Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation

We consider unsupervised domain adaptation (UDA), where labeled data from a source domain (e.g., photographs) and unlabeled data from a target domain (e.g., sketches) are used to learn a classifier for the target domain. Conventional UDA methods (e.g., domain adversarial training) learn domain-invariant features to improve generalization to the target domain. In this paper, we show that contrastive pre-training, which learns features on unlabeled source and target data and then fine-tunes on labeled source data, is competitive with strong UDA methods. However, we find that contrastive pre-training does not learn domain-invariant features, diverging from conventional UDA intuitions. We show theoretically that contrastive pre-training can learn features that vary subtantially across domains but still generalize to the target domain, by disentangling domain and class information. Our results suggest that domain invariance is not necessary for UDA. We empirically validate our theory on benchmark vision datasets.Comment: 35 page

Timing anthropogenic stressors to mitigate their impact on marine ecosystem resilience

© 2017 The Author(s). Better mitigation of anthropogenic stressors on marine ecosystems is urgently needed to address increasing biodiversity losses worldwide. We explore opportunities for stressor mitigation using whole-of-systems modelling of ecological resilience, accounting for complex interactions between stressors, their timing and duration, background environmental conditions and biological processes. We then search for ecological windows, times when stressors minimally impact ecological resilience, defined here as risk, recovery and resistance. We show for 28 globally distributed seagrass meadows that stressor scheduling that exploits ecological windows for dredging campaigns can achieve up to a fourfold reduction in recovery time and 35% reduction in extinction risk. Although the timing and length of windows vary among sites to some degree, global trends indicate favourable windows in autumn and winter. Our results demonstrate that resilience is dynamic with respect to space, time and stressors, varying most strongly with: (i) the life history of the seagrass genus and (ii) the duration and timing of the impacting stress

Attitudes towards the use and acceptance of eHealth technologies : a case study of older adults living with chronic pain and implications for rural healthcare

Acknowledgements The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1. MC’s time writing the paper is funded by the Scottish Government’s Rural and Environmental Science and Analytical Services Division (RESAS) under Theme 8 ‘Vibrant Rural Communities’ of the Food, Land and People Programme (2011–2016). MC is also an Honorary Research Fellow at the Division of Applied Health Sciences, University of Aberdeen. The input of other members of the TOPS research team, Alastair Mort, Fiona Williams, Sophie Corbett, Phil Wilson and Paul MacNamee who contributed to be wider study and discussed preliminary findings reported here with the authors of the paper is acknowledged. We acknowledge the feedback on earlier versions of this paper provided by members of the Trans-Atlantic Rural Research Network, especially Stefanie Doebler and Carmen Hubbard. We also thank Deb Roberts for her comments.Peer reviewedPublisher PD

The Impact of Autoimmune Hepatitis and Its Treatment on Health Utility

Patient reporting suggests that the physical and psychological effects of autoimmune hepatitis (AIH) can be substantial. However, health‐related quality of life (HRQOL) in patients with AIH remains incompletely characterized, and health utility remains to be explored. Treatment for AIH often includes the use of corticosteroids, which are agents that can be associated with significant adverse effects. Here we explore the impact of AIH and its treatments on patient‐reported HRQOL and health utility in a large cohort of prevalent cases from the United Kingdom Autoimmune Hepatitis (UK‐AIH) national study. Data were collected from 990 adult participants with a clinical diagnosis of AIH using validated HRQOL tools including the European Quality‐of‐Life 5‐Dimension 5‐Level (EQ‐5D‐5L) and clinical data forms. The EQ‐5D‐5L dimension scores were compared with UK population norms and with a disease control cohort with primary biliary cholangitis (PBC). Within the AIH cohort, regression analysis was used to explore associations between HRQOL and demographic and clinical variables with a particular focus on the impact of AIH therapies including corticosteroid use. HRQOL, measured by the EQ‐5D‐5L utility index, is shown to be significantly impaired in our cohort of AIH patients compared with population norms. Within the AIH cohort, corticosteroid use was found to be significantly associated with impaired HRQOL, even when controlling for biochemical disease activity status. Conclusion: Our data show evidence of HRQOL impairment in a large cohort of AIH patients compared with the general population. Furthermore, corticosteroid use is strongly associated with decreased HRQOL, independent of remission status. This highlights the need for better corticosteroid‐free therapy approaches and it emphasizes the need for future novel therapeutic trials in AIH

Myosin-I nomenclature.

We suggest that the vertebrate myosin-I field adopt a common nomenclature system based on the names adopted by the Human Genome Organization (HUGO). At present, the myosin-I nomenclature is very confusing; not only are several systems in use, but several different genes have been given the same name. Despite their faults, we believe that the names adopted by the HUGO nomenclature group for genome annotation are the best compromise, and we recommend universal adoption

Local stochastic non-Gaussianity and N-body simulations

Large-scale clustering of highly biased tracers of large-scale structure has emerged as one of the best observational probes of primordial non-Gaussianity of the local type (i.e. f_{NL}^{local}). This type of non-Gaussianity can be generated in multifield models of inflation such as the curvaton model. Recently, Tseliakhovich, Hirata, and Slosar showed that the clustering statistics depend qualitatively on the ratio of inflaton to curvaton power \xi after reheating, a free parameter of the model. If \xi is significantly different from zero, so that the inflaton makes a non-negligible contribution to the primordial adiabatic curvature, then the peak-background split ansatz predicts that the halo bias will be stochastic on large scales. In this paper, we test this prediction in N-body simulations. We find that large-scale stochasticity is generated, in qualitative agreement with the prediction, but that the level of stochasticity is overpredicted by ~30%. Other predictions, such as \xi independence of the halo bias, are confirmed by the simulations. Surprisingly, even in the Gaussian case we do not find that halo model predictions for stochasticity agree consistently with simulations, suggesting that semi-analytic modeling of stochasticity is generally more difficult than modeling halo bias.Comment: v3: minor changes matching published versio

Technical challenges of providing record linkage services for research

Background: Record linkage techniques are widely used to enable health researchers to gain event based longitudinal information for entire populations. The task of record linkage is increasingly being undertaken by specialised linkage units (SLUs). In addition to the complexity of undertaking probabilistic record linkage, these units face additional technical challenges in providing record linkage ‘as a service’ for research. The extent of this functionality, and approaches to solving these issues, has had little focus in the record linkage literature. Few, if any, of the record linkage packages or systems currently used by SLUs include the full range of functions required. Methods: This paper identifies and discusses some of the functions that are required or undertaken by SLUs in the provision of record linkage services. These include managing routine, on-going linkage; storing and handling changing data; handling different linkage scenarios; accommodating ever increasing datasets. Automated linkage processes are one way of ensuring consistency of results and scalability of service. Results: Alternative solutions to some of these challenges are presented. By maintaining a full history of links, and storing pairwise information, many of the challenges around handling ‘open’ records, and providing automated managed extractions are solved. A number of these solutions were implemented as part of the development of the National Linkage System (NLS) by the Centre for Data Linkage (part of the Population Health Research Network) in Australia.Conclusions: The demand for, and complexity of, linkage services are growing. This presents as a challenge to SLUs as they seek to service the varying needs of dozens of research projects annually. Linkage units need to be both flexible and scalable to meet this demand. It is hoped the solutions presented here can help mitigate these difficulties

Voxel-based, brain-wide association study of aberrant functional connectivity in schizophrenia implicates thalamocortical circuitry

Background: Wernicke\u27s concept of \u27sejunction\u27 or aberrant associations among specialized brain regions is one of the earliest hypotheses attempting to explain the myriad of symptoms in psychotic disorders. Unbiased data mining of all possible brain-wide connections in large data sets is an essential first step in localizing these aberrant circuits. Methods: We analyzed functional connectivity using the largest resting-state neuroimaging data set reported to date in the schizophrenia literature (415 patients vs. 405 controls from UK, USA, Taiwan, and China). An exhaustive brain-wide association study at both regional and voxel-based levels enabled a continuous data-driven discovery of the key aberrant circuits in schizophrenia. Results: Results identify the thalamus as the key hub for altered functional networks in patients. Increased thalamus-primary somatosensory cortex connectivity was the most significant aberration in schizophrenia (P=10-18). Overall, a number of thalamic links with motor and sensory cortical regions showed increased connectivity in schizophrenia, whereas thalamo-frontal connectivity was weakened. Network changes were correlated with symptom severity and illness duration, and support vector machine analysis revealed discrimination accuracies of 73.53-80.92%. Conclusions: Widespread alterations in resting-state thalamocortical functional connectivity is likely to be a core feature of schizophrenia that contributes to the extensive sensory, motor, cognitive, and emotional impairments in this disorder. Changes in this schizophrenia-associated network could be a reliable mechanistic index to discriminate patients from healthy controls

Gender Differences in Carbohydrate Metabolism and Carbohydrate Loading

Prior to endurance competition, many endurance athletes participate in a carbohydrate loading regimen in order to help delay the onset of fatigue. The "classic" regimen generally includes an intense glycogen depleting training period of approximately two days followed by a glycogen loading period for 3–4 days, ingesting approximately 60–70% of total energy intake as carbohydrates, while the newer method does not consist of an intense glycogen depletion protocol. However, recent evidence has indicated that glycogen loading does not occur in the same manner for males and females, thus affecting performance. The scope of this literature review will include a brief description of the role of estradiol in relation to metabolism and gender differences seen in carbohydrate metabolism and loading