518 resultados para Gabriella de Lucca


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Mode of access: Internet.

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Mode of access: Internet.

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University of Illinois Library bookplate "From the library of Conte Antonio Cavagna Sangiuliani di Gualdana Lazelada di Bereguardo, purchased 1921" on the inside front cover.

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Mode of access: Internet.

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von L. Kruse

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Background: All Canadian jurisdictions require certain professionals to report suspected or observed child maltreatment. This study examined the types of maltreatment, level of harm and child functioning issues, controlling for family socioeconomic status, age and gender of the child reported by healthcare and non-healthcare professionals. Methods: We conducted chi-square analyses and logistic regression on a national child welfare sample from the 2003 Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-2003) and compared the differences in professional reporting with its previous cycle (CIS-1998) using Bonferroni-corrected confidence intervals. Results: Our analysis of CIS-2003 data revealed that the majority of substantiated child maltreatment is reported to service agencies by non-healthcare professionals (57%), followed by non-professionals (33%) and healthcare professionals (10%). The number of professional reports increased 2.5 times between CIS-1998 and CIS-2003, while non-professionals’ increased 1.7 times. Of the total investigations, professional reports represented 59% in CIS-1998 and 67% in CIS-2003 (p<0.001). Compared to non-healthcare professionals, healthcare professionals more often reported younger children, children who experienced neglect and emotional maltreatment and those assessed as suffering harm and child functioning issues, but less often exposure to domestic violence. Conclusion: The results indicate that healthcare professionals played an important role in identifying children in need of protection considering harm and other child functioning issues. The authors discuss the reasons why underreporting is likely to remain an issue.

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This talk proceeds from the premise that IR should engage in a more substantial dialogue with cognitive science. After all, how users decide relevance, or how they chose terms to modify a query are processes rooted in human cognition. Recently, there has been a growing literature applying quantum theory (QT) to model cognitive phenomena. This talk will survey recent research, in particular, modelling interference effects in human decision making. One aspect of QT will be illustrated - how quantum entanglement can be used to model word associations in human memory. The implications of this will be briefly discussed in terms of a new approach for modelling concept combinations. Tentative links to human adductive reasoning will also be drawn. The basic theme behind this talk is QT can potentially provide a new genre of information processing models (including search) more aligned with human cognition.

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Loli-Pop brings together the relationships between the Loli-Goth and popular culture, and the strong association of the Loli-Goth with the doll, including a selection from Hardy Bernal’s personal collection of Japanese Lolita dolls. This display is supported by the highlight of the show, five full-sized garments created and constructed by AUT University Fashion staff members, Angie Finn, Yvonne Stewart, Lize Niemczyk, Gabriella Trussardi, Carmel Donnelly and Kathryn Hardy Bernal, which demonstrate the designers’ own interpretations of Gothic & Lolita, inspired by Japanese street style. The exhibit is complimented by a backdrop of photographs that illustrate the impact of the outfits when worn, modelled by AUT University Bachelor of Fashion Design students, Emily Huang, Shangshang Cookie Wang, Emily Wang, Shiahug-Wen Sean Kuo and Yanling Wang.

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This report provides an account of the first large-scale scoping study of work integrated learning (WIL) in contemporary Australian higher education. The explicit aim of the project was to identify issues and map a broad and growing picture of WIL across Australia and to identify ways of improving the student learning experience in relation to WIL. The project was undertaken in response to high levels of interest in WIL, which is seen by universities both as a valid pedagogy and as a means to respond to demands by employers for work-ready graduates, and demands by students for employable knowledge and skills. Over a period of eight months of rapid data collection, 35 universities and almost 600 participants contributed to the project. Participants consistently reported the positive benefits of WIL and provided evidence of commitment and innovative practice in relation to enhancing student learning experiences. Participants provided evidence of strong partnerships between stakeholders and highlighted the importance of these relationships in facilitating effective learning outcomes for students. They also identified a range of issues and challenges that face the sector in growing WIL opportunities; these issues and challenges will shape the quality of WIL experiences. While the majority of comments focused on issues involved in ensuring quality placements, it was recognised that placements are just one way to ensure the integration of work with learning. Also, the WIL experience is highly contextualised and impacted by the expectations of students, employers, the professions, the university and government policy.

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Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

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Lung cancer is the most important cause of cancer-related mortality. Resectability and eligibility for treatment with adjuvant chemotherapy is determined by staging according to the TNM classification. Other determinants of tumour behaviour that predict disease outcome, such as molecular markers, may improve decision-making. Activation of the gene encoding human telomerase reverse transcriptase (hTERT) is implicated in the pathogenesis of lung cancer, and consequently detection of hTERT mRNA might have prognostic value for patients with early stage lung cancer. A cohort of patients who underwent a complete resection for early stage lung cancer was recruited as part of the European Early Lung Cancer (EUELC) project. In 166 patients expression of hTERT mRNA was determined in tumour tissue by quantitative real-time RT-PCR and related to that of a house-keeping gene (PBGD). Of a subgroup of 130 patients tumour-distant normal tissue was additionally available for hTERT mRNA analysis. The correlation between hTERT levels of surgical samples and disease-free survival was determined using a Fine and Gray hazard model. Although hTERT mRNA positivity in tumour tissue was significantly associated with clinical stage (Fisher's exact test p=0.016), neither hTERT mRNA detectability nor hTERT mRNA levels in tumour tissue were associated with clinical outcome. Conversely, hTERT positivity in adjacent normal samples was associated with progressive disease, 28% of patients with progressive disease versus 7.5% of disease-free patients had detectable hTERT mRNA in normal tissue [adjusted HR: 3.60 (1.64-7.94), p=0.0015]. hTERT mRNA level in tumour tissue has no prognostic value for patients with early stage lung cancer. However, detection of hTERT mRNA expression in tumour-distant normal lung tissue may indicate an increased risk of progressive disease.

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As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

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INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2013 evaluation campaign, which consisted of four activities addressing three themes: searching professional and user generated data (Social Book Search track); searching structured or semantic data (Linked Data track); and focused retrieval (Snippet Retrieval and Tweet Contextualization tracks). INEX 2013 was an exciting year for INEX in which we consolidated the collaboration with (other activities in) CLEF and for the second time ran our workshop as part of the CLEF labs in order to facilitate knowledge transfer between the evaluation forums. This paper gives an overview of all the INEX 2013 tracks, their aims and task, the built test-collections, and gives an initial analysis of the results

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Chemically inducible gene switches can provide precise control over gene expression, enabling more specific analyses of gene function and expanding the plant biotechnology toolkit beyond traditional constitutive expression systems. The alc gene expression system is one of the most promising chemically inducible gene switches in plants because of its potential in both fundamental research and commercial biotechnology applications. However, there are no published reports demonstrating that this versatile gene switch is functional in transgenic monocotyledonous plants, which include some of the most important agricultural crops. We found that the original alc gene switch was ineffective in the monocotyledonous plant sugar cane, and describe a modified alc system that is functional in this globally significant crop. A promoter consisting of tandem copies of the ethanol receptor inverted repeat binding site, in combination with a minimal promoter sequence, was sufficient to give enhanced sensitivity and significantly higher levels of ethanol inducible gene expression. A longer CaMV 35S minimal promoter than was used in the original alc gene switch also substantially improved ethanol inducibility. Treating the roots with ethanol effectively induced the modified alc system in sugar cane leaves and stem, while an aerial spray was relatively ineffective. The extension of this chemically inducible gene expression system to sugar cane opens the door to new opportunities for basic research and crop biotechnology.