Search

Cement industry production and its materials demand are growing every year, leading to a CO2 and energy footprint increase. The drinking water production is increasing in water treatment plants due to the population growth, raising in turn the waste materials produced. Since these wastes are mainly managed in landfills, this preliminary research work is focused on providing a new sustainable option for valorisation processes, based on the environmental demand of the cement industry. Alkali-activated cements (AACs) can become a proper option to give the water treatment sludge a new life cycle, as they can compete with ordinary Portland cement (OPC) both in properties and sustainability. The main purpose of this study was to evaluate and formulate different AACs based on the use of both raw clay and the water treatment sludge (WTS), as precursors. The raw clay was used without previous thermal dehydroxylation treatment, and the WTS, an aluminosilicate-rich waste, was used partially replacing the raw clay in the AACs formulations. Both precursors and the formulated AACs were characterized by X-ray diffraction (XRD), X-ray fluorescence (XRF) and Fourier-transformed infrared spectroscopy (FT-IR). In addition, the compressive strength, the chemical stability (hydrolytic degradation), and the environmental impact for each AACs formulation were also determined. The results showed that AACs specimens formulated with 20 wt% of WTS (replacing the raw clay) provided the best results, considering both compressive strength and resistance to hydrolytic degradation. Then, it is possible to formulate AACs using raw clay, without prior thermal dehydroxylation treatment, and WTS as precursors. © 2021 Elsevier B.V.

This study aims to understand the absorption patterns of three different kinds of inhaled formulations via in silico modeling using budesonide (BUD) as a model drug. The formulations investigated in this study are: (i) commercially available micronized BUD mixed with lactose (BUD-PT), (ii) BUD nanocrystal suspension (BUD-NC), (iii) BUD nanocrystals embedded hyaluronic acid microparticles (BUD-NEM). The deposition patterns of the three inhaled formulations in the rats’ lungs were determined in vivo and in silico predicted, which were used as inputs in GastroPlus™ software to predict drug absorption following aerosolization of the tested formulations. BUD pharmacokinetics, estimated based on intravenous data in rats, was used to establish a drug-specific in silico absorption model. The BUD-specific in silico model revealed that drug pulmonary solubility and absorption rate constant were the key factors affecting pulmonary absorption of BUD-NC and BUD-NEM, respectively. In the case of BUD-PT, the in silico model revealed significant gastrointestinal absorption of BUD, which could be overlooked by traditional in vivo experimental observation. This study demonstrated that in vitro-in vivo-in silico approach was able to identify the key factors that influence the absorption of different inhaled formulations, which may facilitate the development of orally inhaled formulations with different drug release/absorption rates., Graphical abstract Image, graphical abstract

Five organic fertilizers (DTPA, EDDHA, HEDTA, EDTA and EDDS) were studied as iron sources for photo-Fenton process at natural pH to remove micropollutants (MPs) from wastewater for its reuse in irrigation. The results demonstrated that the stability constant of iron chelates is a key parameter for optimal micropollutants removal and it is linked to the structure of chelator. Mixtures of organic fertilizers were also tested to overcome excessive iron loose and to optimize MPs abatement kinetics. An improvement of photo-Fenton process occurred when using chelating mixtures. For instance, with 50 %EDDS + 50 %EDTA total removal of propranolol (PROP) was achieved at 30 min while EDTA needed up to 90 min of reaction and with EDDS total degradation was not achieved. In addition, the availability of dissolved iron of the mixture at the end of the treatment was 5.5 times higher than EDDS, increasing its suitability as reuse water for irrigation.

Background: The recently published COMPLETE trial has demonstrated that patients with ST-segment elevation myocardial infarction (STEMI) and multivessel coronary artery disease (MVD), who underwent successful percutaneous coronary intervention (PCI) of both culprit and non-culprit (vs. culprit-only) lesions had a reduced risk of major adverse cardiac events (MACE), but not of cardiovascular or total mortality. The aim of this meta-analysis was to assess the efficacy of complete revascularization on cardiovascular or total mortality reduction using available randomized controlled trials (RCTs) including the COMPLETE trial, in hemodynamically stable STEMI patients with MVD. Methods: PubMed, MEDLINE, Embase, Scopus, Google Scholar, CENTRAL and ClinicalTrials.gov databases search identified 10 RCTs of 7033 patients with STEMI and MVD which compared complete (n = 3420) vs. only culprit lesion (n = 3613) PCI for a median 27.7 months follow-up. Random effect risk ratios were used to estimate for efficacy and safety outcomes. Results: Complete revascularization reduced the risk of MACE (10.4% vs.16.6%; RR = 0.59, 95% CI: 0.47 to 0.74, p < 0.0001), CV mortality (2.87% vs. 3.72%; RR = 0.73, 95% CI: 0.56 to 0.95, p = 0.02), reinfarction (5.1% vs. 7.1%; RR = 0.67, 95% CI: 0.52 to 0.86, p = 0.002), urgent revascularization (7.92% vs.17.4%; RR = 0.47, 95% CI: 0.30 to 0.73, p < 0.001), and CV hospitalization (8.68% vs.11.4%; RR = 0.65, 95% CI: 0.44to 0.96, p = 0.03) compared with culprit only revascularization. All-cause mortality, stroke, major bleeding events, or contrast induced nephropathy were not affected by the revascularization strategy. Conclusion: The findings of this meta-analysis suggest that in patients with STEMI and MVD, complete revascularization is superior to culprit-only PCI in reducing the risk of MACE outcomes, including cardiovascular mortality, without increasing the risk of adverse safety outcomes.

Microalgae can be easily integrated into an effective and scalable zero-carbon-emission circular process that exploits their CO2 fixation and wastewater remediation capabilities while simultaneously using their residues as an energy and biofuel source to power global sustainable development. Herein, the use of glycogen-rich Arthrospira platensis microalgae for efficient water decontamination, biofuel production, and CO2 fixation is explored. The circular process is initiated by efficient bioremediation of heavy metals (removal >99%) during microalgal growth, followed by bioethanol production, pellet production, and mineralization of persistent organic pollutants from wastewater, and is accompanied by CO2 fixation and/or oxygen production. Microalgal biomass generated during heavy metal bioremediation is used to produce bioethanol via simultaneous saccharification and fermentation (0.4 L per kg of dried microalgal biomass). The residual biomass obtained after bioethanol production is dried and compressed into pellets for its use as a fuel in biomass boilers (calorific power = 20.6 ± 0.2 MJ kg−1). The iron-rich ashes produced during pellet combustion are subsequently used as heterogeneous re-usable Fenton-like catalysts for the photo-Fenton degradation (mineralization >99%) of persistent organic pollutants. Finally, the low-activity ashes are incorporated into an ash-based medium for the efficient cultivation of microalgae. For each proposed step, product characterization and evaluation were conducted to optimize and enhance the process performance while minimizing negative effects on the environment.

Background Acromegaly is produced by excess growth hormone secreted by a pituitary adenoma of somatotroph cells (ACRO). First-line therapy, surgery and adjuvant therapy with somatostatin analogs, fails in 25% of patients. There is no predictive factor of resistance to therapy. New therapies are investigated using few dispersed tumor cells in acute primary cultures in standard conditions where the cells do not grow, or using rat pituitary cell lines that do not maintain the full somatotroph phenotype. The RET/PIT1/p14ARF/p53 pathway regulates apoptosis in normal pituitary somatotrophs whereas the RET/GDNF pathway regulates survival, controlling PIT1 levels and blocking p14ARF (ARF) and p53 expression. Methods We investigated these two RET pathways in a prospective series of 32 ACRO and 63 non-functioning pituitary adenomas (NFPA), studying quantitative RNA and protein gene expression for molecular-clinical correlations and how the RET pathway might be implicated in therapeutic success. Clinical data was collected during post-surgical follow-up. We also established new'humanized’ pituitary cultures, allowing 20 repeated passages and maintaining the pituitary secretory phenotype, and tested five multikinase inhibitors (TKI: Vandetanib, Lenvatinib, Sunitinib, Cabozantinib and Sorafenib) potentially able to act on the GDNF-induced RET dimerization/survival pathway. Antibody arrays investigated intracellular molecular pathways. Findings In ACRO, there was specific enrichment of all genes in both RET pathways, especially GDNF. ARF and GFRA4 gene expression were found to be opposing predictors of response to first-line therapy. ARF cut-off levels, calculated categorizing by GNAS mutation, were predictive of good response (above) or resistance (below) to therapy months later. Sorafenib, through AMPK, blocked the GDNF/AKT survival action without altering the RET apoptotic pathway. Interpretation Tumor ARF mRNA expression measured at the time of the surgery is a prognosis factor in acromegaly. The RET inhibitor, Sorafenib, is proposed as a potential treatment for resistant ACRO. Fund This project was supported by national grants from Agencia Estatal de Investigacion (AEI) and Instituto Investigacion Carlos III, with participation of European FEDER funds, to IB (PI150056) and CVA (BFU2016-76973-R). It was also supported initially by a grant from the Investigator Initiated Research (IIR) Program (WI177773) and by a non-restricted Research Grant from Pfizer Foundation to IB. Some of the pituitary acromegaly samples were collected in the framework of the Spanish National Registry of Acromegaly (REMAH), partially supported by an unrestricted grant from Novartis to the Spanish Endocrine Association (SEEN). CVA is also supported from a grant of Medical Research Council UK MR/M018539/1.

8 Páginas.-- 4 Figuras.-- 3 Tablas, Sensory quality, assessed following a standardized method, is one of the parameters defining the commercial category of virgin olive oil. Considering the difficulties linked to the organoleptic evaluation, especially the high number of samples to be assessed, setting up instrumental methods to support sensory panels becomes a need for the olive oil sector. Volatile fingerprint by Headspace Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry can be an excellent fit-for-purpose tool as the volatile fraction is responsible for virgin olive oil sensory attributes. A fingerprinting approach was applied to the volatile profile of 176 virgin olive oils previously graded by six official sensory panels. The classification strategy consisted in two sequential Partial Least Square-Discriminant Analysis models built with the aligned chromatograms: the first discriminated extra virgin and non-extra virgin samples; the second classified the latter into virgin or lampante categories. Results were satisfactory in the cross-validation by leave 10%-out (97% of correct classification). For external validation, an uncertainty range was set for the prediction models to detect boundary samples, which would be further assessed by the sensory panels. By doing this, a considerable decrease of the panel workload (around 80%) was achieved, while maintaining a highly reliable classification of samples (error rate, This work was developed in the context of the project OLEUM “Advanced solutions for assuring authenticity and quality of olive oil at global scale”, funded by the European Commission within the Horizon 2020 Program (2014–2020, grant agreement no. 635690). The information and views set out in this article are those of the author(s) and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. B. Quintanilla-Casas thanks the Spanish Ministry of Science, Innovation and Universities predoctoral fellowship FPU16/01744. A. Tres thanks the Spanish Ministry of Economy, Industry and Competitivity “Juan de la Cierva” postdoctoral fellowship (JCI-2012_13412) and the Ministry of Science, Innovation and Universities “Ramón y Cajal” postdoctoral fellowship (RYC-2017-23601).

The extension of ozonation up to ozone (O3) doses beyond immediate ozone demand (IOD) completion combined with continuous addition of hydrogen peroxide (H2O2) was studied as potential strategy of treatment aimed to the effective abatement of ozone-resistant micropollutants (MPs) from wastewater effluents. Through experiments involving the continuous addition of H2O2 in a semi-continuous ozone contactor, it was demonstrated that this new approach could lead to a 36% reduction of the overall O3 needs for a constant H2O2/O3 molar ratio of 0.25 compared with single ozonation, representing a 28% reduction in the energy consumption. This improvement, however, was mainly attributed to H2O2 addition during the secondary ozonation stage, where the direct ozone demand becomes less important. The ¿OH-exposure per consumed ozone (ROHO3) calculation demonstrated that larger H2O2/O3 ratios (0.5-1) lead to a little improvement on oxidation performance during the IOD stage, whereas relationships of 0.25 work markedly better during the secondary stage of the process. Moreover, continuous versus total initial addition of H2O2 were compared and the first one showed better performance, with differences in estimated energy costs up to 21%. Finally, and since monitoring the fate of O3-recalcitrant MPs during the process is essential, two different strategies for the real-time control of the O3-recalcitrant MPs fate during the process were tested, one based on the ROHO3 concept and the other on continuous measurements of ultraviolet absorbance at 254 nm (UVA254). They both showed accurate predictions (R2 > 0.96) for different compounds, effluents and processes.

Erythropoietin is a glycoproteic hormone that regulates hematopoiesis by acting on its specific receptor (EpoR). The expression of EpoR in the central nervous system (CNS) suggests a role for this hormone in the brain. Recently, we developed a new Epo variant without hematopoietic activity called EpoL, which showed marked neuroprotective effects against oxidative stress in brain ischemia related models. In this study, we have evaluated the neuroprotective effects of EpoL against oxidative stress induced by chronic treatment with Aβ. Our results show that EpoL was neuroprotective against Aβ-induced toxicity by a mechanism that implicates EpoR, reduction in reactive oxygen species, and reduction in astrogliosis. Furthermore, EpoL treatment improved calcium handling and SV2 levels. Interestingly, the neuroprotective effect of EpoL against oxidative stress induced by chronic Aβ treatment was achieved at a concentration 10 times lower than that of Epo. In conclusion, EpoL, a new variant of Epo without hematopoietic activity, is of potential interest for the treatment of diseases related to oxidative stress in the CNS such as Alzheimer disease., Grant Innova-Corfo “13IDL2-18688”; Conicyt Grant “Beca Doctorado Nacional no. 21130386”; Fondecyt Grant “1161078”

Background: Respiratory tract infections represent a significant public health risk, and timely and accurate detection of bacterial infections facilitates rapid therapeutic intervention. Furthermore, monitoring the progression of infections after intervention enables ‘course correction’ in cases where initial treatments are ineffective, avoiding unnecessary drug dosing that can contribute to antibiotic resistance. However, current diagnostic and monitoring techniques rely on non-specific or slow readouts, such as radiographic imaging and sputum cultures, which fail to specifically identify bacterial infections and take several days to identify optimal antibiotic treatments. Methods: Here we describe a nanoparticle system that detects P. aeruginosa lung infections by sensing host and bacterial protease activity in vivo, and that delivers a urinary detection readout. One protease sensor is comprised of a peptide substrate for the P. aeruginosa protease LasA. A second sensor designed to detect elastases is responsive to recombinant neutrophil elastase and secreted proteases from bacterial strains. Findings: In mice infected with P. aeruginosa, nanoparticle formulations of these protease sensors—termed activity-based nanosensors (ABNs)—detect infections and monitor bacterial clearance from the lungs over time. Additionally, ABNs differentiate between appropriate and ineffective antibiotic treatments acutely, within hours after the initiation of therapy. Interpretation: These findings demonstrate how activity measurements of disease-associated proteases can provide a noninvasive window into the dynamic process of bacterial infection and resolution, offering an opportunity for detecting, monitoring, and characterizing lung infections. Fund: National Cancer Institute, National Institute of Environmental Health Sciences, National Institutes of Health, National Science Foundation Graduate Research Fellowship Program, and Howard Hughes Medical Institute. Keywords: protease; nanoparticle; diagnostic; bacterial pneumonia, Massachusetts Institute of Technology. David H. Koch School of Chemical Engineering Practice (National Cancer Institute (U.S.) Grant 30-CA14051), National Institute of Environmental Health Sciences (Core Center Grant P30-ES002109), National Institute of Allergy and Infectious Diseases (U.S.) (Grant R01-AI132413)

Hybrid forward osmosis (FO) processes such as forward osmosis with membrane bioreactors (FO-MBR), electrodialysis (FO-ED), nanofiltration (FO-NF) or reverse osmosis (FO-RO) present promising technologies for wastewater reuse in agriculture as they meet high effluent quality requirements, especially regarding boron and/or salt content. An FO-NF demonstration plant for this application was built and operated treating 3 m3 h−1 of real wastewater with a salinity of 3–5 mS cm−1 and 1.5 mg L−1 of boron in continuous mode for 480 days. Three draw solutions (DS) were evaluated in different periods of experimentation. Sodium polyacrylate led to reversible fouling on the FO and NF membranes and the permeate was not suitable for irrigation. Magnesium sulphate, used as DS in a second phase, generated severe irreversible fouling on NF membranes and therefore it was discarded. Finally, magnesium chloride showed the best performance, with FO-NF membranes presenting a stable permeability and low membrane fouling during long-term operation. The FO-NF permeate showed high quality for irrigation, achieving a conductivity value of 1 mS cm−1, a boron concentration below 0.4 mg L−1 and an average SAR of 1.98 (mequ L−1)0.5. DS replacement costs were reduced by working with high rejection NF membranes. However, energy consumption costs associated with the NF step make the global process more energy intensive than conventional technology.

Single-use baby diapers belongs to an important group of products used in the parenting journey because of their high performance and convenience. Single-use baby diapers are normally thrown away after one-time use, resulting in a waste management problem. The goal of this paper was to better understand main environmental concerns of different types of diapers and address how to reduce them, with a special consideration of waste management strategies and user behaviour practices. Furthermore, health and environmental hazards potentially associated with materials included in diapers, or substances formed from diapers during the waste treatment stage, are also analysed (e.g., phthalates, pesticides, dioxins, pesticides). Three main types of baby diapers have been analysed: single-use baby diapers, reusable baby diapers, and biodegradable single-use diapers. Each type of diaper comes with technical characteristics and environmental concerns and challenges, which are discussed in this paper to support the development of measures for the safe(r) and sustainable design, use and end of life management of baby diapers. Justyna Płotka-Wasylka is grateful for the finantial support by the National Science Centre, Poland within the grant project (No.: 2020/37/B/ST4/02886).

This paper combines the Theory of Critical Distances (TCD) and Finite Element Analysis (FEA) to provide estimations of fracture loads in Polyvinyl chloride (PVC) tubular beams containing notch-type defects. The methodology is, however, theoretically applicable to any kind of material and component developing a predominant linear-elastic behavior. FEA is used to determine the stress field at the notch tip, which is then combined with one of the TCD failure criteria (the Point Method, PM) to derive the corresponding critical load. The results prove that this methodology provides reasonable predictions of fracture loads. The authors of this work would like to express their gratitude to the Spanish Ministry of Science and Innovation for the financial support of the project PGC2018-095400-B-I00 “Comportamiento en fractura de materiales compuestos nano-reforzados con defectos tipo entalla”, on the results of which this paper is based.

This paper takes a game theoretical approach to open shop scheduling problems to minimize the sum of completion times. We assume that there is an initial schedule to process the jobs (consisting of a number of operations) on the machines and that each job is owned by a different player. Thus, we can associate a cooperative TU-game to any open shop scheduling problem, assigning to each coalition the maximal cost savings it can obtain through admissible rearrangements of jobs’ operations. A number of different approaches to admissible schedules for a coalition are introduced and, in the main result of the paper, a core allocation rule is provided for games arising from unit (execution times and weights) open shop scheduling problems for the most of these approaches. To sharpen the bounds of the set of open shop scheduling problems that result in games that are balanced, we provide two counterexamples: one for general open shop problems and another for further relaxations of the definition of admissible rearrangements for a coalition.

Scientific literature presents a number of examples in which the mechanical properties of materials are significantly improved by adding small amounts of nano-particles. In many cases, the addition of such nano-particles is performed on polymer-matrix composites, with reported improvements in mechanical, optical, thermal or electrical properties. Therefore, the potential of this technology is huge and a great deal of research work is being performed with the aim of generating new advanced engineering materials. However, this paper presents the other side of the coin. The authors have introduced small amounts of Graphene Oxide (up to 1%) in PA6 with the aim of studying their effect on the fracture properties of the resulting composites. For the particular conditions analyzed here, no improvements in the fracture behavior (in both cracked and notched conditions) have been observed (a similar conclusion may be obtained for the tensile behavior). Other types of material properties were not covered in the analysis. Sharing this kind of (negative) results may save other researchers time and budget, and it is a much more common practice in other fields of science. The authors of this work would like to express their gratitude to the Spanish Ministry of Science and Innovation for the financial support of the project PGC2018-095400-B-I00 “Comportamiento en fractura de materiales compuestos nano-reforzados con defectos tipo entalla”, on the results of which this paper is based.

This paper examines how a nationwide infrastructure investment policy, implemented at the local level, impacted local crime rates. The policy, developed in the wake of the global recession of 2008–09, was designed to boost local economies through job creation. Using monthly figures from the more than 900 municipalities making up the Spanish region of Catalonia, the paper exploits spatial and temporal variations in the Spanish Ministry of Public Administration's random approval of local investment policies, to estimate their impact on both unemployment and crime. The combination of difference-in-differences and IV estimates makes it possible to assess both the size and timing of the policy's impact on the local labor market and on municipal-level crime rates. While the policy did little to palliate the effects of the economic recession in the long run, local public finances did experience a short-term boost, resulting in a temporary reduction in local unemployment rates (as required by the policy), as well as a significant drop in crime rates.

INCEFA-PLUS is a five year project supported by the European Commission HORIZON2020 programme. The project commenced in mid-2015. Sixteen organisations from across Europe have combined forces to deliver new experimental data which will support the development of improved guidelines for assessment of environmental fatigue damage to ensure safe operation of nuclear power plants. Within INCEFA-PLUS, the effects of mean strain and stress, hold time, strain amplitude and surface finish on fatigue endurance of austenitic stainless steels in light water reactor environments are being studied experimentally, these being issues of common interest to all participants. The data obtained is being collected and standardised in an online environmental fatigue database, implemented with the assistance of an INCEFA-PLUS led CEN workshop on this aspect. Towards the end of the project it is planned that INCEFA-PLUS will develop and disseminate methods for including the new data into assessment approaches for environmental fatigue degradation. This paper provides an overall update on project developments since it was last presented at PVP2018 [1]. As well as being a standalone paper, this document will also serve as an introduction to a companion paper being submitted to cover data generated by the project in more detail [2]. In particular, this paper summarises: • The results for Phases 1 & 2 testing. • The plans for Phase 3 testing. • A summary of emerging sensitivities to, and interdependencies between: o Mean strain and stress, surface finish, strain amplitude and hold time. o Environment. o Material. o Laboratory. • The latest thinking on the direction of the project in its final year. • The latest thoughts on how the project results will be used to advance development of improved assessment guidelines. • A summary of dissemination achieved and planned. • Ideas for work after the end of INCEFA-PLUS.

The paper highlights the characteristics of data and big data analytics in manufacturing, more specifically for the industrial asset management. The authors highlight important aspects of the analytical system architecture for purposes of asset management. The authors cover the data and big data technology aspects of the domain of interest. This is followed by application of the big data analytics and technologies, such as machine learning and data mining for asset management. The paper also presents the aspects of visualisation of the results of data analytics. In conclusion, the architecture provides a holistic view of the aspects and requirements of a big data technology application system for purposes of asset management. The issues addressed in the paper, namely equipment health, reliability, effects of unplanned breakdown, etc., are extremely important for today's manufacturing companies. Moreover, the customer's opinion and preferences of the product/services are crucial as it gives an insight into the ways to improve in order to stay competitive in the market. Finally, a successful asset management function plays an important role in the manufacturing industry, which is dependent on the support of proper ICTs for its further success.

We provide an introduction to Multiple Classifier Systems (MCS) including basic nomenclature and describing key elements: classifier dependencies, type of classifier outputs, aggregation procedures, architecture, and types of methods. This introduction complements other existing overviews of MCS, as here we also review the most prevalent theoretical framework for MCS and discuss theoretical developments related to MCS The introduction to MCS is then followed by a review of the application of MCS to the particular field of multimodal biometric person authentication in the last 25 years, as a prototypical area in which MCS has resulted in important achievements. This review includes general descriptions of successful MCS methods and architectures in order to facilitate the export of them to other information fusion problems. Based on the theory and framework introduced here, in the companion paper we then develop in more technical detail recent trends and developments in MCS from multimodal biometrics that incorporate context information in an adaptive way. These new MCS architectures exploit input quality measures and pattern-specific particularities that move apart from general population statistics, resulting in robust multimodal biometric systems. Similarly as in the present paper, methods in the companion paper are introduced in a general way so they can be applied to other information fusion problems as well. Finally, also in the companion paper, we discuss open challenges in biometrics and the role of MCS to advance them, This work was funded by projects CogniMetrics (TEC2015-70627-R) from MINECO/FEDER and RiskTrakc (JUST-2015-JCOO-AG-1). Part of thisthis work was conducted during a research visit of J.F. to Prof. Ludmila Kuncheva at Bangor University (UK) with STSM funding from COST CA16101 (MULTI-FORESEE)

The aim of this paper is to analyse the potential relationship between flash flood events and convective precipitation in Catalonia, as well as any related trends. The paper starts with an overview of flash floods and their trends in the Mediterranean region, along with their associated factors, followed by the definition of, identification of, and trends in convective precipitation. After this introduction the paper focuses on the north-eastern Iberian Peninsula, for which there is a long-term precipitation series (since 1928) of 1-min precipitation from the Fabra Observatory, as well as a shorter (1996–2011) but more extensive precipitation series (43 rain gauges) of 5-min precipitation. Both series have been used to characterise the degree of convective contribution to rainfall, introducing the β parameter as the ratio between convective precipitation versus total precipitation in any period. Information about flood events was obtained from the INUNGAMA database (a flood database created by the GAMA team), with the aim of finding any potential links to convective precipitation. These flood data were gathered using information on damage where flood is treated as a multifactorial risk, and where any trend or anomaly might have been caused by one or more factors affecting hazard, vulnerability or exposure. Trend analysis has shown an increase in flash flood events. The fact that no trends were detected in terms of extreme values of precipitation on a daily scale, nor on the associated ETCCDI (Expert Team on Climate Change Detection and Indices) extreme index, could point to an increase in vulnerability, an increase in exposure, or changes in land use. However, the summer increase in convective precipitation was concentrated in less torrential events, which could partially explain this positive trend in flash flood events. The β parameter has been also used to characterise the type of flood event according to the features of the precipitation. The highest values correspond to short and local events, usually with daily β values above 0.5, while the minimum threshold of daily β for catastrophic flash floods is 0.31.

This paper focuses on the drivers of green technology adoption. We distinguish between end-of-pipe and cleaner production technologies aimed at either pollution mitigation or energy efficiency, respectively. We provide empirical evidence of the relations between existing policy instruments, organizational capabilities of firms and the adoption of different types of green technologies. We use a unique firm level panel dataset of 2562 Spanish manufacturing firms from 2008 to 2014 to carry out the empirical analysis. Our results show, first, that policy instruments drive adoption of green innovation more than organizational capabilities. Second, environmental taxation seems to be ineffective at stimulating the adoption of eco-innovation. Third, both investment subsidies and tax credits do imply higher levels of investments in green technologies. Tax incentives seem to mostly foster cleaner production technologies, while subsidies are used to finance all types of eco-innovations. Fourth, human resources as green employees are positively related with environmental investments. Finally, dynamic capabilities as the introduction of environmental management systems are correlated particularly with cleaner production investments oriented to reduce energy consumption.

Background: Late-life depression (LLD) is characterized by cognitive and social impairments. Determining neurobiological alterations in connectivity in LLD by means of fMRI may lead to a better understanding of the neural basis underlying this disorder and more precise diagnostic markers. The primary objective of this paper is to identify a structural model that best explains the dynamic effective connectivity (EC) of the default mode network (DMN) in LLD patients compared to controls. Methods: Twenty-seven patients and 29 healthy controls underwent resting-state fMRI during a period of eight minutes. In both groups, jackknife correlation matrices were generated with six ROIs of the DMN that constitute the posterior DMN (pDMN). The different correlation matrices were used as input to estimate each structural equation model (SEM) for each subject in both groups incorporating dynamic effects. Results: The results show that the proposed LLD diagnosis algorithm achieves perfect accuracy in classifying LLD patients and controls. This differentiation is based on three aspects: the importance of ROIs 4 and 6, which seem to be the most distinctive among the subnetworks; the shape that the specific connections adopt in their networks, or in other words, the directed connections that are established among the ROIs in the pDMN for each group; and the number of dynamic effects that seem to be greater throughout the six ROIs studied [t = 54.346; df = 54; p < .001; 95 % CI difference = 5.486-5.906]. Limitations: The sample size was moderate, and the participants continued their current medications. Conclusions: The network models that we developed describe a pattern of dynamic activation in the pDMN that may be considered a possible biomarker for LLD, which may allow early diagnosis of this disorder.

In the analysis of the fluid queues, it is necessary to obtain the nonnegative solution of a nonsymmetric algebraic Riccati matrix equation. Under suitable conditions, this solution can be obtained transforming algebraic Riccati equations into unilateral quadratic matrix equations. In this paper, we use an efficient iterative scheme to approximate a solution of this quadratic matrix equation. We improve the efficiency and the accuracy of Newton’s method, widely used in the literature. Moreover, a local convergence result is proved. Finally, we apply this efficient method to approximate the solution of a particular noisy Wiener–Hopf problem and we compare it with Newton’s method. Moreover, a predictor–corrector iterative scheme is constructed that improve the accessibility of the aforesaid method.

In this paper, we study the convergence in the rates of young people Not in Employment, Education or Training (NEET) across the 274 European regions from 2000 to 2019. First, we apply the club convergence methodology and identify the presence of four important clusters with different trends in NEET rates. The estimated clusters consist of sub-national regions in quite distinct parts of Europe. Then, a spatio-temporal econometric model is used to confirm the presence of a reduction in the disparities (β–convergence) of these rates across the European regions. We identify the main drivers in each cluster and calculate the long-run NEET rates. The unemployment rate and the percentage of early leavers from education and training are the main drivers of NEET rates in all clusters. We are grateful for the financial support received from the Spanish Ministry of Economics, Industry and Competitiveness grant PID2020-113452RB-I00 (Silva), from the Generalitat de Catalunya – 2017SGR558 (Silva) and 2017SGR656 (Maynou), and the University Jaume I research project UJI-B2020-16 (Ordóñez).

Recent evidence indicates that alternative policies based on building community can reduce crime, especially in disadvantaged neighborhoods. In this paper we study the effects on local crime rates of bolstering community ties. We take advantage of the quasi-random deployment of a community health policy (Barcelona Salut als Barris, BSaB) that aims to improve health outcomes and reduce inequalities in the most disadvantaged neighborhoods through community-based initiatives. To test whether BSaB reduces crime, we follow a difference-in-differences approach and make use of detailed data from local police and Barcelona City Council administrative records. We find that BSaB significantly reduces a category we term “intimate crimes” in the short term and drug crimes in the long term. The young offender crime rate is also lowered. Evidence suggests that this is due to tighter-knit communities. These results provide evidence in favor of non-traditional crime prevention policies.

Emerging evidence suggests that an effective or functional connectivity network does not use a static process over time but incorporates dynamic connectivity that shows changes in neuronal activity patterns. Using structural equation models (SEMs), we estimated a dynamic component of the effective network through the effects (recursive and nonrecursive) between regions of interest (ROIs), taking into account the lag 1 effect. The aim of the paper was to find the best structural equation model (SEM) to represent dynamic effective connectivity in people with Down syndrome (DS) in comparison with healthy controls. Twenty-two people with DS were registered in a functional magnetic resonance imaging (fMRI) resting-state paradigm for a period of six minutes. In addition, 22 controls, matched by age and sex, were analyzed with the same statistical approach. In both groups, we found the best global model, which included 6 ROIs within the default mode network (DMN). Connectivity patterns appeared to be different in both groups, and networks in people with DS showed more complexity and had more significant effects than networks in control participants. However, both groups had synchronous and dynamic effects associated with ROIs 3 and 4 related to the upper parietal areas in both brain hemispheres as axes of association and functional integration. It is evident that the correct classification of these groups, especially in cognitive competence, is a good initial step to propose a biomarker in network complexity studies.

In this paper, we consider a supply chain that faces a potential brand crisis, with one manufacturer deciding quality improvement and global advertising levels, and one retailer determining local advertising effort. The goodwill model proposed by Nerlove and Arrow (1962) is adopted here under the assumption that when the crisis happens, the companies suffer a sharp decrease in the goodwill. We characterize the feedback Nash equilibrium, and then we compare the corresponding quality and advertising strategies and outcomes with those of the case where the potential crises are absent, and where the companies do not invest in quality. The effects of the instantaneous crisis rate and the short-term and long-term damages are also evaluated. Our results reveal that the pre-crisis quality improvement accelerates the goodwill build-up before the crisis, and also helps the recovery in post-crisis regime. Its twofold function suggests that one of the pre- and post-crisis regimes/instants ought to be matched with more intense investment in both quality and global advertising, depending on the overall effect of instantaneous crisis rate, short-term damage and long-term damage. This carryover effect also brings a non-monotonicity of quality improvement effort and value functions with respect to the instantaneous crisis rate. These properties leave the chance to mitigate the loss by anticipating crisis for both members under certain circumstances.

Carbon nanotubes (CNTs) have been widely studied in the literature for their potential benefits as reinforcement in epoxy matrices. However, the enhancement that these nano-materials can provide to the corresponding epoxy matrix is largely dependent on the manufacturing process and other factors such as the wt.% or the nanotube type, showing different effects on the resulting mechanical properties. In this study, five contents of multi-wall carbon nanotubes (MWCNTs) were introduced in an epoxy resin to analyse their effects on both tensile and fracture properties, with the fracture behaviour being characterised in cracked and in notched conditions (with various radii). The experimental results showed a drastic deterioration of the tensile strength for MWCNTs contents higher than 0.1 wt.%, and no benefit was found in the fracture resistance (only conducted for 0.1 wt.% due to the negative effect observed in the tensile results). Therefore, it seems that the CNTs do not always improve the fracture behaviour of the epoxy matrix. The authors of this work would like to express their gratitude to the Spanish Ministry of Science and Innovation for the financial support of the project PGC2018-095400-B-I00 “Comportamiento en fractura de materiales compuestos nano-reforzados con defectos tipo entalla”, on the results of which this paper is based.

A new version of the code system pengeom , which provides a complete set of tools to handle different geometries in Monte Carlo simulations of radiation transport, is presented. The distribution package consists of a set of Fortran subroutines and a Java graphical user interface that allows building and debugging the geometry-definition file, and producing images of the geometry in two- and three-dimensions. A detailed description of these tools is given in the original paper [ Comput. Phys. Commun. 199 (2016) 102–113] and in the code manual included in the distribution package. The present new version corrects a bug in the Fortran subroutines, and it includes various improvements of the Java graphical user interface. New Version Program Summary Program Title: pengeom CPC Library link to program files: https://doi.org/10.17632/zgswr8kyf5.1 Licensing provisions: CC BY NC 3.0 Programming language: Fortran 90, Java Journal reference of previous version: Comput. Phys. Commun. 199 (2016) 102–113 Does the new version supersede the previous version?: Yes Reasons for the new version: The original Fortran code contained a subtle bug, which had an effect only when (1) a particle moving within a void region entered a material body, and (2) the particle was left in the void volume because of numerical roundoff errors (undershot). In such case, the steering main program erroneously concluded that the particle was in the external vacuum and, consequently, it discontinued the simulation of the particle trajectory. This anomalous behavior has been corrected by shifting the position of the particle a small distance, determined by the parameters of the master ray equation, which places the particle a small distance inside the material body. In the original Fortran subroutines, inconsistencies in the geometry-definition file resulted in a stop of the program; this reaction was hard to control from a graphical user interface. The present new version has been verified to work correctly under Java 8, Java 11, and Java 13. Summary of revisions: In the new version the tracking bug is corrected. In addition, any apparent syntax error is now resolved by returning the control to the calling program with an error flag activated and with an error message. Various aspects of the Java user interface have been improved: the text editor now includes line numbers, which are used to locate possible inconsistencies and errors in the geometry definition file; the size of the application window can now be modified, and the possible sizes of the graphics windows are adapted to the actual resolution of the monitor; the action of keystroke commands under Windows, Linux, and macOS is now the same. Nature of problem: The Fortran subroutines perform all geometry operations in Monte Carlo simulations of radiation transport with arbitrary interaction models. They track particles through complex quadric geometries, i.e., through material systems consisting of homogeneous bodies limited by quadric surfaces. Particles are moved in steps (free flights) of a given length, which is dictated by the simulation program, and are halted when they cross an interface between media of different compositions or when they enter selected bodies. At the end of each step, pengeom returns the indices of the material and body where the particle is. Solution method: pengeom is tailored to optimize simulation speed and accuracy. Fast tracking is accomplished by the use of quadric surfaces, which facilitate the calculation of ray intersections , and of modules (connected volumes limited by quadric surfaces) organized in a hierarchical structure. Optimal accuracy is obtained by considering fuzzy surfaces, with the aid of a simple algorithm that keeps control of multiple intersections of a ray and a surface. The 64-bit Java GUI PenGeomJar provides a complete geometry toolbox; it allows building and debugging of the geometry definition file, as well as visualizing the resulting geometry in two and three dimensions. Additional comments including restrictions and unusual features: All geometrical operations are performed internally. The connection between the steering main program and the tracking routines is through a Fortran module, which contains the state variables of the transported particle, and the input-output arguments of subroutine STEP . Rendering of two- and three-dimensional images is performed by using the pengeoem subroutines, so that what we see in the images is what is passed to the simulation program. By default pengeom can handle systems with up to 5,000 bodies and 10,000 surfaces. These numbers can be increased by editing the source file. [1] J. Almansa, F. Salvat-Pujol, G. Diaz-Londono, A. Carnicer, A.M. Lallena, and Francesc Salvat, Comput. Phys. Commun. 199 (2016) 102–113.

In this paper we estimate the impact of a nationwide public preschool expansion that took place in Spain over the 1990s on criminal behavior later in time. We exploit variation in enrollment rates across Spanish regions and birth-cohorts, and we link education data to a unique administrative crime dataset recording offenses committed in the region of Catalonia over the period 2009-2014. We find that for the average birth cohort, Catalan municipality and year, a 1 percentage point increase in preschool exposure at age 3 yields 1.6% fewer crime actions during youth and young adulthood. We are able to account for region of origin, birth cohort, time and local fixed effects, as well as several region and time-specific controls. Leveraging detailed information on types of crime committed, we propose a categorization of offenses into those likely to have been rationally planned and driven by economic motives, and those in which emotional factors and lack of self-control play a significant role. On average, we find the benefits of preschool to be larger and more robust on crimes belonging to the latter category, suggesting that non-cognitive skills play an important role in explaining the overall effect.

Many software-implemented control flow error detection techniques have been proposed over the years. In an effort to reduce their overhead, recent research has focused on selective approaches. However, correctly applying these approaches can be difficult because their respective literature gives little guidance on the practical implementation. This paper aims to address this concern and proposes a new approach. Our new approach is easier to implement and is applicable on any existing control flow error detection technique. To prove its validity, we apply our new approach to five different control flow error detection techniques and perform fault injection experiments. The results show that the selective implementation, while decreasing the imposed overhead, can have a negative impact on error detection ratio. ispartof: Internet of Things vol:12 status: published

This paper quantifies the combined effect on-the-job training and workers' on-the-job learning decisions have on aggregate employment. Initially, we present an index of on-the-job human capital acquisition (OJHCA) based on data from the OECD program for international assessment of adult competencies. The data shows a positive relationship between the on-the-job training and on-the-job learning indexes and a strong positive correlation between the human capital index and employment rates across OECD economies. Next, we build a search and matching model that hinges on the training provided by firms as well as workers' learning. The model also includes education along with taxes that increase and decrease human capital investments. We calibrate the model to the United Kingdom and analyze the role of taxes and education to explain the variation in human capital acquired on-the-job, employment and productivity across countries. We also obtain the marginal costs in every country that reproduce the levels of on-the-job human capital as observed in the data. The model is almost able to reproduce the observed differences in employment rates between the groups of countries in the highest and lowest tertiles of the OJHCA distribution, and OJHCA accounts for forty percent of the simulated employment differences. Finally, we analyze subsidies to training costs and conclude that a 10% reduction in marginal training cost increases long-term employment by almost 0.5 percentage points We are grateful for the financial support of the Instituto de Estudios Fiscales (Silva and Vázquez-Grenno), the Ministerio de Ciencia e Innovación -PID2019-109813RB-I00 and PID2019-108265RB-I00 (Vázquez-Grenno) and ECO2017-82350-R (Naval and Silva), the Generalitat de Catalunya - 2017SGR796 (Vázquez-Grenno) and -2017SGR558 (Naval and Silva)

Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases.

The Averaged Strain Energy Density (ASED) criterion has been widely used for the prediction of fracture conditions in a number of materials containing notch type defects, similarly to other well-known methodologies such as the Theory of Critical Distances (TCD). This criterion is linear-elastic, so the results obtained in linear-elastic materials have been accurate. However, as soon as the material behavior becomes nonlinear, the resulting accuracy decreases. With the aim of using linear-elastic simple methods (such as the ASED criterion) in nonlinear materials, several attempts have been made to convert a physically nonlinear behavior into an equivalent linear behavior. Thus, when the tensile behavior in plain specimens reveals nonlinearity, but the fracture behavior in the presence of defects is linear, the Equivalent Material Concept (EMC) has been successfully validated (EMC-ASED criterion). However, there are situations in which the nonlinear behavior takes place in both tensile and fracture behaviors, and the EMC-ASED criterion loses accuracy and requires further evolution. At this point, the Fictitious Material Concept allows the analysis of nonlinear materials (at both tensile and fracture conditions) to be performed with significant accuracy. In this context, this article provides the prediction of fracture loads in single edge notched bending (SENB) specimens made of short glass fiber reinforced polyamide 6 (SGFR-PA6, 10 wt.%) containing U-notches and different levels of moisture content. The predictions are obtained through the combination of the FMC and the ASED criterion (FMC-ASED combined criterion). The results are significantly more accurate than those obtained through the ASED and the EMC-ASED criteria, but less accurate than those used when combining the FMC with the TCD. The authors of this work wish to extend their gratitude to the Spanish Ministry of Science and Innovation for the financial support of the Project MAT2014-58443-P: “Análisis del comportamiento en fractura de componentes estructurales con defectos en condiciones debajo confinamiento tensional”, on the results of which this paper is based.

In 3-axis milling operations the surface error caused by the tool/workpiece static deflection assumes a certain shape along the axial depth of cut. The error shape changes considerably according to the cutting strategy, tool geometry and cutting parameters. This paper presents a comprehensive method to identify all the types of surface error profile in down-milling, proposing dedicated analytical equations. This approach has been experimentally validated to assess its accuracy and limits. The results of this approach are meant to ease the surface error prediction and measurement by reducing the number of points to consider along the axial depth of cut.

This paper aims to contribute to the knowledge on how the Smart Tourism Destination (STD) might enhance the Tourist Shopping Journey (TSJ) through offering information sources that meet visitors' needs and preferences. The CAN (Cognitive-Affective-Normative) model was employed to explore the antecedents of using information sources for purchases made in destinations. The importance of the cognitive variables performance and effort expectancy in the purchasing process are highlighted: tourists are pragmatic when consulting information sources in destinations. This study contributes to the knowledge of the role of information sources in TSJ behaviour, and can help managers in the development of STD strategies and services. It also opens new research lines by considering the TSJ as a hitherto unexamined holistic process., Highlights • Being able to provide suitable information in the proper manner is crucial for a Smart Tourism Destination (STD). • STDs must develop the most adequate information strategy and influence positively in the Tourist Shopping Journey. • The search of information is the first stage in the Tourit Shopping Journey. • All dimensions of the CAN model influence on intention to use information sources when tourist shopping. • Tourists aim to make best use of their time behaving in a pragmatic way when shopping.

This paper quantifies the impact of public employment on local labor markets in the long-run. We adopt two quantitative approaches and apply them to the case of Spanish cities. In the first, we develop a 3-sector (public, tradable and non-tradable) search and matching model embedded within a spatial equilibrium model. We characterize the steady state of the model, which we calibrate to match the labor market characteristics of the average Spanish city. The model is then used to simulate the local labor market effects of expanding public sector employment. In the second empirical approach, we use regression analysis to estimate the effects of public sector job expansions on decadal changes (1980-1990 and 1990-2001) in the employment and population of Spanish cities. This analysis exploits the dramatic expansion of public employment that followed the advent of democracy in the period 1980 to 2001. The instrumental variables’ approach that we adopt uses the capital status of cities to instrument for changes in public sector employment. The two empirical approaches yield qualitatively similar results and, thus, cross-check each other. One additional public sector job creates about 1.3 jobs in the private sector. However, these new jobs do not translate into a substantial reduction in the local unemployment rate as better labor market conditions attract new workers to the city. Increasing public employment by 50% only reduces unemployment from 0.156 to 0.150.

Cuenta con otro ed. : IFAC-PapersOnLine Incluida en el vol. 53 Article number: 145388 In this paper, the power quality of interconnected microgrids is managed using a Model Predictive Control (MPC) methodology which manipulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the microgrids working modes: grid-connected, islanded and interconnected. The results and simulations are also applied to the transition between the different working modes. In order to show the potential of the control algorithm a comparison study is carried out with classical Proportional-Integral Pulse Width Modulation (PI-PWM) based controllers. The proposed control algorithm not only improves the transient response in comparison with classical methods but also shows an optimal behavior in all the working modes, minimizing the harmonics content in current and voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems. Ministerio de Economía y Competitividad (España) DPI2016-78338-R Interreg SUDOE SOE3 / P3 / E0901

Network Function Virtualization enables network slicing as a novel paradigmfor service provisioning. With network slicing, Virtual Network Functions(VNFs) can be instantiated at different locations of the infrastructure, choosing their optimal placement based on parameters such as the requirementsof the service or the resources available. One limitation of state-of-the-arttechnology for network slicing is the inability to re-evaluate orchestration decisions once the slice has been deployed, in case of changing service demandsor network conditions.In this paper, we present ACHO, a novel software framework that enablesseamless re-orchestration of VNFs of any kind, including RAN and Core.With ACHO, VNFs and resources can be easily re-assigned to match, e.g.,varying user demands or changes in the nodes' load. ACHO uses lightweightmechanisms, such as splitting the engine of a VNF from the data it requiresto perform its operation, in such a way that, when re-allocating a VNF, onlythe data is moved (a new engine is instantiated in the new location). Wedemonstrate the use of ACHO in a small scale testbed, showing that (i) theproposed re-orchestration is feasible, (ii) it results much faster than existingalternatives (especially for relocation), and (iii) the framework can be readilyapplied to existing VNFs after minimal changes to their implementation. This work was partially supported by the European Commission in the framework of the H2020 5G-PPP 5G-TOURS (Grant no. 856950) project and the 5G-EVE (Grant no. 815074) project.

The main limitation of Concentrated Solar Power (CSP) is its maximum operating temperature, since the main fluid used as heat transfer fluid (HTF) and thermal storage media (TES) is molten salts, which degrade around 565 °C. Therefore, there is great interest in developing HTFs that allow the maximum working temperature to be increased to more than 565 °C. This increase in the maximum operating temperature of the HTFs will, in turn, allow CSP plant efficiency to be enhanced. Different studies have proposed using particles as a medium to capture and store solar energy, but very little is known about the effect on the particles after resisting several cycles of cooling and heating and what happens to the particles’ physical properties when they are fluidized. It is true that a variety of solid particles permit high performance to be achieved at high temperatures and with low material costs, but not all particles are valid for this purpose. This work focuses on different materials considered promising candidates for use as alternative HTF and storage materials in CSP plants, which were characterized and tested: sand, carbo Accucast ID50 and silicon carbide. The properties of the particles before and after being fluidized (assessing their resistance to abrasion) and before and after high temperature (900 °C) thermal treatments (aging treatment) are the main finding of this paper. This work highlights the considerable advantages of SiC and carbo over sand. This study also determines that the combination of high temperature and several hours of fluidization does not affect the diameter of the particles: However, the fluidized samples vary considerably in diameter. In this way, SEM and DSC techniques highlight the problem of the fine appearance associated with sand during fluidization.

The complex interaction between physiological stresses and corrosive human fluids can lead to the premature failure of metallic biomaterials due to the development of Environmental Assisted Cracking (EAC) processes. In this paper, the EAC phenomenon is analysed through a Theory of Critical Distances based methodology, which has been validated in other materials and aggressive environments, and the apparent crack propagation threshold in notched conditions is estimated. Notch-like defects, which are frequently found in aggressive environments, may present higher values of crack propagation thresholds than those exhibited in cracked components. The knowledge of this higher material performance makes it possible to address the problem avoiding oversizing or unnecessary replacements in biomaterials, which leads to an improvement in the quality of life of the people carrying these materials. In this study, the susceptibility of AZ31 magnesium alloy to EAC and the evolution of the apparent crack propagation threshold have been analysed. The aggressive environment used was Simulated Body Fluid (SBF). The main conclusion is that the Theory of Critical Distances predicts the behaviour of this biomaterial in notched conditions and subjected to the aggressive environment being studied. This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.

The problem of vehicle autonomous driving currently represents a topic of great interest from both theoretical and practical points of view. Among the challenging tasks to be addressed within any autonomous driving framework, one of the most important ones is localization from data collected in real time. Within such framework, this paper is specifically focused on the localization problem for rail vehicles, such as railway and tramway vehicles. Our specific interest is on investigating solutions to the localization problem which are (as much as possible) independent on ground sensor infrastructure and are therefore suitable to be employed on any rail vehicle, irrespective of the ground equipment of the specific tracks. To this end, we refer to a multi-sensor framework and, specifically, to a sensor fusion scheme which collects data from different sensors installed on the vehicle (namely, an Inertial Measurement Unit and a Global Positioning System) and carries out a Kalman-based filtering recursion which relies on a simplified vehicle model. With the aim of identifying a solution for the localization problem providing desirable performance, we carry out a comparative simulation analysis concerning different Kalman-based data fusion strategies (in particular, the Extended Kalman Filter and the Unscented Kalman Filter are considered).

Cuenta con otro ed.: IFAC-PapersOnLine Incluída en el vol. 53, Issue 2 Article number 145388 This paper presents a predictive controller whose model is based on input-output data of the nonlinear system to be controlled. It uses a Lipschitz interpolation technique in which new data may be included in the database in real time, so the controller improves the system model online. An exploration and exploitation policy is proposed, allowing the controller to robustly and cautiously steer the system to the best reachable reference, even if the model lacks data in such region. The conditions needed to ensure recursive feasibility in the presence of output and input constraints and in spite of the uncertainties are given. The results are illustrated in a simulated case study. Feder (UE) DPI2016-76493-C3-1-R

This paper develops a unified framework to analyze a continuum of hybrid cooperation agreements along two dimensions: their degree of revenue sharing (scope of alliances) and their degree of cost sharing (scope of joint ventures). The analysis focuses on the air transportation industry, distinguishing between interline and interhub markets. As economies of traffic density become stronger, we find that the socially optimal cooperation agreement moves from full alliance to joint venture in interline markets, whereas it moves from joint ventureto merger in interhub markets. These results are driven by the tradeoff between a procompetitive effect of alliances in interline markets and an anticompetitive effect in interhub markets, along with the efficiency gains associated with joint ventures in interhub markets. We also develop an empirical application for intercontinental routes for the period 2010–2016 that identifies a positive impact of deeper degrees of airline cooperation (revenue and cost sharing) on traffic, both in interline and interhub markets. Therefore, the potential anticompetitive effect of deeper alliances in interhub markets is not observed in our sample.

The aim of this paper is to test two methodologies, applicable to different spatial scales (from regional to local), to predict the capacity of agroecosystems to provide habitats for the species richness of butterflies and birds, based on the ways their socio-metabolic flows change the ecological functionality of bio-cultural landscapes. First, we use the more general Intermediate Disturbance-Complexity (IDC) model to assess how different levels of human appropriation of photosynthetic production affect the landscape functional structure that hosts biodiversity. Second, we apply a more detailed Energy-Landscape Integrated Analysis (ELIA) model that focusses on the energy storage carried out by the internal biomass loops, and the energy information held in the network of energy flows driven by farmers, in order to correlate both (the energy reinvested and redistributed) with the energy imprinted in the landscape patterns and processes that sustain biodiversity. The results obtained after applying both models in the province and the metropolitan region of Barcelona support the Margalef's energy-information-structure hypothesis by showing positive relations between butterflies' species richness, IDC and ELIA, and between birds' species richness and energy information. Our findings support the view that strong relationships between farming energy flows, agroecosystem functioning and biodiversity can be detected, and highlight the importance of farmers' knowledge and labour to maintain bio-cultural landscapes.

Valves are mechanical devices for controlling fluid-flow in pipes of different diameter and service pressures used in several industry sectors. Most demanding industry sectors add custom design requirements and require product validation reports many times even before placing valve purchase orders of varying quantities. Therefore, customer and valve developer requirements must be made compatible, design reliably completed and a design validation report created, all as soon as possible. In order to respond to these market constraints, complete valve design process from product planning to product design and validation delivery must be optimized. This paper reports a 96% time reduction in Simulation Based Design validation and reporting tasks obtained by applying Design Automation in a company that develops valves for this market. Additionally, the architecture and most remarkable features of the Simulation Based Design validation and reporting automation are described.

E-waste is a priority waste stream as identified by the European Commission due to fast technological changes and eagerness of consumers to acquire new products. The value chain of the Waste on Electric and Electronic Equipment (WEEE) has to face several challenges: the EU directives requesting collection targets for 2019–2022, the costs of disassembly processes which is highly dependent on the applied technology and type of discarded device, and the sale of the obtained components and/or raw materials, with market prices varying according to uncontrolled variables at world level. This paper presents a human-robot collaboration for a recycling process where tasks are opportunistically assigned to either a human-being or a robot depending on the condition of the discarded electronic device. This solution presents some important advantages; i.e. tedious and dangerous tasks are assigned to robots whereas more value-added tasks are allocated to humans, thus preserving jobs and increasing job satisfaction. Furthermore, first results from a prototype show greater productivity and profitable projected investment.

The Energy Mix Concentration Index (EMCI) is a quantitative indicator of concentration of the energy mix based upon the Herfindahl-Hirschman Index. We use the EMCI to compare the evolution of the diversification (versus concentration) of energy mixes in the long-term in order to reveal the transformations of the energy structures which determine energy transitions. In this methodological paper we make explicit how to aggregate the energy sources in order to calculate the EMCI, including questions of detail such us the level of aggregation and the transformation of primary electricity to add it up to total consumption. We present alternative figures that illustrate some additional aspects of the relation of the EMCI to total consumption, consumption per capita and energy annual growth. We also show the sensitivity of the indicator to alternative specifications (with and without pre-modern energy sources) and alternative data sets, proving its robustness. • Indicate how to aggregate energy carriers in the calculation of a quantitative index of concentration of the energy mix. • Compare alternative specifications (with or without pre-modern energy carriers). • EMCI focus on the major energy sources in the energy systems. Method name: Herfindahl-Hirschman Index, Keywords: Energy mix, Energy consumption, Energy concentration, Energy diversification, Energy security, Energy transition, Decarbonization, Herfindahl-Hirschman Index, Energy history

There is an ever-increasing complexity of the systems we engineer in modern society, which includes facing the convergence of the embedded world and the open world. This complexity creates increasing difficulty with providing assurance for factors including safety, security and performance. In such a context, the AQUAS project investigates the challenges arising from e.g., the inter-dependence of safety, security and performance of systems and aims at efficient solutions for the entire product life-cycle. The project builds on knowledge of partners gained in current or former EU projects and will demonstrate the newly developed methods and techniques for co-engineering across use cases spanning Aerospace, Medicine, Transport and Industrial Control. A special thanks to all the AQUAS consortium people that have worked on the AQUAS proposal on which this paper is based, especially to Charles Robinson (TRT), the proposal coordinator. The AQUAS project is funded from the ECSEL Joint Undertaking under grant agreement n 737475, and from National funding.

Shape is a property studied for many kinds of particles. Among shape parameters, sphericity and roundness indices had been largely studied to understand several processes. Some of these indices are based on length measurements of the particle obtained from its oriented bounding box (OBB). In this paper we follow a discrete approach based on Extreme Vertices Model and devise new methods to compute the OBB and the mentioned indices. We apply these methods to synthetic sedimentary rocks and to a real dataset of silicon nanocrystals (Si NC) to analyze the obtained results and compare them with those obtained with a classical voxel model.