Source Apportionment of Nitrate Pollution in Surface Water Using Stable Isotopes of N and O in Nitrate and B: A Case Study in Flanders (Belgium)

Excess application to fields of animal manure or mineral fertilizers is generally assumed to be the major source of nitrate pollution in surface and groundwater in agricultural areas in Flanders (Belgium). The Flemish Environment Agency (VMM) suspects, but could not prove, that discharges of untreated domestic sewage or discharges containing mineral fertilizers from hydroculture in greenhouses are also contributing to the nitrate pollution observed in some of the agricultural areas. The objective of this study was to investigate, using stable isotope data of dissolved nitrate and boron, if these suspected sources significantly contribute to the nitrate pollution observed in selected surface water monitoring points in Flanders.JRC.D.4-Isotope measurement

Optimization of culture conditions for exopolysaccharides production in Rhizobium sp. using the response surface method

The combined effects of the processing parameters for exopolysaccharides production by Rhizobium sp. was studied using the experimental design and response surface methodology. The experiments were carried out using a fermenter with 20 L capacity, as the reactor. All processing parameters were online monitored. The temperature [(30 \ub1 1)\ub0C] and pH value (7.0 \ub1 0.1) were kept constant throughout the experimental time. As statistical tools, a complete 23 factorial planning with central point and response surface were used to study the interactions among three relevant variables of the fermentation process: calcium carbonate concentration, aeration and agitation. The processing parameters setup for reaching a maximum response for exopolysaccharides production was obtained when applying the highest values for calcium carbonate concentration (1.1 g/L), aeration (1.3 vvm) and agitation (800 rpm). In addition, the combination of these optimum processing parameters yielded YP/S (g/g) = 0.35

Impaired Bile Acid Metabolism and Gut Dysbiosis in Mice Lacking Lysosomal Acid Lipase

Lysosomal acid lipase (LAL) is the sole enzyme known to be responsible for the hydrolysis of cholesteryl esters and triglycerides at an acidic pH in lysosomes, resulting in the release of unesterified cholesterol and free fatty acids. However, the role of LAL in diet-induced adaptations is largely unexplored. In this study, we demonstrate that feeding a Western-type diet to Lal-deficient (LAL-KO) mice triggers metabolic reprogramming that modulates gut-liver cholesterol homeostasis. Induction of ileal fibroblast growth factor 15 (three-fold), absence of hepatic cholesterol 7α-hydroxylase expression, and activation of the ERK phosphorylation cascade results in altered bile acid composition, substantial changes in the gut microbiome, reduced nutrient absorption by 40%, and two-fold increased fecal lipid excretion in LAL-KO mice. These metabolic adaptations lead to impaired bile acid synthesis, lipoprotein uptake, and cholesterol absorption and ultimately to the resistance of LAL-KO mice to diet-induced obesity. Our results indicate that LAL-derived lipolytic products might be important metabolic effectors in the maintenance of whole-body lipid homeostasis

Unconstrained and Contactless Hand Geometry Biometrics

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM) and k-Nearest Neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices

Co-creation Initiatives in Healthcare in Small Communities

The uses of technology in public spaces are not new, but now we find new forms of social interactions and practices, socio-spatial representations and relationships. The close relationship between real and virtual worlds also opens up new ways of advancing knowledge. In order to facilitate the implementation of Open Science, we explore different co-creation methods with multiple stakeholders. All groups are involved and have influence throughout the project lifecycle: from the beginning, to planning, to implementation, to dissemination. Research activities should involve a wide variety of stakeholders interested, including government, educators, nurses, charities, civil societies, patient groups and the publics, based in a way to (1) obtaining contributions by customers, (2) selecting the best of these contributions, and (3) incorporating these selected contributions into products, processes, or services. Interactions between Information and Communication Technologies (ICT), public spaces, and healthcare are considered as s a tool for connecting people in small communities (enhancing participation). A Platform (DXP - Digital eXperience Platform) through “headless” technologies may provide content management capabilities and easy integration with devices and various sources, driven by user needs and developed with the concept of “Community in mind” in order to create strong and active communities and transform our small communities into more human environments, rather than just more high-tech places, and to understand that “smartness” should be people-friendly. It was applies the Responsible Research and Innovation (RRI) principles on the scientific process and governance, identify drivers and barriers, interests and values for current and future societal challenges.This research was financially supported by the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 741527 (project ORION).S

Does comprehensive education reduce health inequalities?

This article analyses the impact of comprehensive education on health inequalities. Given that education is an important social determinant of health, it is hypothesised that a more equitable comprehensive system could reduce health inequalities in adulthood. To test this hypothesis, we exploited the change from a largely selective to a largely comprehensive system that occurred in the UK from the mid-1960s onwards and compare inequalities in health outcomes of two birth cohorts (1958 and 1970) who attended either system. We studied physical and mental health, health behaviours and life satisfaction in middle age as outcomes and absolute and relative inequalities by social class (of origin and destination) and education. Inverse probability weighting was used to control confounding by socio-economic and education background, and ability test score taken prior to secondary school entry. We did not find consistent evidence that health inequalities were smaller under the comprehensive compared to the selective system and the results were robust under different model specifications. Our study adds to the sparse but growing literature that assesses the impact of social policy on health inequalities

A new framework for sign language alphabet hand posture recognition using geometrical features through artificial neural network (part 1)

Hand pose tracking is essential in sign languages. An automatic recognition of performed hand signs facilitates a number of applications, especially for people with speech impairment to communication with normal people. This framework which is called ASLNN proposes a new hand posture recognition technique for the American sign language alphabet based on the neural network which works on the geometrical feature extraction of hands. A user’s hand is captured by a three-dimensional depth-based sensor camera; consequently, the hand is segmented according to the depth analysis features. The proposed system is called depth-based geometrical sign language recognition as named DGSLR. The DGSLR adopted in easier hand segmentation approach, which is further used in segmentation applications. The proposed geometrical feature extraction framework improves the accuracy of recognition due to unchangeable features against hand orientation compared to discrete cosine transform and moment invariant. The findings of the iterations demonstrate the combination of the extracted features resulted to improved accuracy rates. Then, an artificial neural network is used to drive desired outcomes. ASLNN is proficient to hand posture recognition and provides accuracy up to 96.78% which will be discussed on the additional paper of this authors in this journal

African Linguistics in Central and Eastern Europe, and in the Nordic Countries

Non peer reviewe

The upgrade of the ALICE TPC with GEMs and continuous readout

The upgrade of the ALICE TPC will allow the experiment to cope with the high interaction rates foreseen for the forthcoming Run 3 and Run 4 at the CERN LHC. In this article, we describe the design of new readout chambers and front-end electronics, which are driven by the goals of the experiment. Gas Electron Multiplier (GEM) detectors arranged in stacks containing four GEMs each, and continuous readout electronics based on the SAMPA chip, an ALICE development, are replacing the previous elements. The construction of these new elements, together with their associated quality control procedures, is explained in detail. Finally, the readout chamber and front-end electronics cards replacement, together with the commissioning of the detector prior to installation in the experimental cavern, are presented. After a nine-year period of R&D, construction, and assembly, the upgrade of the TPC was completed in 2020.publishedVersio