A Phenomenological Exploration of Black Male Law Enforcement Officers' Perspectives of Racial Profiling and Their Law Enforcement Career Exploration and Commitment

This phenomenological study explored Black male law enforcement officers’ perspectives of how racial profiling shaped their decisions to explore and commit to a law enforcement career. Criterion and snow ball sampling was used to obtain the 17 participants for this study. Super’s (1990) archway model was used as the theoretical framework. The archway model “is designed to bring out the segmented but unified and developmental nature of career development, to highlight the segments, and to make their origin clear” (Super, 1990, p. 201). Interview data were analyzed using inductive, deductive, and comparative analyses. Three themes emerged from the inductive analysis of the data: (a) color and/or race does matter, (b) putting on the badge, and (c) too black to be blue and too blue to be black. The deductive analysis used a priori coding that was based on Super’s (1990) archway model. The deductive analysis revealed the participants’ career exploration was influenced by their knowledge of racial profiling and how others view them. The comparative analysis between the inductive themes and deductive findings found the theme “color and/or race does matter” was present in the relationships between and within all segments of Super’s (1990) model. The comparative analysis also revealed an expanded notion of self-concept for Black males – marginalized and/or oppressed individuals. Self-concepts, “such as self-efficacy, self-esteem, and role self-concepts, being combinations of traits ascribed to oneself” (Super, 1990, p. 202) do not completely address the self-concept of marginalized and/or oppressed individuals. The self-concept of marginalized and/or oppressed individuals is self-efficacy, self-esteem, traits ascribed to oneself expanded by their awareness of how others view them. (DuBois, 1995; Freire, 1970; Sheared, 1990; Super, 1990; Young, 1990). Ultimately, self-concept is utilized to make career and life decisions. Current human resource policies and practices do not take into consideration that negative police contact could be the result of racial profiling. Current human resource hiring guidelines penalize individuals who have had negative police contact. Therefore, racial profiling is a discriminatory act that can effectively circumvent U.S. Equal Employment Opportunities Commission laws and serve as a boundary mechanism to employment (Rocco & Gallagher, 2004).

Clustering of Rab11 vesicles in influenza A virus infected cells creates hotspots containing the 8 viral ribonucleoproteins

Influenza A virus is an important human pathogen causative of yearly epidemics and occasional pandemics. The ability to replicate within the host cell is a determinant of virulence, amplifying viral numbers for host-to-host transmission. This process requires multiple rounds of entering permissive cells, replication, and virion assembly at the plasma membrane, the site of viral budding and release. The assembly of influenza A virus involves packaging of several viral (and host) proteins and of a segmented genome, composed of 8 distinct RNAs in the form of viral ribonucleoproteins (vRNPs). The selective assembly of the 8-segment core remains one of the most interesting unresolved problems in virology. The recycling endosome regulatory GTPase Rab11 was shown to contribute to the process, by transporting vRNPs to the periphery, giving rise to enlarged cytosolic puncta rich in Rab11 and the 8 vRNPs. We recently reported that vRNP hotspots were formed of clustered vesicles harbouring protruding electron-dense structures that resembled vRNPs. Mechanistically, vRNP hotspots were formed as vRNPs outcompeted the cognate effectors of Rab11, the Rab11-Family-Interacting-Proteins (FIPs) for binding, and as a consequence impair recycling sorting at an unknown step. Here, we speculate on the impact that such impairment might have in host immunity, membrane architecture and viral assembly.

Software for Designing Custom Orbital-Craniofacial Implant Plans

Purpose: Custom cranio-orbital implants have been shown to achieve better performance than their hand-shaped counterparts by restoring skull anatomy more accurately and by reducing surgery time. Designing a custom implant involves reconstructing a model of the patient's skull using their computed tomography (CT) scan. The healthy side of the skull model, contralateral to the damaged region, can then be used to design an implant plan. Designing implants for areas of thin bone, such as the orbits, is challenging due to poor CT resolution of bone structures. This makes preoperative design time-intensive since thin bone structures in CT data must be manually segmented. The objective of this thesis was to research methods to accurately and efficiently design cranio-orbital implant plans, with a focus on the orbits, and to develop software that integrates these methods. Methods: The software consists of modules that use image and surface restoration approaches to enhance both the quality of CT data and the reconstructed model. It enables users to input CT data, and use tools to output a skull model with restored anatomy. The skull model can then be used to design the implant plan. The software was designed using 3D Slicer, an open-source medical visualization platform. It was tested on CT data from thirteen patients. Results: The average time it took to create a skull model with restored anatomy using our software was 0.33 hours ± 0.04 STD. In comparison, the design time of the manual segmentation method took between 3 and 6 hours. To assess the structural accuracy of the reconstructed models, CT data from the thirteen patients was used to compare the models created using our software with those using the manual method. When registering the skull models together, the difference between each set of skulls was found to be 0.4 mm ± 0.16 STD. Conclusions: We have developed a software to design custom cranio-orbital implant plans, with a focus on thin bone structures. The method described decreases design time, and is of similar accuracy to the manual method.

The effect of a Computerised Decision Support System (CDSS) on compliance with the prehospital assessment process: results of an interrupted time-series study

BACKGROUND: Errors in the decision-making process are probably the main threat to patient safety in the prehospital setting. The reason can be the change of focus in prehospital care from the traditional "scoop and run" practice to a more complex assessment and this new focus imposes real demands on clinical judgment. The use of Clinical Guidelines (CG) is a common strategy for cognitively supporting the prehospital providers. However, there are studies that suggest that the compliance with CG in some cases is low in the prehospital setting. One possible way to increase compliance with guidelines could be to introduce guidelines in a Computerized Decision Support System (CDSS). There is limited evidence relating to the effect of CDSS in a prehospital setting. The present study aimed to evaluate the effect of CDSS on compliance with the basic assessment process described in the prehospital CG and the effect of On Scene Time (OST). METHODS: In this time-series study, data from prehospital medical records were collected on a weekly basis during the study period. Medical records were rated with the guidance of a rating protocol and data on OST were collected. The difference between baseline and the intervention period was assessed by a segmented regression. RESULTS: In this study, 371 patients were included. Compliance with the assessment process described in the prehospital CG was stable during the baseline period. Following the introduction of the CDSS, compliance rose significantly. The post-intervention slope was stable. The CDSS had no significant effect on OST. CONCLUSIONS: The use of CDSS in prehospital care has the ability to increase compliance with the assessment process of patients with a medical emergency. This study was unable to demonstrate any effects of OST.

Diferencias regionales en las estructuras de ingresos laborales en Colombia

Dada la persistencia de las diferencias en ingresos laborales por regiones en Colombia, el presente artículo propone cuantificar la magnitud de este diferencial que es atribuida a la diferencia en estructuras de mercado laboral, entendiendo esta última como la diferencia en los retornos a las características de la fuerza laboral. Para ello se propone el uso de un método de descomposición del tipo Oaxaca- Blinder y se compara a Bogotá –la ciudad con mayores ingresos laborales- con otras ciudades principales. Los resultados obtenidos al conducir el ejercicio de descomposición muestran que las diferencias en estructura están a favor de Bogotá y que estas explican más de la mitad de la diferencia total, indicando que si se quieren reducir las disparidades de ingresos laborales entre ciudades no es suficiente con calificar la fuerza laboral y que es necesario indagar por las causas que hacen que los retornos a las características difieran entre ciudades.

Evaluación de la exposición laboral a sílice en empresas de diferentes sectores económicos en Colombia

Introducción: La sílice es un elemento de fácil aprovechamiento y por sus características fisicoquímicas ha sido ampliamente empleado en la industria como objetivo, materia prima o subproducto que genera silicosis en los trabajadores que han estado expuestos a polvo de sílice a través de los años y es una enfermedad que progresa incluso cuando la exposición cesa. La silicosis es conocida como una enfermedad de alta e histórica incidencia y prevalencia a nivel mundial, por lo que es necesario evaluar la exposición laboral a sílice (fracción respirable) en empresas pertenecientes a diferentes sectores económicos que están afiliadas una ARL en Colombia, para contribuir con información diagnóstica actualizada en diferentes regiones y en variadas actividades económicas. Objetivos: Evaluar la exposición laboral a sílice y el nivel de riesgo en empresas afiliadas a una ARL de acuerdo con su ubicación geográfica, actividad económica, área de trabajo, cargo y relacionar las medidas de control empleadas en cada empresa. Materiales y métodos: Se llevó a cabo un estudio de corte transversal sobre 239 mediciones de higiene industrial de 159 empresas de diferentes actividades través de la asociación de variables ocupacionales con las características de la exposición a sílice. Las variables cuantitativas fueron calculadas empleando medidas de tendencia central como media y mediana y medidas de dispersión como rango y desviación estándar con sus correspondientes coeficientes de variación. El nivel máximo permisible o TLV establecido de acuerdo con los parámetros señalados por la Conferencia Americana de Higienistas Industriales Gubernamentales (ACGIH en inglés) y empleado en este estudio para sílice cristalina, fue de 0,025 mg/m3. Resultados: Las actividades económicas que reportaron las mayores concentraciones corregidas a condiciones estándar de polvo de sílice fueron: la minería y actividades Extractivas con 6,340 mg/m3, el mantenimiento industrial, montajes electromecánicos y civiles con 1,312 mg/m3, la maquinaria, metalmecánica, electrodomésticos y equipos con 0,096 mg/m3 y la construcción con 0,702 mg/m3; Discusión: Se realizó un análisis segmentado en dos grupos A y B de acuerdo con el tiempo de medición, se encontró que para el índice de riesgo en ambos grupos indican una sobre-exposición de los trabajadores a niveles críticos, razón por la cual es necesario generar una estrategia de intervención que permita disminuir a tiempo las concentraciones de sílice en las áreas de trabajo y así reducir la exposición de los trabajadores.

Viabilidad Hotel Bosques de Araguaney

El Hotel Bosques de Araguaney es un proyecto de largo plazo que busca promover y consolidar el desarrollo de la región de Puerto Gaitán y del Meta, gracias a las grandes rentas que se han generado en la región por motivo de su riqueza en recursos naturales. Como su nombre lo indica este proyecto se encuentra segmentado en la prestación de servicios de alojamiento, conteniendo otros servicios como la prestación de servicios de restaurante.

Analysis of Pancreas Histological Images for Glucose Intolerance Identification using Wavelet Decomposition

Subtle structural differencescan be observed in the islets of Langer-hans region of microscopic image of pancreas cell of the rats having normal glucose tolerance and the rats having pre-diabetic(glucose intolerant)situa-tions. This paper proposes a way to automatically segment the islets of Langer-hans region fromthe histological image of rat's pancreas cell and on the basis of some morphological feature extracted from the segmented region the images are classified as normal and pre-diabetic.The experiment is done on a set of 134 images of which 56 are of normal type and the rests 78 are of pre-diabetictype. The work has two stages: primarily,segmentationof theregion of interest (roi)i.e. islets of Langerhansfrom the pancreatic cell and secondly, the extrac-tion of the morphological featuresfrom the region of interest for classification. Wavelet analysis and connected component analysis method have been used for automatic segmentationof the images. A few classifiers like OneRule, Naïve Bayes, MLP, J48 Tree, SVM etc.are used for evaluation among which MLP performed the best.

Carbon sequestration associated to the land-use and land-cover changes in the forestry sector in Southern Brazil.

We studied the Paraíba do Sul river watershed , São Paulo state (PSWSP), Southeastern Brazil, in order to assess the land use and cover (LULC) and their implication s to the amount of carbon (C) stored in the forest cover between the years 1985 and 2015. Th e region covers a n area of 1,395,975 ha . We used images made by the Operational Land Imager (OLI) sensor (OLI/Landsat - 8) to produce mappings , and image segmentation techniques to produce vectors with homogeneous characteristics. The training samples and the samples used for classification and validation were collected from the segmented image. To quantify the C stocked in aboveground live biomass (AGLB) , we used an indirect method and applied literature - based reference values. The recovery of 205,690 ha of a secondary Native Forest (NF) after 1985 sequestered 9.7 Tg (Teragram) of C . Considering the whole NF area (455,232 ha), the amount of C accumulated al ong the whole watershed was 3 5 .5 Tg , and the whole Eucalyptus crop (EU) area (113,600 ha) sequester ed 4. 4 Tg of C. Thus, the total amount of C sequestered in the whole watershed (NF + EU) was 3 9 . 9 Tg of C or 1 45 . 6 Tg of CO 2 , and the NF areas were responsible for the large st C stock at the watershed (8 9 %). Therefore , the increase of the NF cover contribut es positively to the reduction of CO 2 concentration in the atmosphere, and Reducing Emissions from Deforestation and Forest Degradation (REDD + ) may become one of the most promising compensation mechanisms for the farmers who increased forest cover at their farms.

Neural states in parietal areas during arm reaching

Since the first subdivisions of the brain into macro regions, it has always been thought a priori that, given the heterogeneity of neurons, different areas host specific functions and process unique information in order to generate a behaviour. Moreover, the various sensory inputs coming from different sources (eye, skin, proprioception) flow from one macro area to another, being constantly computed and updated. Therefore, especially for non-contiguous cortical areas, it is not expected to find the same information. From this point of view, it would be inconceivable that the motor and the parietal cortices, diversified by the information encoded and by the anatomical position in the brain, could show very similar neural dynamics. With the present thesis, by analyzing the population activity of parietal areas V6A and PEc with machine learning methods, we argue that a simplified view of the brain organization do not reflect the actual neural processes. We reliably detected a number of neural states that were tightly linked to distinct periods of the task sequence, i.e. the planning and execution of movement and the holding of target as already observed in motor cortices. The states before and after the movement could be further segmented into two states related to different stages of movement planning and arm posture processing. Rather unexpectedly, we found that activity during the movement could be parsed into two states of equal duration temporally linked to the acceleration and deceleration phases of the arm. Our findings suggest that, at least during arm reaching in 3D space, the posterior parietal cortex (PPC) shows low-level population neural dynamics remarkably similar to those found in the motor cortices. In addition, the present findings suggest that computational processes in PPC could be better understood if studied using a dynamical system approach rather than studying a mosaic of single units.

Analytical pyrolysis to study microplastics and other polymers in the environment

Synthetic polymers constitute a wide class of materials which has enhanced the quality of human life, providing comforts and innovations. Anyway, the increasing production and the incorrect waste management, are leading to the occurrence of polymers in the environment, generating concern. To understand the extent of this issue, analytical investigation holds an essential position. Standardised methods have not established yet, and additional studies are required to improve the present knowledge. The main aim of this thesis was to provide comprehensive information about the potential of pyrolysis coupled with gas-chromatography and mass spectrometry (Py-GC-MS) for polymers investigation, from their characterisation to their identification and quantification in complex matrices. Water-soluble (poly(dimethylsiloxanes), PDMS bearing poly(ethylene glycol), PEG, side chains) and water-insoluble polymers (microplastics, MPs, and bioplastics) were studied. The different studies revealed the possibility to identify heterogeneous classes of polymers, fingerprinting the presence of PDMS copolymers and distinguishing chemically different polyurethanes (PURs). The occurrence of secondary reactions in pyrolysis of polymer mixtures was observed as possible drawback. Pyrolysis products indicative of secondary reactions and their reaction mechanisms were identified. Py-GC-MS also revealed its fundamental role for the identification of polymers composing commercial bioplastics items based. The results aided to identify chemicals that have the potential to migrate in sea waters. Investigations of environmental samples demonstrated the capability of Py-GC-MS to provide reliable, reproducible and comparable results about polymers in complex matrices (PEG-PDMS in sewage sludges and PURs and other MPs in road dusts and spider webs). Criticisms were especially found in quantitation, such as the retrieval reference materials, the construction of reliable calibration protocols and the occurrence of bias due to interferences between pyrolysis products. This thesis pursues the greater purpose to develop harmonised and standardised methods for environmental investigations of polymers, that is fundamental to assess the real state of the environment.

Developing a radiomic based machine learning model to identify patients with resected non-small-cell lung cancer at high risk of relapse

Background There is a wide variation of recurrence risk of Non-small-cell lung cancer (NSCLC) within the same Tumor Node Metastasis (TNM) stage, suggesting that other parameters are involved in determining this probability. Radiomics allows extraction of quantitative information from images that can be used for clinical purposes. The primary objective of this study is to develop a radiomic prognostic model that predicts a 3 year disease free-survival (DFS) of resected Early Stage (ES) NSCLC patients. Material and Methods 56 pre-surgery non contrast Computed Tomography (CT) scans were retrieved from the PACS of our institution and anonymized. Then they were automatically segmented with an open access deep learning pipeline and reviewed by an experienced radiologist to obtain 3D masks of the NSCLC. Images and masks underwent to resampling normalization and discretization. From the masks hundreds Radiomic Features (RF) were extracted using Py-Radiomics. Hence, RF were reduced to select the most representative features. The remaining RF were used in combination with Clinical parameters to build a DFS prediction model using Leave-one-out cross-validation (LOOCV) with Random Forest. Results and Conclusion A poor agreement between the radiologist and the automatic segmentation algorithm (DICE score of 0.37) was found. Therefore, another experienced radiologist manually segmented the lesions and only stable and reproducible RF were kept. 50 RF demonstrated a high correlation with the DFS but only one was confirmed when clinicopathological covariates were added: Busyness a Neighbouring Gray Tone Difference Matrix (HR 9.610). 16 clinical variables (which comprised TNM) were used to build the LOOCV model demonstrating a higher Area Under the Curve (AUC) when RF were included in the analysis (0.67 vs 0.60) but the difference was not statistically significant (p=0,5147).