Online Data Sources Research Articles

Regional resilience for rail freight transport

This paper applies the concept of resilience to the rail freight industry, taking a regional perspective and considering the disturbances that have affected demand over a six year period from 2015 to 2021. This contrasts with many existing studies relating to rail freight which look at managerial factors or only consider short term disruptions. To overcome issues with data availability, four sample weeks were surveyed using online data sources, supplemented by secondary sources. Using the Cardiff Capital Region in Great Britain as an example, we show how the rail freight industry is particularly affected by disturbances in other sectors, due to the connecting role it plays, but also that some new growth paths have emerged. The number of trains operated decreased by 30% over the six year period, with significant declines in coal and automotive traffic following the closure of sources for freight. By contrast, intermodal has seen growth, due to wider economic conditions as well as policy disturbances. The study builds on existing rail freight research, the resilience perspective effectively highlighting that external disturbances affect demand over the long term. Such insights are valuable for regional transport policy makers, who often lack awareness of freight and logistics, as well as practitioners in engaging with regional bodies.

Digital artifacts reveal development and diffusion of climate research

Research for development organizations generate tremendous amount of accessible knowledge, but given their scale, time and resource constraints, the impact of outputs is not systematically analyzed. This is because traditional bibliometric analyses present limitations to synthesize accumulated knowledge and retrofitting indicators to historical outputs. To address these shortcomings, this study proposes an integrated, web-based approach to systematically analyze the production and diffusion of knowledge from large-scale research programs, using climate research of the International Maize and Wheat Improvement Center (CIMMYT) as a case study. Our analytical framework employs text mining, social network analysis and hyperlink analysis to an unstructured mass of publicly available digital artifacts such as institutional repositories, citation databases, and social media to uncover narratives, dynamics, and relationships. Findings show CIMMYT’s climate research is strongly incorporated into a holistic systems approach and that the institution is actively engaged in knowledge exchanges with key actors from the scientific, development and public policy communities. The proposed analytical framework establishes an effective approach for research for development organizations to leverage existing online data sources to assess the extent of their knowledge production, dissemination, and reach.

Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis

AbstractAimGorgonian forests are among the most complex of subtidal habitats in the Mediterranean Sea, supporting high biodiversity and providing diverse ecosystem services. Despite their iconic status, the geographical distribution and condition of gorgonian species is poorly known. Using multiple online data sources, our primary aims were to compile, map and analyse observations of gorgonian forests in Italian coastal waters to assess the biological complexity of gorgonian forests, evaluate impacts and vulnerable species, and identify areas of special interest inside and outside of marine protected areas (MPAs) to help prioritize conservation strategies and actions.LocationItaly. Mediterranean Sea.MethodsUsing a multi‐source data integration approach, we collected and integrated data from scientific publications, the World Wide Web including social media platforms, citizen science projects and SCUBA diver questionnaires into a unified spatial framework. This method provided up‐to‐date information on the geographical distribution, abundance, and health of major habitat‐forming gorgonian species in Italian coastal waters.ResultsHigher abundance and complexity of gorgonian species occurred outside MPAs. Areas of Special Interest (n = 167) were identified (80 inside and 87 outside MPAs). Three locations supported all seven focal species: Capo Caccia MPA, Portofino MPA and Catania (unprotected). The purple gorgonian (Paramuricea clavata), the most abundant and geographically widespread species with highest forest complexity, was affected by multiple stressors including thermal stress, disease and fishing.Main conclusionsThe multi‐source approach was a rapid and cost‐effective tool to gather, analyse and map disparate data on gorgonian forests spanning 27 years of underwater observations both inside and outside of MPAs. The unique perspective given by this approach demonstrates the suboptimal protection of several habitat‐forming gorgonian species. The approach has great potential for wider application and offers a more inclusive participatory model for crowdsourcing and repurposing under‐utilized observations while also increasing ocean literacy.

Behavioural mapping and online data as tools for socio-spatial analysis of public spaces – Bratislava, Slovakia waterfront case study

Abstract Renewal, revitalisation, or reconstruction of public spaces is an inevitable part of the urban dynamics process. However, before any decision of future development is made, it is necessary to be acquainted with the given place. Mapping urban spaces is essential for recognizing the specifics of a certain area, while a relevant analysis should be performed on the basis of multiple data sources. Nonetheless, identification of relevant data sources as well as their limits, which need to be considered, represent challenges in the process. The study aims to highlight the importance of socio-spatial analyses as tools which help to familiarize place makers with public space as well as with the small nuances of its everyday functioning. Relevant online data sources for urban space analysis (Instasights, Strava) and their limits were explored, described, and applied to the area of interest - two banks of the Danube riverfront in Bratislava, Slovakia. The method was supplemented by mapping of human movement and behaviour. The combination of the methods is a relatively fast and simple way to get to know the spatial, social, environmental, aesthetic, and other dimensions of the given space. The interpretation of data illustrates possible outcomes that can be gained through mapping of public spaces before changes or development plans are proposed. Hence, the paper contributes to the repertory of the possible sources of online data that can be used for recognizing the specific characteristics of individual public spaces. This contributes to responsible decision-making about the future of the urban environment, built on data-based arguments. Highlights for public administration, management and planning: • Online data represents a valuable source of city-related information as well as a relevant addition to other mapping methods. • Mapping an area of interest is a necessary step of the data-based planning process and should always precede any development of urban spaces. • A combination of data from various data sources which reflect life in public space can support user-oriented planning and contribute to responsible decision making.

Drivers of Data Quality in Advertising Research: Differences across MTurk and Professional Panel Samples

Crowdsourcing has emerged as a preferred data collection methodology for advertising and social science researchers because these samples avoid the higher costs associated with professional panel data. Yet, there are ongoing concerns about data quality for online sources. This research examines differences in data quality for an advertising experiment across five popular online data sources, including professional panels and crowdsourced platforms. Effects of underlying mechanisms impacting data quality, including response satisficing, multitasking, and effort, are examined. As proposed, a serial mediation model shows that data source is, directly and indirectly, related to these antecedents of data quality. Satisficing is positively related to multitasking and negatively related to effort, and both mediators (in parallel) extend to data quality, indicating that the indirect effects on data quality through these mediating variables are significant. In general, a vetted MTurk sample (i.e., CloudResearch Approved) produces higher quality data than the other four sources. Regardless of the data source, researchers should utilize safeguards to ensure data quality. Safeguards and other strategies to obtain high-quality data from online samples are offered.

Managing Higher Education in Pandemic Era in the Challenge of Education Quality and Equity

The article is to examine several pieces of evidence from previous studies to understand higher education governance in the crisis-era related to the challenges of achieving equal distribution of education quality. Data collection involves searching for many published articles, including journals, books, magazines, and websites that discuss higher education governance issues regarding quality and opportunity. The data analysis involves a comprehensive evaluation data coding system, critical interpretation, and comprehensive and high decision making. The data search is done with the help of technology, especially online data sources using keywords such as the quality of higher education, equal opportunity. Based on the findings, explanations, and discussions, we can summarize that the governance of higher education in the crisis era faces various challenges related to equity and the achievement of high quality. When a crisis occurs, the changes are significant, and they cannot carry out various obligations and intellectual rights so that they ignore the quality and equity of higher education. Therefore, this study recommends that high fences be managed by emphasizing finding solutions to address the challenges of service quality and equity by following guidelines and regulations in force in many countries. It is hoped that this study will become an essential input to solve the challenges of higher education afflicted by various crises.
 Keywords: Education Quality and Equity, Managing Higher Education, Education in Pandemic Era

Emotional and Cognitive Impairment among Cardiac Patients - A Narrative Review

Cardiovascular disease is a major group of contributing 31% of global mortality rate. The lifestyle changes are the key role to develop such diseases. The cardiovascular diseases are altering the life style practices and need to change their routine life style. There are many related co morbidities that may arise after the cardiac event. In which the emotional and cognitive co morbidities are making further risk to the subsequent cardiac event. Therefore the correct and prompt treatment is needed for the prevention of the co morbidities. The main aim of this narrative review is to find out the burden of emotional and cognitive impairment and to find out the effect of relaxation technique on the reduction of the emotional and cognitive impairment among cardiac patients. Mainly the online data sources including PubMed, PubMed central, Cochrane, Medline, Google scholar were searched for the related studies. The main emotional imbalance are depression and stress. In which depression is contributing the major role among cardiac patients. The major pathophysiological changes after myocardial infarction that lea to the emotional and cognitive symptoms are due to the reduced blood supply to brain and the anaerobic metabolism. There are different complimentary therapies are there for the management of the emotional co morbidities. In which the relaxation therapy is very useful therapy in the emotional imbalance management.

Open data and model integration through generic model agent toolkit in CyberWater framework

The CyberWater project is created to develop an open data and open model integration framework for studying complex environmental and water problems, where diverse online data sources can be directly accessed by diverse models without any need of users’ extra effort on the tedious tasks of data preparation for their models. We present our design and development of a novel generic model agent toolkit in the context of CyberWater, which enables users to integrate their models into the CyberWater system without writing any new code, significantly simplifying the data and model integration task. CyberWater adopts a visual scientific workflow system, VisTrails, which also supports provenance and reproducible computing. Our approach and the developed generic model agent toolkit are demonstrated, via CyberWater framework, with automated and flexible workflows through integrating data and models using real-world use cases. Two popular hydrological models, VIC and DHSVM, are used for illustrations.

Covid-19 Disaster Management Through Websites and Social Media Regency/City Government in the Special Region of Yogyakarta

The severity of criticism in handling the COVID-19 pandemic has made local governments turn to information and communication technology to back up various important information in mitigating the handling of COVID-19. Although the district/city government in Yogyakarta has taken advantage of digitalization in the operation of its government system, it is still a question mark whether the district/city local government can utilize websites and social media as a means and media for handling COVID -19 effectively and efficiently mapping COVID-19 data. And socialization of its handling to the community. The research method used is descriptive qualitative research to obtain comprehensive data related to disaster management through websites and social media by the district/city government in Yogyakarta. The results show that the use of websites and social media by the Sleman Regency Government and Yogyakarta City Government to mitigate the COVID-19 pandemic is utilizing online data sources for early detection of disease; in the form of notification of diagnosed cases, data visualization tools for decision support, namely the use of collecting public health data in real-time, as well as the use of public communications related to the mitigation of the covid-19 pandemic. The conclusion obtained is that the use of pages and social media used by the Sleman Regency Government and the Yogyakarta City Government has similarities in their use, both back office, and front office. However, there are differences in information content both on the page and on social media users.

Big Data Analysis of Covid-19 Spread Based on Distribution Map and Protocol Regulations with Business Intelligence

Various parties analyze the total cases of the Corona virus every day to prevent a high level of spread. Big Data technology involves data that is diverse, rapidly changing, super large in size so that conventional technology cannot be handled effectively. Four stages of processing Big Data until the output it produces is information for users, namely acquired, accessed, analytics, and application. Business Intelligence serves to transform operational, transactional data into useful information within the company. Big Data Analytics analyzes information, IDE for current and past business decisions visualized in graphical form. The problem in this study is modeled in the Big Data architecture with the aim of comparing the trend of the spread of Covid-19 related to process regulation. Based on the distribution map data and the regulation of health protocol rules with various online data sources, structured and unstructured using Business Intelligence (BI) cleaning data, three patterns of spread of the corona virus were found, High Cases, Medium Cases and Low Cases from 34 provinces throughout Indonesia. West Java Province became the first order of the highest cases during May 2021 with an average case of 21% followed by DKI Jakarta 14%.

The Perils of Estimating Disengagement Effects of Deadly Terrorist Attacks Utilizing Social Media Data

AbstractThis comment discusses the impact of social media rule enforcement protocols on research on online data sources. It argues that the conclusions of the article ‘Do Islamic State's Deadly Attacks Disengage, Deter, or Mobilize Supporters?’ concerning the recruitment effects of deadly attacks cannot be assumed to hold when considering the timing of Twitter account suspensions. It highlights four ways in which suspensions can confound evidence of demobilization despite the introduction of control variables and fixed-effects model specifications. All change the composition of the sample in four non-random ways. First, suspending connected Islamic State accounts may result in follower loss. Secondly, Twitter suspension procedures may be tied to account characteristics, such as follower accrual rates. Thirdly, suspended accounts that re-emerge introduce replication bias. Fourthly, account closure may reflect user movement to other platforms in response to changing security environments following deadly attacks. In conclusion, caution is advised when platform-introduced variation risks altering the sample composition in non-random ways.

Mixed Methodology of Scientific Research in Healthcare.

Background:Scientific research is usually classified as quantitative or qualitative. However, methodologists are increasingly emphasizing the integration of qualitative and quantitative data as the center of mixed methods (mix methodologies). Mixed research method implies the use of different research methods, ie. quantitative and qualitative methods in one study.Objective:The aim of this review paper is to present the purpose of using a mixed methodology in health research.Methods:The relevant articles were searched from online data sources including PubMed and Google Scholar.Results:This approach to the use of mixed methods creates opportunities for a deeper study of various problems. The purpose of using mixed research methods is to obtain valid answers to research questions, however the researcher may still have different reasons or purposes for which he wants to strengthen the research study and its conclusions by applying mixed methods. The use of mixed scientific methodology is widely used in the field of health outcomes and should not be limited to a closed list of possible methodological options.Conclusion:Recently, there has been an increase in the number of scientific studies in healthcare that use mixed research methods. The advantage of applying this scientific method is that through the triangulation of data obtained by different (quantitative / qualitative) approaches, we get a deeper and more complete picture of the phenomenon in health care that we observe.

Factors influencing the global distribution of the endangered Egyptian vulture

Vultures are ecologically important primarily because of their scavenging role in cleaning carcasses of the environment. Because of anthropogenic impacts, the Egyptian vulture (Neophron percnopterus) has suffered catastrophic declines in parts of its range and, thus, information about its global distribution and factors influencing its occurrence within this range are essential for its conservation. To this end, we estimated the global distribution of Egyptian vulture and variables related to this distribution. We used occurrence points (n = 4740) from online data sources and literature, environmental variables related to these sites and Maximum Entropy software to model the distribution of this species and its relationship to environmental variables during the entire year, breeding and overwintering. Out of ~ 49 million km2 study area, the Egyptian vulture had a predicted range of 6,599,508 km2 distributed across three continents: Africa, Asia and Europe. The densest distribution was in Southern Europe, India and Northern Africa and a sparser distribution was around Mid and Western Africa, the Middle East and Afghanistan. Climate was related to the vulture’s most probable range: in particular medium temperature seasonality and low precipitation during the coldest yearly quarter were important variables regardless of the season of observations examined. Conservation of identified habitats and mitigation of anthropogenic impacts to conserve these vultures are recommended for immediate and long-term conservation of the Egyptian vulture globally.

Social Networking Trend in Improving Educational Leadership Competency in Higher Learning: Systematic Data Analysis

This study examined social network trends in improving educational leadership quality and higher learning outcomes through systematic data analysis. Forward or backwards, the quality of human resources and scholarly output in the academic environment is closely related to social networking, which is increasingly becoming a phenomenon today. The researcher has carried out a series of data collection through electronic searches in several international publications in various scientific communication contexts to understand this. Furthermore, the analysis process includes understanding the study questions, coding, analysis, and in-depth interpretation to obtain valid and reliable study findings that answer this study's questions. Our e-search, especially on the Google Scholar data source, ERIC publications, and other online data sources from the 2010 to 2021 publications, was prioritized. Based on the discussion of results and observations of current social networking trends, it can be concluded that social networking brings benefits such as building social relationships, communication, keeping up with renewal, more personal relationships, more genuine connections, advertising, and other networking among educational leaders worldwide.

Covid-19 Disaster Management through Websites and Social Media Regency/City Government in the Special Region of Yogyakarta

The severity of criticism in handling the COVID-19 pandemic has made local governments turn to information and communication technology to back up various important information in mitigating the handling of COVID-19. Although the district/city government in Yogyakarta has taken advantage of digitalization in the operation of its government system, it is still a question mark whether the district/city local government can utilize websites and social media as a means and media for handling COVID -19 effectively and efficiently mapping COVID-19 data. And socialization of its handling to the community. The research method used is descriptive qualitative research to obtain comprehensive data related to disaster management through websites and social media by the district/city government in Yogyakarta. The results show that the use of websites and social media by the Sleman Regency Government and Yogyakarta City Government to mitigate the COVID-19 pandemic is utilizing online data sources for early detection of disease; in the form of notification of diagnosed cases, data visualization tools for decision support, namely the use of collecting public health data in real-time, as well as the use of public communications related to the mitigation of the covid-19 pandemic. The conclusion obtained is that the use of pages and social media used by the Sleman Regency Government and the Yogyakarta City Government has similarities in their use, both back office and front office. However, there are differences in information content both on the page and social media users.

Urohidrosis as an overlooked cooling mechanism in long-legged birds

Behavioural thermoregulation could buffer the impacts of climate warming on vertebrates. Specifically, the wetting of body surfaces and the resulting evaporation of body fluids serves as a cooling mechanism in a number of vertebrates coping with heat. Storks (Ciconiidae) frequently excrete onto their legs to prevent overheating, a phenomenon known as urohidrosis. Despite the increasingly recognised role of bare and highly vascularised body parts in heat exchange, the ecological and evolutionary determinants of urohidrosis have been largely ignored. We combine urohidrosis data from a scientifically curated media repository with microclimate and ecological data to investigate the determinants of urohidrosis in all extant stork species. Our phylogenetic generalised linear mixed models show that high temperature, humidity and solar radiation, and low wind speed, promote the use of urohidrosis across species. Moreover, species that typically forage in open landscapes exhibit a more pronounced use of urohidrosis than those mainly foraging in waterbodies. Substantial interspecific variation in temperature thresholds for urohidrosis prevalence points to different species vulnerabilities to high temperatures. This integrated approach that uses online data sources and methods to model microclimates should provide insight into animal thermoregulation and improve our capacity to make accurate predictions of climate change’s impact on biodiversity.

Analisa Big Data Penyebaran Covid-19 Berdasarkan Peta Sebaran dan Peraturan Protokol Dengan Business Intelligence (BI)

In 2020, the Province of Bali succeeded in suppressing Covid-19 without Large-Scale Social Restrictions (PSBB), with the discipline of residents carrying out the prokes appeal. Various parties are reviewing the numbers up and down the spread of the Corona virus in order to anticipate a spike in cases. Big Data technology involves data that is diverse, rapidly changing, super large in size so that conventional technology is not able to handle it effectively. Big Data has a size, speed, variety that is too extreme to be managed by conventional techniques. Four stages of processing Big Data to produce output information for users, namely acquired, accessed, analytics, and application. Business Intelligence serves to transform operational, transactional data into useful information within the company. Big Data Analytics analyzes information, identifies it for current and past business decisions visualized in graphical form. The problem in this study is modeled in the Big Data architecture with the aim of mapping the trend of the spread of Covid-19 related to process regulation. From the distribution map data and regulation of health protocol rules with various online data sources, structured and unstructured using Business Intelligence (BI) data cleansing, three patterns of the spread of the corona virus were found in High Cases, Medium Cases and Low Cases from 34 provinces throughout Indonesia. West Java Province became the first order of the highest cases during May 2021 with an average case of 21% followed by DKI Jakarta 14%.

Emotional and Cognitive Impairment Among Cardiac Patients - A Narrative Review

Cardiovascular disease is a major group of contributing 31% of global mortality rate. The lifestyle changesare the key role to develop such diseases. The cardiovascular diseases are altering the life style practices andneed to change their routine life style. There are many related co morbidities that may arise after the cardiacevent. In which the emotional and cognitive co morbidities are making further risk to the subsequent cardiacevent. Therefore the correct and prompt treatment is needed for the prevention of the co morbidities. The mainaim of this narrative review is to find out the burden of emotional and cognitive impairment and to find outthe effect of relaxation technique on the reduction of the emotional and cognitive impairment among cardiacpatients. Mainly the online data sources including PubMed, PubMed central, Cochrane, Medline, Googlescholar were searched for the related studies. The main emotional imbalance are depression and stress.In which depression is contributing the major role among cardiac patients. The major pathophysiologicalchanges after myocardial infarction that lea to the emotional and cognitive symptoms are due to the reducedblood supply to brain and the anaerobic metabolism. There are different complimentary therapies are therefor the management of the emotional co morbidities. In which the relaxation therapy is very useful therapyin the emotional imbalance management.

Rosa Damascena mill for treating adults' anxiety, depression, and stress: A systematic review and dose-response meta-analysis of randomized controlled trials.

Recent studies have reported conflicting findings on the antianxiety, antidepressant, and anti-stress properties of Rosa Damascena Mill (RDM). Therefore, the present systematic review and meta-analysis were conducted on the effects of RDM for treating anxiety, depression, and stress amongst adults. The online data sources of Cochrane Central Register of Controlled Trials, PubMed, Scopus, Web of Science, Embase, ProQuest, and Scientific Information Database were searched from inception to June 30, 2021. The randomized controlled trials (RCTs), which examined the effects of RDM (in any form of administration) on adults' anxiety, depression, and stress, were included. A random-effects model was applied to pool the data, and a total of 32 publications were included. The results of the meta-analysis revealed that administration of RDM significantly reduced state anxiety (effect size [ES]: 24, standardized mean difference [SMD]: -1.74, 95% confidence interval [CI]: -2.29, -1.20; p < .001), depression (ES: 7, SMD: -0.87, 95% CI: -1.47, -0.28; p=.004), and stress (ES: 4, SMD: -1.33, 95% CI: -1.98, -0.69; p < .001). However, the treatment had no significant effect on trait anxiety (ES: 6, weighted mean difference: -0.75, 95% CI: -1.93, 0.43; p=.214). The association between the total administration dosage and/or duration of RDM and the changes in state anxiety and depression was not dose-dependent. Most RCTs had a fair methodological quality based on the Cochrane risk of bias assessment tool. Besides, the quality of evidence ranged from very low to moderate according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Hence, further high-quality RCTs are needed to draw reliable conclusions regarding the use of RDM for treating adults' anxiety, depression, and stress.

Analysis of a Vaping-Associated Lung Injury Outbreak through Participatory Surveillance and Archival Internet Data.

The US Centers for Disease Control and Prevention alerted of a suspected outbreak of lung illness associated with using E-cigarette products in September 2019. At the time that the CDC published its alert little was known about the causes of the outbreak or who was at risk for it. Here we provide insights into the outbreak through analysis of passive reporting and participatory surveillance. We collected data about vaping habits and associated adverse reactions from four data sources pertaining to people in the USA: A participatory surveillance platform (YouVape), Reddit, Google Trends, and Bing. Data were analyzed to identify vaping behaviors and reported adverse events. These were correlated among sources and with prior reports. Data was obtained from 720 YouVape users, 4331 Reddit users, and over 1 million Bing users. Large geographic variation was observed across vaping products. Significant correlation was found among the data sources in reported adverse reactions. Models of participatory surveillance data found specific product and adverse reaction associations. Specifically, cannabidiol was found to be associated with fever, while tetrahydrocannabinol was found to be correlated with diarrhea. Our results demonstrate that utilization of different, complementary, online data sources provide a holistic view of vaping associated lung injury while augmenting traditional data sources.