Optimum delay and mean square error using CMA

The performance of the constant modulus algorithm can suffer because of the existence of local minima with large mean squared error (MSE). This paper presents a new way of obtaining the optimum MSE over all delays using a second equalizer under a mixed constant modulus and cross correlation algorithm (CM-CCA). Proof of convergence is obtained for the noiseless case. Simulations demonstrate the potential of the metho

Subject-specific, multiscale simulation of electrophysiology: a software pipeline for image-based models and application examples

Many simulation studies in biomedicine are based on a similar sequence of processing steps, starting from images and running through geometric model generation, assignment of tissue properties, numerical simulation and visualization of the results—a process known as image-based geometric modelling and simulation. We present an overview of software systems for implementing such a sequence both within highly integrated problem-solving environments and in the form of loosely integrated pipelines. Loose integration in this case indicates that individual programs function largely independently but communicate through files of a common format and support simple scripting, so as to automate multiple executions wherever possible. We then describe three specific applications of such pipelines to translational biomedical research in electrophysiology

CDKI-73 is a novel pharmacological inhibitor of Rab11 cargo delivery and innate immune secretion

Innate immunity is critical for host defence against pathogen and environmental challenge and this involves the production and secretion of immune mediators, such as antimicrobial peptides and pro-inflammatory cytokines. However, when dysregulated, innate immunity can contribute to multifactorial diseases, including inflammatory rheumatic disorders, type 2 diabetes, cancer, neurodegenerative and cardiovascular diseases and even septic shock. During an innate immune response, antimicrobial peptides and cytokines are trafficked via Rab11 multivesicular endosomes, and then sorted into Rab11 vesicles for traffic to the plasma membrane and secretion. In this study, a cyclin-dependent kinase inhibitor CDKI-73 was used to determine its effect on the innate immune response, based on previously identified targets for this compound. Our results showed that CDKI-73 inhibited the delivery of Rab11 vesicles to the plasma membrane, resulting in the accumulation of large multivesicular Rab11 endosomes near the cell periphery. In addition to the effect on endosome delivery, CDKI-73 down-regulated the amount of innate immune cargo, including the antimicrobial peptide Drosomycin and pro-inflammatory cytokines interleukin-6 (IL-6) and tumour necrosis factor alpha (TNFα). We concluded that CDKI-73 has the potential to regulate the delivery and secretion of certain innate immune cargo, which could be used to control inflammation.Alexandra Sorvina, Tetyana Shandala, Shudong Wang, David J. Sharkey, Emma Parkinson-Lawrence, Stavros Selemidis and Douglas A. Brook

Signatures of the slow solar wind streams from active regions in the inner corona

Some of local sources of the slow solar wind can be associated with spectroscopically detected plasma outflows at edges of active regions accompanied with specific signatures in the inner corona. The EUV telescopes (e.g. SPIRIT/CORONAS-F, TESIS/CORONAS-Photon and SWAP/PROBA2) sometimes observed extended ray-like structures seen at the limb above active regions in 1MK iron emission lines and described as "coronal rays". To verify the relationship between coronal rays and plasma outflows, we analyze an isolated active region (AR) adjacent to small coronal hole (CH) observed by different EUV instruments in the end of July - beginning of August 2009. On August 1 EIS revealed in the AR two compact outflows with the Doppler velocities V =10-30 km/s accompanied with fan loops diverging from their regions. At the limb the ARCH interface region produced coronal rays observed by EUVI/STEREO-A on July 31 as well as by TESIS on August 7. The rays were co-aligned with open magnetic field lines expanded to the streamer stalks. Using the DEM analysis, it was found that the fan loops diverged from the outflow regions had the dominant temperature of ~1 MK, which is similar to that of the outgoing plasma streams. Parameters of the solar wind measured by STEREO-B, ACE, WIND, STEREO-A were conformed with identification of the ARCH as a source region at the Wang-Sheeley-Arge map of derived coronal holes for CR 2086. The results of the study support the suggestion that coronal rays can represent signatures of outflows from ARs propagating in the inner corona along open field lines into the heliosphere.Comment: Accepted for publication in Solar Physics; 31 Pages; 13 Figure

The Fezzan Project 2001: Preliminary report on the fifth season of work

AbstractThe Fezzan Project completed its five-year fieldwork cycle in 2001. The geographical research team located numerous additional palaeolake sites within the Edeyen Ubari, using a combination of Remote Sensing technology and field visits. Additional samples were taken for analysis and dating from many lake edge locations, relating to both the large Pleistocene lake and to the numerous smaller Holocene lakes that have been identified by the team. The excavations at Old Germa were taken down through Garamantian occupation levels to the natural subsoil below the earliest cultural horizon. The earliest activity, represented by a few mudbrick walls and hearths built directly on the natural soil, is believed to date toc. 400-300 BC. Traces of several phases of Garamantian buildings were uncovered, along with numerous rubbish pits, which yielded a rich assemblage of finds, including, for the first time, examples of Garamantian figurines, small 3-D sculptures of humans and animals. Work on the various classes of finds (pottery, small finds, lithics and other stone artefacts, metallurgical evidence, etc.) complemented the excavation work. In addition, a small amount of further survey work was carried out on sites in the Wadi al-Ajal, along with a contour survey of Old Germa and standing building survey at a number of other sites.</jats:p

Seasonal size variation in the predatory cladoceran Bythotrephes cederstroemii in Lake Michigan

1.  Dry weight, body length and spine length were measured for the exotic cladoceran Bythotrephes cederstroemii collected from offshore and inshore stations in southeastern Lake Michigan. Average dry weight of each developmental stage exhibited seasonal variation by a factor of more than 5. 2.  Mean dry weight of Bythotrephes was closely correlated with water temperature. Contrary to the inverse relationship between water temperature and body size frequently observed for other invertebrates, the dry weight of Bythotrephes increased at higher ambient temperatures. 3.  No significant correlation was observed between abundances of major zooplankton taxa and the dry weight of Bythotrephes . An indirect effect of temperature on prey consumption may cause seasonal variation in dry weight of Bythotrephes in Lake Michigan. 4.  Distances between adjacent pairs of barbs, added to the caudal spine with each moult, are significantly shorter in Bythotrephes which produce resting eggs. Less material investment in the exoskeleton of sexually reproducing females was observed in favour of growth and reproduction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74641/1/j.1365-2427.1994.tb00842.x.pd

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

3D visualization processes for recreating and studying organismal form

The study of biological form is a vital goal of evolutionary biology and functional morphology. We review an emerging set of methods that allow scientists to create and study accurate 3D models of living organisms and animate those models for biomechanical and fluid dynamic analyses. The methods for creating such models include 3D photogrammetry, laser and CT-scanning, and 3D software. New multi-camera devices can be used to create accurate 3D models of living animals in the wild and captivity. New websites and virtual reality/augmented reality devices now enable the visualization and sharing of these data. We provide examples of these approaches for animals ranging from large whales to lizards and show applications for several areas: Natural history collections; body condition/scaling, bioinspired robotics, computational fluids dynamics (CFD), machine learning, and education. We provide two data sets to demonstrate the efficacy of CFD and machine learning approaches and conclude with a prospectus