1,023 research outputs found

    Urban Design of Bristol Waterfront, Lower Thames Street

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    Collaboration with the Town of Bristol in the fall of 2013 when students in ARCH 415, Advanced Design Studio – Urban, under the guidance of Professor Ulker Copur, studied the waterfront area along the west side of Thames Street, from State Street south to the armory in Bristol, Rhode Island, including the continuation of a public boardwalk through the area linking up with the adjacent properties. The designs created by students would be used to guide the town in developing a master plan for the area and the new Bristol Maritime Welcome Center

    The relationship of molecular structure to mesomorphism in some aromatic esters of diphenols

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    Matter exists principally in three distinct states -crystalline solid, isotropic liquid, and gas. Individual units in both the liquid and gaseous state are more or less mobile, while in the crystalline solid state these units are held in the rigid, three dimensional configuration of a crystalline lattice. Consequently, the crystalline solid is regarded as the most highly ordered of the three states of matter. Heating a crystalline solid increases the thermal vibrations and the ordered arrangement begins to break down. The solid passes from the highly organized crystalline state to the disorganized isotropic liquid. In 1888, Friedrich Reinitzer discovered that, on melting cholesteryl benzoate, the solid collapsed to form a turbid liquid which, on further heating, gave the normal, transparent, isotropic liquid.1 This turbid liquid exhibited properties of both liquid and crystalline forms of matter; the substance was both birefringent (a property of crystals) and fluid. Although Reinitzer is credited with discovering the liquid crystalline phenomenon, Lehmann2 was first to suggest the name "liquid crystals", and to describe their properties. Later, Friedel3,4 proposed the term "mesomorphs" or "mesophases" for substances that were neither isotropic liquids nor crystalline solids. Since both terminologies are generally accepted, the terms liquid crystal and mesomorph, or liquid crystallinity and mesomorphism, will be used interchangeably throughout this thesis

    Laboratory testing for wear performance of selected wood floor finishes

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    Eight wood floor finishes were applied to quarter-sawn, red oak flooring blocks and, along with a factory finished block, were tested under laboratory conditions to determine the degree of wear of each of the finishes. A loss in film thickness of the finish was considered wear. Test blocks included four replicates each of polyurethane, vinyl, epoxy, amino resin, lacquer, shellac, varnish, penetrating seal, and a prefinished specimen. Blocks were tested on the Simulated Human Wear Producing Machine consisting of a treadmill and cam-operated legs and feet developed by Dr. Henry Bowen and his engineering students of the Biological and Agricultural Engineering Department at North Carolina State University in Raleigh. A Zeiss Light-Section Microscope was used to measure the film thickness of finishes. Four measurements were recorded from predetermined locations and the mean computed for each test specimen of each finish before testing and during testing at one, two, four, five, six, and eight hour intervals. Blocks were rotated on the machine after each measurement period

    The role of costs in tax evasion : non-selfish attitudes or percuniary motivations?

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    In this thesis we examined the role of non-selfish attitudes in determining tax evasion. We contrasted the argument of the standard approach according to which tax payers choose the amount of income to declare (being motivated merely by monetary considerations) with the idea that some individuals may be inherently honest and would never evade even if it paid them to do so.The first two chapters set the scene for the ideas we developed in the rest of the thesis. We reviewed the standard portfolio model, and drew our attention to three predictions that appeared to be inconsistent with empirical evidence: a) A rise in the tax rate causes a decrease in the amount of tax evasion. This result is counter-intuitive and has little empirical support. b) If all agents maximised expected utility, it is difficult to explain why some evade and others do not. Assuming fine rates and detection rates to be the same across all agents, different degrees of risk aversion explain different amounts of tax evaded but do not explain why some people evade and others do not. c) There is a general view that, given actual fine rates and the probability of audit, the amount of evasion undertaken is too low, in relation to what the standard model predicts. This idea is not to our knowledge fully argued, in that it is unclear exactly how much evasion the standard model does predict. Also it is unclear how large empirical estimates of evasion actually are in the context of the portfolio model. Actual evasion must be compared with the amount of income that an agent is able to hide from the tax authority.We considered the economic literature on the role of morals in tax evasion together with some empirical evidence. In particular, we focused on the Myles and Naylor model which considers tax compliance as a social custom, and on Bordignon's analysis, which examines the role of fairness considerations in deterring tax evasion. In Myles and Naylor's model the issue of the effect of an increase in the tax rate on tax evasion is not completely resolved. It is possible to get an increase in tax evasion after an increase in the tax rate, but this will occur only because those who were previously honest start to evade, i.e. more people become evaders. Existing evaders would still decrease tax evasion after an increase in the tax rate, as in the Yitzhaki model. Hence the Myles and Naylor analysis offers only a partial resolution to this puzzling prediction. Bordignon's analysis is more satisfactory in this respect: in his model people can end up evading more, when the tax rises, even when they were previously evading. This happens when individuals perceive the increase in the tax rate as unfair and consequently are prepared to evade more than previously.Hence the puzzling prediction concerning the effect of a change in the tax rate is not completely resolved by the models on social interactions. We also pointed out that the argument that some people are inherently honest is vulnerable to evolutionary forces. Once we allow preferences to change and selfish attitudes to be present in the social environment, altruistic behaviour can be undermined by an increased tendency to "selfishness". Furthermore the simple arguments we gave suggested some difficulties in explaining how "honest" and "utility maximising" individuals could coexist in equilibrium. This general argument is not new to economics, having appeared as long back as 1959 in Tullock's famous paper on voting.The argument that some people may be inherently honest and not evade even if it would pay to do so is not completely satisfactory. In the models we considered people are assumed to be motivated by non-selfish considerations, some sort of predisposition to altruistic behaviour seems to be taken as given, rather than explained. There has been a large amount of literature that suggests some form of "altruism" motivates economic decisions. However the models and evidence that point in this direction suggest that the stability of altruistic or co-operative behaviour relies on some form of reciprocity. This argument for altruism is weaker in the context of tax evasion, however. Tax evasion is by its nature a hidden activity and individuals cannot observe each other. Moreover a single taxpayer can be reciprocal only with an anonymous group. Hence reciprocity considerations and punishment of cheaters are likely to be a lot less effective than in many of the cases studied. In the light of this, the question of why individuals should consider tax compliance as part of a social custom remains an open question.Empirical evidence on this issue is rather thin, in that most of empirical studies do not consider this question directly. From the studies we discussed, the evidence on the role of morals is not compelling. More compelling is the role of opportunities and costs of evasion in determining tax compliance. Curiously this issue has been neglected by the literature in the standard portfolio model. Here the only cost for evading is the fine, which is incurred only in case of detection.We explored the idea that costs or opportunities rather than willingness to evade might determine evaders' behaviour: some people may not evade simply because it is too costly or because they do not have the opportunity to do so. By introducing a minor modification to the standard approach, to allow for a cost element in evasion, we get some different results. In particular we show that it is possible to predict an increase in tax evasion after an increase in the tax rate, without relying on any particular psychological motivation. It is also possible to get a mixed outcome of evaders and non-evaders, even if individuals have the same income and face the same probability of detection. Typically, evaders are less risk averse than nonevaders. Different degrees of risk aversion lead to different choices on whether or not to evade. This was not a characteristic of the standard model.In Chapter 5 we analysed the optimal audit policy when taxpayers have different opportunities to evade. The analysis can be extended in various ways: 1) by considering different sizes for the two groups of tax payers; 2) by allowing individuals to choose the group to which they belong. This pursues the idea developed by Cowell (1985). 3) The choice of the tax rate could be endogenised, to allow more interaction among the taxpayer, the tax authority and tax enforcement agency. This would obviously require an explicit social welfare based approach. 4) It is also possible that the government could directly affect evasion by controlling the cost of compliance. In particular it could be interesting to examine how much of the compliance cost should be borne by the government and how much by the individual.These are directions for possible future research. NoteThe last chapter of the thesis is joint work with Thibaud Vergé at CMPO

    Collaborative Research between Aston Research Centre for Healthy Ageing (ARCHA) and the ExtraCare Charitable Trust

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    Executive Summary A Longitudinal evaluation of the ExtraCare Approach 1.0 Introduction This report consists of a summary of the full findings. Throughout the report the emphasis is on key learning points: what are the implications of the findings and what could be further developed? ExtraCare management have contributed with a brief summary of their responses or plans to emphasise the collaborative nature of this project, to be found in Section 13.0 of the document. Original objectives: We set out with the overall objective of evaluating whether the ExtraCare approach gives positive outcomes for healthy ageing which result in measurable health and social care cost savings. In a longitudinal study, 162 new residents are compared against 39 control participants. We took measures of health, well-being, cognitive ability and mobility at entry, 3, 12 and 18 months. Qualitative data were gathered using focus groups, interviews and case studies. People were additionally invited to keep a diary to record activities. Outcomes also include health and social care usage and costs to contribute to answering the original question. ExtraCare villages and schemes taking part: Fourteen Villages and Schemes took part in the project. 2.0 Numbers of people taking part Initial targets for recruitment of 160 new residents and 25 control participants were slightly exceeded (162 and 33 respectively), although ExtraCare well-being data at baseline was only available for 151 of these. Over the centres used, 17% of new residents took part. By 18 months there were 108 ExtraCare and 29 control participants in the study for the Aston assessments (69 and 29 respectively for well-being data. The attrition is indicated by the difference between initial and final Aston assessments, whereas the difficulties in getting complete well-being (health) data are illustrated by the difference between the final Aston and final well-being data (108-69 = 39 missing well-being assessments). For the crucial 12 month health data (NHS or Care use are measured over 12 months) there are 96 ExtraCare residents (as against 127 residents in the Aston assessments, that is, 31 missing due to missing well-being assessments). There are 666 Aston assessments and 530 well-being assessments across the four time points. For qualitative data we conducted two or three focus groups at eight sites (total of 74 participants). We individually interviewed six residents within 2-5 months of moving into ExtraCare, then at 6 and 18 months after moving in. This was the only longitudinal component of the qualitative work. Three Case studies were conducted which included interviews and observation within the ExtraCare site. We interviewed two managers formally and when on site met with managers and staff groups to discuss general issues. Attrition: 40% of ExtraCare and 29% of Control participants left the study before completion. With our longitudinal design feature of periodically adding in new volunteers with matched duration of residence, this resulted in overall attrition of 29% (33.3% for residents, 6% for controls), comparing favourably with other similar studies. 33% attrition was anticipated in calculations of sample size. Attrition was selective to participants who were less well. Twelve ExtraCare volunteers died during the period (7.4%) and 14 stated their own or partner’s illness as a reason for not continuing. One qualitative interview volunteer died between the second and third meeting. Those lost to sample were no older than those still available at 18 months. Data summary and challenges: There were some challenges with the ExtraCare Well-being Advisors’ data entry throughout the study which did eventually result in some loss of data, resulting in a mismatch between numbers with full Aston data and those with full well-being data, despite our best efforts and those of the Well-being Advisors. One of the most significant issues was gaps and changes in well-being staffing. Additional financial resources were authorised by ExtraCare to ensure that some of the missing assessments could be carried out where there was a longer term staffing vacancy. Nevertheless, there are still sufficient numbers for most of the analyses planned. ExtraCare was already planning a new centrally stored and more user-friendly data base, so any future data will be easier to use for all concerned. Further description of initial sample: ExtraCare participants were significantly older than controls on average, had more chronic illnesses and differed in terms of socio-economic groupings such that there were fewer professional and higher management and more people with unskilled occupational backgrounds. Control group participants perceived their health to be significantly better than did ExtraCare participants at baseline, and had fewer care needs or functional limitations. Cognitive function and emotional well-being differed between the groups at baseline, even controlling for age differences. There were proportionately more men in the ExtraCare sample than in the Control sample (38.3% as compared with 25.8%). 3.0 Summary from the Diary data 57 ExtraCare and 22 control participants agreed at baseline to keep a diary of their activities over the period, down to 35 and 12 respectively by 18 months. Number of activities was categorised broadly into social, physical and intellectual activity types. There was significant increase in activities over the first 3 months in all categories, but then a levelling off or decrease. For the full duration, only social activity increase remained significant. Given our understanding of the benefits of physical, intellectual and social engagement, these findings indicate a need for continued efforts to involve people, support them to get involved, and listen to what they would like in terms of activities. At baseline, there were five people who reported no activities of any nature but there were none at any subsequent time period. 4.0 Summary from the Qualitative data The aim of the qualitative arm of this study was to try to understand residents’ perspectives and experiences of daily life in ExtraCare. We approached the data with openness and regarded participants as experts of their own experience. It is important to emphasise that whether residents’ accounts of life in ExtraCare are ‘true’ or not, they are real to them and can tell us important things about perceptions and feelings. As well as gaining accounts from residents we also met with managers and conducted observations when visiting each of the eight sites in our sample. Sample description: We aimed to gather data from a range of residents and staff. A total of 144 people (131 ExtraCare residents) took part in the qualitative components of the study. Of the 6 focus group resident participants, 83 were in villages and 48 in schemes. Of the six interview participants, three were in receipt of care or social support, one had private care, one was cared for by his wife, and one had no care. All reported at least one significant health concern. Overview of findings: The focus groups generated some rich data around how ExtraCare had changed over time but also whether initial expectations were maintained. We focus on three areas which have shown to be consistent areas of concern to residents of ExtraCare taking part in focus groups and interviews: 1. connectivity in and beyond ExtraCare; 2. perceptions of change in ExtraCare; 3. negotiating transitions and increasing needs. • Volunteering was experienced positively by some as a way of connecting to others in the ExtraCare community, or as a “new lease of life”; for some it was something they felt unable to do and therefore marginalised them from the ‘able’ residents. • Some residents retained connections from the wider community and were able to maintain friendships; others struggled to meet people and felt lonely within the ExtraCare community. • There was a feeling of change at ExtraCare among residents who had lived there a long time. Some of this was financial but other aspects were about a perceived culture shift in the organisation. • Residents’ sense of well-being may come from experiential activities, i.e. finding enjoyment in other people’s activities or through reading or watching television. • Domiciliary care provided can be experienced as a boost of independence to set one free to do activities one enjoys rather than worrying about the mundane activities of everyday life. • Some residents expressed reticence to seek care perhaps through guilt around their own sense of duty to care for a spouse or through embarrassment or pride. • Seeking care was perceived by some as letting go of one’s independence. Identity: There were less obvious subjective changes (or changes at the level of identity) in which residents sought to maintain inclusion in mainstream ExtraCare life and be seen as independent and self-sufficient, but were perhaps struggling to do so. This may not be consciously registered, but some perceptions of changes and decline in ExtraCare raised may relate to transitions in identity and subjectivity. However, in some locations during the period there were changes in provision of care due to Local Authority changing contracting arrangements. Some complaints may be well founded, of course, but there is also a need to listen to residents’ complaints (against ExtraCare management and against other residents) as markers of difficult transitions, requiring emotional support. 5.0 Changes across time in the key psychological and functional measures The most dramatic differences occurred in the early months after moving in, detailed in previous reports. Now there are data at four time points, we can use growth curve modelling to examine effects of time. The analyses employed a set of complex statistical controls for attrition, age differences and in some circumstances for ceiling effects (healthy people having no reported problems on some measures, e.g. Activities of Daily Living measures). As such, great care has been taken to ensure the reliability of findings. Effects over time which were different to control group changes (that is, ExtraCare effects): There were significant continuous improvements across the period in depression, perceived health, memory and autobiographical memory, in a way that was significantly different from the way the measure changed over time for the control group. Positive Effects over time which were not significantly different from control group changes: These are changes that we need to know about but which are not unique to ExtraCare residents. This was the case for: anxiety, communication limitations and fluency (executive function). Variables which varied with age in the control group but not for the residents: This was the case for: Instrumental Activities of Daily living (IADL) and Social Function limitations. ExtraCare may be reducing the normally expected change in function with increasing age. This is also a feature of the fact that decisions to move into ExtraCare are usually needs related, rather than age related. The two most important implications are that: • some factors can be changed: decline is not inevitable and improvement is possible even in variables that commonly decline with increasing age, given a supportive environment; • Age itself is less important than health in terms of determining need for support and potential decline 6.0 Well-being data Comparisons here are focussed on Baseline to 12 month data. Social care costs: 19% of the sample were in receipt of care at both time points. ExtraCare costs an average of £427.98 less per person per annum than comparative local authority charges. This difference is greater at higher levels of care, and varies according to local authority costs in each location. For the people who were in the sample at both time points, the difference reduced from £414.61 to £363.77. Savings for the more expensive levels of care increase over time. NHS Costs – Comparing EC and Control Participants: Total NHS costs were estimated for each participant, including practice and district nurse, GP and outpatient appointments as well as admissions. Average ExtraCare resident NHS costs reduced by 47% over 12 months. Control NHS costs reduced by 14.1%. BUT when you control for the fact that the more poorly are the people who left the sample this is a 38% reduction, (still a significant reduction). This equates to an average saving of £1114.94 per person per year. In using this figure to scale up for the whole population, it should be borne in mind that this is probably a maximum, e.g. we did not assess people who do not have capacity to consent, and we may surmise that many very poorly people do not take part at all. Costs for these people may not have shown reductions to the same extent. Health profile Medications, illnesses and lifestyle: ExtraCare participants took more prescribed medications than did controls and had a significantly greater number of chronic illnesses at baseline. However, this was related to the age difference in the samples, rather than any other difference between the groups. There were subtle differences in prevalence of specific co-morbidities, and the control group fared better throughout in terms of lifestyle factors (exercise, consumption of fruit and vegetables). Over the 18 month period, both groups showed improvements in blood pressure. There were reductions in BMI and Waist circumference between baseline and 18 months in ExtraCare residents while these remained unchanged in control group. There was a significant initial increase in number of prescribed medications for the ExtraCare group perhaps as well-being support resulted in new diagnoses, but this then remained stable. A reduction in polypharmacy was anticipated, given the use of medication review, but this did not clearly occur. There was no significant change in number of co-morbidities. Healthcare use: GP visits and ExtraCare drop-in clinics: After 12 months GP usage (planned) by ExtraCare residents in the sample had decreased by 46%. No such reduction was seen in 8 emergency appointment data. We investigated the hypothesis that this may be because residents use the well-being drop-in clinic as a substitute for booking routine GP appointments, given that well-being drop-in appointments steadily increased over the period. At baseline, number of dropins and number of planned GP visits was significantly positively correlated – the more a person visited their GP, the more they visited the drop-in clinic too. At 12 months, this relationship had gone completely. Drop-ins increased and GP visits reduced over time. Despite this, the relationship does not become negative which would have been definitive evidence that drop-ins are directly replacing GP visits. That is, it is not the case that the more a person visited the drop-in centre, the less they visited their GP. The change is not necessarily reflecting individual level changes, just in the group as a whole. Planned and unplanned hospital admissions and length of stay: The average number of planned admissions to hospital reduced for ExtraCare participants by 12 months by 31% (no change for control participants). The large variance and small effect size means that this was NOT a statistically reliable change. Number of unplanned admissions did not change for either group. Together, these findings support the Drop-in clinic model: (i) Availability of local, accessible, relatively informal health support, particularly for ongoing dayto-day chronic illness care, that does not need an appointment (a drop-in service), can have a significant effect on reducing GP usage, giving potential cost savings. (ii) Communities where homes are accessible, care support is readily available and existing care needs understood may result in reduced length of stays in hospital. Duration of unplanned hospital stays: This reduced from a median of 5-7 days at baseline, to 1-2 days thereafter. This was not related to increase in number of Drop-ins. 7.0 Frailty Frailty is defined as a state of high vulnerability for adverse health outcomes when exposed to a stressor, that is, an absence of resilience. Frailty is related to morbidity and mortality, and utilisation of healthcare. Crucially, frailty, and especially pre-frail states, are malleable. The Frailty Profile: We constructed a frailty measure for this population at each assessment to compare longitudinally, using a frailty profile concept (Rockwood et al, 2006). People were categorised into frail, pre-frail and not frail based on published criteria. ExtraCare residents were frailer than controls throughout. Initial improvements in frailty did not continue over the full period, although the initial improvements may have delayed decline. Nevertheless, a focus on interventions to prevent or reduce frailty could be further developed and evaluated using such an indicator. Frail Participants: Of the 44 residents categorised as frail at baseline, 22 remained in the sample 18 months later, 14 (63.6%) remained categorised as frail with 8 returning to a pre-frail or not frail state. One control participant was categorised as frail at baseline, returning to a not frail state by 18 months. Pre-frail residents: Given that the “pre-frail” is used to indicate people at risk of becoming frail, it is important to know if this occurred for ExtraCare residents. Of the 62 people designated as prefrail at Baseline, 42 were still in the sample at 18 months and 8 (19%) had returned to a not frail state, with 4.7% being designated as frail at 12 months. Ten control participants were categorised as pre-frail at Baseline. Of the 8 remaining at 18 months, all were still in the same category. Putting it together: Frailty and Costs. As indicated in Section 5, NHS costs in total reduced significantly. The reduction for the frail residents was the most striking: for those in the sample at 9 baseline and follow-up, this changed from an average of £3274.21to £1588.04 average per person. That is, a 51.5% drop. Use of this figure needs to bear in mind that the frailest within this group are those who have died or dropped out of the study. Reductions in social care costs over time were much smaller (£2-300 per person on average). Care costs for frail participants are much higher than for pre-frail participants. A frail participant’s average annual care costs were £4720.96 at the 12 month point, as compared to £61.40 for a prefrail resident (given that most pre-frail residents are on zero care). This underlines the importance of strategies to intervene in pre-frailty to reduce the likelihood of it becoming frail. Physical versus cognitive frailty: In order to determine the source of impacts more precisely, we produced a separate cognitive and physical frailty profile. The data showed that cognitive and physical frailty predict care level jumps from one level to the next differently, with cognitive frailty having a more even influence. The main predictor of higher levels was cognitive frailty (although modelling was not possible with the small numbers on care). 8.0 Modelling: What predicts change? Which measures are useful for predicting decline in independence outcomes? IADL: Change in ACE-R (overall cognitive function) and change in frailty: e.g. for every one point increase in ACE-R, it became less likely that IADL would decline. This did not differ by group. Functional Limitations Profile: Baseline age and increase in Depression: e.g. for every one point increase in depressive symptoms, people were 1.36 times more likely to have increases in functional limitations. A focus on rehabilitation and improvement of cognitive function and on treatment or prevention of depression will have important direct effects on independent function and quality of life, and therefore on need for further care and support. Which measures are particularly useful for predicting Care level? Care Level: Frailty, IADL and ADL (a more basic independence measure), and ability to stand up from a chair (time taken or inability). Given that IADL can be impacted by change in its underlying predictors, rehabilitative focus on these predictors would then have an impact on care needed. However, good linguistic ability was also an important predictor of Care Level. Once frailty, IADL and ADL, and sit-to-stand was taken into account, language had an opposite effect – people with higher language ability were more likely to have higher care levels, suggesting that those who could communicate well and understand information may be more likely to get the care they need. Poorer linguistic abilities seem to result in people being less likely to get care, even in the context of frailty. This has important implications for an advocacy role for frail people in helping them get the care they need. This issue reduces from Baseline onwards, validating ExtraCare’s support, but it does still have an effect. Which measures are particularly useful for predicting well-being outcomes? The main predictor of improvement in depression, perceived health and autobiographical memory in the total sample is which group a person is in, the ExtraCare residents or the control group, whereby living in ExtraCare predicts improvements in these wellbeing measures. Depression/mood improvement: change in cognitive function; change in anxiety e.g.an increase in anxiety of one point reduced the chance of mood improving (people were ¾ as likely to 10 improve on mood if their anxiety increased). Number of chronic illnesses was marginally significant (p<0.01) again reducing the chance of improvement in mood as numbers of illnesses increased and should also be borne in mind. Given that we generally an overall improvement in mood for ExtraCare
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