A synthetic sample of short-cadence solar-like oscillators for TESS

NASA's Transiting Exoplanet Survey Satellite (TESS) has begun a two-year survey of most of the sky, which will include lightcurves for thousands of solar-like oscillators sampled at a cadence of two minutes. To prepare for this steady stream of data, we present a mock catalogue of lightcurves, designed to realistically mimic the properties of the TESS sample. In the process, we also present the first public release of the asteroFLAG Artificial Dataset Generator, which simulates lightcurves of solar-like oscillators based on input mode properties. The targets are drawn from a simulation of the Milky Way's populations and are selected in the same way as TESS's true Asteroseismic Target List. The lightcurves are produced by combining stellar models, pulsation calculations and semi-empirical models of solar-like oscillators. We describe the details of the catalogue and provide several examples. We provide pristine lightcurves to which noise can be added easily. This mock catalogue will be valuable in testing asteroseismology pipelines for TESS and our methods can be applied in preparation and planning for other observatories and observing campaigns.Comment: 14 pages, 6 figures, accepted for publication in ApJS. Archives containing the mock catalogue are available at https://doi.org/10.5281/zenodo.1470155 and the pipeline to produce it at https://github.com/warrickball/s4tess . The first public release of the asteroFLAG Artificial Dataset Generator v3 (AADG3) is described at https://warrickball.github.io/AADG3

Cardiac arrhythmia in individuals with steroid sulfatase deficiency (X linked ichthyosis): candidate anatomical and biochemical pathways

Circulating steroids, including sex hormones, can affect cardiac development and function. In mammals, steroid sulfatase (STS) is the enzyme solely responsible for cleaving sulfate groups from various steroid molecules, thereby altering their activity and water solubility. Recent studies have indicated that Xp22.31 genetic deletions encompassing STS (associated with the rare dermatological condition X-linked ichthyosis), and common variants within the STS gene, are associated with a markedly elevated risk of cardiac arrhythmias, notably atrial fibrillation/flutter. Here, we consider emerging basic science and clinical findings which implicate structural heart abnormalities (notably septal defects) as a mediator of this heightened risk, and propose candidate cellular and biochemical mechanisms. Finally, we consider how the biological link between STS activity and heart structure/function might be investigated further and the clinical implications of work in this area

X-linked ichthyosis: New insights into a multi-system disorder

Background X-linked ichthyosis (XLI) is a rare genetic condition almostexclusively affecting males; it is characterised by abnormal desquamation and retentionhyperkeratosis, and presents with polygonal brown scales. Most cases resultfrom genetic deletions within Xp22.31 spanning the STS (steroid sulfatase)gene, with the remaining cases resulting from STS-specific mutations. For manyyears it has been recognised that individuals with XLI are at increased risk ofcryptorchidism and corneal opacities. Methods We discuss emerging evidence that such individuals are alsomore likely to be affected by a range of neurodevelopmental and psychiatrictraits, by cardiac arrhythmias, and by rare fibrotic and bleeding-relatedconditions. We consider candidate mechanisms that may confer elevatedlikelihood of these individual conditions, and propose a novel commonbiological risk pathway. Results Understanding the prevalence, nature and co-occurrence ofcomorbidities associated with XLI is critical for ensuring early identificationof symptoms and for providing the most effective genetic counselling andmultidisciplinary care for affected individuals. Conclusion Future work in males with XLI, and in new preclinical andcellular model systems, should further clarify underlying pathophysiologicalmechanisms amenable to therapeutic intervention

COIN:Contrastive Identifier Network for Breast Mass Diagnosis in Mammography

Computer-aided breast cancer diagnosis in mammography is a challenging problem, stemming from mammographical data scarcity and data entanglement. In particular, data scarcity is attributed to the privacy and expensive annotation. And data entanglement is due to the high similarity between benign and malignant masses, of which manifolds reside in lower dimensional space with very small margin. To address these two challenges, we propose a deep learning framework, named Contrastive Identifier Network (\textsc{COIN}), which integrates adversarial augmentation and manifold-based contrastive learning. Firstly, we employ adversarial learning to create both on- and off-distribution mass contained ROIs. After that, we propose a novel contrastive loss with a built Signed graph. Finally, the neural network is optimized in a contrastive learning manner, with the purpose of improving the deep model's discriminativity on the extended dataset. In particular, by employing COIN, data samples from the same category are pulled close whereas those with different labels are pushed further in the deep latent space. Moreover, COIN outperforms the state-of-the-art related algorithms for solving breast cancer diagnosis problem by a considerable margin, achieving 93.4\% accuracy and 95.0\% AUC score. The code will release on ***

A Deep DUAL-PATH Network for Improved Mammogram Image Processing

We present, for the first time, a novel deep neural network architecture called \dcn with a dual-path connection between the input image and output class label for mammogram image processing. This architecture is built upon U-Net, which non-linearly maps the input data into a deep latent space. One path of the \dcnn, the locality preserving learner, is devoted to hierarchically extracting and exploiting intrinsic features of the input, while the other path, called the conditional graph learner, focuses on modeling the input-mask correlations. The learned mask is further used to improve classification results, and the two learning paths complement each other. By integrating the two learners our new architecture provides a simple but effective way to jointly learn the segmentation and predict the class label. Benefiting from the powerful expressive capacity of deep neural networks a more discriminative representation can be learned, in which both the semantics and structure are well preserved. Experimental results show that \dcn achieves the best mammography segmentation and classification simultaneously, outperforming recent state-of-the-art models.Comment: To Appear in ICCASP 2019 Ma

ELECTROMYOGRAPHICAL ANALYSIS OF HAMSTRING RESISTANCE TRAINING EXERCISES

This study evaluated the EMG activity of the hamstring and quadriceps muscle groups during resistance training exercises commonly used for training the hamstrings. Subjects included 34 collegiate athletes. Hamstring and quadriceps MVIC and 6 repetition maximum loads were determined. Data were collected 72 hours later, during the performance of 6 randomly ordered exercises, including back squats, seated leg curls, stiff leg dead lifts, single leg dead lifts, good mornings, and “Russian curls.” Data were analyzed using RMS values normalized to MVIC. A one way repeated measures ANOVA revealed that significant differences existed between several exercises. Additionally, the ratio of hamstring to quadriceps co-activation was significantly different between all exercises

The application of resilience concepts in palaeoecology

The concept of resilience has become increasingly important in ecological and socio-ecological literature. With its focus on the temporal behaviour of ecosystems, palaeoecology has an important role to play in developing a scientific understanding of ecological resilience. We provide a critical review of the ways in which resilience is being addressed by palaeoecologists. We review ~180 papers, identifying the definitions or conceptualisations of ‘resilience’ that they use, and analysing the ways in which palaeoecology is contributing to our understanding of ecological resilience. We identify three key areas for further development. Firstly, the term ‘resilience’ is frequently defined too broadly to be meaningful without further qualification. In particular, palaeoecologists need to distinguish between ‘press’ vs. ‘pulse’ disturbances, and ‘ecological’ vs. ‘engineering’ resilience. Palaeoecologists are well placed to critically assess the extent to which these dichotomies apply in real (rather than theoretical) ecosystems, where climate and other environmental parameters are constantly changing. Secondly, defining a formal ‘response model’ - a statement of the anticipated relationships between proxies, disturbances and resilience properties - can help to clarify arguments, especially inferred causal links, since the difficulty of proving causation is a fundamental limitation of palaeoecology for understanding ecosystem drivers and responses. Thirdly, there is a need for critical analysis of the role of scale in ecosystem resilience. Different palaeoenvironmental proxies are differently able to address the various temporal and spatial scales of ecological change, and these limitations, as well as methodological constraints on inherently noisy proxy data, need to be explored and addressed.PostprintPeer reviewe

Nondestructive SEM for surface and subsurface wafer imaging

The scanning electron microscope (SEM) is considered as a tool for both failure analysis as well as device characterization. A survey is made of various operational SEM modes and their applicability to image processing methods on semiconductor devices