Water quality monitoring: a ‘toolbox’ in response to the EU’s Water Framework Directive requirements

International audienc

Electrical Writing of Magnetic and Resistive Multistates in CoFe Films Deposited onto Pb[Zrx_xTi1−x_{1-x}]O3_3

Electric control of magnetic properties is an important challenge for modern magnetism and spintronic development. In particular, an ability to write magnetic state electrically would be highly beneficial. Among other methods, the use of electric field induced deformation of piezoelectric elements is a promising low-energy approach for magnetization control. We investigate the system of piezoelectric substrate Pb[Zr$_x$Ti$_{1-x}$]O$_3$ with CoFe overlayers, extending the known reversible bistable electro-magnetic coupling to surface and multistate operations, adding the initial state reset possibility. Increasing the CoFe thickness improves the magnetoresistive sensitivity, but at the expenses of decreasing the strain-mediated coupling, with optimum magnetic thin film thickness of the order of 100 nm. The simplest resistance strain gauge structure is realized and discussed as a multistate memory cell demonstrating both resistive memory (RRAM) and magnetoresistive memory (MRAM) functionalities in a single structure.Comment: 20th International Conference on Magnetism, ICM 2015, 11 pages, 7 figure

Optical Writing of Magnetic Properties by Remanent Photostriction.

We present an optically induced remanent photostriction in BiFeO_{3}, resulting from the photovoltaic effect, which is used to modify the ferromagnetism of Ni film in a hybrid BiFeO_{3}/Ni structure. The 75% change in coercivity in the Ni film is achieved via optical and nonvolatile control. This photoferromagnetic effect can be reversed by static or ac electric depolarization of BiFeO_{3}. Hence, the strain dependent changes in magnetic properties are written optically, and erased electrically. Light-mediated straintronics is therefore a possible approach for low-power multistate control of magnetic elements relevant for memory and spintronic applications

Systems thinking and efficiency under emissions constraints: Addressing rebound effects in digital innovation and policy

Innovations and efficiencies in digital technology have lately been depicted as paramount in the green transition to enable the reduction of greenhouse gas emissions, both in the information and communication technology (ICT) sector and the wider economy. This, however, fails to adequately account for rebound effects that can offset emission savings and, in the worst case, increase emissions. In this perspective, we draw on a transdisciplinary workshop with 19 experts from carbon accounting, digital sustainability research, ethics, sociology, public policy, and sustainable business to expose the challenges of addressing rebound effects in digital innovation processes and associated policy. We utilize a responsible innovation approach to uncover potential ways forward for incorporating rebound effects in these domains, concluding that addressing ICT-related rebound effects ultimately requires a shift from an ICT efficiency-centered perspective to a “systems thinking” model, which aims to understand efficiency as one solution among others that requires constraints on emissions for ICT environmental savings to be realized

Surface indicators are correlated with soil multifunctionality in global drylands

Multiple ecosystem functions need to be considered simultaneously to manage and protect the several ecosystem services that are essential to people and their environments. Despite this, cost effective, tangible, relatively simple and globally relevant methodologies to monitor in situ soil multifunctionality, that is, the provision of multiple ecosystem functions by soils, have not been tested at the global scale. We combined correlation analysis and structural equation modelling to explore whether we could find easily measured, field-based indicators of soil multifunctionality (measured using functions linked to the cycling and storage of soil carbon, nitrogen and phosphorus). To do this, we gathered soil data from 120 dryland ecosystems from five continents. Two soil surface attributes measured in situ (litter incorporation and surface aggregate stability) were the most strongly associated with soil multifunctionality, even after accounting for geographic location and other drivers such as climate, woody cover, soil pH and soil electric conductivity. The positive relationships between surface stability and litter incorporation on soil multifunctionality were greater beneath the canopy of perennial vegetation than in adjacent, open areas devoid of vascular plants. The positive associations between surface aggregate stability and soil functions increased with increasing mean annual temperature. Synthesis and applications. Our findings demonstrate that a reduced suite of easily measured in situ soil surface attributes can be used as potential indicators of soil multifunctionality in drylands world-wide. These attributes, which relate to plant litter (origin, incorporation, cover), and surface stability, are relatively cheap and easy to assess with minimal training, allowing operators to sample many sites across widely varying climatic areas and soil types. The correlations of these variables are comparable to the influence of climate or soil, and would allow cost-effective monitoring of soil multifunctionality under changing land-use and environmental conditions. This would provide important information for evaluating the ecological impacts of land degradation, desertification and climate change in drylands world-wide.Fil: Eldridge, David J.. University of New South Wales; AustraliaFil: Delgado Baquerizo, Manuel. Universidad Rey Juan Carlos; EspañaFil: Quero, José L.. Universidad de Córdoba; EspañaFil: Ochoa, Victoria. Universidad Rey Juan Carlos; España. Universidad de Alicante; EspañaFil: Gozalo, Beatriz. Universidad Rey Juan Carlos; España. Universidad de Alicante; EspañaFil: García Palacios, Pablo. Universidad Rey Juan Carlos; EspañaFil: Escolar, Cristina. Universidad Rey Juan Carlos; EspañaFil: García Gómez, Miguel. Universidad Politécnica de Madrid; EspañaFil: Prina, Aníbal. Universidad Nacional de La Pampa; ArgentinaFil: Bowker, Mathew A.. Northern Arizona University; Estados UnidosFil: Bran, Donaldo Eduardo. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche; ArgentinaFil: Castro, Ignacio. Universidad Experimental Simón Rodríguez; VenezuelaFil: Cea, Alex. Universidad de La Serena; ChileFil: Derak, Mchich. No especifíca;Fil: Espinosa, Carlos I.. Universidad Técnica Particular de Loja; EcuadorFil: Florentino, Adriana. Universidad Central de Venezuela; VenezuelaFil: Gaitán, Juan José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Suelos; Argentina. Universidad Nacional de Luján. Departamento de Tecnología; ArgentinaFil: Gatica, Mario Gabriel. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Centro de Investigaciones de la Geosfera y Biosfera. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Investigaciones de la Geosfera y Biosfera; ArgentinaFil: Gómez González, Susana. Universidad de Cádiz; EspañaFil: Ghiloufi, Wahida. Université de Sfax; TúnezFil: Gutierrez, Julio R.. Universidad de La Serena; ChileFil: Guzman, Elizabeth. Universidad Técnica Particular de Loja; EcuadorFil: Hernández, Rosa M.. Universidad Experimental Simón Rodríguez; VenezuelaFil: Hughes, Frederic M.. Universidade Estadual de Feira de Santana; BrasilFil: Muiño, Walter. Universidad Nacional de La Pampa; ArgentinaFil: Monerris, Jorge. No especifíca;Fil: Ospina, Abelardo. Universidad Central de Venezuela; VenezuelaFil: Ramírez, David A.. International Potato Centre; PerúFil: Ribas Fernandez, Yanina Antonia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Centro de Investigaciones de la Geosfera y Biosfera. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Investigaciones de la Geosfera y Biosfera; ArgentinaFil: Romão, Roberto L.. Universidade Estadual de Feira de Santana; BrasilFil: Torres Díaz, Cristian. Universidad del Bio Bio; ChileFil: Koen, Terrance B.. No especifíca;Fil: Maestre, Fernando T.. Universidad Rey Juan Carlos; España. Universidad de Alicante; Españ

Surface indicators are correlated with soil multifunctionality in global drylands

1. Multiple ecosystem functions need to be considered simultaneously to manage and protect the several ecosystem services that are essential to people and their environments. Despite this, cost effective, tangible, relatively simple and globally relevant methodologies to monitor in situ soil multifunctionality, that is, the provision of multiple ecosystem functions by soils, have not been tested at the global scale. 2. We combined correlation analysis and structural equation modelling to explore whether we could find easily measured, field‐based indicators of soil multifunctionality (measured using functions linked to the cycling and storage of soil carbon, nitrogen and phosphorus). To do this, we gathered soil data from 120 dryland ecosystems from five continents. 3. Two soil surface attributes measured in situ (litter incorporation and surface aggregate stability) were the most strongly associated with soil multifunctionality, even after accounting for geographic location and other drivers such as climate, woody cover, soil pH and soil electric conductivity. The positive relationships between surface stability and litter incorporation on soil multifunctionality were greater beneath the canopy of perennial vegetation than in adjacent, open areas devoid of vascular plants. The positive associations between surface aggregate stability and soil functions increased with increasing mean annual temperature. 4. Synthesis and applications. Our findings demonstrate that a reduced suite of easily measured in situ soil surface attributes can be used as potential indicators of soil multifunctionality in drylands world‐wide. These attributes, which relate to plant litter (origin, incorporation, cover), and surface stability, are relatively cheap and easy to assess with minimal training, allowing operators to sample many sites across widely varying climatic areas and soil types. The correlations of these variables are comparable to the influence of climate or soil, and would allow cost‐effective monitoring of soil multifunctionality under changing land‐use and environmental conditions. This would provide important information for evaluating the ecological impacts of land degradation, desertification and climate change in drylands world‐wide.This work was funded by the European Research Council ERC Grant agreement 242658 (BIOCOM). CYTED funded networking activities (EPES, Acción 407AC0323). D.J.E. acknowledges support from the Australian Research Council (DP150104199) and F.T.M. support from the European Research Council (BIODESERT project, ERC Grant agreement no 647038), from the Spanish Ministerio de Economía y Competitividad (BIOMOD project, ref. CGL2013-44661-R) and from a Humboldt Research Award from the Alexander von Humboldt Foundation. M.D.-B. was supported by REA grant agreement no 702057 from the Marie Sklodowska-Curie Actions of the Horizon 2020 Framework Programme H2020-MSCA-IF-2016), J.R.G. acknowledges support from CONICYT/FONDECYT no 1160026

The Psychological Science Accelerator's COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20\%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors

The Liver Tumor Segmentation Benchmark (LiTS)

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LITS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2016 and International Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017. Twenty four valid state-of-the-art liver and liver tumor segmentation algorithms were applied to a set of 131 computed tomography (CT) volumes with different types of tumor contrast levels (hyper-/hypo-intense), abnormalities in tissues (metastasectomie) size and varying amount of lesions. The submitted algorithms have been tested on 70 undisclosed volumes. The dataset is created in collaboration with seven hospitals and research institutions and manually reviewed by independent three radiologists. We found that not a single algorithm performed best for liver and tumors. The best liver segmentation algorithm achieved a Dice score of 0.96(MICCAI) whereas for tumor segmentation the best algorithm evaluated at 0.67(ISBI) and 0.70(MICCAI). The LITS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.Comment: conferenc