ARAquá: software para avaliação de risco ambiental de agrotóxico.

O software ARAquá foi desenvolvido para auxiliar as avaliações de riscos ambientais de agrotóxicos, considerando as possíveis contaminações de corpos d?água superficiais e subterrâneos, através da comparação de suas concentrações estimadas em cenários de uso agrícola com parâmetros de qualidade de água. O programa foi desenvolvido com o Ambiente de Desenvolvimento Integrado DELPHI 7, sendo PASCAL a linguagem de programação. O software utiliza dados referentes ao local, solo e agrotóxico para a realização de seus cálculos. Para executar o aplicativo é necessário um sistema operacional da plataforma Windows e um computador com uma configuração básica de hardware. Nesse trabalho a operacionalidade do ARAquá é exemplificada com dados de entrada pré-cadastrados, que seguem com o software.bitstream/item/35294/1/boletim6ATUAL.pd

Observation of the Baryonic Flavor-Changing Neutral Current Decay Lambda_b -> Lambda mu+ mu-

We report the first observation of the baryonic flavor-changing neutral current decay Lambda_b -> Lambda mu+ mu- with 24 signal events and a statistical significance of 5.8 Gaussian standard deviations. This measurement uses ppbar collisions data sample corresponding to 6.8fb-1 at sqrt{s}=1.96TeV collected by the CDF II detector at the Tevatron collider. The total and differential branching ratios for Lambda_b -> Lambda mu+ mu- are measured. We find B(Lambda_b -> Lambda mu+ mu-) = [1.73+-0.42(stat)+-0.55(syst)] x 10^{-6}. We also report the first measurement of the differential branching ratio of B_s -> phi mu+ mu- using 49 signal events. In addition, we report branching ratios for B+ -> K+ mu+ mu-, B0 -> K0 mu+ mu-, and B -> K*(892) mu+ mu- decays.Comment: 8 pages, 2 figures, 4 tables. Submitted to Phys. Rev. Let

Measurements of branching fraction ratios and CP-asymmetries in suppressed B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^- decays

We report the first reconstruction in hadron collisions of the suppressed decays B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^-, sensitive to the CKM phase gamma, using data from 7 fb^-1 of integrated luminosity collected by the CDF II detector at the Tevatron collider. We reconstruct a signal for the B^- -> D(-> K^+ pi^-)K^- suppressed mode with a significance of 3.2 standard deviations, and measure the ratios of the suppressed to favored branching fractions R(K) = [22.0 \pm 8.6(stat)\pm 2.6(syst)]\times 10^-3, R^+(K) = [42.6\pm 13.7(stat)\pm 2.8(syst)]\times 10^-3, R^-(K)= [3.8\pm 10.3(stat)\pm 2.7(syst]\times 10^-3, as well as the direct CP-violating asymmetry A(K) = -0.82\pm 0.44(stat)\pm 0.09(syst) of this mode. Corresponding quantities for B^- -> D(-> K^+ pi^-)pi^- decay are also reported.Comment: 8 pages, 1 figure, accepted by Phys.Rev.D Rapid Communications for Publicatio

Gestione sostenibile delle foreste Mediterranee e uso energetico delle biomasse forestali residuali

he book describes the reasons that led the Regional Department of Rural and Territorial Development to take part in the PROFORBIOMED Project. They can be summarized by the need to dispose of a tool for the sustainable management of all the state-owned forests of the Region. As a matter of fact, the Project aims at developing a model of sustainable forest management, through the recovery and reuse of wood scraps from ordinary silvicultural operations, to be used for the production of power and heat inside of a process adopting natural renewable energy sources. The main actions taken and the methodologies adopted are described, as well as the principles and instruments required for the setting up and execution of the work. Some of the most relevant are: the drafting of “Forest Management Plans”, the “Short Supply Chain” and the “Biomass Traceability Protocol”, together with the application of “Best Practices” of Management and the “Monitoring of impacts” caused by the woody biomass extraction procedures. The “forest – wood – energy” chain developed and proposed is exclusively related to the territory pertaining to one municipality, and with CHP plants fed with biomass exclusively produced within the territory of each municipality, in strict compliance with the “sustainable forest management” principles, as well as with the fundamental principle of “short supply chain”. For these reasons the CHP plans proposed shall be sized according to the biomass available in each municipality, with the possibility of integrating residual forest biomass with other waste wood resources potentially available in the territory and coming from prunings in agricultural activities. Therefore, the replicable model prepared and proposed by PROFORBIOMED aims at appraising from the economic point of view a waste product, such is currently considered the residual forest biomass from the forests of Sicily, and at the same time significantly improving the natural environment, thanks to the reduction in oil consumption

INvolvement of breast CAncer patients during oncological consultations: a multicentre randomised controlled trial--the INCA study protocol.

INTRODUCTION: Studies on patient involvement show that physicians make few attempts to involve their patients who ask few questions if not facilitated. On the other hand, the patients who participate in the decision-making process show greater treatment adherence and have better health outcomes. Different methods to encourage the active participation during oncological consultation have been described; however, similar studies in Italy are lacking. The aims of the present study are to (1) assess the effects of a preconsultation intervention to increase the involvement of breast cancer patients during the consultation, and (2) explore the role of the attending companions in the information exchange during consultation. METHODS AND ANALYSIS: All female patients with breast cancer who attend the Oncology Out-patient Services for the first time will provide an informed consent to participate in the study. They are randomly assigned to the intervention or to the control group. The intervention consists of the presentation of a list of relevant illness-related questions, called a question prompt sheet. The primary outcome measure of the efficacy of the intervention is the number of questions asked by patients during the consultation. Secondary outcomes are the involvement of the patient by the oncologist; the patient's perceived achievement of her information needs; the patient's satisfaction and ability to cope; the quality of the doctor-patient relationship in terms of patient-centeredness; and the number of questions asked by the patient's companions and their involvement during the consultation. All outcome measures are supposed to significantly increase in the intervention group. ETHICS AND DISSEMINATION: The study was approved by the local Ethics Committee of the Hospital Trust of Verona. Study findings will be disseminated through peer-reviewed publications and conference presentations. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01510964

Sleep-wake sensitive mechanisms of adenosine release in the basal forebrain of rodents : an in vitro study

Adenosine acting in the basal forebrain is a key mediator of sleep homeostasis. Extracellular adenosine concentrations increase during wakefulness, especially during prolonged wakefulness and lead to increased sleep pressure and subsequent rebound sleep. The release of endogenous adenosine during the sleep-wake cycle has mainly been studied in vivo with microdialysis techniques. The biochemical changes that accompany sleep-wake status may be preserved in vitro. We have therefore used adenosine-sensitive biosensors in slices of the basal forebrain (BFB) to study both depolarization-evoked adenosine release and the steady state adenosine tone in rats, mice and hamsters. Adenosine release was evoked by high K+, AMPA, NMDA and mGlu receptor agonists, but not by other transmitters associated with wakefulness such as orexin, histamine or neurotensin. Evoked and basal adenosine release in the BFB in vitro exhibited three key features: the magnitude of each varied systematically with the diurnal time at which the animal was sacrificed; sleep deprivation prior to sacrifice greatly increased both evoked adenosine release and the basal tone; and the enhancement of evoked adenosine release and basal tone resulting from sleep deprivation was reversed by the inducible nitric oxide synthase (iNOS) inhibitor, 1400 W. These data indicate that characteristics of adenosine release recorded in the BFB in vitro reflect those that have been linked in vivo to the homeostatic control of sleep. Our results provide methodologically independent support for a key role for induction of iNOS as a trigger for enhanced adenosine release following sleep deprivation and suggest that this induction may constitute a biochemical memory of this state

Basic ideas and tools for projection-based model reduction of parametric partial differential equations

We provide first the functional analysis background required for reduced order modeling and present the underlying concepts of reduced basis model reduction. The projection-based model reduction framework under affinity assumptions, offline-online decomposition and error estimation is introduced. Several tools for geometry parametrizations, such as free form deformation, radial basis function interpolation and inverse distance weighting interpolation are explained. The empirical interpolation method is introduced as a general tool to deal with non-affine parameter dependency and non-linear problems. The discrete and matrix versions of the empirical interpolation are considered as well. Active subspaces properties are discussed to reduce high-dimensional parameter spaces as a pre-processing step. Several examples illustrate the methodologies

Chapter 12: Weighted Reduced Order Methods for Uncertainty Quantification

Partial differential equations (PDEs) represent an effective tool to model phenomena in applied sciences. Realistic problems usually depend on several physical and geometrical parameters that can be calibrated exploiting real data. In real scenarios, however, these parameters are affected by uncertainty due to measurement errors or scattered data information. To deal with more reli- able models which take into account this issue, the numerical approximation of stochastic PDEs can be exploited. In the Uncertainty Quantification (UQ) context, many simulations are run to better understand the system at hand and to compute statistics of outcomes over quantities of interest. In particular, the input parameters of the stochastic PDEs are assumed to be random finite–dimensional variables