910 resultados para Cannabis dependence


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We present STAR measurements of azimuthal anisotropy by means of the two- and four-particle cumulants nu(2) (nu(2){2} and nu(2){4}) for Au + Au and Cu + Cu collisions at center-of-mass energies root S-NN = 62.4 and 200 GeV. The difference between nu(2){2}(2) and nu(2){4}(2) is related to nu(2) fluctuations (sigma(nu 2)) and nonflow (delta(2)). We present an upper limit to sigma(nu 2)/nu 2. Following the assumption that eccentricity fluctuations sigma(epsilon) dominate nu(2) fluctuations nu(2)/sigma nu(2) approximate to epsilon/sigma epsilon we deduce the nonflow implied for several models of eccentricity fluctuations that would be required for consistency with nu(2){2} and nu(2){4}. We also present results on the ratio of nu(2) to eccentricity.

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We prove that any two Poisson dependent elements in a free Poisson algebra and a free Poisson field of characteristic zero are algebraically dependent, thus answering positively a question from Makar-Limanov and Umirbaev (2007) [8]. We apply this result to give a new proof of the tameness of automorphisms for free Poisson algebras of rank two (see Makar-Limanov and Umirbaev (2011) [9], Makar-Limanov et al. (2009) [10]). (C) 2011 Elsevier Inc. All rights reserved.

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Fraud is a global problem that has required more attention due to an accentuated expansion of modern technology and communication. When statistical techniques are used to detect fraud, whether a fraud detection model is accurate enough in order to provide correct classification of the case as a fraudulent or legitimate is a critical factor. In this context, the concept of bootstrap aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the adjusted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper, for the first time, we aim to present a pioneer study of the performance of the discrete and continuous k-dependence probabilistic networks within the context of bagging predictors classification. Via a large simulation study and various real datasets, we discovered that the probabilistic networks are a strong modeling option with high predictive capacity and with a high increment using the bagging procedure when compared to traditional techniques. (C) 2012 Elsevier Ltd. All rights reserved.

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Abstract Background Cannabis intoxication is related to a number of physical and mental health risks with ensuing social costs. However, little attention has been given to the investigation of possible pharmacological interactions in this condition. Objective To review the available scientific literature concerning pharmacological interventions for the treatment of the acute effects of cannabis. Methods A search was performed on the Pubmed, Lilacs, and Scielo online databases by combining the terms cannabis, intoxication, psychosis, anxiety, and treatment. The articles selected from this search had their reference lists checked for additional publications related to the topic of the review. Results The reviewed articles consisted of case reports and controlled clinical trials and are presented according to interventions targeting the physiological, psychiatric, and cognitive symptoms provoked by cannabis. The pharmacological interventions reported in these studies include: beta-blockers, antiarrhythmic agents, antagonists of CB-1 and GABA-benzodiazepine receptors, antipsychotics, and cannabidiol. Conclusion Although scarce, the evidence on pharmacological interventions for the management of cannabis intoxication suggests that propanolol and rimonabant are the most effective compounds currently available to treat the physiological and subjective effects of the drug. Further studies are necessary to establish the real effectiveness of these two medications, as well as the effectiveness of other candidate compounds to counteract the effects of cannabis intoxication, such as cannabidiol and flumazenil.

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Abstract Background Tobacco and cannabis use are strongly interrelated, but current national and international cessation programs typically focus on one substance, and address the other substance either only marginally or not at all. This study aimed to identify the demand for, and describe the development and content of, the first integrative group cessation program for co-smokers of cigarettes and cannabis. Methods First, a preliminary study using expert interviews, user focus groups with (ex-)smokers, and an online survey was conducted to investigate the demand for, and potential content of, an integrative smoking cessation program (ISCP) for tobacco and cannabis co-smokers. This study revealed that both experts and co-smokers considered an ISCP to be useful but expected only modest levels of readiness for participation.Based on the findings of the preliminary study, an interdisciplinary expert team developed a course concept and a recruitment strategy. The developed group cessation program is based on current treatment techniques (such as motivational interviewing, cognitive behavioural therapy, and self-control training) and structured into six course sessions.The program was evaluated regarding its acceptability among participants and course instructors. Results Both the participants and course instructors evaluated the course positively. Participants and instructors especially appreciated the group discussions and the modules that were aimed at developing personal strategies that could be applied during simultaneous cessation of tobacco and cannabis, such as dealing with craving, withdrawal, and high-risk situations. Conclusions There is a clear demand for a double cessation program for co-users of cigarettes and cannabis, and the first group cessation program tailored for these users has been developed and evaluated for acceptability. In the near future, the feasibility of the program will be evaluated. Trial registration Current Controlled Trials ISRCTN15248397

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The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

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CONTEXT AND OBJECTIVES: Themes like alcohol and drug abuse, relationship difficulties, psychoses, autism and personality dissociation disorders have been widely used in films. Psychiatry and psychiatric conditions in various cultural settings are increasingly taught using films. Many articles on cinema and psychiatry have been published but none have presented any methodology on how to select material. Here, the authors look at the portrayal of abusive use of alcohol and drugs during the Brazilian cinema revival period (1994 to 2008). DESIGN AND SETTING: Qualitative study at two universities in the state of São Paulo. METHODS: Scenes were selected from films available at rental stores and were analyzed using a specifically designed protocol. We assessed how realistic these scenes were and their applicability for teaching. One author selected 70 scenes from 50 films (graded for realism and teaching applicability > 8). These were then rated by another two judges. Rating differences among the three judges were assessed using nonparametric tests (P < 0.001). Scenes with high scores (> 8) were defined as "quality scenes". RESULTS: Thirty-nine scenes from 27 films were identified as "quality scenes". Alcohol, cannabis, cocaine, hallucinogens and inhalants were included in these. Signs and symptoms of intoxication, abusive/harmful use and dependence were shown. CONCLUSIONS: We have produced rich teaching material for discussing psychopathology relating to alcohol and drug use that can be used both at undergraduate and at postgraduate level. Moreover, it could be seen that certain drug use behavioral patterns are deeply rooted in some Brazilian films and groups.

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Temperature dependent transient curves of excited levels of a model Eu3+ complex have been measured for the first time. A coincidence between the temperature dependent rise time of the 5D0 emitting level and decay time of the 5D1 excited level in the [Eu(tta)3(H2O)2] complex has been found, which unambiguously proves the T1→5D1→5D0 sensitization pathway. A theoretical approach for the temperature dependent energy transfer rates has been successfully applied to the rationalization of the experimental data.

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The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

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This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

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The fundamental goal of this thesis is the determination of the isospin dependence of the Ar+Ni fusion-evaporation cross section. Three Ar isotope beams, with energies of about 13AMeV, have been accelerated and impinged onto isotopically enriched Ni targets, in order to produce Pd nuclei, with mass number varying from 92 to 104. The measurements have been performed by the high performance 4pi detector INDRA, coupled with the magnetic spectrometer VAMOS. Even if the results are very preliminary, the obtained fusion-evaporation cross sections behaviour gives a hint at the possible isospin dependence of the fusion-evaporation cross sections.

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Sudden cardiac death due to ventricular arrhythmia is one of the leading causes of mortality in the world. In the last decades, it has proven that anti-arrhythmic drugs, which prolong the refractory period by means of prolongation of the cardiac action potential duration (APD), play a good role in preventing of relevant human arrhythmias. However, it has long been observed that the “class III antiarrhythmic effect” diminish at faster heart rates and that this phenomenon represent a big weakness, since it is the precise situation when arrhythmias are most prone to occur. It is well known that mathematical modeling is a useful tool for investigating cardiac cell behavior. In the last 60 years, a multitude of cardiac models has been created; from the pioneering work of Hodgkin and Huxley (1952), who first described the ionic currents of the squid giant axon quantitatively, mathematical modeling has made great strides. The O’Hara model, that I employed in this research work, is one of the modern computational models of ventricular myocyte, a new generation began in 1991 with ventricular cell model by Noble et al. Successful of these models is that you can generate novel predictions, suggest experiments and provide a quantitative understanding of underlying mechanism. Obviously, the drawback is that they remain simple models, they don’t represent the real system. The overall goal of this research is to give an additional tool, through mathematical modeling, to understand the behavior of the main ionic currents involved during the action potential (AP), especially underlining the differences between slower and faster heart rates. In particular to evaluate the rate-dependence role on the action potential duration, to implement a new method for interpreting ionic currents behavior after a perturbation effect and to verify the validity of the work proposed by Antonio Zaza using an injected current as a perturbing effect.

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In 1998 a pilot experiment was carried out to study the helicity dependence of photoreaction cross sections using circularly polarized real photons on longitudinally polarized deuterons in a deuterated butanol target. The knowledge of these cross sections is required to test the validity of the Gerasimov-Drell-Hearn sum rule on the deuteron and the neutron. The focus of this thesis is on the results for the differential and total cross sections for the photodisintegration reaction for various photon energies in the range from 200 to 450 MeV using data taken with the detector system DAPHNE. The current understanding of the NN interaction as represented by the calculations by M. Schwamb could be confirmed within the given uncertainties. In addition, the detector DAPHNE has been prepared for the main experiment in 2003. The according work is presented together with results of the quality-test measurements of the renewed detector components.

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Der erste experimentelle Test der GDH-Summenregel für das Proton wurde 1998 am MAMI-Beschleuniger der Universität Mainz durchgeführt. Ferner wurde ein Pilot-Experiment mit einem polarisierten Deuteron-Target vorgenommen. Dieselbe Kollaboration führte 2003 ein auf das Deuteron ausgerichtetes Experiment durch mit der Absicht, die GDH-Summenregel für das Neutron zu untersuchen. Der in beiden Experimenten verwendete Aufbau erlaubt nicht nur die Messung des totalen Wirkungsquerschnitts, sondern auch gleichzeitig einzelne Teilreaktionen zu studieren. In dieser Arbeit werden die Daten des Deuteron-Pilot-Experiments von 1998 analysiert. Desweiteren wird eine Studie der Helizitätsabhängigkeit der differenziellen Wirkungsquerschnitte für drei Pion-Photoproduktionskanäle des Deuterons in der oberen Hälfte der Delta-Resonanz präsentiert. Diese Ergebnisse werden mit einem theoretischen Modell verglichen. Dabei wurde eine hinreichend gute Übereinstimmung für die unpolarisierten Reaktionen gefunden, während für die polarisierten Kanäle kleinere Diskrepanzen beobachtet wurden. Der Targetpolarisationsgrad ist einer der relevanten Parameter, der für eine absolute Normalisierung der Wirkungsquerschnitte notwendig ist. Die Analyse dieses Parameters für die 2003er Daten wird in der vorliegenden Arbeit vorgestellt. Zur Zeit ist in Mainz ein Frozen-Spin-Target im Bau. Es wird als Target für polarisierte Protonen oder polarisierte Deuteronen für zukünftige Experimente mit dem Crystal Ball zur Verfügung stehen. Die Vorbereitungen der verschiedenen Subsysteme dieses Aufbaus stellten einen wichtigen Teil dieser Arbeit dar. Die fundamentalen Grundlagen der Methode und deren technische Umsetzung, sowie der momentane Status der Aufbauarbeiten am Target werden im Detail präsentiert.