75 resultados para Clustering and objective measures


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During the benthic cultivation process of Mytilus edulis (blue mussels), wild mussel seed is often transplanted from naturally occurring subtidal beds to sheltered in-shore waters to be grown to a commercial size. The survival of these relaid mussels is ultimately a function of their quality and physiological condition upon relaying and it has been recognised that mussels can suffer from a loss in condition following transportation. We investigated whether the process of being transported to ongrowing plots had a negative effect on the physiological health and resultant behaviour of mussels by simulating transportation conditions in a controlled experiment. Mussels were kept, out of water, in plastic piping to recreate translocation conditions and further, we tested if depth held in a ship hold (0, 1.5 and 3 m) and length of time emersed (12, 24 and 48 h) affected mussel condition and behaviour. Physiological condition was assessed by quantifying mussel tissue pH and whole tissue glucose, glycogen, succinate and propionate concentrations. The rate of byssogenesis was also quantified to estimate recovery following a period of re-immersion. The depth at which mussels were held did not affect any of the physiological indicators of mussel stress but short-term byssus production was affected. Mussels held at 3 m produced fewer byssus threads during the first 72 h following re-immersion compared with mussels at 0 m (i.e. not buried) suggesting that depth held can impede recovery following transportation. Duration of emersion affected all stress indicators. Specifically, mussels held out of water for 48 h had a reduced physiological condition compared with those emersed for just 12 h. This work has practical implications for the benthic cultivation industry and based on these results we recommend that mussels are held out of water for less than 24 h prior to relaying to ensure physiological health and resultant condition is preserved.

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Increasingly semiconductor manufacturers are exploring opportunities for virtual metrology (VM) enabled process monitoring and control as a means of reducing non-value added metrology and achieving ever more demanding wafer fabrication tolerances. However, developing robust, reliable and interpretable VM models can be very challenging due to the highly correlated input space often associated with the underpinning data sets. A particularly pertinent example is etch rate prediction of plasma etch processes from multichannel optical emission spectroscopy data. This paper proposes a novel input-clustering based forward stepwise regression methodology for VM model building in such highly correlated input spaces. Max Separation Clustering (MSC) is employed as a pre-processing step to identify a reduced srt of well-conditioned, representative variables that can then be used as inputs to state-of-the-art model building techniques such as Forward Selection Regression (FSR), Ridge regression, LASSO and Forward Selection Ridge Regression (FCRR). The methodology is validated on a benchmark semiconductor plasma etch dataset and the results obtained are compared with those achieved when the state-of-art approaches are applied directly to the data without the MSC pre-processing step. Significant performance improvements are observed when MSC is combined with FSR (13%) and FSRR (8.5%), but not with Ridge Regression (-1%) or LASSO (-32%). The optimal VM results are obtained using the MSC-FSR and MSC-FSRR generated models. © 2012 IEEE.

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Objective To demonstrate the potential value of screening for Down's Syndrome using highly correlated repeated measures of serum markers taken in the first and second trimesters of pregnancy. Design A Monte Carlo simulation study. Population Detection rates and false positive rates relating to the maternal age distribution of England and Wales for the period 1996 to 1998 were obtained using marker distributions from the SURUSS study. Results Screening using first trimester nuchal translucency and repeated measures of uE3 and PAPP-A in the first and second trimester has an estimated false positive rate of 0.3% for an 85% detection rate. This should be compared with the integrated test with an estimated false positive rate of 1.2% for the same detection rate. Conclusionsâ?? The performance of repeated measures screening tests, and their acceptability to women, should be assessed in further prospective studies.

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We evaluated a structured pharmaceutical care program for elderly patients (> 65 yrs) with congestive heart failure (CHF) based on objective measures of disease control, quality of life, and use of health care facilities in a randomized, controlled, longitudinal, prospective clinical trial. The 42 patients in group A received education from a pharmacist on the disease and its treatment, and lifestyle changes that could help control symptoms. Patients also were encouraged to monitor their symptoms and comply with prescribed drug therapy. If necessary, dosage regimens were simplified in liaison with hospital physicians. The 41 control patients (group B) received standard care. The following outcome measures were assessed in all patients at baseline (before the start of the trial) and at 3, 6, 9, and 12 months: 2-minute walk test, blood pressure, body weight, pulse, forced vital capacity, quality of life [disease-specific (Minnesota Living with Heart Failure questionnaire) and generic (SF-36)], knowledge of symptoms and drugs, compliance with therapy, and use of health care facilities (hospital admissions, visits to emergency room, emergency calls). Patients in group A showed improved compliance with drug therapy, which in turn improved their exercise capacity compared with those in group B; education on management of symptoms, lifestyle changes, and dietary recommendations were also of benefit. Group A patients significantly improved knowledge of their drug therapy over the 12-month study and had fewer hospital admissions compared with group B patients. They also had improved outcomes compared with group B, despite the small samples. An extension of this trial to other sites with pooling of results would provide additional evidence of the value of this structured program in elderly patients with CHF.

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The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.

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Climate change during the last five decades has impacted significantly on natural ecosystems and the rate of current climate change is of great concern among conservation biologists. Species Distribution Models (SDMs) have been used widely to project changes in species’ bioclimatic envelopes under future climate scenarios. Here, we aimed to advance this technique by assessing future changes in the bioclimatic envelopes of an entire mammalian order, the Lagomorpha, using a novel framework for model validation based jointly on subjective expert evaluation and objective model evaluation statistics. SDMs were built using climatic, topographical and habitat variables for all 87 lagomorph species under past and current climate scenarios. Expert evaluation and Kappa values were used to validate past and current models and only those deemed ‘modellable’ within our framework were projected under future climate scenarios (58 species). Phylogenetically-controlled regressions were used to test whether species traits correlated with predicted responses to climate change. Climate change is likely to impact more than two-thirds of lagomorph species, with leporids (rabbits, hares and jackrabbits) likely to undertake poleward shifts with little overall change in range extent, whilst pikas are likely to show extreme shifts to higher altitudes associated with marked range declines, including the likely extinction of Kozlov’s Pika (Ochotona koslowi). Smaller-bodied species were more likely to exhibit range contractions and elevational increases, but showing little poleward movement, and fecund species were more likely to shift latitudinally and elevationally. Our results suggest that species traits may be important indicators of future climate change and we believe multi-species approaches, as demonstrated here, are likely to lead to more effective mitigation measures and conservation management. We strongly advocate studies minimising data gaps in our knowledge of the Order, specifically collecting more specimens for biodiversity archives and targeting data deficient geographic regions.

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Clusters of text documents output by clustering algorithms are often hard to interpret. We describe motivating real-world scenarios that necessitate reconfigurability and high interpretability of clusters and outline the problem of generating clusterings with interpretable and reconfigurable cluster models. We develop two clustering algorithms toward the outlined goal of building interpretable and reconfigurable cluster models. They generate clusters with associated rules that are composed of conditions on word occurrences or nonoccurrences. The proposed approaches vary in the complexity of the format of the rules; RGC employs disjunctions and conjunctions in rule generation whereas RGC-D rules are simple disjunctions of conditions signifying presence of various words. In both the cases, each cluster is comprised of precisely the set of documents that satisfy the corresponding rule. Rules of the latter kind are easy to interpret, whereas the former leads to more accurate clustering. We show that our approaches outperform the unsupervised decision tree approach for rule-generating clustering and also an approach we provide for generating interpretable models for general clusterings, both by significant margins. We empirically show that the purity and f-measure losses to achieve interpretability can be as little as 3 and 5%, respectively using the algorithms presented herein.

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This papers examines the use of trajectory distance measures and clustering techniques to define normal
and abnormal trajectories in the context of pedestrian tracking in public spaces. In order to detect abnormal
trajectories, what is meant by a normal trajectory in a given scene is firstly defined. Then every trajectory
that deviates from this normality is classified as abnormal. By combining Dynamic Time Warping and a
modified K-Means algorithms for arbitrary-length data series, we have developed an algorithm for trajectory
clustering and abnormality detection. The final system performs with an overall accuracy of 83% and 75%
when tested in two different standard datasets.

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Informal caregiving can be a demanding role which has been shown to impact on physical, psychological and social wellbeing. Methodological weaknesses including small sample sizes and subjective measures of mental health have led to inconclusive evidence about the relationship between informal caregiving and mental health. This paper reports on a study carried out in a UK region which investigated the relationship between informal caregiving and mental ill health. The analysis was conducted by linking three datasets, the Northern Ireland Longitudinal Study, the Northern Ireland Enhanced Prescribing Database and the Proximity to Service Index from the Northern Ireland Statistics and Research Agency. Our analysis used both a subjective measure of mental ill health, i.e. a question asked in the 2011 Census, and an objective measure, whether the respondents had been prescribed antidepressants by a General Practitioner between 2010 and 2012. We applied binary logistic multilevel modelling to these two responses to test whether, and for what sub-groups of the population, informal caregiving was related to mental ill health. The results showed that informal caregiving per se was not related to mental ill health although there was a strong relationship between the intensity of the caregiving role and mental ill health. Females under 50, who provided over 19 hours of care, were not employed or worked part-time and who provided care in both 2001 and 2011 were at a statistically significantly elevated risk of mental ill health. Caregivers in remote areas with limited access to shops and services were also at a significantly increased risk as evidenced by prescription rates for antidepressants. With community care policies aimed at supporting people to remain at home, the paper highlights the need for further research in order to target resources appropriately.

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Background: The aim of the SPHERE study is to design, implement and evaluate tailored practice and personal care plans to improve the process of care and objective clinical outcomes for patients with established coronary heart disease (CHD) in general practice across two different health systems on the island of Ireland.CHD is a common cause of death and a significant cause of morbidity in Ireland. Secondary prevention has been recommended as a key strategy for reducing levels of CHD mortality and general practice has been highlighted as an ideal setting for secondary prevention initiatives. Current indications suggest that there is considerable room for improvement in the provision of secondary prevention for patients with established heart disease on the island of Ireland. The review literature recommends structured programmes with continued support and follow-up of patients; the provision of training, tailored to practice needs of access to evidence of effectiveness of secondary prevention; structured recall programmes that also take account of individual practice needs; and patient-centred consultations accompanied by attention to disease management guidelines.

Methods: SPHERE is a cluster randomised controlled trial, with practice-level randomisation to intervention and control groups, recruiting 960 patients from 48 practices in three study centres (Belfast, Dublin and Galway). Primary outcomes are blood pressure, total cholesterol, physical and mental health status (SF-12) and hospital re-admissions. The intervention takes place over two years and data is collected at baseline, one-year and two-year follow-up. Data is obtained from medical charts, consultations with practitioners, and patient postal questionnaires. The SPHERE intervention involves the implementation of a structured systematic programme of care for patients with CHD attending general practice. It is a multi-faceted intervention that has been developed to respond to barriers and solutions to optimal secondary prevention identified in preliminary qualitative research with practitioners and patients. General practitioners and practice nurses attend training sessions in facilitating behaviour change and medication prescribing guidelines for secondary prevention of CHD. Patients are invited to attend regular four-monthly consultations over two years, during which targets and goals for secondary prevention are set and reviewed. The analysis will be strengthened by economic, policy and qualitative components.

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BACKGROUND AND PURPOSE: Elevated plasma homocysteine level has been associated with increased risk for cardiovascular and cerebrovascular disease. Variation in the levels of this amino acid has been shown to be due to nutritional status and methylenetetrahydrofolate reductase (MTHFR) genotype. METHODS: Under a case-control design we compared fasting levels of homocysteine and MTHFR genotypes in groups of subjects consisting of stroke, vascular dementia (VaD), and Alzheimer disease patients and normal controls from Northern Ireland. RESULTS: A significant increase in plasma homocysteine was observed in all 3 disease groups compared with controls. This remained significant after allowance for confounding factors (age, sex, hypertension, cholesterol, smoking, creatinine, and nutritional measures). MTHFR genotype was not found to influence homocysteine levels, although the T allele was found to increase risk for VaD and perhaps dementia after stroke. CONCLUSIONS: We report that moderately high plasma levels of homocysteine are associated with stroke, VaD, and Alzheimer disease. This is not due to vascular risk factors, nutritional status, or MTHFR genotype

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Angiotensin converting enzyme inhibitors (ACEis) are widely used anti-hypertensive agents that are also reported to have positive effects on mood and cognition. The present study examined the influence of the ACEi, perindopril, on cognitive performance and anxiety measures in rats. Two groups of rats were treated orally for one week with the ACEi, perindopril, at doses of 0.1 and 1.0mg/kg/day. Learning was assessed by the reference memory task in the water maze, comparing treated to control rats. Over five training days both perindopril-treated groups learnt the location of the submerged platform in the water maze task significantly faster than control rats. A 60s probe trial on day 6 showed that the 1.0mg/kg/day group spent significantly longer time in the training quadrant than control rats. This improved performance in the swim maze task was not due to the effect of perindopril on motor activity or the anxiety levels of the rats as perindopril-treated and control animals behaved similarly in activity boxes and on the elevated+maze. These results confirm the anecdotal human studies that ACEis have a positive influence on cognition and provide possibilities for ACEis to be developed into therapies for memory loss.

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Osteoporosis (OP) is one of the most prevalent bone diseases worldwide with bone fracture the major clinical consequence. The effect of OP on fracture repair is disputed and although it might be expected for fracture repair to be delayed in osteoporotic individuals, a definitive answer to this question still eludes us. The aim of this study was to clarify the effect of osteoporosis in a rodent fracture model. OP was induced in 3-month-old rats (n = 53) by ovariectomy (OVX) followed by an externally fixated, mid-diaphyseal femoral osteotomy at 6 months (OVX group). A further 40 animals underwent a fracture at 6 months (control group). Animals were sacrificed at 1, 2, 4, 6, and 8 weeks postfracture with outcome measures of histology, biomechanical strength testing, pQCT, relative BMD, and motion detection. OVX animals had significantly lower BMD, slower fracture repair (histologically), reduced stiffness in the fractured femora (8 weeks) and strength in the contralateral femora (6 and 8 weeks), increased body weight, and decreased motion. This study has demonstrated that OVX is associated with decrease in BMD (particularly in trabecular bone) and a reduction in the mechanical properties of intact bone and healing fractures. The histological, biomechanical, and radiological measures of union suggest that OVX delayed fracture healing. (C) 2007 Orthopaedic Research Society. Published by Wiley Periodicals.

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Objective: The aim was to investigate whether there was an association between periodontitis or tooth loss in a homogeneous group of 60-70-year-old Western European men and either a sustained high or low level of C-reactive protein (CRP).
Material and Methods: Men enrolled in a cohort study of cardiovascular disease in Northern Ireland were screened in 1990-1994 and rescreened in 2001-2004, when a periodontal examination was completed. High-sensitivity CRP was measured from fasting blood samples. There were 806 men with six or more teeth who had either a high level (>3 mg/l) or a lower level of CRP at both time points. Multivariate analysis was carried out using logistic regression with adjustment for possible confounders. Models were constructed with the CRP level as the outcome variable and various measures of periodontal status (low and high threshold periodontitis) or tooth loss as predictor variables. Confounders included in the analysis were known cardiovascular risk factors of age, smoking, diabetes, BMI and socioeconomic status.
Results: There were 67 men who had a high value of CRP (>3 mg/l) and 739 men who had a CRP value =3 mg/l at both time points. The unadjusted odds ratio (OR) for advanced periodontitis to be associated with high CRP was 3.62, p=0.0003. The association was somewhat attenuated but remained significant (OR=2.49, p=0.02) after adjustment for confounders. A high level of tooth loss was also associated with high CRP with an adjusted OR of 2.17, p=0.008. Low threshold periodontitis was not associated with the level of CRP.
Conclusion: There was an association between advanced periodontitis and elevated CRP levels as measured at two time points at a 10-year interval in the 60-70-year-old European males investigated. This association was adjusted for various cardiovascular risk factors. There was also an association between high levels of tooth loss and high CRP in the men studied.

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Background and Purpose—Severe upper limb paresis is a major contributor to disability after stroke. This study investigated the efficacy of a new nonrobotic training device, the Sensorimotor Active Rehabilitation Training (SMART) Arm, that was used with or without electromyography-triggered electrical stimulation of triceps brachii to augment elbow extension, permitting stroke survivors with severe paresis to practice a constrained reaching task.

Methods—A single-blind, randomized clinical trial was conducted with 42 stroke survivors with severe and chronic paresis. Thirty-three participants completed the study, of whom 10 received training using the SMART Arm with electromyography-triggered electrical stimulation, 13 received training using the SMART Arm alone, and 10 received no intervention (control). Training consisted of 12 1-hour sessions over 4 weeks. The primary outcome measure was “upper arm function,” item 6 of the Motor Assessment Scale. Secondary outcome measures included impairment measures; triceps muscle strength, reaching force, modified Ashworth scale; and activity measures: reaching distance and Motor Assessment Scale. Assessments were administered before (0 weeks) and after training (4 weeks) and at 2 months follow-up (12 weeks).

Results—Both SMART Arm groups demonstrated significant improvements in all impairment and activity measures after training and at follow-up. There was no significant difference between these 2 groups. There was no change in the control group.

Conclusions—Our findings indicate that training of reaching using the SMART Arm can reduce impairment and improve activity in stroke survivors with severe and chronic upper limb paresis, highlighting the benefits of intensive task-oriented practice, even in the context of severe paresis.