60 resultados para Inverse Problem in Optics

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The production of electron–positron pairs in time-dependent electric fields (Schwinger mechanism) depends non-linearly on the applied field profile. Accordingly, the resulting momentum spectrum is extremely sensitive to small variations of the field parameters. Owing to this non-linear dependence it is so far unpredictable how to choose a field configuration such that a predetermined momentum distribution is generated. We show that quantum kinetic theory along with optimal control theory can be used to approximately solve this inverse problem for Schwinger pair production. We exemplify this by studying the superposition of a small number of harmonic components resulting in predetermined signatures in the asymptotic momentum spectrum. In the long run, our results could facilitate the observation of this yet unobserved pair production mechanism in quantum electrodynamics by providing suggestions for tailored field configurations.

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SETTING: Correctional settings and remand prisons. OBJECTIVE: To critically discuss calculations for epidemiological indicators of the tuberculosis (TB) burden in prisons and to provide recommendations to improve study comparability. METHODS: A hypothetical data set illustrates issues in determining incidence and prevalence. The appropriate calculation of the incidence rate is presented and problems arising from cross-sectional surveys are clarifi ed. RESULTS: Cases recognized during the fi rst 3 months should be classifi ed as prevalent at entry and excluded from any incidence rate calculation. The numerator for the incidence rate includes persons detected as having developed TB during a specifi ed period of time subsequent to the initial 3 months. The denominator is persontime at risk from 3 months onward to the end point (TB or end of the observation period). Preferably, entry time, exit time and event time are known for each inmate to determine person-time at risk. Failing that, an approximation consists of the sum of monthly head counts, excluding prevalent cases and those persons no longer at risk from both the numerator and the denominator. CONCLUSIONS: The varying durations of inmate incarceration in prisons pose challenges for quantifying the magnitude of the TB problem in the inmate population. Recommendations are made to measure incidence and prevalence.

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We study existence of random elements with partially specified distributions. The technique relies on the existence of a positive ex-tension for linear functionals accompanied by additional conditions that ensure the regularity of the extension needed for interpreting it as a probability measure. It is shown in which case the extens ion can be chosen to possess some invariance properties. The results are applied to the existence of point processes with given correlation measure and random closed sets with given two-point covering function or contact distribution function. It is shown that the regularity condition can be efficiently checked in many cases in order to ensure that the obtained point processes are indeed locally finite and random sets have closed realisations.

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In training networks, particularly small and medium-sized enterprises pool their resources to train apprentices within the framework of the dual VET system, while an intermediary organisation is tasked with managing operations. Over the course of their apprenticeship, the apprentices switch from one training company to another on a (half-) yearly basis. Drawing on a case study of four training networks in Switzerland and the theoretical framework of the sociology of conventions, this paper aims to understand the reasons for the slow dissemination and reluctant adoption of this promising form of organising VET in Switzerland. The results of the study show that the system of moving from one company to another creates a variety of free-rider constellations in the distribution of the collectively generated corporative benefits. This explains why companies are reluctant to participate in this model. For the network to be sustainable, the intermediary organisation has to address discontent arising from free-rider problems while taking into account that the solutions found are always tentative and will often result in new free-rider problems.

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Low back pain (LBP) is the most prevalent health problem in Switzerland and a leading cause of reduced work performance and disability. This study estimated the total cost of LBP in Switzerland in 2005 from a societal perspective using a bottom-up prevalence-based cost-of-illness approach. The study considers more cost categories than are typically investigated and includes the costs associated with a multitude of LBP sufferers who are not under medical care. The findings are based on a questionnaire completed by a sample of 2,507 German-speaking respondents, of whom 1,253 suffered from LBP in the last 4 weeks; 346 of them were receiving medical treatment for their LBP. Direct costs of LBP were estimated at 2.6 billion and direct medical costs at 6.1% of the total healthcare expenditure in Switzerland. Productivity losses were estimated at 4.1 billion with the human capital approach and 2.2 billion with the friction cost approach. Presenteeism was the single most prominent cost category. The total economic burden of LBP to Swiss society was between 1.6 and 2.3% of GDP.

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Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

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Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

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We present a model for plasticity induction in reinforcement learning which is based on a cascade of synaptic memory traces. In the cascade of these so called eligibility traces presynaptic input is first corre lated with postsynaptic events, next with the behavioral decisions and finally with the external reinforcement. A population of leaky integrate and fire neurons endowed with this plasticity scheme is studied by simulation on different tasks. For operant co nditioning with delayed reinforcement, learning succeeds even when the delay is so large that the delivered reward reflects the appropriateness, not of the immediately preceeding response, but of a decision made earlier on in the stimulus - decision sequence . So the proposed model does not rely on the temporal contiguity between decision and pertinent reward and thus provides a viable means of addressing the temporal credit assignment problem. In the same task, learning speeds up with increasing population si ze, showing that the plasticity cascade simultaneously addresses the spatial problem of assigning credit to the different population neurons. Simulations on other task such as sequential decision making serve to highlight the robustness of the proposed sch eme and, further, contrast its performance to that of temporal difference based approaches to reinforcement learning.

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The skin irritant polyyne falcarinol (panaxynol, carotatoxin) is found in carrots, parsley, celery, and in the medicinal plant Panax ginseng. In our ongoing search for new cannabinoid (CB) receptor ligands we have isolated falcarinol from the endemic Sardinian plant Seseli praecox. We show that falcarinol exhibits binding affinity to both human CB receptors but selectively alkylates the anandamide binding site in the CB(1) receptor (K(i)=594nM), acting as covalent inverse agonist in CB(1) receptor-transfected CHO cells. Given the inherent instability of purified falcarinol we repeatedly isolated this compound for biological characterization and one new polyyne was characterized. In human HaCaT keratinocytes falcarinol increased the expression of the pro-allergic chemokines IL-8 and CCL2/MCP-1 in a CB(1) receptor-dependent manner. Moreover, falcarinol inhibited the effects of anandamide on TNF-alpha stimulated keratinocytes. In vivo, falcarinol strongly aggravated histamine-induced oedema reactions in skin prick tests. Both effects were also obtained with the CB(1) receptor inverse agonist rimonabant, thus indicating the potential role of the CB(1) receptor in skin immunopharmacology. Our data suggest anti-allergic effects of anandamide and that falcarinol-associated dermatitis is due to antagonism of the CB(1) receptor in keratinocytes, leading to increased chemokine expression and aggravation of histamine action.

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The A(H1N1)pdm09 influenza virus is a highly contagious pathogen which caused the 2009 influenza pandemic. The virus is known to affect mainly younger people and may be a problem in crowded living conditions. The aim of the study was to describe a major A(H1N1)pdm09 outbreak in a Swiss military boot camp and to develop suggestions for similar future situations.

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