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1.
  • Kinyoki, DK, et al. (författare)
  • Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017
  • 2020
  • Ingår i: Nature medicine. - : Springer Science and Business Media LLC. - 1546-170X .- 1078-8956. ; 26:5, s. 750-759
  • Tidskriftsartikel (refereegranskat)abstract
    • A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic.
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  • Abbafati, Cristiana, et al. (författare)
  • 2020
  • Tidskriftsartikel (refereegranskat)
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6.
  • Nguyen, Thanh N, et al. (författare)
  • Global Impact of the COVID-19 Pandemic on Stroke Volumes and Cerebrovascular Events: A 1-Year Follow-up.
  • 2023
  • Ingår i: Neurology. - 1526-632X. ; 100:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Declines in stroke admission, IV thrombolysis (IVT), and mechanical thrombectomy volumes were reported during the first wave of the COVID-19 pandemic. There is a paucity of data on the longer-term effect of the pandemic on stroke volumes over the course of a year and through the second wave of the pandemic. We sought to measure the effect of the COVID-19 pandemic on the volumes of stroke admissions, intracranial hemorrhage (ICH), IVT, and mechanical thrombectomy over a 1-year period at the onset of the pandemic (March 1, 2020, to February 28, 2021) compared with the immediately preceding year (March 1, 2019, to February 29, 2020).We conducted a longitudinal retrospective study across 6 continents, 56 countries, and 275 stroke centers. We collected volume data for COVID-19 admissions and 4 stroke metrics: ischemic stroke admissions, ICH admissions, IVT treatments, and mechanical thrombectomy procedures. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases.There were 148,895 stroke admissions in the 1 year immediately before compared with 138,453 admissions during the 1-year pandemic, representing a 7% decline (95% CI [95% CI 7.1-6.9]; p < 0.0001). ICH volumes declined from 29,585 to 28,156 (4.8% [5.1-4.6]; p < 0.0001) and IVT volume from 24,584 to 23,077 (6.1% [6.4-5.8]; p < 0.0001). Larger declines were observed at high-volume compared with low-volume centers (all p < 0.0001). There was no significant change in mechanical thrombectomy volumes (0.7% [0.6-0.9]; p = 0.49). Stroke was diagnosed in 1.3% [1.31-1.38] of 406,792 COVID-19 hospitalizations. SARS-CoV-2 infection was present in 2.9% ([2.82-2.97], 5,656/195,539) of all stroke hospitalizations.There was a global decline and shift to lower-volume centers of stroke admission volumes, ICH volumes, and IVT volumes during the 1st year of the COVID-19 pandemic compared with the prior year. Mechanical thrombectomy volumes were preserved. These results suggest preservation in the stroke care of higher severity of disease through the first pandemic year.This study is registered under NCT04934020.
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7.
  • Feigin, Valery L., et al. (författare)
  • Global, regional, and national burden of stroke and its risk factors, 1990-2019 : a systematic analysis for the Global Burden of Disease Study 2019
  • 2021
  • Ingår i: Lancet Neurology. - : Elsevier. - 1474-4422 .- 1474-4465. ; 20:10, s. 795-820
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. Methods We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. Findings In 2019, there were 12.2 million (95% UI 11.0-13.6) incident cases of stroke, 101 million (93.2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6.55 million (6.00-7.02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11.6% [10.8-12.2] of total deaths) and the third-leading cause of death and disability combined (5.7% [5.1-6.2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70.0% (67.0-73.0), prevalent strokes increased by 85.0% (83.0-88.0), deaths from stroke increased by 43.0% (31.0-55.0), and DALYs due to stroke increased by 32.0% (22.0-42.0). During the same period, age-standardised rates of stroke incidence decreased by 17.0% (15.0-18.0), mortality decreased by 36.0% (31.0-42.0), prevalence decreased by 6.0% (5.0-7.0), and DALYs decreased by 36.0% (31.0-42.0). However, among people younger than 70 years, prevalence rates increased by 22.0% (21.0-24.0) and incidence rates increased by 15.0% (12.0-18.0). In 2019, the age-standardised stroke-related mortality rate was 3.6 (3.5-3.8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3.7 (3.5-3.9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62.4% of all incident strokes in 2019 (7.63 million [6.57-8.96]), while intracerebral haemorrhage constituted 27.9% (3.41 million [2.97-3.91]) and subarachnoid haemorrhage constituted 9.7% (1.18 million [1.01-1.39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79.6 million [67.7-90.8] DALYs or 55.5% [48.2-62.0] of total stroke DALYs), high body-mass index (34.9 million [22.3-48.6] DALYs or 24.3% [15.7-33.2]), high fasting plasma glucose (28.9 million [19.8-41.5] DALYs or 20.2% [13.8-29.1]), ambient particulate matter pollution (28.7 million [23.4-33.4] DALYs or 20.1% [16.6-23.0]), and smoking (25.3 million [22.6-28.2] DALYs or 17.6% [16.4-19.0]). Interpretation The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.
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8.
  • Micah, Angela E., et al. (författare)
  • Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
  • 2021
  • Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 398:10308, s. 1317-1343
  • Forskningsöversikt (refereegranskat)abstract
    • Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.
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9.
  • Kinyoki, DK, et al. (författare)
  • Mapping child growth failure across low- and middle-income countries
  • 2020
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 577:7789, s. 231-
  • Tidskriftsartikel (refereegranskat)abstract
    • Childhood malnutrition is associated with high morbidity and mortality globally1. Undernourished children are more likely to experience cognitive, physical, and metabolic developmental impairments that can lead to later cardiovascular disease, reduced intellectual ability and school attainment, and reduced economic productivity in adulthood2. Child growth failure (CGF), expressed as stunting, wasting, and underweight in children under five years of age (0–59 months), is a specific subset of undernutrition characterized by insufficient height or weight against age-specific growth reference standards3–5. The prevalence of stunting, wasting, or underweight in children under five is the proportion of children with a height-for-age, weight-for-height, or weight-for-age z-score, respectively, that is more than two standard deviations below the World Health Organization’s median growth reference standards for a healthy population6. Subnational estimates of CGF report substantial heterogeneity within countries, but are available primarily at the first administrative level (for example, states or provinces)7; the uneven geographical distribution of CGF has motivated further calls for assessments that can match the local scale of many public health programmes8. Building from our previous work mapping CGF in Africa9, here we provide the first, to our knowledge, mapped high-spatial-resolution estimates of CGF indicators from 2000 to 2017 across 105 low- and middle-income countries (LMICs), where 99% of affected children live1, aggregated to policy-relevant first and second (for example, districts or counties) administrative-level units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the ambitious World Health Organization Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and progress exist across and within countries; our maps identify high-prevalence areas even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where the highest-need populations reside, these geospatial estimates can support policy-makers in planning interventions that are adapted locally and in efficiently directing resources towards reducing CGF and its health implications.
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  • Ahmadilivani, M. H., et al. (författare)
  • A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks
  • 2024
  • Ingår i: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 56:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Artificial Intelligence (AI) and, in particular, Machine Learning (ML), have emerged to be utilized in various applications due to their capability to learn how to solve complex problems. Over the past decade, rapid advances in ML have presented Deep Neural Networks (DNNs) consisting of a large number of neurons and layers. DNN Hardware Accelerators (DHAs) are leveraged to deploy DNNs in the target applications. Safety-critical applications, where hardware faults/errors would result in catastrophic consequences, also benefit from DHAs. Therefore, the reliability of DNNs is an essential subject of research. In recent years, several studies have been published accordingly to assess the reliability of DNNs. In this regard, various reliability assessment methods have been proposed on a variety of platforms and applications. Hence, there is a need to summarize the state-of-the-art to identify the gaps in the study of the reliability of DNNs. In this work, we conduct a Systematic Literature Review (SLR) on the reliability assessment methods of DNNs to collect relevant research works as much as possible, present a categorization of them, and address the open challenges. Through this SLR, three kinds of methods for reliability assessment of DNNs are identified, including Fault Injection (FI), Analytical, and Hybrid methods. Since the majority of works assess the DNN reliability by FI, we characterize different approaches and platforms of the FI method comprehensively. Moreover, Analytical and Hybrid methods are propounded. Thus, different reliability assessment methods for DNNs have been elaborated on their conducted DNN platforms and reliability evaluation metrics. Finally, we highlight the advantages and disadvantages of the identified methods and address the open challenges in the research area. We have concluded that Analytical and Hybrid methods are light-weight yet sufficiently accurate and have the potential to be extended in future research and to be utilized in establishing novel DNN reliability assessment frameworks.
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  • Ahmadilivani, M. H., et al. (författare)
  • Analysis and Improvement of Resilience for Long Short-Term Memory Neural Networks
  • 2023
  • Ingår i: Proc. IEEE Int. Symp. Defect Fault Toler. VLSI Nanotechnol. Syst., DFT. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350315004
  • Konferensbidrag (refereegranskat)abstract
    • The reliability of Artificial Neural Networks (ANNs) has emerged as a prominent research topic due to their increasing utilization in safety-critical applications. Long Short-Term Memory (LSTM) ANNs have demonstrated significant advantages in healthcare applications, primarily attributed to their robust processing of time-series data and memory-facilitated capabilities. This paper, for the first time, presents a comprehensive and fine-grain analysis of the resilience of LSTM-based ANNs in the context of gait analysis using fault injection into weights. Additionally, we improve their resilience by replacing faulty weights with zero, enabling ANNs to withstand environments that are up to 20 times harsher while experiencing up to 7 times fewer critical faults than an unprotected ANN.
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  • Ahmadilivani, M. H., et al. (författare)
  • Cost-Effective Fault Tolerance for CNNs Using Parameter Vulnerability Based Hardening and Pruning
  • 2024
  • Ingår i: Proceedings - 2024 IEEE 30th International Symposium on On-line Testing and Robust System Design, IOLTS 2024. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350370553
  • Konferensbidrag (refereegranskat)abstract
    • Convolutional Neural Networks (CNNs) have become integral in safety-critical applications, thus raising concerns about their fault tolerance. Conventional hardwaredependent fault tolerance methods, such as Triple Modular Redundancy (TMR), are computationally expensive, imposing a remarkable overhead on CNNs. Whereas fault tolerance techniques can be applied either at the hardware level or at the model levels, the latter provides more flexibility without sacrificing generality. This paper introduces a model-level hardening approach for CNNs by integrating error correction directly into the neural networks. The approach is hardwareagnostic and does not require any changes to the underlying accelerator device. Analyzing the vulnerability of parameters enables the duplication of selective filters/neurons so that their output channels are effectively corrected with an efficient and robust correction layer. The proposed method demonstrates fault resilience nearly equivalent to TMR-based correction but with significantly reduced overhead. Nevertheless, there exists an inherent overhead to the baseline CNNs. To tackle this issue, a cost-effective parameter vulnerability based pruning technique is proposed that outperforms the conventional pruning method, yielding smaller networks with a negligible accuracy loss. Remarkably, the hardened pruned CNNs perform up to 24% faster than the hardened un-pruned ones.
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  • Ahmadilivani, M. H., et al. (författare)
  • Enhancing Fault Resilience of QNNs by Selective Neuron Splitting
  • 2023
  • Ingår i: AICAS 2023 - IEEE International Conference on Artificial Intelligence Circuits and Systems, Proceeding. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350332674
  • Konferensbidrag (refereegranskat)abstract
    • The superior performance of Deep Neural Networks (DNNs) has led to their application in various aspects of human life. Safety-critical applications are no exception and impose rigorous reliability requirements on DNNs. Quantized Neural Networks (QNNs) have emerged to tackle the complexity of DNN accelerators, however, they are more prone to reliability issues.In this paper, a recent analytical resilience assessment method is adapted for QNNs to identify critical neurons based on a Neuron Vulnerability Factor (NVF). Thereafter, a novel method for splitting the critical neurons is proposed that enables the design of a Lightweight Correction Unit (LCU) in the accelerator without redesigning its computational part.The method is validated by experiments on different QNNs and datasets. The results demonstrate that the proposed method for correcting the faults has a twice smaller overhead than a selective Triple Modular Redundancy (TMR) while achieving a similar level of fault resiliency. 
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15.
  • Ahmadilivani, Mohammed. H., et al. (författare)
  • Special Session : Approximation and Fault Resiliency of DNN Accelerators
  • 2023
  • Ingår i: Proceedings of the IEEE VLSI Test Symposium. - : IEEE Computer Society. - 9798350346305
  • Konferensbidrag (refereegranskat)abstract
    • Deep Learning, and in particular, Deep Neural Network (DNN) is nowadays widely used in many scenarios, including safety-critical applications such as autonomous driving. In this context, besides energy efficiency and performance, reliability plays a crucial role since a system failure can jeopardize human life. As with any other device, the reliability of hardware architectures running DNNs has to be evaluated, usually through costly fault injection campaigns. This paper explores approximation and fault resiliency of DNN accelerators. We propose to use approximate (AxC) arithmetic circuits to agilely emulate errors in hardware without performing fault injection on the DNN. To allow fast evaluation of AxC DNN, we developed an efficient GPU-based simulation framework. Further, we propose a fine-grain analysis of fault resiliency by examining fault propagation and masking in networks.
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16.
  • Ahmed, A., et al. (författare)
  • Toward High-Performance Triboelectric Nanogenerators by Engineering Interfaces at the Nanoscale : Looking into the Future Research Roadmap
  • 2020
  • Ingår i: Advanced Materials Technologies. - : Wiley-Blackwell. - 2365-709X. ; 5:11, s. 2000520-
  • Tidskriftsartikel (refereegranskat)abstract
    • To meet the future need for clean and sustainable energies, there has been considerable interest in the development of triboelectric nanogenerators (TENGs) that scavenge waste mechanical energies. The performance of a TENG at the macroscale is determined by the multifaceted role of surface and interface properties at the nanoscale, whose understanding is critical for the future development of TENGs. Therefore, various protocols from the atomic to the macrolevel for fabrication and tuning of surfaces and interfaces are required to obtain the desired TENG performance. These protocols branch out into three categories: chemical engineering, physical engineering, and structural engineering. Chemical engineering is an affordable and optimal strategy for introducing more surface polarities and higher work functions for the improvement of charge transfer. Physical engineering includes the utilization of surface morphology control, and interlayer interactions, which can enhance the active interfacial area and electron transfer capacity. Structural engineering at the macroscale, which includes device and electrode design/modifications has a considerable effect on the performance of TENGs. Future challenges and promising research directions related to the construction of next-generation TENG devices, taking into consideration “interfaces” are also presented.
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17.
  • Berisa, Aldin, et al. (författare)
  • Comparative Evaluation of Various Generations of Controller Area Network Based on Timing Analysis
  • 2023
  • Ingår i: IEEE Int. Conf. Emerging Technol. Factory Autom., ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350339918
  • Konferensbidrag (refereegranskat)abstract
    • This paper performs a comparative evaluation of various generations of Controller Area Network (CAN), including the classical CAN, CAN Flexible Data-Rate (FD), and CAN Extra Long (XL). We utilize response-time analysis for the evaluation. In this regard, we identify that the state of the art lacks the response-time analysis for CAN XL. Hence, we discuss the worst-case transmission times calculations for CAN XL frames and incorporate them to the existing analysis for CAN to support response-time analysis of CAN XL frames. Using the extended analysis, we perform a comparative evaluation of the three generations of CAN by analyzing an automotive industrial use case. In crux, we show that using CAN FD is more advantageous than the classical CAN and CAN XL when using frames with payloads of up to 8 bytes, despite the fact that CAN XL supports higher bit rates. For frames with 12-64 bytes payloads, CAN FD performs better than CAN XL when running at the same bit rate, but CAN XL performs better when running at a higher bit rate. Additionally, we discovered that CAN XL performs better than the classical CAN and CAN FD when the frame payload is over 64 bytes, even if it runs at the same or higher bit rates than CAN FD.
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  • Bidgoli, Ali M., et al. (författare)
  • NeuroPIM : Felxible Neural Accelerator for Processing-in-Memory Architectures
  • 2023
  • Ingår i: Proceedings - 2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems, DDECS 2023. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350332773 ; , s. 51-56
  • Konferensbidrag (refereegranskat)abstract
    • The performance of microprocessors under many modern workloads is mainly limited by the off-chip memory bandwidth. The emerging process-in-memory paradigm present a unique opportunity to reduce data movement overheads by moving computation closer to memory. State-of-the-art processing-in-memory proposals stack a logic layer on top of one or multiple memory layers in a 3D fashion and leverage the logic layer to build near-memory processing units. Such processing units are either application-specific accelerators or general-purpose cores. In this paper, we present NeuroPIM, a new processing-in-memory architecture that uses a neural network as the memory-side general-purpose accelerator. This design is mainly motivated by the observation that in many real-world applications, some program regions, or even the entire program, can be replaced by a neural network that is learned to approximate the program's output. NeuroPIM benefits from both the flexibility of general-purpose processors and superior performance of application-specific accelerators. Experimental results show that NeuroPIM provides up to 41% speedup over a processor-side neural network accelerator and up to 8x speedup over a general-purpose processor.
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19.
  • Caretta, Martina Angela, et al. (författare)
  • Water
  • 2022
  • Ingår i: Climate Change 2022: Impacts, Adaptation and Vulnerability : Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change - Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)
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20.
  • Finch, Jo, et al. (författare)
  • Social work and countering violent extremism in Sweden and the UK
  • 2022
  • Ingår i: European Journal of Social Work. - : Routledge. - 1369-1457 .- 1468-2664. ; 25:1, s. 119-130
  • Tidskriftsartikel (refereegranskat)abstract
    • Social Work in Europe, is now being tasked with managing the 'problems' of terrorism, i.e supporting those affected by terrorist attacks, managing returnees affiliated with Terrorist groups in the Middle East, or, as will be discussed here, identifying those at risk from radicalisation and extremism. Both Britain and Sweden have Counter-Terrorism policies, but recent developments in both countries have made it a statutory requirement for social workers to work within such policies. This paper seeks to explore the policies in both countries, utilising a comparative approach to consider the similarities in not only policy and practice but also in the ethical consequences such policies pose for social workers across Europe. The exploration considers; the extent to which anti-radicalisation policies influence social work practices in Sweden and the UK and how they might undermine social work as a human rights profession. The results indicate that anti-radicalisation policies run the risk of reducing social work to become a 'policing profession' practising social control. This has substantial consequences for social work and its global ethics, which should be considered and struggled against by social workers committed to principles of social justice and human rights.
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21.
  • Garmabaki, A.H.S., et al. (författare)
  • Assessing climate-induced risks to urban railway infrastructure
  • 2024
  • Ingår i: International Journal of Systems Assurance Engineering and Management. - : Springer. - 0975-6809 .- 0976-4348.
  • Tidskriftsartikel (refereegranskat)abstract
    • Climate change and its severe impacts pose a number of challenges to transport infrastructure, particularly railway infrastructure, requiring immediate action. A railway system is a linear distributed asset passing different geographical locations and exposed to heterogeneous vulnerabilities under diverse environmental conditions. Furthermore, most of the railway infrastructure assets were designed and built without in-depth analysis of future climate impacts. This paper considers the effects of extreme temperatures on urban railway infrastructure assets, including rail, “switches and crossings”. The data for this study were gathered by exploring various railway infrastructure and meteorological databases over 19 years. In addition, a comprehensive nationwide questionnaire survey of Swedish railway infrastructure, railway maintenance companies, and municipalities has been conducted to assess the risks posed by climate change. A risk and vulnerability assessment framework for railway infrastructure assets is developed. The study shows that track buckling and vegetation fires due to the effect of hot temperatures and rail defects and breakage due to the effect of cold temperatures pose a medium risk. On the other hand, supportability losses due to cold temperatures are classified as high risk. The impact analysis helps infrastructure managers systematically identify and prioritize climate risks and develop appropriate climate adaptation measures and actions to cope with future climate change impacts.
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22.
  • Gholami, A., et al. (författare)
  • Porosity prediction from pre-stack seismic data via committee machine with optimized parameters
  • 2022
  • Ingår i: Journal of Petroleum Science and Engineering. - : Elsevier BV. - 0920-4105. ; 210
  • Tidskriftsartikel (refereegranskat)abstract
    • Prediction of porosity from the seismic data via geophysical methods when limited number of wells are available is a challenging task that has high uncertainties. This study aims to construct a hybrid data-driven predictive model to establish a quantitative correlation between seismic pre-stack (SPS) data and the porosity. First, three intelligent models that are optimized by bat-inspired algorithm (BA): optimized neural network (ONN), optimized fuzzy inference system (OFIS), and optimized support vector regression (OSVR) are constructed for relating porosity to the SPS data. Then, to benefit from all individual optimized models, a final hybrid model was built via committee machine (CM) where single models are combined with a proper weight to predict porosity in the reservoir space. This approach is examined on the SPS data from an oil field in the Persian Gulf with a single exploratory well where input parameters (Vp, Vs, and rho) to the AI models are derived from a two-parameter inversion method. We found that the coefficient of determination, root mean square error, average absolute relative error, and symmetric mean absolute percentage error for the CM are 0.923615, 0.015793, 0.132280, and 0.061310, respectively. Moreover, based on four statistical indexes that are calculated for each model, CM outperformed its individual elements followed by the OSRV. A comprehensive analysis of the results confirms that CM with the OM elements is a superior approach for computing porosity from the SPS in the well and then throughout the entire reservoir volume. This strategy can aid petroleum engineers to have a better forecast of porosity population in the reservoir static model immediately following the data that is obtained from the first exploratory well. Ultimately, successful implementation of this approach will promptly delineate sweet spots that can replace uncertain and complicated conventional geophysical methods.
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23.
  • Kattih, Mafaz, et al. (författare)
  • National prevalence of atopic dermatitis in Korean adolescents from 2009 to 2022
  • 2024
  • Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 14:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Previous studies have examined the prevalence of allergic diseases in adolescents 1-2 years after the emergence of the COVID-19 pandemic. However, more data is needed to understand the long-term impact of COVID-19 on allergic diseases. Thus, we aimed to examine the trend of the atopic dermatitis prevalence in Korean adolescents before and during the COVID-19 pandemic across 14 years. Additionally, we analyze the risk factors of atopic dermatitis (AD) based on the results. The Korean Disease Control and Prevention Agency conducted the Korea Youth Risk Behavior Web-based Survey from 2009 to 2022, from which the data for this study were obtained. Prevalence trends were compared across subgroups, and the beta difference (beta diff) was calculated. We computed odds ratios to examine changes in the disease prevalence before and during the pandemic. This study included a total of 917,461 participants from 2009 to 2022. The prevalence of atopic dermatitis increased from 6.79% (95% CI 6.66-6.91) in 2009-2011 to 6.89% (95% CI 6.72-7.05) in 2018-2019, then decreased slightly to 5.82% (95% CI 5.60-6.04) in 2022. Across the 14 years, middle school student status, low parent's highest education level, low household income, non-alcohol consumption, non-smoker smoking status, no suicidal thoughts, and no suicide attempts were associated with increased risk of atopic dermatitis, while female sex, rural residence, high BMI, low school performance, low household income, and no feelings of sadness and despair was associated with a small increase. This study examined the prevalence of atopic dermatitis across an 18-year, and found that the prevalence increased in the pre-pandemic then decreased during the start of the pandemic and remained constant throughout the pandemic. This trend could be explained mainly by the large scale social and political changes that occurred during the COVID-19 pandemic.
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24.
  • Mahdiani, H., et al. (författare)
  • Computation reuse-aware accelerator for neural networks
  • 2020
  • Ingår i: Hardware Architectures for Deep Learning. - : Institution of Engineering and Technology. - 9781785617683 ; , s. 147-158
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
    • Power consumption has long been a significant concern in neural networks. In particular, large neural networks that implement novel machine learning techniques require much more computation, and hence power, than ever before. In this chapter, we showed that computation reuse could exploit the inherent redundancy in the arithmetic operations of the neural network to save power. Experimental results showed that computation reuse, when coupled with the approximation property of neural networks, can eliminate up to 90% of multiplication, effectively reducing power consumption by 61%, on average in the presented architecture. The proposed computation reuse -aware design can be extended in several ways. First, it can be integrated into several state-of-the-art customized architectures for LSTM, spiking, and convolutional neural network models to further reduce power consumption. Second, we can couple computation reuse with existing mapping and scheduling algorithms toward developing reusable scheduling and mapping methods for neural network. Computation reuse can also boost the performance of the methods that eliminate ineffectual computations in deep learning neural networks. Evaluating the impact of CORN on reliability and customizing the CORN architecture for FPGA-based neural network implementation are the other future works in this line.
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25.
  • Petzold, Axel, et al. (författare)
  • Diagnosis and classification of optic neuritis
  • 2022
  • Ingår i: Lancet Neurology. - : ELSEVIER SCIENCE INC. - 1474-4422 .- 1474-4465. ; 21:12, s. 1120-1134
  • Forskningsöversikt (refereegranskat)abstract
    • There is no consensus regarding the classification of optic neuritis, and precise diagnostic criteria are not available. This reality means that the diagnosis of disorders that have optic neuritis as the first manifestation can be challenging. Accurate diagnosis of optic neuritis at presentation can facilitate the timely treatment of individuals with multiple sclerosis, neuromyelitis optica spectrum disorder, or myelin oligodendrocyte glycoprotein antibody-associated disease. Epidemiological data show that, cumulatively, optic neuritis is most frequently caused by many conditions other than multiple sclerosis. Worldwide, the cause and management of optic neuritis varies with geographical location, treatment availability, and ethnic background. We have developed diagnostic criteria for optic neuritis and a classification of optic neuritis subgroups. Our diagnostic criteria are based on clinical features that permit a diagnosis of possible optic neuritis; further paraclinical tests, utilising brain, orbital, and retinal imaging, together with antibody and other protein biomarker data, can lead to a diagnosis of definite optic neuritis. Paraclinical tests can also be applied retrospectively on stored samples and historical brain or retinal scans, which will be useful for future validation studies. Our criteria have the potential to reduce the risk of misdiagnosis, provide information on optic neuritis disease course that can guide future treatment trial design, and enable physicians to judge the likelihood of a need for long-term pharmacological management, which might differ according to optic neuritis subgroups.
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26.
  • Scutelnic, Adrian, et al. (författare)
  • Management of Cerebral Venous Thrombosis Due to Adenoviral COVID-19 Vaccination.
  • 2022
  • Ingår i: Annals of neurology. - : Wiley. - 1531-8249 .- 0364-5134. ; 92:4, s. 562-573
  • Tidskriftsartikel (refereegranskat)abstract
    • Cerebral venous thrombosis (CVT) caused by vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare adverse effect of adenovirus-based severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) vaccines. In March 2021, after autoimmune pathogenesis of VITT was discovered, treatment recommendations were developed. These comprised immunomodulation, non-heparin anticoagulants, and avoidance of platelet transfusion. The aim of this study was to evaluate adherence to these recommendations and its association with mortality.We used data from an international prospective registry of patients with CVT after the adenovirus-based SARS-CoV-2 vaccination. We analyzed possible, probable, or definite VITT-CVT cases included until January 18, 2022. Immunomodulation entailed administration of intravenous immunoglobulins and/or plasmapheresis.Ninety-nine patients with VITT-CVT from 71 hospitals in 17 countries were analyzed. Five of 38 (13%), 11 of 24 (46%), and 28 of 37 (76%) of the patients diagnosed in March, April, and from May onward, respectively, were treated in-line with VITT recommendations (p<0.001). Overall, treatment according to recommendations had no statistically significant influence on mortality (14/44 [32%] vs 29/55 [52%], adjusted odds ratio [OR]=0.43, 95% confidence interval [CI]=0.16-1.19). However, patients who received immunomodulation had lower mortality (19/65 [29%] vs 24/34 [70%], adjusted OR=0.19, 95% CI=0.06-0.58). Treatment with non-heparin anticoagulants instead of heparins was not associated with lower mortality (17/51 [33%] vs 13/35 [37%], adjusted OR=0.70, 95% CI=0.24-2.04). Mortality was also not significantly influenced by platelet transfusion (17/27 [63%] vs 26/72 [36%], adjusted OR=2.19, 95% CI=0.74-6.54).In patients with VITT-CVT, adherence to VITT treatment recommendations improved over time. Immunomodulation seems crucial for reducing mortality of VITT-CVT. ANN NEUROL 2022;92:562-573.
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27.
  • Sepanlou, Sadaf G., et al. (författare)
  • The global, regional, and national burden of cirrhosis by cause in 195 countries and territories, 1990-2017 : a systematic analysis for the Global Burden of Disease Study 2017
  • 2020
  • Ingår i: The Lancet Gastroenterology & Hepatology. - 2468-1253. ; 5:3, s. 245-266
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Cirrhosis and other chronic liver diseases (collectively referred to as cirrhosis in this paper) are a major cause of morbidity and mortality globally, although the burden and underlying causes differ across locations and demographic groups. We report on results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 on the burden of cirrhosis and its trends since 1990, by cause, sex, and age, for 195 countries and territories. Methods We used data from vital registrations, vital registration samples, and verbal autopsies to estimate mortality. We modelled prevalence of total, compensated, and decompensated cirrhosis on the basis of hospital and claims data. Disability-adjusted life-years (DALYs) were calculated as the sum of years of life lost due to premature death and years lived with disability. Estimates are presented as numbers and age-standardised or age-specific rates per 100 000 population, with 95% uncertainty intervals (UIs). All estimates are presented for five causes of cirrhosis: hepatitis B, hepatitis C, alcohol-related liver disease, non-alcoholic steatohepatitis (NASH), and other causes. We compared mortality, prevalence, and DALY estimates with those expected according to the Socio-demographic Index (SDI) as a proxy for the development status of regions and countries. Findings In 2017, cirrhosis caused more than 1.32 million (95% UI 1.27-1.45) deaths (440000 [416 000-518 000; 33.3%] in females and 883 000 [838 000-967 000; 66.7%] in males) globally, compared with less than 899 000 (829 000-948 000) deaths in 1990. Deaths due to cirrhosis constituted 2.4% (2.3-2.6) of total deaths globally in 2017 compared with 1.9% (1.8-2.0) in 1990. Despite an increase in the number of deaths, the age-standardised death rate decreased from 21.0 (19.2-22.3) per 100 000 population in 1990 to 16.5 (15.8-18-1) per 100 000 population in 2017. Sub-Saharan Africa had the highest age-standardised death rate among GBD super-regions for all years of the study period (32.2 [25.8-38.6] deaths per 100 000 population in 2017), and the high-income super-region had the lowest (10.1 [9.8-10-5] deaths per 100 000 population in 2017). The age-standardised death rate decreased or remained constant from 1990 to 2017 in all GBD regions except eastern Europe and central Asia, where the age-standardised death rate increased, primarily due to increases in alcohol-related liver disease prevalence. At the national level, the age-standardised death rate of cirrhosis was lowest in Singapore in 2017 (3.7 [3.3-4.0] per 100 000 in 2017) and highest in Egypt in all years since 1990 (103.3 [64.4-133.4] per 100 000 in 2017). There were 10.6 million (10.3-10.9) prevalent cases of decompensated cirrhosis and 112 million (107-119) prevalent cases of compensated cirrhosis globally in 2017. There was a significant increase in age-standardised prevalence rate of decompensated cirrhosis between 1990 and 2017. Cirrhosis caused by NASH had a steady age-standardised death rate throughout the study period, whereas the other four causes showed declines in age-standardised death rate. The age-standardised prevalence of compensated and decompensated cirrhosis due to NASH increased more than for any other cause of cirrhosis (by 33.2% for compensated cirrhosis and 54.8% for decompensated cirrhosis) over the study period. From 1990 to 2017, the number of prevalent cases snore than doubled for compensated cirrhosis due to NASH and more than tripled for decompensated cirrhosis due to NASH. In 2017, age-standardised death and DALY rates were lower among countries and territories with higher SDI. Interpretation Cirrhosis imposes a substantial health burden on many countries and this burden has increased at the global level since 1990, partly due to population growth and ageing. Although the age-standardised death and DALY rates of cirrhosis decreased from 1990 to 2017, numbers of deaths and DALYs and the proportion of all global deaths due to cirrhosis increased. Despite the availability of effective interventions for the prevention and treatment of hepatitis B and C, they were still the main causes of cirrhosis burden worldwide, particularly in low-income countries. The impact of hepatitis B and C is expected to be attenuated and overtaken by that of NASH in the near future. Cost-effective interventions are required to continue the prevention and treatment of viral hepatitis, and to achieve early diagnosis and prevention of cirrhosis due to alcohol-related liver disease and NASH.
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28.
  • SeyyedAghaei Rezaei, S. H., et al. (författare)
  • NoM : Network-on-Memory for Inter-bank Data Transfer in Highly-banked Memories
  • 2020
  • Ingår i: IEEE Computer Architecture Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1556-6056. ; 19:1, s. 80-83
  • Tidskriftsartikel (refereegranskat)abstract
    • Data copy is a widely-used memory operation in many programs and operating system services. In conventional computers, data copy is often carried out by two separate read and write transactions that pass data back and forth between the memory hierarchy and processor registers. Some prior mechanisms propose to avoid this unnecessary data movement by using the shared internal bus in DRAM chip to directly copy data between two DRAM banks. While these methods exhibit superior performance, compared to conventional techniques, this technique does not allow data copy over different DRAM channels. Hence, this technique has limited benefit for the emerging 3D stacked memories (such as HMC and HBM) that contains tens of banks across multiple memory controllers. In this paper, we present Network-on-Memory (NoM), a lightweight inter-bank communication scheme that enables direct data copy within memory. NoM adopts a TDM-based circuit-switching design, where circuit setup is done by the memory controller. Compared to previous state-of-the-art approaches, NoM enables both data copy over multiple DRAM channels and concurrent copy operation. Our evaluation shows that NoM improves the performance of data-intensive workloads by 3.8X on average compare to the state-of-the-art techniques, respectively. IEEE
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29.
  • Sharafati, Ahmad, et al. (författare)
  • Development of Advanced Computer Aid Model for Shear Strength of Concrete Slender Beam Prediction
  • 2020
  • Ingår i: Applied Sciences. - Switzerland : MDPI. - 2076-3417. ; 10:11
  • Tidskriftsartikel (refereegranskat)abstract
    • High-strength concrete (HSC) is highly applicable to the construction of heavy structures. However, shear strength (Ss) determination of HSC is a crucial concern for structure designers and decision makers. The current research proposes the novel models based on the combination of adaptive neuro-fuzzy inference system (ANFIS) with several meta-heuristic optimization algorithms, including ant colony optimizer (ACO), differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO), to predict the Ss of HSC slender beam. The proposed models were constructed using several input combinations incorporating several related dimensional parameters such as effective depth of beam (d), shear span (a), maximum size of aggregate (ag), compressive strength of concrete (fc), and percentage of tension reinforcement (ρ). To assess the impact of the non-homogeneity of the dataset on the prediction result accuracy, two possible modeling scenarios, (i) non-processed (initial) dataset (NP) and (ii) pre-processed dataset (PP), are inspected by several performance indices. The modeling results demonstrated that ANFIS-PSO hybrid model attained the best prediction accuracy over the other models and for the pre-processed input parameters. Several uncertainty analyses were examined (i.e., model, variables, and data), and results indicated predicting the HSC shear strength was more sensitive to the model structure uncertainty than the input parameters.
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30.
  • Solmi, Marco, et al. (författare)
  • Physical and mental health impact of COVID-19 on children, adolescents, and their families :
  • 2022
  • Ingår i: Journal of Affective Disorders. - : Elsevier. - 0165-0327 .- 1573-2517. ; 299, s. 367-376
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The COVID-19 pandemic has altered daily routines and family functioning, led to closing schools, and dramatically limited social interactions worldwide. Measuring its impact on mental health of vulnerable children and adolescents is crucial. Methods: The Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT - www. coh-fit.com) is an on-line anonymous survey, available in 30 languages, involving >230 investigators from 49 countries supported by national/international professional associations. COH-FIT has thee waves (until the pandemic is declared over by the WHO, and 6-18 months plus 24-36 months after its end). In addition to adults, COH-FIT also includes adolescents (age 14-17 years), and children (age 6-13 years), recruited via nonprobability/snowball and representative sampling and assessed via self-rating and parental rating. Nonmodifiable/modifiable risk factors/treatment targets to inform prevention/intervention programs to promote health and prevent mental and physical illness in children and adolescents will be generated by COH-FIT. Co primary outcomes are changes in well-being (WHO-5) and a composite psychopathology P-Score. Multiple behavioral, family, coping strategy and service utilization factors are also assessed, including functioning and quality of life. Results: Up to June 2021, over 13,000 children and adolescents from 59 countries have participated in the COHFIT project, with representative samples from eleven countries. Limitations: Cross-sectional and anonymous design. Conclusions: Evidence generated by COH-FIT will provide an international estimate of the COVID-19 effect on childrens, adolescents and families, mental and physical health, well-being, functioning and quality of life, informing the formulation of present and future evidence-based interventions and policies to minimize adverse effects of the present and future pandemics on youth.
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31.
  • Solmi, Marco, et al. (författare)
  • The collaborative outcomes study on health and functioning during infection times in adults (COH-FIT-Adults) : Design and methods of an international online survey targeting physical and mental health effects of the COVID-19 pandemic
  • 2022
  • Ingår i: Journal of Affective Disorders. - : Elsevier. - 0165-0327 .- 1573-2517. ; 299, s. 393-407
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: . High-quality comprehensive data on short-/long-term physical/mental health effects of the COVID-19 pandemic are needed. Methods: . The Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT) is an international, multi-language (n=30) project involving >230 investigators from 49 countries/territories/regions, endorsed by national/international professional associations. COH-FIT is a multi-wave, on-line anonymous, cross-sectional survey [wave 1: 04/2020 until the end of the pandemic, 12 months waves 2/3 starting 6/24 months threreafter] for adults, adolescents (14-17), and children (6-13), utilizing non-probability/snowball and representative sampling. COH-FIT aims to identify non-modifiable/modifiable risk factors/treatment targets to inform prevention/intervention programs to improve social/health outcomes in the general population/vulnerable subgrous during/after COVID-19. In adults, co-primary outcomes are change from pre-COVID-19 to intra-COVID-19 in well-being (WHO-5) and a composite psychopathology P-Score. Key secondary outcomes are a P-extended score, global mental and physical health. Secondary outcomes include health-service utilization/ functioning, treatment adherence, functioning, symptoms/behaviors/emotions, substance use, violence, among others. Results: . Starting 04/26/2020, up to 14/07/2021 >151,000 people from 155 countries/territories/regions and six continents have participated. Representative samples of >= 1,000 adults have been collected in 15 countries. Overall, 43.0% had prior physical disorders, 16.3% had prior mental disorders, 26.5% were health care workers, 8.2% were aged >= 65 years, 19.3% were exposed to someone infected with COVID-19, 76.1% had been in quarantine, and 2.1% had been COVID 19-positive. Limitations: . Cross-sectional survey, preponderance of non-representative participants. Conclusions: . Results from COH-FIT will comprehensively quantify the impact of COVID-19, seeking to identify high-risk groups in need for acute and long-term intervention, and inform evidence-based health policies/strategies during this/future pandemics.
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32.
  • Solmi, Marco, et al. (författare)
  • Validation of the Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT) questionnaire for adults
  • 2023
  • Ingår i: Journal of Affective Disorders. - : ELSEVIER. - 0165-0327 .- 1573-2517. ; 326, s. 249-261
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The Collaborative Outcome study on Health and Functioning during Infection Times (COH-FIT; www.coh-fit.com) is an anonymous and global online survey measuring health and functioning during the COVID-19 pandemic. The aim of this study was to test concurrently the validity of COH-FIT items and the in-ternal validity of the co-primary outcome, a composite psychopathology "P-score". Methods: The COH-FIT survey has been translated into 30 languages (two blind forward-translations, consensus, one independent English back-translation, final harmonization). To measure mental health, 1-4 items ("COH-FIT items") were extracted from validated questionnaires (e.g. Patient Health Questionnaire 9). COH-FIT items measured anxiety, depressive, post-traumatic, obsessive-compulsive, bipolar and psychotic symptoms, as well as stress, sleep and concentration. COH-FIT Items which correlated r >= 0.5 with validated companion question-naires, were initially retained. A P-score factor structure was then identified from these items using exploratory factor analysis (EFA) and confirmatory factor analyses (CFA) on data split into training and validation sets. Consistency of results across languages, gender and age was assessed. Results: From >150,000 adult responses by May 6th, 2022, a subset of 22,456 completed both COH-FIT items and validated questionnaires. Concurrent validity was consistently demonstrated across different languages for COH-FIT items. CFA confirmed EFA results of five first-order factors (anxiety, depression, post-traumatic, psychotic, psychophysiologic symptoms) and revealed a single second-order factor P-score, with high internal reliability (omega = 0.95). Factor structure was consistent across age and sex. Conclusions: COH-FIT is a valid instrument to globally measure mental health during infection times. The P-score is a valid measure of multidimensional mental health.
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33.
  • Taheri, Mahdi, et al. (författare)
  • APPRAISER : DNN Fault Resilience Analysis Employing Approximation Errors
  • 2023
  • Ingår i: Proceedings - 2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems, DDECS 2023. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350332773 ; , s. 124-127
  • Konferensbidrag (refereegranskat)abstract
    • Nowadays, the extensive exploitation of Deep Neural Networks (DNNs) in safety-critical applications raises new reliability concerns. In practice, methods for fault injection by emulation in hardware are efficient and widely used to study the resilience of DNN architectures for mitigating reliability issues already at the early design stages. However, the state-of-the-art methods for fault injection by emulation incur a spectrum of time-, design-and control-complexity problems. To overcome these issues, a novel resiliency assessment method called APPRAISER is proposed that applies functional approximation for a non-conventional purpose and employs approximate computing errors for its interest. By adopting this concept in the resiliency assessment domain, APPRAISER provides thousands of times speed-up in the assessment process, while keeping high accuracy of the analysis. In this paper, APPRAISER is validated by comparing it with state-of-the-art approaches for fault injection by emulation in FPGA. By this, the feasibility of the idea is demonstrated, and a new perspective in resiliency evaluation for DNNs is opened.
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34.
  • Taheri, M., et al. (författare)
  • DeepAxe : A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators
  • 2023
  • Ingår i: Proceedings - International Symposium on Quality Electronic Design, ISQED. - : IEEE Computer Society. - 9798350334753
  • Konferensbidrag (refereegranskat)abstract
    • While the role of Deep Neural Networks (DNNs) in a wide range of safety-critical applications is expanding, emerging DNNs experience massive growth in terms of computation power. It raises the necessity of improving the reliability of DNN accelerators yet reducing the computational burden on the hardware platforms, i.e. reducing the energy consumption and execution time as well as increasing the efficiency of DNN accelerators. Therefore, the trade-off between hardware performance, i.e. area, power and delay, and the reliability of the DNN accelerator implementation becomes critical and requires tools for analysis.In this paper, we propose a framework DeepAxe for design space exploration for FPGA-based implementation of DNNs by considering the trilateral impact of applying functional approximation on accuracy, reliability and hardware performance. The framework enables selective approximation of reliability-critical DNNs, providing a set of Pareto-optimal DNN implementation design space points for the target resource utilization requirements. The design flow starts with a pre-trained network in Keras, uses an innovative high-level synthesis environment DeepHLS and results in a set of Pareto-optimal design space points as a guide for the designer. The framework is demonstrated on a case study of custom and state-of-the-art DNNs and datasets. 
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35.
  • Thorell, Kaisa, 1983, et al. (författare)
  • The Helicobacter pylori Genome Project: insights into H. pylori population structure from analysis of a worldwide collection of complete genomes
  • 2023
  • Ingår i: Nature Communications. - 2041-1723. ; 14:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Helicobacter pylori, a dominant member of the gastric microbiota, shares co-evolutionary history with humans. This has led to the development of genetically distinct H. pylori subpopulations associated with the geographic origin of the host and with differential gastric disease risk. Here, we provide insights into H. pylori population structure as a part of the Helicobacter pylori Genome Project (HpGP), a multi-disciplinary initiative aimed at elucidating H. pylori pathogenesis and identifying new therapeutic targets. We collected 1011 well-characterized clinical strains from 50 countries and generated high-quality genome sequences. We analysed core genome diversity and population structure of the HpGP dataset and 255 worldwide reference genomes to outline the ancestral contribution to Eurasian, African, and American populations. We found evidence of substantial contribution of population hpNorthAsia and subpopulation hspUral in Northern European H. pylori. The genomes of H. pylori isolated from northern and southern Indigenous Americans differed in that bacteria isolated in northern Indigenous communities were more similar to North Asian H. pylori while the southern had higher relatedness to hpEastAsia. Notably, we also found a highly clonal yet geographically dispersed North American subpopulation, which is negative for the cag pathogenicity island, and present in 7% of sequenced US genomes. We expect the HpGP dataset and the corresponding strains to become a major asset for H. pylori genomics.
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