A New Sparsification and Reconstruction Strategy for Compressed Sensing Photoacoustic Tomography

Compressed sensing (CS) is a promising approach to reduce the number of measurements in photoacoustic tomography (PAT) while preserving high spatial resolution. This allows to increase the measurement speed and to reduce system costs. Instead of collecting point-wise measurements, in CS one uses various combinations of pressure values at different sensor locations. Sparsity is the main condition allowing to recover the photoacoustic (PA) source from compressive measurements. In this paper we introduce a new concept enabling sparse recovery in CS PAT. Our approach is based on the fact that the second time derivative applied to the measured pressure data corresponds to the application of the Laplacian to the original PA source. As typical PA sources consist of smooth parts and singularities along interfaces the Laplacian of the source is sparse (or at least compressible). To efficiently exploit the induced sparsity we develop a reconstruction framework to jointly recover the initial and the modified sparse source. Reconstruction results with simulated as well as experimental data are given.Comment: 15 pages, 10 figure

A MS-lesion pattern discrimination plot based on geostatistics

Introduction A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. Methods A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. Results Parameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot. Conclusions The geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis

A R-Script for Generating Multiple Sclerosis Lesion Pattern Discrimination Plots

Càlcul estadístic R; Geoestadística; Esclerosi múltipleCálculo estadístico R; Geoestadística; Esclerosis múltipleR statistical computing; Geostatistics; Multiple sclerosisOne significant characteristic of Multiple Sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is the evolution of highly variable patterns of white matter lesions. Based on geostatistical metrics, the MS-Lesion Pattern Discrimination Plot reduces complex three- and four-dimensional configurations of MS-White Matter Lesions to a well-arranged and standardized two-dimensional plot that facilitates follow-up, cross-sectional and medication impact analysis. Here, we present a script that generates the MS-Lesion Pattern Discrimination Plot, using the widespread statistical computing environment R. Input data to the script are Nifti-1 or Analyze-7.5 files with individual MS-White Matter Lesion masks in Montreal Normal Brain geometry. The MS-Lesion Pattern Discrimination Plot, variogram plots and associated fitting statistics are output to the R console and exported to standard graphics and text files. Besides reviewing relevant geostatistical basics and commenting on implementation details for smooth customization and extension, the paper guides through generating MS-Lesion Pattern Discrimination Plots using publicly available synthetic MS-Lesion patterns. The paper is accompanied by the R script LDPgenerator.r, a small sample data set and associated graphics for comparison

With United Forces : How Design-Based Research can Link Theory and Practice in the Transdisciplinary Sphere of CLIL

This paper intends to exemplify how a design-based research (DBR) methodology can be used to put theory into practice by reporting on a first research cycle of a larger DBR project in the context of upper secondary CLIL history education in Austria. The project aims to identify design principles of teaching techniques and materials which both support the acquisition of subject-specific competences and language. To this end, this study draws on Dalton-Puffer's (2013) construct of Cognitive Discourse Functions (CDFs), comprising seven key categories of academic language functions which have also been shown to be closely linked to historical competences. In the course of this study, the researcher and a collaborating teacher systematically developed CDF-based history materials, which were then applied in the classroom and continuously evaluated, usinginterviews, observations, and written tasks for data collection.Results of the first research cycle suggest that students lack awareness of possible connections between content and language learning and struggle with expressing complex historical content. Both teacher and students responded positively to the intervention on a general level, but pointed out a number of potential refinements, such as a more continuous and balanced intertwining of content and language.Aquest article aspira a exemplificar com es pot utilitzar una metodologia d'investigació basada en el disseny d'una intervenció (DBR, sigles en anglès) per portar la teoria a la pràctica. A més a més, proporciona informació sobre el primer cicle d'investigació d'un projecte DBR de major abast, en un context educatiu d'història AICLE en el cicle superior de secundària a Àustria.L'objectiu del projecte és identificar els principis que inspiren les estratègies didàctiques i els materials d'ensenyament que fomenten l'adquisició de competències i llenguatge específics de la matèria. En aquest sentit, aquest estudi es basa en el concepte Funcions cognitivo-discursives (FCD), de Dalton-Puffer (2013), que comprèn set categories clau de funcions del llenguatge acadèmic, les quals, segons s'ha demostrat, estan estretament relacionades amb les competències històriques.En el curs d'aquest estudi, la persona investigadora i un docent col·laborador van desenvolupar sistemàticament materials de l'ensenyament de la història basats en el FCD que, posteriorment, es van pilotar i avaluar de forma continuada a l'aula, emprant entrevistes, observacions i tasques d'escriptura, utilitzades com a dades.Els resultats del primer cicle d'investigació suggereixen que els estudiants mostren una manca de consciència sobre les possibles connexions entre l'aprenentatge del contingut i el de la llengua, i tenen dificultats per expressar continguts històrics complexos. Tant el docent com els estudiants van respondre positivament a la intervenció en un nivell general, però van assenyalar una sèrie de possibles millores, tals com una interrelació més continuada i equilibrada de contingut i llengua.Este artículo aspira a ejemplificar cómo se puede utilizar una metodología de investigación basada en el diseño de una intervención (DBR, siglas en inglés) para llevar la teoría a la práctica. Además, proporciona información sobre el primer ciclo de investigación de un proyecto DBR de mayor alcance, en un contexto educativo de historia AICLE en el ciclo superior de secundaria en Austria.El objetivo del proyecto es identificar los principios que inspiran las estrategias didácticas y los materiales de enseñanza que fomentan la adquisición de competencias y lenguaje específicos de la asignatura. Para este fin, este estudio se basa en el constructo Funciones cognitivo-discursivas (FCD), de Dalton-Puffer (2013), que comprende siete categorías clave de funciones del lenguaje académico, las cuales, según se ha demostrado, están estrechamente relacionadas con las competencias históricas.En el curso de este estudio, la persona investigadora y un docente colaborador desarrollaron sistemáticamente materiales de enseñanza de la historia basados en el FCD, que luego se pilotaron y evaluaron de forma continuada en el aula, utilizando entrevistas, observaciones y tareas de escritura, utilizadas como datos.Los resultados del primer ciclo de investigación sugieren que los estudiantes muestran falta de conciencia sobre las posibles conexiones entre el aprendizaje del contenido y el de la lengua, y tienen dificultades para expresar contenidos históricos complejos. Tanto el docente como los estudiantes respondieron positivamente a la intervención en un nivel general, pero señalaron una serie de posibles mejoras tales como una interrelación más continuada y equilibrada de contenido y lenguaje

Breaking the Resolution limit in Photoacoustic Imaging using Positivity and Sparsity

In this tutorial, we aim to directly recreate some of our "aha" moments when exploring the impact of heat diffusion on the spatial resolution limit of photothermal imaging. Our objective is also to communicate how this physical limit can nevertheless be overcome and include some concrete technological applications. Describing diffusion as a random walk, one insight is that such a stochastic process involves not only a Gaussian spread of the mean values in space, with the variance proportional to the diffusion time, but also temporal and spatial fluctuations around these mean values. All these fluctuations strongly influence the image reconstruction immediately after the short heating pulse. The Gaussian spread of the mean values in space increases the entropy, while the fluctuations lead to a loss of information that blurs the reconstruction of the initial temperature distribution and can be described mathematically by a spatial convolution with a Gaussian thermal point-spread-function (PSF). The information loss turns out to be equal to the mean entropy increase and limits the spatial resolution proportional to the depth of the imaged subsurface structures. This principal resolution limit can only be overcome by including additional information such as sparsity or positivity. Prior information can be also included by using a deep neural network with a finite degrees of freedom and trained on a specific class of image examples for image reconstructio

Evaluation of remotely sensed soil moisture products using crowdsourced measurements

Global soil moisture products retrieved from various sensors onboard satellites are becoming readily available. However, validation of such products is a crucial step to ensure their reliability. In-situ measurements, which provide the most accurate soil moisture estimates, are often used as reference dataset, but they are limited in number. The GROW Observatory (GROW) was initiated to demonstrate that a 'Citizens' Observatory' (CO) can provide and utilise unprecedented amounts of data. We present GROW as a case study and demonstrate, for the first time, the use of crowdsourced observations to assess the temporal and spatial consistency of various satellite-derived soil moisture products. In particular, we provide evidence of the added value to Earth Observation, thanks to (i) the high number of sensors deployed, covering a wide range of land use, environmental, and climatic conditions, and (ii) the unique spatial density in GROW. Our results confirmed that SMAP and ESA CCI SM can better capture the temporal dynamics compared to the other products investigated. We found high uncertainties due to the spatial mismatch between in-situ and satellite observations, not only for coarse scale but also for high-resolution soil moisture products. This finding highlights the importance of crowdsourced observations, which have the potential to reduce representativeness errors. Finally, a preliminary analysis of the spatial consistency of Sentinel-1 soil moisture showed a poor agreement against GROW data. We conclude presenting the challenges and the steps that will follow this preliminary analysis, as well as design guidelines for COs to meaningfully contribute to Earth Observation.<br/

What determines growth potential and juvenile quality of farmed fish species?

Enhanced production of high quality and healthy fry is a key target for a successful and competitive expansion of the aquaculture industry. Although large quantities of fish larvae are produced, survival rates are often low or highly variable and growth potential is in most cases not fully exploited, indicating significant gaps in our knowledge concerning optimal nutritional and culture conditions. Understanding the mechanisms that control early development and muscle growth are critical for the identification of time windows in development that introduce growth variation, and improve the viability and quality of juveniles. This literature review of the current state of knowledge aims to provide a framework for a better understanding of fish skeletal muscle ontogeny, and its impact on larval and juvenile quality as broadly defined. It focuses on fundamental biological knowledge relevant to larval phenotype and quality and, in particular, on the factors affecting the development of skeletal muscle. It also discusses the available methodologies to assess growth and larvae/juvenile quality, identifies gaps in knowledge and suggests future research directions. The focus is primarily on the major farmed non-salmonid fish species in Europe that include gilthead sea bream, European sea bass, turbot, Atlantic cod, Senegalese sole and Atlantic halibut

The G Protein-Coupled Receptor GPR17: Overview and Update

The GPR17 receptor is a G protein-coupled receptor (GPCR) that seems to respond to two unrelated families of endogenous ligands: nucleotide sugars (UDP, UDP-galactose, and UDP-glucose) and cysteinyl leukotrienes (LTD4 , LTC4 , and LTE4 ), with significant affinity at micromolar and nanomolar concentrations, respectively. This receptor has a broad distribution at the level of the central nervous system (CNS) and is found in neurons and in a subset of oligodendrocyte precursor cells (OPCs). Unfortunately, disparate results emerging from different laboratories have resulted in a lack of clarity with regard to the role of GPR17-targeting ligands in OPC differentiation and in myelination. GPR17 is also highly expressed in organs typically undergoing ischemic damage and has various roles in specific phases of adaptations that follow a stroke. Under such conditions, GPR17 plays a crucial role; in fact, its inhibition decreases the progression of ischemic damage. This review summarizes some important features of this receptor that could be a novel therapeutic target for the treatment of demyelinating diseases and for repairing traumatic injury