Geostatistical Data Fusion Estimation Methods of Ambient PM2.5 and Polycyclic Aromatic Hydrocarbons

Fine Particulate Matter (PM2.5) is a complex air pollutant associated with a host of adverse health effects. In epidemiologic studies there is a need to accurately predict exposures to reduce misclassification. Recently there has been a surge in data fusion methods which combine observed data with gridded modeled data like the regulatory Community Multiscale Air Quality (CMAQ) model. Substantial resources are allocated to the evaluation of CMAQ. However, this model has inherent error and uncertainty. Currently, CMAQ can only be operationally evaluated at locations where observed data exist, leaving potentially large spatial and temporal gaps in a given modeling domain. This study develops a framework for evaluating gridded air quality modeled data that can then be corrected for systematic error and combined with observed data in a geostatistical framework. First, this dissertation develops the novel Regionalized Air quality Model Performance (RAMP) method that performs a non-homogenous, non-linear, non-homoscedastic model evaluation at each CMAQ grid for a well-documented 2001 regulatory episode across the continental United States. The RAMP method comparatively outperforms other model evaluation methods with a 22.1% reduction in Mean Square Error (MSE). Secondly, the RAMP corrected CMAQ modeled data are combined with observed data in the modern Bayesian Maximum Entropy (BME) geostatistical framework which combines the accuracy of observed data with the spatial and temporal coverage of gridded modeled data. RAMP BME resulted in a 6-7 times increase in spatial refinement compared to using kriging alone. Lastly, the data rich PM2.5 environment is contrasted with the data poor environment of Polycyclic Aromatic Hydrocarbons (PAHs). The Mass Fraction (MF) BME method is developed through a relatively small number of paired PM2.5 and PAH values and is applied to PM2.5 observed locations where PAH have not been observed to create the first detailed spatial maps of PAH across North Carolina in 2005. The MF BME method reduces MSE by over 39% compared with using kriging alone. Accurate assessment of ambient air pollutants is essential in public health to explore and elucidate true underlying relationships between pollutants and health endpoints.Doctor of Philosoph

Global land use regression and Bayesian Maximum Entropy spatiotemporal estimation of PM2.5 yearly average concentrations across the United States

Knowledge of PM2.5 concentrations across the United States is limited due to sparse monitoring across space and time. This work incorporates a land use regression (LUR) mean trend into the Bayesian Maximum Entropy (BME) framework along with Gaussian-truncated soft data that accounts for sampling incompleteness to provide estimations in the contiguous United States from 1999 to 2009. The LUR model was optimized to explain the most variability as possible given variable hyperparameters. Variables in the final model included elevation, average car miles driven, average traffic through-put, population density, SO2 point source emissions, and NH3 point source emissions. Compared to a kriging method with a constant mean trend this method showed a mean squared error reduction of over 35%. This is one of the few works to successfully develop a LUR model on a domain of this magnitude across space and time and incorporate the BME estimation methodology

Satisfacción con la vida y calidad de vida laboral

Busca conocer cuál es la relación que existe entre la Satisfacción con la Vida (SCV) y Calidad de Vida Laboral (CVL) que tienen los docentes de instituciones educativas estatales de Lima Metropolitana de la UGEL N°3. Se habla de profesores puesto que es la mayor masa trabajadora del país y si ellos no poseen una buena calidad de vida laboral no se encontraran satisfechos con su vida y por ende la calidad de vida en el país no es la adecuada para lograr una óptima vivencia. Se ha elaborado un instrumento para medir la Calidad de Vida Laboral (CVL). Encuentra que si existe una relación entre SCV y CVL de los docentes, esta es significativa y ligeramente moderada con tendencia negativa, además se analiza cada uno de sus componentes, esto como base para que sirvan de sustento para implementar mejoras en las políticas de recursos humanos del Ministerio de Educación peruano.Tesi

Regionalized PM2.5 Community Multiscale Air Quality model performance evaluation across a continuous spatiotemporal domain

The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error

An LUR/BME Framework to Estimate PM 2.5 Explained by on Road Mobile and Stationary Sources

Knowledge of particulate matter concentrations <2.5 μm in diameter (PM2.5) across the United States is limited due to sparse monitoring across space and time. Epidemiological studies need accurate exposure estimates in order to properly investigate potential morbidity and mortality. Previous works have used geostatistics and land use regression (LUR) separately to quantify exposure. This work combines both methods by incorporating a large area variability LUR model that accounts for on road mobile emissions and stationary source emissions along with data that take into account incompleteness of PM2.5 monitors into the modern geostatistical Bayesian Maximum Entropy (BME) framework to estimate PM2.5 across the United States from 1999 to 2009. A cross-validation was done to determine the improvement of the estimate due to the LUR incorporation into BME. These results were applied to known diseases to determine predicted mortality coming from total PM2.5 as well as PM2.5 explained by major contributing sources. This method showed a mean squared error reduction of over 21.89% oversimple kriging. PM2.5 explained by on road mobile emissions and stationary emissions contributed to nearly 568 090 and 306 316 deaths, respectively, across the United States from 1999 to 2007

Factors Affecting Entrepreneurial Intention and Behavior among the Indigenous Farming Community in Bun-ayan, Sabangan, Mountain Province, Philippines

With the shift of direction of the Philippine economy towards being an agribusiness-driven sector from agricultural farming, the indigenous peoples were encouraged to engage in entrepreneurship that would improve their socioeconomic status and bring development to their communities. The study assessed the factors affecting the entrepreneurial intention and behavior among the indigenous farmers in Bun-ayan, Sabangan, Mountain Province, by means of analyzing the entrepreneurial indicators and predictors through correlation and multiple regression analysis among 74 indigenous farmers. Among all the entrepreneurship predictors in this research, age, educational attainment, years in farming, the occupation of the father and mother, entrepreneurial inclination, entrepreneurial role model, entrepreneurial education, personal attitude, subjective norm, and perceived behavioral control were significantly related to entrepreneurial intention. Among the significant variables extracted from the correlation analysis, the factors affecting entrepreneurial intention and behavior are age, father’s occupation, and entrepreneurial inclination. Furthermore, this study conclude that sociodemographic factors and entrepreneurial inclination are enough to determine the intention of the indigenous farmers to engage themselves in entrepreneurial activities for the theory of planned behavior becomes insignificant when other predictors are incorporated with it. Thus, though there is evidence of a high level of entrepreneurial intentions among the indigenous farming community, challenges pertinent to culture preservation vis-à-vis its capacity to translate such intention into entrepreneurial behavior need to be addressed

Assessing Medical Student’s Ability to Interpret Traumatic Injuries on Computed Tomography Before and After the Third Year Clerkships

Introduction. Exposure to radiologic images during clinical rotationsmay improve students’ skill levels. This study aimed to quantifythe improvement in radiographic interpretation of life-threateningtraumatic injuries gained during third year clinical clerkships (MS-3). Methods. We used a paired-sample prospective study design tocompare students’ accuracy in reading computed tomography (CT)images at the beginning of their third year clerkships (Phase I) andagain after completion of all of their third year clerkships (Phase II).Students were shown life-threatening injuries that included head,chest, abdomen, and pelvic injuries. Overall scores for Phase II werecompared with Phase I, as well as sub-scores for each anatomicalregion: head, chest, abdomen, and pelvis. Results. Only scores from students participating in both Phase Iand Phase II (N = 57) were used in the analysis. After completingtheir MS3 clerkship, students scored significantly better overall andin every anatomical region. Phase I and Phase II overall mean scoreswere 1.2 ± 1.1 vs. 4.6 ± 1.8 (p &lt; 0.001). Students improved the mostwith respect to injuries of the head and chest and the area of leastimprovement was in interpreting CT scans of the abdomen. Althoughimprovements in reading radiographic images were noted after theclerkship year, students accurately diagnosed only 46% of life-threateningimages on CT scan in the trauma setting. Conclusions. These results indicated that enhanced education isneeded for medical students to interpret CT scans.Kans J Med 2018;11(4):91-94

Satisfaction of an employee in a sports entity: design and validation of a measurement scale

This research aims to generate validation and reliability of an instrument to measure employee satisfaction in a sports entity, comprising 28 items in six factors, using a Lickert type measure. The sample comprises n = 187 employees of the State Sports Commission of Sonora, Mexico, with 75.4% men and 24.6% women, between the ages of 18 to 56 years, grouping the different ages of workers in five groups (18 to 25 years, 26 to 35 years, 36 to 45 years, 46 to 55 years and > 56 years. Carrying out the exploratory factor analysis (AFE) and confirmatory factor analysis (AFC). Satisfactory values were obtained, resulting in Kaiser-Meyer-Olkin values of .91, and the Bartlett test was statistically significant with a value (χ² = 3296.01, gl = 378; p <. 001), six factors were extracted with eigen values greater than 1 and that together explain 69.08% of the total variance. the indices of the model in the confirmatory factor analysis were satisfactory: χ2 / df = 1.29, NNFI = .99, CFI = .99, and RMSEA = .03., The results of internal consistency using Cronbach's alpha index with values in this case greater than .70, composite reliability (CR) with values between .88 and .94, and the average variance index extracted (AVE), meanwhile, alsoshowed adequate values, in a range between .60 and .83. It is considered that the survey of employee satisfaction was statistically validated, obtaining psychometric guarantees and thereby providing a tool for the evaluation of the subject, accrediting it as useful for research, being able to be used by professionals, managers and those responsible within the different organizations

“On the shoulders of giants” the history of women and men in Physics as a teaching innovation in Engineering degrees

This paper describes the results of the teaching innovation project. It was putting into practice at the School of Engineering of the University of Cádiz during the academic year 2016/2017. It was called "If I have seen further it is because I am sitting on the shoulders of giants. A little history of Women and Men in the history of Science and Engineering in the classrooms of the Higher School of Engineering". The main objective of the project was to inform the students of the first year of the Degrees of Electricity, Industrial Electronics, Industrial Technology, Aerospace, about the biographies and the contributions of some of the "giants" of the Physics and Engineering. It supposed a recovery of the History of the Physics in the teaching in the Degrees of Engineering. Moreover, we have tried to make visible some of these researches, especially, the feminine scientists. The realization of this project has increased the motivation of the students for the learning of physics. Knowing the biographies, contributions, successes and failures of great scientists, predisposes students to understand more complex concepts and, at the same time, taking those giants as a source of inspiration