28 resultados para STOCHASTIC OPTIMAL CONTROL


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The method of stochastic dynamic programming is widely used in ecology of behavior, but has some imperfections because of use of temporal limits. The authors presented an alternative approach based on the methods of the theory of restoration. Suggested method uses cumulative energy reserves per time unit as a criterium, that leads to stationary cycles in the area of states. This approach allows to study the optimal feeding by analytic methods.

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Executive Summary The unifying theme of this thesis is the pursuit of a satisfactory ways to quantify the riskureward trade-off in financial economics. First in the context of a general asset pricing model, then across models and finally across country borders. The guiding principle in that pursuit was to seek innovative solutions by combining ideas from different fields in economics and broad scientific research. For example, in the first part of this thesis we sought a fruitful application of strong existence results in utility theory to topics in asset pricing. In the second part we implement an idea from the field of fuzzy set theory to the optimal portfolio selection problem, while the third part of this thesis is to the best of our knowledge, the first empirical application of some general results in asset pricing in incomplete markets to the important topic of measurement of financial integration. While the first two parts of this thesis effectively combine well-known ways to quantify the risk-reward trade-offs the third one can be viewed as an empirical verification of the usefulness of the so-called "good deal bounds" theory in designing risk-sensitive pricing bounds. Chapter 1 develops a discrete-time asset pricing model, based on a novel ordinally equivalent representation of recursive utility. To the best of our knowledge, we are the first to use a member of a novel class of recursive utility generators to construct a representative agent model to address some long-lasting issues in asset pricing. Applying strong representation results allows us to show that the model features countercyclical risk premia, for both consumption and financial risk, together with low and procyclical risk free rate. As the recursive utility used nests as a special case the well-known time-state separable utility, all results nest the corresponding ones from the standard model and thus shed light on its well-known shortcomings. The empirical investigation to support these theoretical results, however, showed that as long as one resorts to econometric methods based on approximating conditional moments with unconditional ones, it is not possible to distinguish the model we propose from the standard one. Chapter 2 is a join work with Sergei Sontchik. There we provide theoretical and empirical motivation for aggregation of performance measures. The main idea is that as it makes sense to apply several performance measures ex-post, it also makes sense to base optimal portfolio selection on ex-ante maximization of as many possible performance measures as desired. We thus offer a concrete algorithm for optimal portfolio selection via ex-ante optimization over different horizons of several risk-return trade-offs simultaneously. An empirical application of that algorithm, using seven popular performance measures, suggests that realized returns feature better distributional characteristics relative to those of realized returns from portfolio strategies optimal with respect to single performance measures. When comparing the distributions of realized returns we used two partial risk-reward orderings first and second order stochastic dominance. We first used the Kolmogorov Smirnov test to determine if the two distributions are indeed different, which combined with a visual inspection allowed us to demonstrate that the way we propose to aggregate performance measures leads to portfolio realized returns that first order stochastically dominate the ones that result from optimization only with respect to, for example, Treynor ratio and Jensen's alpha. We checked for second order stochastic dominance via point wise comparison of the so-called absolute Lorenz curve, or the sequence of expected shortfalls for a range of quantiles. As soon as the plot of the absolute Lorenz curve for the aggregated performance measures was above the one corresponding to each individual measure, we were tempted to conclude that the algorithm we propose leads to portfolio returns distribution that second order stochastically dominates virtually all performance measures considered. Chapter 3 proposes a measure of financial integration, based on recent advances in asset pricing in incomplete markets. Given a base market (a set of traded assets) and an index of another market, we propose to measure financial integration through time by the size of the spread between the pricing bounds of the market index, relative to the base market. The bigger the spread around country index A, viewed from market B, the less integrated markets A and B are. We investigate the presence of structural breaks in the size of the spread for EMU member country indices before and after the introduction of the Euro. We find evidence that both the level and the volatility of our financial integration measure increased after the introduction of the Euro. That counterintuitive result suggests the presence of an inherent weakness in the attempt to measure financial integration independently of economic fundamentals. Nevertheless, the results about the bounds on the risk free rate appear plausible from the view point of existing economic theory about the impact of integration on interest rates.

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Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

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Protective immune responses relyon TCR-mediated recognition of antigenspresented by MHC molecules. Tcells directed against tumor antigensare thought to express TCRs of loweraffinity/avidity than pathogen-specificT lymphocytes. An attractivestrategy to improve anti-tumor T cellresponses is to adoptively transferCD8+ T cells engineered with TCRsof optimized affinity. However, themechanisms that control optimal Tcell activation and responsiveness remainpoorly defined. We aim at characterizingTCR-pMHC binding parametersand downstream signalingevents that regulate T cell functionalityby using an in silico designedpanel of tumor antigen-specific TCRsof incremental affinity for pMHC(Kd100 M- 15 nM).We found that optimalT cell responses (cytokine secretionand target cell killing) occurredwithin a well-defined window ofTCR-pMHC binding affinity (5 M-1 M), while drastic functional declinewas detected in T cells expressingvery low and very high TCRaffinities,which was not caused by any increasein apoptosis. Whole-genomemicroarray analysis revealed that Tcells with optimal TCR affinitieshighly up-regulated transcription ofgenes typical of T cell activation (i.e.IFN-, NF-B and TNFR), while reducedexpression was detected in Tcells of very low or very high TCR affinity.Strikingly, hierarchical clusteringshowed that the latter two variantsclustered together with the un-stimulatedcontrol Tcells.Yet, despite commonclustering, several genes seemedto be differentially expressed, suggestingthat the mechanisms involvedin this "unresponsiveness state" maydiffer between those two variants. Finally,calcium influx assays also demonstratedattenuated responses in Tcells of very high TCR affinity. Ourresults indicate that optimal T cellfunction is tightly controlled within adefinedTCRaffinity window throughvery proximal TCR-mediated mechanisms,possibly at the TCR-pMHCbinding interface. Uncovering themechanisms regulating optimal/maximalT cell function is essential to understandand promote therapeutic designlike adoptive T cell therapy.

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During the first two trimesters of intrauterine life, fetal sex steroid production is driven by maternal human chorionic gonadotropin (hCG). The HPG axis is activated around the third trimester and remains active for the first 6-months of neonatal life. This so-called mini-puberty is a developmental window that has profound effects on future potential for fertility. In early puberty, GnRH secretion is reactivated first at night and then night and day. Pulsatile GnRH stimulates both LH and FSH, which induce maturation of the seminiferous tubules and Leydig cells. Congenital hypogonadotropic hypogonadism (CHH) results from GnRH deficiency. Men with CHH lack the mini-pubertal and pubertal periods of Sertoli Cell proliferation and thus present with prepubertal testes (<4mL) and low inhibin serum levels --reflecting diminished SC numbers. To induce full maturation of the testes, GnRH-deficient patients can be treated with either pulsatile GnRH, hCG or combined gonadotropin therapy (FSH+hCG). Fertility outcomes with each of these regimens are highly variable. Recently, a randomized, open label treatment study (n=13) addressed the question of whether a sequential treatment with FSH alone prior to LH and FSH (via GnRH pump) could enhance fertility outcomes. All men receiving the sequential treatment developed sperm in the ejaculate, whereas 2/6 men in the other group remained azoospermic. A large, multicenter clinical trial is needed to definitively prove the optimal treatment approach for severe CHH.

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Certain strains of fluorescent pseudomonads are important biological components of agricultural soils that are suppressive to diseases caused by pathogenic fungi on crop plants. The biocontrol abilities of such strains depend essentially on aggressive root colonization, induction of systemic resistance in the plant, and the production of diffusible or volatile antifungal antibiotics. Evidence that these compounds are produced in situ is based on their chemical extraction from the rhizosphere and on the expression of antibiotic biosynthetic genes in the producer strains colonizing plant roots. Well-characterized antibiotics with biocontrol properties include phenazines, 2,4-diacetylphloroglucinol, pyoluteorin, pyrrolnitrin, lipopeptides, and hydrogen cyanide. In vitro, optimal production of these compounds occurs at high cell densities and during conditions of restricted growth, involving (i) a number of transcriptional regulators, which are mostly pathway-specific, and (ii) the GacS/GacA two-component system, which globally exerts a positive effect on the production of extracellular metabolites at a posttranscriptional level. Small untranslated RNAs have important roles in the GacS/GacA signal transduction pathway. One challenge in future biocontrol research involves development of new strategies to overcome the broad toxicity and lack of antifungal specificity displayed by most biocontrol antibiotics studied so far.

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With six targeted agents approved (sorafenib, sunitinib, temsirolimus, bevacizumab [+interferon], everolimus and pazopanib), many patients with metastatic renal cell carcinoma (mRCC) will receive multiple therapies. However, the optimum sequencing approach has not been defined. A group of European experts reviewed available data and shared their clinical experience to compile an expert agreement on the sequential use of targeted agents in mRCC. To date, there are few prospective studies of sequential therapy. The mammalian target of rapamycin (mTOR) inhibitor everolimus was approved for use in patients who failed treatment with inhibitors of vascular endothelial growth factor (VEGF) and VEGF receptors (VEGFR) based on the results from a Phase III placebo-controlled study; however, until then, the only licensed agents across the spectrum of mRCC were VEGF(R) inhibitors (sorafenib, sunitinib and bevacizumab + interferon), and as such, a large body of evidence has accumulated regarding their use in sequence. Data show that sequential use of VEGF(R) inhibitors may be an effective treatment strategy to achieve prolonged clinical benefit. The optimal place of each targeted agent in the treatment sequence is still unclear, and data from large prospective studies are needed. The Phase III AXIS study of second-line sorafenib vs. axitinib (including post-VEGF(R) inhibitors) has completed, but the data are not yet published; other ongoing studies include the Phase III SWITCH study of sorafenib-sunitinib vs. sunitinib-sorafenib (NCT00732914); the Phase III 404 study of temsirolimus vs. sorafenib post-sunitinib (NCT00474786) and the Phase II RECORD 3 study of sunitinib-everolimus vs. everolimus-sunitinib (NCT00903175). Until additional data are available, consideration of patient response and tolerability to treatment may facilitate current decision-making regarding when to switch and which treatment to switch to in real-life clinical practice.

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Genomic islands (GEI) comprise a recently recognized large family of potentially mobile DNA elements and play an important role in the rapid differentiation and adaptation of bacteria. Most importantly, GEIs have been implicated in the acquisition of virulence factors, antibiotic resistances or toxic compound metabolism. Despite detailed information on coding capacities of GEIs, little is known about the regulatory decisions in individual cells controlling GEI transfer. Here, we show how self-transfer of ICEclc, a GEI in Pseudomonas knackmussii B13 is controlled by a series of stochastic processes, the result of which is that only a few percent of cells in a population will excise ICEclc and launch transfer. Stochastic processes have been implicated before in producing bistable phenotypic transitions, such as sporulation and competence development, but never before in horizontal gene transfer (HGT). Bistability is instigated during stationary phase at the level of expression of an activator protein InrR that lays encoded on ICEclc, and then faithfully propagated to a bistable expression of the IntB13 integrase, the enzyme responsible for excision and integration of the ICEclc. Our results demonstrate how GEI of a very widespread family are likely to control their transfer rates. Furthermore, they help to explain why HGT is typically confined to few members within a population of cells. The finding that, despite apparent stochasticity, HGT rates can be modulated by external environmental conditions provides an explanation as to why selective conditions can promote DNA exchange.

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BACKGROUND: Assessment of the proportion of patients with well controlled cardiovascular risk factors underestimates the proportion of patients receiving high quality of care. Evaluating whether physicians respond appropriately to poor risk factor control gives a different picture of quality of care. We assessed physician response to control cardiovascular risk factors, as well as markers of potential overtreatment in Switzerland, a country with universal healthcare coverage but without systematic quality monitoring, annual report cards on quality of care or financial incentives to improve quality. METHODS: We performed a retrospective cohort study of 1002 randomly selected patients aged 50-80 years from four university primary care settings in Switzerland. For hypertension, dyslipidemia and diabetes mellitus, we first measured proportions in control, then assessed therapy modifications among those in poor control. "Appropriate clinical action" was defined as a therapy modification or return to control without therapy modification within 12 months among patients with baseline poor control. Potential overtreatment of these conditions was defined as intensive treatment among low-risk patients with optimal target values. RESULTS: 20% of patients with hypertension, 41% with dyslipidemia and 36% with diabetes mellitus were in control at baseline. When appropriate clinical action in response to poor control was integrated into measuring quality of care, 52 to 55% had appropriate quality of care. Over 12 months, therapy of 61% of patients with baseline poor control was modified for hypertension, 33% for dyslipidemia, and 85% for diabetes mellitus. Increases in number of drug classes (28-51%) and in drug doses (10-61%) were the most common therapy modifications. Patients with target organ damage and higher baseline values were more likely to have appropriate clinical action. We found low rates of potential overtreatment with 2% for hypertension, 3% for diabetes mellitus and 3-6% for dyslipidemia. CONCLUSIONS: In primary care, evaluating whether physicians respond appropriately to poor risk factor control, in addition to assessing proportions in control, provide a broader view of the quality of care than relying solely on measures of proportions in control. Such measures could be more clinically relevant and acceptable to physicians than simply reporting levels of control.

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Even though patients who develop ischemic stroke despite taking antiplatelet drugs represent a considerable proportion of stroke hospital admissions, there is a paucity of data from investigational studies regarding the most suitable therapeutic intervention. There have been no clinical trials to test whether increasing the dose or switching antiplatelet agents reduces the risk for subsequent events. Certain issues have to be considered in patients managed for a first or recurrent stroke while receiving antiplatelet agents. Therapeutic failure may be due to either poor adherence to treatment, associated co-morbid conditions and diminished antiplatelet effects (resistance to treatment). A diagnostic work up is warranted to identify the etiology and underlying mechanism of stroke, thereby guiding further management. Risk factors (including hypertension, dyslipidemia and diabetes) should be treated according to current guidelines. Aspirin or aspirin plus clopidogrel may be used in the acute and early phase of ischemic stroke, whereas in the long-term, antiplatelet treatment should be continued with aspirin, aspirin/extended release dipyridamole or clopidogrel monotherapy taking into account tolerance, safety, adherence and cost issues. Secondary measures to educate patients about stroke, the importance of adherence to medication, behavioral modification relating to tobacco use, physical activity, alcohol consumption and diet to control excess weight should also be implemented.

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Spontaneous polarization without spatial cues, or symmetry breaking, is a fundamental problem of spatial organization in biological systems. This question has been extensively studied using yeast models, which revealed the central role of the small GTPase switch Cdc42. Active Cdc42-GTP forms a coherent patch at the cell cortex, thought to result from amplification of a small initial stochastic inhomogeneity through positive feedback mechanisms, which induces cell polarization. Here, I review and discuss the mechanisms of Cdc42 activity self-amplification and dynamic turnover. A robust Cdc42 patch is formed through the combined effects of Cdc42 activity promoting its own activation and active Cdc42-GTP displaying reduced membrane detachment and lateral diffusion compared to inactive Cdc42-GDP. I argue the role of the actin cytoskeleton in symmetry breaking is not primarily to transport Cdc42 to the active site. Finally, negative feedback and competition mechanisms serve to control the number of polarization sites.

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The fight against doping in sports has been governed since 1999 by the World Anti-Doping Agency (WADA), an independent institution behind the implementation of the World Anti-Doping Code (Code). The intent of the Code is to protect clean athletes through the harmonization of anti-doping programs at the international level with special attention to detection, deterrence and prevention of doping.1 A new version of the Code came into force on January 1st 2015, introducing, among other improvements, longer periods of sanctioning for athletes (up to four years) and measures to strengthen the role of anti-doping investigations and intelligence. To ensure optimal harmonization, five International Standards covering different technical aspects of the Code are also currently in force: the List of Prohibited Substances and Methods (List), Testing and Investigations, Laboratories, Therapeutic Use Exemptions (TUE) and Protection of Privacy and Personal Information. Adherence to these standards is mandatory for all anti-doping stakeholders to be compliant with the Code. Among these documents, the eighth version of International Standard for Laboratories (ISL), which also came into effect on January 1st 2015, includes regulations for WADA and ISO/IEC 17025 accreditations and their application for urine and blood sample analysis by anti-doping laboratories.2 Specific requirements are also described in several Technical Documents or Guidelines in which various topics are highlighted such as the identification criteria for gas chromatography (GC) and liquid chromatography (LC) coupled to mass spectrometry (MS) techniques (IDCR), measurements and reporting of endogenous androgenic anabolic agents (EAAS) and analytical requirements for the Athlete Biological Passport (ABP).

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Electrical neuromodulation of lumbar segments improves motor control after spinal cord injury in animal models and humans. However, the physiological principles underlying the effect of this intervention remain poorly understood, which has limited the therapeutic approach to continuous stimulation applied to restricted spinal cord locations. Here we developed stimulation protocols that reproduce the natural dynamics of motoneuron activation during locomotion. For this, we computed the spatiotemporal activation pattern of muscle synergies during locomotion in healthy rats. Computer simulations identified optimal electrode locations to target each synergy through the recruitment of proprioceptive feedback circuits. This framework steered the design of spatially selective spinal implants and real-time control software that modulate extensor and flexor synergies with precise temporal resolution. Spatiotemporal neuromodulation therapies improved gait quality, weight-bearing capacity, endurance and skilled locomotion in several rodent models of spinal cord injury. These new concepts are directly translatable to strategies to improve motor control in humans.