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2022 ◽  
Vol 13 (2) ◽  
pp. 1-23
Author(s):  
Han Bao ◽  
Xun Zhou ◽  
Yiqun Xie ◽  
Yingxue Zhang ◽  
Yanhua Li

Estimating human mobility responses to the large-scale spreading of the COVID-19 pandemic is crucial, since its significance guides policymakers to give Non-pharmaceutical Interventions, such as closure or reopening of businesses. It is challenging to model due to complex social contexts and limited training data. Recently, we proposed a conditional generative adversarial network (COVID-GAN) to estimate human mobility response under a set of social and policy conditions integrated from multiple data sources. Although COVID-GAN achieves a good average estimation accuracy under real-world conditions, it produces higher errors in certain regions due to the presence of spatial heterogeneity and outliers. To address these issues, in this article, we extend our prior work by introducing a new spatio-temporal deep generative model, namely, COVID-GAN+. COVID-GAN+ deals with the spatial heterogeneity issue by introducing a new spatial feature layer that utilizes the local Moran statistic to model the spatial heterogeneity strength in the data. In addition, we redesign the training objective to learn the estimated mobility changes from historical average levels to mitigate the effects of spatial outliers. We perform comprehensive evaluations using urban mobility data derived from cell phone records and census data. Results show that COVID-GAN+ can better approximate real-world human mobility responses than prior methods, including COVID-GAN.


2022 ◽  
Vol 11 (2) ◽  
pp. 653-661
Author(s):  
Yong-Jik Lee ◽  
Robert Davis* ◽  
Yue Li

<p style="text-align: justify;">Most research has examined flipped learning within the context of face-to-face (F2F) instruction. However, previous research has not effectively explored the possibility of how online synchronous flipped learning influences pre-service teachers (PSTs) in teacher education programs during Coronavirus disease (COVID-19). Recognizing the gap in the literature, this paper explored three aspects of online synchronous flipped learning by understanding 1) PSTs' learner engagement, 2) self-directed learning, and 3) learner satisfaction in a Korean university. The data was collected from Korean PST's interviews, reflection notes, and course evaluations. The thematic analysis was used to analyze qualitative data sources. The study findings showed that PSTs favored a synchronous online FL because it encouraged them to engage in various collaborative activities through Zoom breakout sessions. Also, pre-class materials from online FL can positively enhance the PSTs' self-directed learning process. Based on these findings, this study provides suggestions on how to effectively implement online synchronous flipped learning in teacher education programs.</p>


2022 ◽  
Vol 18 (2) ◽  
pp. 0-0

The purpose of the study is to elucidate linkage of Omnichannel retail business model with innovation and technological advancements. The study is exploratory and qualitative in nature, based on primary and secondary data sources collected from varied retail sectors such as fashion, furniture, eyecare and electronics . The study has used Business Model Canvass (BMC) as a tool for strategic analysis. The study presents findings about business model and strategies in Omnichannel context from Indian retailers. The findings of the study posits four main dimensions resultant of digitalization and technological advancements in Omnichannel retail, namely Omnichannel Intensity, Organizational Structure Integration, Operations and Supply Chain Management Innovation, Data Analytics and Intelligence. Cross-channel Integration and Data Analytics & Intelligence have been found to be contributing enormously towards the strategic growth of Omnichannel retailers, thus emerging as the prominent managerial implications of the study.


Genus ◽  
2022 ◽  
Vol 78 (1) ◽  
Author(s):  
Helena Cruz Castanheira ◽  
José Henrique Costa Monteiro da Silva

AbstractThe production, compilation, and publication of death registration records is complex and usually involves many institutions. Assessing available data and the evolution of the completeness of the data compiled based on demographic techniques and other available data sources is of great importance for countries and for having timely and disaggregated mortality estimates. In this paper, we assess whether it is reasonable, based on the available data, to assume that there is a sex difference in the completeness of male and female death records in Peru in the last 30 years. In addition, we assess how the gap may have evolved with time by applying two-census death distribution methods on health-related registries and analyzing the information from the Demographic and Health Surveys and civil registries. Our findings suggest that there is no significant sex difference in the completeness of male and female health-related registries and, consequently, the sex gap currently observed in adult mortality estimates might be overestimated.


2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Kavita Singh ◽  
Qingfeng Li ◽  
Karar Zunaid Ahsan ◽  
Sian Curtis ◽  
William Weiss

Abstract Background Many low- and middle-income countries cannot measure maternal mortality to monitor progress against global and country-specific targets. While the ultimate goal for these countries is to have complete civil registrations systems, other interim strategies are needed to provide timely estimates of maternal mortality. Objective The objective is to inform on potential options for measuring maternal mortality. Methods This paper uses a case study approach to compare methodologies and estimates of pregnancy-related mortality ratio (PRMR)/maternal mortality ratio (MMR) obtained from four different data sources from similar time periods in Bangladesh, Mozambique, and Bolivia—national population census; post-census mortality survey; household sample survey; and sample vital registration system (SVRS). Results For Bangladesh, PRMR from the 2011 census falls closely in line with the 2010 household survey and SVRS estimates, while SVRS’ MMR estimates are closer to the PRMR estimates obtained from the household survey. Mozambique's PRMR from household survey method is comparable and shows an upward trend between 1994 and 2011, whereas the post-census mortality survey estimated a higher MMR for 2007. Bolivia's DHS and post-census mortality survey also estimated comparable MMR during 1998–2003. Conclusions Overall all these data sources presented in this paper have provided valuable information on maternal mortality in Bangladesh, Mozambique, and Bolivia. It also outlines recommendations to estimate maternal mortality based on the advantages and disadvantages of several approaches. Contribution Recommendations in this paper can help health administrators and policy planners in prioritizing investment for collecting reliable and contemporaneous estimates of maternal mortality while progressing toward a complete civil registration system.


2022 ◽  
Vol 4 (1) ◽  
Author(s):  
Pavel P Kuksa ◽  
Yuk Yee Leung ◽  
Prabhakaran Gangadharan ◽  
Zivadin Katanic ◽  
Lauren Kleidermacher ◽  
...  

ABSTRACT Querying massive functional genomic and annotation data collections, linking and summarizing the query results across data sources/data types are important steps in high-throughput genomic and genetic analytical workflows. However, these steps are made difficult by the heterogeneity and breadth of data sources, experimental assays, biological conditions/tissues/cell types and file formats. FILER (FunctIonaL gEnomics Repository) is a framework for querying large-scale genomics knowledge with a large, curated integrated catalog of harmonized functional genomic and annotation data coupled with a scalable genomic search and querying interface. FILER uniquely provides: (i) streamlined access to &gt;50 000 harmonized, annotated genomic datasets across &gt;20 integrated data sources, &gt;1100 tissues/cell types and &gt;20 experimental assays; (ii) a scalable genomic querying interface; and (iii) ability to analyze and annotate user’s experimental data. This rich resource spans &gt;17 billion GRCh37/hg19 and GRCh38/hg38 genomic records. Our benchmark querying 7 × 109 hg19 FILER records shows FILER is highly scalable, with a sub-linear 32-fold increase in querying time when increasing the number of queries 1000-fold from 1000 to 1 000 000 intervals. Together, these features facilitate reproducible research and streamline integrating/querying large-scale genomic data within analyses/workflows. FILER can be deployed on cloud or local servers (https://bitbucket.org/wanglab-upenn/FILER) for integration with custom pipelines and is freely available (https://lisanwanglab.org/FILER).


2022 ◽  
Vol 3 (4) ◽  
Author(s):  
Inez Cara Alexander Phoek

Community economic empowerment is an important approach to realize a balanced, developing and just economic structure, to realize a successful economic empowerment, community business capacity must become strong and independent, and in sync with community’s best potential and product, in this paper is coastal community. The purpose of this study is how the main strategies and work programs that need to be taken to improve the economy of the community in Merauke Regency by optimally utilizing coastal community resources and knowing the inhibiting and supporting factors of empowerment. Qualitative research method with a SWOT analysis tool with a focus on data sources based on the results of interviews and discussions with the fisheries service and fisheries business actors. The results of the study explain that the increase in fisherman productivity has the highest weight value which is carried out by increasing the role of capital assistance and market intervention, verified by the efforts of coastal communities.


2022 ◽  
Vol 14 (2) ◽  
pp. 908
Author(s):  
Elyakim Ben-Hakoun ◽  
Eddy Van De Voorde ◽  
Yoram Shiftan

Located in the Middle East, Haifa Port serves both local and international trade interests (from Asia, Europe, America, Africa, etc.). Due to its strategic location, the port is part of the Belt and Road initiative. This research investigates Haifa Port’s emissions contribution to the existing daily emission inventory level in the area. This research is based on a developed full bottom-up model framework that looks at the single vessel daily voyage through its port call stages. The main data sources for vessel movements used in this research are the Israel Navy’s movements log and the Israel Administration of Shipping and Ports’ (ASP) operational vessel movements and cargo log. The Fuel Consumption (FC) data and Sulfur Content (SC) levels are based on official Israel ASP survey data. The observation years in this research are 2010–2018, with a focus on the Ocean-Going Vessel (OGV) type only. The results show that the vessel fleet calling at Israel ports mainly comprises vessels that have a lower engine tier grade (i.e., Tier 0 and 1), which is considered a heavy contributor to nitrogen oxide (NOx) pollution. The study recommends an additional cost charged (selective tariff) to reflect the external social cost linked to the single vessel air pollution combined with supportive technological infrastructure and economic incentive tools (e.g., electric subsidy) to attract or influence vessel owners to assign vessels equipped with new engine tier grades for calls at Israeli ports.


2022 ◽  
Vol 12 ◽  
Author(s):  
Lisiane Freitas Leal ◽  
Claudia Garcia Serpa Osorio-de-Castro ◽  
Luiz Júpiter Carneiro de Souza ◽  
Felipe Ferre ◽  
Daniel Marques Mota ◽  
...  

Background: In Brazil, studies that map electronic healthcare databases in order to assess their suitability for use in pharmacoepidemiologic research are lacking. We aimed to identify, catalogue, and characterize Brazilian data sources for Drug Utilization Research (DUR).Methods: The present study is part of the project entitled, “Publicly Available Data Sources for Drug Utilization Research in Latin American (LatAm) Countries.” A network of Brazilian health experts was assembled to map secondary administrative data from healthcare organizations that might provide information related to medication use. A multi-phase approach including internet search of institutional government websites, traditional bibliographic databases, and experts’ input was used for mapping the data sources. The reviewers searched, screened and selected the data sources independently; disagreements were resolved by consensus. Data sources were grouped into the following categories: 1) automated databases; 2) Electronic Medical Records (EMR); 3) national surveys or datasets; 4) adverse event reporting systems; and 5) others. Each data source was characterized by accessibility, geographic granularity, setting, type of data (aggregate or individual-level), and years of coverage. We also searched for publications related to each data source.Results: A total of 62 data sources were identified and screened; 38 met the eligibility criteria for inclusion and were fully characterized. We grouped 23 (60%) as automated databases, four (11%) as adverse event reporting systems, four (11%) as EMRs, three (8%) as national surveys or datasets, and four (11%) as other types. Eighteen (47%) were classified as publicly and conveniently accessible online; providing information at national level. Most of them offered more than 5 years of comprehensive data coverage, and presented data at both the individual and aggregated levels. No information about population coverage was found. Drug coding is not uniform; each data source has its own coding system, depending on the purpose of the data. At least one scientific publication was found for each publicly available data source.Conclusions: There are several types of data sources for DUR in Brazil, but a uniform system for drug classification and data quality evaluation does not exist. The extent of population covered by year is unknown. Our comprehensive and structured inventory reveals a need for full characterization of these data sources.


Semantic Web ◽  
2022 ◽  
pp. 1-24
Author(s):  
Marlene Goncalves ◽  
David Chaves-Fraga ◽  
Oscar Corcho

With the increase of data volume in heterogeneous datasets that are being published following Open Data initiatives, new operators are necessary to help users to find the subset of data that best satisfies their preference criteria. Quantitative approaches such as top-k queries may not be the most appropriate approaches as they require the user to assign weights that may not be known beforehand to a scoring function. Unlike the quantitative approach, under the qualitative approach, which includes the well-known skyline, preference criteria are more intuitive in certain cases and can be expressed more naturally. In this paper, we address the problem of evaluating SPARQL qualitative preference queries over an Ontology-Based Data Access (OBDA) approach, which provides uniform access over multiple and heterogeneous data sources. Our main contribution is Morph-Skyline++, a framework for processing SPARQL qualitative preferences by directly querying relational databases. Our framework implements a technique that translates SPARQL qualitative preference queries directly into queries that can be evaluated by a relational database management system. We evaluate our approach over different scenarios, reporting the effects of data distribution, data size, and query complexity on the performance of our proposed technique in comparison with state-of-the-art techniques. Obtained results suggest that the execution time can be reduced by up to two orders of magnitude in comparison to current techniques scaling up to larger datasets while identifying precisely the result set.


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