Deployment and evaluation of an Industry 4.0 use case over 5G

The arrival of 5G paves the way for the deployment of the so-called Industry 4.0, which is a new paradigm devoted to the digital transformation of manufacturing and factory production. Because of the resources required to perform this transformation, the importance of field trials and experimentation cannot be overstated, both to support the design of novel methodologies and to validate these designs. In this article, we leverage the 5G EVE end-to-end open platform to design and validate a novel operation approach for automated guided vehicles (AGVs). This use case consists of the placement of the intelligence that controls the AGV in a remote entity. This movement could improve and simplify the operation of industrial processes. The customizability of the 5G validation platform proves fundamental to evaluate the solution under different deployment architectures and to assess its performance under hazardous radio conditions. Our results demonstrate the ability of 5G to handle latency-constrained use cases with superior performance compared to the current state-of-the-art mobile technology.This work was partly funded by the European Commission under the European Union's Horizon 2020 program, grant agreement number 815074 (5G EVE project). The article solely reflects the views of the authors. The Commission is not responsible for the contents of this article or any use made thereof. The authors would like to thank Ignacio Berberana and Neftali Gonzalez from the 5TONIC Laboratory for their support in setting up the Spanish site

The European Industrial Data Space (EIDS)

This research work has been performed in the framework of the Boost 4.0 Big Data lighthouse initiative, a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 780732. This datadriven digital transformation research is also endorsed by the Digital Factory Alliance (DFA)The path that the European Commission foresees to leverage data in the best possible way for the sake of European citizens and the digital single market clearly addresses the need for a European Data Space. This data space must follow the rules, derived from European values. The European Data Strategy rests on four pillars: (1) Governance framework for access and use; (2) Investments in Europe’s data capabilities and infrastructures; (3) Competences and skills of individuals and SMEs; (4) Common European Data Spaces in nine strategic areas such as industrial manufacturing, mobility, health, and energy. The project BOOST 4.0 developed a prototype for the industrial manufacturing sector, called European Industrial Data Space (EIDS), an endeavour of 53 companies. The publication will show the developed architectural pattern as well as the developed components and introduce the required infrastructure that was developed for the EIDS. Additionally, the population of such a data space with Big Data enabled services and platforms is described and will be enriched with the perspective of the pilots that have been build based on EIDS.publishersversionpublishe

Longitudinal association of dietary acid load with kidney function decline in an older adult population with metabolic syndrome

Background: Diets high in acid load may contribute to kidney function impairment. This study aimed to investigate the association between dietary acid load and 1-year changes in glomerular filtration rate (eGFR) and urine albumin/creatinine ratio (UACR). Methods: Older adults with overweight/obesity and metabolic syndrome (mean age 65 ± 5 years, 48% women) from the PREDIMED-Plus study who had available data on eGFR (n = 5,874) or UACR (n = 3,639) at baseline and after 1 year of follow-up were included in this prospective analysis. Dietary acid load was estimated as potential renal acid load (PRAL) and net endogenous acid production (NEAP) at baseline from a food frequency questionnaire. Linear and logistic regression models were fitted to evaluate the associations between baseline tertiles of dietary acid load and kidney function outcomes. One year-changes in eGFR and UACR were set as the primary outcomes. We secondarily assessed ≥ 10% eGFR decline or ≥10% UACR increase. Results: After multiple adjustments, individuals in the highest tertile of PRAL or NEAP showed higher one-year changes in eGFR (PRAL, β: –0.64 ml/min/1.73 m2; 95% CI: –1.21 to –0.08 and NEAP, β: –0.56 ml/min/1.73 m2; 95% CI: –1.13 to 0.01) compared to those in the lowest category. No associations with changes in UACR were found. Participants with higher levels of PRAL and NEAP had significantly higher odds of developing ≥10% eGFR decline (PRAL, OR: 1.28; 95% CI: 1.07–1.54 and NEAP, OR: 1.24; 95% CI: 1.03–1.50) and ≥10 % UACR increase (PRAL, OR: 1.23; 95% CI: 1.04–1.46) compared to individuals with lower dietary acid load. Conclusions: Higher PRAL and NEAP were associated with worse kidney function after 1 year of follow-up as measured by eGFR and UACR markers in an older Spanish population with overweight/obesity and metabolic syndrome

Ultra-processed foods consumption as a promoting factor of greenhouse gas emissions, water, energy, and land use: A longitudinal assessment

Background: Dietary patterns can produce an environmental impact. Changes in people's diet, such as the increased consumption of ultra-processed food (UPF) can not only influence human health but also environment sustainability. Objectives: Assessment of the impact of 2-year changes in UPF consumption on greenhouse gas emissions and water, energy and land use. Design A 2-year longitudinal study after a dietary intervention including 5879 participants from a Southern European population between the ages of 55-75 years with metabolic syndrome. Methods Food intake was assessed using a validated 143-item food frequency questionnaire, which allowed classifying foods according to the NOVA system. In addition, sociodemographic data, Mediterranean diet adherence, and physical activity were obtained from validated questionnaires. Greenhouse gas emissions, water, energy and land use were calculated by means of the Agribalyse® 3.0.1 database of environmental impact indicators for food items. Changes in UPF consumption during a 2-year period were analyzed. Statistical analyses were conducted using computed General Linear Models. Results: Participants with major reductions in their UPF consumption reduced their impact by −0.6 kg of CO2eq and −5.3 MJ of energy. Water use was the only factor that increased as the percentage of UPF was reduced. Conclusions: Low consumption of ultra-processed foods may contribute to environmental sustainability. The processing level of the consumed food should be considered not only for nutritional advice on health but also for environmental protection

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Dietary intake of polychlorinated dibenzo-p-dioxins and furans, adiposity and obesity status

Introduction: The principal source of exposure to Polychlorinated dibenzo-p-dioxins and polychlorinated dibenzo-p-furans (PCDD/Fs) in humans comes from food intake. PCDD/Fs, are a family of potential endocrine disruptors and have been associated with different chronic diseases such as diabetes and hypertension. However, studies assessing the relationship between dietary exposure to PCDD/Fs and adiposity or obesity status in a middle-aged population are limited. Objective: To assess cross-sectionally and longitudinally the associations between estimated dietary intake (DI) of PCDD/Fs and body mass index (BMI), waist circumference, and the prevalence/incidence of obesity and abdominal obesity in a middle-aged population. Methods: In 5899 participants aged 55-75 years (48% women) living with overweight/obesity from the PREDIMED-plus cohort, PCDD/Fs DI was estimated using a 143-item validated food-frequency questionnaire, and the levels of food PCDD/F expressed as Toxic Equivalents (TEQ). Consequently, cross-sectional and prospective associations between baseline PCDD/Fs DI (in pgTEQ/week) and adiposity or obesity status were assessed at baseline and after 1-year follow-up using multivariable cox, logistic or linear regression models. Results: Compared to participants in the first PCDD/F DI tertile, those in the highest tertile presented a higher BMI (β-coefficient [confidence interval]) (0.43kg/m2 [0.22; 0.64]; P-trend <0.001), a higher waist circumference (1.11 cm [0.55; 1.66]; P-trend <0.001), and a higher prevalence of obesity and abdominal obesity (1.05 [1.01; 1.09] and 1.02 [1.00; 1.03]; P-trend = 0.09 and 0.027, respectively). In the prospective analysis, participants in the top PCDD/F DI baseline tertile showed an increase in waist circumference compared with those in the first tertile after 1-year of follow-up (β-coefficient 0.37 cm [0.06; 0.70]; P-trend = 0.015). Conclusion: Higher DI of PCDD/Fs was positively associated with adiposity parameters and obesity status at baseline and with changes in waist circumference after 1-year of follow-up in subjects living with overweight/obesity. Further large prospective studies using a different population with longer follow-up periods are warranted in the future to strengthen our results. Keywords: Abdominal obesity; Adiposity; Endocrine disrupting chemicals; Obesity; Polychlorinated dibenzo-p-furans (PCDD/F)

Izaña Atmospheric Research Center. Activity Report 2015-2016

This report is a summary of the many activities at the Izaña Atmospheric Research Center to the broader community. The combination of operational activities, research and development in state-of-the-art measurement techniques, calibration and validation and international cooperation encompass the vision of WMO to provide world leadership in expertise and international cooperation in weather, climate, hydrology and related environmental issues

Ultra-processed foods consumption as a promoting factor of greenhouse gas emissions, water, energy, and land use: A longitudinal assessment

Background: Dietary patterns can produce an environmental impact. Changes in people's diet, such as the increased consumption of ultra-processed food (UPF) can not only influence human health but also environment sustainability. Objectives: Assessment of the impact of 2-year changes in UPF consumption on greenhouse gas emissions and water, energy and land use. Design: A 2-year longitudinal study after a dietary intervention including 5879 participants from a Southern European population between the ages of 55-75 years with metabolic syndrome. Methods: Food intake was assessed using a validated 143-item food frequency questionnaire, which allowed classifying foods according to the NOVA system. In addition, sociodemographic data, Mediterranean diet adherence, and physical activity were obtained from validated questionnaires. Greenhouse gas emissions, water, energy and land use were calculated by means of the Agribalyse® 3.0.1 database of environmental impact indicators for food items. Changes in UPF consumption during a 2-year period were analyzed. Statistical analyses were conducted using computed General Linear Models. Results: Participants with major reductions in their UPF consumption reduced their impact by -0.6 kg of CO2eq and -5.3 MJ of energy. Water use was the only factor that increased as the percentage of UPF was reduced. Conclusions: Low consumption of ultra-processed foods may contribute to environmental sustainability. The processing level of the consumed food should be considered not only for nutritional advice on health but also for environmental protection