Suchergebnisse

El desempeño laboral es una variable que permite lograr el éxito en toda organización y mucho más en las municipales donde se llevan a cabo tareas complejas con grandes impactos para sus parroquias pertenecientes, razón por la cual es necesario contar con información en torno a los factores inmersos para la toma de acciones pertinentes. Este artículo se realiza con el objetivo de determinar los factores personales y de riesgos psicosociales asociados al desempeño laboral de los funcionarios del municipio del cantón Chunchi. La metodología aplicada fue de tipo cuantitativo; el nivel de investigación fue exploratoria, descriptiva y correlacional, mientras que su método fue cuantitativa, descriptiva y correlacional. Los instrumentos utilizados para la recolección de datos fueron el Cuestionario SUSESO/ISTAS21 y el Cuestionario de desempeño laboral de Murphy. Los resultados muestran que la mayoría de funcionarios presenta un riesgo alto en relación al apoyo social (85,90%) y las compensaciones (84,90%), mientras que, muestran un riesgo bajo (43,80%) y medio (40,60%) respecto a la doble presencia. En relación el desempeño laboral, todos los factores son importantes: desempeño de las tareas (4,67), desempeño contextual (4,58) y el desempeño organizacional (4,70). Respecto a la correlación existente entre los factores personales y psicosociales se determinó que entre las variables y las dimensiones del desempeño laboral son en su mayoría nulas; únicamente se encontró una correlación negativa moderada entre las exigencias psicológicas y el desempeño de tareas (-0,364), y entre las compensaciones y el desempeño de tareas (0,504), con esto se indicó que el desempeño laboral es relativamente independiente de los factores analizados.

El burnout es un problema de salud de repercusiones mundiales, es también, un factor de riesgo laboral de acuerdo con la Organización Mundial de la Salud, que afecta la calidad de vida, salud mental y puede poner en riesgo la integridad personal. Las personas que lo padecen tienen pocas habilidades para afrontar el estrés, provocando agotamiento emocional, despersonalización y disminución del desempeño personal. La metodología utilizada en este estudio es de tipo descriptivo y explicativo, se aborda la problemática del burnout en trabajadores de la mina Bella Rica del cantón Ponce Enríquez-Azuay, a partir de la aplicación del Inventario de burnout de Maslach (MBI) y de una ficha socioeconómica en una muestra por conveniencia en 30 trabajadores mineros, los datos obtenidos nos permiten señalar que el 100% de los participantes no han alcanzado la realización personal, y 83% presenta agotamiento emocional y despersonalización, entre los factores psicosociales identificados se encontró el rango de edad promedio 25-30 años que representó el 36.67%, los participantes masculinos 83.33% y los femeninos 16.67%, educación mayoritariamente secundaria (46.7%), el estado civil unión libre 43.3% y el tipo de empleo contrato indefinido en el 60% de la muestra, en términos generales se concluyó que existen factores de riesgo en los trabajadores mineros y el nivel de afectación medio repercute en su salud mental y desempeño laboral.

Most of the tools and diagnosis models of Masticatory Efficiency (ME) are not well documented or severely limited to simple image processing approaches. This study presents a novel expert system for ME assessment based on automatic recognition of mixture patterns of masticated two-coloured chewing gums using a combination of computational intelligence and image processing techniques. The hypotheses tested were that the proposed system could accurately relate specimens to the number of chewing cycles, and that it could identify differences between the mixture patterns of edentulous individuals prior and after complete denture treatment. This study enrolled 80 fully-dentate adults (41 females and 39 males, 25 ± 5 years of age) as the reference population; and 40 edentulous adults (21 females and 19 males, 72 ± 8.9 years of age) for the testing group. The system was calibrated using the features extracted from 400 samples covering 0, 10, 15, and 20 chewing cycles. The calibrated system was used to automatically analyse and classify a set of 160 specimens retrieved from individuals in the testing group in two appointments. The ME was then computed as the predicted number of chewing strokes that a healthy reference individual would need to achieve a similar degree of mixture measured against the real number of cycles applied to the specimen. The trained classifier obtained a Mathews Correlation Coefficient score of 0.97. ME measurements showed almost perfect agreement considering pre- and post-treatment appointments separately (κ ≥ 0.95). Wilcoxon signed-rank test showed that a complete denture treatment for edentulous patients elicited a statistically significant increase in the ME measurements (Z = -2.31, p < 0.01). We conclude that the proposed expert system proved able and reliable to accurately identify patterns in mixture and provided useful ME measurements. ; This work was funded by the Secretaria Nacional de Educación, Ciencia y Teconología (SENESCYT) of the Government of Ecuador, with budget allocation No. 0099-SPP, http://www.educacionsuperior.gob.ec.

COVID-19 has changed our lives forever. The world we knew until now has been transformed and nowadays we live in a completely new scenario in a perpetual restructuring transition, in which the way we live, relate, and communicate with others has been altered permanently. Within this context, risk communication is playing a decisive role when informing, transmitting, and channeling the flow of information in society. COVID-19 has posed a real pandemic risk management challenge in terms of impact, preparedness, response, and mitigation by governments, health organizations, non-governmental organizations (NGOs), mass media, and stakeholders. In this study, we monitored the digital ecosystems during March and April 2020, and we obtained a sample of 106,261 communications through the analysis of APIs and Web Scraping techniques. This study examines how social media has affected risk communication in uncertain contexts and its impact on the emotions and sentiments derived from the semantic analysis in Spanish society during the COVID-19 pandemic.

The reactivation of very large landslides may cause severe damage to society. Its prevention and management requires detailed information on the geometry and structure of these landslides, but the use of standard techniques (boreholes) may be prohibitive from an economic point of view. To overcome these difficulties, geophysical techniques are of special interest because they allow for studying very large areas at a reasonable cost. In this paper, we present a case study wherein the analysis of ambient noise allowed us to produce a model of a large landslide near Granada (southern Spain). The geometry and location of the failure zone, as well as the assessment of the state of involved materials, were estimated by combining two available boreholes and different geophysical techniques (downhole tests and the spectral analysis of ambient noise, horizontal to vertical spectral ratios (HVSR) and the frequency-wavenumber (f-k) methods). The results have allowed us to differentiate between values within the landslide mass with respect to those of stable materials, and to perform for the first time a comprehensive geological model of this unstable mass. Differences were also observed within the landslide mass (earth flow vs. slide zones), which are attributed to differences in the degree of alteration and the disturbance of the internal structure of materials constituting the landslide mass. These results show that techniques based on the measurement of ambient noise are of special interest for studying very large, highly remolded landslide masses ; This study was funded by the EU (FEDER), by the Secretaría de Estado de Investigación, Desarrollo e Innovación of the Spanish government (projects CGL2015-65602-R and CGL2016-77688- R), by the Junta de Andalucía (project GGI3002IDIN), the Programa Operativo FEDER Andalucía 2014-2020-call made by the University of Jaén 2018, and by Research Groups VIGROB-184 and VIGROB-116 (University of Alicante)