Portuguese strengths and fragilities on safety and health practices

Despite improvements over the years, accidents continue to be a scourge in the construction sector, leading to an increase in the number of journal articles addressing the issue, in an attempt to help construction industry to increase safety performance [1]. This paper aims to, helping construction industry and particulary tunneling community, describe the Portuguese approach to most typical health and safety problems in underground excavations performed with the Sequential Excavation Method (SEM). The article will address various topics, from safety management and organizational practices, to collective and personal protection equipment, to emergency planning. nt problems in safety and health matters are similar to several other countries, the paper will expose a compilation of Portuguese best practices used to solve that problems. This enunciation of best practices describes experience from most important and recognized Project Owners and Contractors in Portugal. In a second phase it will be analysed Portuguese weaknesses, identifying preventive measures, and their comparative importance, that should be adopted in Portugal in order to reduce accidents and health diseases.

Dispersion of fillers in viscoelastic polymer matrices using Eulerian-Lagrangian approaches

Understanding the behavior of c omplex composite materials using mixing procedures is fundamental in several industrial processes. For instance, polymer composites are usually manufactured using dispersion of fillers in polymer melt matrices. The success of the filler dispersion depends both on the complex flow patterns generated and on the polymer melt rheological behavior. Consequently, the availability of a numerical tool that allow to model both fluid and particle would be very useful to increase the process insight. Nowadays there ar e computational tools that allow modeling the behavior of filled systems, taking into account both the behavior of the fluid (Computational Rheology) and the particles (Discrete Element Method). One example is the DPMFoam solver of the OpenFOAM ® framework where the averaged volume fraction momentum and mass conservation equations are used to describe the fluid (continuous phase) rheology, and the Newton’s second law of motion is used to compute the particles (discrete phase) movement. In this work the refer red solver is extended to take into account the elasticity of the polymer melts for the continuous phase. The solver capabilities will be illustrated by studying the effect of the fluid rheology on the filler dispersion, taking into account different fluid types (generalized Newtonian or viscoelastic) and particles volume fraction and size. The results obtained are used to evaluate the relevance of considering the fluid complex rheology for the prediction of the composites morphology

Determination of the top-quark pole mass using t(t)over-bar+1-jet events collected with the ATLAS experiment in 7 TeV pp collisions

The normalized differential cross section for top-quark pair production in association with at least one jet is studied as a function of the inverse of the invariant mass of the tt¯+1-jet system. This distribution can be used for a precise determination of the top-quark mass since gluon radiation depends on the mass of the quarks. The experimental analysis is based on proton--proton collision data collected by the ATLAS detector at the LHC with a centre-of-mass energy of 7 TeV corresponding to an integrated luminosity of 4.6 fb−1. The selected events were identified using the lepton+jets top-quark-pair decay channel, where lepton refers to either an electron or a muon. The observed distribution is compared to a theoretical prediction at next-to-leading-order accuracy in quantum chromodynamics using the pole-mass scheme. With this method, the measured value of the top-quark pole mass, mpolet, is: mpolet =173.7 ± 1.5 (stat.) ± 1.4 (syst.) +1.0−0.5 (theory) GeV. This result represents the most precise measurement of the top-quark pole mass to date.

Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

An Equation for the Prediction of Oxygen Consumption in a Brazilian Population

Background: The equations predicting maximal oxygen uptake (VO2max or peak) presently in use in cardiopulmonary exercise testing (CPET) softwares in Brazil have not been adequately validated. These equations are very important for the diagnostic capacity of this method. Objective: Build and validate a Brazilian Equation (BE) for prediction of VO2peak in comparison to the equation cited by Jones (JE) and the Wasserman algorithm (WA). Methods: Treadmill evaluation was performed on 3119 individuals with CPET (breath by breath). The construction group (CG) of the equation consisted of 2495 healthy participants. The other 624 individuals were allocated to the external validation group (EVG). At the BE (derived from a multivariate regression model), age, gender, body mass index (BMI) and physical activity level were considered. The same equation was also tested in the EVG. Dispersion graphs and Bland-Altman analyses were built. Results: In the CG, the mean age was 42.6 years, 51.5% were male, the average BMI was 27.2, and the physical activity distribution level was: 51.3% sedentary, 44.4% active and 4.3% athletes. An optimal correlation between the BE and the CPET measured VO2peak was observed (0.807). On the other hand, difference came up between the average VO2peak expected by the JE and WA and the CPET measured VO2peak, as well as the one gotten from the BE (p = 0.001). Conclusion: BE presents VO2peak values close to those directly measured by CPET, while Jones and Wasserman differ significantly from the real VO2peak.

Bayesian Inference in the Time Varying Cointegration Model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

Multiplex ultra-performance liquid chromatography-tandem mass spectrometry method for simultaneous quantification in human plasma of fluconazole, itraconazole, hydroxyitraconazole, posaconazole, voriconazole, voriconazole-N-oxide, anidulafungin, and caspofungin.

Therapeutic drug monitoring (TDM) may contribute to optimizing the efficacy and safety of antifungal therapy because of the large variability in drug pharmacokinetics. Rapid, sensitive, and selective laboratory methods are needed for efficient TDM. Quantification of several antifungals in a single analytical run may best fulfill these requirements. We therefore developed a multiplex ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method requiring 100 μl of plasma for simultaneous quantification within 7 min of fluconazole, itraconazole, hydroxyitraconazole, posaconazole, voriconazole, voriconazole-N-oxide, caspofungin, and anidulafungin. Protein precipitation with acetonitrile was used in a single extraction procedure for eight analytes. After reverse-phase chromatographic separation, antifungals were quantified by electrospray ionization-triple-quadrupole mass spectrometry by selected reaction monitoring detection using the positive mode. Deuterated isotopic compounds of azole antifungals were used as internal standards. The method was validated based on FDA recommendations, including assessment of extraction yields, matrix effect variability (<9.2%), and analytical recovery (80.1 to 107%). The method is sensitive (lower limits of azole quantification, 0.01 to 0.1 μg/ml; those of echinocandin quantification, 0.06 to 0.1 μg/ml), accurate (intra- and interassay biases of -9.9 to +5% and -4.0 to +8.8%, respectively), and precise (intra- and interassay coefficients of variation of 1.2 to 11.1% and 1.2 to 8.9%, respectively) over clinical concentration ranges (upper limits of quantification, 5 to 50 μg/ml). Thus, we developed a simple, rapid, and robust multiplex UPLC-MS/MS assay for simultaneous quantification of plasma concentrations of six antifungals and two metabolites. This offers, by optimized and cost-effective lab resource utilization, an efficient tool for daily routine TDM aimed at maximizing the real-time efficacy and safety of different recommended single-drug antifungal regimens and combination salvage therapies, as well as a tool for clinical research.

An approximate solution method for boundary layer flow of a power law fluid over a flat plate

The work in this paper deals with the development of momentum and thermal boundary layers when a power law fluid flows over a flat plate. At the plate we impose either constant temperature, constant flux or a Newton cooling condition. The problem is analysed using similarity solutions, integral momentum and energy equations and an approximation technique which is a form of the Heat Balance Integral Method. The fluid properties are assumed to be independent of temperature, hence the momentum equation uncouples from the thermal problem. We first derive the similarity equations for the velocity and present exact solutions for the case where the power law index n = 2. The similarity solutions are used to validate the new approximation method. This new technique is then applied to the thermal boundary layer, where a similarity solution can only be obtained for the case n = 1.

Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Long-term efficacy and safety of atazanavir/ritonavir treatment in a cohort of treatment-naïve HIV patients: An interim analysis of the REMAIN study.

Purpose: Combined antiretroviral therapy has dramatically improved HIV-infected individuals survival. Long-term strategies are currently needed to achieve the goal of durable virologic suppression. However, long-term available data for specific antiretrovirals (ARV) are limited. In clinical trials, boosted atazanavir (ATV/r) regimens has shown good efficacy and tolerability in ARV-naïve patients for up to 4 years. The REMAIN study aimed to evaluate the long-term outcomes of ATV/r regimens in ARV-naïve patients in a real life setting. Methods: Non-comparative, observational study conducted in Germany, Portugal and Spain. Historical and longitudinal follow-up data was extracted six monthly from the medical record of HIV-infected, treatment-naïve patients, who initiated an ATV/r-regimen between 2008 and 2010. The primary endpoint was the proportion of patients remaining on ATV treatment over time. Secondary endpoints included virologic response (HIV-1 RNA <50 c/mL and <500 c/mL), reasons for discontinuation and long-term safety. The duration of treatment and time to virologic failure (VF) were analyzed using the Kaplan- Meier method. Data from an interim analysis including patients with at least one year of follow-up are reported here. Results: A total of 411 patients were included in this interim analysis [median (Q1, Q3) follow-up: 23.42 (16.25, 32.24) months≥: 77% male; median age 40 years [min, max: 19, 78≥; 16% IDUs; 18% CDC C; 18% hepatitis C. TDF/FTC was the most common backbone (85%). At baseline, median (Q1, Q3) HIV-RNA and CD4 cell count were 4.91 (4.34, 5.34) log10 c/mL and 256 (139, 353) cells/mm3, respectively. The probability of remaining on treatment was 0.84 (95% CI: 0.80, 0.87) and 0.72 (95% CI: 0.67, 0.76) for the first and second year, respectively. After 2 years of follow-up, 84% (95% CI: 0.79, 0.88) of patients were virologically suppressed (<50 c/mL). No major protease inhibitors mutations were observed at VF. Overall, 125 patients (30%) discontinued ATV therapy [median (Q1, Q3) time to discontinuation: 11.14 (6.24, 19.35) months]. Adverse events (AEs) were the main reason for discontinuation (n =47, 11%). Hyperbilirubinaemia was the most common AE leading to discontinuation (14 patients). No unexpected AEs were reported. Conclusions: In a real life clinical setting, ATV/r regimens showed durable virologic efficacy with good tolerability in an ARV-naïve population. Data from longer follow-up will provide additional valuable information.

Safety in vicinity of industrials plants: risk assessment and land use planning

The aim of this book is to survey on different Land Use Planning and safety approaches in vicinity of industrial plants. As this research is associated with three broad fields of Land Use Planning, safety and security, the set principle is to avoid unnecessary and over detailed information, but including the useful ones to provide a comprehensive resource which can be applicable for several purposes. Besides, the proposed method, which is explained in Chapter 7, can initiate a new field for future of Land Use Planning in vicinity of industrial plants.

Prediction and discrimination of osteoporotic hip fracture in postmenopausal women.

Osteoporotic hip fractures increase dramatically with age and are responsible for considerable morbidity and mortality. Several treatments to prevent the occurrence of hip fracture have been validated in large randomized trials and the current challenge is to improve the identification of individuals at high risk of fracture who would benefit from therapeutic or preventive intervention. We have performed an exhaustive literature review on hip fracture predictors, focusing primarily on clinical risk factors, dual X-ray absorptiometry (DXA), quantitative ultrasound, and bone markers. This review is based on original articles and meta-analyses. We have selected studies that aim both to predict the risk of hip fracture and to discriminate individuals with or without fracture. We have included only postmenopausal women in our review. For studies involving both men and women, only results concerning women have been considered. Regarding clinical factors, only prospective studies have been taken into account. Predictive factors have been used as stand-alone tools to predict hip fracture or sequentially through successive selection processes or by combination into risk scores. There is still much debate as to whether or not the combination of these various parameters, as risk scores or as sequential or concurrent combinations, could help to better predict hip fracture. There are conflicting results on whether or not such combinations provide improvement over each method alone. Sequential combination of bone mineral density and ultrasound parameters might be cost-effective compared with DXA alone, because of fewer bone mineral density measurements. However, use of multiple techniques may increase costs. One problem that precludes comparison of most published studies is that they use either relative risk, or absolute risk, or sensitivity and specificity. The absolute risk of individuals given their risk factors and bone assessment results would be a more appropriate model for decision-making than relative risk. Currently, a group appointed by the World Health Organization and lead by Professor John Kanis is working on such a model. It will therefore be possible to further assess the best choice of threshold to optimize the number of women needed to screen for each country and each treatment.

Development of a cost-effective method for platelet-rich plasma (PRP) preparation for topical wound healing.

Platelet-rich plasma (PRP) is a volume of plasma fraction of autologous blood having platelet concentrations above baseline whole-blood values due to processing and concentration. PRP is used in various surgical fields to enhance soft-tissue and bone healing by delivering supra-physiological concentrations of autologous platelets at the site of tissue damage. These preparations may provide a good cellular source of various growth factors and cytokines, and modulate tissue response to injury. Common clinically available materials for blood preparations combined with a two-step centrifugation protocol at 280g each, to ensure cellular component integrity, provided platelet preparations which were concentrated 2-3 fold over total blood values. Costs were shown to be lower than those of other methods which require specific equipment and high-cost disposables, while safety and traceability can be increased. PRP can be used for the treatment of wounds of all types including burns and also of split-thickness skin graft donor sites, which are frequently used in burn management. The procedure can be standardized and is easy to adapt in clinical settings with minimal infrastructure, thus enabling large numbers of patients to benefit from a form of cellular therapy.

Collection of tracheal aspirate: safety and microbiological concordance between two techniques

Objective: To evaluate the safety of the performance of the traditional and protected collection techniques of tracheal aspirate and to identify qualitative and quantitative agreement of the results of microbiological cultures between the techniques. Method: Clinical, prospective, comparative, single-blind research. The sample was composed of 54 patients of >18 years of age, undergoing invasive mechanical ventilation for a period of ≥48 hours and with suspected Ventilator Associated Pneumonia. The two techniques were implemented in the same patient, one immediately after the other, with an order of random execution, according to randomization by specialized software. Results: No significant events occurred oxygen desaturation, hemodynamic instability or tracheobronchial hemorrhage (p<0.05) and, although there were differences in some strains, there was qualitative and quantitative agreement between the techniques (p<0.001). Conclusion: Utilization of the protected technique provided no advantage over the traditional and execution of both techniques was safe for the patient.