38 research outputs found
The required competencies of project managers in metallurgical companies in the Czech Republic
This paper is focussed on the problems of competencies of project managers in the corporate practice of metallurgical companies in the Czech Republic. The authors aim to assess the requirements imposed on the position of a project manager from the point of view of the corporate management. The authors identify the basic areas playing a significant role in assessment of project managers’ competencies. They represent procedures applicable within selection of a project manager. Subsequently, the authors present outcomes of a survey, these outcomes show requirements of corporate management represented by human resource department managers of metallurgical companies in the Czech Republic when recruiting project managers in practice
Recommended from our members
Reducing greenhouse gas emissions in Czechoslovakia
In this paper are presented important findings on the potential for energy conservation and carbon emissions reduction over the coming decades in Czechoslovakia. The authors describe the state of the energy use in Czechoslovakia today and the measures required to transform its energy system to a market-based economy oriented towards the environmental goal of decreased energy intensity. This work furthers our understanding of the need for energy efficiency in the newly forming market economies of East and Central Europe. This paper is part of a series of country studies sponsored by the Global Climate Division of the Office of Policy, Planning, and Evaluation, United States Environmental Protection Agency (EPA). We have completed similar studies in Canada, the former Soviet Union, France, Hungary, Italy, Japan, Poland the United Kingdom, and the United States. Research is currently underway or planned in Bulgaria, Romania, and Ukraine
Antibody response to sand fly saliva is a marker of transmission intensity but not disease progression in dogs naturally infected with Leishmania infantum
BACKGROUND: Antibody responses to sand fly saliva have been suggested to be a useful marker of exposure to sand fly bites and Leishmania infection and a potential tool to monitor the effectiveness of entomological interventions. Exposure to sand fly bites before infection has also been suggested to modulate the severity of the infection. Here, we test these hypotheses by quantifying the anti-saliva IgG response in a cohort study of dogs exposed to natural infection with Leishmania infantum in Brazil. METHODS: IgG responses to crude salivary antigens of the sand fly Lutzomyia longipalpis were measured by ELISA in longitudinal serum samples from 47 previously unexposed sentinel dogs and 11 initially uninfected resident dogs for up to 2 years. Antibody responses were compared to the intensity of transmission, assessed by variation in the incidence of infection between seasons and between dogs. Antibody responses before patent infection were then compared with the severity of infection, assessed using tissue parasite loads and clinical symptoms. RESULTS: Previously unexposed dogs acquired anti-saliva antibody responses within 2 months, and the rate of acquisition increased with the intensity of seasonal transmission. Over the following 2 years, antibody responses varied with seasonal transmission and sand fly numbers, declining rapidly in periods of low transmission. Antibody responses varied greatly between dogs and correlated with the intensity of transmission experienced by individual dogs, measured by the number of days in the field before patent infection. After infection, anti-saliva antibody responses were positively correlated with anti-parasite antibody responses. However, there was no evidence that the degree of exposure to sand fly bites before infection affected the severity of the infection. CONCLUSIONS: Anti-saliva antibody responses are a marker of current transmission intensity in dogs exposed to natural infection with Leishmania infantum, but are not associated with the outcome of infection
Parkinson Disease Detection from Speech Articulation Neuromechanics
Aim: The research described is intended to give a description of articulation dynamics as a correlate of the kinematic behavior of the jaw-tongue biomechanical system, encoded as a probability distribution of an absolute joint velocity. This distribution may be used in detecting and grading speech from patients affected by neurodegenerative illnesses, as Parkinson Disease. Hypothesis: The work hypothesis is that the probability density function of the absolute joint velocity includes information on the stability of phonation when applied to sustained vowels, as well as on fluency if applied to connected speech. Methods: A dataset of sustained vowels recorded from Parkinson Disease patients is contrasted with similar recordings from normative subjects. The probability distribution of the absolute kinematic velocity of the jaw-tongue system is extracted from each utterance. A Random Least Squares Feed-Forward Network (RLSFN) has been used as a binary classifier working on the pathological and normative datasets in a leave-one-out strategy. Monte Carlo simulations have been conducted to estimate the influence of the stochastic nature of the classifier. Two datasets for each gender were tested (males and females) including 26 normative and 53 pathological subjects in the male set, and 25 normative and 38 pathological in the female set. Results: Male and female data subsets were tested in single runs, yielding equal error rates under 0.6% (Accuracy over 99.4%). Due to the stochastic nature of each experiment, Monte Carlo runs were conducted to test the reliability of the methodology. The average detection results after 200 Montecarlo runs of a 200 hyperplane hidden layer RLSFN are given in terms of Sensitivity (males: 0.9946, females: 0.9942), Specificity (males: 0.9944, females: 0.9941) and Accuracy (males: 0.9945, females: 0.9942). The area under the ROC curve is 0.9947 (males) and 0.9945 (females). The equal error rate is 0.0054 (males) and 0.0057 (females). Conclusions: The proposed methodology avails that the use of highly normalized descriptors as the probability distribution of kinematic variables of vowel articulation stability, which has some interesting properties in terms of information theory, boosts the potential of simple yet powerful classifiers in producing quite acceptable detection results in Parkinson Disease
Parkinson Disease detetion from speech articulation neuromechanics
The research described is intended to give a description of articulation dynamics as a correlate of the kinematic behavior of the jaw-tongue biomechanical system, encoded as a probability distribution of an absolute joint velocity. This distribution may be used in detecting and grading speech from patients affected by neurodegenerative illnesses, as Parkinson Disease
Neuromechanical modelling of articulatory movements from surface electromyography and speech formants
Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson’s Disease
Recommended from our members
Reducing greenhouse gas emissions in Czechoslovakia
In this paper are presented important findings on the potential for energy conservation and carbon emissions reduction over the coming decades in Czechoslovakia. The authors describe the state of the energy use in Czechoslovakia today and the measures required to transform its energy system to a market-based economy oriented towards the environmental goal of decreased energy intensity. This work furthers our understanding of the need for energy efficiency in the newly forming market economies of East and Central Europe. This paper is part of a series of country studies sponsored by the Global Climate Division of the Office of Policy, Planning, and Evaluation, United States Environmental Protection Agency (EPA). We have completed similar studies in Canada, the former Soviet Union, France, Hungary, Italy, Japan, Poland the United Kingdom, and the United States. Research is currently underway or planned in Bulgaria, Romania, and Ukraine
Monthly rainfall erosivity: Conversion factors for different time resolutions and regional assessments
As a follow up and an advancement of the recently published Rainfall Erosivity Database at European Scale (REDES) and the respective mean annual R-factor map, the monthly aspect of rainfall erosivity has been added to REDES. Rainfall erosivity is crucial to be considered at a monthly resolution, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices) as well as natural hazard protection (landslides and flood prediction). We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland) or former data density was not satisfactory (Austria, France, and Spain). The different time resolutions (from 5 to 60 min) of high temporal data require a conversion of monthly R-factor based on a pool of stations with available data at all time resolutions. Because the conversion factors show smaller monthly variability in winter (January: 1.54) than in summer (August: 2.13), applying conversion factors on a monthly basis is suggested. The estimated monthly conversion factors allow transferring the R-factor to the desired time resolution at a European scale. The June to September period contributes to 53% of the annual rainfall erosivity in Europe, with different spatial and temporal patterns depending on the region. The study also investigated the heterogeneous seasonal patterns in different regions of Europe: on average, the Northern and Central European countries exhibit the largest R-factor values in summer, while the Southern European countries do so from October to January. In almost all countries (excluding Ireland, United Kingdom and North France), the seasonal variability of rainfall erosivity is high. Very few areas (mainly located in Spain and France) show the largest from February to April. The average monthly erosivity density is very large in August (1.67) and July (1.63), while very small in January and February (0.37). This study addresses the need to develop monthly calibration factors for seasonal estimation of rainfall erosivity and presents the spatial patterns of monthly rainfall erosivity in European Union and Switzerland. Moreover, the study presents the regions and seasons under threat of rainfall erosivity