51 resultados para Guide for ways to support the most vulnerable families in society


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Organizations introduce acceptable use policies to deter employee computer misuse. Despite the controlling, monitoring and other forms of interventions employed, some employees misuse the organizational computers to carry out their personal work such as sending emails, surfing internet, chatting, playing games etc. These activities not only waste productive time of employees but also bring a risk to the organization. A questionnaire was administrated to a random sample of employees selected from large and medium scale software development organizations, which measured the work computer misuse levels and the factors that influence such behavior. The presence of guidelines provided no evidence of significant effect on the level of employee computer misuse. Not having access to Internet /email away from work and organizational settings were identified to be the most significant influences of work computer misuse.

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The Homeric epics are among the greatest masterpieces of literature, but when they were produced is not known with certainty. Here we apply evolutionary-linguistic phylogenetic statistical methods to differences in Homeric, Modern Greek and ancient Hittite vocabulary items to estimate a date of approximately 710–760 BCE for these great works. Our analysis compared a common set of vocabulary items among the three pairs of languages, recording for each item whether the words in the two languages were cognate – derived from a shared ancestral word – or not. We then used a likelihood-based Markov chain Monte Carlo procedure to estimate the most probable times in years separating these languages given the percentage of words they shared, combined with knowledge of the rates at which different words change. Our date for the epics is in close agreement with historians' and classicists' beliefs derived from historical and archaeological sources.

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OBJECTIVE: This study modeled win and lose trials in a simple gambling task to examine the effect of entire win-lose situations (WIN, LOSS, or TIE) on single win/lose trials and related neural underpinnings. METHODS: The behavior responses and brain activities of 17 participants were recorded by an MRI scanner while they performed a gambling task. Different conditions were compared to determine the effect of the task on the behavior and brain activity of the participants. Correlations between brain activity and behavior were calculated to support the imaging results. RESULTS: In win trials, LOSS caused less intense posterior cingulate activity than TIE. In lose trials, LOSS caused more intense activity in the right superior temporal gyrus, bilateral superior frontal gyrus, bilateral anterior cingulate, bilateral insula cortex, and left orbitofrontal cortex than WIN and TIE. CONCLUSIONS: The experiences of the participants in win trials showed great similarity among different win-lose situations. However, the brain activity and behavior responses of the participants in lose trials indicated that they experienced stronger negative emotion in LOSS. The participants also showed an increased desire to win in LOSS than in WIN or TIE conditions.

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Advances in hardware and software technologies allow to capture streaming data. The area of Data Stream Mining (DSM) is concerned with the analysis of these vast amounts of data as it is generated in real-time. Data stream classification is one of the most important DSM techniques allowing to classify previously unseen data instances. Different to traditional classifiers for static data, data stream classifiers need to adapt to concept changes (concept drift) in the stream in real-time in order to reflect the most recent concept in the data as accurately as possible. A recent addition to the data stream classifier toolbox is eRules which induces and updates a set of expressive rules that can easily be interpreted by humans. However, like most rule-based data stream classifiers, eRules exhibits a poor computational performance when confronted with continuous attributes. In this work, we propose an approach to deal with continuous data effectively and accurately in rule-based classifiers by using the Gaussian distribution as heuristic for building rule terms on continuous attributes. We show on the example of eRules that incorporating our method for continuous attributes indeed speeds up the real-time rule induction process while maintaining a similar level of accuracy compared with the original eRules classifier. We termed this new version of eRules with our approach G-eRules.

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Despite diversity in family dynamics within and between societies, globally, it is adults who are usually relied upon to care for family members who are sick, disabled or have other care needs. Young people in Zambia and other African countries affected by the HIV epidemic are under increasing pressure to obtain a good education and employment to support their families, whilst some also have to cope with the loss of parents and care for relatives with little external support. This article discusses the findings of qualitative research that explored the experiences of young people (aged 14-30) who had significant family caring responsibilities and those without such responsibilities in Zambia. Interviews and life-mapping methods were conducted with a total of 35 young people living in rural and urban areas, 12 parents and relatives and 12 professionals. We analyse young people's experiences and perceptions of socially expected transitions, such as completing education and earning an income to support themselves and their families, in addition to more unpredictable changes in young people's family lives. ‘Critical moments’ (Thomson et al, 2002), such as bereavement and loss of parents and other family members, disinheritance of assets and property grabbing, migration and mobility between different relatives homes, parental divorce and separation, often had significant impacts on young people’s ability to navigate their pathways to adulthood according to wider social norms and expectations. A more relational conceptualisation of youth transitions is needed that takes account of young people's caring responsibilities and changing family dynamics.

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The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.