448 resultados para 003


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This study attempts to understand the nature of violence suffered by the adolescents of Kolkata (erstwhile Calcutta) and to identify its relation with their socio-economic background and mental health variables such as anxiety, adjustment, and self-concept. It is a cross-sectional study covering a total of 370 adolescents (182 boys and 188 girls) from six higher secondary schools in Kolkata. The data was gathered by way of a semi-structured questionnaire and three standard psychological tests. Findings revealed that 52.4%, 25.1%, and 12.7% adolescents suffered psychological, physical, and sexual violence in the last year. Older adolescents (aged 17–18 years) suffered more psychological violence than the younger ones (15–16 years) (p < 0.05). Sixty nine (18.6%) adolescent students stood witness to violence between adult members in the family. More than three-fifth (61.9%) adolescents experienced at least one type of violence, while one-third (32.7%) experienced physical or sexual violence or both. Whatever its nature is, violence leaves a scar on the mental health of the victims. Those who have been through regular psychological violence reported high anxiety, emotional adjustment problem, and low self-concept. Sexual abuse left a damaging effect on self-concept (p < 0.05), while psychological violence or the witnessing of violence prompted high anxiety scores (p < 0.05), poor emotional adjustment (p < 0.05), and low self-concept (p < 0.05). This study stresses the need to provide individual counselling services to the maltreated adolescents of Kolkata so that their psychological traumas can heal and that they can move on in life with new hopes and dreams.

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Large integration of solar Photo Voltaic (PV) in distribution network has resulted in over-voltage problems. Several control techniques are developed to address over-voltage problem using Deterministic Load Flow (DLF). However, intermittent characteristics of PV generation require Probabilistic Load Flow (PLF) to introduce variability in analysis that is ignored in DLF. The traditional PLF techniques are not suitable for distribution systems and suffer from several drawbacks such as computational burden (Monte Carlo, Conventional convolution), sensitive accuracy with the complexity of system (point estimation method), requirement of necessary linearization (multi-linear simulation) and convergence problem (Gram–Charlier expansion, Cornish Fisher expansion). In this research, Latin Hypercube Sampling with Cholesky Decomposition (LHS-CD) is used to quantify the over-voltage issues with and without the voltage control algorithm in the distribution network with active generation. LHS technique is verified with a test network and real system from an Australian distribution network service provider. Accuracy and computational burden of simulated results are also compared with Monte Carlo simulations.

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Recently, second-generation (non-vegetable oil) feedstocks for biodiesel production are receiving significant attention due to the cost and social effects connected with utilising food products for the production of energy products. The Beauty leaf tree (Calophyllum inophyllum) is a potential source of non-edible oil for producing second-generation biodiesel because of its suitability for production in an extensive variety of atmospheric condition, easy cultivation, high fruit production rate, and the high oil content in the seed. In this study, oil was extracted from Beauty leaf tree seeds through three different oil extraction methods. The important physical and chemical properties of these extracted Beauty leaf oils were experimentally analysed and compared with other commercially available vegetable oils. Biodiesel was produced using a two-stage esterification process combining of an acid catalysed pre-esterification process and an alkali catalysed transesterification process. Fatty acid methyl ester (FAME) profiles and important physicochemical properties were experimentally measured and estimated using equations based on the FAME analysis. The quality of Beauty leaf biodiesels was assessed and compared with commercially available biodiesels through multivariate data analysis using PROMETHEE-GAIA software. The results show that mechanical extraction using a screw press produces oil at a low cost, however, results in low oil yields compared with chemical oil extraction. High pressure and temperature in the extraction process increase oil extraction performance. On the contrary, this process increases the free fatty acid content in the oil. A clear difference was found in the physical properties of Beauty leaf oils, which eventually affected the oil to biodiesel conversion process. However, Beauty leaf oils methyl esters (biodiesel) were very consistent physicochemical properties and able to meet almost all indicators of biodiesel standards. Overall this study found that Beauty leaf is a suitable feedstock for producing second-generation biodiesel in commercial scale. Therefore, the findings of this study are expected to serve as the basis for further development of Beauty leaf as a feedstock for industrial scale second-generation biodiesel production.

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This paper conceptualizes a framework for bridging the BIM (building information modelling)-specifications divide through augmenting objects within BIM with specification parameters derived from a product library. We demonstrate how model information, enriched with data at various LODs (levels of development), can evolve simultaneously with design and construction using different representation of a window object embedded in a wall as lifecycle phase exemplars at different levels of granularity. The conceptual standpoint is informed by the need for exploring a methodological approach which extends beyond current limitations of current modelling platforms in enhancing the information content of BIM models. Therefore, this work demonstrates that BIM objects can be augmented with construction specification parameters leveraging product libraries.

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We investigate the association between asset revaluations of non-current assets and audit fees, using a sample of ASX 300 companies from the years 2003–2007.We report that there is a significant increase in the audit fees paid when non-financial assets (PPEs, investment properties and intangible assets) are measured at fair values. Moreover, we provide evidence that an independent valuer or appraiser significantly weakens the positive association between asset revaluations and audit fees. Furthermore, companies whose noncurrent assets are revalued upwards and those that revalue their non-current assets upwards every year have significantly higher audit fees. Additional tests provide empirical evidence that the strength of corporate governance has a moderating effect on the level of audit fees. This study contributes to the ongoing debate on the role of fair value accounting. The findings suggest agency costs associated with fair value estimates may offset the benefits from the use of fair value accounting.

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Here, we present the results of two genome-wide scans in two diverse populations in which a consistent use of recently introduced migraine-phenotyping methods detects and replicates a locus on 10q22-q23, with an additional independent replication. No genetic variants have been convincingly established in migraine, and although several loci have been reported, none of them has been consistently replicated. We employed the three known migraine-phenotyping methods (clinical end diagnosis, latent-class analysis, and trait-component analysis) with robust multiple testing correction in a large sample set of 1675 individuals from 210 migraine families from Finland and Australia. Genome-wide multipoint linkage analysis that used the Kong and Cox exponential model in Finns detected a locus on 10q22-q23 with highly significant evidence of linkage (LOD 7.68 at 103 cM in female-specific analysis). The Australian sample showed a LOD score of 3.50 at the same locus (100 cM), as did the independent Finnish replication study (LOD score 2.41, at 102 cM). In addition, four previously reported loci on 8q21, 14q21, 18q12, and Xp21 were also replicated. A shared-segment analysis of 10q22-q23 linked Finnish families identified a 1.6-9.5 cM segment, centered on 101 cM, which shows in-family homology in 95% of affected Finns. This region was further studied with 1323 SNPs. Although no significant association was observed, four regions warranting follow-up studies were identified. These results support the use of symptomology-based phenotyping in migraine and suggest that the 10q22-q23 locus probably contains one or more migraine susceptibility variants.

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Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period.

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Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

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Using 20 years of employment and job mobility data from a representative German sample (N = 1259), we employ optimal matching analysis (OMA) to identify six career patterns which deviate from the traditional career path of long-term, full-time employment in one organization. Then, in further analyses, we examine which socio-demographic predictors affect whether or not individuals follow that traditional career path. Results indicate that age, gender, marital status, number of children, education, and career starts in the public sector significantly predicted whether or not individuals followed the traditional career path. The article concludes with directions for future theoretical and methodological research on career patterns.

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Most research on career adaptability has examined the construct as an individual differences variable and neglected that it may vary within an individual over a short period of time. In two daily diary studies, the author investigated the relationships of career adaptability and its four dimensions (concern, control, curiosity, and confidence) to their daily manifestations as well as daily job and career outcomes. Both Study 1 (N = 53) and Study 2 (N = 234) demonstrated substantial within-person variability in employees' behavioral expressions of career adaptability across five work days. Results further showed that daily career adaptability and daily confidence positively predicted daily task and career performance, as well as daily job and career satisfaction. Daily control positively predicted daily task performance, as well as daily job and career satisfaction. Daily concern positively predicted daily career performance and satisfaction, and daily curiosity positively predicted daily career satisfaction.

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According to career construction theory, continuous adaptation to the work environment is crucial to achieve work and career success. In this study, we examined the relative importance of career adaptability for job performance ratings using an experimental policy-capturing design. Employees (N = 135) from different vocational backgrounds rated the overall job performance of fictitious employees in 40 scenarios based on information about their career adaptability, mental ability, conscientiousness, and job complexity. We used multilevel modeling to investigate the relative importance of each factor. Consistent with expectations, career adaptability positively predicted job performance ratings, and this effect was relatively smaller than the effects of conscientiousness and mental ability. Job complexity did not moderate the effect of career adaptability on job performance ratings, suggesting that career adaptability predicts job performance ratings in high-, medium-, and low-complexity jobs. Consistent with previous research, the effect of mental ability on job performance ratings was stronger in high- compared to low-complexity jobs. Overall, our findings provide initial evidence for the predictive validity of employees' career adaptability with regard to other people's ratings of job performance.

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This chapter reviews the concepts of organizational culture and climate and applies them to environmental sustainability. Though culture and climate are often used interchangeably, the chapter identifies key distinctions between them and highlights how they can complement one another. The two concepts are used to discuss how the organizational context for environmental sustainability, and employee perceptions thereof, influence individual pro-environmental behavior. Organizational climate is integrated with a dynamic model of organizational culture to describe how pro-environmental cultures and climates emerge. The chapter also highlights how organizations with different motivations can create pro-environmental cultures and climates. The chapter uses the Sierra Nevada Brewing Company as an archetype of an organization with a pro-environmental culture and climate. In the course of the discussion, the chapter nominates several imperatives for research and recommendations for practice.

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Objective To identify factors associated with critical care nurses’ engagement in end-of-life care practices. Methods Multivariable regression modelling was undertaken on 392 responses to an online self-report survey of end-of-life care practices and factors influencing practice by Australian critical care nurses’. Univariate general linear models were built for six end-of-life care practice areas. Results Six statistically significant (p < 0.001) models were developed: Information sharing F(3, 377) = 40.53, adjusted R2 23.8%; Environmental modification F(5, 380) = 19.55, adjusted R2 19.4%; Emotional support F(10, 366) = 12.10, adjusted R2 22.8%; Patient and family centred decision making F(8, 362) = 17.61 adjusted R2 26.4%; Symptom management F(8, 376) = 7.10, adjusted R2 11.3%; and Spiritual support F(9, 367) = 14.66, adjusted R2 24.6%. Stronger agreement with values consistent with a palliative approach, and greater support for patient and family preferences were associated with higher levels of engagement in end-of-life care practices. Higher levels of preparedness and access to opportunities for knowledge acquisition were associated with engagement in the interpersonal practices of patient and family centred decision making and emotional support. Conclusion This study provides evidence for interventions to address factors associated with nurse engagement to increase participation in all end-of-life care practice areas.

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The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

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As business environments become even more competitive, project teams are required to make an effort to operate external linkages from within an organization or across organizational boundaries. Nevertheless, some members boundary-span less extensively, isolating themselves and their project teams from external environments. Our study examines why some members boundary-span more or less through the framework of group attachment theory. Data from 521 project-team members in construction and engineering industries revealed that the more individuals worry about their project team’s acceptance (group attachment anxiety), the more likely they are to perceive intergroup competition, and thus put more efforts into operating external linkages and resources to help their own teams outperform competitors. In contrast, a tendency to distrust their project teams (group attachment avoidance) generates members’ negative construal of their team’s external image, and thus fewer efforts are made at operating external linkages. Thus, project leaders and members with high group-attachment-anxiety may be best qualified for external tasks.