Active Unsupervised Texture Segmentation on a Diffusion Based Feature Space

In this report, we propose a novel and efficient approach for active unsurpervised texture segmentation. First, we show how we can extract a small set of good features for texture segmentation based on the structure tensor and nonlinear diffusion. Then, we propose a variational framework that allows to incorporate these features in a level set based unsupervised segmentation process that adaptively takes into account their estimated statistical information inside and outside the region to segment. Unlike features obtained by Gabor filters, our approach naturally leads to a significantly reduced number of feature channels. Thus, the supervised part of a texture segmentation algorithm, where the choice of good feature channels has to be learned in advance, can be omitted, and we get an efficient solution for unsupervised texture segmentation. The actual segmentation process based on the new features is an active and adaptative contour model that estimates dynamically probability density functions inside and outside a region and produces very convincing results. It is implemented using a fast level set based active contour technique and has been tested on various real textured images. The performance of the approach is favorably compared to recent studies

Deep unsupervised domain adaptation applied to the Cherenkov Telescope Array Large-Sized Telescope

The Cherenkov Telescope Array is the next generation of observatory using imaging air Cherenkov technique for very-high-energy gamma-ray astronomy. Its first prototype telescope is operational on-site at La Palma and its data acquisitions allowed to detect known sources, study new ones, and to confirm the performance expectations. The application of deep learning for the reconstruction of the incident particle physical properties (energy, direction of arrival and type) have shown promising results when conducted on simulations. Nevertheless, its application to real observational data is challenging because deep-learning-based models can suffer from domain shifts. In the present article, we address this issue by implementing domain adaptation methods into state-of-art deep learning models for Imaging Atmospheric Cherenkov Telescopes event reconstruction to reduce the domain discrepancies, and we shed light on the gain in performance that they bring along

Simulation of 3D periodic piezoelectric transducers radiating in layered media using Finite Element/Boundary element Analysis

Abstract. This paper is devoted to the description of a mixed finite element/boundary element analysis for the simulation of any periodic transducer radiating in any combination of solid and fluids assuming flat interfaces and linear operation regime. The theoretical developments required in that purpose are described and different examples of transducers are considered to demonstrate the interest of the proposed approach. 1

Extracellular matrix and growth factor engineering for controlled angiogenesis in regenerative medicine

Blood vessel growth plays a key role in regenerative medicine, both to restore blood supply to ischemic tissues and to ensure rapid vascularization of clinical-size tissue-engineered grafts. For example, vascular endothelial growth factor (VEGF) is the master regulator of physiological blood vessel growth and is one of the main molecular targets of therapeutic angiogenesis approaches. However, angiogenesis is a complex process and there is a need to develop rational therapeutic strategies based on a firm understanding of basic vascular biology principles, as evidenced by the disappointing results of initial clinical trials of angiogenic factor delivery. In particular, the spatial localization of angiogenic signals in the extracellular matrix (ECM) is crucial to ensure the proper assembly and maturation of new vascular structures. Here, we discuss the therapeutic implications of matrix interactions of angiogenic factors, with a special emphasis on VEGF, as well as provide an overview of current approaches, based on protein and biomaterial engineering that mimic the regulatory functions of ECM to optimize the signaling microenvironment of vascular growth factors

Relations among neutrino observables in the light of a large theta_13 angle

The recent T2K and MINOS indications for a "large" theta_13 neutrino mixing angle can be accommodated in principle by an infinite number of Yukawa flavour structures in the seesaw model. Without considering any explicit flavour symmetry, there is an instructive exercise one can do: to determine the simplest flavour structures which can account for the data with a minimum number of parameters, simply assuming these parameters to be uncorrelated. This approach points towards a limited number of simple structures which show the minimum complexity a neutrino mass model must generally involve to account for the data. These basic structures essentially lead to only 4 relations between the neutrino observables. We emphasize that 2 of these relations, |sin theta_13|=(tan theta_23/cos delta)*(1-tan theta_12)/(1+tan theta_12) and |sin theta_13| = sin theta_12 R^1/4, with R= Delta m^2_21/Delta m^2_32, have several distinctive properties. First, they hold not only with a minimum number of parameters, but also for complete classes of more general models. Second, any value of theta_13 within the T2K and MINOS ranges can be obtained from these relations by taking into account small perturbations. Third, they turn out to be the pivot relations of models with approximate conservation of lepton number, which allow the seesaw interactions to induce observable flavour violating processes, such as mu -> e gamma and tau -> mu gamma. Finally, in specific cases of this kind, these structures have the rather unique property to allow a full reconstruction of the seesaw Lagrangian from low energy data.Comment: 13 pages, 3 figure

IWGSC Sequence Repository: Moving towards tools to facilitate data integration for the reference sequence of wheat

URGI is a genomics and bioinformatics research unit at INRA (French National institute for Agricultural Research), dedicated to plants and crop parasites. We develop and maintain a genomic and genetic Information System called GnpIS that manages multiple types of wheat data. Under the umbrella of the IWGSC (International Wheat Genome Sequencing Consortium), we have set up a Sequence Repository on the Wheat@URGI website to store, browse and BLAST the data being generated by the wheat genome project: http://wheat-urgi.versailles.inra.fr/Seq-Repository. The repository holds the wheat physical maps, the chromosome survey sequence data for the individual chromosomes of breadwheat, draft sequences for diploid and tetraploid wheats and provides browsable access to the BAC-based reference sequence for chromosome 3B, the first of the chromosomes to be completed by the consortium. I will highlight the new features and data available in the Sequence Repository (e.g., new BLAST functionalities) and, in particular, present what we have done to address needs and concerns raised during the IWGSC S&P workshop last year. In addition, I will open the discussion about the future needs for tools to facilitate the integration of data to produce the reference sequence

J Ultrasound Med

Chest CT is the reference test for assessing pulmonary injury in suspected or diagnosed COVID-19 with signs of clinical severity. This study aimed to evaluate the association of a lung ultrasonography score and unfavorable clinical evolution at 28 days. The eChoVid is a multicentric study based on routinely collected data that was conducted in 8 emergency units in France; patients were included between March 19, 2020 and April 28, 2020 and underwent lung ultrasonography, a short clinical assessment by 2 emergency physicians blinded to each other's assessment, and chest CT. Lung ultrasonography consisted of scoring lesions from 0 to 3 in 8 chest zones, thus defining a global score (GS) of severity from 0 to 24. The primary outcome was the association of lung damage severity as assessed by the GS at day 0 and patient status at 28 days. Secondary outcomes were comparing the performance between GS and CT scan and the performance between a new trainee physician and an ultrasonography expert in scores. For the 328 patients analyzed, the GS showed good performance in predicting clinical worsening at 28 days (area under the receiver operating characteristic curve [AUC] 0.83, sensitivity 84.2%, specificity 76.4%). The GS showed good performance in predicting the CT severity assessment (AUC 0.84, sensitivity 77.2%, specificity 83.7%). A lung ultrasonography GS is a simple tool that can be used in the emergency department to predict unfavorable assessment at 28 days in patients with COVID-19

Shifting the limits in wheat research and breeding using a fully annotated reference genome

Introduction: Wheat (Triticum aestivum L.) is the most widely cultivated crop on Earth, contributing about a fifth of the total calories consumed by humans. Consequently, wheat yields and production affect the global economy, and failed harvests can lead to social unrest. Breeders continuously strive to develop improved varieties by fine-tuning genetically complex yield and end-use quality parameters while maintaining stable yields and adapting the crop to regionally specific biotic and abiotic stresses. Rationale: Breeding efforts are limited by insufficient knowledge and understanding of wheat biology and the molecular basis of central agronomic traits. To meet the demands of human population growth, there is an urgent need for wheat research and breeding to accelerate genetic gain as well as to increase and protect wheat yield and quality traits. In other plant and animal species, access to a fully annotated and ordered genome sequence, including regulatory sequences and genome-diversity information, has promoted the development of systematic and more time-efficient approaches for the selection and understanding of important traits. Wheat has lagged behind, primarily owing to the challenges of assembling a genome that is more than five times as large as the human genome, polyploid, and complex, containing more than 85% repetitive DNA. To provide a foundation for improvement through molecular breeding, in 2005, the International Wheat Genome Sequencing Consortium set out to deliver a high-quality annotated reference genome sequence of bread wheat. Results: An annotated reference sequence representing the hexaploid bread wheat genome in the form of 21 chromosome-like sequence assemblies has now been delivered, giving access to 107,891 high-confidence genes, including their genomic context of regulatory sequences. This assembly enabled the discovery of tissue- and developmental stage–related gene coexpression networks using a transcriptome atlas representing all stages of wheat development. The dynamics of change in complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. Aspects of the future value of the annotated assembly for molecular breeding and research were exemplarily illustrated by resolving the genetic basis of a quantitative trait locus conferring resistance to abiotic stress and insect damage as well as by serving as the basis for genome editing of the flowering-time trait. Conclusion: This annotated reference sequence of wheat is a resource that can now drive disruptive innovation in wheat improvement, as this community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding. Importantly, the bioinformatics capacity developed for model-organism genomes will facilitate a better understanding of the wheat genome as a result of the high-quality chromosome-based genome assembly. By necessity, breeders work with the genome at the whole chromosome level, as each new cross involves the modification of genome-wide gene networks that control the expression of complex traits such as yield. With the annotated and ordered reference genome sequence in place, researchers and breeders can now easily access sequence-level information to precisely define the necessary changes in the genomes for breeding programs. This will be realized through the implementation of new DNA marker platforms and targeted breeding technologies, including genome editing

Inert scalar doublet asymmetry as origin of dark matter

In the inert scalar doublet framework, we analyze what would be the effect of a B-L asymmetry that could have been produced at high temperature in the thermal bath of the Universe. We show that unless the "λ5" scalar interaction is tiny, this asymmetry is automatically reprocessed in part into an inert scalar asymmetry that could be at the origin of dark matter today. Along this scenario, the inert mass scale lies in the few-TeV range, and direct detection constraints require that the inert scalar particles decay into a lighter dark matter particle which, as the inert doublet, is odd under a Z2 symmetry.SCOPUS: ar.jinfo:eu-repo/semantics/publishe