27 resultados para Real Root Isolation Methods
Resumo:
Critical real-time ebedded (CRTE) Systems require safe and tight worst-case execution time (WCET) estimations to provide required safety levels and keep costs low. However, CRTE Systems require increasing performance to satisfy performance needs of existing and new features. Such performance can be only achieved by means of more agressive hardware architectures, which are much harder to analyze from a WCET perspective. The main features considered include cache memòries and multi-core processors.Thus, althoug such features provide higher performance, corrent WCET analysis methods are unable to provide tight WCET estimations. In fact, WCET estimations become worse than for simple rand less powerful hardware. The main reason is the fact that hardware behavior is deterministic but unknown and, therefore, the worst-case behavior must be assumed most of the time, leading to large WCET estimations. The purpose of this project is developing new hardware designs together with WCET analysis tools able to provide tight and safe WCET estimations. In order to do so, those pieces of hardware whose behavior is not easily analyzable due to lack of accurate information during WCET analysis will be enhanced to produce a probabilistically analyzable behavior. Thus, even if the worst-case behavior cannot be removed, its probabilty can be bounded, and hence, a safe and tight WCET can be provided for a particular safety level in line with the safety levels of the remaining components of the system. During the first year the project we have developed molt of the evaluation infraestructure as well as the techniques hardware techniques to analyze cache memories. During the second year those techniques have been evaluated, and new purely-softwar techniques have been developed.
Resumo:
The pseudo-spectral time-domain (PSTD) method is an alternative time-marching method to classicalleapfrog finite difference schemes in the simulation of wave-like propagating phenomena. It is basedon the fundamentals of the Fourier transform to compute the spatial derivatives of hyperbolic differential equations. Therefore, it results in an isotropic operator that can be implemented in an efficient way for room acoustics simulations. However, one of the first issues to be solved consists on modeling wallabsorption. Unfortunately, there are no references in the technical literature concerning to that problem. In this paper, assuming real and constant locally reacting impedances, several proposals to overcome this problem are presented, validated and compared to analytical solutions in different scenarios.
Resumo:
The Pseudo-Spectral Time Domain (PSTD) method is an alternative time-marching method to classical leapfrog finite difference schemes inthe simulation of wave-like propagating phenomena. It is based on the fundamentals of the Fourier transform to compute the spatial derivativesof hyperbolic differential equations. Therefore, it results in an isotropic operator that can be implemented in an efficient way for room acousticssimulations. However, one of the first issues to be solved consists on modeling wall absorption. Unfortunately, there are no references in thetechnical literature concerning to that problem. In this paper, assuming real and constant locally reacting impedances, several proposals toovercome this problem are presented, validated and compared to analytical solutions in different scenarios.
Resumo:
The well-known lack of power of unit root tests has often been attributed to the shortlength of macroeconomic variables and also to DGP s that depart from the I(1)-I(0)alternatives. This paper shows that by using long spans of annual real GNP and GNPper capita (133 years) high power can be achieved, leading to the rejection of both theunit root and the trend-stationary hypothesis. This suggests that possibly neither modelprovides a good characterization of these data. Next, more flexible representations areconsidered, namely, processes containing structural breaks (SB) and fractional ordersof integration (FI). Economic justification for the presence of these features in GNP isprovided. It is shown that the latter models (FI and SB) are in general preferred to theARIMA (I(1) or I(0)) ones. As a novelty in this literature, new techniques are appliedto discriminate between FI and SB models. It turns out that the FI specification ispreferred, implying that GNP and GNP per capita are non-stationary, highly persistentbut mean-reverting series. Finally, it is shown that the results are robust when breaksin the deterministic component are allowed for in the FI model. Some macroeconomicimplications of these findings are also discussed.
Resumo:
This paper presents a comparative analysis of linear and mixed modelsfor short term forecasting of a real data series with a high percentage of missing data. Data are the series of significant wave heights registered at regular periods of three hours by a buoy placed in the Bay of Biscay.The series is interpolated with a linear predictor which minimizes theforecast mean square error. The linear models are seasonal ARIMA models and themixed models have a linear component and a non linear seasonal component.The non linear component is estimated by a non parametric regression of dataversus time. Short term forecasts, no more than two days ahead, are of interestbecause they can be used by the port authorities to notice the fleet.Several models are fitted and compared by their forecasting behavior.
Resumo:
Companies are under IAS 40 required to report fair values of investment properties on the balance sheet or to disclose them in the notes. The standard requires also that companies have to disclose the methods and significant assumptions applied in determining fair values of investment properties. However, IAS 40 does not include any illustrative examples or other guidance on how to apply the disclosure requirements. We use a sample with publicly traded companies from the real estate sector in the EU. We find that a majority of the companies use income based methods for the measurement of fair values but there are considerable cross-country variations in the level of disclosures about the assumptions used in determining fair values. More specifically, we find that Scandinavian and German origin companies disclose more than French and English origin companies. We also test whether disclosure quality is associated with enforcement quality measured with the “Rule of Law” index according to Kaufmann et al. (2010), and associated with a secrecy- versus transparency-measure based on Gray (1988). We find a positive association between disclosure and earnings quality and a negative association with secrecy.
Resumo:
In the past decades drug discovery practice has escaped from the complexity of the formerly used phenotypic screening in animals to focus on assessing drug effects on isolated protein targets in the search for drugs that exclusively and potently hit one selected target, thought to be critical for a given disease, while not affecting at all any other target to avoid the occurrence of side-effects. However, reality does not conform to these expectations, and, conversely, this approach has been concurrent with increased attrition figures in late-stage clinical trials, precisely due to lack of efficacy and safety. In this context, a network biology perspective of human disease and treatment has burst into the drug discovery scenario to bring it back to the consideration of the complexity of living organisms and particularly of the (patho)physiological environment where protein targets are (mal)functioning and where drugs have to exert their restoring action. Under this perspective, it has been found that usually there is not one but several disease-causing genes and, therefore, not one but several relevant protein targets to be hit, which do not work on isolation but in a highly interconnected manner, and that most known drugs are inherently promiscuous. In this light, the rationale behind the currently prevailing single-target-based drug discovery approach might even seem a Utopia, while, conversely, the notion that the complexity of human disease must be tackled with complex polypharmacological therapeutic interventions constitutes a difficult-torefuse argument that is spurring the development of multitarget therapies.
Resumo:
In this work annealing and growth of CuInS2 thin films is investigated with quasireal-time in situ Raman spectroscopy. During the annealing a shift of the Raman A1 mode towards lower wave numbers with increasing temperature is observed. A linear temperature dependence of the phonon branch of ¿2 cm¿1/100 K is evaluated. The investigation of the growth process (sulfurization of metallic precursors) with high surface sensitivity reveals the occurrence of phases which are not detected with bulk sensitive methods. This allows a detailed insight in the formation of the CuInS2 phases. Independent from stoichiometry and doping of the starting precursors the CuAu ordering of CuInS2 initially forms as the dominating ordering. The transformation of the CuAu ordering into the chalcopyrite one is, in contrast, strongly dependent on the precursor composition and requires high temperatures.
Resumo:
This paper re-examines the null of stationary of real exchange rate for a panel of seventeen OECD developed countries during the post-Bretton Woods era. Our analysis simultaneously considers both the presence of cross-section dependence and multiple structural breaks that have not received much attention in previous panel methods of long-run PPP. Empirical results indicate that there is little evidence in favor of PPP hypothesis when the analysis does not account for structural breaks. This conclusion is reversed when structural breaks are considered in computation of the panel statistics. We also compute point estimates of half-life separately for idiosyncratic and common factor components and find that it is always below one year.
Resumo:
Plants constitute an excellent ecosystem for microorganisms. The environmental conditions offered differ considerably between the highly variable aerial plant part and the more stable root system. Microbes interact with plant tissues and cells with different degrees of dependence. The most interesting from the microbial ecology point of view, however, are specific interactions developed by plant-beneficial (either non-symbiotic or symbiotic) and pathogenic microorganisms. Plants, like humans and other animals, also become sick, but they have evolved a sophisticated defense response against microbes, based on a combination of constitutive and inducible responses which can be localized or spread throughout plant organs and tissues. The response is mediated by several messenger molecules that activate pathogen-responsive genes coding for enzymes or antimicrobial compounds, and produces less sophisticated and specific compounds than immunoglobulins in animals. However, the response specifically detects intracellularly a type of protein of the pathogen based on a gene-for-gene interaction recognition system, triggering a biochemical attack and programmed cell death. Several implications for the management of plant diseases are derived from knowledge of the basis of the specificity of plant-bacteria interactions. New biotechnological products are currently being developed based on stimulation of the plant defense response, and on the use of plant-beneficial bacteria for biological control of plant diseases (biopesticides) and for plant growth promotion (biofertilizers)
Resumo:
In the past decades drug discovery practice has escaped from the complexity of the formerly used phenotypic screening in animals to focus on assessing drug effects on isolated protein targets in the search for drugs that exclusively and potently hit one selected target, thought to be critical for a given disease, while not affecting at all any other target to avoid the occurrence of side-effects. However, reality does not conform to these expectations, and, conversely, this approach has been concurrent with increased attrition figures in late-stage clinical trials, precisely due to lack of efficacy and safety. In this context, a network biology perspective of human disease and treatment has burst into the drug discovery scenario to bring it back to the consideration of the complexity of living organisms and particularly of the (patho)physiological environment where protein targets are (mal)functioning and where drugs have to exert their restoring action. Under this perspective, it has been found that usually there is not one but several disease-causing genes and, therefore, not one but several relevant protein targets to be hit, which do not work on isolation but in a highly interconnected manner, and that most known drugs are inherently promiscuous. In this light, the rationale behind the currently prevailing single-target-based drug discovery approach might even seem a Utopia, while, conversely, the notion that the complexity of human disease must be tackled with complex polypharmacological therapeutic interventions constitutes a difficult-torefuse argument that is spurring the development of multitarget therapies.
Resumo:
BACKGROUND: This study examined potential predictors of remission among patients treated for major depressive disorder (MDD) in a naturalistic clinical setting, mostly in the Middle East, East Asia, and Mexico. METHODS: Data for this post hoc analysis were taken from a 6-month prospective, noninterventional, observational study that involved 1,549 MDD patients without sexual dysfunction at baseline in 12 countries worldwide. Depression severity was measured using the Clinical Global Impression of Severity and the 16-item Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR16). Depression-related pain was measured using the pain-related items of the Somatic Symptom Inventory. Remission was defined as a QIDS-SR16 score ≤5. Generalized estimating equation regression models were used to examine baseline factors associated with remission during follow-up. RESULTS: Being from East Asia (odds ratio [OR] 0.48 versus Mexico; P<0.001), a higher level of depression severity at baseline (OR 0.77, P=0.003, for Clinical Global Impression of Severity; OR 0.92, P<0.001, for QIDS-SR16), more previous MDD episodes (OR 0.92, P=0.007), previous treatments/therapies for depression (OR 0.78, P=0.030), and having any significant psychiatric and medical comorbidity at baseline (OR 0.60, P<0.001) were negatively associated with remission, whereas being male (OR 1.29, P=0.026) and treatment with duloxetine (OR 2.38 versus selective serotonin reuptake inhibitors, P<0.001) were positively associated with remission. However, the association between Somatic Symptom Inventory pain scores and remission no longer appeared to be significant in this multiple regression (P=0.580), (P=0.008 in descriptive statistics), although it remained significant in a subgroup of patients treated with selective serotonin reuptake inhibitors (OR 0.97, P=0.023), but not in those treated with duloxetine (P=0.182). CONCLUSION: These findings are largely consistent with previous reports from the USA and Europe. They also highlight the potential mediating role of treatment with duloxetine on the negative relationship between depression-related pain and outcomes of depression.