on scenario analysis. The objectives of the model are to minimize the total cost and shorten the delivery time simultaneously. The model can also optimize product procurement and refrigerated vehicle renting. The multi-scenario optimization model is applied to a Chinese cold chain logistics center to verify its effectiveness.
Construction and Application of Tennis Teaching Digital Resources Based on Deep Learning
Authors: Zhao Tingting
Published: December 2021

Tennis teaching is an important part of traditional physical education in China. It aims to cultivate students’ lifelong exercise habits, improve learning efficiency, and promote social development. Therefore, based on the concepts of deep learning and digital resource construction, this paper proposes the course structure design. This paper first describes the current situation of tennis teaching, then studies the relevant content of deep learning, and discusses the most commonly used neural network algorithm in the field of deep learning. Then, using the research method of the questionnaire survey, combined with the digital teaching mode, the teaching of Chinese college students tennis group research, and compared with the traditional teaching mode. The results showed that the experimental group (EP) learned more balanced technical movements than the control group (CP). The teaching effect of digital resource tennis course is better than conventional teaching, which shows that digital resource tennis course can master students’ skills better than conventional teaching. Therefore, the construction of digital resources based on deep learning can improve students’ tennis technology and stimulate students’ interest in tennis.
Genetic Diversity, Antimicrobial Resistance Pattern, and Biofilm Formation in Klebsiella pneumoniae Isolated from Patients with Coronavirus Disease 2019 (COVID‐19) and Ventilator‐Associated Pneumonia
Authors: Ghanizadeh Asma , Najafizade Maede , Rashki Somaye , Marzhoseyni Zeynab , Motallebi Mitra
Published: December 2021

Introduction. Patients with acute respiratory distress syndrome caused by coronavirus disease 2019 (COVID‐19) are at risk for superadded infections, especially infections caused by multidrug resistant (MDR) pathogens. Before the COVID‐19 pandemic, the prevalence of MDR infections, including infections caused by MDR Klebsiella pneumoniae (K. pneumoniae), was very high in Iran. This study is aimed at assessing the genetic diversity, antimicrobial resistance pattern, and biofilm formation in K. pneumoniae isolates obtained from patients with COVID‐19 and ventilator‐associated pneumonia (VAP) hospitalized in an intensive care unit (ICU) in Iran. Methods. In this cross‐sectional study, seventy K. pneumoniae isolates were obtained from seventy patients with COVID‐19 hospitalized in the ICU of Shahid Beheshti hospital, Kashan, Iran, from May to September, 2020. K. pneumoniae was detected through the ureD gene. Antimicrobial susceptibility testing was done using the Kirby‐Bauer disc diffusion method, and biofilm was detected using the microtiter plate assay method. Genetic diversity was also analyzed through polymerase chain reaction based on enterobacterial repetitive intergenic consensus (ERIC‐PCR). The BioNumerics software (v. 8.0, Applied Maths, Belgium) was used for analyzing the data and drawing dendrogram and minimum spanning tree. Findings. K. pneumoniae isolates had varying levels of resistance to antibiotics meropenem (80.4%), cefepime‐aztreonam‐piperacillin/tazobactam (70%), tobramycin (61.4%), ciprofloxacin (57.7%), gentamicin (55.7%), and imipenem (50%). Around 77.14% of isolates were MDR, and 42.8% of them formed biofilm. Genetic diversity analysis revealed 28 genotypes (E1–E28) and 74.28% of isolates were grouped into ten clusters (i.e., clusters A–J). Clusters were further categorized into three major clusters, i.e., clusters E, H, and J. Antimicrobial resistance to meropenem, tobramycin, gentamicin, and ciprofloxacin in cluster J was significantly higher than cluster H, denoting significant relationship between ERIC clusters and antimicrobial resistance. However, there was no significant difference among major clusters E, H, and J respecting biofilm formation. Conclusion. K. pneumoniae isolates obtained from patients with COVID‐19 have high antimicrobial resistance, and 44.2% of them have genetic similarity and can be clustered in three major clusters. There is a significant difference among clusters respecting antimicrobial resistance.
Internet of Things Supervision System and Supply Chain Financial Supervision Methods Based on Blockchain Technology
Authors: Zhang Jun
Published: December 2021

With the continuous progress of blockchain technology, how to use it for commodity traceability has become a concern. This study mainly discusses the Internet of Things supervision system and supply chain financial supervision method based on blockchain technology. The whole blockchain network is a decentralized system, which consists of six layers: data layer, network layer, and consensus layer. These three layers are the foundation layer; the other three layers are incentive layer, contract layer, and application layer. The interface of the platform needs to be conceived in combination with the business of building materials. According to the functional differentiation, the required interfaces mainly include information generation interface, information verification, information retrieval, and other information interfaces. Smart contracts can process data, operate asset transactions, manage smart assets, and expand the ability of blockchain to use data. In this way, the blockchain technology can trace the source of the data, so as to ensure the authenticity and security of the data. Blockchain technology can be used in data tracking. Specifically, in the building materials industry, with the help of blockchain technology, building material mixing enterprises can see the raw materials such as sand and gravel purchased under the order, the region where they are produced, the time point of transportation, the carrier, etc. In the process of supply chain financial supervision experiment, when the pledge rate of building materials is within the range of [0.4206,1], the bank income under the block chain mode is higher. The system designed in this study realizes the certification and traceability of building materials and has good use value.
Research on Hysteresis Modeling and Compensation Method of Giant Magnetostrictive Force Sensor
Authors: Wang Chuanli , Shi Rui , Yu Caofeng , Chen Zhuo , Wang Yu
Published: December 2021

Linearity is an important index for evaluating the performance of various sensors. Under the Villari effect, there may be some hysteresis between the input force and the output voltage of a force sensor, meaning that the output will be multivalued and nonlinear. To improve the linearity and eliminate the hysteresis of such sensors, an output compensation method using a variable bias current is proposed based on the bidirectional energy conversion mechanism of giant magnetostrictive material. First, the magnetization relationship between the input force, bias current, and flux density is established. Second, a nonlinear neural network model of the force‐magnetization hysteresis and a neural network model for the compensation control of the force sensor are established. These models are trained using the magnetic flux density‐force curve and the magnetic flux density‐current curve, respectively. Taking the optimal linearity as the objective function, the bias current under different input forces is optimized. Finally, a bias current control system is developed and an experimental test platform is built to verify the proposed method. The results show that the proposed variable bias current hysteresis compensation method enables the linearity under the return of the force sensor to reach 1.6%, which is around 48.3% higher than under previous methods. Thus, the proposed variable bias current method effectively suppresses the hysteresis phenomenon and provides improved linearity for giant magnetostrictive force sensors.
Computer‐Aided Diagnostics of Heart Disease Risk Prediction Using Boosting Support Vector Machine
Authors: Owusu Ebenezer , Boakye-Sekyerehene Prince , Appati Justice Kwame , Ludu Julius Yaw
Published: December 2021

Heart diseases are a leading cause of death worldwide, and they have sparked a lot of interest in the scientific community. Because of the high number of impulsive deaths associated with it, early detection is critical. This study proposes a boosting Support Vector Machine (SVM) technique as the backbone of computer‐aided diagnostic tools for more accurately forecasting heart disease risk levels. The datasets which contain 13 attributes such as gender, age, blood pressure, and chest pain are taken from the Cleveland clinic. In total, there were 303 records with 6 tuples having missing values. To clean the data, we deleted the 6 missing records through the listwise technique. The size of data, and the fact that it is a purely random subset, made this approach have no significant effect for the experiment because there were no biases. Salient features are selected using the boosting technique to speed up and improve accuracies. Using the train/test split approach, the data is then partitioned into training and testing. SVM is then used to train and test the data. The C parameter is set at 0.05 and the linear kernel function is used. Logistic regression, Nave Bayes, decision trees, Multilayer Perceptron, and random forest were used to compare the results. The proposed boosting SVM performed exceptionally well, making it a better tool than the existing techniques.
Study on the Effects of Powder‐Liquid Ratio and Cement Ratio on Mechanical Properties and Microscopic Characteristics of Polymer‐Cement Composite
Authors: Huang Zhe , Xu Jinyu , Leng Binglin , Ren Weibo , Chang Sen , Wang Zhihang , Xia Wei
Published: December 2021

This paper is about a study on the mechanical properties of a new polymer‐cement composite (PCC) in constant elongation, tension, and shear. The study explored the effects of powder‐liquid ratio and cement ratio on the mechanical properties of PCC through detecting the strength, deformation, and energy consumption of specimens under different powder‐liquid ratios and cement ratios. In addition, scanning electron microscope and mercury injection apparatus were used for an in‐depth analysis on the micromorphology and pore structure features of PCC under different powder‐liquid ratios and cement ratios to explore the influence of powder‐liquid ratio and cement ratio of the micromechanical properties of PCC. The results showed that, with the increase of powder‐liquid ratio and cement ratio, the constant elongation adhesion strength of PCC decreased, and, at a high powder‐liquid ratio (0.55) or a high cement ratio (0.5), the constant elongation adhesion strength of PCC completely disappeared. Meanwhile, with the increase of powder‐liquid ratio and cement ratio, the tensile shear strength of PCC increased, while the deformation capacity of PCC decreased. The optimal ranges of powder‐liquid ratio and cement ratio for PCC were 0.35–0.4 and 0.3‐0.4, respectively. Furthermore, the increased powder‐liquid ratio and cement ratio made the total pore volume decreased and pore structure refined, which improved the compactness of PCC, thus influencing the performance of PCC macroscopically. An achievement for the study is a flexible composite material, which was formulated with the polymer film as continuous base phase, as well as the inorganic composition and cement hydrates as dispersion phase. The material can effectively improve the economy and practicability of cementation of fissures for airfield pavement.
Variational Quantum Circuit-Based Reinforcement Learning for POMDP and Experimental Implementation
Authors: Kimura Tomoaki , Shiba Kodai , Chen Chih-Chieh , Sogabe Masaru , Sakamoto Katsuyoshi , Sogabe Tomah
Published: December 2021

Variational quantum circuit is proposed for applications in supervised learning and reinforcement learning to harness potential quantum advantage. However, many practical applications in robotics and time-series analysis are in partially observable environment. In this work, we propose an algorithm based on variational quantum circuits for reinforcement learning under partially observable environment. Simulations suggest learning advantage over several classical counterparts. The learned parameters are then tested on IBMQ systems to demonstrate the applicability of our approach for real-machine-based predictions.
The Effect and Mechanism of Exercise Training on Rats with Poststroke Depression Based on the Intestinal Flora
Authors: Yang Jiaen , Zhou Guangjin , Ou Zixuan , Jia Ning , Wang Dong
Published: December 2021

Depression of poststroke depression (PSD) is the most common neuropsychiatric complication after stroke. Patients with PSD had higher mortality, more cognitive disorder, lower quality of life, and higher suicidal tendency. The pathogenesis of PSD mainly involves neurotransmitter inflammatory factors, HPA and BDNF. Enteral dysfunction and intestinal flora disorders caused by stroke can participate in the pathogenesis of PSD through various ways, such as immune, endocrine, and nervous system. In this experiment, we used exercise training as an intervention means to explore the curative effect and possible mechanism by observing the changes of behavior, inflammatory factors, and intestinal flora in rats. The results show that the mechanism of exercise training to improve the depressive behavior of rats may be related to inhibiting the expression of proinflammatory factors and increasing the number of lactic acid bacteria in the intestine.
A Surface Family with a Common Asymptotic Null Curve in Minkowski 3-Space

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Authors: Alluhaibi Nadia , Abdel-Baky Rashad A.
Published: December 2021

This approach is on constructing a surface family with a common asymptotic null curve. It has provided the necessary and sufficient condition for the curve to be an asymptotic null curve and extended the study to ruled and developable surfaces. Subsequently, the study has examined the Bertrand offsets of a surface family with a common asymptotic null curve. Lastly, we support the results of this approach by some examples.
Treatment of Radiation‐Induced Brain Necrosis
Authors: Yang Xiaojing , Ren Hanru , Fu Jie
Published: December 2021

Radiation‐induced brain necrosis (RBN) is a serious complication of intracranial as well as skull base tumors after radiotherapy. In the past, due to the lack of effective treatment, radiation brain necrosis was considered to be progressive and irreversible. With better understanding in histopathology and neuroimaging, the occurrence and development of RBN have been gradually clarified, and new treatment methods are constantly emerging. In recent years, some scholars have tried to treat RBN with bevacizumab, nerve growth factor, and gangliosides and have achieved similar results. Some cases of brain necrosis can be repairable and reversible. We aimed to summarize the incidence, pathogenesis, and treatment of RBN.
Nanomaterial by Sol‐Gel Method: Synthesis and Application
Authors: Bokov Dmitry , Turki Jalil Abduladheem , Chupradit Supat , Suksatan Wanich , Javed Ansari Mohammad , Shewael Iman H. , Valiev Gabdrakhman H. , Kianfar Ehsan
Published: December 2021

The sol‐gel process is a more chemical method (wet chemical method) for the synthesis of various nanostructures, especially metal oxide nanoparticles. In this method, the molecular precursor (usually metal alkoxide) is dissolved in water or alcohol and converted to gel by heating and stirring by hydrolysis/alcoholysis. Since the gel obtained from the hydrolysis/alcoholysis process is wet or damp, it should be dried using appropriate methods depending on the desired properties and application of the gel. For example, if it is an alcoholic solution, the drying process is done by burning alcohol. After the drying stage, the produced gels are powdered and then calcined. The sol‐gel method is a cost‐effective method and due to the low reaction temperature there is good control over the chemical composition of the products. The sol‐gel method can be used in the process of making ceramics as a molding material and can be used as an intermediate between thin films of metal oxides in various applications. The materials obtained from the sol‐gel method are used in various optical, electronic, energy, surface engineering, biosensors, and pharmaceutical and separation technologies (such as chromatography). The sol‐gel method is a conventional and industrial method for the synthesis of nanoparticles with different chemical composition. The basis of the sol‐gel method is the production of a homogeneous sol from the precursors and its conversion into a gel. The solvent in the gel is then removed from the gel structure and the remaining gel is dried. The properties of the dried gel depend significantly on the drying method. In other words, the “removing solvent method” is selected according to the application in which the gel will be used. Dried gels in various ways are used in industries such as surface coating, building insulation, and the production of special clothing. It is worth mentioning that, by grinding the gel by special mills, it is possible to achieve nanoparticles.