Risk factors for myocardial infarct: a case-control study in Oporto, Portugal

A case-control study of coronary heart disease (CHD) was conducted in Oporto, Portugal. The cases series consisted of 100 consecutive patients with first time acute myocardial infarction who were admitted to the Coronary and Intermediate Care Units of a major teaching hospital. The community controls were 198 individuals without evidence of CHD by the Rose questionnaire and electrocardiography, selected by random digit dialing, with a participation rate of 70%. Data was collected by trained interviewers using a structured questionnaire and blood samples were obtained for selected laboratory data. The main analysis was made through unconditional logistic regression with calculations of odds ratios (OR). Age, OR: 1.5 (95% CI: 0.8-2.9), male gender, OR: 6.7 (3.6-12.3), family history of premature CHD, OR: 2.4 (1.4-4.3), diabetes, OR: 3.4 (1.6-7.4), antecedents of hypertension, OR:1.9 (1.1-3.1), history of high cholesterol levels, OR: 2.3 (1.4-3.9), high levels of physical activity, OR: 2.0 (0.9-4.1) and tobacco smoking, OR: 8.3 (3.8-18.5) were significant risk factors of acute myocardial infarction. After controlling for demographic variables and for the mutual confounding effects of the risk factors, the investigated factors that remained significantly associated with the risk of developing acute myocardial infarction were male gender, OR: 17.3 (4.8-62.3), family history of CHD, OR: 3.6 (1.4-9.6), diabetes, OR: 4.2 (1.0-18.1), high cholesterol levels OR: 2.7 (1.2-6.1) and smoking habits, OR: 7.7 (1.8-32.4). A negative association with high education levels was significant after controlling for all the variables, OR: 0.01 (0.01-0.5).     

Parameter Estimation in Groundwater Hydrology Using Artificial Neural Networks

The capability of artificial neural networks to act as universal function approximators has been traditionally used to model problems in which the relation between dependent and independent variables is poorly understood. In this paper, the capability of an artificial neural network to provide a data-driven approximation of the explicit relation between transmissivity and hydraulic head as described by the groundwater flow equation is demonstrated. Techniques are applied to determine the optimal number of nodes and training patterns needed for a neural network to approximate groundwater parameters for a simulated groundwater modeling case study. Furthermore, the paper explains how such an approximation can be used for the purpose of parameter estimation in groundwater hydrology.     

Stability for impulsive control systems

In this paper we extend the notion of the control Lyapounov pair of functions and derive a stability theory for impulsive control systems. The control system is a measure driven differential inclusion that is partly absolutely continuous and partly singular. Some examples illustrating the features of Lyapounov stability are provided.     

Expert systems as tools for the explanation of the legal domain: The ARPO experiences

The necessity of having explanations of the knowledge used by professionals, such as the jurists, who are not accustomed to using formal languages, makes it necessary to develop strategies for capturing and storing knowledge with computers. This action eventually needs to work in special programs using standard resources. This is made in the program ARPO, using an expert system in order to explain the jurist's knowledge. The paper speaks about the steps made in this sense from the experiences of ARPO.     

Bursting and tonic discharges in two classes of reticular thalamic neurons

1. Two types of cat reticular (RE) thalamic cells were disclosed by means of intracellular recordings under urethan anesthesia. The RE neurons were identified by their typical depolarizing spindle oscillations in response to synchronous stimulation of the internal capsule. 2. In type I neurons (n = 41), depolarizing current pulses induced tonic firing at the resting or slightly depolarized membrane potential (Vm) and triggered high-frequency spike bursts at a Vm more negative than -75 mV. As well, these cells discharged rebound bursts at the break of a hyperpolarizing current pulse. Internal capsule stimulation elicited spindle sequences made off by depolarizing waves giving rise to spike bursts. 3. Type II cells (n = 9) did not discharge spike bursts to large depolarizing current pulses even when the Vm reached -100 mV, nor did they fire rebound bursts after long-lasting hyperpolarizing current pulses or spike bursts riding on the rhythmic depolarizing components of spindle sequences. 4. Compared with type I cells, type II cells showed less frequency accommodation during tonic firing. The latter neuronal class discharged at high frequencies (40 Hz) with slight DC depolarization, approximately 8-10 Hz at the resting Vm, and no underlying synaptic or subthreshold oscillatory events could be detected when the firing was blocked by DC hyperpolarization. 5. The presence of two cell classes in the RE nucleus challenges the common view that this nucleus consists of a single neuronal class. We suggest that a different set of conductances is present in type II RE neurons, thus preventing the low-threshold Ca2+ current from dominating the behavior of these cells.     

The evolution of the U.S. industrial landscape, 1969–1995

The industrial landscape of the U.S. has undergone major changes in the last three decades, which have affected the location of the work-force as much as sector location. This paper adopts a dynamic approach in order to analyse the principal characteristics of this process in the time-period 1969–1995 among the twenty two-digit SIC industries. Two main conclusions have emerged. First, we find that, in general, industries are tending to reduce their degree of concentration. Secondly, the classification of industries according to different economic criteria allows us to test the degree of compliance with various theoretical propositions and to detect relevant empirical regularities. Received: July 2001/Accepted: August 2002 The authors would like to express their thanks to two anonymous referees for their valuable comments and observations on an earlier version of this work. Similarly, they are grateful for the financial support provided by the University of Zaragoza under Project UZ2001-SOC-09.     

Establishment of an empirical correlation for estimating the thermal conductivity of igneous rocks

A correlation to predict the thermal conductivity of andesitic igneous rocks is developed from measured data on drill cores from wells from the Los Azufres geothermal field, Mexico. The correlation was developed from density, porosity, and thermal conductivity. Seventeen determinations were made on drill cores extracted at varying depths from 12 wells. Thermal conductivity varied from 1.05 to 2.34 W · m^–1 · K^–1, while bulk density varied from 2050 to 2740 kg · m^–3 and grain density varied from 2610 to 2940 kg · m^–3. Total porosity varied from 1.9 to 24.7%. Two polynomial regressions, one linear and one quadratic, were tested on the thermal conductivity-times-bulk density product, with total porosity as the independent variable. The correlation coefficients and residual mean square deviations were 0.83 and 0.00491 for the linear fit and 0.87 and 0.00425 for the quadratic model, respectively. For porosities up to about 18%, both models showed very close predictions, but for larger values, the quadratic model appeared to be better and it is recommended for the porosity range from 0 to 25%. Furthermore, density and porosity may be determined from drill cuttings, which are more readily available than cores.Paper presented at the Tenth Symposium on Thermophysical Properties, June 20–23, 1988, Gaithersburg, Maryland, U.S.A.     

The performance of forced convection greenhouse driers

An analytical study of the evaporation rate in two types of forced convection greenhouse driers, the single and the double chamber systems, is presented. A performance parameter defined to compare both driers and its dependence on the operational variables is studied introducing the concept of the characteristic function. The drying curve is calculated and a time scale change is introduced to reduce the curves obtained under different operational conditions to a single generalized drying curve. Simulation tests for red pepper are presented showing that the use of a double chamber drier improves the productivity by almost 90%.