| 1. |
- Lozano, Rafael, et al.
(författare)
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Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - : Elsevier. - 1474-547X .- 0140-6736. ; 392:10159, s. 2091-2138
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Tidskriftsartikel (refereegranskat)abstract
- Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.
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| 2. |
- Usman, Muhammad, et al.
(författare)
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A Blockchain based Scalable Domain Access Control Framework for Industrial Internet of Things
- 2024
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Ingår i: IEEE Access. - : IEEE. - 2169-3536.
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Tidskriftsartikel (refereegranskat)abstract
- Industrial Internet of Things (IIoT) applications consist of resource constrained interconnected devices that make them vulnerable to data leak and integrity violation challenges. The mobility, dynamism, and complex structure of the network further make this issue more challenging. To control the information flow in such environments, access control is critical to make collaboration and communication safe. To deal with these challenges, recent studies employ attribute-based access control on top of blockchain technology. However, the attribute-based access control frameworks suffer due to high computational overhead. In this paper, we propose an improved role-based access control framework using hyperledger blockchain to deal with IIoT requirements with less computational overhead making the information control process more efficient and real-time. The proposed framework leverages a layered architecture of chaincodes to implement the improved access control framework that handles the permission delegation and conflict management to deal with the dynamism of the IIoT network. The system uses a Policy Contract, Device Contract, and Access Contract to manage the workflow of the whole access control process. Each chaincode in the proposed framework is isolated in terms of its responsibilities to make the design low coupled. The integration of improved access control with blockchain enables the proposed framework to provide a highly scalable solution, tamper-proof, and flexible to manage conflicting scenarios. The proposed system outperforms the recent studies significantly in computational overhead in extensive simulation results. To verify the scalability and efficiency, the proposed is evaluated against a large number of concurrent virtual clients in simulation and statistical analysis proves that the proposed system is promising for further research in this domain.
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| 3. |
- Usman, Muhammad, et al.
(författare)
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Automatic Hybrid Access Control in SCADA-Enabled IIoT Networks Using Machine Learning
- 2023
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 23:8
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Tidskriftsartikel (refereegranskat)abstract
- The recent advancements in the Internet of Things have made it converge towards critical infrastructure automation, opening a new paradigm referred to as the Industrial Internet of Things (IIoT). In the IIoT, different connected devices can send huge amounts of data to other devices back and forth for a better decision-making process. In such use cases, the role of supervisory control and data acquisition (SCADA) has been studied by many researchers in recent years for robust supervisory control management. Nevertheless, for better sustainability of these applications, reliable data exchange is crucial in this domain. To ensure the privacy and integrity of the data shared between the connected devices, access control can be used as the front-line security mechanism for these systems. However, the role engineering and assignment propagation in access control is still a tedious process as its manually performed by network administrators. In this study, we explored the potential of supervised machine learning to automate role engineering for fine-grained access control in Industrial Internet of Things (IIoT) settings. We propose a mapping framework to employ a fine-tuned multilayer feedforward artificial neural network (ANN) and extreme learning machine (ELM) for role engineering in the SCADA-enabled IIoT environment to ensure privacy and user access rights to resources. For the application of machine learning, a thorough comparison between these two algorithms is also presented in terms of their effectiveness and performance. Extensive experiments demonstrated the significant performance of the proposed scheme, which is promising for future research to automate the role assignment in the IIoT domain.
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| 4. |
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| 5. |
- Shah, Shahid, et al.
(författare)
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Assessment of health-related quality of life among patients with obesity, hypertension and type 2 diabetes mellitus and its relationship with multimorbidity
- 2023
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 18:8
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Tidskriftsartikel (refereegranskat)abstract
- Obesity, hypertension (HTN) and type 2 diabetes (T2D) are among the multifactorial disorders that occur at higher prevalence in a population. This study aims to assess the health-related quality of life (HRQoL) of patients with obesity, HTN and T2D individually and in the form of multimorbidity. A questionnaire-based cross-sectional study was conducted among the patients in 15 private clinics of Punjab, Pakistan. A stratified random sampling technique was used to collect the data from patients with obesity, HTN and T2D or their comorbidity. A total of 1350 patients responded by completing the questionnaire. The HRQoL of these patients was assessed using the EQ-5D-5L questionnaire (a standardized instrument for measuring generic health status). Statistical analysis was performed using chi-square test, Mann-Whitney U test, and Kruskal-Wallis test. Multivariate linear regression model was used to model the visual analogue scale (VAS) score. In total, 15% of patients had combined obesity, HTN and T2D; 16.5% had HTN and T2D; 13.5% had obesity and HTN and 12.8% had obesity and T2D. Only 15.8% of patients had obesity, 14.3% had HTN, and 12% had T2D. Mann Whitney-U test gave the statistically significant (p = <0.001) HRQoL VAS score55.1 (±23.2) of patients with the obesity. HRQoL VAS scores of patients with obesity were found to be higher when compared to patients with both T2D 49.8 (±15.4) and HTN 48.2 (±21). Diagnosis of one, two and three diseases showed significant results in VAS with all variables including gender (p = 0.004), educational level (p = <0.001), marital status (p<0.001), residence (p = <0.001), financial situation (p = <0.001) and monthly income (p = <0.001). The most frequently observed extremely problematic dimension was anxiety/ depression (47%) and the self-care (10%) was the least affected. Patient HRQoL is decreased by T2D, HTN, and obesity. The impact of these diseases coexisting is more detrimental to HRQoL.
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| 6. |
- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 7. |
- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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