121 research outputs found

    Stochastic Learning Feedback Hybrid Automata for Dynamic Power Management in Embedded Systems

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    Dynamic power management (DPM) refers to the strategies employed at system level to reduce energy expenditure (i.e. to prolong battery life) in embedded systems. The trade-off involved in DPM techniques is between the reductions of energy consumption and latency suffered by the tasks. Such trade-offs need to be decided at runtime, making DPM an on-line problem. We formulate DPM as a hybrid automaton control problem and integrate stochastic control. The control strategy is learnt dynamically using stochastic learning hybrid automata (SLHA) with feedback learning algorithms. Simulation-based experiments show the expediency of the feedback systems in stationary environments. Further experiments reveal that SLHA attains better trade-offs than several former predictive algorithms under certain trace data

    Stochastic Learning Feedback Hybrid Automata for Power Management in Embedded Systems

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    In this paper we show that stochastic learning automata based feedback control switching strategy can be used for dynamic power management (DPM) employed at the system level. DPM strategies are usually incorporated at the operating systems of embedded devices to exploit multiple power states available in today\u27s ACPI compliant devices. The idea is to switch between power states depending on the device usage, and since device usage times are not deterministic, probabilistic techniques are often used to create stochastic strategies, or strategies that make decisions based on probabilities of device usage spans. Previous work (Irani et al., 2001) has shown how to approximate the probability distribution of device idle times and dynamically update them, and then use such knowledge in controlling power states. Here, we use stochastic learning automata (SLA) which interacts with the environment to update such probabilities, and then apply techniques similar to (Irani et al., 2001) to optimize power usage with minimal effect on response time for the devices

    A Cell-Free Microtiter Plate Screen for Improved [FeFe] Hydrogenases

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    , a potential renewable fuel. Attempts to exploit these catalysts in engineered systems have been hindered by the biotechnologically inconvenient properties of the natural enzymes, including their extreme oxygen sensitivity. Directed evolution has been used to improve the characteristics of a range of natural catalysts, but has been largely unsuccessful for [FeFe] hydrogenases because of a lack of convenient screening platforms. [FeFe] hydrogenase HydA1 with a specific activity ∼4 times that of the wild-type enzyme. cell extracts, which allows unhindered access to the protein maturation and assay environment

    Mental Health Diagnoses and Utilization of VA Non-Mental Health Medical Services Among Returning Iraq and Afghanistan Veterans

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    Over 35% of returned Iraq and Afghanistan veterans in VA care have received mental health diagnoses; the most prevalent is post-traumatic stress disorder (PTSD). Little is known about these patients’ use of non-mental health medical services and the impact of mental disorders on utilization. To compare utilization across three groups of Iraq and Afghanistan veterans: those without mental disorders, those with mental disorders other than PTSD, and those with PTSD. National, descriptive study of 249,440 veterans newly utilizing VA healthcare between October 7, 2001 and March 31, 2007, followed until March 31, 2008. We used ICD9-CM diagnostic codes to classify mental health status. We compared utilization of outpatient non-mental health services, primary care, medical subspecialty, ancillary services, laboratory tests/diagnostic procedures, emergency services, and hospitalizations during veterans’ first year in VA care. Results were adjusted for demographics and military service and VA facility characteristics. Veterans with mental disorders had 42–146% greater utilization than those without mental disorders, depending on the service category (all P < 0.001). Those with PTSD had the highest utilization in all categories: 71–170% greater utilization than those without mental disorders (all P < 0.001). In adjusted analyses, compared with veterans without mental disorders, those with mental disorders other than PTSD had 55% higher utilization of all non-mental health outpatient services; those with PTSD had 91% higher utilization. Female sex and lower rank were also independently associated with greater utilization. Veterans with mental health diagnoses, particularly PTSD, utilize significantly more VA non-mental health medical services. As more veterans return home, we must ensure resources are allocated to meet their outpatient, inpatient, and emergency needs

    Clinical use of biomarkers of survival in pulmonary fibrosis

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    <p>Abstract</p> <p>Background</p> <p>Biologic predictors or biomarkers of survival in pulmonary fibrosis with a worse prognosis, more specifically in idiopathic pulmonary fibrosis would help the clinician in deciding whether or not to treat since treatment carries a potential risk for adverse events. These decisions are made easier if accurate and objective measurements of the patients' clinical status can predict the risk of progression to death.</p> <p>Method</p> <p>A literature review is given on different biomarkers of survival in interstitial lung disease, mainly in IPF, since this disease has the worst prognosis.</p> <p>Conclusion</p> <p>Serum biomarkers, and markers measured by medical imaging as HRCT, pertechnegas, DTPA en FDG-PET are not ready for clinical use to predict mortality in different forms of ILD. A baseline FVC, a change of FVC of more than 10%, and change in 6MWD are clinically helpful predictors of survival.</p

    Tspan8 is expressed in breast cancer and regulates E-cadherin/catenin signalling and metastasis accompanied by increased circulating extracellular vesicles

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    Tspan8 exhibits a functional role in many cancer types including pancreatic, colorectal, oesophagus carcinoma, and melanoma. We present a first study on the expression and function of Tspan8 in breast cancer. Tspan8 protein was present in the majority of human primary breast cancer lesions and metastases in the brain, bone, lung, and liver. In a syngeneic rat breast cancer model, Tspan8+^{+} tumours formed multiple liver and spleen metastases, while Tspan8^{-} tumours exhibited a significantly diminished ability to metastasise, indicating a role of Tspan8 in metastases. Addressing the underlying molecular mechanisms, we discovered that Tspan8 can mediate up‐regulation of E‐cadherin and down‐regulation of Twist, p120‐catenin, and β‐catenin target genes accompanied by the change of cell phenotype, resembling the mesenchymal–epithelial transition. Furthermore, Tspan8+^{+} cells exhibited enhanced cell–cell adhesion, diminished motility, and decreased sensitivity to irradiation. As a regulator of the content and function of extracellular vesicles (EVs), Tspan8 mediated a several‐fold increase in EV number in cell culture and the circulation of tumour‐bearing animals. We observed increased protein levels of E‐cadherin and p120‐catenin in these EVs; furthermore, Tspan8 and p120‐catenin were co‐immunoprecipitated, indicating that they may interact with each other. Altogether, our findings show the presence of Tspan8 in breast cancer primary lesion and metastases and indicate its role as a regulator of cell behaviour and EV release in breast cancer

    Assessing Tuberculosis Case Fatality Ratio: A Meta-Analysis

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    Background: Recently, the tuberculosis (TB) Task Force Impact Measurement acknowledged the need to review the assumptions underlying the TB mortality estimates published annually by the World Health Organization (WHO). TB mortality is indirectly measured by multiplying estimated TB incidence with estimated case fatality ratio (CFR). We conducted a meta-analysis to estimate the TB case fatality ratio in TB patients having initiated TB treatment. Methods: We searched for eligible studies in the PubMed and Embase databases through March 4(th) 2011 and by reference listing of relevant review articles. Main analyses included the estimation of the pooled percentages of: a) TB patients dying due to TB after having initiated TB treatment and b) TB patients dying during TB treatment. Pooled percentages were estimated using random effects regression models on the combined patient population from all studies. Main Results: We identified 69 relevant studies of which 22 provided data on mortality due to TB and 59 provided data on mortality during TB treatment. Among HIV infected persons the pooled percentage of TB patients dying due to TB was 9.2% (95% Confidence Interval (CI): 3.7%-14.7%) and among HIV uninfected persons 3.0% (95% CI: 21.2%-7.4%) based on the results of eight and three studies respectively providing data for this analyses. The pooled percentage of TB patients dying during TB treatment was 18.8% (95% CI: 14.8%-22.8%) among HIV infected patients and 3.5% (95% CI: 2.0%-4.92%) among HIV uninfected patients based on the results of 27 and 19 studies respectively. Conclusion: The results of the literature review are useful in generating prior distributions of CFR in countries with vital registration systems and have contributed towards revised estimates of TB mortality This literature review did not provide us with all data needed for a valid estimation of TB CFR in TB patients initiating TB treatmen

    Enhancing discovery of genetic variants for posttraumatic stress disorder through integration of quantitative phenotypes and trauma exposure information

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    Background Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods
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