10 research outputs found
Effect of light and activated charcoal on tracheary element differentiation in callus cultures of <em>Pinus radiata</em> D. Don.
No full textLight has been found to increase the proportion of tracheary elements differentiating in callus cultures derived from xylem-parenchyma of Pinus radiata D. Don grown on an induction medium containing activated charcoal but no phytohormones. The differentiation rate increased from 20% when callus was grown in darkness to 45% when callus was grown with a 16 h or 24 h photoperiod. When callus was grown with a 16 h photoperiod, tracheary elements were observed 2 days after transfer of callus to the induction medium, as compared to 5 days when callus was cultured in darkness. The differentiation rate was also influenced by the concentration of activated charcoal added to the induction medium, the optimum concentration being 5 g l(-1). Exclusion of activated charcoal from the induction medium decreased the differentiation rate to 2%. The activities of the lignin-related enzymes L-phenylalanine ammonia lyase and cinnamyl alcohol dehydrogenase were significantly higher in cell cultures grown with a 16 h photoperiod as compared to when grown in darkness. The results show that light had a stimulating effect on tracheary element differentiation and the activities of lignin-related enzymes in P. radiata callus cultures. The new growth conditions markedly improve this cell culture system and make it particularly useful for functional gene testing and cell-wall analysis of in vitro grown tracheary elements of coniferous gymnosperms
Development of very high rate and resolution neutron detectors with novel readout and DAQ hard- and software in DETNI
No full textn the Joint Research Activity DETNI (DETectors for Neutron Instrumentation) of the FP6 EU Integrated Infrastructure Initiative for Neutron Scattering and Muon Spectroscopy (NMI3) prototypes of three novel modular thermal neutron area detector types, based on thin solid neutron converters, were built and tested, which were developed for time- and wavelength resolved neutron detection with 2-D spatial and time resolutions of 50–1000 μm (FWHM) and of up to 2 ns, respectively, and for counting rates in the 107 – 108 cps range, i.e. for coping with the highest resolution and rate requirements at pulsed spallation neutron sources with MW average proton beam power like ESS. The detector types are (i) four-fold segmented modules of Silicon microstrip detectors (Si-MSD) with 157Gd converter layer between two double-sided Si sensors with 80 1⁄4m strip pitch, (ii) hybrid low-pressure microstrip gas chamber (MSGC) detectors with three-stage gas amplification and 2-D position-sensitive MSGC plates either side of a composite 157Gd/CsI converter, (iii) CASCADE detectors with cascaded 10B-coated GEM (Gas Electron Multiplier) foils either side of a 2-D position-sensitive readout electrode. For readout in DETNI prototypes of two novel, channel-wise self-triggered high-rate ASICs, of ADC-FPGA boards with Gigabit glass fiber readout and of the necessary data acquisition firmware and software have been developed. The ASICs, i.e. the 128-channel n-XYTER ASIC, optimized for the Si-MSD and strip hit rates of 200 khits/s, and the 32-channel MSGCROC ASIC for the MSGC with variable amplification and strip rates of 900 khits/s, deliver for each strip spatial and 4 (2) ns time stamp resolution, respectively, the latter e.g. for correlating x and y strips unambiguously, as well as analog amplitude resolution for center-of-gravity interpolation and gating. In this paper the current status of prototyping will be reported
The 10B based Jalousie neutron detector – An alternative for filled position sensitive counter tubes
No full textAbsolute efficiency measurements with the 10B based Jalousie detector
No full textThe 10B based Jalousie detector is a replacement for 3He counter tubes, which are not affordable any more for large area detectors due to the 3He crisis. In this paper we will show absolute detection efficiency measurements, conducted at the HEiDi instrument at the FRM II in Munich, which prove that the predicted efficiency can be achieved. This validates the detector concept and its adoption in the POWTEX instrument
Utilisation of Single Tooth Procedures to Establish the Cutting Mechanics of Woodworking Hand-saw Teeth
No full textThe work reported in this thesis details the original research undertaken by the author into the cutting mechanics of wood-working handsaw tooth geometries. The research can be separated into three distinctive sections. The first section is a review of both fundamental and recent literature regarding wood characteristics and machining processes. The second section documents the findings of a cutting process in which a variety of work-piece parameters were evaluated whilst limiting the parameters associated with tooth geometry. The third and final section documents the findings of a cutting process in which a variety of tooth geometry parameters were evaluated whilst limiting work-piece variation.
Two separate experimental procedures were developed to carry out the work for sections two and three respectively: The first of these procedures utilised a CNC router machine to perform the controlled cutting action. A single “rip” tooth was attached to the tool holder. The workpiece was constrained to a tri-axis dynamometer which was used to measure the resultant tool forces in the relative X, Y and Z axes. At the same time a universal testing machine was employed to perform mechanical test procedures on a variety of wood species. A predictive cutting force model was developed using the obtained mechanical properties as categorical predictors.
The second procedure utilised a shaper machine to perform the controlled cutting action. Three different saw tooth geometries were evaluated for only one variety of wood species. A tri-axis dynamometer was again used to measure the resultant tool forces. The geometric parameters of each tooth were carefully evaluated at using SEM micrographs. A predictive cutting force model using the geometric parameters as categorical predictors was developed.
Chip and surface formation was carefully evaluated. For procedure one this involved observation of the chip/surfaces under an optical microscope. For procedure two this involved capturing footage of the cutting process using a high speed camera.
The findings of the research show that un-bevelled teeth with orthogonal edges generally yield high cutting forces. However, these teeth are very effective at removing material along the wood grain in a “chisel like” cutting action. Bevelled teeth with sharp lateral edges generally yield low cutting forces. These teeth are well suited to severing the wood fibres perpendicular to the grain in a “knife like” cutting action
Development of Very High Rate and Resolution Neutron Detectors with Novel Readout and DAQ Hard and Software in DETNI
No full textAbiotic And Biotic Stresses And Changes In The Lignin Content And Composition In Plants
No full textLignin is a polymer of phenylpropanoid compounds formed through a complex biosynthesis route, represented by a metabolic grid for which most of the genes involved have been sequenced in several plants, mainly in the model-plants Arabidopsis thaliana and Populus. Plants are exposed to different stresses, which may change lignin content and composition. In many cases, particularly for plant-microbe interactions, this has been suggested as defence responses of plants to the stress. Thus, understanding how a stressor modulates expression of the genes related with lignin biosynthesis may allow us to develop study-models to increase our knowledge on the metabolic control of lignin deposition in the cell wall. 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Particulate Matter 10 μm (PM10), 2.5 μm (PM2.5) Datasets gathered by direct measurement, low-cost sensor and by public air quality stations in Fontibón, Bogotá D.C., Colombia
No full textConcentration of particulate matter directly affects air quality and human health. Three
sources of information were used in this work to generate datasets on this matter at the
Fontibon county in Bogota, Colombia. The first source was a Davis AirLink ® low-cost
sensor air quality readings for PM2.5, PM10 and meteorological variables. The sensor
was installed in the referred area, collecting air quality readings for PM2.5, PM10, as
well as temperature, relative humidity, dew point, wet bulb, and heat index as
meteorological variables during the months of May to August 2022. The second source
was collecting by direct measurement the PM10 particles using a Tisch ® Hi- Vol
equipment, evaluated the concentration of particulate matter PM10 in the same area
for 27 days. Finally, raw data was provided by the Bogotá’s Environmental District
Bureau (SDA), validating in this work the data readings for the years 2021 and 2022
from the two meteorological stations located in the same county, named Fontibon and
Movil Fontibon, including Air quality data for PM 2.5, PM 10, Carbon Monoxide (CO),
Ozone, Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2) and the meteorological variables
wind speed, wind direction, temperature, precipitation, relative humidity (RH) and
Barometric pressure.
A Machine Learning model was made to perform the mining and completeness of the
missing data with an iterative imputation and with a regression model, and the
Pearson, Spearman and Kendall correlation coefficients were calculated, using Python
languageUniversidad Libre - facultad de ingeniería - Maestría en ingeniería con énfasis en analítica de dato
Monitoreo de la contaminación del aire urbano utilizando dispositivos sensores de bajo costo
No full textIlustraciones, gráficas, tablasThe study of urban air pollution holds paramount significance within the realms of environmental science and public health. Urban areas are epicenters of diverse human activities, industrial operations, and vehicular traffic, collectively contributing to elevated concentrations of air pollutants. As the use of LCS devices becomes more prevalent in citizen science initiatives, educational purposes, rise of information and awareness, it is crucial to establish their performance characteristics and evaluation metrics for air pollution monitoring. This thesis focuses on evaluating the performance of Low-cost sensors (LCS) in the monitoring of PM2.5 concentrations in outdoor urban environments in Colombia using data mining and machine learning models. The results show that the polynomial regression and Artificial Neural Networks models present a better enhancing in the accuracy and precision of the measurements of the different models of LCS used in this study compared with simple linear regression and other machine learning models. Lastly, the project endeavors to demonstrate the applicability of LCS devices for monitoring PM2.5 concentration in various transportation modes within the city of Medellin. This research contributes to the broader understanding of LCS devices' potential in enhancing air quality monitoring and their suitability for citizen-driven initiatives in regions lacking regulatory-grade instruments.El estudio de la contaminación del aire urbano tiene una importancia fundamental en los ámbitos de la ciencia ambiental y la salud pública. Las áreas urbanas son epicentros de diversas actividades humanas, operaciones industriales y tráfico vehicular, contribuyendo colectivamente a concentraciones elevadas de contaminantes atmosféricos. A medida que el uso de dispositivos LCS se vuelve más frecuente en iniciativas de ciencia ciudadana, con fines educativos, aumento de información y conciencia, es crucial establecer sus características de rendimiento y métricas de evaluación para el monitoreo de la contaminación del aire. Esta tesis se centra en evaluar el rendimiento de los sensores de bajo costo (LCS) en el monitoreo de las concentraciones de PM2.5 en entornos urbanos al aire libre en Colombia mediante la minería de datos y modelos de aprendizaje automático. Los resultados muestran que los modelos de regresión polinómica y redes neuronales artificiales mejoran la precisión y la exactitud de las mediciones de los diferentes modelos de LCS utilizados en este estudio en comparación con la regresión lineal simple y otros modelos de aprendizaje de máquinas. Por último, el proyecto pretende demostrar la aplicabilidad de los dispositivos LCS para monitorear la concentración de PM2.5 en diversos modos de transporte dentro de la ciudad de Medellín. Esta investigación contribuye a una comprensión más amplia del potencial de los dispositivos LCS para mejorar el monitoreo de la calidad del aire y su idoneidad para iniciativas impulsadas por ciudadanos en regiones que carecen de instrumentos de calidad regulatoria. (text tomado de la fuente)Colciencias Convocatoria 727 doctorados nacionalesDoctoradoDoctor en IngenieríaInvestigación de operacionesÁrea Curricular de Ingeniería de Sistemas e Informátic
