997 resultados para Temperature Relationships


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The scope of this work is the systematic study of the silicidation process affecting tungsten filaments at high temperature (1900ºC) used for silane decomposition in the hot-wire chemical vapour deposition technique (HWCVD). The correlation between the electrical resistance evolution of the filaments, Rfil(t), and the different stages of the their silicidation process is exposed. Said stages correspond to: the rapid formation of two WSi2 fronts at the cold ends of the filaments and their further propagation towards the middle of the filaments; and, regarding the hot central portion of the filaments: a initial stage of silicon dissolution into the tungsten bulk, with a random duration for as-manufactured filaments, followed by the inhomogeneous nucleation of W5Si3 (which is later replaced by WSi2) and its further growth towards the filaments core. An electrical model is used to obtain real-time information about the current status of the filaments silicidation process by simply monitoring their Rfil(t) evolution during the HWCVD process. It is shown that implementing an annealing pre-treatment to the filaments leads to a clearly repetitive trend in the monitored Rfil(t) signatures. The influence of hydrogen dilution of silane on the filaments silicidation process is also discussed.

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The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

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ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. RESULTS: We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. CONCLUSIONS: We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

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Body temperature of the European water-shrew Neomys fodiens was reinvestigated with intraperitoneally implanted radiotransmitters. Two animals, caged in outdoor conditions, were tested during February and March. Mean body temperature (Tb) during rest was 37.0°C, during activity 37.5°C. During stress of capture Tb increased to 38.4°C, and during a social confrontation mean Tb was 39.4°C. During forced swimming Tb decreased at a rate of 1.1°C per minute in an animal with wet fur. However, when kept in adequate conditions, animals could maintain their body temperature at a level of about 37°C in most of the tested situations. In water of 2.6°C, mean Tb after 6 min of forced swimming or diving was 37.4°C, comparable to Tb terrestrial activity. In these animals the fur remained dry even on its surface. The pelt of these shrews has a hydrophobic property which seems to be unique compared to other semiaquatic mammals.

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The control of whitefly Bemisia tabaci (Gennadius) biotype B (Hemiptera: Aleyrodidae) on okra (Abelmoschus esculentus L.) consists primarily in the use of insecticides, due to the lack of information on other mortality factors. The objective of this study was to evaluate the spatial and temporal population dynamics of the whitefly B. tabaci biotype B on two successive A. esculentus var. "Santa Cruz" plantations. Leaf chemical composition, leaf nitrogen and potassium contents, trichome density, canopy height, plant age, predators, parasitoids, total rainfall and median temperature were evaluated and their relationships with whitefly on okra were determined. Monthly number estimates of whitefly adults, nymphs (visual inspection) and eggs (magnifying lens) occurred on bottom, middle and apical parts of 30 plants/plantation (one leaf/plant). Plants senescence and natural enemies, mainly Encarsia sp., Chrysoperla spp. and Coccinellidae, were some of the factors that most contributed to whitefly reduction. The second okra plantation, 50 m apart from the first, was strongly attacked by whitefly, probably because of the insect migration from the first to the second plantation. No significant effects of the plant canopy on whitefly eggs and adults distribution were found. A higher number of whitefly nymphs was found on the medium part than on the bottom part.

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Kale Brassica oleracea var. acephala is attacked by whitefly Bemisia tabaci, aphid Brevicoryne brassicae and Thrips tabaci. One of the main reasons for extensive insecticide application is the lack of information about factors that control insect population. The objectives of this study were to investigate the relationships between predators and parasitoids, organic compound leaves, levels of leaf nitrogen and potassium, total rainfall, relative humidity, sunlight and median temperature on the abundance of whitefly, aphid, and thrips in kale genotype "Talo Roxo". The beating tray method, direct counting and magnifying lens were used to estimate the number of these pests, predators and parasitoids. Median temperature, sunlight and relative humidity correlated to the amount of leaf nonacosane, which in turn was associated with aphids population increase. A tendency in the reduction of aphids and thrips populations with increase in total rainfall was observed. The whitefly can be a harmful pest in kale producing regions of higher temperature and smaller rainfall. In regions which present moderate temperature, where there is a high incidence of aphids, genotype with low leaf wax content should be chosen. Natural enemies, especially the parasitoid Adialytus spp., can control agents of the aphids population in kale.

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Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

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The objective of this work was to develop a simplified numerical procedure for the estimation of accumulated monthly hours of solarized soil temperatures. The proposed model requires monthly means of daily solar radiation and maximum air temperature as input data, and a daily pattern of temperature variation assumed to be sine-shaped. The procedure was verified using observations made during the years 1992 and 1993 in Jaguariúna, SP. The proposed procedure can predict monthly temperature hours at 10 cm depth in the solarized soil, with acceptable accuracy, in the region for which it was developed.

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PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

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The objective of this work was to investigate the relationships between predators and parasitoids, leaf chemical composition, levels of leaf nitrogen and potassium, total rainfall, relative humidity, daylight and median temperature on the intensity of whitefly, aphid, and thrips attack on cabbage. Whitefly, aphids and thrips population tended to proliferate in the final stage of plant or reached a peak population about 40 days after plantation. The whitefly and thrips tended to increase with an increase in the median temperature. A dependence of Cheiracanthium inclusum and Adialytus spp. populations on whitefly and aphids populations, respectively, was observed. No significant effect was detected between K and nonacosane leaf content and aphid population. However, an increase in leaf N content was followed by a decrease of this insect population. No significant relation was observed between leaf N, K and nonacosane and whitefly and thrips populations. Highest nonacosane levels were observed in plants 40 days after transplant, and relative humidity correlated negatively with nonacosane. Natural enemies, especially the parasitoid Adialytus spp. and the spiders can be useful controlling agents of the whitefly and aphids in cabbage. Median temperature can increase whitefly and thrips populations.

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The objective of this work was to evaluate the effects of temperature (10, 20, 30, 20/10 and 30/10ºC) and period of storage on electrical conductivity (EC) in four seed lots of corn (Zea mays L.), as well as the mineral composition of the soaking solution. EC test determines indirectly the integrity of seed membrane systems, and is used for the assessment of seed vigor, because this test detects the seed deterioration process since its early phase. The research comprised determinations of water content, germination, accelerated aging (AA), cold (CT) and EC vigor tests, and determinations of Ca2+, Mg2+ and K+ release to the solution, after seed soaking of four corn seed lots. The evaluations were performed each four months during a period of 16 months. For statistical analysis, a completely randomized split plot design was used with eight replications. Except for seed lots stored at 10ºC, all vigor evaluations revealed a decline in vigor, but AA and CT showed more sensitiveness to declines of seed physiological quality than EC. Potassium was the main leached ion regardless of the storage temperature.

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The effect of curing temperature, in the range of 4.4 to 22.8 degrees C (40 to 73 degrees F), on strength development was studied based on the maturity and pulse velocity measurements in this report. The strength-maturity relationships for various mixes using a Type I cement and using a Type IP cement, respectively, were experimentally developed. The similar curves for early age strength development of both the patching concrete, using a Type I cement with the addition of calcium chloride, and the fast track concrete, using a Type III cement and fly ash, have also been proposed. For the temperature ranges studied, the strength development of concrete can be determined using a pulse velocity measurement, but only for early ages up to 24 hours. These obtained relationships can be used to determine when a pavement can be opened to traffic. The amount of fly ash substitution, up to 30%, did not have a significant influence on the strength-maturity relationship.

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Seasonal variations in ground temperature and moisture content influence the load carrying capacity of pavement subgrade layers. To improve pavement performance, pavement design guidelines require knowledge of environmental factors and subgrade stiffness relationships. As part of this study, in-ground instrumentation was installed in the pavement foundation layers of a newly constructed section along US Highway 20 near Fort Dodge, Iowa, to monitor the seasonal variations in temperature, frost depth, groundwater levels, and moisture regime. Dynamic cone penetrometer (DCP), nuclear gauge, and Clegg hammer tests were performed at 64 test points in a 6-ft x 6-ft grid pattern to characterize the subgrade stiffness properties (i.e., resilient modulus) prior to paving. The purpose of this paper is to present the field instrumentation results and the observed changes in soil properties due to seasonal environmental effects.