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

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lack awareness of possible connections between content and language learning and struggle with expressing complex historical content.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/

Sentinel-1-based analysis of the severe flood over Pakistan 2022

In August and September 2022, Pakistan was hit by a severe flood, and millions of people were impacted. The Sentinel-1-based flood mapping algorithm developed by Technische Universität Wien (TU Wien) for the Copernicus Emergency Management Service (CEMS) global flood monitoring (GFM) component was used to document the propagation of the flood from 10 August to 23 September 2022. The results were evaluated using the flood maps from the CEMS rapid mapping component. Overall, the algorithm performs reasonably well with a critical success index of up to 80 %, while the detected differences can be primarily attributed to the time difference of the algorithm's results and the corresponding reference. Over the 6-week time span, an area of 30 492 km2 was observed to be flooded at least once, and the maximum extent was found to be present on 30 August. The study demonstrates the ability of the TU Wien flood mapping algorithm to fully automatically produce large-scale results and how key data of an event can be derived from these results.</p

Long-term Soil Moisture Time Series Analyses based on Active Microwave Backscatter Measurements

Active microwave sensors operating at lower microwave frequencies in the range from 1 to 10 GHz provide backscatter measurements that are sensitive to the moisture content of the soil. Thanks to a series of European C-band (5.3 GHz) scatterometers, which were first flown on board of the European Remote Sensing satellites ERS-1 and ERS-2, and later on board of MetOp-A and MetOp -B, we are now in the possession of a long-term soil moisture time series starting in 1991. The creation of globally consistent long-term soil moisture time series is a challenging task. The TU-Wien soil moisture algorithm is adopted to tackle these challenges. In this paper we present two methodologies that were developed to ensure radiometric stability of the European C-band scatterometers. The objective of sensor intra-calibration is to monitor and correct for radiometric instabilities within one scatterometer mission, while sensor inter-calibration aims to remove radiometric differences across several missions. In addition, a novel vegetation modelling approach is presented that enables the estimation of vegetation parameters for each day across several years to account for yearly to longer-term changes in vegetation phenology and land cover

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

Widespread occurrence of anomalous C-band backscatter signals in arid environments caused by subsurface scattering

Backscatter measured by scatterometers and Synthetic Aperture Radars is sensitive to the dielectric properties of the soil and normally increases with increasing soil moisture content. However, when the soil is dry, the radar waves penetrate deeper into the soil, potentially sensing subsurface scatterers such as near-surface rocks and stones. In this paper we propose an exponential model to describe the impact of such subsurface scatterers on C-Band backscatter measurements acquired by the Advanced Scatterometer (ASCAT) on board of the METOP satellites. The model predicts an increase of the subsurface scattering contributions with decreasing soil wetness that may counteract the signal from the soil surface. This may cause anomalous backscatter signals that deteriorate soil moisture retrievals from ASCAT. We test whether this new model is able to explain ASCAT observations better than a bare soil backscatter model without a subsurface scattering term, using k-fold cross validation and the Bayesian Information Criterion for model selection. We find that arid landscapes with Leptosols and Arenosols represent ideal environmental conditions for the occurrence of subsurface scattering. Nonetheless, subsurface scattering may also become important in more humid environments during dry spells. We conclude that subsurface scattering is a widespread phenomenon that (i) needs to be accounted for in active microwave soil moisture retrievals and (ii) has a potential for soil mapping, particularly in arid and semi-arid environments