Treatment of essential arterial hypertension with hypercholesterolemia. Effects of an alpha-adrenergic blocker and an inhibitor of the angiotensin converting enzyme

BACKGROUND: Hypertension and hypercholesterolemia are frequently associated with this leading to considerable cardiovascular risk. METHODS: An open parallel randomized study was performed in which the effects of doxazosin, an alpha-adrenergic blocker and enalapril, an inhibitor of the angiotensin converting enzyme were compared in 70 patients with essential high blood pressure and plasma cholesterol levels greater than 240 mg/dl. Following 2-4 weeks of placebo administration the patients were randomly treated with one of the two drugs. When required doses were increased and hydrochlorothiazide added until blood pressure lower than 160/95 mmHg was achieved. After this period the patients were observed for a minimum of 8 weeks. The mean length of the study was of 22 weeks. RESULTS: Both drugs significantly reduced blood pressure without modifying cardiac frequency. Doxazosin tended to favorably modify the lipid profile of the plasma while enalapril significantly reduced the levels of cholesterol, lipids and high density lipoproteins (HDL). Upon termination of the study the total HDL/cholesterol index increased 8.6% in those treated with doxazosin and decreased 5.5% in those receiving enalapril (p < 0.05). CONCLUSIONS: Although doxazosin and enalapril are potent antihypertensive drugs, the effects on plasma lipid obtained with doxazosin indicate that a reduction in cardiovascular risk was achieved with this drug in the patients included in this study.     

Income, Time Effects and Direct Preferences in a Multimodal Choice Context: Application of Mixed RP/SP Models with Non-Linear Utilities

Transport problems typically involve at least two types of constraints, on income and on time. Therefore, the indirect utility function depends either on the income available after having subtracted the cost of the discrete alternative and on the free time left after having worked and travelled by each competing option. In the typical linear-in-the-attributes and in-the-parameters specification, that represents the first grade approximation of the indirect utility function, the effect of income and time constraints cancel out and only the cost and time of the alternatives matter in the comparison between them. From a microeconomic point of view this is equivalent to assume that income and time effects could be disregarded; which is not always the case. To account for these effects the utility function should include second order attributes; however, in non-linear utility functions it may not be easy to distinguish among several effects that could be relevant: direct preferences for good and leisure, and simple interactions between attributes other than income and time effects. This paper analyses these effects from a theoretical point of view focusing on the possible confounding problem in detecting income and time effects. We use a dataset collected for a modal choice context and containing both revealed and stated preference data, and estimate several NL models examining the effect of the different second-order terms on detecting income and time effects. We compared specifications including square cost and time attributes, interactions between time and cost, cost divided by the income available to be spent on free time, and time multiplied by free time. Our results confirm the strong effect of direct preferences for goods and leisure time on choice, and the potential confounding effect between quadratic attributes and other non-linear omitted terms. Finally, we also found that care should be taken in highlighting income and time effects using mixed data sources, since confounding effects can occur when non-linearities are accounted for in both data sets.     

Crystallization and melting behaviour of poly(butylene terephthalate) in poly(butylene terephthalate)/polyarylate blends

Summary The crystallization and melting behaviour of poly(butylene terephthalate) has been studied in the pure state and in its blends with a polyarylate of bisphenol A and isophthalic/terephthalic acids. Differential scanning calorimetry has been used as experimental technique and the effects of different thermal treatments have been analyzed. Results show the hindrance for the crystallization of poly(butylene terephthalate) imposed by the presence of polyarylate, as well as the existence of multiple melting after isothermal crystallization. Explanations are given for the observed behaviours.     

Deciding bisimilarity is<Emphasis Type="Italic">P</Emphasis>-complete

In finite labelled transition systems the problems of deciding strong bisimilarity, observation equivalence and observation congruence areP-complete under many—oneNC-reducibility. As a consequence, algorithms for automated analysis of finite state systems based on bisimulation seem to be inherently sequential in the following sense: the design of anNC algorithm to solve any of these problems will require an algorithmic breakthrough, which is exceedingly hard to achieve.     

Using knowledge of misunderstandings to increase the robustness of spoken dialogue systems

This paper proposes a new technique to increase the robustness of spoken dialogue systems employing an automatic procedure that aims to correct frames incorrectly generated by the system’s component that deals with spoken language understanding. To do this the technique carries out a training that takes into account knowledge of previous system misunderstandings. The correction is transparent for the user as he is not aware of some mistakes made by the speech recogniser and thus interaction with the system can proceed more naturally. Experiments have been carried out using two spoken dialogue systems previously developed in our lab: Saplen and Viajero, which employ prompt-dependent and prompt-independent language models for speech recognition. The results obtained from 10,000 simulated dialogues show that the technique improves the performance of the two systems for both kinds of language modelling, especially for the prompt-independent language model. Using this type of model the Saplen system increases sentence understanding by 19.54%, task completion by 26.25%, word accuracy by 7.53%, and implicit recovery of speech recognition errors by 20.3%, whereas for the Viajero system these figures increase by 14.93%, 18.06%, 6.98% and 15.63%, respectively.     

A multiobjective GRASP–VND algorithm to solve the waste collection problem

In this paper, the waste collection problem (WCP) of a city in the south of Spain is addressed as a multiobjective routing problem that considers three objectives. From the company's perspective, the minimization of the travel cost is desired as well as that of the total number of vehicles. Additionally, from the employee's point of view, a set of balanced routes is also sought. Four variants of a multiobjective hybrid algorithm are proposed. Specifically, a GRASP (greedy randomized adaptive search procedure) with a VND (variable neighborhood descent) is combined. The best GRASP–VND algorithm found is applied in order to solve the real‐world WCP of a city in the south of Spain.     

Google Scholar Metrics evolution: an analysis according to languages

In November 2012 the Google Scholar Metrics (GSM) journal rankings were updated, making it possible to compare bibliometric indicators in the ten languages indexed—and their stability—with the April 2012 version. The h-index and h-5 median of 1,000 journals were analysed, comparing their averages, maximum and minimum values and the correlation coefficient within rankings. The bibliometric figures grew significantly. In just seven and a half months the h-index of the journals increased by 15 % and the median h-index by 17 %. This growth was observed for all the bibliometric indicators analysed and for practically every journal. However, we found significant differences in growth rates depending on the language in which the journal is published. Moreover, the journal rankings seem to be stable between April and November, reinforcing the credibility of the data held by Google Scholar and the reliability of the GSM journal rankings, despite the uncontrolled growth of Google Scholar. Based on the findings of this study we suggest, firstly, that Google should upgrade its rankings at least semi-annually and, secondly, that the results should be displayed in each ranking proportionally to the number of journals indexed by language.     

Geographical Authentication of Tequila According to its Mineral Content by Means of Support Vector Machines

The elemental profile of tequila samples from the three main production areas of the State of Jalisco, namely Amatitlan, Guadalajara, and Tequila, was used to carry out their geographical characterization. With this aim, the concentration of Al, Ba, Ca, Cu, Fe, K, Mg, Mn, Na, S, Sr, and Zn was determined by inductively coupled plasma atomic emission spectroscopy. Principal component analysis was addressed to visualize data trends. The number of input variables was reduced by means of backward stepwise linear discriminant analysis and support vector machines were used to construct an adequate classification model. The best classification performance was obtained by a linear support vector machine model with 100% of prediction ability.