900 resultados para Variables from CGTMSE
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The INTAMAP FP6 project has developed an interoperable framework for real-time automatic mapping of critical environmental variables by extending spatial statistical methods and employing open, web-based, data exchange protocols and visualisation tools. This paper will give an overview of the underlying problem, of the project, and discuss which problems it has solved and which open problems seem to be most relevant to deal with next. The interpolation problem that INTAMAP solves is the generic problem of spatial interpolation of environmental variables without user interaction, based on measurements of e.g. PM10, rainfall or gamma dose rate, at arbitrary locations or over a regular grid covering the area of interest. It deals with problems of varying spatial resolution of measurements, the interpolation of averages over larger areas, and with providing information on the interpolation error to the end-user. In addition, monitoring network optimisation is addressed in a non-automatic context.
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Meta-analysis was used to quantify the moderating effects of seven properties of cognitions-accessibility, temporal stability, direct experience, involvement, certainty, ambivalence and affective-cognitive consistency-on cognition-intention and cognition-behaviour relations. Literature searches revealed 44 studies that could be included in the review. Findings showed that all of the properties, except involvement, moderated attitude-behaviour consistency. Similarly, all relevant moderators improved the consistency between intentions and behaviour. Temporal stability moderated PBC-behaviour relations, certainty moderated subjective norm-intention relations, and ambivalence, certainty, and involvement all moderated attitude-intention relations. Overall, temporal stability appeared to be the strongest moderator of cognition-behaviour relations.
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While the quantum of advances from the public sector banks (PSBs) to the MSEs has increased over the years in absolute terms, from Rs.46, 045 crore in March 2000 to Rs.1, 85,208 crore in March 2009, the share of the 7credit to the MSE sector in the Net Bank Credit (NBC) has declined from 12.5 per cent to 10.9 per cent. Similarly, there has been a decline in the share of micro sector as a percentage of Net Bank Credit (NBC) from 7.8 per cent in March 2000 to 4.9% in March 2009. (TKA.Nair, 2010)9.The major reasons for low availability of bank finance to this sector are high risk perception of the banks in lending to MSEs and high transaction costs in processing of loan applications of MSEs. The problem is more serious for micro enterprises requiring small loans and the first generation entrepreneursThe thesis studies the divergence in guidelines by, CGTMSE, RBI & Bank of Baroda on collateral free lending and analyses the awareness of MSE about CGTMSE lending. The researcher tries to assess the problems faced by borrowers in availing advance under CGTMSE from Bank of Baroda, Kerala.
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Empirical studies on the impact of women’s paid jobs on their empowerment and welfare in the Bangladesh context are rare. The few studies on the issue to date have all been confined to the garment workers only although studies indicate that women’s workforce participation in Bangladesh has increased across-the-board. Besides, none of these studies has made an attempt to control for the non-working women and/or applied any statistical technique to control for the effects of other pertinent determinants of women’s empowerment and welfare such as education, age, religion and place of living. This study overcomes these drawbacks and presents alternative assessments of the link between women’s workforce participation and empowerment on the basis of survey data from the two largest cities in Bangladesh. While the generic assessment indicates that women’s paid jobs have positive implications for women’s participation in decisions on fertility, children’s education and healthcare as well as their possession and control of resources, the econometric assessment negates most of these observations. Women’s education, on the other hand, appears to be more important than their participation in the labour force. The study underlines the fact that by omitting other relevant explanatory variables from the analysis, the previous studies might have overestimated the impact of women’s paid work on their empowerment. Among other things, the paper also highlights the importance of women’s job category, religion and regional differences for women’s empowerment.
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House re-invasion by native triatomines after insecticide-based control campaigns represents a major threat for Chagas disease vector control. We conducted a longitudinal intervention study in a rural section (Area III, 407 houses) of Pampa del Indio, northeastern Argentina, and used wing geometric morphometry to compare pre-spray and post-spray (re-infestant bugs) Triatoma infestanspopulations. The community-wide spraying with pyrethroids reduced the prevalence of house infestation by T. infestans from 31.9% to < 1% during a four-year follow-up, unlike our previous studies in the neighbouring Area I. Two groups of bug collection sites differing in wing shape variables before interventions (including 221 adults from 11 domiciles) were used as a reference for assigning 44 post-spray adults. Wing shape variables from post-spray, high-density bug colonies and pre-spray groups were significantly different, suggesting that re-infestant insects had an external origin. Insects from one house differed strongly in wing shape variables from all other specimens. A further comparison between insects from both areas supported the existence of independent re-infestation processes within the same district. These results point to local heterogeneities in house re-infestation dynamics and emphasise the need to expand the geographic coverage of vector surveillance and control operations to the affected region.
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The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).
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Background Longitudinal epidemiological studies involving child/adolescent mental health problems are scarce in developing countries, particularly in regions characterized by adverse living conditions. We examined the influence of psychosocial factors on the trajectory of child/adolescent mental health problems (CAMHP) over time. Methods A population-based sample of 6- to 13-year-olds with CAMHP was followed-up from 2002–2003 (Time 1/T1) to 2007–2008 (Time 2/T2), with 86 out of 124 eligible children/adolescents at T1 being reassessed at T2 (sample loss: 30.6%). Outcome: CAMHP at T2 according to the Child Behavior Checklist/CBCL’s total problem scale. Psychosocial factors: T1 variables (child/adolescent’s age, family socioeconomic status); trajectory of variables from T1 to T2 (child/adolescent exposure to severe physical punishment, mother exposure to severe physical marital violence, maternal anxiety/depression); and T2 variables (maternal education, child/adolescent’s social support and pro-social activities). Results Multivariate analysis identified two risk factors for child/adolescent MHP at T2: aggravation of child/adolescent physical punishment and aggravation of maternal anxiety/depression. Conclusions The current study shows the importance of considering child/adolescent physical punishment and maternal anxiety/depression in intervention models and mental health care policies.
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Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^
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As the length of marine cores increases and sampling intervals decrease, the need for rapid and inexpensive means of determining sediment composition has become apparent. In this study we examine one potentially useful technique for assessing compositional changes in marine cores, diffuse reflectance spectrophotometry. We examined near-ultraviolet, visible, and near-infrared reflectance spectra from five data sets. Each data set consists of calibration samples and test samples. The calibration samples' spectra were related to a sediment component using multiple linear regression. The resulting regression or calibration equations were then evaluated using the test samples. Calibration equations were written relating spectra to several sediment components incduding carbonate (Atlantic and east Pacific Rise ODP Site 847), organic carbon content (Atlantic and east Pacific Rise), and opal content (east Pacific Rise). The correlation coefficients for the regression equations ranged from a high of 0.99 for carbonate and opal at ODP Site 847 to a low of 0.97 for Atlantic carbonate indicating that spectral variations are highly correlated to sediment composition. All of the equations include a substantial number of variables from shorter visible and longer near ultraviolet wavelengths suggesting that these wavelengths are especially important for devices designed specifically to scan marine cores. Although equations for estimating organic and carbonate content appear independent of other sediment components, the opal equation is strongly dependent on carbonate content indicating that opal concentration is correlated to carbonate content. Tests of the calibration equations indicated that all our equations reasonably estimate the pattern of changes, either down core or in surface sediments. Where our spectral estimates have difficulty is with absolute values, frequently over or underestimating observed values by a substantial amount. Within these limitations diffuse reflectance spectrophotometry can be a useful tool for characterizing marine cores and as our understanding of the relationship between spectra and mineralogy improves so will estimates of absolute values.
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To use or not to use a disliked gift is a dilemma for recipients. Their choice will affect their relationship with the giver as well as marketing and business. However, the study of this topic is scarce in the consumer behavior discipline. Through a survey on 1269 adults in Ecuador, a Latin American country, this study identifies variables from the recipient, the giver, their relationship, and the gift. These variables provide the solution to the dilemma and, according to these findings, present implications for theory and practice.
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We study the dynamics of on-line learning in multilayer neural networks where training examples are sampled with repetition and where the number of examples scales with the number of network weights. The analysis is carried out using the dynamical replica method aimed at obtaining a closed set of coupled equations for a set of macroscopic variables from which both training and generalization errors can be calculated. We focus on scenarios whereby training examples are corrupted by additive Gaussian output noise and regularizers are introduced to improve the network performance. The dependence of the dynamics on the noise level, with and without regularizers, is examined, as well as that of the asymptotic values obtained for both training and generalization errors. We also demonstrate the ability of the method to approximate the learning dynamics in structurally unrealizable scenarios. The theoretical results show good agreement with those obtained by computer simulations.
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The ability of the United States Air Force (USAF) to sustain a high level of operational ability and readiness is dependent on the proficiency and expertise of its pilots. Recruitment, education, training, and retention of its pilot force are crucial factors in the USAF's attainment of its operational mission: defense of this nation and its allies. Failure of a student pilot during a training program does not only represent a loss of costly training expenditures to the American public, but often consists of loss of human life, aircraft, and property. This research focused on the Air Force Reserve Officer Training Corps' (AFROTC) selection method for student pilots for the light aircraft training (LATR) program. The LATR program is an intense 16 day flight training program that precedes the Air Force's undergraduate pilot training (UPT) program. The study subjects were 265 AFROTC cadets in the LATR program. A variety of independent variables from each subject's higher education curricular background as well as results of preselection tests, participation in varsity athletics, prior flying experience and gender were evaluated against subsequent performance in LATR. Performance was measured by a quantitative performance score developed by this researcher based on 28 graded training factors as well as overall pass or fail of the LATR program. Study results showed participation in university varsity athletics was very significantly and positively related to performance in the LATR program, followed by prior flying experience and to a very slight degree portions of the Air Force Officers Qualifying Test. Not significantly related to success in the LATR program were independent variables such as grade point average, scholastic aptitude test scores, academic major, gender and the AFROTC selection and ranking system.
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Montado decline has been reported since the end of the nineteenth century in southern Portugal and increased markedly during the 1980s. Consensual reports in the literature suggest that this decline is due to a number of factors, such as environmental constraints, forest diseases, inappropriate management, and socioeconomic issues. An assessment on the pattern of montado distribution was conducted to reveal how the extent of land management, environmental variables, and spatial factors contributed to montado area loss in southern Portugal from 1990 to 2006. A total of 14 independent variables, presumably related to montado loss, were grouped into three sets: environmental variables, land management variables, and spatial variables. From 1990 to 2006, approximately 90,054 ha disappeared in the montado area, with an estimated annual regression rate of 0.14 % year-1. Variation partitioning showed that the land management model accounted for the highest percentage of explained variance (51.8 %), followed by spatial factors (44.6 %) and environmental factors (35.5 %). These results indicate that most variance in the large-scale distribution of recent montado loss is due to land management, either alone or in combination with environmental and spatial factors. The full GAM model showed that different livestock grazing is one of the most important variables affecting montado loss. This suggests that optimum carrying capacity should decrease to 0.18–0.60 LU ha-1 for livestock grazing in montado under current ecological conditions in southern Portugal.
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The citrus greening (or huanglongbing) disease has caused serious problems in citrus crops around the world. An early diagnostic method to detect this malady is needed due to the rapid dissemination of Candidatus Liberibacter asiaticus (CLas) in the field. This analytical study investigated the fluorescence responses of leaves from healthy citrus plants and those inoculated with CLas by images from a stereomicroscope and also evaluated their potential for the early diagnosis of the infection caused by this bacterium. The plants were measured monthly, and the evolution of the bacteria on inoculated plants was monitored by real-time quantitative polymerase chain reaction (RT-qPCR) amplification of CLas sequences. A statistical method was used to analyse the data. The selection of variables from histograms of colours (colourgrams) of the images was optimized using a paired Student's t-test. The intensity of counts for green colours from images of fluorescence had clearly minor variations for healthy plants than diseased ones. The darker green colours were the indicators of healthy plants and the light colours for the diseased. The method of fluorescence images is novel for fingerprinting healthy and diseased plants and provides an alternative to the current method represented by PCR and visual inspection. A new, non-subjective pattern of analysis and a non-destructive method has been introduced that can minimize the time and costs of analyses.