84 research outputs found
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Performance portability of Earth system models with user-controlled GGDML code translation
The increasing need for performance of earth system modeling and other scientific domains pushes the computing technologies in diverse architectural directions. The development of models needs technical expertise and skills of using tools that are able to exploit the hardware capabilities. The heterogeneity of architectures complicates the development and the maintainability of the models. To improve the software development process of earth system models, we provide an approach that simplifies the code maintainability by fostering separation of concerns while providing performance portability. We propose the use of high-level language extensions that reflect scientific concepts. The scientists can use the programming language of their own choice to develop models, however, they can use the language extensions optionally wherever they need. The code translation is driven by configurations that are separated from the model source code. These configurations are prepared by scientific programmers to optimally use the machine’s features. The main contribution of this paper is the demonstration of a user-controlled source-to-source translation technique of earth system models that are written with higher-level semantics. We discuss a flexible code translation technique that is driven by the users through a configuration input that is prepared especially to transform the code, and we use this technique to produce OpenMP or OpenACC enabled codes besides MPI to support multi-node configurations
Predicting the outcomes of traumatic brain injury using accurate and dynamic predictive model
Predictive models have been used widely to predict the diseases outcomes in health sector. These predictive models are emerged with new information and communication technologies. Traumatic brain injury has recognizes as a serious and crucial health problem all over the world. In order to predict brain injuries outcomes, the predictive models are still suffered with predictive performance. In this paper, we propose a new predictive model and traumatic brain injury predictive model to improve the predictive performance to classifying the disease predictions into different categories. These proposed predictive models support to develop the traumatic brain injury predictive model. A primary dataset is constructed which is based on approved set of features by the neurologist. The results of proposed model is indicated that model has achieved the best average ranking in terms of accuracy, sensitivity and specificity
A critical review on the synthesis of natural sodium alginate based composite materials: An innovative biological polymer for biomedical delivery applications
Sodium alginate (Na-Alg) is water-soluble, neutral, and linear polysaccharide. It is the derivative of alginic acid which comprises 1,4-β-d-mannuronic (M) and α-l-guluronic (G) acids and has the chemical formula (NaC6H7O6). It shows water-soluble, non-toxic, biocompatible, biodegradable, and non-immunogenic properties. It had been used for various biomedical applications, among which the most promising are drug delivery, gene delivery, wound dressing, and wound healing. For different biomedical applications, it is used in different forms with the help of new techniques. That is the reason it had been blended with different polymers. In this review article, we present a comprehensive overview of the combinations of sodium alginate with natural and synthetic polymers and their biomedical applications involving delivery systems. All the scientific/technical issues have been addressed, and we have highlighted the recent advancements
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AIMES: advanced computation and I/O methods for earth-system simulations
Dealing with extreme scale Earth-system models is challenging from the computer science perspective, as the required computing power and storage capacity are steadily increasing.
Scientists perform runs with growing resolution or aggregate results from many similar smaller-scale runs with slightly different initial conditions (the so-called ensemble runs).
In the fifth Coupled Model Intercomparison Project (CMIP5), the produced datasets require more than three Petabytes of storage and the compute and storage requirements are increasing significantly for CMIP6.
Climate scientists across the globe are developing next-generation models based on improved numerical formulation leading to grids that are discretized in alternative forms such as an icosahedral (geodesic) grid.
The developers of these models face similar problems in scaling, maintaining and optimizing code.
Performance portability and the maintainability of code are key concerns of scientists as, compared to industry projects, model code is continuously revised and extended to incorporate further levels of detail.
This leads to a rapidly growing code base that is rarely refactored.
However, code modernization is important to maintain productivity of the scientist working
with the code and for utilizing performance provided by modern and future architectures.
The need for performance optimization is motivated by the evolution of the parallel architecture landscape from
homogeneous flat machines to heterogeneous combinations of processors with deep memory hierarchy.
Notably, the rise of many-core, throughput-oriented accelerators, such as GPUs, requires non-trivial code changes at minimum and, even worse, may necessitate a substantial rewrite of the existing codebase.
At the same time, the code complexity increases the difficulty for computer scientists and vendors to understand and optimize the code for a given system.
Storing the products of climate predictions requires a large storage and archival system which is expensive.
Often, scientists restrict the number of scientific variables and write interval to keep the costs
balanced.
Compression algorithms can reduce the costs significantly but can also increase the scientific yield of simulation runs.
In the AIMES project, we addressed the key issues of programmability, computational efficiency and I/O limitations that are common in next-generation icosahedral earth-system models.
The project focused on the separation of concerns between domain scientist, computational scientists, and computer scientists
Synthesis, Characterization, and Biological Properties of Iron Oxide Nanoparticles Synthesized from Apis mellifera Honey
Green approaches for nanoparticle synthesis have emerged as biocompatible, economical, and environment-friendly alternatives to counteract the menace of microbial drug resistance. Recently, the utilization of honey as a green source to synthesize Fe2O3-NPs has been introduced, but its antibacterial activity against one of the opportunistic MDR pathogens, Klebsiella pneumoniae, has not been explored. Therefore, this study employed Apis mellifera honey as a reducing and capping agent for the synthesis of iron oxide nanoparticles (Fe2O3-NPs). Subsequent to the characterization of nanoparticles, their antibacterial, antioxidant, and anti-inflammatory properties were appraised. In UV-Vis spectroscopic analysis, the absorption band ascribed to the SPR peak was observed at 350 nm. XRD analysis confirmed the crystalline nature of Fe2O3-NPs, and the crystal size was deduced to be 36.2 nm. Elemental analysis by EDX validated the presence of iron coupled with oxygen in the nanoparticle composition. In ICP-MS, the highest concentration was of iron (87.15 ppm), followed by sodium (1.49 ppm) and other trace elements (<1 ppm). VSM analysis revealed weak magnetic properties of Fe2O3-NPs. Morphological properties of Fe2O3-NPs revealed by SEM demonstrated that their average size range was 100–150 nm with a non-uniform spherical shape. The antibacterial activity of Fe2O3-NPs was ascertained against 30 clinical isolates of Klebsiella pneumoniae, with the largest inhibition zone recorded being 10 mm. The MIC value for Fe2O3-NPs was 30 µg/mL. However, when mingled with three selected antibiotics, Fe2O3-NPs did not affect any antibacterial activity. Momentous antioxidant (IC50 = 22 µg/mL) and anti-inflammatory (IC50 = 70 µg/mL) activities of Fe2O3-NPs were discerned in comparison with the standard at various concentrations. Consequently, honey-mediated Fe2O3-NP synthesis may serve as a substitute for orthodox antimicrobial drugs and may be explored for prospective biomedical applications. © 2023 by the authors.Princess Nourah Bint Abdulrahman University, PNU: PNURSP2023R108This research project was supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R108), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
Structured headache services as the solution to the ill-health burden of headache: 1. Rationale and description
In countries where headache services exist at all, their focus is usually on specialist (tertiary) care. This is clinically and economically inappropriate: most headache disorders can effectively and more efficiently (and at lower cost) be treated in educationally supported primary care. At the same time, compartmentalizing divisions between primary, secondary and tertiary care in many health-care systems create multiple inefficiencies, confronting patients attempting to navigate these levels (the “patient journey”) with perplexing obstacles. High demand for headache care, estimated here in a needs-assessment exercise, is the biggest of the challenges to reform. It is also the principal reason why reform is necessary. The structured headache services model presented here by experts from all world regions on behalf of the Global Campaign against Headache is the suggested health-care solution to headache. It develops and refines previous proposals, responding to the challenge of high demand by basing headache services in primary care, with two supporting arguments. First, only primary care can deliver headache services equitably to the large numbers of people needing it. Second, with educational supports, they can do so effectively to most of these people. The model calls for vertical integration between care levels (primary, secondary and tertiary), and protection of the more advanced levels for the minority of patients who need them. At the same time, it is amenable to horizontal integration with other care services. It is adaptable according to the broader national or regional health services in which headache services should be embedded. It is, according to evidence and argument presented, an efficient and cost-effective model, but these are claims to be tested in formal economic analyses
Antidiabetic Effect of Monolluma quadrangula Is Mediated via Modulation of Glucose Metabolizing Enzymes, Antioxidant Defenses, and Adiponectin in Type 2 Diabetic Rats
Monolluma quadrangula is a succulent bush traditionally used to treat diabetes and peptic ulcer. The present study aimed to investigate the effect of M. quadrangula hydroethanolic extract on glucose tolerance, insulin sensitivity, glucose metabolizing enzymes, lipid profile, and adiponectin expression in type 2 diabetic rats. In addition, the study evaluated the antioxidant and anti-inflammatory activities of the M. quadrangula extract. Type 2 diabetes was induced by feeding rats a high-fat diet (HFD) for 8 weeks followed by 30 mg/kg streptozotocin (STZ). Diabetic rats received 300 or 600 mg/kg M. quadrangula extract for 4 weeks. HFD/STZ diabetic rats showed impaired glucose tolerance, reduced insulin secretion, and insulin resistance. HFD and STZ induced a significant increase in serum cholesterol, triglycerides and proinflammatory cytokines, and liver lipid peroxidation. Treatment with M. quadrangula extract ameliorated these metabolic disturbances and increased liver glycogen, hexokinase activity, and antioxidants. M. quadrangula declined the activity of liver glucose-6-phosphatase and fructose-1,6-biphosphatase. In addition, M. quadrangula extract increased serum adiponectin levels and hepatic adiponectin expression in HFD/STZ diabetic rats. In conclusion, M. quadrangula exerts antidiabetic effect mediated via ameliorating glucose tolerance, insulin sensitivity, glucose metabolizing enzymes, and antioxidant defenses. Increased adiponectin levels and expression seems to mediate, at least in part, the antidiabetic effect of M. quadrangula
Monolluma quadrangula Protects against Oxidative Stress and Modulates LDL Receptor and Fatty Acid Synthase Gene Expression in Hypercholesterolemic Rats
Hypercholesterolemia is a metabolic disorder associated with oxidative stress. The present study investigated the protective effect of Monolluma quadrangula extract on hypercholesterolemia-induced oxidative stress in the liver and heart of high-cholesterol-diet- (HCD-) fed rats. The experimental animals received HCD for 10 weeks and were concurrently treated with 300 or 600 mg/kg M. quadrangula extract. HCD-fed rats showed a significant increase in serum triglycerides, total cholesterol, LDL-cholesterol, vLDL-cholesterol, and cardiovascular risk indices along with decreased HDL-cholesterol and antiatherogenic index. The M. quadrangula extract significantly improved dyslipidemia and atherogenesis in HCD-fed rats. HCD induced a significant increase in serum transaminases, creatine kinase-MB, and proinflammatory cytokines. In addition, HDC induced a significant increase in hepatic and cardiac lipid peroxidation and decreased antioxidant enzymes. Treatment with the M. quadrangula extract significantly alleviated liver and heart function markers, decreased proinflammatory cytokines and lipid peroxidation, and enhanced the antioxidant defenses. Also, the M. quadrangula extract significantly reduced the expression of fatty acid synthase (FAS) and increased the expression of LDL receptor in the liver of HCD-fed rats. In conclusion, the M. quadrangula extract has a potent antihyperlipidemic and cholesterol-lowering effect on HCD-fed rats. The beneficial effects of the M. quadrangula extract were mediated through the increased antioxidant defenses, decreased inflammation and lipid peroxidation, and modulated hepatic FAS and LDL receptor gene expression
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