bluuebunny/crossref_metadata_2025 huggingface dataset:
Concurrent chemoradiation and brachytherapy alone or in combination with nelfinavir in locally advanced cervical cancer (NELCER): study protocol for a phase III trial
Authors: Chopra Supriya , Goda Jayant Sastri , Mittal Prachi , Mulani Jaahid , Pant Sidharth , Pai Venkatesh , Kannan Sadhna , Deodhar Kedar , Krishnamurthy Manjunath Nookala , Menon Santosh , Charnalia Mayuri , Shah Sneha , Rangarajan Venkatesh , Gota Vikram , Naidu Lavanya , Sawant Sheela , Thakkar Praffula , Popat Palak , Ghosh Jaya , Rath Sushmita , Gulia Seema , Engineer Reena , Mahantshetty Umesh , Gupta Sudeep
Published: May 2022

Introduction

In locally advanced cervical cancer, nodal, local and distant relapse continue to be significant patterns of relapse. Therefore, strategies to improve the efficacy of chemoradiation are desirable such as biological pathway modifiers and immunomodulating agents. This trial will investigate the impact of nelfinavir, a protease inhibitor that targets the protein kinase B (AKT) pathway on disease-free survival (DFS).

Methods and analysis

Radiosensitising effect of nelfinavir in locally advanced carcinoma of cervix is a single-centre, open-label, parallel-group, 1:1 randomised phase-III study. Patients aged over 18 years with a diagnosis of carcinoma cervix stage III are eligible for the study. After consenting, patients will undergo randomisation to chemoradiation and brachytherapy arm or nelfinavir with chemoradiation and brachytherapy arm. The primary aim of the study is to compare the difference in 3-year DFS between the two arms. Secondary aims are locoregional control, overall survival, toxicity and quality of life between the two arms. Pharmacokinetics of nelfinavir and its impact on tumour AKT, programmed cell death ligand 1, cluster of differentiation 4, cluster of differentiation 8 and natural killer 1.1 expression will be investigated. The overall sample size of 348 with 1 planned interim analysis achieves 80% power at a 0.05 significance level to detect a HR of 0.66 when the proportion surviving in the control arm is 0.65. The planned study duration is 8 years.

Ethics and dissemination

The trial is approved by the Institutional Ethics Committee-I of Tata Memorial Hospital, Mumbai (reference number: IEC/0317/1543/001) and will be monitored by the data safety monitoring committee. The study results will be disseminated via peer-reviewed scientific journals, and conference presentations. Study participants will be accrued after obtaining written informed consent from them. The confidentiality and privacy of study participants will be maintained.

Trial registration number

The trial is registered with Clinical Trials Registry-India (CTRI/2017/08/009265) and ClinicalTrials.gov (NCT03256916).
Assessment of COVID-19 pandemic responses in African countries: thematic synthesis of WHO intra-action review reports
Authors: Talisuna Ambrose , Iwu Chinwe , Okeibunor J , Stephen Mary , Musa Emmanuel Onuche , Herring Belinda Louise , Ramadan Otim Patrick Cossy , Yota Daniel , Nanyunja Miriam , Mpairwe Allan , Banza Freddy Mutoka , Diallo Amadou Bailo , Wango Roland Kimbi , Massidi Christian , Njenge Hilary Kagume , Traore Martin , Oke Antonio , Bonkoungou Boukare , Mayigane Landry Ndriko , Conteh Ishata Nannie , Senait Fekadu , Chungong Stella , Impouma Benido , Ngoy Nsenga , Wiysonge Charles Shey , Yoti Zabulon , Gueye Abdou Salam
Published: May 2022

Objectives

We conducted a review of intra-action review (IAR) reports of the national response to the COVID-19 pandemic in Africa. We highlight best practices and challenges and offer perspectives for the future.

Design

A thematic analysis across 10 preparedness and response domains, namely, governance, leadership, and coordination; planning and monitoring; risk communication and community engagement; surveillance, rapid response, and case investigation; infection prevention and control; case management; screening and monitoring at points of entry; national laboratory system; logistics and supply chain management; and maintaining essential health services during the COVID-19 pandemic.

Setting

All countries in the WHO African Region were eligible for inclusion in the study. National IAR reports submitted by March 2021 were analysed.

Results

We retrieved IAR reports from 18 African countries. The COVID-19 pandemic response in African countries has relied on many existing response systems such as laboratory systems, surveillance systems for previous outbreaks of highly infectious diseases and a logistics management information system. These best practices were backed by strong political will. The key challenges included low public confidence in governments, inadequate adherence to infection prevention and control measures, shortages of personal protective equipment, inadequate laboratory capacity, inadequate contact tracing, poor supply chain and logistics management systems, and lack of training of key personnel at national and subnational levels.

Conclusion

These findings suggest that African countries’ response to the COVID-19 pandemic was prompt and may have contributed to the lower cases and deaths in the region compared with countries in other regions. The IARs demonstrate that many technical areas still require immediate improvement to guide decisions in subsequent waves or future outbreaks.
Impact of aeroplane noise on mental and physical health: a quasi-experimental analysis
Authors: Wang Scarlett Sijia , Glied Sherry , Williams Sharifa , Will Brian , Muennig Peter Alexander
Published: May 2022

Objectives

Historically, departures at New York City’s LaGuardia airport flew over a large sports complex within a park. During the US Open tennis games, flights were diverted to fly over a heavily populated foreign-born neighbourhood for roughly 2 weeks out of the year so that the tennis match was not disturbed (the ‘TNNIS’ departure). In 2012, the use of the TNNIS departure became year-round to better optimise flight patterns around the metropolitan area.

Methods

We exploited exogenously induced spatial and temporal variation in flight patterns to examine difference-in-difference effects of this new exposure to aircraft noise on the health of individual residents in the community relative to individuals residing within a demographically similar community that was not impacted. We used individual-level Medicaid records, focusing on conditions associated with noise: sleep disturbance, psychological stress, mental illness, substance use, and cardiovascular disease.

Results

We found that increased exposure to aeroplane noise was associated with a significant increase in insomnia across all age groups, but particularly in children ages 5–17 (OR=1.64, 95% CI=1.12 to 2.39). Cardiovascular disease increased significantly both among 18–44-year-old (OR=1.45, 95% CI=1.41 to 1.49) and 45–64-year-old Medicaid recipients (OR=1.15, 95% CI=1.07 to 1.25). Substance use and mental health-related emergency department visits also increased. For ages 5–17,rate ratio (RR) was 4.11 (95% CI=3.28 to 5.16); for ages 18–44, RR was 2.46 (95% CI=2.20 to 2.76); and for ages 45–64, RR was 1.48 (95% CI=1.31 to 1.67).

Conclusion

We find that increased exposure to aeroplane noise was associated with an increase in diagnosis of cardiovascular disease, substance use/mental health emergencies and insomnia among local residents.
Optimising the treatment for uncomplicated acute appendicitis (OPTIMA trial): a protocol for a multicentre, randomised, double-blinded placebo-controlled study
Authors: Wu Jie , Jiang Haiyang , Li Shikuan , Wu Xiuwen , Wang Peige , Sawyer Robert , Ren Jianan
Published: May 2022

Introduction

Emerging evidence has shown that an antibiotic first strategy is a viable treatment option for uncomplicated acute appendicitis (AA). Although there has recently been an interest and increase in the use of antibiotics as the primary strategy for treating uncomplicated AA, there is no consensus regarding the optimum antibiotic regimen. In particular, the long-term outcomes of different antibiotic regimens, such as the recurrence rate, still lack evidence. Given that the flora of the appendix is mainly anaerobic bacteria, we hypothesised that antianaerobe regimens could decrease the recurrence rate compared with those that did not include antianaerobic antibiotics.

Methods and analysis

The OPTIMA(Optimising the treatment for uncomplicated acute appendicitis) trial is a multicentre, double-blinded placebo-controlled superiority randomised study aimed to evaluate the role of antianaerobic antibiotics in the resolution of uncomplicated AA. Patients (18–65 years) with uncomplicated AA (without gangrenous, perforated appendicitis, appendiceal abscess, or appendiceal fecaliths) are eligible for inclusion. The primary endpoint of this study is the success rate of the treatment, defined as the resolution of AA resulting in discharge from the hospital without surgical intervention and recurrent symptoms within one year. Secondary endpoints include mortality, postintervention complications, recurrent symptoms up to one year after treatment, hospital stay, sick leave, treatment cost, pain symptom scores and quality of life. Data are reported as the number of cases (%), median (range) and relative risk, which will be analysed using the Mann-Whitney U test or χ2 test, as appropriate. P-value<0.05 will be considered significant.

Ethics and dissemination

The protocol has been approved by the Ethics Committee of Jinling Hospital on 13 November 2018 (2018NZKY-027-01). The trial findings will be published in peer-reviewed journals.

Trial registration number

ChiCTR1800018896.
Contribution of an extensive medication-based comorbidity index (Rx-Risk) in explaining the excess mortality after hip fracture in older Norwegians: a NOREPOS cohort study
Authors: Holvik Kristin , Hjellvik Vidar , Karlstad Øystein , Gunnes Nina , Hoff Mari , Tell Grethe S , Meyer Haakon E
Published: May 2022

Objectives

Patients with hip fracture are typically characterised by extensive comorbidities and excess mortality. Methods that account for a wide range of comorbidities are needed when attempting to identify causal associations in registry-based studies. We aimed to study the association between the prescription-based Rx-Risk Comorbidity Index (abbreviated Rx-Risk) and mortality by history of hip fracture, and to quantify the contribution of Rx-Risk in explaining the excess mortality after hip fracture.

Setting

In this prospective study, we used nationwide registry data from outpatient care. Rx-Risk was based on filled prescriptions recorded in the Norwegian Prescription Database. Medications were mapped to 46 comorbidity categories by Anatomical Therapeutic Chemical code. Information on hip fractures during 1994–2013 was available from the Norwegian Epidemiologic Osteoporosis Studies hip fracture database, and year of death was obtained from Statistics Norway. We estimated 1-year mortality risk (January through December 2014) according to Rx-Risk score based on dispensed prescriptions in 2013, history of hip fracture, age and sex using Poisson regression.

Participants

All individuals aged 65 years and older who were alive by the end of 2013 and had filled at least one prescription in an outpatient pharmacy in Norway in 2013 (n=735 968).

Results

Mortality increased exponentially with increasing Rx-Risk scores, and it was highest in persons with a history of hip fracture across the major range of Rx-Risk scores. Age- and sex-adjusted mortality risk difference according to history of hip fracture (yes vs no) was 4.4 percentage points (7.8% vs 3.4%). Adjustment for Rx-Risk score further attenuated this risk difference to 3.3 percentage points.

Conclusions

History of hip fracture and comorbidity assessed by Rx-Risk are independent risk factors for mortality in the community-dwelling older population in Norway. Comorbidity explained a quarter of the excess mortality in persons with a history of hip fracture.
Safety and feasibility study of non-invasive robot-assisted high-intensity focused ultrasound therapy for the treatment of atherosclerotic plaques in the femoral artery: protocol for a pilot study
Authors: Simons Michelle V , Groen Marijn H A , de Borst Gert J , Leiner Tim , Doevendans Pieter A F , Ebbini Emad , Slieker Fons J B , van Es René , Hazenberg Constantijn E V B
Published: May 2022

Introduction

Peripheral arterial disease (PAD) is an atherosclerotic disease leading to stenosis and/or occlusion of the arterial circulation of the lower extremities. The currently available revascularisation methods have an acceptable initial success rate, but the long-term patency is limited, while surgical revascularisation is associated with a relatively high perioperative risk. This urges the need for development of less invasive and more effective treatment modalities. This protocol article describes a study investigating a new non-invasive technique that uses robot assisted high-intensity focused ultrasound (HIFU) to treat atherosclerosis in the femoral artery.

Methods and analysis

A pilot study is currently performed in 15 symptomatic patients with PAD with a significant stenosis in the common femoral and/or proximal superficial femoral artery. All patients will be treated with the dual-mode ultrasound array system to deliver imaging-guided HIFU to the atherosclerotic plaque. Safety and feasibility are the primary objectives assessed by the technical feasibility of this therapy and the 30-day major complication rate as primary endpoints. Secondary endpoints are angiographic and clinical success and quality of life.

Ethics and dissemination

Ethical approval for this study was obtained in 2019 from the Medical Ethics Committee of the University Medical Center Utrecht, the Netherlands. Data will be presented at national and international conferences and published in a peer-reviewed journal.

Trial registration number

NL7564.
Unemployment due to the SARS-CoV-2-pandemic among people with and without severe disabilities: a difference-in-differences analysis
Authors: Booke Frederike , Fauser David , Reims Nancy , Bethge Matthias
Published: May 2022

Objectives

Unemployment reduces health and impairs participation in important areas of life, especially for people with severe disabilities, who tend to have a longer duration of unemployment and are less likely to find new employment than their counterparts without such constraints. Our analysis examines the increase in unemployment due to the SARS-CoV-2 pandemic among people with and without severe disabilities in Germany.

Methods

Monthly cross-sectional data on unemployment for 2019 and 2020 were provided by the Federal Employment Agency. We used a difference-in-differences model to estimate the increase in unemployment attributable to the pandemic. The months April to December 2020 represented the months of exposure to the pandemic. Incidence rate ratios (IRRs) are reported.

Results

The increase in unemployment among people with severe disabilities due to the pandemic is 11.2% (IRR 1.112; 95% CI 1.107 to 1.117). People with severe disabilities receiving unemployment benefits due to unemployment lasting less than a year (Social Code III: short-term unemployment) and women have been most affected. Among people without severe disabilities, unemployment has increased by 24.8% due to the pandemic (IRR 1.248; 95% CI 1.246 to 1.249), while people receiving unemployment benefits according to social code III and men have been most affected. Both groups show a varying increase in unemployment depending on the region of residency.

Conclusions

The findings show a particularly significant increase in unemployment among people without severe disabilities. People with severe disabilities might be less impacted due to the special legal protection against their dismissal. The clear regional differences in the increase in unemployment suggest a strong influence of regional economics.
Workings of science
Authors: Delic Kemal A. , Riley Jeff A.
Published: May 2022

While most people are not familiar with the details of how artificial intelligence (AI) works, the term itself is becoming more familiar to the non-scientific community, to the point that it ("AI") has almost become part of the regular vernacular of the ordinary person. AI has been with us for a long time-from first beginnings in ancient times in the form of automatons and other devices mimicking humans or other animals, through the middle of the last century when the term "artificial intelligence was actually coined, to the present times where it (the label rather than the actual technology) is entering the psyche of the general public.

This article explores the notion that the technology we call artificial intelligence is not yet ripe, but is establishing itself as a science in its own right, and that by 2156-the 200 year anniversary of the coining of the term-the technology should be in a position to deliver on its promises.
A MEC Offloading Strategy Based on Improved DQN and Simulated Annealing for Internet of Behavior
Authors: Yuan Xiaoming , Tian Hansen , Zhang Zedan , Zhao Zheyu , Liu Lei , Sangaiah Arun Kumar , Yu Keping
Published: May 2022

The Internet of Medical Things (IoMT) and Artificial Intelligence (AI) have brought unprecedented opportunities to meet massive behavioral data access and personalization requirements for Internet of Behavior (IoB). They facilitate the communication and computing resource allocation to guarantee low delay and energy consumption demands in healthcare. This article presents an improved offloading algorithm for Mobile Edge Computing (MEC) based on Deep Q Network (DQN) and Simulated Annealing (SA) for IoB. Firstly, we analyze the network model and establish a task cost function based on processing delay and energy consumption. Secondly, we define a Distributed Optimization Problem (DOP) to maximize individual utilities and system utility, which is proved to be a potential countermeasure. Thirdly, we conduct Markov modeling for the current offloading strategy-making scheme and define the objectives and constraints of the optimization function. At the same time, the SA is introduced into the DQN Algorithm, which improves the capacity of the algorithm by focusing on the exploration in the early stage and following the experience value in the later stage. From the simulation results, we can see that compared with the traditional scheme, the proposed strategy can maximize the utilization of the system and reduce processing delay and energy consumption.
JDAN: Joint Detection and Association Network for Real-Time Online Multi-Object Tracking
Authors: Wang Haidong , He Xuan , Li Zhiyong , Yuan Jin , Li Shutao
Published: May 2022

In the last few years, enormous strides have been made for object detection and data association, which are vital subtasks for one-stage online multi-object tracking (MOT). However, the two separated submodules involved in the whole MOT pipeline are processed or optimized separately, resulting in a complex method design and requiring manual settings. In addition, few works integrate the two subtasks into a single end-to-end network to optimize the overall task. In this study, we propose an end-to-end MOT network called joint detection and association network (JDAN) that is trained and inferred in a single network. All layers in JDAN are differentiable, and can be optimized jointly to detect targets and output an association matrix for robust multi-object tracking. What’s more, we generate suitable pseudo-labels to address the data inconsistency between object detection and association. The detection and association submodules could be optimized by the composite loss function that is derived from the detection results and the generated pseudo association labels, respectively. The proposed approach is evaluated on two MOT challenge datasets, and achieves promising performance compared with classic and latest methods.
Near-infrared Imaging for Information Embedding and Extraction with Layered Structures
Authors: Jiang Weiwei , Yu Difeng , Wang Chaofan , Sarsenbayeva Zhanna , van Berkel Niels , Goncalves Jorge , Kostakos Vassilis
Published: May 2022

Non-invasive inspection and imaging techniques are used to acquire non-visible information embedded in samples. Typical applications include medical imaging, defect evaluation, and electronics testing. However, existing methods have specific limitations, including safety risks (e.g., X-ray), equipment costs (e.g., optical tomography), personnel training (e.g., ultrasonography), and material constraints (e.g., terahertz spectroscopy). Such constraints make these approaches impractical for everyday scenarios. In this article, we present a method that is low-cost and practical for non-invasive inspection in everyday settings. Our prototype incorporates a miniaturized near-infrared spectroscopy scanner driven by a computer-controlled 2D-plotter. Our work presents a method to optimize content embedding, as well as a wavelength selection algorithm to extract content without human supervision. We show that our method can successfully extract occluded text through a paper stack of up to 16 pages. In addition, we present a deep-learning-based image enhancement model that can further improve the image quality and simultaneously decompose overlapping content. Finally, we demonstrate how our method can be generalized to different inks and other layered materials beyond paper. Our approach enables a wide range of content embedding applications, including chipless information embedding, physical secret sharing, 3D print evaluations, and steganography.
Does Policy Matter in Carsharing Traveling? Evolution Game Model-Based Carsharing and Private Car Study
Authors: Luo Wei , Qiu Shi , Jiao Pengpeng , Yao Liya , Wang Yi
Published: May 2022

As an alternative trip mode to the private car, carsharing mode first emerged in Europe in the 1940s. Although it possesses many merits such as convenience, affordability, and comfort, its development is far slower than the private car in recent years. Identifying the factors affecting the users’ choice between carsharing and private car is becoming very important. This paper proposes an evolution game model to explore the competitive choice process between carsharing and private car under different government policies. First, an evolution game model with incomplete information is developed to analyze the travel choice of carsharing over private car. The influences of government policy are taken into consideration. Then, the evolutionary stable strategy solution of the model is derived from replicator dynamics, and a discussion about the stable condition is presented. Finally, a case study is conducted to validate the proposed model. This study provides a rationale for agencies to improve the current carsharing choice rate between carsharing and private car.
Exploring the Mechanism of Weikang Keli in Inhibiting Gastric Cancer through the MAPK Signaling Pathway: Based on Network Pharmacology and Experimental Verification
Authors: Shao Xiang , Liu Yuping , Jiang Cuihua , Sun Yue , Zhang Qiyang , Gu Jialin , Huo Jiege , Hu Canhong
Published: May 2022

Background. With a high incidence and limited treatments, gastric cancer (GC) seriously threatens human health worldwide. Weikang Keli (WK) is a compound prescription summed up from clinical experience. In our previous studies, WK has been proved to exert antitumor effects. However, there are no research studies to discuss and verify its mechanism as a compound. Objective. The aim of the study is to explore the potential molecular mechanism of WK in the treatment of GC with the aid of network pharmacology and verify it through experiments. Methods. Related databases were used to obtain genes and targets of WK and gastric cancer. A protein-protein interaction (PPI) network is constructed and visualized by Cytoscape 3.7.2. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to analyze core targets. The cell viability of MFC and BGC-823 cells was determined by CCK8. Immunofluorescence was used to determine autophagy of GC cells. Moreover, the effect of WK on the MAPK signaling pathway in GC cells and tumor tissues of ICR mice was detected by Western blot. Results. A total of 106 cross targets of WK and GC were obtained. According to the enrichment analysis of GO and KEGG, we target the MAPK signaling pathway to discuss the mechanism of WK on GC. Cell experiments proved that WK inhibited the viability of gastric cancer cells in a dose-dependent and time-dependent manner. Autophagosome aggregation and an increase in the expression of an autophagy marker protein LC3-II can also be observed in WK groups. Further animal experiments showed that the tumor inhibition rate of WK showed a dose-effect relationship. Moreover, the expressions of p-JNK, p-p38, and p-ERR1/2 proteins in the MAPK signaling pathway in WK Group were downregulated both in the cell and animal experiments, compared with the blank control group. Conclusion. WK showed an explicit antitumor effect on gastric cancer through the MAPK signaling pathway, and the curative effect varies in different concentrations. Besides, in model mice, the antitumor effect of high-dose WK group is close to that of platinum. This study provided a theoretical basis for the application of WK in the clinical treatment of gastric cancer.
Expected Length of the Shortest Path of the Traveling Salesman Problem in 3D Space
Authors: Yang Hongtai , Lu Xiaoqian , Zhou Xinan , Zheng Rong , Liu Yugang , Tao Siyu
Published: May 2022

Finding the shortest path of the traveling salesman problem (TSP) is a typical NP-hard problem and one of the basic optimization problems. TSP in three-dimensional space (3D-TSP) is an extension of TSP. It plays an important role in the fields of 3D path planning and UAV inspection, such as forest fire patrol path planning. Many existing studies have focused on the expected length of the shortest path of TSP in 2D space. The expected length of the shortest path in 3D space has not yet been studied. To fill this gap, this research focuses on developing models to estimate the expected length of the shortest path of 3D-TSP. First, different experimental scenarios are designed by combining different service areas and the number of demand points. Under each scenario, the specified number of demand points is randomly generated, and an improved genetic algorithm and Gurobi are used to find the shortest path. A total of 500 experiments are performed for each scenario, and the average length of the shortest path is calculated. The models to estimate the expected length of the shortest path are proposed. Model parameters are estimated and k-fold cross-validation is used to evaluate the goodness of fit. Results show that all the models fit the data well and the best model is selected. The developed models can be used to estimate the expected length of the shortest path of 3D-TSP and provide important references for many applications.
Evaluation Method of Roof Damage Degree and a Case Study in Maoping Lead-Zinc Mine, Yunnan
Authors: Yang Jun , Qiao Linke , Wang Zhixiu , Wang Han
Published: May 2022

With the continuous increase in the mining depth of underground mineral resources, the geological conditions encountered in mining have become more complex. The complex geological conditions have led to varying degrees of roof damage, especially the frequent occurrence of roof collapse accidents in metal mines, causing huge losses to mining enterprises. How to evaluate the risk of roof subsidence, falling, and even collapse under different geological conditions has become the primary issue. This article first selects the main evaluation indicators in the domestic and foreign roadway roof failure research literature for statistical analysis. Then, according to the statistical results, a classification approach of roof damage degree using the fuzzy comprehensive clustering method is established with roof rock strength, broken degree, roadway section size, buried depth, and roof sinking amount as evaluation indicators. The damage of the top plate is divided into five grades: minor damage, obvious damage, serious damage, extremely serious damage, and devastating damage. Finally, the established evaluation method was applied to the project site-supporting work of the 760 m main transport roadway in Yunnan Maoping Lead-Zinc Mine. The evaluation result is consistent with the actual situation on-site. The research results can provide a reference for the roof stability analysis under the background of this project and similar projects and at the same time help the next step in the classification control of different levels of roof stability and the design of the overall roadway support.
Research on Pattern Recognition of Lower Limb Motion Based on Convolutional Neural Network
Authors: Zhang Xia , Tao Sihan
Published: May 2022

Accurate motion recognition is essential for assist devices such as exoskeletons to achieve human-robot communion. However, at present, the technology of lower limb motion pattern recognition still has the problems of small amount of data and low recognition accuracy. In this paper, the lower limb motion was taken as the object, and the surface electromyography (sEMG) signals of five gaits of going upstairs without weight, going downstairs without weight, going upstairs with weight, going downstairs with weight, and walking on a level surface without weight were collected. Based on the feature extraction of the sEMG signal, a convolutional neural network (CNN) with a feature set as the input is constructed, and a new lower limb motion pattern recognition method is proposed. The recognition accuracy and work feature of the proposed method are compared with several other classification and recognition methods. The experimental results show that, compared with the traditional methods, the method of using the feature set as input for CNN can better represent the features of the prediction model, and the pattern recognition accuracy is higher. The recognition accuracy of the five gaits are all greater than 96.96%, and the error rate is less than 7%, indicating that the proposed method has higher recognition accuracy. This method provides theoretical support for achieving compliant power assistance and promoting motor function rehabilitation with rehabilitation robots, power-assisted robots, and other equipment.
Multiple HD Screen-Based Virtual Studio System with Learned Mask-Free Portrait Harmonization
Authors: Jiang Jimao , Lin Jiaxin , Su Yuntao , Fang Li , Ye Long
Published: May 2022

Virtual studio technology allows producers to combine live-action footage and computer-generated imagery and has promoted the development of film and television industry. However, the existing green screen-based virtual studio limits the visual effects just in postproduction. In this paper, we propose a new virtual studio system based on the recent emerging technology using multiple high-definition (HD) screens. Besides using traditional computer graphics like other similar systems, our system enables to capture panoramic video from the real world as the background and project it onto multiple HD screens, so as to recreate the scene in the studio. In addition, we propose a mask-free portrait harmonization network to make sure that the appearances of the foreground region and the background are consistent. Our portrait harmonization network does not need any auxiliary foreground mask and works in an end-to-end manner, which meets the postprocessing requirements for our virtual studio. Experimental result on real composite images shows that our network is superior to the state-of-the-art image harmonization method under the task of portrait harmonization. We also demonstrate our system with a CAVE system.
Innovation of Teaching Method of Digital Media Art Based on Convolutional Neural Network
Authors: Liu Yumei
Published: May 2022

In order to improve the effect of digital media art teaching, this study combines the neural network algorithm to carry out the innovation of digital media art teaching resource management and teaching method innovation. The scheme proposed in this study divides the video frame into image blocks and then uses the BDCT transform to convert the video frame from the spatial domain to the frequency domain. Generally speaking, the DCT coefficient has the characteristic of energy concentration. In order to reduce the metadata needed to transmit the position of the discarded frequency-domain coefficients, the method proposed in this study divides the frequency-domain coefficients of different blocks into bands according to frequency and compresses the video in units of bands. Finally, this study constructs a digital media art teaching innovation system based on a convolutional neural network. The experimental research results show that the digital media art teaching system based on the convolutional neural network can effectively improve the teaching effect of digital media art.
Research on the Optimization of the Physical Education Teaching Mode Based on Cluster Analysis under the Background of Big Data
Authors: Die Hu , Lianhong Liu
Published: May 2022

With the rise of digital campuses, online learning platforms, and the improvement of educational technology, the interaction between teachers and students has entered a new stage. Especially under the influence of CSCL (Computer Supported Collaborative Learning), computer-assisted collaborative learning, and E-learning (Electronic Learning) network digital learning that emerged in recent times, new technologies are changing the way people learn. Students’ learning is not limited to one-way absorption of knowledge taught by teachers, and the interaction between students and teachers, students and students, and the interaction between students and the teaching environment are increasingly appearing in modern teaching classrooms. This paper optimizes the physical education management based on the clustering algorithm under the background of big data, uses the popular Java language to write codes to realize all the functions of the algorithm, and uses some small examples to prove the correctness of the fuzzy clustering algorithm sex. The algorithm reads a file through the input and output streams FileReader and BufferedReader. The content of the file is the relevant information of the physical education mode. It gives the methods to calculate the cluster center (i.e., the center of mass), calculate the distance, correct the fuzzy classification matrix, and display the matrix. (i.e., output matrix), conversion to deterministic classification method, calculation of classification coefficients, and basic functions such as average fuzzy entropy. According to the data, if the FCM clustering method is not used, but the previous average method is used as the evaluation basis, there will be results that we do not want to see, but if we use the FCM algorithm, the evaluation result is that what we want to see is more specific. From the analysis results, thematic teaching + basic teaching seems to be the most popular mode of physical education.
The Characterization of Liquefied Petroleum Gas (LPG) Using a Modified Bunsen Burner
Authors: Alfarraj Bader A , Al-Harbi Ahmed A. , Binjuwair Saud A. , Alkhedhair Abdullah
Published: May 2022

The equivalence ratio ranges were found between 22.77 and 42.93 for the Saudi LPG/air mixture using a traditional Bunsen burner. An operation problem was found with a traditional Bunsen burner for the Saudi LPG/air mixture, especially in a lean mixture. Therefore, a Bunsen burner was successfully modified to overcome the limits of operation with different mixtures of Saudi LPG/air and a stable flame was obtained. The equivalence ratio ranges were found between 0.68 and 1.30 using the modified Bunsen burner. A premixed flame was used for the modified Bunsen burner. A MATLAB algorithm was successfully applied to flame image processing and measurement of laminar burning velocity. The laminar burning velocity was determined to be approximately 35 ± 0.91 cm/s under stoichiometric conditions using the modified Bunsen burner for the Saudi LPG/air mixture. The half-cone angle of the flame was found to be 16.20 ± 0.76°. The minimum flame height was observed to be 21.50 ± 0.22 mm above the Bunsen burner exit.
PLS-SEM Model of Integrated Stem Education Concept and Network Teaching Model of Architectural Engineering Course
Authors: Wang Ping
Published: May 2022

In order to cultivate talents more effectively in construction engineering and cultivate students’ critical thinking, creative thinking, high-level thinking, as well as students’ perseverance, learning ability, global competence, and responsibility, combined with the integrated stem education concept, this paper makes an in-depth study on the online teaching model of construction engineering course in PLS-SEM mode. This paper mainly discusses how to apply stem education concept in architectural engineering teaching through literature analysis and the design of architectural engineering teaching cases. Take the integrated stem education concept as the guiding ideology, design research as the methodological guidance, and learn from the research model of design research in the field of curriculum and teaching “formative research.” After the prototype of the teaching mode is put forward, with three rounds of iterative implementation and revision, a feasible and effective mathematics teaching mode in Engineering Higher Vocational Colleges under the concept of stem education (hereinafter referred to as “stem-HVE teaching mode”) is finally obtained. It provides a new way for engineering teaching and opens a new chapter of integrated stem education in the field of engineering teaching.
The Combined Use of Platelet-Rich Plasma Clot Releasate and Allogeneic Human Umbilical Cord Mesenchymal Stem Cells Rescue Glucocorticoid-Induced Osteonecrosis of the Femoral Head
Authors: Wang Yanxue , Luan Shuo , Yuan Ze , Wang Shaoling , Fan Shengnuo , Ma Chao , Wu Shaoling
Published: May 2022

Glucocorticoid-induced osteonecrosis of the femoral head (ONFH) is a refractory disease. The treatment options for ONFH, especially nonsurgical ones, merit further investigation. To evaluate the combinatorial therapeutic effects of platelet-rich plasma clot releasate (PRCR) and umbilical cord mesenchymal stem cells (UC-MSCs) on glucocorticoid-induced ONFH, a dexamethasone (DEX)-treated cell model and a high-dose methylprednisolone (MPS)-treated rat model were established. Cell counting kit-8 (CCK-8) assay was performed in vitro to determine the optimum dosage of PRCR for UC-MSC viability. The effects of PRCR, UC-MSCs, and PRCR + UC-MSCs on cell viability, apoptosis, migration, and differentiation capacities of DEX-treated bone marrow mesenchymal stem cells (BMSCs) and human umbilical vein endothelial cell (HUVECs) were explored via Transwell assays. Western blotting was conducted to evaluate the expression levels of RUNX2, VEGF, caspase-3, and Bcl-2 in the coculture systems. Ultrasound-guided intra-articular PRCR, UC-MSCs, and PRCR + UC-MSC injections were performed on the ONFH model rats. Microcomputed tomography, histological and immunohistochemical analyses, tartrate-resistant acid phosphatase (TRAP) staining, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining were used to assess the therapeutic effects of PRCR and UC-MSCs on bone loss and necrosis induced by high-dose MPS. Results of this study revealed that the in vitro application of PRCR, UC-MSCs, and PRCR + UC-MSCs reversed the impaired proliferation and migration capacities and resisted apoptosis of BMSCs and HUVECs induced by DEX. Moreover, the PRCR and UC-MSC application significantly improved the alkaline phosphatase (ALP) and alizarin red (ALR) staining of BMSCs and tube formation capacity of HUVECs and promoted the protein expression of RUNX2 in BMSCs and VEGF in HUVECs. Similarly, in the ONFH rat model, the intra-articular injection of UC-MSCs and PRCR improved the subchondral bone mass parameters; promoted the expression of ALP, RUNX2, and VEGF; suppressed osteoclast overactivity; and resisted cell apoptosis. The combination of PRCR and UC-MSCs shows promising therapeutic effects in treating glucocorticoid-induced ONFH. The current study provides important information on intra-articular therapy, paving the way for the clinical management of ONFH in the future.
Robust Authentication System with Privacy Preservation of Biometrics
Authors: Patil Sonali D. , Raut Roshani , Jhaveri Rutvij H. , Ahanger Tariq Ahamed , Dhade Pallavi V. , Kathole Atul B. , Vhatkar Kapil N.
Published: May 2022

IoT-based multi-biometric system is a blend of multiple biometric templates that can be used for user authentication/verification using sensors. The leakage of the biometric trait information may cause critical privacy and security issues. It is expected to protect the privacy details of individuals through the irreversibility, unlinkability, and renewability of multi-biometric templates used in the authentication system. This study presents a robust authentication system with secure multi-biometric template protection techniques based on discrete cosine transform feature transformation and Lagrange’s interpolation-based image transformation. Three biometric traits namely iris, fingerprint, and palm print are recorded using sensors to validate the proposed multi-biometric template protection system. The fusion of all traits used is giving an average of 95.42% genuine acceptance rate and an average of 4.57% false rejection rate. Despite any number of biometric templates used for authentication, the proposed image transformation techniques keep the size of the final storage requirement as 8 X 8, which achieves constant space complexity (O(1)). The stored template is not linked with original templates; it is irreversible and renewable as new enrolment of the same individual will produce a new template every time. Overall, the proposed technique provides a secure authentication system with high accuracy, a constant size database, and the privacy preservation of biometric traits.
Comparison of Airway Pressure Release Ventilation to High-Frequency Oscillatory Ventilation in Neonates with Refractory Respiratory Failure
Authors: Arya Shreyas , Kingma Melissa L. , Dornette Stacey , Weber Amy , Bardua Cathy , Mierke Sarah , Kingma Paul S.
Published: May 2022

Background. Airway pressure release ventilation (APRV) is a relatively new mode of ventilation in neonates. We hypothesize that APRV is an effective rescue mode in infants failing conventional ventilation and it is comparable in survival rates to rescue with high-frequency oscillatory ventilation (HFOV). Methods. This is a 6-year retrospective cohort study of infants that failed synchronized intermittent mandatory ventilation (SIMV) and were rescued with either APRV or HFOV. For comparison, we divided infants into two groups (28-37 and >37 weeks) based on their corrected gestational age (CGA) at failure of SIMV. Results. Ninety infants were included in the study. Infants rescued with APRV (

n
=
46

) had similar survival rates to those rescued with HFOV (

n
=
44

)—28-37 weeks CGA (APRV 78% vs. HFOV 84%,

p
=
0.68

) and >37 weeks CGA (APRV 76% vs. HFOV 72%,

p
=
0.74

). Use of APRV was not associated with an increase in pneumothorax (APRV 0% and HFOV 10%,

p
=
0.31

, in 28-37 weeks CGA, and APRV 0% and HFOV 4%,

p
=
0.22

, in >37 weeks CGA). Conclusion. APRV can be effectively used to rescue infants with refractory respiratory failure on SIMV. When compared to HFOV, rescue with APRV is not associated with an increase in mortality or pneumothorax.
Generalized Difference-Cum Exponential Class of Estimators for Estimating Population Parameters of the Sensitive Variable
Authors: Vishwakarma Gajendra K. , Yadav Subhash Kumar , Bari Tarushree
Published: May 2022

We propose a generalized class of estimators to estimate general population parameters of susceptible research variables using additional auxiliary information in SRSWOR. The population constants such as the coefficient of variation, the population mean, the standard deviation, and the population mean square are defined using a conventional estimator. The expression for the mean square errors of the proposed class is derived up to the first order of approximation. To compare the effectiveness of the proposed class of estimators, an empirical study is conducted utilizing real and simulated data sets. Theoretical and empirical research demonstrates that the suggested generalized class of estimators outperforms other current estimators.
Fair and Efficient Robust Secret Sharing Scheme against Rushing Adversaries
Authors: Zhang En , Yang Renlin , Fan Haiju , Qin Leiyong
Published: May 2022

Robust secret sharing (RSS) is an extension of secret sharing, which can reconstruct a secret correctly even if any

t

shares are incorrect. The existing scheme would not effectively achieve fairness. Moreover, even for an optimal scheme, RSS still has the problem that one party is verified by multiple parties, leading to expensive communication costs. In this work, we construct a blockchain-aided RSS scheme that can ensure decentralization and fairness. The central building block for our scheme to handle a rushing adversary is a bulletin board we implement on the InterPlanetary File System. Furthermore, we design a monetary penalty mechanism to impose real penalties on corrupt parties. Each participant either uploads his share correctly or loses his deposit. In addition, our scheme eliminates considerable communication between participants. Compared with the previous schemes, our scheme has a lower communication complexity, which is close to

O
˜

n

. We conduct experiments to show the performance of our scheme. To our knowledge, this is the first implementation of a fair RSS scheme. For shares with a length of 128 bits, the time for each participant to execute the verification phase is 470 ms.
Application of Image Online Processing Technology in Analysis of Urban Commonwealth and Problem of Urban Residents’ Gap between the Rich and the Poor
Authors: Li Fang
Published: May 2022

Background. Since the liberalization and deregulation, with the development of market economy and industrialization, our country, i.e., China, has stepped into the ranks of middle-income countries in the overall level of economic development. However, there is a gap between the rich and the poor in our country, which is gradually widening, which not only has an impact on the creation of a harmonious socialist society but also attracts more and more people’s attention. At present, it has aroused the high attention of the society. Objective. Under the condition that the gap between the rich and the poor is too large and the theory of common prosperity is misinterpreted, some people begin to question whether the socialist road with Chinese characteristics can really realize common prosperity. Methods. Therefore, how to understand Deng Xiaoping’s notion of sharing prosperity and how to close the gap between affluent and poor in China is a major issue related to the socialist faith of the broad masses of people, and it is also a problem that must be paid attention to and solved urgently at present. Results. The presented study employs advanced online processing technology to accurately measure urban wealth and uses Internet image online processing technology to examine the gap between the rich and the poor. The gap between the rich and the poor of urban residents is analyzed scientifically. Moreover, the Internet image online processing technology is applied to the analysis of urban common prosperity and urban wealth gap and finally to provide an accurate analysis content for the examination of the gap between the rich and the poor and the common prosperity of the residents. Conclusions. Finally, it is verified by experiments that the online processing technology of Internet image can be effectively applied to the analysis of urban common prosperity and the gap between the rich and the poor of urban residents.