A qualitative study of the views of residents with dementia, their relatives and staff about work practice in long-term care settings

Background: Most people living in 24-hour care settings have dementia, and little is known about what makes long-term care a positive experience for them.Method: This carer-led qualitative study examined working practices in 24-hour long-term care-settings, including hospitals, nursing and residential homes, with the aim of finding out and making recommendations about such settings. Using semi-structured interviews, managers, nurses and care assistants were asked about work practices, such as how they coped with difficult behavior, about shifts, staffing levels, staff retention and training. Relatives of residents with dementia were asked about their role and perceptions of the care provided, and residents were asked for their opinions of their care.Results: Staff reported that residents presented with increasingly challenging behavior compared to the past, and that sometimes staffing levels and skills were inadequate. Of all the settings, hospitals had the most problems with staffing levels and retention, staff-relative relationships and staff support systems. Relatives saw their own role as positive. People with dementia of varying severity could usefully evaluate some of the services they received.Discussion: Dementia-specific training and education of staff in all long-term care-settings, including induction, should address the management of problem behavior in dementia and thereby improve staff fulfilment and relatives' satisfaction. The long-stay hospital may not be appropriate as a "home for life" for those with dementia, and we recommend that long-stay care settings should be able to cater flexibly for a range of resident needs

Magnetocaloric effect in hexacyanochromate Prussian blue analogs

We report on the magnetocaloric properties of two molecule-based hexacyanochromate Prussian blue analogs, nominally CsNi[Cr(CN)_6](H_2O) and Cr_3[Cr(CN)_6]_2x12(H_2O). The former orders ferromagnetically below Tc=90 K, whereas the latter is a ferrimagnet below Tc=230 K. For both, we find significantly large magnetic entropy changes DSm associated to the magnetic phase transitions. Notably, our studies represent the first attempt to look at molecule-based materials in terms of the magnetocaloric effect for temperatures well above the liquid helium range.Comment: 4 pages, 6 figure

Matreex: Compact and Interactive Visualization for Scalable Studies of Large Gene Families.

Studying gene family evolution strongly benefits from insightful visualizations. However, the ever-growing number of sequenced genomes is leading to increasingly larger gene families, which challenges existing gene tree visualizations. Indeed, most of them present users with a dilemma: display complete but intractable gene trees, or collapse subtrees, thereby hiding their children's information. Here, we introduce Matreex, a new dynamic tool to scale up the visualization of gene families. Matreex's key idea is to use "phylogenetic" profiles, which are dense representations of gene repertoires, to minimize the information loss when collapsing subtrees. We illustrate Matreex's usefulness with three biological applications. First, we demonstrate on the MutS family the power of combining gene trees and phylogenetic profiles to delve into precise evolutionary analyses of large multicopy gene families. Second, by displaying 22 intraflagellar transport gene families across 622 species cumulating 5,500 representatives, we show how Matreex can be used to automate large-scale analyses of gene presence-absence. Notably, we report for the first time the complete loss of intraflagellar transport in the myxozoan Thelohanellus kitauei. Finally, using the textbook example of visual opsins, we show Matreex's potential to create easily interpretable figures for teaching and outreach. Matreex is available from the Python Package Index (pip install Matreex) with the source code and documentation available at https://github.com/DessimozLab/matreex

Asymmetric preference formation in willingness to pay estimates in discrete choice models

Individuals when faced with choices amongst a number of alternatives often adopt a variety of processing rules, ranging from simple linear to complex non-linear treatment of each attribute defining the offer of each alternative. In this paper we investigate the presence of asymmetry in preferences to test for reference effects and differential willingness to pay according to whether we are valuing gains or losses. The findings offer clear evidence of an asymmetrical response to increases and decreases in attributes when compared to the corresponding values for a reference alternative, where the degree of asymmetry varies across attributes and population segments

A Vision for the Pioneer Valley Riverfront Club

The goal of Planning Studio is to develop a student’s techniques for collecting, analyzing, synthesizing spatial and non-spatial data and presenting that collective data in a manner (i.e., report, video, presentation, charettes) that is understandable to academics, professionals, and the public. Planning Studio allows students to integrate knowledge from coursework and research, and apply such knowledge to resolving representative planning problems. At UMASS Amherst, these problems are found in neighborhood, rural, urban, and/or regional settings. In Fall 2013, the course completed three projects: Master Plans & Land-Use Elements, the Revitalization of the Lower Worthington Street District (Springfield, MA), a Vision for the Pioneer Valley Riverfront Club (Springfield, MA). For a Vision for the Pioneer Valley Riverfront Club, the Studio Team of six students was tasked with helping the newly invigorated nonprofit rowing club write a plan that implements their vision and expands their programs the next five years. Historically, the rowing club was an organization with a small budget and devoted following. Recently, the organization experienced an influx of revenue in the form of a public health grant. This new budget presents opportunities for organizational prosperity and sustainability and the Studio Team provides strategies to sustain the organization. The client was Pioneer Valley Riverfront Club

Cost and time damping: evidence from aggregate rail direct demand models

There is a significant body of evidence from both disaggregate choice modelling literature and practical travel demand forecasting that the responsiveness to cost and possibly to time diminishes with journey length. This has, in Britain at least, been termed ‘Cost Damping’, and is recognised in guidance issued by the UK Department for Transport. However, the consistency of the effect across modes and data types has not been established. Cost damping, if it exists, affects both the forecasting of demand and our understanding of behaviour. This paper aims to investigate the evidence for cost and time damping in rail demand using aggregate rail ticket sales data. The rail ticket sales data in Britain has, for many years, formed the basis of analysis of a wide range of impacts of rail demand. It records the number of tickets sold between station pairs, and it is generally felt to provide a reasonably accurate reflection of travel demand. However, the consistency of these direct demand models with choice modelling and highway demand model structures has not been investigated. Rail direct demand models estimated by ticket sales data indicate only slight variation in the fare elasticity with distance, as is evidenced in the largest meta-analysis of price elasticities conducted to date (Wardman, 2014). This study of UK elasticities shows strong variation between urban and inter-urban trips, presumably a segmentation at least in part by purpose, but less remaining variation by trip length. A lack of variation by length supports the hypothesis of cost damping, because constant cost sensitivity would imply that fare elasticity would increase strongly with distance, because of the increasing impact of higher fares at longer distances. In this paper we indicate that rail direct demand models have some consistency of behavioural paradigm with utility based choice models used in highway planning. We go on to use rail demand data to estimate time and fare elasticities in the context of various cost damping functions. Our empirical contribution is to estimate time elasticities on a basis directly comparable with cost elasticities and to show that the phenomenon of cost damping is strongly present in ticket sales data. This finding implies that cost damping should be included in models intended for multimodal analysis, which may otherwise give incorrect predictions

Closed-Form Bayesian Inferences for the Logit Model via Polynomial Expansions

Articles in Marketing and choice literatures have demonstrated the need for incorporating person-level heterogeneity into behavioral models (e.g., logit models for multiple binary outcomes as studied here). However, the logit likelihood extended with a population distribution of heterogeneity doesn't yield closed-form inferences, and therefore numerical integration techniques are relied upon (e.g., MCMC methods). We present here an alternative, closed-form Bayesian inferences for the logit model, which we obtain by approximating the logit likelihood via a polynomial expansion, and then positing a distribution of heterogeneity from a flexible family that is now conjugate and integrable. For problems where the response coefficients are independent, choosing the Gamma distribution leads to rapidly convergent closed-form expansions; if there are correlations among the coefficients one can still obtain rapidly convergent closed-form expansions by positing a distribution of heterogeneity from a Multivariate Gamma distribution. The solution then comes from the moment generating function of the Multivariate Gamma distribution or in general from the multivariate heterogeneity distribution assumed. Closed-form Bayesian inferences, derivatives (useful for elasticity calculations), population distribution parameter estimates (useful for summarization) and starting values (useful for complicated algorithms) are hence directly available. Two simulation studies demonstrate the efficacy of our approach.Comment: 30 pages, 2 figures, corrected some typos. Appears in Quantitative Marketing and Economics vol 4 (2006), no. 2, 173--20

Luminescent water dispersible microporous polymeric nanospheres

Water-dispersible porous polymeric dispersions (PPDs) have been synthesised by reversible addition-fragmentation chain transfer mediated polymerisation-induced self-assembly (RAFT-mediated PISA). The core-shell particles posses a microporous core formed from divinylbenzene and fumaronitrile while the outer polyethylene glycol shell enables the particles to be dispersible in a wide range of solvents. The PPD was shown to have a heirarchical structure of small primary nanoparticles within larger, well-defined aggregates of 220 nm as measured by electron microscopy and small angle x-ray scattering (SAXS) and exhibited a surface area of 274 m2/g. Furthermore these samples were found to be fluoresent and demonstrate selective detection of harmful nitroaramatics in solution with extremly low limits of detection, 169 ppb for picric acid, as well as possessing a CO2 uptake of 1.1 mmol/g at 273 K

Practical solutions for sampling alternatives in large-scale models

Many large-scale real-world transport applications have choice sets that are so large as to make model estimation and application computationally impractical. The ability to estimate models on subsets of the alternatives is thus of great appeal, and correction approaches have existed since the late 1970s for the simple multinomial logit (MNL) model. However, many of these models in practice rely on nested logit specifications, for example, in the context of the joint choice of mode and destination. Recent research has put forward solutions for such generalized extreme value (GEV) structures, but these structures remain difficult to apply in practice. This paper puts forward a simplification of the GEV method for use in computationally efficient implementations of nested logit. The good performance of this approach is illustrated with simulated data, and additional insights into sampling error are also provided with different sampling strategies for MNL

General Chemistry Student Attitudes and Success with Use of Online Homework: Traditional- Responsive versus Adaptive-Responsive

We investigated whether use of an adaptive-responsive online homework system (OHS) that tailors homework to students’ prior knowledge and periodically reassesses students to promote learning through practice retrieval has inherent advantages over traditional-responsive online homework. A quasi-experimental cohort control post-test-only design with nonequivalent groups and propensity scores with nearest neighbor matching (n = 6,114 pairs) was used. The adaptive system was found to increase the odds of a higher final letter grade for average, below average, and failing students. However, despite the learning advantages, students self-reported less favorable attitudes toward adaptive-responsive (3.15 of 5) relative to traditional-responsive OHS (3.31). Specific to the adaptive OHS, the following were found: (i) student attitudes were moderately and positively correlated (r = 0.36, p \u3c 0.01) to final letter grade, (ii) most students (95%) reported engaging in remediation of incorrect responses, (iii) a majority of students (69%) reported changes in study habits, and (iv) students recognized the benefit of using adaptive OHS by ranking its assignments and explanations or review materials as two of the top three most useful course aspects contributing to perceived learning. Instructors can use our findings to inform their choice of online homework system for formative assessment of chemistry learning by weighing the benefits, disadvantages, and learning pedagogies of traditional-responsive versus adaptive-responsive systems