Reflow soldering in an oxidant atmosphere

Dissertação de mestrado integrado em Materials Engineering

Subendocardial fibrosis in remote myocardium results from reduction of coronary driving pressure during acute infarction in rats

OBJECTIVE: To investigate the role of hemodynamic changes occurring during acute MI in subsequent fibrosis deposition within non-MI. METHODS: By using the rat model of MI, 3 groups of 7 rats each [sham, SMI (MI <30%), and LMI (MI >30%)] were compared. Systemic and left ventricular (LV) hemodynamics were recorded 10 minutes before and after coronary artery ligature. Collagen volume fraction (CVF) was calculated in picrosirius red-stained heart tissue sections 4 weeks later. RESULTS: Before surgery, all hemodynamic variables were comparable among groups. After surgery, LV end-diastolic pressure increased and coronary driving pressure decreased significantly in the LMI compared with the sham group. LV dP/dt max and dP/dt min of both the SMI and LMI groups were statistically different from those of the sham group. CVF within non-MI interventricular septum and right ventricle did not differ between each MI group and the sham group. Otherwise, subendocardial (SE) CVF was statistically greater in the LMI group. SE CVF correlated negatively with post-MI systemic blood pressure and coronary driving pressure, and positively with post-MI LV dP/dt min. Stepwise regression analysis identified post-MI coronary driving pressure as an independent predictor of SE CVF. CONCLUSION: LV remodeling in rats with MI is characterized by predominant SE collagen deposition in non-MI and results from a reduction in myocardial perfusion pressure occurring early on in the setting of MI.

Development of a life cycle management system for remote products.

The research described in this thesis has been developed as a part of the Reliability and Field Data Management for Multi-Component Products (REFIDAM) Project. This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway-Mayo Institute of Technology and an industrial company, Thermo King Europe. The project aimed to develop a system to manage the information required for maintenance costing, cost of ownership, reliability assessment and improvement of multi-component products, by establishing information flows between the customer network and across the Thermo King organisation.

The Feedback Effect of Intensity of Ionizing Radiation With the Light Ions Content in Atmosphere. Paradox (the Tbilisi Type of a Smog), or Usual Phenomenon for the Strongly Pollution Cities?.

თბილისში მსუბუქი იონების, რადონის და გალაქტიკური კოსმოსური სხივების ნეიტრონული კომპონენტის ინტენსივობის 2009-2010 წლებში კომპლექსური მონიტორინგის მონაცემების მიხედვით გამოვლენილია მაიონიზებელი გამოსხივების ინტენსივობისა და ატმოსფეროში მსუბუქი იონების შემცველობის უკუკავშირის ეფექტი.

Influence of Aerosol Pollution of Atmosphere in Tbilisi on Air Electric Conductivity in Dusheti

The results of investigations of the influence of aerosol pollution of atmosphere in Tbilisi (the capital of the Georgia, city with the greatest level of air pollution) on the total air electric conductivity in Dusheti (the small city, located in 40-45 km to the north of Tbilisi) are represented.

Analysis of the Atmosphere Aerosol and Ozone Condition Over Tbilisi Using Satellite Data and Ground Truth Measurements

Ground-based measurements of the parameters of atmosphere in Tbilisi during the same period, which are provided by the Mikheil Nodia Institute of geophysics, were used as calibration data. Satellite data monthly averaging, preprocessing, analysis and visualization was performed using Giovanni web-based application. Maps of trends and periodic components of the atmosphere aerosol optical thickness and ozone concentration over the study area were calculated.

Static diffusion models of the upper atmosphere with empirical temperature profiles.

v. 8 no. 9

Effects of a nursery CO2 enriched atmosphere on the germination and seedling morphology of two Mediterranean oaks with contrasting leaf habit

Abstract: The use of an enriched CO2 atmosphere in tree nurseries has been envisaged as a promising technique to increase productivity and to obtain seedlings with a higher root/shoot ratio, an essential trait to respond to water stress in Mediterranean-type ecosystems. In that framework, we have analyzed the effects of three levels of atmospheric CO2 concentration (350, 500 and 700 ppm) on the germination rate, growth and morphology of seedlings of two Mediterranean oaks used in reforestation programs: the evergreen Quercus ilex L. and the deciduous Quercus cerrioides Wilk. et Costa. CO2 enrichment increased the germination rate of Q. cerrioides (from 70±7 to 81±3 %) while it decreased that of Q. ilex (from 71±10 to 41±12 %). Seedlings of both species increased approximately 60% their total biomass in response to CO2 enrichment but at two different CO2 concentrations: 500 ppm for Q. cerrioides and 700 ppm for Q. ilex. This increase in seedlings biomass was entirely due to an augmentation of root biomass. Considering germination and biomass partitioning, an enriched CO2 atmosphere might not be appropriate for growing Mediterranean evergreen oaks, such as Q. ilex, since it reduces acorn germination and the only gains in root biomass occur at a high concentration (700 ppm). On the other hand, a moderate CO2 enrichment (500 ppm) appears as a promising nursery technique to stimulate the germination, growth and root/shoot ratio of deciduous oaks, such as Q. cerrioides. Resumen: El uso de una atmósfera enriquecida en CO2 durante la fase de vivero puede contribuir a aumentar la producción viverística, a la vez que ayudar a conseguir plántulas con una mayor relación biomasa subterránea/biomasa aérea, más adecuadas para hacer frente al severo estrés hídrico que generalmente limita el éxito de las repoblaciones en el clima Mediterráneo. En este estudio hemos analizado el efecto de tres niveles de abonado carbónico atmosférico (350, 500 y 750 ppm) en la germinación y morfología de plántulas de encina (Quercus ilex) y roble cerrioide (Quercus cerrioides). Una atmósfera enriquecida en CO2 incrementó la germinación de Q. cerrioides (de 70±7 a 81±3 %) mientras que disminuyó la de Q. ilex (de 71±10 a 41±12 %). Las plántulas de ambas especies incrementaron aproximadamente un 60% su biomasa en respuesta a una mayor concentración de CO2, aunque esta respuesta se produjo a diferentes dosis: 500 ppm en Q. cerrioides y 700 ppm en Q. ilex. El aumento en la biomasa total de las plántulas se debió enteramente a un mayor desarrollo de su sistema radical, Considerando tanto la germinación como los efectos sobre la relación biomasa subterránea/biomasa aérea, una atmósfera enriquecida en CO2 no parece ser un tratamiento adecuado para la producción en vivero de plántulas de Q.ilex, puesto que diminuye su germinación y solo aumenta su sistema radicular a dosis muy elevadas (700 ppm). Por el contrario, un aumento moderado en la concentración de CO2 (500 ppm) aparece como una técnica interesante para estimular el crecimiento y obtener plántulas de Q. cerrioides con un sistema radical más desarrollado.

Carbon dioxide in scree slope deposits: A pathway from atmosphere to pedogenic carbonate

A continuum of carbon, from atmospheric CO2 to secondary calcium carbonate, has been studied in a soil associ- ated with scree slope deposits in the Jura Mountains of Switzerland. This approach is based on former studies conducted in other environments. This C continuum includes atmospheric CO2, soil organic matter (SOM), soil CO2, dissolved inorganic carbon (DIC) in soil solutions, and secondary pedogenic carbonate. Soil parameters (pCO2, temperature, pH, Cmin and Corg contents), soil solution chemistry, and isotopic compositions of soil CO2, DIC, carbonate and soil organic matter (δ13CCO2, δ13CDIC, δ13Ccar and δ13CSOM values) have been monitored at different depths (from 20 to 140 cm) over one year. Results demonstrated that the carbon source in secondary carbonate (mainly needle fiber calcite) is related to the dissolved inorganic carbon, which is strongly dependent on soil respiration. The heterotrophic respiration, rather than the limestone parent material, seems to control the pedogenic carbon cycle. The correlation of δ13Corg values with Rock-Eval HI and OI indices demonstrates that, in a soil associated to scree slope deposits, the main process responsible for 13C-enrichment in SOM is related to bac- terial oxidative decarboxylation. Finally, precipitation of secondary calcium carbonate is enhanced by changes in soil pCO2 associated to the convective movement of air masses induced by temperature gradients (heat pump effect) in the highly porous scree slope deposits. The exportation of soil C-leachates from systems such as the one studied in this paper could partially explain the "gap in the European carbon budget" reported by recent studies.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.