Artificial intelligence assisted Mid-infrared laser spectroscopy in situ detection of petroleum in soils

A simple, remote-sensed method of detection of traces of petroleum in soil combining artificial intelligence (AI) with mid-infrared (MIR) laser spectroscopy is presented. A portable MIR quantum cascade laser (QCL) was used as an excitation source, making the technique amenable to field applications. The MIR spectral region is more informative and useful than the near IR region for the detection of pollutants in soil. Remote sensing, coupled with a support vector machine (SVM) algorithm, was used to accurately identify the presence/absence of traces of petroleum in soil mixtures. Chemometrics tools such as principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA), and SVM demonstrated the e ectiveness of rapidly di erentiating between di erent soil types and detecting the presence of petroleum traces in di erent soil matrices such as sea sand, red soil, and brown soil. Comparisons between results of PLS-DA and SVM were based on sensitivity, selectivity, and areas under receiver-operator curves (ROC). An innovative statistical analysis method of calculating limits of detection (LOD) and limits of decision (LD) from fits of the probability of detection was developed. Results for QCL/PLS-DA models achieved LOD and LD of 0.2% and 0.01% for petroleum/soil, respectively. The superior performance of QCL/SVM models improved these values to 0.04% and 0.003%, respectively, providing better identification probability of soils contaminated with petroleum

Mid-Infrared laser spectroscopy detection and quantification of explosives in soils using multivariate analysis and artificial intelligence

A tunable quantum cascade laser (QCL) spectrometer was used to develop methods for detecting and quantifying high explosives (HE) in soil based on multivariate analysis (MVA) and artificial intelligence (AI). For quantification, mixes of 2,4-dinitrotoluene (DNT) of concentrations from 0% to 20% w/w with soil samples were investigated. Three types of soils, bentonite, synthetic soil, and natural soil, were used. A partial least squares (PLS) regression model was generated for predicting DNT concentrations. To increase the selectivity, the model was trained and evaluated using additional analytes as interferences, including other HEs such as pentaerythritol tetranitrate (PETN), trinitrotoluene (TNT), cyclotrimethylenetrinitramine (RDX), and non-explosives such as benzoic acid and ibuprofen. For the detection experiments, mixes of different explosives with soils were used to implement two AI strategies. In the first strategy, the spectra of the samples were compared with spectra of soils stored in a database to identify the most similar soils based on QCL spectroscopy. Next, a preprocessing based on classical least squares (Pre-CLS) was applied to the spectra of soils selected from the database. The parameter obtained based on the sum of the weights of Pre-CLS was used to generate a simple binary discrimination model for distinguishing between contaminated and uncontaminated soils, achieving an accuracy of 0.877. In the second AI strategy, the same parameter was added to a principal component matrix obtained from spectral data of samples and used to generate multi-classification models based on different machine learning algorithms. A random forest model worked best with 0.996 accuracy and allowing to distinguish between soils contaminated with DNT, TNT, or RDX and uncontaminated soils

Characterization of a winter upwelling event in the Northern Galician Rias

II International Symposium in Marine Sciences = II Simposio internacional de Ciencias del Mar, Vigo, 27-30 abril 2009N

Colombian consensus recommendations for diagnosis, management and treatment of the infection by SARS-COV-2/ COVID-19 in health care facilities - Recommendations from expert´s group based and informed on evidence

La Asociación Colombiana de Infectología (ACIN) y el Instituto de Evaluación de Nuevas Tecnologías de la Salud (IETS) conformó un grupo de trabajo para desarrollar recomendaciones informadas y basadas en evidencia, por consenso de expertos para la atención, diagnóstico y manejo de casos de Covid 19. Estas guías son dirigidas al personal de salud y buscar dar recomendaciones en los ámbitos de la atención en salud de los casos de Covid-19, en el contexto nacional de Colombia

Birds vs bricks: Patterns of species diversity in response to urbanization in a Neotropical Andean city.

Urbanization is currently one the most important causes of biodiversity loss. The Colombian Andes is a well-known hotspot for biodiversity, however, it also exhibit high levels of urbanization, making it a useful site to document how species assemblages respond to habitat transformation. To do this, we compared the structure and composition of bird assemblages between rural and urban habitats in Armenia, a medium sized city located in the Central Andes of Colombia. In addition, we examined the influence of urban characteristics on bird species diversity within the city of Armenia. From September 2016 to February 2017 we performed avian surveys in 76 cells (250 x 250 m each) embedded within Armenia city limits; and in 23 cells (250 x 250 m each) in rural areas around Armenia. We found that bird diversity was significantly lower in urban habitats than in rural habitats, and differed in species composition by 29%. In urban cells, with higher abiotic noise intensity and higher impervious surface area, we found lower bird diversity than that in urban cells with higher guadual (Guadua angustifolia patches), and forested surface areas. We did not find segregation of urban cells according to the species composition, although additional bird surveys inside urban forests remnant are needed to be more conclusive about this aspect. Altogether, our results highlight the importance of green areas embedded within cities to conserve bird diversity through reducing the ecological impact of urbanization on avian biodiversity

Diversidad biológica y cultural del sur de la Amazonia colombiana

La gran cuenca amazónica compartida por Brasil, Colombia, Perú, Bolivia, Venezuela, Ecuador y las tres Guyanas, contiene una de las mayores riquezas biológicas y culturales del planeta y es considerada parte de la seguridad ecológica global. Constituye el 45% de los bosques tropicales del mundo, es una de las áreas silvestres más extensas y de mayor reserva de agua dulce del planeta, su sistema hídrico es el mayor tributario de todos los océanos, alberga aún, cerca de 379 grupos étnicos y en cuanto a endemismo, no existe otra región que se le aproxime. En Colombia, la Amazonia a lo largo de la historia ha sufrido distintos procesos de intervención antrópica: la conquista; la colonización; el auge del caucho y la quina; la explotación maderera, petrolera; la implementación de cultivos de uso ilícito y de sistemas productivos no aptos a las condiciones del medio natural; entre otros, son procesos que han socavado tanto los recursos biológicos como los culturales. Conscientes de la problemática actual de la Amazonia así como de la importancia que reviste para el mundo y para el país, la Corporación para el Desarrollo Sostenible del Sur de la Amazonia –Corpoamazonia– y el Instituto de Investigación de Recursos Biológicos Alexander von Humboldt –IAvH-, firmaron en el año 2004 un convenio con el n de aunar esfuerzos para formular el plan de acción en biodiversidad en la región sur de la Amazonia colombiana (departamentos de Caquetá, Putumayo y Amazonas). El plan de acción, busca posicionar la biodiversidad en el desarrollo regional y contribuir a un mayor conocimiento y a unas mejores prácticas de conservación y utilización sostenible de los recursos biológicos y culturales de este importante espacio geográfico. Desarrolla a escala regional, la Política Nacional en Biodiversidad y la Propuesta Técnica de Plan de Acción Nacional en Biodiversidad – Biodiversidad siglo XXI -

Memorias IX Congreso Geológico Venezolano (1)

Memorias del IX Congreso Geológico Venezolan

Avances de la Investigación en Ingeniería

El texto está conformado por 31 capítulos, agrupados en 5 grandes áreas temáticas. En la primera parte se encuentran los trabajos relacionados con el tema de los Recursos Hidráulicos; en la segunda parte se tratan temas relacionados con la Planificación y Gestión del Territorio; la tercera parte está relacionada con el Manejo Integral de los Recursos Agua, Aire y Suelo; la cuarta parte incluye la Investigación Aplicada a la Ingeniería de Sistemas, y la última parte comprende la Investigación Aplicada a la Ingeniería Civil