598 research outputs found
Managing orthodontic appliances in everyday life: A qualitative study of young people’s experiences with removable functional appliances, fixed appliances and retainers
Objective:
To compare young people’s experiences of wearing a range of orthodontic appliances.
Design:
A cross-sectional, qualitative study with purposive sampling.
Setting:
UK dental teaching hospital.
Participants:
Twenty-six orthodontic patients aged 11–17 years.
Methods:
Patients participated in in-depth semi-structured interviews. All interviews were transcribed verbatim and analysed thematically.
Results:
Young people reported physical, practical and emotional impacts from their appliances. Despite these reported impacts, participants described ‘getting used’ to and, therefore, not being bothered by their appliance. Framework analysis of the data identified a multi-dimensional social process of managing everyday life with an appliance. This involves addressing the ‘dys-appearance’ of the body through physically adapting to an appliance. This process also includes psychological approaches, drawing on social networks, developing strategies and situating experiences in a longer-term context. Engaging in this process allowed young people to address the physical, practical and emotional impacts of their appliances.
Conclusion:
This qualitative research has identified how young people manage everyday life with an appliance. Understanding this process will help orthodontists to support their patients
Development of the orthodontic treatment impact questionnaire: cross-sectional validation
Introduction
The need to involve patients in developing and evaluating health care interventions is now well-recognized. This study assesses and refines the Orthodontic Treatment Impact Questionnaire for use as a patient-reported outcome in an interventional clinical trial to evaluate and compare any orthodontic interventions.
Methods
The face and content validity of a previously developed questionnaire were tested in 2 focus groups involving adolescents aged 11-17 years. They were wearing a range of orthodontic appliances and at different treatment stages. A similar cross-sectional convenience sample completed the questionnaire during routine appliance adjustment appointments. A Rasch model, using item response theory, was used for item reduction, assessment of the response format, and differential item functioning. Spearman’s rank correlation was used to assess construct validity, Cronbach α for internal consistency and reliability, and intraclass correlation coefficient for test-retest reliability.
Results
Seven adolescents (4 females, 3 males) were involved in the initial testing; 181 (117 females, 64 males; mean age, 14.7 ± 1.5 years) completed the questionnaire once and 41 twice. The initial measure demonstrated a misfit to the Rasch model. Ten of the original 31 items had disordered thresholds and were removed. The 5-point scale was changed to a 3-point scale. None of the participants demonstrated a misfit to the model. Construct validity (P = 0.480), internal consistency (Cronbach α = 0.827) and test-retest reliability (intraclass correlation coefficient = 0.85; 95% confidence interval, 0.73-0.92) were good.
Conclusions
The initial Orthodontic Treatment Impact Questionnaire was tested and modified using item response theory. The modified questionnaire demonstrated good construct validity, reliability, and internal consistency. Further testing to assess generalizability and longitudinal responsiveness is required
copanlisib monotherapy activity in relapsed or refractory indolent b cell lymphoma combined analysis from phase i and ii studies
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Image labeling and grouping by minimizing linear functionals over cones
We consider energy minimization problems related to image labeling, partitioning, and grouping, which typically show up at mid-level stages of computer vision systems. A common feature of these problems is their intrinsic combinatorial complexity from an optimization pointof-view. Rather than trying to compute the global minimum - a goal we consider as elusive in these cases - we wish to design optimization approaches which exhibit two relevant properties: First, in each application a solution with guaranteed degree of suboptimality can be computed. Secondly, the computations are based on clearly defined algorithms which do not comprise any (hidden) tuning parameters. In this paper, we focus on the second property and introduce a novel and general optimization technique to the field of computer vision which amounts to compute a sub optimal solution by just solving a convex optimization problem. As representative examples, we consider two binary quadratic energy functionals related to image labeling and perceptual grouping. Both problems can be considered as instances of a general quadratic functional in binary variables, which is embedded into a higher-dimensional space such that sub optimal solutions can be computed as minima of linear functionals over cones in that space (semidefinite programs). Extensive numerical results reveal that, on the average, sub optimal solutions can be computed which yield a gap below 5% with respect to the global optimum in case where this is known
Learning and Action Alliance framework to facilitate stakeholder collaboration and social learning in urban flood risk management
Flood and water management governance may be enhanced through partnership working, intra- and cross-organisational collaborations, and wide stakeholder participation. Nonetheless, barriers associated with ineffective communication, fragmented responsibilities and ‘siloed thinking’ restrict open dialogue and discussion. The Learning and Action Alliance (LAA) framework may help overcome these barriers by enabling effective engagement through social learning, and facilitating targeted actions needed to deliver innovative solutions to environmental problems. By increasing the adaptive capacity of decision-makers and participants, social learning through LAAs may lead to concerted action and sustained processes of behavioural change. In this paper, we evaluate the LAA framework as a catalyst for change that supports collaborative working and facilitates transition to more sustainable flood risk management. We use a case study in Newcastle-upon-Tyne, UK, to demonstrate how the LAA framework brought together disparate City stakeholders to co-produce new knowledge, negotiate innovative actions and, ultimately, work towards implementing a new vision for sustainable urban flood risk management. The shared vision of Newcastle as a ‘Blue-Green City’ that emerged is founded on a strong platform for social learning which increased organisations’ and individuals’ capacities to manage differences in perspectives and behaviours, reframe knowledge, and make collective decisions based on negotiation and conflict resolution. Broad recommendations based on lessons learned from the Newcastle LAA are presented to aid other cities and regions in establishing and running social learning platforms
New constraints on the evolution of the stellar-to-dark matter connection : a combined analysis of galaxy-galaxy lensing, clustering, and stellar mass functions from z = 0.2 to z = 1
Using data from the COSMOS survey, we perform the first joint analysis of galaxy-galaxy weak lensing, galaxy spatial clustering, and galaxy number densities. Carefully accounting for sample variance and for scatter between stellar and halo mass, we model all three observables simultaneously using a novel and self-consistent theoretical framework. Our results provide strong constraints on the shape and redshift evolution of the stellar-to-halo mass relation (SHMR) from z = 0.2 to z = 1. At low stellar mass, we find that halo mass scales as Mh vpropM 0.46 * and that this scaling does not evolve significantly with redshift from z = 0.2 to z = 1. The slope of the SHMR rises sharply at M * > 5 × 1010 M ☉ and as a consequence, the stellar mass of a central galaxy becomes a poor tracer of its parent halo mass. We show that the dark-to-stellar ratio, Mh /M *, varies from low to high masses, reaching a minimum of Mh /M * ~ 27 at M * = 4.5 × 1010 M ☉ and Mh = 1.2 × 1012 M ☉. This minimum is important for models of galaxy formation because it marks the mass at which the accumulated stellar growth of the central galaxy has been the most efficient. We describe the SHMR at this minimum in terms of the "pivot stellar mass," M piv *, the "pivot halo mass," M piv h , and the "pivot ratio," (Mh /M *)piv. Thanks to a homogeneous analysis of a single data set spanning a large redshift range, we report the first detection of mass downsizing trends for both M piv h and M piv *. The pivot stellar mass decreases from M piv * = 5.75 ± 0.13 × 1010 M ☉ at z = 0.88 to M piv * = 3.55 ± 0.17 × 1010 M ☉ at z = 0.37. Intriguingly, however, the corresponding evolution of M piv h leaves the pivot ratio constant with redshift at (Mh /M *)piv ~ 27. We use simple arguments to show how this result raises the possibility that star formation quenching may ultimately depend on Mh /M * and not simply on Mh , as is commonly assumed. We show that simple models with such a dependence naturally lead to downsizing in the sites of star formation. Finally, we discuss the implications of our results in the context of popular quenching models, including disk instabilities and active galactic nucleus feedback
An FPTAS for optimizing a class of low-rank functions over a polytope
We present a fully polynomial time approximation scheme (FPTAS) for optimizing a very general class of non-linear functions of low rank over a polytope. Our approximation scheme relies on constructing an approximate Pareto-optimal front of the linear functions which constitute the given low-rank function. In contrast to existing results in the literature, our approximation scheme does not require the assumption of quasi-concavity on the objective function. For the special case of quasi-concave function minimization, we give an alternative FPTAS, which always returns a solution which is an extreme point of the polytope. Our technique can also be used to obtain an FPTAS for combinatorial optimization problems with non-linear objective functions, for example when the objective is a product of a fixed number of linear functions. We also show that it is not possible to approximate the minimum of a general concave function over the unit hypercube to within any factor, unless P = NP. We prove this by showing a similar hardness of approximation result for supermodular function minimization, a result that may be of independent interest
The New Political History
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66569/2/10.1177_000276427702100204.pd
Inflation Physics from the Cosmic Microwave Background and Large Scale Structure
Fluctuations in the intensity and polarization of the cosmic microwave background (CMB) and the large-scale distribution of matter in the universe each contain clues about the nature of the earliest moments of time. The next generation of CMB and large-scale structure (LSS) experiments are poised to test the leading paradigm for these earliest moments---the theory of cosmic inflation---and to detect the imprints of the inflationary epoch, thereby dramatically increasing our understanding of fundamental physics and the early universe. A future CMB experiment with sufficient angular resolution and frequency coverage that surveys at least 1 of the sky to a depth of 1 uK-arcmin can deliver a constraint on the tensor-to-scalar ratio that will either result in a 5-sigma measurement of the energy scale of inflation or rule out all large-field inflation models, even in the presence of foregrounds and the gravitational lensing B-mode signal. LSS experiments, particularly spectroscopic surveys such as the Dark Energy Spectroscopic Instrument, will complement the CMB effort by improving current constraints on running of the spectral index by up to a factor of four, improving constraints on curvature by a factor of ten, and providing non-Gaussianity constraints that are competitive with the current CMB bounds
Single-dot Spectroscopy of GaAs Quantum Dots Fabricated by Filling of Self-assembled Nanoholes
We study the optical emission of single GaAs quantum dots (QDs). The QDs are fabricated by filling of nanoholes in AlGaAs and AlAs which are generated in a self-assembled fashion by local droplet etching with Al droplets. Using suitable process parameters, we create either uniform QDs in partially filled deep holes or QDs with very broad size distribution in completely filled shallow holes. Micro photoluminescence measurements of single QDs of both types establish sharp excitonic peaks. We measure a fine-structure splitting in the range of 22–40μeV and no dependence on QD size. Furthermore, we find a decrease in exciton–biexciton splitting with increasing QD size
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