Measuring the difference between actual and reported food intakes in the context of energy balance under laboratory conditions

Acknowledgements The present study was funded by the Food Standards Agency, UK. The Food Standards Agency had no role in the design, analysis or writing of this article. The authors’ responsibilities were as follows: R. J. S., L. M. O’R. and G. W. H. designed the research; L. M. O’R. and Z. F. conducted the research and analysed the data; G. W. H. performed the statistical analyses; P. R. carried out the DLW analysis; R. J. S. had primary responsibility for the final content; R. J. S., L. M. O’R., Z. F., S. W. and M. B. E. L. wrote the paper.Peer reviewedPublisher PD

Communication in cross-cultural consultations in primary care in Europe: the case for improvement. The rationale for the RESTORE FP 7 project

The purpose of this paper is to substantiate the importance of research about barriers and levers to the implementation of supports for cross-cultural communication in primary care settings in Europe. After an overview of migrant health issues, with the focus on communication in cross-cultural consultations in primary care and the importance of language barriers, we highlight the fact that there are serious problems in routine practice that persist over time and across different European settings. Language and cultural barriers hamper communication in consultations between doctors and migrants, with a range of negative effects including poorer compliance and a greater propensity to access emergency services. It is well established that there is a need for skilled interpreters and for professionals who are culturally competent to address this problem. A range of professional guidelines and training initiatives exist that support the communication in cross-cultural consultations in primary care. However, these are commonly not implemented in daily practice. It is as yet unknown why professionals do not accept or implement these guidelines and interventions, or under what circumstances they would do so. A new study involving six European countries, RESTORE (REsearch into implementation STrategies to support patients of different ORigins and language background in a variety of European primary care settings), aims to address these gaps in knowledge. It uses a unique combination of a contemporary social theory, normalisation process theory (NPT) and participatory learning and action (PLA) research. This should enhance understanding of the levers and barriers to implementation, as well as providing stakeholders, with the opportunity to generate creative solutions to problems experienced with the implementation of such interventions

Functional effects of 17alpha-hydroxyprogesterone caproate (17P) on human myometrial contractility in vitro

BACKGROUND: 17alpha-hydroxyprogesterone caproate (17P) administration reportedly improves outcome for women with a previous spontaneous preterm delivery. This study, using in vitro strips of human uterine smooth muscle, aimed to investigate the direct non-genomic effects of 17P on spontaneous and induced contractions in tissues obtained during pregnancy, and in the non-pregnant state. METHODS: Biopsies of human myometrium were obtained at elective cesarean section, and from hysterectomy specimens, and dissected strips suspended for isometric recordings. The effects of 17P (1 nmol/L -10 micro mol/L) on spontaneous and agonist-induced (oxytocin 0.5 nmol/L for pregnant, phenylephrine 10 μmol/L for non-pregnant) contractions were measured. Integrals of contractile activity, including the mean maximal inhibition values (MMI) observed at the maximal concentration, were compared with those from simultaneously run control strips. RESULTS: There was no significant direct effect exerted by 17P on pregnant or non-pregnant human myometrial contractility. The MMI ± SEM for spontaneous contractions in pregnant myometrium was 4.9% ± 7.2 (n = 6; P = 0.309) and for oxytocin-induced contractions was 2.2% ± 1.3 (n = 6; P = 0.128). For non-pregnant myometrium, the MMI ± SEM for spontaneous contractions was 8.8% ± 11.0 (n = 6; P = 0.121) and for phenylephrine induced contractions was -7.9% ± 6.5 (n = 6; P = 0.966). CONCLUSIONS: The putative benefits of 17P for preterm labor prevention are not achieved, even partially, by a direct utero-relaxant effect. These findings outline the possibility that genomic effects of 17P, achieved over long periods of administration, are required for its reported therapeutic benefits

A Stochastic Fluid Model Approach to the Stationary Distribution of the Maximum Priority Process

In traditional priority queues, we assume that every customer upon arrival has a fixed, class-dependent priority, and that a customer may not commence service if a customer with a higher priority is present in the queue. However, in situations where a performance target in terms of the tails of the class-dependent waiting time distributions has to be met, such models of priority queueing may not be satisfactory. In fact, there could be situations where high priority classes easily meet their performance target for the maximum waiting time, while lower classes do not. Here, we are interested in the stationary distribution at the times of commencement of service of this maximum priority process. Until now, there has been no explicit expression for this distribution. We construct a mapping of the maximum priority process to a tandem fluid queue, which enables us to find expressions for this stationary distribution. We derive the results for the stationary distribution of the maximum priority process at the times of the commencement of service.Comment: The Eleventh International Conference on Matrix-Analytic Methods in Stochastic Models (MAM11), 2022, Seoul, Republic of Kore

Sixteen years of bathymetry and waves at San Diego beaches.

Sustained, quantitative observations of nearshore waves and sand levels are essential for testing beach evolution models, but comprehensive datasets are relatively rare. We document beach profiles and concurrent waves monitored at three southern California beaches during 2001-2016. The beaches include offshore reefs, lagoon mouths, hard substrates, and cobble and sandy (medium-grained) sediments. The data span two energetic El Niño winters and four beach nourishments. Quarterly surveys of 165 total cross-shore transects (all sites) at 100 m alongshore spacing were made from the backbeach to 8 m depth. Monthly surveys of the subaerial beach were obtained at alongshore-oriented transects. The resulting dataset consists of (1) raw sand elevation data, (2) gridded elevations, (3) interpolated elevation maps with error estimates, (4) beach widths, subaerial and total sand volumes, (5) locations of hard substrate and beach nourishments, (6) water levels from a NOAA tide gauge (7) wave conditions from a buoy-driven regional wave model, and (8) time periods and reaches with alongshore uniform bathymetry, suitable for testing 1-dimensional beach profile change models

Learning Representations that Support Extrapolation

Extrapolation -- the ability to make inferences that go beyond the scope of one's experiences -- is a hallmark of human intelligence. By contrast, the generalization exhibited by contemporary neural network algorithms is largely limited to interpolation between data points in their training corpora. In this paper, we consider the challenge of learning representations that support extrapolation. We introduce a novel visual analogy benchmark that allows the graded evaluation of extrapolation as a function of distance from the convex domain defined by the training data. We also introduce a simple technique, temporal context normalization, that encourages representations that emphasize the relations between objects. We find that this technique enables a significant improvement in the ability to extrapolate, considerably outperforming a number of competitive techniques.Comment: ICML 202

The Relational Bottleneck as an Inductive Bias for Efficient Abstraction

A central challenge for cognitive science is to explain how abstract concepts are acquired from limited experience. This effort has often been framed in terms of a dichotomy between empiricist and nativist approaches, most recently embodied by debates concerning deep neural networks and symbolic cognitive models. Here, we highlight a recently emerging line of work that suggests a novel reconciliation of these approaches, by exploiting an inductive bias that we term the relational bottleneck. We review a family of models that employ this approach to induce abstractions in a data-efficient manner, emphasizing their potential as candidate models for the acquisition of abstract concepts in the human mind and brain