125 research outputs found
MDSClone : multidimensional scaling aided clone detection in Internet of Things
Cloning is a very serious threat in the Internet of Things (IoT), owing to the simplicity for an attacker to gather configuration and authentication credentials from a non-tamper-proof node, and replicate it in the network. In this paper, we propose MDSClone, a novel clone detection method based on multidimensional scaling (MDS). MDSClone appears to be very well suited to IoT scenarios, as it (i) detects clones without the need to know the geographical positions of nodes, and (ii) unlike prior methods, it can be applied to hybrid networks that comprise both static and mobile nodes, for which no mobility pattern may be assumed a priori. Moreover, a further advantage of MDSClone is that (iii) the core part of the detection algorithm can be parallelized, resulting in an acceleration of the whole detection mechanism. Our thorough analytical and experimental evaluations demonstrate that MDSClone can achieve a 100% clone detection probability. Moreover, we propose several modifications to the original MDS calculation, which lead to over a 75% speed up in large scale scenarios. The demonstrated efficiency of MDSClone proves that it is a promising method towards a practical clone detection design in IoT
High Performance Multicell Series Inverter-Fed Induction Motor Drive
This document is the Accepted Manuscript version of the following article: M. Khodja, D. Rahiel, M. B. Benabdallah, H. Merabet Boulouiha, A. Allali, A. Chaker, and M. Denai, ‘High-performance multicell series inverter-fed induction motor drive’, Electrical Engineering, Vol. 99 (3): 1121-1137, September 2017. The final publication is available at Springer via DOI: https://doi.org/10.1007/s00202-016-0472-4.The multilevel voltage-source inverter (VSI) topology of the series multicell converter developed in recent years has led to improved converter performance in terms of power density and efficiency. This converter reduces the voltage constraints between all cells, which results in a lower transmission losses, high switching frequencies and the improvement of the output voltage waveforms. This paper proposes an improved topology of the series multicell inverter which minimizes harmonics, reduces torque ripples and losses in a variable-speed induction motor drive. The flying capacitor multilevel inverter topology based on the classical and modified phase shift pulse width modulation (PSPWM, MPSPWM) techniques are applied in this paper to minimize harmonic distortion at the inverter output. Simulation results are presented for a 2-kW induction motor drive and the results obtained demonstrate reduced harmonics, improved transient responses and reference tracking performance of the voltage in the induction motor and consequently reduced torque ripplesPeer reviewe
A hierarchical key pre-distribution scheme for fog networks
Security in fog computing is multi-faceted, and one particular challenge is establishing a secure communication channel between fog nodes and end devices. This emphasizes the importance of designing efficient and secret key distribution scheme to facilitate fog nodes and end devices to establish secure communication channels. Existing secure key distribution schemes designed for hierarchical networks may be deployable in fog computing, but they incur high computational and communication overheads and thus consume significant memory. In this paper, we propose a novel hierarchical key pre-distribution scheme based on “Residual Design” for fog networks. The proposed key distribution scheme is designed to minimize storage overhead and memory consumption, while increasing network scalability. The scheme is also designed to be secure against node capture attacks. We demonstrate that in an equal-size network, our scheme achieves around 84% improvement in terms of node storage overhead, and around 96% improvement in terms of network scalability. Our research paves the way for building an efficient key management framework for secure communication within the hierarchical network of fog nodes and end devices.
KEYWORDS: Fog Computing, Key distribution, Hierarchical Networks
Epidermal neural crest stem cell transplantation as a promising therapeutic strategy for ischemic stroke
Introduction: Cell-based therapy is considered as promising strategy to cure stroke. However, employing appropriate type of stem cell to fulfill many therapeutic needs of cerebral ischemia is still challenging. In this regard, the current study was designed to elucidate therapeutic potential of epidermal neural crest stem cells (EPI-NCSCs) compared to bone marrow mesenchymal stem cells (BM-MSCs) in rat model of ischemic stroke. Methods: Ischemic stroke was induced by middle cerebral artery occlusion (MCAO) for 45 minutes. Immediately after reperfusion, EPI-NCSCs or BM-MSCs were transplanted via intra-arterial or intravenous route. A test for neurological function was performed before ischemia and 1, 3, and 7 days after MCAO. Also, infarct volume ratio and relative expression of 15 selected target genes were evaluated 7 days after transplantation. Results: EPI-NCSCs transplantation (both intra-arterial and intravenous) and BM-MSCs transplantation (only intra-arterial) tended to result in a better functional outcome, compared to the MCAO group; however, this difference was not statistically significant. The infarct volume ratio significantly decreased in NCSC-intra-arterial, NCSC-intravenous and MSC-intra-arterial groups compared to the control. EPI-NCSCs interventions led to higher expression levels of Bdnf, nestin, Sox10, doublecortin, β-III tubulin, Gfap, and interleukin-6, whereas neurotrophin-3 and interleukin-10 were decreased. On the other hand, BM-MSCs therapy resulted in upregulation of Gdnf, β-III tubulin, and Gfap and down-regulation of neurotrophin-3, interleukin-1, and interleukin-10. Conclusion: These findings highlight the therapeutic effects of EPI-NCSCs transplantation, probably through simultaneous induction of neuronal and glial formation, as well as Bdnf over-expression in a rat model of ischemic strok
Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example
© The Author(s) 2017 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/ genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.Peer reviewedFinal Published versio
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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026
Background
The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic; characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic; and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness.
Methods
In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need.
Findings
In 2019, at the onset of the COVID-19 pandemic, US7·3 trillion (95% UI 7·2–7·4) in 2019; 293·7 times the 43·1 billion in development assistance was provided to maintain or improve health. The pandemic led to an unprecedented increase in development assistance targeted towards health; in 2020 and 2021, 37·8 billion was provided for the health-related COVID-19 response. Although the support for pandemic preparedness is 12·2% of the recommended target by the High-Level Independent Panel (HLIP), the support provided for the health-related COVID-19 response is 252·2% of the recommended target. Additionally, projected spending estimates suggest that between 2022 and 2026, governments in 17 (95% UI 11–21) of the 137 LMICs will observe an increase in national government health spending equivalent to an addition of 1% of GDP, as recommended by the HLIP.
Interpretation
There was an unprecedented scale-up in DAH in 2020 and 2021. We have a unique opportunity at this time to sustain funding for crucial global health functions, including pandemic preparedness. However, historical patterns of underfunding of pandemic preparedness suggest that deliberate effort must be made to ensure funding is maintained
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