CCCORE: Cloud Container for Collaborative Research

Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high- performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on–demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources

A Novel Intelligence-based e-Procurement System to offer Maximum Fairness Index in Ongoing Auction Process

A perfect auction policy is one of the most strategic elements that contribute to success factor for any e-Procurement system. An auction policy can be only term as an effective if it really offer win-win situation to both the bidder as well as to the merchant. After reviewing existing studies on e-Procurement system, it is found that there isno effective research work focusing on this point and maximum research contribution has limited its scope to certain application or case studis. Hence, the proposed system introduces a novel e-Procurement system which is equipped by an itelligence-building process for performing predictive analysis of ongoing auction process. A mathematical modelling is implemented where all teh variables have been formed using practical implementation of auction system and followed by optimization process using regression-based approach. The study outcome shows that proposed system offers better response time and higher predictive accuracy in contrast to existing approaches

Insights on Extent of Effectiveness, Trend, and Gap in Existing Frameworks for e-Procurement System

With the advancement of technologies, the organization and business applications are witnessed with the increasing trends to adopt cut edge technologies to normalize their business process.  However, this trend was not observed much on the e-Procurement system, where the existing users still place the purchase order using conventional web-based approach that cannot address various ongoing challenges in eProcurement system. This paper attempts to review the existing trends and challenges of web-based eProcurement system and discusses that with the adoption of cloud computing as present trend, such ongoing issues of eProcurement can be addressed. The paper discusses the effectiveness of the existing techniques with interpretation of research gap

Modelling of E-Governance Framework for Mining Knowledge from Massive Grievance Redressal Data

With the massive proliferation of online applications for the citizens with abundant resources, there is a tremendous hike in usage of e-governance platforms. Right from entrepreneur, players, politicians, students, or anyone who are highly depending on web-based grievance redressal networking sites, which generates loads of massive grievance data that are not only challenging but also highly impossible to understand. The prime reason behind this is grievance data is massive in size and they are highly unstructured. Because of this fact, the proposed system attempts to understand the possibility of performing knowledge discovery process from grievance Data using conventional data mining algorithms. Designed in Java considering massive number of online e-governance framework from civilian’s grievance discussion forums, the proposed system evaluates the effectiveness of performing datamining for Big data

Setting our sights on infectious diseases

In May 2019, the Wellcome Centre for Anti-Infectives Research (WCAIR) at the University of Dundee, UK, held an international conference with the aim of discussing some key questions around discovering new medicines for infectious diseases and a particular focus on diseases affecting Low and Middle Income Countries. There is an urgent need for new drugs to treat most infectious diseases. We were keen to see if there were lessons that we could learn across different disease areas and between the preclinical and clinical phases with the aim of exploring how we can improve and speed up the drug discovery, translational, and clinical development processes. We started with an introductory session on the current situation and then worked backward from clinical development to combination therapy, pharmacokinetic/pharmacodynamic (PK/PD) studies, drug discovery pathways, and new starting points and targets. This Viewpoint aims to capture some of the learnings

Estimating global injuries morbidity and mortality: methods and data used in the Global Burden of Disease 2017 study

BACKGROUND: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future

Estimating global injuries morbidity and mortality : methods and data used in the Global Burden of Disease 2017 study

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.Peer reviewe

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe

Socialization, legitimation and the transfer of biomedical knowledge to low- and middle-income countries: analyzing the case of emergency medicine in India

BACKGROUND: Medical specialization is a key feature of biomedicine, and is a growing, but weakly understood aspect of health systems in many low- and middle-income countries (LMICs), including India. Emergency medicine is an example of a medical specialty that has been promoted in India by several high-income country stakeholders, including the Indian diaspora, through transnational and institutional partnerships. Despite the rapid evolution of emergency medicine in comparison to other specialties, this specialty has seen fragmentation in the stakeholder network and divergent training and policy objectives. Few empirical studies have examined the influence of stakeholders from high-income countries broadly, or of diasporas specifically, in transferring knowledge of medical specialization to LMICs. Using the concepts of socialization and legitimation, our goal is to examine the transfer of medical knowledge from high-income countries to LMICs through domestic, diasporic and foreign stakeholders, and the perceived impact of this knowledge on shaping health priorities in India. METHODS: This analysis was conducted as part of a broader study on the development of emergency medicine in India. We designed a qualitative case study focused on the early 1990s until 2015, analyzing data from in-depth interviewing (n = 87), document review (n = 248), and non-participant observation of conferences and meetings (n = 6). RESULTS: From the early 1990s, domestic stakeholders with exposure to emergency medicine in high-income countries began to establish Emergency Departments and initiate specialist training in the field. Their efforts were amplified by the active legitimation of emergency medicine by diasporic and foreign stakeholders, who formed transnational partnerships with domestic stakeholders and organized conferences, training programs and other activities to promote the field in India. However, despite a broad commitment to expanding specialist training, the network of domestic, diasporic and foreign stakeholders was highly fragmented, resulting in myriad unstandardized postgraduate training programs and duplicative policy agendas. Further, the focus in this time period was largely on training specialists, resulting in more emphasis on a medicalized, tertiary-level form of care. CONCLUSIONS: This analysis reveals the complexities of the roles and dynamics of domestic, diasporic and foreign stakeholders in the evolution of emergency medicine in India. More research and critical analyses are required to explore the transfer of medical knowledge, such as other medical specialties, models of clinical care, and medical technologies, from high-income countries to India