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Search: WFRF:(Sanz Miguel)

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2.
  • Kehoe, Laura, et al. (author)
  • Make EU trade with Brazil sustainable
  • 2019
  • In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
  • Journal article (other academic/artistic)
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4.
  • Glasbey, JC, et al. (author)
  • 2021
  • swepub:Mat__t
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5.
  • Mireles, Miguel, et al. (author)
  • Non-invasive and quantitative in vivo monitoring of gold nanoparticle concentration and tissue hemodynamics by hybrid optical spectroscopies
  • 2019
  • In: Nanoscale. - : ROYAL SOC CHEMISTRY. - 2040-3364 .- 2040-3372. ; 11:12, s. 5595-5606
  • Journal article (peer-reviewed)abstract
    • Owing to their unique combination of chemical and physical properties, inorganic nanoparticles show a great deal of potential as suitable agents for early diagnostics and less invasive therapies. Yet, their translation to the clinic has been hindered, in part, by the lack of non-invasive methods to quantify their concentration in vivo while also assessing their effect on the tissue physiology. In this work, we demonstrate that diffuse optical techniques, employing near-infrared light, have the potential to address this need in the case of gold nanoparticles which support localized surface plasmons. An orthoxenograft mouse model of clear cell renal cell carcinoma was non-invasively assessed by diffuse reflectance and correlation spectroscopies before and over several days following a single intravenous tail vein injection of polyethylene glycol-coated gold nanorods (AuNRs-PEG). Our platform enables to resolve the kinetics of the AuNR-PEG uptake by the tumor in quantitative agreement with ex vivo inductively coupled plasma mass spectroscopy. Furthermore, it allows for the simultaneous monitoring of local tissue hemodynamics, enabling us to conclude that AuNRs-PEG do not significantly alter the animal physiology. We note that the penetration depth of this current probe was a few millimeters but can readily be extended to centimeters, hence gaining clinical relevance. This study and the methodology presented here complement the nanomedicine toolbox by providing a flexible platform, extendable to other absorbing agents that can potentially be translated to human trials.
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  • 2021
  • swepub:Mat__t
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  • 2021
  • swepub:Mat__t
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8.
  • Albert, Marie Christine, et al. (author)
  • Identification of FasL as a crucial host factor driving COVID-19 pathology and lethality
  • 2024
  • In: Cell Death and Differentiation. - 1350-9047. ; 31:5, s. 544-557
  • Journal article (peer-reviewed)abstract
    • The dysregulated immune response and inflammation resulting in severe COVID-19 are still incompletely understood. Having recently determined that aberrant death-ligand-induced cell death can cause lethal inflammation, we hypothesized that this process might also cause or contribute to inflammatory disease and lung failure following SARS-CoV-2 infection. To test this hypothesis, we developed a novel mouse-adapted SARS-CoV-2 model (MA20) that recapitulates key pathological features of COVID-19. Concomitantly with occurrence of cell death and inflammation, FasL expression was significantly increased on inflammatory monocytic macrophages and NK cells in the lungs of MA20-infected mice. Importantly, therapeutic FasL inhibition markedly increased survival of both, young and old MA20-infected mice coincident with substantially reduced cell death and inflammation in their lungs. Intriguingly, FasL was also increased in the bronchoalveolar lavage fluid of critically-ill COVID-19 patients. Together, these results identify FasL as a crucial host factor driving the immuno-pathology that underlies COVID-19 severity and lethality, and imply that patients with severe COVID-19 may significantly benefit from therapeutic inhibition of FasL.
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10.
  • Bischoff, Stephan C, et al. (author)
  • Towards a multidisciplinary approach to understand and manage obesity and related diseases
  • 2017
  • In: Clinical Nutrition. - : Elsevier BV. - 0261-5614 .- 1532-1983. ; 36:4, s. 917-938
  • Research review (peer-reviewed)abstract
    • Overnutrition and sedentary lifestyle result in overweight or obesity defined as abnormal or excessive fat accumulation that may impair health. According to the WHO, the worldwide prevalence of obesity nearly doubled between 1980 and 2008. In 2008, over 50% of both men and women in the WHO European Region were overweight, and approximately 23% of women and 20% of men were obese. Comprehensive diagnostic and therapeutic approaches should include nutritional treatment to favor the best metabolic and nutritional outcome, as well as to induce potential disease-specific benefits from selected nutritional regimens. Obesity is usually accompanied by an increased muscle mass. This might explain why obesity, under particular circumstances such as cancer or high age, might have protective effects, a phenomenon named the 'obesity paradox'. However, loss of muscle mass or function can also occur, which is associated with poor prognosis and termed 'sarcopenic obesity'. Therefore, treatment recommendations may need to be individualized and adapted to co-morbidities. Since obesity is a chronic systemic disease it requires a multidisciplinary approach, both at the level of prevention and therapy including weight loss and maintenance. In the present personal review and position paper, authors from different disciplines including endocrinology, gastroenterology, nephrology, pediatrics, surgery, geriatrics, intensive care medicine, psychology and psychiatry, sports medicine and rheumatology, both at the basic science and clinical level, present their view on the topic and underline the necessity to provide a multidisciplinary approach, to address this epidemic.
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  • Cardós-Alonso, María Carmen, et al. (author)
  • Use of self-efficacy scale in mass casualty incidents during drill exercises
  • 2024
  • In: BMC Health Services Research. - : BioMed Central (BMC). - 1472-6963. ; 24:1
  • Journal article (peer-reviewed)abstract
    • Introduction: Medical First Responders (MFRs) in the emergency department SUMMA 112 are tasked with handling the initial management of Mass Casualty Incidents (MCI) and building response capabilities. Training plays a crucial role in preparing these responders for effective disaster management. Yet, evaluating the impact of such training poses challenges since true competency can only be proven amid a major event. As a substitute gauge for training effectiveness, self-efficacy has been suggested.Objective: The purpose of this study is to employ a pre- and post-test assessment of changes in perceived self-efficacy among MFRs following an intervention focused on the initial management of MCI. It also aimed to evaluate a self-efficacy instrument for its validity and reliability in this type of training.Method: In this study, we used a pretest (time 1 = T1) – post-test (time 2 = T2) design to evaluate how self-efficacy changed after a training intervention with 201 MFRs in initial MCI management. ANOVA within-subjects and between subjects analyses were used. Results: The findings reveal a noteworthy change in self-efficacy before and after training among the 201 participants. This suggests that the training intervention positively affected participants’ perceived capabilities to handle complex situations like MCI.Conclusion: The results allow us to recommend a training program with theory components together with practical workshops and live, large-scale simulation exercises for the training of medical first responders in MCI, as it significantly increases their perception of the level of self-efficacy for developing competencies associated with disaster response.
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13.
  • Del Cura-González, Isabel, et al. (author)
  • How to Improve Healthcare for Patients with Multimorbidity and Polypharmacy in Primary Care : A Pragmatic Cluster-Randomized Clinical Trial of the MULTIPAP Intervention
  • 2022
  • In: Journal of Personalized Medicine. - : MDPI AG. - 2075-4426. ; 12:5
  • Journal article (peer-reviewed)abstract
    • (1) Purpose: To investigate a complex MULTIPAP intervention that implements the Ariadne principles in a primary care population of young-elderly patients with multimorbidity and polypharmacy and to evaluate its effectiveness for improving the appropriateness of prescriptions. (2) Methods: A pragmatic cluster-randomized clinical trial was conducted involving 38 family practices in Spain. Patients aged 65-74 years with multimorbidity and polypharmacy were recruited. Family physicians (FPs) were randomly allocated to continue usual care or to provide the MULTIPAP intervention based on the Ariadne principles with two components: FP training (eMULTIPAP) and FP patient interviews. The primary outcome was the appropriateness of prescribing, measured as the between-group difference in the mean Medication Appropriateness Index (MAI) score change from the baseline to the 6-month follow-up. The secondary outcomes were quality of life (EQ-5D-5L), patient perceptions of shared decision making (collaboRATE), use of health services, treatment adherence, and incidence of drug adverse events (all at 1 year), using multi-level regression models, with FP as a random effect. (3) Results: We recruited 117 FPs and 593 of their patients. In the intention-to-treat analysis, the between-group difference for the mean MAI score change after a 6-month follow-up was -2.42 (95% CI from -4.27 to -0.59) and, between baseline and a 12-month follow-up was -3.40 (95% CI from -5.45 to -1.34). There were no significant differences in any other secondary outcomes. (4) Conclusions: The MULTIPAP intervention improved medication appropriateness sustainably over the follow-up time. The small magnitude of the effect, however, advises caution in the interpretation of the results given the paucity of evidence for the clinical benefit of the observed change in the MAI.
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14.
  • Giralt, Sergio, et al. (author)
  • American Society of Blood and Marrow Transplantation, European Society of Blood and Marrow Transplantation, Blood and Marrow Transplant Clinical Trials Network, and International Myeloma Working Group Consensus Conference on Salvage Hematopoietic Cell Transplantation in Patients with Relapsed Multiple Myeloma.
  • 2015
  • In: Biology of Blood and Marrow Transplantation. - : Elsevier BV. - 1083-8791. ; 21:12, s. 2039-2051
  • Journal article (peer-reviewed)abstract
    • In contrast to the upfront setting in which the role of high-dose therapy with autologous hematopoietic cell transplantation (HCT) as consolidation of a first remission in patients with multiple myeloma (MM) is well established, the role of high-dose therapy with autologous or allogeneic HCT has not been extensively studied in MM patients relapsing after primary therapy. The International Myeloma Working Group together with the Blood and Marrow Transplant Clinical Trials Network, the American Society of Blood and Marrow Transplantation, and the European Society of Blood and Marrow Transplantation convened a meeting of MM experts to: (1) summarize current knowledge regarding the role of autologous or allogeneic HCT in MM patients progressing after primary therapy, (2) propose guidelines for the use of salvage HCT in MM, (3) identify knowledge gaps, (4) propose a research agenda, and (5) develop a collaborative initiative to move the research agenda forward. After reviewing the available data, the expert committee came to the following consensus statement for salvage autologous HCT: (1) In transplantation-eligible patients relapsing after primary therapy that did NOT include an autologous HCT, high-dose therapy with HCT as part of salvage therapy should be considered standard; (2) High-dose therapy and autologous HCT should be considered appropriate therapy for any patients relapsing after primary therapy that includes an autologous HCT with initial remission duration of more than 18 months; (3) High-dose therapy and autologous HCT can be used as a bridging strategy to allogeneic HCT; (4) The role of postsalvage HCT maintenance needs to be explored in the context of well-designed prospective trials that should include new agents, such as monoclonal antibodies, immune-modulating agents, and oral proteasome inhibitors; (5) Autologous HCT consolidation should be explored as a strategy to develop novel conditioning regimens or post-HCT strategies in patients with short (less than 18 months remissions) after primary therapy; and (6) Prospective randomized trials need to be performed to define the role of salvage autologous HCT in patients with MM relapsing after primary therapy comparing it to "best non-HCT" therapy. The expert committee also underscored the importance of collecting enough hematopoietic stem cells to perform 2 transplantations early in the course of the disease. Regarding allogeneic HCT, the expert committee agreed on the following consensus statements: (1) Allogeneic HCT should be considered appropriate therapy for any eligible patient with early relapse (less than 24 months) after primary therapy that included an autologous HCT and/or high-risk features (ie, cytogenetics, extramedullary disease, plasma cell leukemia, or high lactate dehydrogenase); (2) Allogeneic HCT should be performed in the context of a clinical trial if possible; (3) The role of postallogeneic HCT maintenance therapy needs to be explored in the context of well-designed prospective trials; and (4) Prospective randomized trials need to be performed to define the role salvage allogeneic HCT in patients with MM relapsing after primary therapy.
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  • Hehlmann, Ruediger, et al. (author)
  • The European LeukemiaNet : achievements and perspectives
  • 2011
  • In: Haematologica. - : Ferrata Storti Foundation (Haematologica). - 0390-6078 .- 1592-8721. ; 96:1, s. 156-162
  • Journal article (peer-reviewed)abstract
    • The only way to cure leukemia is by cooperative research. To optimize research, the European Leukemia Net integrates 105 national leukemia trial groups and networks, 105 interdisciplinary partner groups and about 1,000 leukemia specialists from 175 institutions. They care for tens of thousands of leukemia patients in 33 countries across Europe. Their ultimate goal is to cure leukemia. Since its inception in 2002, the European Leukemia Net has steadily expanded and has unified leukemia research across Europe. The European Leukemia Net grew from two major roots: 1) the German Competence Network on Acute and Chronic Leukemias; and 2) the collaboration of European Investigators on Chronic Myeloid Leukemia. The European Leukemia Net has improved leukemia research and management across Europe. Its concept has led to funding by the European Commission as a network of excellence. Other sources (European Science Foundation; European Leukemia Net-Foundation) will take over when the support of the European Commission ends.
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17.
  • Huyghe, Jeroen R., et al. (author)
  • Discovery of common and rare genetic risk variants for colorectal cancer
  • 2019
  • In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:1, s. 76-
  • Journal article (peer-reviewed)abstract
    • To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 x 10(-8), bringing the number of known independent signals for CRC to similar to 100. New signals implicate lower-frequency variants, Kruppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.
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18.
  • Jürgensen, Jan Henning, 1987- (author)
  • Individual Failure Rate Modelling and Exploratory Failure Data Analysis for Power System Components
  • 2018
  • Doctoral thesis (other academic/artistic)abstract
    • A set of vital societal functions such as health and safety are necessary for today's society to function and to secure the life of its individuals. Infrastructure is required to provide and maintain these functions. This for society critical infrastructure includes electronic communication technology, transport systems, oil \& gas supply, water supply, and the supply of electric power. The electric power system plays a central role in the critical infrastructure since it is required to operate all others. Therefore, outages in the power system can have severe consequences not solely for the supply of electricity but also for the supply of water, gas, and food. To provide a reliable and safe power supply, power system operators are applying asset management strategies to investigate, plan, maintain, and utilize the system and its components while improving the performance under its own financial constraints.One approach to increase the reliability of the power grid while decreasing costs is maintenance planning, scheduling, and optimization. To optimize maintenance, a reliability measure for power system components is required. The failure rate, which is the probability of failure in a predefined interval, is utilized in maintenance optimization. Thus far, an average failure rate has been assigned to all components of the same type due to a shortage of component failure data. However, this limits the accuracy of maintenance techniques since the component heterogeneity is neglected. Moreover, the actual failure rate is being underrated or overrated and it is a challenge to identify the impact of conducted maintenance tasks.This thesis presents how the failure rate accuracy can be improved despite limited failure data available. Firstly, an introduction to failure rate modelling theory, concepts, and definitions is given to provide a common understanding for the later chapters and papers. Secondly, regression models are presented which can be used to model, predict, and characterise the failure rate and failure intensity for power system components. The Cox regression and regression models for count data are applied to two case studies of disconnector and circuit breaker failure data. The results contribute to an improved modelling of the failure rate on individual level but also improve the understanding of risk factor's impact on component failures. However, the aforementioned regression models have rarely been applied in the power system domain due to the limited failure data. Thirdly, the necessity to distinguish between population and individual failure rates is illustrated and risk factors and methods are presented, which are frequently used in failure rate modelling. Moreover, the thesis presents a method to calculate and predict individual failure rates despite the occurrence of actual failures which is of particular advantage for new components.
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20.
  • Levis, Mark, et al. (author)
  • Results from a randomized trial of salvage chemotherapy followed by lestaurtinib for patients with FLT3 mutant AML in first relapse
  • 2011
  • In: Blood. - : American Society of Hematology. - 1528-0020 .- 0006-4971. ; 117:12, s. 3294-3301
  • Journal article (peer-reviewed)abstract
    • In a randomized trial of therapy for FMS-like tyrosine kinase-3 (FLT3) mutant acute myeloid leukemia in first relapse, 224 patients received chemotherapy alone or followed by 80 mg of the FLT3 inhibitor lestaurtinib twice daily. Endpoints included complete remission or complete remission with incomplete platelet recovery (CR/CRp), overall survival, safety, and tolerability. Correlative studies included pharmacokinetics and analysis of in vivo FLT3 inhibition. There were 29 patients with CR/CRp in the lestaurtinib arm and 23 in the control arm (26% vs 21%; P = .35), and no difference in overall survival between the 2 arms. There was evidence of toxicity in the lestaurtinib-treated patients, particularly those with plasma levels in excess of 20 mu M. In the lestaurtinib arm, FLT3 inhibition was highly correlated with remission rate, but target inhibition on day 15 was achieved in only 58% of patients receiving lestaurtinib. Given that such a small proportion of patients on this trial achieved sustained FLT3 inhibition in vivo, any conclusions regarding the efficacy of combining FLT3 inhibition with chemotherapy are limited. Overall, lestaurtinib treatment after chemotherapy did not increase response rates or prolong survival of patients with FLT3 mutant acute myeloid leukemia in first relapse. This study is registered at www.clinicaltrials.gov as #NCT00079482. (Blood. 2011;117(12): 3294-3301)
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21.
  • Ljungqvist, Olle, et al. (author)
  • The European fight against malnutrition
  • 2010
  • In: Clinical Nutrition. - : Elsevier. - 0261-5614 .- 1532-1983. ; 29:2, s. 149-150
  • Journal article (peer-reviewed)
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22.
  • Mazidi, Peyman, et al. (author)
  • A Comparative Study of Techniques Utilized in Analysis of Wind Turbine Data
  • 2016
  • Conference paper (peer-reviewed)abstract
    • Power produced by a wind turbine is dependent on many factors with different importance degrees. Knowing the main factors can be found by a thorough analysis of all the factors and their correlation and impact on the main output, active power produced by the wind turbine. Therefore, it is important to monitor the performance of the wind turbines in order to minimize the operation and maintenance costs by pointing out abnormalities. This paper analyzes the main factors affecting active output power of a wind turbine which are Gearbox Temperature, Pitch Angle, Rotor Speed and Wind Speed. The data monitored and measured is for over a 12-month period. Several techniques, Kohonen Maps, Multilayer Perceptron, Decision Trees and Rough Sets, are applied to these data. The objective is to show a comparison of different techniques, their positive and negative points and give the reader the ability to choose the best technique for the study based on the their advantages and disadvantages. For the assessment of data, MATLAB and WEKA software are utilized. Each study presents its accuracy based on the output error.
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23.
  • Mazidi, Peyman, et al. (author)
  • A Performance and Maintenance Evaluation Framework for Wind Turbines
  • 2016
  • Conference paper (peer-reviewed)abstract
    • In this paper, a data driven framework forperformance and maintenance evaluation (PAME) of windturbines (WT) is proposed. To develop the framework, SCADAdata of WTs are adopted and several parameters are carefullyselected to create a normal behavior model. This model which isbased on Neural Networks estimates operation of WT andaberrations are collected as deviations. Afterwards, in order tocapture patterns of deviations, self-organizing map is applied tocluster the deviations. From investigations on deviations andclustering results, a time-discrete finite state space Markov chainis built for mid-term operation and maintenance evaluation.With the purpose of performance and maintenance assessment,two anomaly indexes are defined and mathematically formulated.Moreover, Production Loss Profit is defined for PreventiveMaintenance efficiency assessment. By comparing the indexescalculated for 9 WTs, current performance and maintenancestrategies can be evaluated, and results demonstrate capabilityand effectiveness of the proposed framework.
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25.
  • Mazidi, Peyman (author)
  • From Condition Monitoring to Maintenance Management in Electric Power System Generation with focus on Wind Turbines
  • 2018
  • Doctoral thesis (other academic/artistic)abstract
    • With increase in the number of sensors installed on sub-assemblies of industrial components, the amount of data collected is rapidly increasing. These data hold information in the areas of operation of the system and evolution of health condition of the components. Therefore, extracting the knowledge from the data can bring about significant improvements in the aforementioned areas.This dissertation provides a path for achieving such an objective. It starts by analyzing the data at the sub-assembly level of the components and creates four frameworks for analysis of operation and maintenance (O&M) for past, present and future horizons at the component level. These frameworks allow improvement in operation, maintenance planning, cost reduction, efficiency and performance of the industrial components. Next, the dissertation evaluates whether such models can be linked with system level analysis and how providing such a link could provide additional improvements for system operators. Finally, preventive maintenance (PM) in generation maintenance scheduling (GMS) in electric power systems is reviewed and updated with recent advancements such as connection to the electricity market and detailed implementation of health condition indicators into the maintenance models. In particular, maintenance scheduling through game theory in deregulated power system, for offshore wind farm (OWF) and an islanded microgrid (MG) are investigated.The results demonstrate improvements in reducing cost and increasing profit for the market agents and system operators as well as asset owners. Moreover, the models also deliver an insight on how direct integration of the collected operation data through the developed component level models can assist in improving the operation and management of maintenance for the system.
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26.
  • Mazidi, Peyman, et al. (author)
  • Health Condition Model for Wind Turbine Monitoring through Neural Networks and Proportional Hazard Models
  • 2017
  • In: Journal of Risk and Reliability. - : Sage Publications. - 1748-006X .- 1748-0078. ; 231:5
  • Journal article (peer-reviewed)abstract
    • In this article, a parametric model for health condition monitoring of wind turbines is developed. The study is based on the assumption that a wind turbine’s health condition can be modeled through three features: rotor speed, gearbox temperature and generator winding temperature. At first, three neural network models are created to simulate normal behavior of each feature. Deviation signals are then defined and calculated as accumulated time-series of differences between neural network predictions and actual measurements. These cumulative signals carry health condition–related information. Next, through nonlinear regression technique, the signals are used to produce individual models for considered features, which mathematically have the form of proportional hazard models. Finally, they are combined to construct an overall parametric health condition model which partially represents health condition of the wind turbine. In addition, a dynamic threshold for the model is developed to facilitate and add more insight in performance monitoring aspect. The health condition monitoring of wind turbine model has capability of evaluating real-time and overall health condition of a wind turbine which can also be used with regard to maintenance in electricity generation in electric power systems. The model also has flexibility to overcome current challenges such as scalability and adaptability. The model is verified in illustrating changes in real-time and overall health condition with respect to considered anomalies by testing through actual and artificial data.
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27.
  • Mazidi, Peyman, et al. (author)
  • Impact of health indicators on maintenance management and operation of power systems
  • 2017
  • In: Journal of Risk and Reliability. - : Sage Publications. - 1748-006X .- 1748-0078. ; 231:6, s. 716-731
  • Journal article (peer-reviewed)abstract
    • This article proposes a maintenance management and risk reduction approach. The approach introduces two reliability-based indexes called condition indicator and risk indicator. Condition indicator is a unit-less parameter that comes directly from monitored condition of a component and converts the categorical condition into a numerical value. Risk indicator in megawatt represents the risk imposed by the health of a component onto the system. To demonstrate application of the indicators, they are implemented through an hourly network constraint unit commitment problem and applied in a test system where the analysis of impact of condition of the generators to the operation is the new contribution. The results demonstrate how addition of such indicators will impact the operation of the grid and maintenance scheduling. The results show the benefit for the system operator as the overall failure risk in the system is taken into account, and the benefit for the asset owner as the direct impact of the maintenance to be carried out can be investigated. Two of the main outcomes of the maintenance management and risk reduction approach are as follows: asset owners can analyze their maintenance strategies and evaluate their impacts in the maintenance scheduling, and system operators can operate the grid with higher security and lower risk of failure.
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28.
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29.
  • Mazidi, Peyman, et al. (author)
  • Performance Analysis and Anomaly Detection in Wind Turbines based on Neural Networks and Principal Component Analysis
  • 2017
  • Conference paper (peer-reviewed)abstract
    • This paper proposes an approach for maintenancemanagement of wind turbines based on their life. The proposedapproach uses performance analysis and anomaly detection(PAAD) which can detect anomalies and point out the originof the detected anomalies. This PAAD algorithm utilizes neuralnetwork (NN) technique in order to detect anomalies in theperformance of the wind turbine (system layer), and then appliesprincipal component analysis (PCA) technique to uncover theroot of the detected anomalies (component layer). To validatethe accuracy of the proposed algorithm, SCADA data obtainedfrom online condition monitoring of a wind turbine are utilized.The results demonstrate that the proposed PAAD algorithm hasthe capability of exposing the cause of the anomalies. Reducingtime and cost of maintenance and increasing availability and inreturn profits in form of savings are some of the benefits of theproposed PAAD algorithm.
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30.
  • Mazidi, Peyman, et al. (author)
  • Profit-maximization generation maintenance scheduling through bi-level programming
  • 2018
  • In: European Journal of Operational Research. - : ELSEVIER SCIENCE BV. - 0377-2217 .- 1872-6860. ; 264:3, s. 1045-1057
  • Journal article (peer-reviewed)abstract
    • This paper addresses the generation maintenance scheduling (GMS) dilemma in a deregulated power system. At first, under a centralized cost minimization framework, a GMS is formulated and set as the benchmark (cost-minimization GMS). Then, the cost-minimization is changed into a profit-maximization problem of generation companies (GENCOs) and the GMS is developed as a bi-level optimization. Karush-Kuhn-Tucker conditions are applied to transform the bi-level into a single-level mixed-integer linear problem and subsequently, Nash equilibrium is obtained as the final solution for the GMS under a deregulated market (profit-maximization GMS). Moreover, to incorporate reliability and economic regulatory constraints, two rescheduling signals (incentive and penalty) are considered as coordination processes among GENCOs and independent system operators. These signals are based on energy-not-supplied and operation cost, and ensure that the result of profit-maximization GMS is in the given reliability and social cost limits, respectively. These limits are obtained from the cost-minimization GMS. Lastly, the model is evaluated on a test system. The results demonstrate applicability and challenges in GMS problems. 
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31.
  • Mazidi, Peyman, et al. (author)
  • Simulation Model based on Reliability and Maintenance of a Component and Their Effect on Cost
  • 2016
  • Conference paper (peer-reviewed)abstract
    • Maintenance actions are importantactivities carried out by utilities to maintain theoperability, reliability and sustainability of systems.These actions are mainly divided into two categories,corrective and preventive with different degrees, e.g.as-good-as-new, as-bad-as-old, imperfect. In this paper,a general flexible maintenance model is created thatintegrates both corrective and preventive maintenanceactions as well as their maintenance degree. Themodel incorporates a novel parameter, maintenanceefficiency, which inherently influences maintenanceactions and the behavior of the component under study.Impact of each maintenance action are evaluated andobserved by considering several implemented indices,e.g. expenses, reliability etc. For input data,information on failure history of the componentsuffice. The model is implemented and run in ARENAsoftware and the study presented shows accurately therelation and impact of employed variables.
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32.
  • Mazidi, Peyman, et al. (author)
  • Strategic Maintenance Scheduling of an Offshore Wind Farm in a Deregulated Power System
  • 2017
  • In: Energies. - : MDPI AG. - 1996-1073. ; 10:3
  • Journal article (peer-reviewed)abstract
    • This paper proposes a model for strategic maintenance scheduling of offshore wind farms (SMSOWF) in a deregulated power system. The objective of the model is to plan the maintenance schedules in a way to maximize the profit of the offshore wind farm. In addition, some network constraints, such as transmission lines capacity, and wind farm constraints, such as labor working shift, wave height limit and wake effect, as well as unexpected outages, are included in deterministic and stochastic studies. Moreover, the proposed model provides the ability to incorporate information from condition monitoring systems. SMSOWF is formulated through a bi-level formulation and then transformed into a single-level through Karush-Kuhn-Tucker conditions. The model is validated through a test system, and the results demonstrate applicability, advantages and challenges of harnessing the full potential of the model.
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33.
  • Mazidi, Peyman, et al. (author)
  • Wind Turbine Prognostics and Maintenance Management based on a Hybrid Approach of Neural Networks and Proportional Hazards Model
  • 2017
  • In: Journal of Risk and Reliability. - : Sage Publications. - 1748-006X .- 1748-0078. ; 231:2, s. 121-129
  • Research review (peer-reviewed)abstract
    • This paper proposes an approach for stress condition monitoring and maintenance assessment in wind turbines(WT) through large amounts of collected data from supervisory control and data acquisition (SCADA) system. Theobjectives of the proposed approach are: to provide a stress condition model for health monitoring, to assess the WT’smaintenance strategies, and to provide recommendations on current maintenance schemes for future operations ofthe wind farm. At first, several statistical techniques, namely Principal component analysis, Pearson, Spearman andKendall correlations, mutual information, regressional ReliefF and decision trees are used and compared to assessthe data for dimensionality reduction and parameter selection. Next, a normal behavior model is constructed by anartificial neural network which performs condition monitoring analysis. Then, a model based on mathematical form ofProportional hazards model is developed where it represents stress condition of the WT. Finally, those two modelsare jointly employed in order to analyze the overall performance of the WT over the study period. Several cases areanalyzed with a five-year SCADA data and maintenance information is utilized to develop and validate the proposedapproach.
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34.
  • Mazidi, Peyman, et al. (author)
  • Wind Turbine Prognostics and Maintenance Management based on a Hybrid Approach of Neural Networks and Proportional Hazards Model
  • 2016
  • In: Journal of Risk and Reliability. - 1748-006X .- 1748-0078.
  • Journal article (peer-reviewed)abstract
    • This paper proposes an approach for stress condition monitoring and maintenance assessment in wind turbines (WTs) through large amounts of collected data from the supervisory control and data acquisition (SCADA) system. The objectives of the proposed approach are to provide a stress condition model for health monitoring, to assess the WT’s maintenance strategies, and to provide recommendations on current maintenance schemes for future operations of the wind farm. At first, several statistical techniques, namely principal component analysis, Pearson, Spearman and Kendall correlations, mutual information, regressional ReliefF and decision trees are used and compared to assess the data for dimensionality reduction and parameter selection. Next, a normal behavior model is constructed by an artificial neural network which performs condition monitoring analysis. Then, a model based on the mathematical form of a proportional hazards model is developed where it represents the stress condition of the WT. Finally, those two models are jointly employed in order to analyze the overall performance of the WT over the study period. Several cases are analyzed with five-year SCADA data and maintenance information is utilized to develop and validate the proposed approach.
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35.
  • Norte, Ana Cláudia, et al. (author)
  • Host dispersal shapes the population structure of a tick-borne bacterial pathogen
  • 2020
  • In: Molecular Ecology. - : Wiley. - 0962-1083 .- 1365-294X. ; 29:3, s. 485-501
  • Journal article (peer-reviewed)abstract
    • Birds are hosts for several zoonotic pathogens. Because of their high mobility, especially of longdistance migrants, birds can disperse these pathogens, affecting their distribution and phylogeography. We focused on Borrelia burgdorferi sensu lato, which includes the causative agents of Lyme borreliosis, as an example for tick-borne pathogens, to address the role of birds as propagation hosts of zoonotic agents at a large geographical scale. We collected ticks from passerine birds in 11 European countries. B. burgdorferi s.l. prevalence in Ixodes spp. was 37% and increased with latitude. The fieldfare Turdus pilaris and the blackbird T. merula carried ticks with the highest Borrelia prevalence (92 and 58%, respectively), whereas robin Erithacus rubecula ticks were the least infected (3.8%). Borrelia garinii was the most prevalent genospecies (61%), followed by B. valaisiana (24%), B. afzelii (9%), B. turdi (5%) and B. lusitaniae (0.5%). A novel Borrelia genospecies “Candidatus Borrelia aligera” was also detected. Multilocus sequence typing (MLST) analysis of B. garinii isolates together with the global collection of B. garinii genotypes obtained from the Borrelia MLST public database revealed that: (a) there was little overlap among genotypes from different continents, (b) there was no geographical structuring within Europe, and (c) there was no evident association pattern detectable among B. garinii genotypes from ticks feeding on birds, questing ticks or human isolates. These findings strengthen the hypothesis that the population structure and evolutionary biology of tick-borne pathogens are shaped by their host associations and the movement patterns of these hosts.
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36.
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37.
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38.
  • Rivera, Antonio, et al. (author)
  • On the Exciton Model for Ion-Beam Damage: The Example of TiO2
  • 2010
  • In: Nuclear Instruments and Methods in Physics Research Section B. - : Elsevier BV. - 0168-583X .- 1872-9584. ; 268, s. 3122-3126
  • Journal article (peer-reviewed)abstract
    • The non-radiative exciton decay model recently developed to account for swift ion-beam damage toLiNbO3 is, here, discussed within a general physical perspective, taking previous work on alkali halides as a reference. Some general rules for the validity of excitonic models have been put forward, allowing one to predict the irradiation behaviour of other materials. As a new example of application, some preliminary data on the generation and growth of uniform amorphous layers induced by irradiation with Br at 13 MeV and 25 MeV have been performed on rutile (TiO2). In addition sub-threshold irradiations with Br ions at 9 MeV have been carried out. Defects generation is observed as a result. This effect is explained with the exciton model. Experiments are in the electronic excitation regime and use moderate fluences in the range of 6 x 1012 to 1.5x 1014 cm-2. The results show similar features to those found for LiNbO3 and are, in principle, consistent with a non-radiative exciton decay model.
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39.
  • Sanz-Barbero, Belén, et al. (author)
  • Factors associated with the utilization of primary care emergency centers in a Spanish region with high population dispersion : a mixed-methods study
  • 2014
  • In: BMC Health Services Research. - : BioMed Central. - 1472-6963. ; 14, s. 368-
  • Journal article (peer-reviewed)abstract
    • Background: Adequate access to primary care emergency centers is particularly important in rural areas isolated from urban centers. However, variability in utilization of emergency services located in primary care centers among inhabitants of nearby geographical areas is understudied. The objectives of this study are twofold: 1) to analyze the association between the availability of municipal emergency care centers and utilization of primary care emergency centers (PCEC), in a Spanish region with high population dispersion; and 2) to determine healthcare providers' perceptions regarding PCEC utilization. Methods: A mixed-methods study was conducted. Quantitative phase: multilevel logistic regression modeling using merged data from the 2003 Regional Health Survey of Castile and Leon and the 2001 census data (Spain). Qualitative phase: 14 in-depth-interviews of rural-based PCEC providers. Results: Having PCEC as the only emergency center in the municipality was directly associated with its utilization (p < 0.001). Healthcare providers perceived that distance to hospital increased PCEC utilization, and distance to PCEC decrease its use. PCEC users were considered to be predominantly workers and students with scheduling conflicts with rural primary care opening hours. Conclusions: The location of emergency care centers is associated with PCEC utilization. Increasing access to primary care by extending hours may be an important step toward optimal PCEC utilization. Further research would determine whether lower PCEC use by certain groups is associated with disparities in access to care.
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41.
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42.
  • Testor, Pierre, et al. (author)
  • OceanGliders: A component of the integrated GOOS
  • 2019
  • In: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 6
  • Research review (peer-reviewed)abstract
    • The OceanGliders program started in 2016 to support active coordination and enhancement of global glider activity. OceanGliders contributes to the international efforts of the Global Ocean Observation System (GOOS) for Climate, Ocean Health and Operational Services. It brings together marine scientists and engineers operating gliders around the world: (1) to observe the long-term physical, biogeochemical, and biological ocean processes and phenomena that are relevant for societal applications; and, (2) to contribute to the GOOS through real-time and delayed mode data dissemination. The OceanGliders program is distributed across national and regional observing systems and significantly contributes to integrated, multi-scale and multi-platform sampling strategies. OceanGliders shares best practices, requirements, and scientific knowledge needed for glider operations, data collection and analysis. It also monitors global glider activity and supports the dissemination of glider data through regional and global databases, in real-time and delayed modes, facilitating data access to the wider community. OceanGliders currently supports national, regional and global initiatives to maintian and expand the capabilities and application of gliders to meet key global challenges such as improved measurement of ocean boundary currents, water transformation and storm forecast.
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43.
  • Tinetti, G., et al. (author)
  • A chemical survey of exoplanets with ARIEL
  • 2018
  • In: Experimental Astronomy. - : Springer Science and Business Media LLC. - 0922-6435 .- 1572-9508. ; 46:1, s. 135-209
  • Journal article (peer-reviewed)abstract
    • 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.
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44.
  • Tinetti, Giovanna, et al. (author)
  • The science of EChO
  • 2010
  • In: Proceedings of the International Astronomical Union. - 1743-9213 .- 1743-9221. ; 6:S276, s. 359-370
  • Journal article (peer-reviewed)abstract
    • The science of extra-solar planets is one of the most rapidly changing areas of astrophysics and since 1995 the number of planets known has increased by almost two orders of magnitude. A combination of ground-based surveys and dedicated space missions has resulted in 560-plus planets being detected, and over 1200 that await confirmation. NASA's Kepler mission has opened up the possibility of discovering Earth-like planets in the habitable zone around some of the 100,000 stars it is surveying during its 3 to 4-year lifetime. The new ESA's Gaia mission is expected to discover thousands of new planets around stars within 200 parsecs of the Sun. The key challenge now is moving on from discovery, important though that remains, to characterisation: what are these planets actually like, and why are they as they are In the past ten years, we have learned how to obtain the first spectra of exoplanets using transit transmission and emission spectroscopy. With the high stability of Spitzer, Hubble, and large ground-based telescopes the spectra of bright close-in massive planets can be obtained and species like water vapour, methane, carbon monoxide and dioxide have been detected. With transit science came the first tangible remote sensing of these planetary bodies and so one can start to extrapolate from what has been learnt from Solar System probes to what one might plan to learn about their faraway siblings. As we learn more about the atmospheres, surfaces and near-surfaces of these remote bodies, we will begin to build up a clearer picture of their construction, history and suitability for life. The Exoplanet Characterisation Observatory, EChO, will be the first dedicated mission to investigate the physics and chemistry of Exoplanetary Atmospheres. By characterising spectroscopically more bodies in different environments we will take detailed planetology out of the Solar System and into the Galaxy as a whole. EChO has now been selected by the European Space Agency to be assessed as one of four M3 mission candidates. © International Astronomical Union 2011.
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45.
  • Torrubiano-Domínguez, J, et al. (author)
  • No effect of unemployment on intimate partner-related femicide during the financial crisis : a longitudinal ecological study in Spain
  • 2015
  • In: BMC Public Health. - : Springer Science and Business Media LLC. - 1471-2458. ; 15
  • Journal article (peer-reviewed)abstract
    • BACKGROUND: Spain's financial crisis has been characterized by an increase in unemployment. This increase could have produced an increase in deaths of women due to intimate partner-related femicides (IPF). This study aims to determine whether the increase in unemployment among both sexes in different regions in Spain is related to an increase in the rates of IPF during the current financial crisis period.METHODS: An ecological longitudinal study was carried out in Spain's 17 regions. Two study periods were defined: pre-crisis period (2005-2007) and crisis period (2008-2013). IPF rates adjusted by age and unemployment rates for men and women were calculated. We fitted multilevel linear regression models in which observations at level 1 were nested within regions according to a repeated measurements design.RESULTS: Rates of unemployment have progressively increased in Spain, rising above 20 % from 2008 to 2013 in some regions. IPF rates decreased in some regions during crisis period with respect to pre-crisis period. The multilevel analysis does not support the existence of a significant relationship between the increase in unemployment in men and women and the decrease in IPF since 2008.DISCUSSION: The increase in unemployment in men and women in Spain does not appear to have an effect on IPF. The results of the multilevel analysis discard the hypothesis that the increase in the rates of unemployment in women and men are related to an increase in IPF rates.CONCLUSIONS: The decline in IPF since 2008 might be interpreted as the result of exposure to other factors such as the lower frequency of divorces in recent years or the medium term effects of the integral protection measures of the law on gender violence that began in 2005.
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48.
  • Thomas, HS, et al. (author)
  • 2019
  • swepub:Mat__t
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