| 1. |
- Aziz, Maria, et al.
(author)
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Efficient Removal of Lead and Chromium From Aqueous Media Using Selenium Based Nanocomposite Supported by Orange Peel
- 2022
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In: Frontiers in Environmental Science. - : Frontiers Media S.A.. - 2296-665X. ; 10
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Journal article (peer-reviewed)abstract
- This study presents the synthesis of activated orange peel, derived from bio-waste (orange peel) and its doping with selenium nano-particles to enhance the adsorption capacity. The synthesized nanocomposite orange peel/Selenium (OP/Se) was applied as adsorbents for the removal of Lead (Pb) and Chromium (Cr) from synthetic waste water as an economical water cleaning technology. Orange peel/Selenium nanocomposite was characterized by X-Ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR) and Scanning electron microscopy (SEM). Scanning electron microscopy results showed the porous structure of OP/Se nanocomposite and distinct peaks observed in XRD and FTIR spectra depicted the successful synthesis of nanocomposite. Batch experiments were conducted to figure out the effect of different parameters on adsorption of Pb and Cr by using Atomic Absorption Spectroscopy. The maximum adsorption capacity of 99.9% was achieved for both lead and chromium at acidic pH. While at temperature of 60°C the maximum adsorption of 98.3 and 95.9% was found for Pb and Cr respectively. Furthermore the experimental data was examined with Pseudo-first order, first-order and Pseudo-second order kinetic model, as well as Morris Intraparticle diffusion model where the pseudo second order was best fitted which indicated the chemisorption mechanism in adsorption process. The adsorption process followed the Langmuir isotherm model verified that OP/Se nanocomposite was found to be favorable for the process of adsorption. The adsorption thermodynamics indicate that adsorption of heavy metals ions is spontaneous (ΔG° < 0) and the adsorption increases with increase in temperature which means that reaction was endothermic in nature. This study revealed that the synthesized bio-activated nanocomposite was an efficient adsorbent material for the removal of heavy metals from waste water.
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| 2. |
- Micah, Angela E., et al.
(author)
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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
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In: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 398:10308, s. 1317-1343
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Research review (peer-reviewed)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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| 3. |
- Afzal, Wasif, et al.
(author)
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On using grey literature and google scholar in systematic literature reviews in software engineering
- 2020
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In: IEEE Access. - United States. - 2169-3536. ; 8, s. 36226-36243
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Journal article (peer-reviewed)abstract
- © 2013 IEEE. Context: The inclusion of grey literature (GL) is important to remove publication bias while gathering available evidence regarding a certain topic. The number of systematic literature reviews (SLRs) in Software Engineering (SE) is increasing but we do not know about the extent of GL usage in these SLRs. Moreover, Google Scholar is rapidly becoming a search engine of choice for many researchers but the extent to which it can find the primary studies is not known. Objective: This tertiary study is an attempt to i) measure the usage of GL in SLRs in SE. Furthermore this study proposes strategies for categorizing GL and a quality checklist to use for GL in future SLRs; ii) explore if it is feasible to use only Google Scholar for finding scholarly articles for academic research. Method: We have conducted a systematic mapping study to measure the extent of GL usage in SE SLRs as well as to measure the feasibility of finding primary studies using Google Scholar. Results and conclusions: a) Grey Literature: 76.09% SLRs (105 out of 138) in SE have included one or more GL studies as primary studies. Among total primary studies across all SLRs (6307), 582 are classified as GL, making the frequency of GL citing as 9.23%. The intensity of GL use indicate that each SLR contains 5 primary studies on average (total intensity of GL use being 5.54). The ranking of GL tells us that conference papers are the most used form 43.3% followed by technical reports 28.52%. Universities, research institutes, labs and scientific societies together make up 67.7% of GL used, indicating that these are useful sources for searching GL. We additionally propose strategies for categorizing GL and criteria for evaluating GL quality, which can become a basis for more detailed guidelines for including GL in future SLRs. b) Google Scholar Results: The results show that Google Scholar was able to retrieve 96% of primary studies of these SLRs. Most of the primary studies that were not found using Google Scholar were from grey sources.
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| 4. |
- Axfors, Cathrine, et al.
(author)
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Mortality outcomes with hydroxychloroquine and chloroquine in COVID-19 from an international collaborative meta-analysis of randomized trials
- 2021
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aim to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We present a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality has been extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses include patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine is 1.11 (95% CI: 1.02, 1.20; I-2=0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I-2=0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine is associated with increased mortality in COVID-19 patients, and there is no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities. Hydroxychloroquine and chloroquine have been investigated as a potential treatment for Covid-19 in several clinical trials. Here the authors report a meta-analysis of published and unpublished trials, and show that treatment with hydroxychloroquine for patients with Covid-19 was associated with increased mortality, and there was no benefit from chloroquine.
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| 5. |
- Azhar, Muhammad Rizwan, et al.
(author)
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Electrodeposited Metal Organic Framework toward Excellent Hydrogen Sensing in an Ionic Liquid
- 2020
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In: ACS APPLIED NANO MATERIALS. - : American Chemical Society (ACS). - 2574-0970. ; 3:5, s. 4376-4385
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Journal article (peer-reviewed)abstract
- The synthesis of thin films of metal organic frame-works (MOFs) is a rapidly growing area owing to the use of these highly functional nanomaterials for various applications. In this study, a thin layer of a typical MOF, copper benzene tricarboxylate (HKUST-1), was synthesized by electrodeposition on a glassy carbon (GC) electrode using a potential-step chronoamperometric technique at room temperature. Various characterization techniques including Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS) were used to verify the successful deposition of the MOF film and its structure. The electrodeposited MOF crystals showed cuboctahedral morphology with macropores. The MOF modified electrode was applied for hydrogen gas sensing in a room-temperature ionic liquid (RTIL) for the first time. A 4-fold increase in current was observed compared to a precious metal, that is, platinum, and the electrode exhibited a significant catalytic activity compared to the bare GC electrode, making it a very promising low cost material for hydrogen gas sensing.
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| 6. |
- Azhar, Muhammad Waqar, 1986, et al.
(author)
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Approx-RM: Reducing Energy on Heterogeneous Multicore processors under Accuracy and Timing Constraints
- 2023
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In: Transactions on Architecture and Code Optimization. - 1544-3973 .- 1544-3566. ; 20:3
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Journal article (peer-reviewed)abstract
- Reducing energy consumption while providing performance and quality guarantees is crucial for computing systems ranging from battery-powered embedded systems to data centers. This paper considers approximate iterative applications executing on heterogeneous multi-core platforms under user-specified performance and quality targets. We note that allowing a slight yet bounded relaxation in solution quality can considerably reduce the required iteration count and thereby can save significant amounts of energy. To this end, this paper proposes Approx-RM, a resource management scheme that reduces energy expenditure while guaranteeing a specified performance as well as accuracy target. Approx-RMpredicts the number of iterations required to meet the relaxed accuracy target at run-time. The time saved generates execution-time slack, which allows Approx-RM to allocate fewer resources on a heterogeneous multi-core platform in terms of DVFS, core type, and core count to save energy while meeting the performance target. Approx-RMcontributes with lightweight methods for predicting the iteration count needed to meet the accuracy target and the resources needed to meet the performance target. Approx-RM uses the aforementioned predictions to allocate just enoughresources to comply with quality of service constraints to save energy. Our evaluation shows energy savings of 31.6%, on average, compared to Race-to-idle when the accuracy is only relaxed by 1%. Approx-RM incurs timing and energy overheads of less than 0.1%.
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| 7. |
- Azhar, Muhammad Waqar, 1986, et al.
(author)
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ARADA: Adaptive Resource Allocation for Improving Energy Efficiency in Deep Learning Accelerators
- 2023
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In: Proceedings of the 20th ACM International Conference on Computing Frontiers 2023, CF 2023. - 9798400701405 ; , s. 63-72
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Conference paper (peer-reviewed)abstract
- Deep Learning (DL) applications are entering every part of our life given their ability to solve complex problems. Nevertheless, energy efficiency is still a major concern due to the large computational and memory requirements. State-of-the-art accelerators strive to address this issue by optimizing the architecture to the compute requirements of DL algorithms. However, there is always a mismatch between compute and memory requirements and what is offered by a particular design. A way to close this gap is by providing run-time adaptation or resource allocation to improve efficiency. This paper proposes an adaptive resource allocation for deep learning applications (ARADA) with the goal of improving energy efficiency for deep learning accelerators. This is leveraged by having a layer-by-layer resource allocation. The rationale is that each layer in the DL model has a unique compute and memory bandwidth requirement and allocating fixed resources to all layers leads to inefficiencies. This can be achieved by means of resource allocation (e.g., voltage-frequency, memory bandwidth) to save energy without sacrificing performance. Experimental results show that applying ARADA to the execution of 9 state-of-the-art CNN models results in an energy savings of 38% on average compared to race-to-idle for an Edge TPU coupled with LPDDR4 off-chip memory.
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| 8. |
- Azhar, Muhammad Waqar, 1986, et al.
(author)
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Task-RM: A Resource Manager for Energy Reduction in Task-Parallel Applications under Quality of Service Constraints
- 2022
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In: Transactions on Architecture and Code Optimization. - : Association for Computing Machinery (ACM). - 1544-3973 .- 1544-3566. ; 19:1
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Journal article (peer-reviewed)abstract
- Improving energy efficiency is an important goal of computer system design. This article focuses on a general model of task-parallel applications under quality-of-service requirements on the completion time. Our technique, called Task-RM, exploits the variance in task execution-times and imbalance between tasks to allocate just enough resources in terms of voltage-frequency and core-allocation so that the application completes before the deadline. Moreover, we provide a solution that can harness additional energy savings with the availability of additional processors. We observe that, for the proposed run-time resource manager to allocate resources, it requires specification of the soft deadlines to the tasks. This is accomplished by analyzing the energy-saving scenarios offline and by providing Task-RM with the performance requirements of the tasks. The evaluation shows an energy saving of 33% compared to race-to-idle and 22% compared to dynamic slack allocation (DSA) with an overhead of less than 1%.
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| 9. |
- Azhar, Muhammad Waqar, 1986
(author)
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Techniques to Improve Energy Efficiency on Heterogeneous Multiprocessors under Timing and Quality Constraints
- 2022
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Doctoral thesis (other academic/artistic)abstract
- Traditionally, applications are executed without the notion of a computational deadline and often use all available system resources, which leads to higher energy consumption. User specification of Quality of Service (QoS) constraints, in terms of completion time and solution quality, opens up for allocation of just enough resources to an application to finish just in time and thereby save energy. Modern heterogeneous multiprocessor (HMP) platforms provide a set of configurable resources, including a frequency range of dynamic voltage frequency scaling (DVFS), one among a set processor types, and one or a plurality of processors of each type. They can be configured at run-time to open up new opportunities for resource management. This thesis presents techniques to reduce energy consumption under QoS constraints by allocating resources at run-time on heterogeneous multiprocessor platforms targeting sequential and parallel iterative and task-parallel applications. The proposed techniques rely on a progress-tracking framework that monitors and predicts how much time is left until the application finishes. Furthermore, the proposed framework enables the prediction of computation demand and performance requirements for future iterations or tasks. The first contribution of this thesis is a resource management technique, called SLOOP, targeting single-threaded applications. SLOOP allocates resources, i.e., processor type and DVFS, for each iteration to meet deadlines while using the prediction of computational demand and execution time. The second contribution of this thesis is a resource-management scheme, called SaC, for multi-threaded applications executing on HMPs, where resources also include the number of processors besides DVFS and processor type. SaC first chooses the most energy-efficient configuration that meets the deadline. The proposed technique collects execution-time slack over subsequent iterations to select a configuration that can save energy. The third contribution of this thesis is a resource manager, called Task-RM, for task-parallel applications executing on HMPs under QoS constraints. Task-RM exploits the variance in task execution times and imbalance between sibling tasks to allocate just enough resources in terms of DVFS and processor type. It uses an innovative off-line analysis to avoid redoing scheduling analysis at run-time. Finally, the fourth contribution is a scheme, called Approx-RM, that can exploit accuracy-energy trade-offs in approximate iterative applications. Approx-RM allocates an appropriate amount of resources while guaranteeing timing and solution quality specifications. Approx-RM first predicts the iteration count required to meet the quality target and then allocates enough resources on an HMP in terms of DVFS, processor type, and processor count to save energy while meeting a performance target.
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| 10. |
- Griessl, René, et al.
(author)
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A Scalable, Heterogeneous Hardware Platform for Accelerated AIoT based on Microservers
- 2023
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In: Shaping the Future of IoT with Edge Intelligence How Edge Computing Enables the Next Generation of IoT Applications. - 9788770040273 ; , s. 179-196
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Book chapter (other academic/artistic)abstract
- Performance and energy efficiency are key aspects of next-generation AIoT hardware. This chapter presents a scalable, heterogeneous hardware platform for accelerated AIoT based on microserver technology. It integrates several accelerator platforms based on technologies like CPUs, embedded GPUs, FPGAs, or specialized ASICs, supporting the full range of the cloud−edgeIoT continuum. The modular microserver approach enables the integrationof different, heterogeneous accelerators into one platform. Benchmarking the various accelerators takes performance, energy efficiency, and accuracy into account. The results provide a solid overview of available accelerator solutions and guide hardware selection for AIoT applications from the far edge to the cloud.
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