The Individualized Genetic Barrier Predicts Treatment Response in a Large Cohort of HIV-1 Infected Patients.

The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests.

The changing relationship between commodity prices and equity prices in commodity exporting

We explore the linkage between equity and commodity markets, focusing in particular on its evolution over time. We document that a country's equity market valuehas significant out-of-sample predictive ability for the future global commodity priceindex for several primary commodity-exporting countries. The out-of-sample predictive ability of the equity market appears around 2000s. The results are robust to usingseveral control variables as well as firm-level equity data. Finally, our results indicatethat exchange rates are a better predictor of commodity prices than equity markets,especially at very short horizons.

Exchange rate predictability

The main goal of this article is to provide an answer to the question: "Does anything forecast exchange rates, and if so, which variables?". It is well known thatexchange rate fluctuations are very difficult to predict using economic models, andthat a random walk forecasts exchange rates better than any economic model (theMeese and Rogoff puzzle). However, the recent literature has identified a series of fundamentals/methodologies that claim to have resolved the puzzle. This article providesa critical review of the recent literature on exchange rate forecasting and illustratesthe new methodologies and fundamentals that have been recently proposed in an up-to-date, thorough empirical analysis. Overall, our analysis of the literature and thedata suggests that the answer to the question: "Are exchange rates predictable?" is,"It depends" -on the choice of predictor, forecast horizon, sample period, model, andforecast evaluation method. Predictability is most apparent when one or more of thefollowing hold: the predictors are Taylor rule or net foreign assets, the model is linear, and a small number of parameters are estimated. The toughest benchmark is therandom walk without drift.

Smith Predictor Sliding Mode Closed-loop Glucose Controller in Type 1 Diabetes

Type 1 diabetic patients depend on external insulin delivery to keep their blood glucose within near-normal ranges. In this work, two robust closed-loop controllers for blood glucose regulation are developed to prevent the life-threatening hypoglycemia, as well as to avoid extended hyperglycemia. The proposed controllers are designed by using the sliding mode control technique in a Smith predictor structure. To improve meal disturbance rejection, a simple feedforward controller is added to inject meal-time insulin bolus. Simulations scenarios were used to test the controllers, and showed the controllers ability to maintain the glucose levels within the safe limits in the presence of errors in measurements, modeling and meal estimation

Balance nutricional y número de hojas como variables de predicción del rendimiento del plátano Hartón

El objetivo de este trabajo fue desarrollar una ecuación de regresión que permitiese estimar el rendimiento (Y) del plátano Hartón (Musa AAB subgrupo plátano cv. Hartón), con la relación entre el Índice de Balance de Nutrientes DRIS (IBN-DRIS) (X1) y el número de hojas de la planta madre (X2). Usando un muestreo completamente al azar, se colectaron 398 muestras de tejido foliar. Se obtuvo la ecuación: Y = 30,351** - 8,644** log X1 + 0,27502*X2, con R² de 0,6206***, con distribución normal de los residuos. Pudo demostrarse que con la misma se puede predecir el rendimiento potencial de cualquier plantación del plátano Hartón en el área de estudio.

Tachycardia is a strong predictor of cardiovascular events in the value trial

Objective: Tachycardia is associated with hypertension and is a predictor of cardiovascular events. The predictive effect of tachycardia might reflect its connection with hypertension. In this analysis of 15,245 VALUE study patients we explore whether tachycardia predicts cardiovascular endpoints in high risk hypertension and whether the in-trial blood pressure lowering modified the tachycardia - related risk. Methods: Heart rate from ECG readings at baseline and annually throughout the trial. Results: In the Cox Regression analysis the primary endpoint hazard ratio for a 10 beats per minute increment of baseline heart rate was 1.16 (1.12-1.2) p < 0.0001, 1.17 (1.13-1.22) p < 0.0001 and 1.22 (1.18-1.27) p < 0.0001 unadjusted, adjusted for baseline blood pressure and for blood pressure plus risk factors, respectively. Primary endpoints strikingly increased in the highest quintile of baseline heart rate (=/>79 beats). Primary endpoints in the highest heart rate quintile were 30 % higher in first, 55 % in second, 55 % in third, 52 % in fourth and 46 % in the fifth year of the study. The in-trial heart rate was also a potent predictor. The primary endpoint hazard ratios of highest heart rate quintile versus pooled lower 4 quintiles was (1.34-1.66) p < 0.0001 unadjusted, 1.52 (1.36-1.69) p <0.0001 adjusted for baseline blood pressure and risk factors and 1.52 (1.36-1.69) p < 0.0001 further adjusted for in trial pressure. The increase of primary events in the upper quintile of in-trial heart rate was 68% in the group with good and 63% in the group with inadequate blood pressure control (both p < 0.0001 by log rank test). Conclusions: 1./ Tachycardia is a short term marker and a long term predictor of adverse event in high risk hypertension. 2./ Tachycardia contributes to the residual cardiovascular risk regardless of the degree of BP control. We hypothesize heart rate lowering with appropriate drugs may further decrease the cardiovascular risk in patients with high risk hypertension and tachycardia.

Increasing stair climbing in a train station: effects of contextual variables and visibility

Accumulation of physical activity during daily living is a current public health target that is influenced by the layout of the built environment. This study reports how the layout of the environment may influence responsiveness to an intervention. Pedestrian choices (n = 41 717) between stairs and the adjacent escalators were monitored for seven weeks in a train station (Birmingham, UK). After a 3.5 week baseline period, a stair riser banner intervention to increase stair climbing was installed on two staircases adjacent to escalators and monitoring continued for a further 3.5 weeks. Logistic regression analyses revealed that the visibility of the intervention, defined as the area of visibility in the horizontal plane opposite to the direction of travel (termed the isovist) had a major effect on success of the intervention. Only the largest isovist produced an increase in stair climbing (isovist=77.6 m2, OR = 1.10, CIs 1.02-1.19; isovist=40.7 m2, OR = 0.98, CIs 0.91-1.06; isovist=53.2 m2, OR = 1.00, CIs 0.95-1.06). Additionally, stair climbing was more common during the morning rush hour (OR = 1.56, CIs 1.80-2.59) and at higher levels of pedestrian traffic volume (OR = 1.92, CIs 1.68-2.21). The layout of the intervention site can influence responsiveness to point-of-choice interventions. Changes to the design of train stations may maximize the choice of the stairs at the expense of the escalator by pedestrians leaving the station.

Trust in medical organizations predicts pandemic (H1N1) 2009 vaccination behavior and perceived efficacy of protection measures in the Swiss public

Following the recent avian influenza and pandemic (H1N1) 2009 outbreaks, public trust in medical and political authorities is emerging as a new predictor of compliance with officially recommended protection measures. In a two-wave longitudinal survey of adults in French-speaking Switzerland, trust in medical organizations longitudinally predicted actual vaccination status 6 months later, during the pandemic (H1N1) 2009 vaccination campaign. No other variables explained significant amounts of variance. Trust in medical organizations also predicted perceived efficacy of officially recommended protection measures (getting vaccinated, washing hands, wearing a mask, sneezing into the elbow), as did beliefs about health issues (perceived vulnerability to disease, threat perceptions). These findings show that in the case of emerging infectious diseases, actual behavior and perceived efficacy of protection measures may have different antecedents. Moreover, they suggest that public trust is a crucial determinant of vaccination behavior and underscore the practical importance of managing trust in disease prevention campaigns.

Proposal of three thermodynamic variables to discriminate between storms associated with hail and storms with intense rainfall in Catalonia (Proposta de tres variables termodinàmiques per discriminar entre tempestes amb pedregades i tempestes amb pluges intenses)

Between late spring and early fall, the development of storms is common in Catalonia. Despite the fact that they usually produce heavy showers of short duration, they can also involve severe weather with ice pellets or hail. While the latter usually affect inland regions, and there are numerous publications on these cases; the analysis of events affecting the coast and causing damage to public and private properties is not so well developed. The aim of this study is to provide additional thermodynamic indicators that help differentiate storms with hail from storms without hail, considering cases that have affected various regions of Catalonia, mainly coastal areas. The aim is to give more information to improve prognosis and the ability to detail information in these situations. The procedure developed involved the study of several episodes of heavy rainfall and hail that hit Catalonia during the 2003-2009 period, mainly in the province of Girona, and validated the proposal during the campaign of late summer and fall of 2009, as well as 2012. For each case, several variables related to temperature, humidity and wind were analyzed at different levels of the atmosphere, while the information provided by the radio sounding in Barcelona was also taken into account. From this study, it can be concluded that the temperature difference between 500 hPa and 850 hPa, the humidity in the lower layers of the atmosphere and the LI index are good indicators for the detection of storms with associated hail.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.

Variation in biomass related variables of reed canary grass

Selostus: Ruokohelven biomassan tuotantoon vaikuttavien ominaisuuksien vaihtelu

Summer ozone cycles in the Lisbon metropolitan area and its relation to some meteorological variables

The aim of this work is to study the tropospheric ozone concentrations and daily peak cycles in the Lisbon MetropolitanArea (LMA) during the summer season (June, July and August, JJA) covering the 4-yr study period 2002-2005. Theresults show that all the stations have the same pattern: a minimum in the early morning followed by an increase at 1000UTC reaching to a peak at 1300-1400 UTC, dropped again to minimum values 1800 UTC but with different concentrationsdue to regional and local wind circulations and complex dynamic interactions. We identified in Lisbon city the ozone “weekendeffect”. Finally, we studied an episode of very high levels of tropospheric ozone and related daily ozone concentrationswith some meteorological variables.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen