Mixup-Inf-Net: A data augmentation algorithm for segmentation of new coronary pneumonia infections

In 2020, the global spread of Coronavirus Disease 2019 exposed entire world to a severe health crisis. This has limited fast and accurate screening of suspected cases due to equipment shortages and and harsh testing environments. The current diagnosis of suspected cases has benefited greatly from the use of radiographic brain imaging, also including X-ray and scintigraphy, as a crucial addition to screening tests for new coronary pneumonia disease. However, it is impractical to gather enormous volumes of data quickly, which makes it difficult for depth models to be trained. To solve these problems, we obtained a new dataset by data augmentation Mixup method for the used chest CT slices. It uses lung infection segmentation (Inf-Net [1]) in a deep network and adds a learning framework with semi-supervised to form a Mixup-Inf-Net semi-supervised learning framework model to identify COVID-19 infection area from chest CT slices. The system depends primarily on unlabeled data and merely a minimal amount of annotated data is required;therefore, the unlabeled data generated by Mixup provides good assistance. Our framework can be used to improve improve learning and performance. The SemiSeg dataset and the actual 3D CT images that we produced are used in a variety of tests, and the analysis shows that Mixup-Inf-Net semi-supervised outperforms most SOTA segmentation models learning framework model in this study, which also enhances segmentation performance. © 2023 SPIE.

Research on cold chain logistics optimization model considering low-carbon emissions

Cold chain logistics distribution orders have increased due to the impact of COVID-19. In view of the increasing difficulty of route optimization and the increase of carbon emissions in the process of cold chain logistics distribution, a mathematical model for route optimization of cold chain logistics distribution vehicles with minimum comprehensive cost is established by considering the cost of carbon emission intensity comprehensively in this paper. The main contributions of this paper are as follows: 1) An improved hybrid ant colony algorithm is proposed, which combined simulated annealing algorithm to get rid of the local optimal solution. 2) Chaotic mapping is introduced in pheromone update to accelerate convergence and improve search efficiency. The effectiveness of the proposed method in optimizing cold chain logistics distribution path and reducing costs is verified by simulation experiments and comparison with the existing classical algorithms. © 2023 The Author(s). Published by Oxford University Press.

POSSIBLE ROLE OF PEPTIDE EPITOPES OF COVID-19 BNT-162B2 MRNA VACCINE IN FOMENTING AUTOIMMUNITY: AN IN SILICO ANALYSIS

BackgroundFollowing the launch of the global COVID-19 vaccination campaign, there have been increased reports of autoimmune diseases developing de novo following vaccination. These cases include rheumatoid arthritis, autoimmune hepatitis, immune thrombotic thrombocytopenia, and connective tissue diseases. Nevertheless, COVID-19 vaccines are considered safe for patients with autoimmune diseases and are strongly recommended.ObjectivesThe aim of this in silico analysis is to investigate the presence of protein epitopes encoded by the BNT-162b2 mRNA vaccine, one of the most commonly administered COVID-19 vaccines, that could elicit an aberrant adaptive immune response in predisposed individuals.MethodsThe FASTA sequence of the protein encoded by the BNT-162b2 vaccine was retrieved from http://genome.ucsc.edu and used as a key input to the Immune Epitope Database and Analysis Resource (www.iedb.org). Linear peptides with 90% BLAST homology were selected, and T-cell, B-cell, and MHC ligand assays without MHC restriction were searched and evaluated. HLA-disease associations were screened on the HLA-SPREAD platform (https://hla-spread.igib.res.in) by selecting only positive markers.ResultsA total of 183 epitopes were found, corresponding to 178 SARS-CoV-2 and 5 SARS-CoV spike epitopes, respectively. Results were obtained from 22 T-cell assays, 398 B-cell assays, and 2 MHC ligand assays. Complementary receptors included 1080 T-cell receptors and 0 B-cell receptors.Specifically, the IEDB_epitope:1329790 (NATNVVIKVCEFQFCNDPFLGVYY) was shown to bind to HLA-DRB1*15:02 and HLA-DRB1*15:03 alleles, whereas the IEDB_epitope:1392457 (TKCTLKSFTVEKGIYQTSNFRVQPT) was reported to bind to HLA-DRB1*07:01, HLA-DRB1*03:01, HLA-DRB3*01:01, and HLA-DRB4*01:01 alleles. The HLA alleles detected were found to be positively associated with various immunological disorders (Table 1).Table 1.MHC-restricted epitopes of the BNT-162b2 vaccine and potentially associated immunological conditionsEpitopeAssayMHC moleculeAssociated disease (population)NATNVVIKVCEFQFCNDPFLGVYY + OX(C10)cellular MHC/mass spectrometry ligand presentationHLA-DRB1*15:02Takayasu arteritis (Japanese) Arthritis (Taiwanese) Scleroderma (Japanese) Colitis (Japanese)HLA-DRB1*15:03Systemic lupus erythematosus (Mexican American)TKCTLKSFTVEKGIYQTSNFRVQPT + SCM(K2)as aboveHLA-DRB1*07:01Allergy, hypersensitivity (Caucasian)HLA-DRB1*03:01Type 1 diabetes (African) Sarcoidosis, good prognosis (Finnish)HLA-DRB3*01:01Graves' disease (Caucasian) Thymoma (Caucasian) Sarcoidosis (Scandinavian) Autoimmune hepatitis (Caucasian)HLA-DRB4*01:01Vitiligo (Saudi Arabian)ConclusionSimilar to the SARS-CoV-2 spike protein, the protein product of the BNT-162b2 mRNA vaccine contains immunogenic epitopes that may trigger autoimmune phenomena in predisposed individuals. Genotyping for HLA alleles may help identify at-risk individuals. However, further research is needed to elucidate the underlying mechanisms and potential clinical implications.References[1]Vita R, Mahajan S, Overton JA et al. The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Res. 2019 Jan 8;47(D1):D339-D343. doi: 10.1093/nar/gky1006.[2]Dholakia D, Kalra A, Misir BR et al. HLA-SPREAD: a natural language processing based resource for curating HLA association from PubMed s. BMC Genomics 23, 10 (2022). https://doi.org/10.1186/s12864-021-08239-0[3]Parker R, Partridge T, Wormald C et al. Mapping the SARS-CoV-2 spike glycoprotein-derived peptidome presented by HLA class II on dendritic cells. Cell Rep. 2021 May 25;35(8):109179. doi: 10.1016/j.celrep.2021.109179.[4]Knierman MD, Lannan MB, Spindler LJ et al. The Human Leukocyte Antigen Class II Immunopeptidome of the SARS-CoV-2 Spike Glycoprotein. Cell Rep. 2020 Dec 1;33(9):108454. doi: 10.1016/j.celrep.2020.108454.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

A Brief Statistical and Geostatistical Survey of the Relationship between COVID-19 and By-Mail Balloting in the 2020 North Carolina General Election

Adding to the already polarizing 2020 general election was the COVID-19 pandemic. One way in which this pandemic greatly affected the election was through an increased participation in by-mail, or mail-in, ballots. The state of North Carolina experienced a 316 percent increase in by-mail votes between 2016 and 2020, when approximately 977,186 votes were cast by mail. It is no surprise that this increase was due to the COVID-19 pandemic;however, these by-mail voting patterns are spatial in nature and vary across the state. This research measures to what degree COVID-19 rates affected by-mail voting rates. Using geographic information systems data developed from robust tabular files provided by the North Carolina State Board of Elections, by-mail votes were calculated and mapped at ZIP code scale and compared to COVID-19 rates measured at different dates. By-mail rates taken from final absentee tallies for the highest and lowest COVID-19 ZIP codes saw no significant differences across multiple dates (30 September 2020 and 31 October 2020) when COVID-19 data were collected. COVID-19 hot spots (high COVID-19 rates surrounded by other high COVID-19 rates) were extracted using geostatistical techniques and compared to COVID-19 cold spots (low COVID-19 rates surrounded by other low COVID-19 rates). It was found the lowest by-mail rates actually occurred in these COVID-19 hot spots across both dates, as well a metric that expressed percentage change in COVID-19 rates in the month before the 2020 election.Alternate :COVID-19使得已经两极分化的2020年美国大选, 变得更加雪上加霜。COVID-19影响选举的一种方式是邮寄选票的增加。2016年至2020年, 北卡罗来纳州的邮寄选票增加了316%, 共约977,186张。毫无疑问, COVID-19导致了邮寄选票的增加。然而, 邮寄选票在本质上是空间性的, 并且在北卡罗来纳州的各个地方具有差异性。本研究计算了COVID-19发病率对邮寄选票比例的影响程度。利用北卡罗来纳州选举委员会提供的准确的表格文件, 本文制作了地理信息系统数据, 在邮政编码尺度上对邮寄选票进行计算和制图, 并将这些邮寄选票与不同时间的COVID-19发病率进行了比较。在拥有最高和最低COVID-19发病率的邮政编码和不同时间（2020年9月30日和2020年10月31日）, 从缺失人数统计中得到的邮寄选票比例没有显著差异。利用地学统计方法提取COVID-19热点（COVID-19高发病率在空间上被其它高发病率所包围）, 并与COVID-19冷点（COVID-19低发病率在空间上被其它低发病率所包围）进行比较。结果发现, 在这两个时间内, 最低邮寄选票比例出现在COVID-19热点地区。本文还制定了一个指标, 可以表示2020年大选前一个月的COVID-19发病率百分比的变化。

Mapping the riskscape of using privately-owned short-term lets for specialist family violence crisis accommodation

COVID-19 has generated many problems and some opportunities in the housing market. The potential role of privately-owned short-term lets meeting specialist family violence crisis accommodation demand is one such opportunity. This paper engages with an important and increasing practice in the Australian context, of the utilisation of private housing stock as a component part of a public housing crisis response system, in this case explored in relation to domestic and family violence. In seeking to gain insights into the feasibility of this practice, this article will first frame mixed public/private accommodation provision as potentially overlapping relations between a thin territory of insufficient crisis infrastructure and a thick territory of commodified short-term let infrastructure. Second, this paper situates the potential of this intersection of mixed private/public responses in terms of riskscapes by unpacking how risk is perceived within these contested territories. The findings highlight tensions between both real and perceived understandings of safety, housing, wellbeing, economic and political risks. While there was some support for utilising short-term lets for crisis accommodation, barriers were revealed to adding thickness to the crisis accommodation space. Given increasing homelessness in Australia, diversifying crisis models could offer increased violence-prevention infrastructure to support women.

The semiotics of the anti-COVID-19 mask

The pandemic spreading of the COVID-19 virus has led to the global need to introduce, often by law, the medical face mask, which can undoubtedly be considered as "the object of 2020.” In a few months, most human faces around the world in the public space, but also often in the private space, have been covered with various kinds of protective masks. Very soon, these objects have become the centre of several discursive productions, going from medical reports to media coverage, from artistic representations to ironic memes. The medical face mask was not totally new in the west, where it was already present in special circumstances, like dentists' studios or emergency rooms, and was quite familiar in the east, especially in Japan, China, and Korea. Yet such massive introduction changed the meaning of the medical face mask in every context. Old habits were reconfigured or clashed with the new ones, giving rise to a novel syntax, semantics, and pragmatics of the human face in conjunction with this device and in the context of the global pandemic. The present paper offers an introduction to a semiotic mapping of such radical cultural change and its likely consequences.

Microlearning as an Educational Technology: Information Requests and Bibliometric Analysis

The article provides an overview of research sources on microlearning. Micro-learning is a modern educational trend, as the development of digital technologies and limitations, in particular caused by COVID-19, change the ways of effective learning and teaching. Emphasis is placed on the terms used to describe microlearning. Furthermore, various methods of bibliometric analysis and mapping of the science were used for the presentation. Furthermore, the dynamics of the publication activity regarding the query "microlearning” in the databases Scopus and Web of Science Core Collection for the period 2010–2021 are determined. Based on selected publications with the help of VOSviewer, the terminological maps are constructed and their main points of intersection are revealed. The results of the study revealed a stable exploratory and scientific interest in the application and effective implementation of microlearning as an interdisciplinary study. Clear visualization of the obtained data made it possible to identify the main areas of research in micro-learning in the fields of technical, engineering and educational sciences. Moreover, microlearning as an educational technology is the least favorable term represented in the publication field, which can be considered as a promising area of further research. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

A Bibliometric Analysis of Sustainable Food Consumption: Historical Evolution, Dominant Topics and Trends

The major goal of this study is to trace the emergence of SFC-related research across time, using a thematic map and a list of corresponding publications. In addition, this study aims to determine the author who has made the most significant contribution to this particular field. This study provides a comprehensive bibliometric analysis of the historical development and current trends in sustainable food consumption research, examining 2265 articles published between 1990 and 2023. Using the bibliometrics package of R Studio software version 4.2.1 and its Biblioshiny package, articles from the Scopus and Web of Science databases are examined. In the field of sustainable food consumption, we identify five distinct research phases: initial stagnation, infant growth, post-economic crisis, expanding phase and COVID-19 and post-pandemic. While research on broader sustainability topics can be traced back to the early 20th century, a very limited number of articles on sustainable food consumption was published in the 1990s. However, the number of publications increased incrementally over time, with a notable uptick in interest around 2015, and the subject was still being discussed in 2022. The emergence of the COVID-19 pandemic marked the beginning of the most recent phase of research, which analyzed the consumption patterns of consumers before and after the pandemic. Our study highlights key authors, documents and sources related to sustainable food consumption. The United States, Italy and the United Kingdom emerged as the most active contributors to the research on sustainable food consumption and were additionally the countries with the largest global market shares for organic products. Major sub-themes including organic food, food waste, sustainable development and food security, together with consumer behavior and organic products appeared as being the most researched sub-themes of recent times. The results of this study suggest that more research is related to sustainable food consumption in countries with a low organic food market share. In addition, the investigation of actual data on food waste, carbon footprints and greenhouse gas emissions resulting from food production and consumption is essential to gain holistic insights.

Dangerous liaisons? Applying the social harm perspective to the social inequality, housing and health trifecta during the Covid-19 pandemic

Global rates of excess mortality attributable to the Covid-19 pandemic provide a fresh impetus to make sense of the associations between income inequality, housing inequality and the social gradient in health, suggesting new questions about the ways in which housing and health are treated in the framing and development of public policy. The first half of the paper uses a social harm lens to examine the threefold associations of the social inequality, housing and health trifecta and offers new insights for policy analysis which foregrounds the production, transmission, and experience of various types of harm which occur within the home. The main body of the paper then draws upon the outcomes of an international systematic literature mapping review of 213 Covid-19 research papers to demonstrate three specific harms associated with stay-at-home lockdowns: (i) intimate partner and domestic violence, (ii) poor mental health and (iii) health harming behaviours. The reported findings are interpreted using a social harm perspective and some implications for policy analysis are illustrated. The paper concludes with a reflection on the efficacy of social harm as a lens for policy analysis and suggests directions for further research in housing studies and zemiology.

The handbook of security

The substantially revised third edition of The Handbook of Security provides the most comprehensive analysis of scholarly security debates and issues to date. It reflects the developments in security technology, the convergence of the cyber and security worlds, and the fact that security management has become even more business focused. It covers newer topics like terrorism, violence, and cybercrime through various offence types such as commercial robbery and bribery. This handbook comprises mostly brand new chapters and a few thoroughly revised chapters, with discussions of the impact of the pandemic. It includes contributions from some of the world's leading scholars from an even broader geographic scale to critique the way security is provided and managed. It speaks to professionals working in security and students studying security-related courses. Chapter 5 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. All rights reserved.

COVID-19 Media Chatter and Macroeconomic Reflectors on Black Swan: A Spanish and Indian Stock Markets Comparison

Predictive analytics of financial markets in developed and emerging economies during the COVID-19 regime is undeniably challenging due to unavoidable uncertainty and the profound proliferation of negative news on different platforms. Tracking the media echo is crucial to explaining and anticipating the abrupt fluctuations in financial markets. The present research attempts to propound a robust framework capable of channeling macroeconomic reflectors and essential media chatter-linked variables to draw precise forecasts of future figures for Spanish and Indian stock markets. The predictive structure combines Isometric Mapping (ISOMAP), which is a non-linear feature transformation tool, and Gradient Boosting Regression (GBR), which is an ensemble machine learning technique to perform predictive modelling. The Explainable Artificial Intelligence (XAI) is used to interpret the black-box type predictive model to infer meaningful insights. The overall results duly justify the incorporation of local and global media chatter indices in explaining the dynamics of respective financial markets. The findings imply marginally better predictability of Indian stock markets than their Spanish counterparts. The current work strives to compare and contrast the reaction of developed and developing financial markets during the COVID-19 pandemic, which has been argued to share a close resemblance to the Black Swan event when applying a robust research framework. The insights linked to the dependence of stock markets on macroeconomic indicators can be leveraged for policy formulations for augmenting household finance. © 2023 by the authors.

Remote Laboratory Experiments: Fan Map Generation and Airfoil Flow Characterization

This paper presents the procedure followed to conduct two various experiments as part of the ‘Mechanical Laboratory' course of the Mechanical Engineering department, at Aristotle University of Thessaloniki, during the Covid-19 period. Adapting to the personal contact restrictions imposed by the health issue outbreak, a remote experimental method is proposed. In the first experiment, the students had to generate the operational map of a cooling computer fan while on the second one the characteristic parameters of a symmetric airfoil needed to be measured. Multifunctional control panel interfaces were introduced to the students. Through these applications, the student had the opportunity to run the experiments, assess the raw data, monitor all the necessary flow parameters and acquire the important variables. The students had to post-process the results and submit two reports, one for each experiment. This teaching method provided the students with the experience of real research project and guided them to use modern tools to enhance the quality of their future work. This publication focuses on the address of the challenges, arose during the automation of the experiments. The remote experimental sessions indicated some advantages in learning procedure which was also reflected on the assignment grades. The development of the procedure has been successfully implemented and tested over a couple of years while the quarantine measure have been in place. Furthermore, the experience gained will be used to implement modern communication protocols in the experimental set-ups.

STRENGTHS AND TRANSFORMABILITY OF HEALTHCARE STRUCTURES IN CAMPANIA

In Italy the Covid-19 pandemic has revealed infrastructural and operational fragilities of the healthcare system, as well as a profound need for building modernization and upgrade as it emerges from the planned investments of the PNRR too. The Campania Region confirms the national trend in terms of consistency and age of the healthcare real estate, in some cases of artistic and cultural interest, which is underused and thus susceptible to possible regeneration. The paper aims at defining a decision support tool to track dimensional and typological parameters of the analyzed buildings and at defining a priority scale of possible enhancement and upgrade interventions. The methodology has three phases: mapping the real estate;defining a potentiality index which links building and urban characteristics to possible transformations;defining a transformability index to describe the predisposition of buildings to undergo interventions. From the cross-reading of the obtained indexes the decision maker can define the best strategy and perspective for a well informed and sustainable regeneration plan. © 2022, Luciano Editore. All rights reserved.

Analyzing the effects of COVID-19 pandemic on supplier performance evaluation factors via fuzzy cognitive map with a hybrid learning system

PurposeThe COVID-19 pandemic has proven that how supply chain management (SCM) can become a crucial process for sustainability of the world's production/service. The global supply chain crisis during pandemic has affected most of the sectors. Home and personal care products manufacturers are among them. In this study (1) the problems at SCM of personal and home care products manufacturers during pandemic are discussed with the help of medium-size manufacturer and (2) the factors affecting suppliers' performance for the relevant sector during COVID-19 are analyzed comprehensively.Design/methodology/approachThe importance of the factors is evaluated using fuzzy cognitive maps that can help to reveal hidden casual relationships with the help of expert knowledge. In order to eliminate subjectivity due to usage of expert knowledge, the maps are trained with a hybrid learning approach that consists of Non-linear Learning and Extended Great Deluge Algorithms to increase robustness of the analysis.FindingsThe findings of the study indicate that the factors such as general quality level of products/services, compliance to delivery time, communication skills and total production capacity of suppliers have been crucial factors during pandemic.Originality/valueWhile the implementation of the hybrid learning approach on supply chain can fill the gap in the relevant literature, the promising results of the study can prove the convenience of the methodology to model the of complex systems like supply chain processes.

Supply Chain Risk Diffusion in Partially Mapping Double-Layer Hypernetworks.

The impact of COVID-19 is global, and uncertain information will affect product quality and worker efficiency in the complex supply chain network, thus bringing risks. Aiming at individual heterogeneity, a partial mapping double-layer hypernetwork model is constructed to study the supply chain risk diffusion under uncertain information. Here, we explore the risk diffusion dynamics, drawing on epidemiology, and establish an SPIR (Susceptible-Potential-Infected-Recovered) model to simulate the risk diffusion process. The node represents the enterprise, and hyperedge represents the cooperation among enterprises. The microscopic Markov chain approach (MMCA) is used to prove the theory. Network dynamic evolution includes two removal strategies: (i) removing aging nodes; (ii) removing key nodes. Using Matlab to simulate the model, we found that it is more conducive to market stability to eliminate outdated enterprises than to control key enterprises during risk diffusion. The risk diffusion scale is related to interlayer mapping. Increasing the upper layer mapping rate to strengthen the efforts of official media to issue authoritative information will reduce the infected enterprise number. Reducing the lower layer mapping rate will reduce the misled enterprise number, thereby weakening the efficiency of risk infection. The model is helpful for understanding the risk diffusion characteristics and the importance of online information, and it has guiding significance for supply chain management.

Mapping of Journal of Hospitality and Tourism Insights themes: a retrospective overview

PurposeRecognising the literature of a field is vital for advancement in that field. Yet, there has not been a systematic analysis of recent publications published in the Journal of Hospitality and Tourism Insights (JHTI). Therefore, this research aims to do a bibliometric analysis of articles published in JHTI during the previous five years.Design/methodology/approachThis study used bibliometric techniques and indicators to analyse JHTI publications from 2018 to 2022. The data utilised in the study were obtained from Scopus and subsequently subjected to analysis through the Bibliometrix software.FindingsThe findings show good collaboration between the production components (country, institution and author) in JHTI. The co-occurrence analysis of keywords comprises five clusters;the co-citation analysis comprises six;and a group of articles connected with psychological aspects and areas such as motivation, attitude, customer engagement, place attachment and behavioural intention was the most remarkable cluster. Sharing economy, destination marketing, destination image and some, to an extent, social media and revenue management are just a few of the niche themes that have the potential to come up.Research limitations/implicationsThis study will be helpful as a roadmap for researchers in different fields who are interested in such studies, as well as for editorial board members and those who work in JHTI.Practical implicationsScholars and practitioners may benefit the most from this research by obtaining insight into the development of JHTI's research and the areas of the hospitality and tourism industries that need more study.Originality/valueThe current study is both necessary and valuable because it is the first to provide insight into the effectiveness and intellectual framework of the hospitality and tourism literature selected by the JHTI.

Opportunities and Required Skills in Data-Driven Jobs: Empirical Evidence from Indian Job Markets

The COVID-19 pandemic has forced us to restrict human physical interaction;given this context, the demand for artificial intelligence (AI) and robots is likely to increase in the future. Moreover, the current recession due to the pandemic and global lockdown restrictions has impacted job markets worldwide. Nevertheless, technology enthusiasts believe that the market will see increased job demand in the domain of analytics in the future, and interestingly, this field has grown exponentially in the recent past, triggering high demand for analytics professionals. This study examines the skill sets for prospective data analytics professionals and maps them based on various job profiles offered to data science professionals and provides a comprehensive picture of the data science landscape and alleviates the misconceptions of students and gives them the right perspective. The study also provides detailed insights on the jobs available to analytics professionals across profiles, places, and companies specifically in the Indian context.

A QGIS plugin for BONDS project: integrating field data with geographical, remote sensing and health information

Open source Geographic Information System (GIS) have been fostering spatial data research such as Earth observation and environmental monitoring for more than 30 years. More recently, globally available geospatial information combined with web technologies are providing new environments and tools for data handling. Thus, binding the mapping and processing capabilities of traditional GIS to the accessibility and reliability of web-based data providers can bring new opportunities for research. In this paper, we built a QGIS plugin to explore the integration of different public data providers in Brazil along with field data produced by the BONDS project. The biOdiversity conservatioN with Development in Amazon wetlandS project (BONDS) proposes to develop biodiversity scenarios for the Amazonian floodplains aiming to support solutions to preserve biodiversity and ecosystem services. The use of web services enabled dynamic and fast access to several products ranging from remote sensing images, land use and land cover, territorial cartography, water quality, to COVID-19 health data, and more. © 2022 National Institute for Space Research, INPE. All rights reserved.

Feasibility of Remote Mapping and Clinical Support Using Novel Software

Background: Covid redefined how the world functions. The electrophysiology (EP) community identified multiple needs that arose due to this paradigm and redefined workflows. The geographic paucity of experienced clinical mapping support was a crucial issue that limited the worldwide adoption of complex ablation procedures. Objective(s): To ascertain the feasibility and safety of utilizing a novel software for remote mapping and remote clinical support for all spectrums of cardiac ablation procedures and to compare the adoption of ablation technology in that geography. Method(s): Ablation procedures performed at Metromed International Cardiac Centre (MICC), India were included in this early feasibility analysis (EFA). All procedures were performed by a single EP operator. Remote Clinical support was provided by an EP physician (primary operator's sibling) in the USA. All mapping was performed by an experienced mapper from a remote location 400 miles away from the primary EP operator in India. The mapping system utilized was Ensite Precision with SJM Connect software. Result(s): 300 contiguous ablation procedures from 2020 to 2022 were included in this EFA. The proprietory SJM Connect software allows remote access to the Ensite console via a secured connection. The software requires the operator to be granted access to the Ensite console via a permission request that must be acknowledged on the Ensite Console. The software will then allow the remote operator to levels of access to the system, view-only access, or complete control of the console to provide full remote support. Communication occurs between the remote user and the console via a chat function and over a voice call. This remote connection can be terminated at any time from either the console or the remote operator. There is no PHI displayed. Results detailing case demographics and acute procedural success and safety will be presented. Results comparing the adoption of ablation technology with the previous 3 years in this geography will be presented. Conclusion(s): This EFA demonstrates the safety and efficacy of using remote clinical support and remote mapping for ablation procedures. This opens a world of possibilities including the expansion of ablation technology to all corridors of the world with experienced clinical and mapping support connecting the EP community on a worldwide platform. Additional studies and strategies are needed to further understand the implication of remote support algorithms in bridging the healthcare gaps in the field of cardiac EP. [Formula presented]Copyright © 2023

Urban restaurants and online food delivery during the COVID-19 pandemic: a spatial and socio-demographic analysis

In this research, we analyzed the delivery service areas of restaurants, customer satisfaction, and restaurant sales of urban restaurants during the COVID-19 pandemic. We obtained the datasets on food ordering options and restaurant rankings based on Google Maps, Open Street Map, and widely known online food order applications in Iran. Based on this analysis we further modeled suitable areas for future extension of restaurants. We analyzed the online food order data of restaurants' sales and food delivery reports for 1050 restaurants in the city of Tabriz. We collected and analyzed data on the restaurant locations, the number of food orders for each restaurant, and the number of customers and their locations. Our results revealed that the spatial dimension of the newly emerging food delivery areas is of utmost importance for the success of restaurants. This indicates that an optimal location is not longer only dependent on factors like population density and competitors in the direct vicinity but on the services density even from more distant competitors. The results indicate that an optimized spatial distribution of the restaurants together with efficient quality in services can contribute to optimistic urban development. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.