941 resultados para Leverage points


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We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.

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The study focuses on the public participation during the decision-making process of the High Speed Rail Project (popularly known as TGV) in Portugal. The study analyzes the media references on the topic and its actors in a quantitative and qualitative way from September 2008 to November 2009 anchored in the 2009 Legislatives and Local elections. The work concludes that despite the political polarization around the High Speed Rail Project, contributing to bring it to public debate, it didn’t allow for an improvement in qualitative information that could allow the emergence of an active and informed citizen participation in the debate.

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Trabalho avaliado na unidade “Métodos Interactivos de Participação e Decisão” do Programa Doutoral em Avaliação de Tecnologia na FCT-UNL sob orientação da Profª Lia Vasconcelose do Prof. Nuno Videira. [Relatório entregue em Dezembro de 2011]

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Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.

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In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use–poverty–environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local—highly contextual—development potentials is key to shaping outcomes of the land use–poverty–environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change.

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In October 2008, the 5th Environmental Management for Sustainable Universities (EMSU) international conference was held in Barcelona, Spain. It dealt with the need to rethink how our higher educational institutions are facing sustainability. This special issue has been primarily derived from contributions to that conference. This issue builds upon related academic international publications, which have analysed how to use the critical position of universities to accelerate their pace of working to help to make the transition to truly SUSTAINABLE SOCIETIES! This issue focus is on the ‘softer’ issues, such as changes in values, attitudes, motivations, as well as in curricula, societal interactions and assessments of the impacts of research. Insights derived from the interplay of the ‘softer’ issues with the ‘harder’ issues are empowering academic leaders to effectively use leverage points to make changes in operations, courses, curricula, and research. Those changes are being designed to help their students and faculty build resilient and sustainable societies within the context of climate change, the Decade of Education for Sustainable Development (DESD), and the UN Millennium Development Goals (MDGs). The overall systems approach presented by Stephens and Graham provides a structured framework to systematize change for sustainability in higher education, by stressing on the one hand the need for “learning to learn” and on the other hand by integrating leadership and cultural aspects. The “niche” level they propose for innovative interactions between practitioners such as EMSU is exemplary developed by all of the other documents in this special issue. To highlight some of the key elements of the articles in this issue, there are proposals for new educational methods based in sustainability science, a set of inspirational criteria for SD research activities, new course ranking and assessment methods and results of psychological studies that provide evidence that participatory approaches are the most effective way to change values within university members in order to facilitate the development and sharing of new sustainability norms.

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This nonexperimental, correlational study (N = 283) examined the relation among job fit, affective commitment, psychological climate, discretionary effort, intention to turnover, and employee engagement. An internet-based self-report survey battery of six scales were administered to a heterogeneous sampling of organizations from the fields of service, technology, healthcare, retail, banking, nonprofit, and hospitality. Hypotheses were tested through correlational and hierarchical regression analytic procedures. Job fit, affective commitment, and psychological climate were all significantly related to employee engagement and employee engagement was significantly related to both discretionary effort and intention to turnover. For the discretionary effort model, the hierarchical regression analysis results suggested that the employees who reported experiencing a positive psychological climate were more likely to report higher levels of discretionary effort. As for the intention to turnover model, the hierarchical regression analysis results indicated that affective commitment and employee engagement predicted lower levels of an employee’s intention to turnover. The regression beta weights ranged from to .43 to .78, supporting the theoretical, empirical, and practical relevance of understanding the impact of employee engagement on organizational outcomes. Implications for HRD theory, research, and practice are highlighted as possible strategic leverage points for creating conditions that facilitate the development of employee engagement as a means for improving organizational performance.

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This ex post facto study (N = 209) examined the relationships between employer job strategies and job retention among organizations participating in Florida welfare-to-work network programs and associated the strategies with job retention data to determine best practices. ^ An internet-based self-report survey battery was administered to a heterogeneous sampling of organizations participating in the Florida welfare-to-work network program. Hypotheses were tested through correlational and hierarchical regression analytic procedures. The partial correlation results linked each of the job retention strategies to job retention. Wages, benefits, training and supervision, communication, job growth, work/life balance, fairness and respect were all significantly related to job retention. Hierarchical regression results indicated that the training and supervision variable was the best predictor of job retention in the regression equation. ^ The size of the organization was also a significant predictor of job retention. Large organizations reported higher job retention rates than small organizations. There was no statistical difference between the types of organizations (profit-making and non-profit) and job retention. The standardized betas ranged from to .26 to .41 in the regression equation. Twenty percent of the variance in job retention was explained by the combination of demographic and job retention strategy predictors, supporting the theoretical, empirical, and practical relevance of understanding the association between employer job strategies and job retention outcomes. Implications for adult education and human resource development theory, research, and practice are highlighted as possible strategic leverage points for creating conditions that facilitate the development of job strategies as a means for improving former welfare workers’ job retention.^

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Static state estimators currently in use in power systems are prone to masking by multiple bad data. This is mainly because the power system regression model contains many leverage points; typically they have a cluster pattern. As reported recently in the statistical literature, only high breakdown point estimators are robust enough to cope with gross errors corrupting such a model. This paper deals with one such estimator, the least median of squares estimator, developed by Rousseeuw in 1984. The robustness of this method is assessed while applying it to power systems. Resampling methods are developed, and simulation results for IEEE test systems discussed. © 1991 IEEE.

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Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

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Chronic pain has been often associated with myofascial pain syndrome (MPS), which is determined by myofascial trigger points (MTrP). New features have been tested for MTrP diagnosis. The aim of this study was to evaluate two-dimensional ultrasonography (2D US) and ultrasound elastography (UE) images and elastograms of upper trapezius MTrP during electroacupuncture (EA) and acupuncture (AC) treatment. 24 women participated, aged between 20 and 40 years (M ± SD = 27.33 ± 5.05) with a body mass index ranging from 18.03 to 27.59 kg/m2 (22.59 ± 3.11), a regular menstrual cycle, at least one active MTrP at both right (RTPz) and left trapezius (LTPz) and local or referred pain for up to six months. Subjects were randomized into EA and AC treatment groups and the control sham AC (SHAM) group. Intensity of pain was assessed by visual analogue scale; MTrP mean area and strain ratio (SR) by 2D US and UE. A significant decrease of intensity in general, RTPz, and LTPz pain was observed in the EA group (p = 0.027; p < 0.001; p = 0.005, respectively) and in general pain in the AC group (p < 0.001). Decreased MTrP area in RTPz and LTPz were observed in AC (p < 0.001) and EA groups (RTPz, p = 0.003; LTPz, p = 0.005). Post-treatment SR in RTPz and LTPz was lower than pre-treatment in both treatment groups. 2D US and UE effectively characterized MTrP and surrounding tissue, pointing to the possibility of objective confirmation of subjective EA and AC treatment effects.

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PURPOSE: The aim of this study was to assess the contamination status of endodontic absorbent paper points from sterilized or not sterilized commercial packs, as well as paper points exposed to the dental office environment. METHODS: Twenty absorbent paper points were evaluated for contamination status packed under different conditions: commercial/sterilized pack, commercial/non-sterilized pack, exposed to the clinical environment, and intentionally contaminated (positive control). Contamination was determined qualitatively and quantitatively by aerobiosis, capnophilic growth, and pour plate. The Petri dishes were analyzed with a colony counter, and the results were expressed as colony-forming units. The data were analyzed by Kruskal-Wallis test (α=0.05). RESULTS: No difference in colony-forming units was found among the groups of endodontic absorbent paper points. All groups were contaminated by fungi and bacteria. CONCLUSION: It can be concluded that the sterilization of absorbent endodontic paper points before clinical use should be recommended regardless of commercial presentation

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The HACCP system is being increasingly used to ensure food safety. This study investigated the validation of the control measures technique in order to establish performance indicators of this HACCP system in the manufacturing process of Lasagna Bolognese (meat lasagna). Samples were collected along the manufacturing process as a whole, before and after the CCPs. The following microorganism s indicator (MIs) was assessed: total mesophile and faecal coliform counts. The same MIs were analyzed in the final product, as well as, the microbiological standards required by the current legislation. A significant reduction in the total mesophile count was observed after cooking (p < 0.001). After storage, there was a numerical, however non-significant change in the MI count. Faecal coliform counts were also significantly reduced (p < 0.001) after cooking. We were able to demonstrate that the HACCP system allowed us to meet the standards set by both, the company and the Brazilian regulations, proved by the reduction in the established indicators

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Background Minimal residual disease is an important independent prognostic factor in childhood acute lymphoblastic leukemia. The classical detection methods such as multiparameter flow cytometry and real-time quantitative polymerase chain reaction analysis are expensive, time-consuming and complex, and require considerable technical expertise. Design and Methods We analyzed 229 consecutive children with acute lymphoblastic leukemia treated according to the GBTLI-99 protocol at three different Brazilian centers. Minimal residual disease was analyzed in bone marrow samples at diagnosis and on days 14 and 28 by conventional homo/heteroduplex polymerase chain reaction using a simplified approach with consensus primers for IG and TCR gene rearrangements. Results At least one marker was detected by polymerase chain reaction in 96.4%, of the patients. By combining the minimal residual disease results obtained on days 14 and 28, three different prognostic groups were identified: minimal residual disease negative on days 14 and 28, positive on day 14/negative on day 28, and positive on both. Five-year event-free survival rates were 85%, 75.6%,, and 27.8%, respectively (p<0.0001). The same pattern of stratification held true for the group of intensively treated children. When analyzed in other subgroups of patients such as those at standard and high risk at diagnosis, those with positive B-derived CD10, patients positive for the TEL/AML1 transcript, and patients in morphological remission on a day 28 marrow, the event-free survival rate was found to be significantly lower in patients with positive minimal residual disease on day 28. Multivariate analysis demonstrated that the detection of minimal residual disease on day 28 is the most significant prognostic factor. Conclusions This simplified strategy for detection of minimal residual disease was feasible, reproducible, cheaper and simpler when compared with other methods, and allowed powerful discrimination between children with acute lymphoblastic leukemia with a good and poor outcome.

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Given a compact 2 dimensional manifold M we classify all continuous flows phi without wandering points on M. This classification is performed by finding finitely many pairwise disjoint open phi-invariant subsets {U(1), U(2), ..., U(n)} of M such that U(i=1)(n) (U(i)) over bar = M and each U(i) is either a suspension of an interval exchange transformation, or a maximal open cylinder made up of closed trajectories of phi.