882 resultados para Symptom Clusters
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A busca por maior competitividade frente ao mercado cada vez mais concorrido, a perseguição pela maximização dos lucros nas organizações, e as maneiras para tornar as organizações mais eficientes são assuntos largamente debatidos em discussões nos ambientes empresariais e acadêmicos, áreas em que a administração é requerida para analisar o universo de possibilidades em busca dos objetivos acima. Principalmente sobre as pequenas e médias empresas (PME), os impactos dos custos decorrentes de falta de infraestruturas adequadas em transportes, movimentação de materiais e em logística em geral, tornam estas organizações menos competitivas. Uma das alternativas que deve ser apresentada é um agrupamento destas organizações em um mesmo espaço físico, os denominados clusters, a fim de compartilharem alguns destes custos, além de experiências para atingirem alguns ganhos também em escala. Na logística, existe a possibilidade de compartilhamento de diversos serviços, onde deverá ser identificada boa parte do potencial de ganho com este modelo, que é aplicado para diversos segmentos inclusive ao redor do mundo. Em especial no Brasil onde a carga tributária é elevada e muito complexa, quando se opta pelo modelo de cluster, haverá ganhos em escala inclusive na tributação fiscal das movimentações de mercadorias. Através do levantamento bibliográfico e a comparação de dados de diversos artigos e de instituições públicas e privadas, objetiva-se apresentar as vantagens das operações no modelo cluster, a possibilidade dos ganhos pelo cooperativismo existente nestes empreendimentos entre outras formas de benefícios possíveis na logística compartilhada pelas empresas do cluster, além de possíveis desvantagens e limitações. .
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This paper examines the link between cluster development and inward foreign direct investment. The conventional policy approach has been to assume that inward foreign direct investment (FDI) can stimulate significant clustering activity, thus generating significant spillovers. This paper, however, questions this and shows that, while clusters can generate significant productivity spillovers from FDI, this only occurs in pre-existing clusters. Further, the paper demonstrates that foreign-owned firms that enter clusters also appropriate spillovers when domestic firms undertake investment, raising the possibility that clusters are important locations for so called technology, or knowledge sourcing activities by MNEs. © 2006 Oxford University Press.
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Book review
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This study investigated whether Negative Affectivity (NA) causes bias in self-report measures of activity limitations or whether NA has a real, non-artifactual association with activity limitations. The Symptom Perception Hypothesis (NA negatively biases self-reporting), Disability Hypothesis (activity limitations cause NA) and Psychosomatic Hypothesis (NA causes activity limitations) were examined longitudinally using both self-report and objective activity limitations measures. Participants were 101 stroke patients and their caregivers interviewed within two weeks of discharge, six weeks later and six months post-discharge. NA and self-report, proxy-report and observed performance activity (walking) limitations were assessed at each interview. NA was associated with activity limitations across measures. Both the Disability and Psychosomatic Hypotheses were supported: initial NA predicted objective activity limitations at six weeks but, additionally, activity limitations at six weeks predicted NA at six months. These results suggest that NA both affects and is affected by activity limitations and does not simply influence reporting.
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The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.
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Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.
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Comprehensive coverage of all aspects of Michael Porter's works Contributions from leading authorities across the disciplines Contains response from Porter Harvard professor, Michael Porter has been one of the most influential figures in strategic management research over the last three decades. He infused a rigorous theoretical framework of industrial organization economics with the then still embryonic field of strategic management and elevated it to its current status as an academic discipline. Porter's outstanding career is also characterized by its cross-disciplinary nature. Following his most important work on strategic management, he then made a leap to the policy side and dealt with a completely different set of analytical units. More recently he has made a foray into inner city development, environmental regulations, and health care services. Throughout these explorations Porter has maintained his integrative approach, seeking a road that links management case studies and the general model building of mainstream economics. With expert contributors from a range of disciplines including strategic management, economic development, economic geography, and planning, this book assesses the contribution Michael Porter has made to these respective disciplines. It clarifies the sources of tension and controversy relating to all the major strands of Porter's work, and provides academics, students, and practitioners with a critical guide for the application of Porter's models. The book highlights that while many of the criticisms of Porter's ideas are valid, they are almost an inevitable outcome for a scholar who has sought to build bridges across wide disciplinary valleys. His work has provided others with a set of frameworks to explore in more depth the nature of competition, competitive advantage, and clusters from a range of vantage points.
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Pain is a ubiquitous yet highly variable experience. The psychophysiological and genetic factors responsible for this variability remain unresolved. We hypothesised the existence of distinct human pain clusters (PCs) composed of distinct psychophysiological and genetic profiles coupled with differences in the perception and the brain processing of pain. We studied 120 healthy subjects in whom the baseline personality and anxiety traits and the serotonin transporter-linked polymorphic region (5-HTTLPR) genotype were measured. Real-time autonomic nervous system parameters and serum cortisol were measured at baseline and after standardised visceral and somatic pain stimuli. Brain processing reactions to visceral pain were studied in 29 subjects using functional magnetic resonance imaging (fMRI). The reproducibility of the psychophysiological responses to pain was assessed at 1 year. In group analysis, visceral and somatic pain caused an expected increase in sympathetic and cortisol responses and activated the pain matrix according to fMRI studies. However, using cluster analysis, we found 2 reproducible PCs: at baseline, PC1 had higher neuroticism/anxiety scores (P ≤ 0.01); greater sympathetic tone (P < 0.05); and higher cortisol levels (P ≤ 0.001). During pain, less stimulus was tolerated (P ≤ 0.01), and there was an increase in parasympathetic tone (P ≤ 0.05). The 5-HTTLPR short allele was over-represented (P ≤ 0.005). PC2 had the converse profile at baseline and during pain. Brain activity differed (P ≤ 0.001); greater activity occurred in the left frontal cortex in PC1, whereas PC2 showed greater activity in the right medial/frontal cortex and right anterior insula. In health, 2 distinct reproducible PCs exist in humans. In the future, PC characterization may help to identify subjects at risk for developing chronic pain and may reduce variability in brain imaging studies. © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.
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Self-sustained spin clusters are analytically linked to ergodicity breaking in fully connected Ising and Sherrington-Kirkpatick (SK) models, relating the less understood spin space to the well understood state space. This correspondence is established through the absence of clusters in the paramagnetic phase, the presence of one dominant cluster in the Ising ferromagnet, and the formation of nontrivial clusters in SK spin glass. Yet unobserved phenomena are also revealed such as a first order phase transition in cluster sizes in the SK ferromagnet. The method could be adapted to investigate other spin models. © 2013 American Physical Society.
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Purpose: Ind suggests front line employees can be segmented according to their level of brand-supporting performance. His employee typology has not been empirically tested. The paper aims to explore front line employee performance in retail banking, and profile employee types. Design/methodology/approach: Attitudinal and demographic data from a sample of 404 front line service employees in a leading Irish bank informs a typology of service employees. Findings: Champions, Outsiders and Disruptors exist within retail banking. The authors provide an employee profile for each employee type. They found Champions amongst males, and older employees. The highest proportion of female employees surveyed were Outsiders. Disruptors were more likely to complain, and rated their performance lower than any other employee type. Contrary to extant literature, Disruptors were more likely to hold a permanent contract than other employee types. Originality/value: The authors augment the literature by providing insights about the profile of three employee types: Brand Champions, Outsiders and Disruptors. Moreover, the authors postulate the influence of leadership and commitment on each employee type. The cluster profiles raise important questions for hiring, training and rewarding front line banking employees. The authors also provide guidelines for managers to encourage Champions, and curtail Disruptors. © Emerald Group Publishing Limited.
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The undisputed link of the agricultural sector with regional economies, along with the increased competition, fosters agri-business companies to rethink their business philosophy and to transform from isolated firms to members of more extended business formations. The paper examines a particular type of business network, the cluster. It focuses on the concept of clusters and on cluster-based strategies in the context of agriculture. In particular, the paper explores the value of clusters by taking into consideration the particularities of the agricultural sector. Potential benefits and constraints of agri-business cluster development are also presented.
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ABSTRACT: Purpose. Virtual reality devices, including virtual reality head-mounted displays, are becoming increasingly accessible to the general public as technological advances lead to reduced costs. However, there are numerous reports that adverse effects such as ocular discomfort and headache are associated with these devices. To investigate these adverse effects, questionnaires that have been specifically designed for other purposes such as investigating motion sickness have often been used. The primary purpose of this study was to develop a standard questionnaire for use in investigating symptoms that result from virtual reality viewing. In addition, symptom duration and whether priming subjects elevates symptom ratings were also investigated. Methods. A list of the most frequently reported symptoms following virtual reality viewing was determined from previously published studies and used as the basis for a pilot questionnaire. The pilot questionnaire, which consisted of 12 nonocular and 11 ocular symptoms, was administered to two groups of eight subjects. One group was primed by having them complete the questionnaire before immersion; the other group completed the questionnaire postviewing only. Postviewing testing was carried out immediately after viewing and then at 2-min intervals for a further 10 min. Results. Priming subjects did not elevate symptom ratings; therefore, the data were pooled and 16 symptoms were found to increase significantly. The majority of symptoms dissipated rapidly, within 6 min after viewing. Frequency of endorsement data showed that approximately half of the symptoms on the pilot questionnaire could be discarded because <20% of subjects experienced them. Conclusions. Symptom questionnaires to investigate virtual reality viewing can be administered before viewing, without biasing the findings, allowing calculation of the amount of change from pre- to postviewing. However, symptoms dissipate rapidly and assessment of symptoms needs to occur in the first 5 min postviewing. Thirteen symptom questions, eight nonocular and five ocular, were determined to be useful for a questionnaire specifically related to virtual reality viewing using a head-mounted display.