Automatic Detection of Laryngeal Pathology on Sustained Vowels Using Short-Term Cepstral Parameters: Analysis of Performance and Theoretical Justification

The majority of speech signal analysis procedures for automatic detection of laryngeal pathologies mainly rely on parameters extracted from time domain processing. Moreover, calculation of these parameters often requires prior pitch period estimation; therefore, their validity heavily depends on the robustness of pitch detection. Within this paper, an alternative approach based on cepstral- domain processing is presented which has the advantage of not requiring pitch estimation, thus providing a gain in both simplicity and robustness. While the proposed scheme is similar to solutions based on Mel-frequency cepstral parameters, already present in literature, it has an easier physical interpretation while achieving similar performance standards

Perturbative evolution of far off-resonance driven two-level systems: Coherent population trapping, localization, and harmonic generation

The time evolution of driven two-level systems in the far off-resonance regime is studied analytically. We obtain a general first-order perturbative expression for the time-dependent density operator which is applicable regardless of the coupling strength value. In the strong field regime, our perturbative expansion remains valid even when the far off-resonance condition is not fulfilled. We find that, in the absence of dissipation, driven two-level systems exhibit coherent population trapping in a certain region of parameter space, a property which, in the particular case of a symmetric double-well potential, implies the well-known localization of the system in one of the two wells. Finally, we show how the high-order harmonic generation that this kind of systems display can be obtained as a straightforward application of our formulation.Comment: 14 pages, LaTeX, 2 figures, acknowledgments adde

Tobacco Taxes as the Unsung Hero: Impact of a Tax Increase on Advancing Sustainable Development in Colombia

Objective: Tobacco taxes are a well-established cost-effective policy to prevent Noncommunicable Diseases. This paper evaluates the expected effects of a tobacco tax increase on the Sustainable Development Goals in Colombia. Methods: We use microsimulation to build an artificial society that mimics the observed characteristics of Colombia’s population, and from there we simulate the behavioral response to a tax increase of COP$4,750 (an increase that has been discussed by policy makers and legislators) and the subsequent effects in all SDGs. Results: The tobacco tax hike reduces the number of smokers (from 4.51 to 3.45 MM smokers) and smoking intensity, resulting in a drop in the number of cigarettes smoked in Colombia (from 332.3 to 215.5 MM of 20-stick packs). Such reduction is expected to decrease premature mortality, healthcare costs, poverty and people facing catastrophic expenditure on healthcare, to increase health, income and gender equity, and to strengthen domestic resource mobilization even in the presence of illicit cigarettes. Conclusion: Tobacco taxes are an effective intervention for public health and a powerful instrument to advance on the 2030 Sustainable Development Agenda. Relevance: A comprehensive analysis of the impact of tobacco taxes on all areas of Sustainable Development is missing in the empirical literature. Such perspective is needed to break the barriers for further tobacco tax increases by gathering wider societal support, especially from stakeholders and key decision makers from development areas other than health. SDG Nr: SDG3 (health), SDG 1 (no poverty), SDG 4 (education), SDG 5 (gender equality), SDG6 (water), SDG10 (inequality), SDG12 (responsible production and consumption), SDG17 (partnerships)

Caracterización parcial de una proteinasa coagulante de la leche aislada del alcaucil (Cynara scolymus L., Asteraceae)

The presence of proteinases in Cynara scolyrnus L. ( artichoke ) has been investigated by determining the proteolytic and milk clotting activities of crude extracts of different parts of the inflorescence in various stages of development, as well as of leaves and roots. Although all the preparations showed a certain extent of proteolytic activity, only those of adult leaves, pappus, and immature and mature flowers were able to clot milk. The extract of the upper (violet) part of mature flowers exhibited optimum activity at acid pH values (90% of maximum activity at pH 3.5 - 5.0) which was strongly inhibited by pepstatine A, suggesting the presence of aspartic proteinases. This extract had a low thermal stability at temperatures above 45ºC, which could be a useful property in cheese making process, as it could be quickly inactivated by moderate heating.Se ha estudiado la presencia de proteinasas en el alcaucil (Cynara scolymus L.) midiendo la actividad proteolítica y la capacidad coagulante de la leche de preparaciones crudas de diferentes partes de la inflorescencia en distintos estadios de desarrollo, así como en raíces y hojas. Si bien se detecta actividad proteolitica en todas las preparaciones, sólo las de hojas adultas, de papus y de flores inmaduras y maduras son capaces de coagular la leche. El extracto de la parte superior (violeta) de las flores maduras exhibe un perfil de pH que es óptimo en la zona ácida (90% de máxima actividad entre pH 3,5 y 5,0), pero la actividad es fuertemente inhibida por pepstatina A, lo que sugeriría la presencia de una o más proteinasas aspárticas. La estabilidad térmica del extracto es baja a temperaturas superiores a 45ºC, circunstancia que puede resultar de utilidad en la producción de quesos, ya que la enzima puede ser inactivada a temperaturas moderadas

Permanent-magnet atom chips for the study of long, thin atom clouds

Atom-chip technology can be used to confine atoms tightly using permanently magnetised videotape along with external magnetic fields. The one-dimensional (1D) gas regime can be realised and studied by trapping the atoms in high-aspect-ratio traps in which the radial motion of the system is confined to zero-point oscillation

FPGA-Based Urinalysis Using Principal Component Analysis

Urinalysis is considered to be a common test performed in laboratory in order to diagnose Urinary Tract Infection (UTI). It undergoes three stages, which include macroscopic, dipstick, and microscopic analysis. This paper describes a way of performing urinalysis for UTI detection using the Principal Component Analysis (PCA) implemented using a Field Programmable Gate Array (FPGA). Input to the system is from five ion-selective sensors that measure five different components specifically sodium, nitrite, nitrate, potassium, and pH level of a urine sample. Tests show that the system obtained an accuracy of 94.13% for standard urinalysis showing the accuracy of sensors and measurements used. To be able to detect the presence of UTI in urines, an outlier detection method Principal Component Analysis (PCA), was used. PCA is a tool used in reducing multidimensional data to lesser dimensions while keeping all the information. An accuracy of 83.33% in detecting UTI infection was achieved. The accuracy of FPGA implementation of PCA was compared with MATLAB calculation results and an accuracy of 99.917% was achieved

Variability of the prevalence of depression in function of sociodemographic and environmental factors: ecological model

Major depression etiopathogenesis is related to a wide variety of genetics, demographic and psychosocial factors, as well as to environmental factors. The objective of this study is to analyze sociodemographic and environmental variables that are related to the prevalence of depression through correlation analysis and to develop a regression model that explains the behavior of this disease from an ecological perspective. This is an ecological, retrospective, cross-sectional study. The target population was 1,148,430 individuals over the age of 16 who were registered in Aragon (Spain) during 2010, with electronic medical records in the community’s primary health care centers. The spatial unit was the Basic Health Area (BHA). The dependent variable was the diagnosis of Depression and the ecological independent variables were: Demographic variables (gender and age), population distribution, typology of the entity, population structure by sex and age, by nationality, by education, by work, by salary, by marital status, structure of the household by number of members, and state of the buildings. The results show moderate and positive correlations with higher rates of depression in areas having a higher femininity index, higher population density, areas with a higher unemployment rate and higher average salary. The results of the linear regression show that aging +75 and rural entities act as protective factors for depression, while urban areas and deficient buildings act as risk factors. In conclusion, the ecological methodology may be a useful tool which, together with the statistical epidemiological analysis, can help in the political decision making process

Analyzing the social factors that influence willingness to pay for the management of invasive alien species under two different strategies: eradication and prevention

This an accepted author's manuscript (AAM) version of an article published in Environmental Management, 48 (2011): 418-43