An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.

Effects of Interviewer Experience on Components of Nonresponse in the European Social Survey

We analyze interviewer related nonresponse differences in face-to-face surveys distinguishing three types of interviewers: those who have previous experience with the same high standard cross-sectional survey ("experienced"), those who were chosen by the survey agency to complete refusal conversions ("seniors"), and usual interviewers. The nonresponse components are obtaining household contact, target person contact, and target person cooperation. In addition we examine if interviewer homogeneity with respect to these components is different across the three interviewer groups. Data come from the European Social Survey (ESS) contact forms from four countries which participated during the three rounds 2002/04/06 and used the same survey agency that in turn used to some extent the same interviewers. To analyze interviewer effects, we use discrete two-level models. We find some evidence of better performance by both senior and experienced interviewers and indications of greater homogeneity for nonresponse components, especially for those that contain room for improvement. Surprisingly, the senior interviewers do not outperform those experienced. We conclude that survey agencies should make more efforts to decrease the comparatively high interviewer turnover.

La planification de sortie des personnes âgées hospitalisées dans un service de médecine

Contexte: la planification infirmière de sortie des personnes âgées est une composante importante des soins pour assurer une transition optimale entre l'hôpital et la maison. Beaucoup d'événements indésirables peuvent survenir après la sortie de l'hôpital. Dans une perspective de système de santé, les facteurs qui augmentent ce risque incluent un nombre croissant de patients âgés, l'augmentation de la complexité des soins nécessitant une meilleure coordination des soins après la sortie, ainsi qu'une augmentation de la pression financière. Objectif: évaluer si les interventions infirmières liées à la planification de sortie chez les personnes âgées et leurs proches aidants sont prédictives de leur perception d'être prêts pour le départ, du niveau d'anxiété du patient le jour de la sortie de l'hôpital et du nombre de recours non programmé aux services de santé durant les trente jours après la sortie. Méthode: le devis est prédictif corrélationnel avec un échantillon de convenance de 235 patients. Les patients âgés de 65 ans de quatre unités d'hôpitaux dans le canton de Vaud en Suisse ont été recrutés entre novembre 2011 et octobre 2012. Les types et les niveaux d'interventions infirmières ont été extraits des dossiers de soins et analysés selon les composantes du modèle de Naylor. La perception d'être prêt pour la sortie et l'anxiété ont été mesurées un jour avant la sortie en utilisant l'échelle de perception d'être prêt pour la sortie et l'échelle Hospital Anxiety and Depression. Un mois après la sortie, un entretien téléphonique a été mené pour évaluer le recours non programmé aux services de santé durant cette période. Des analyses descriptives et un modèle randomisé à deux niveaux ont été utilisés pour analyser les données. Résultats: peu de patients ont reçu une planification globale de sortie. L'intervention la plus fréquente était la coordination (M = 55,0/100). et la moins fréquente était la participation du patient à la planification de sortie (M = 16,1/100). Contrairement aux hypothèses formulées, les patients ayant bénéficié d'un plus grand nombre d'interventions infirmières de préparation à la sortie ont un niveau moins élevé de perception d'être prêt pour le départ (B = -0,3, p < 0,05, IC 95% [-0,57, -0,11]); le niveau d'anxiété n'est pas associé à la planification de sortie (r = -0,21, p <0,01) et la présence de troubles cognitifs est le seul facteur prédictif d'une réhospitalisation dans les 30 jours après la sortie de l'hôpital ( OR = 1,50, p = 0,04, IC 95% [1,02, 2,22]). Discussion: en se focalisant sur chaque intervention de la planification de sortie, cette étude permet une meilleure compréhension du processus de soins infirmiers actuellement en cours dans les hôpitaux vaudois. Elle met en lumière les lacunes entre les pratiques actuelles et celles de pratiques exemplaires donnant ainsi une orientation pour des changements dans la pratique clinique et des recherches ultérieures. - Background: Nursing discharge planning in elderly patients is an important component of care to ensure optimal transition from hospital to home. Many adverse events may occur after hospital discharge. From a health care system perspective, contributing factors that increase the risk of these adverse events include a growing number of elderly patients, increased complexity of care requiring better care coordination after discharge, as well as increased financial pressure. Aim: To investigate whether older medical inpatients who receive comprehensive discharge planning interventions a) feel more ready for hospital discharge, b) have reduced anxiety at the time of discharge, c) have lower health care utilization after discharge compared to those who receive less comprehensive interventions. Methods: Using a predictive correlational design, a convenience sample of 235 patients was recruited. Patients aged 65 and older from 4 units of hospitals in the canton of Vaud in Switzerland were enrolled between November 2011 and October 2012. Types and level of interventions were extracted from the medical charts and analyzed according to the components of Naylor's model. Discharge readiness and anxiety were measured one day before discharge using the Readiness for Hospital Discharge Scale and the Hospital Anxiety and Depression scale. A telephone interview was conducted one month after hospital discharge to asses unplanned health services utilization during this follow-up period. Descriptive analyses and a two- level random model were used for statistical analyses. Results: Few patients received comprehensive discharge planning interventions. The most frequent intervention was Coordination (M = 55,0/100) and the least common was Patient participation in the discharge planning (M = 16,1/100). Contrary to our hypotheses, patients who received more nursing discharge interventions were significantly less ready to go home (B = -0,3, p < 0,05, IC 95% [-0,57, -0,11]); their anxiety level was not associated with their readiness for hospital discharge (r = -0,21, p <0,01) and cognitive impairment was the only factor that predicted rehospitalization within 30 days after discharge ( OR = 1,50, p = 0,04, IC 95% [1,02, 2,22]). Discussion: By focusing on each component of the discharge planning, this study provides a greater and more detailed insight on the usual nursing process currently performed in medical inpatients units. Results identified several gaps between current and Best practices, providing guidance to changes in clinical practice and further research.

The persistence of abnormal returns at industry and firm levels

The present paper proposes a model for the persistence of abnormal returnsboth at firm and industry levels, when longitudinal data for the profitsof firms classiffied as industries are available. The model produces a two-way variance decomposition of abnormal returns: (a) at firm versus industrylevels, and (b) for permanent versus transitory components. This variancedecomposition supplies information on the relative importance of thefundamental components of abnormal returns that have been discussed in theliterature. The model is applied to a Spanish sample of firms, obtainingresults such as: (a) there are significant and permanent differences betweenprofit rates both at industry and firm levels; (b) variation of abnormal returnsat firm level is greater than at industry level; and (c) firm and industry levelsdo not differ significantly regarding rates of convergence of abnormal returns.

Koulusaavutusaineiston analyysi asetelmaperusteisilla ja kaksitasoisilla logit-regressiomalleilla

Summary: The analysis of educational data with design-based and two-level logistic regression models

Minimal optimal generalized quantum measurements

Optimal and finite positive operator valued measurements on a finite number N of identically prepared systems have recently been presented. With physical realization in mind, we propose here optimal and minimal generalized quantum measurements for two-level systems. We explicitly construct them up to N = 7 and verify that they are minimal up to N = 5.

Organisational adaptation of multi-agent systems in a peer-to-peer scenario

Organisations in Multi-Agent Systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents' behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system's purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents'relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system's adaptation is lower than its benefits.

A multilevel multiscale finite volume method

The Multiscale Finite Volume (MsFV) method has been developed to efficiently solve reservoir-scale problems while conserving fine-scale details. The method employs two grid levels: a fine grid and a coarse grid. The latter is used to calculate a coarse solution to the original problem, which is interpolated to the fine mesh. The coarse system is constructed from the fine-scale problem using restriction and prolongation operators that are obtained by introducing appropriate localization assumptions. Through a successive reconstruction step, the MsFV method is able to provide an approximate, but fully conservative fine-scale velocity field. For very large problems (e.g. one billion cell model), a two-level algorithm can remain computational expensive. Depending on the upscaling factor, the computational expense comes either from the costs associated with the solution of the coarse problem or from the construction of the local interpolators (basis functions). To ensure numerical efficiency in the former case, the MsFV concept can be reapplied to the coarse problem, leading to a new, coarser level of discretization. One challenge in the use of a multilevel MsFV technique is to find an efficient reconstruction step to obtain a conservative fine-scale velocity field. In this work, we introduce a three-level Multiscale Finite Volume method (MlMsFV) and give a detailed description of the reconstruction step. Complexity analyses of the original MsFV method and the new MlMsFV method are discussed, and their performances in terms of accuracy and efficiency are compared.

An operator formulation of the multiscale finite-volume method with correction function

The multiscale finite-volume (MSFV) method has been derived to efficiently solve large problems with spatially varying coefficients. The fine-scale problem is subdivided into local problems that can be solved separately and are coupled by a global problem. This algorithm, in consequence, shares some characteristics with two-level domain decomposition (DD) methods. However, the MSFV algorithm is different in that it incorporates a flux reconstruction step, which delivers a fine-scale mass conservative flux field without the need for iterating. This is achieved by the use of two overlapping coarse grids. The recently introduced correction function allows for a consistent handling of source terms, which makes the MSFV method a flexible algorithm that is applicable to a wide spectrum of problems. It is demonstrated that the MSFV operator, used to compute an approximate pressure solution, can be equivalently constructed by writing the Schur complement with a tangential approximation of a single-cell overlapping grid and incorporation of appropriate coarse-scale mass-balance equations.

Towards Machine Consciousness: Grounding Abstract Models as pi-Processes

We present a two-level model of concurrent communicating systems (CCS) to serve as a basis formachine consciousness. A language implementing threads within logic programming is ¯rstintroduced. This high-level framework allows for the de¯nition of abstract processes that can beexecuted on a virtual machine. We then look for a possible grounding of these processes into thebrain. Towards this end, we map abstract de¯nitions (including logical expressions representingcompiled knowledge) into a variant of the pi-calculus. We illustrate this approach through aseries of examples extending from a purely reactive behavior to patterns of consciousness.

Taajuusmuuttajan häviöidensimulointityökalun kehitys

Diplomityössä on kehitetty kaksitasoisen jännitevälipiirillisen taajuusmuuttajan häviöiden simulointiin käytettävä simulointimalli osaksi säädettävän sähkömoottorikäytön simulointityökalua, jolla voidaan analysoida eri säätöalgoritmien, kuormituksen ja kytkentätaajuuden vaikutusta taajuusmuuttajan häviöihin. Aluksi on selvitetty yksityiskohtaisesti taajuusmuuttajan häviölähteet ja häviöiden fysikaalinen tausta. Taajuusmuuttajassa käytettäville komponenteille on esitetty simulointimalleja. Taajuusmuuttajan malli ja häviöiden laskenta-algoritmit on toteutettu C-kielellä. Taajuusmuuttajan malli vastaa perusrakenteeltaan ACS800-02-0260-5 - taajuusmuuttajaa. ACS800-02-0260-5 -taajuusmuuttajan häviöitä on simuloitu erilaisissa kuormitustilanteissa, ja simulointien tueksi taajuusmuuttajan häviöt on pyritty selvittämään laboratoriomittauksin.

1000 V sähkönjakelujärjestelmän teknistaloudellisen kannattavuuden tarkastelu

Tässä työssä tutkitaan 1000 V pienjännitejakelun taloudellista kannattavuutta. Tutkimus perustuu teoreettiseen tarkasteluun, jossa noudatetaan yleisiä verkostosuunnittelun periaatteita. EU-lainsäädäntö mahdollistaa 1000 V pienjänniteportaan sijoittamisen nykyisen keskijänniteverkon ja pienjänniteverkon väliin lisäten kolmannen jakelujänniteportaan nykyään käytettävien 20 kV ja 0,4 kV väliin. Jakeluverkkojen kehittämiseksi on etsittävä ratkaisu, joka on taloudellinen sekä asiakkaiden että verkonhaltijoiden kannalta. Tällaiset ratkaisut pienentävät verkon käytön kokonaiskustannuksia ja parantavat sähkön laatua. Lisättäessä jakeluverkkoon kolmas jänniteporras, keskijänniteverkon johtopituus lyhenee ja varsinkin lyhyiden haarajohtojen määrä vähenee. Tämä vähentää keskijänniteverkossa esiintyvien keskeytysten määrää ja pienentää keskeytyskustannuksia. Kilovoltin järjestelmä on kannattava korvattaessa sillä osa keskijänniteverkkoa, tai estettäessä perinteisellä järjestelmällä tarvittava muuntopiirin jakaminen. Osana varsinaista pienjänniteverkkoa ei kilovoltinjärjestelmä ole kannattava. Tässä työssä kolmijänniteportaista jakeluverkkoa tutkitaan teoreettisilla verkkosuunnitelmilla, joita tehdään muutamille perusverkkotopologioille. Taloudellista kannattavuutta tutkitaan vertaamalla perinteistä kaksijänniteportaista ja kolmijänniteportaista verkkoratkaisua kustannusten suhteen teknisten reunaehtojen puitteissa. 1000 V pienjännitejakelu vaatii uudenlaisia verkostokomponentteja. Näistä on erityisesti käsitelty 1/0,4 kV pienjännitemuuntajaa. Muuntajasuunnittelun lähtökohtana on 1000 V verkon käyttäminen keskijänniteverkon jatkeena maasta erotettuna verkkona.

The effect of learning on the evolution of new courtship behavior: a simulation model

The fact that individuals learn can change the relationship between genotype and phenotype in the population, and thus affect the evolutionary response to selection. Here we ask how male ability to learn from female response affects the evolution of a novel male behavioral courtship trait under pre-existing female preference (sensory drive). We assume a courtship trait which has both a genetic and a learned component, and a two-level female response to males. With individual-based simulations we show that, under this scenario, learning generally increases the strength of selection on the genetic component of the courtship trait, at least when the population genetic mean is still low. As a consequence, learning not only accelerates the evolution of the courtship trait, but also enables it when the trait is costly, which in the absence of learning results in an adaptive valley. Furthermore, learning can enable the evolution of the novel trait in the face of gene flow mediated by immigration of males that show superior attractiveness to females based on another, non-heritable trait. However, rather than increasing monotonically with the speed of learning, the effect of learning on evolution is maximized at intermediate learning rates. This model shows that, at least under some scenarios, the ability to learn can drive the evolution of mating behaviors through a process equivalent to Waddington's genetic assimilation.

Condutância molecular e biomolecular

The concept of molecular conductance is discussed in terms of the propagation of an electronic interaction, between electron donor and acceptor groups, through the bonds of a molecular structure where these groups are embedded. The electronic interaction propagation is described by a Green's function matrix element, in a donor-bridge-acceptor molecular system reduced to a two-level representation.

Analyzing Carbon Trade Permits in Optimization Framework

The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.