278 research outputs found

    Voltage dip generator for testing wind turbines connected to electrical networks

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    This paper describes a new voltage dip generator that allows the shape of the time profile of the voltage generated to be configured. The use of this device as a tool to test the fault ride-through capability of wind turbines connected to the electricity grid can provide some remarkable benefits: First, this system offers the possibility of adapting the main features of the time–voltage profile generated (dip depth, dip duration, the ramp slope during the recovery process after clearing fault, etc.) to the specific requirements set forth by the grid operation codes, in accordance with different network electrical systems standards. Second, another remarkable ability of this system is to provide sinusoidal voltage and current wave forms during the overall testing process without the presence of harmonic components. This is made possible by the absence of electronic converters. Finally, the paper includes results and a discussion on the experimental data obtained with the use of a reduced size laboratory prototype that was constructed to validate the operating features of this new device

    Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

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    This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license

    Timing of antibiotic therapy in the ICU

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    Severe or life threatening infections are common among patients in the intensive care unit (ICU). Most infections in the ICU are bacterial or fungal in origin and require antimicrobial therapy for clinical resolution. Antibiotics are the cornerstone of therapy for infected critically ill patients. However, antibiotics are often not optimally administered resulting in less favorable patient outcomes including greater mortality. The timing of antibiotics in patients with life threatening infections including sepsis and septic shock is now recognized as one of the most important determinants of survival for this population. Individuals who have a delay in the administration of antibiotic therapy for serious infections can have a doubling or more in their mortality. Additionally, the timing of an appropriate antibiotic regimen, one that is active against the offending pathogens based on in vitro susceptibility, also influences survival. Thus not only is early empiric antibiotic administration important but the selection of those agents is crucial as well. The duration of antibiotic infusions, especially for ÎČ-lactams, can also influence antibiotic efficacy by increasing antimicrobial drug exposure for the offending pathogen. However, due to mounting antibiotic resistance, aggressive antimicrobial de-escalation based on microbiology results is necessary to counterbalance the pressures of early broad-spectrum antibiotic therapy. In this review, we examine time related variables impacting antibiotic optimization as it relates to the treatment of life threatening infections in the ICU. In addition to highlighting the importance of antibiotic timing in the ICU we hope to provide an approach to antimicrobials that also minimizes the unnecessary use of these agents. Such approaches will increasingly be linked to advances in molecular microbiology testing and artificial intelligence/machine learning. Such advances should help identify patients needing empiric antibiotic therapy at an earlier time point as well as the specific antibiotics required in order to avoid unnecessary administration of broad-spectrum antibiotics

    Experimental Evaluation of the Factors That Influence CylindricalWater Projection Devices against IEDs

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    Terrorists usually employ Improvised Explosive Devices (IEDs) to cause maximum damage with a single action, in asymmetric war scenarios. In the counter-terrorism fight, bomb disposal specialists have to combat these instruments by safeguarding their lives, avoiding fortuitous IED explosion, and preserving evidence of the device that could lead to the capture of the perpetrators. Some very effective deactivation tools that combine these features are high-speed water-explosive projection devices. To understand and quantify the impacts of the many factors that intervene in their operation and effectiveness, extensive experimental tests should be conducted. However, Operations Research techniques allow robust results to be obtained by minimizing experiments. This study focuses on the use of Design of Experiments (DoE), with a factorial experiment plan divided into two levels, to analyze the influence of the amount of explosive, the diameter of the device (that is, the mass of water to be projected), the density of the water, the distance at which the IED is located, and the resistance of the inner tube material. Results show that the mass of explosive, the diameter of the device, the interaction of the mass of explosive and the density of the water, and the interaction between the resistance of the inner tube and the diameter of the container have a strong influence on the speed of projected water.This work was supported by the Cuerpo Nacional de PolicĂ­a and Centro Universitario de la Defensa de Zaragoza (grant number: CUD2020-21)

    Expert Statements on the Standard of Care in Critically Ill Adult Patients With Atypical Hemolytic Uremic Syndrome.

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    A typical hemolytic uremic syndrome (aHUS) presents similarly to thrombotic thrombocytopenic purpura (TTP) and other causes or conditions with thrombotic microangiopathy (TMA), such as disseminated intravascular coagulation or sepsis. Similarity in clinical presentation may hinder diagnosis and optimal treatment selection in the urgent setting in the ICU. However, there is currently no consensus on the diagnosis or treatment of aHUS for ICU specialists. This review aims to summarize available data on the diagnosis and treatment strategies of aHUS in the ICU to enhance the understanding of aHUS diagnosis and outcomes in patients managed in the ICU. To this end, a review of the recent literature (January 2009-March 2016) was performed to select the most relevant articles for ICU physicians. Based on the paucity of adult aHUS cases overall and within the ICU, no specific recommendations could be formally graded for the critical care setting. However, we recognize a core set of skills required by intensivists for diagnosing and managing patients with aHUS: recognizing thrombotic microangiopathies, differentiating aHUS from related conditions, recognizing involvement of other organ systems, understanding the pathophysiology of aHUS, knowing the diagnostic workup and relevant outcomes in critically ill patients with aHUS, and knowing the standard of care for patients with aHUS based on available data and guidelines. In conclusion, managing critically ill patients with aHUS requires basic skills that, in the absence of sufficient data from patients treated within the ICU, can be gleaned from an increasingly relevant literature outside the ICU. More data on critically ill patients with aHUS are needed to validate these conclusions within the ICU setting

    A formal framework to prove the correctness of model driven engineering composition operators

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    International audienceCurrent trends in system engineering combine modeling, composition and verification technologies in order to harness their ever growing complexity. Each composition operator dedicated to a different modeling concern should be proven to be property preserving at assembly time. These proofs are usually burdensome with repetitive aspects. Our work targets the factorisation of these aspects relying on primitive generic composition operators used to express more sophisticated language specific ones. These operators are defined for languages expressed with OMG MOF metamodeling technologies. The proof are done with the Coq proof assistant relying on the Coq4MDE framework defined previously. These basic operators, Union and Substitution, are illustrated using the MOF Package Merge as composition operator and the preservation of model conformance as verified property

    Multi-drug resistance, inappropriate initial antibiotic therapy and mortality in Gram-negative severe sepsis and septic shock: A retrospective cohort study

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    INTRODUCTION: The impact of in vitro resistance on initially appropriate antibiotic therapy (IAAT) remains unclear. We elucidated the relationship between non-IAAT and mortality, and between IAAT and multi-drug resistance (MDR) in sepsis due to Gram-negative bacteremia (GNS). METHODS: We conducted a single-center retrospective cohort study of adult intensive care unit patients with bacteremia and severe sepsis/septic shock caused by a gram-negative (GN) organism. We identified the following MDR pathogens: MDR P. aeruginosa, extended spectrum beta-lactamase and carbapenemase-producing organisms. IAAT was defined as exposure within 24 hours of infection onset to antibiotics active against identified pathogens based on in vitro susceptibility testing. We derived logistic regression models to examine a) predictors of hospital mortality and b) impact of MDR on non-IAAT. Proportions are presented for categorical variables, and median values with interquartile ranges (IQR) for continuous. RESULTS: Out of 1,064 patients with GNS, 351 (29.2%) did not survive hospitalization. Non-survivors were older (66.5 (55, 73.5) versus 63 (53, 72) years, P = 0.036), sicker (Acute Physiology and Chronic Health Evaluation II (19 (15, 25) versus 16 (12, 19), P <0.001), and more likely to be on pressors (odds ratio (OR) 2.79, 95% confidence interval (CI) 2.12 to 3.68), mechanically ventilated (OR 3.06, 95% CI 2.29 to 4.10) have MDR (10.0% versus 4.0%, P <0.001) and receive non-IAAT (43.4% versus 14.6%, P <0.001). In a logistic regression model, non-IAAT was an independent predictor of hospital mortality (adjusted OR 3.87, 95% CI 2.77 to 5.41). In a separate model, MDR was strongly associated with the receipt of non-IAAT (adjusted OR 13.05, 95% CI 7.00 to 24.31). CONCLUSIONS: MDR, an important determinant of non-IAAT, is associated with a three-fold increase in the risk of hospital mortality. Given the paucity of therapies to cover GN MDRs, prevention and development of new agents are critical

    Predictors of hospital mortality among septic ICU patients with Acinetobacter spp. bacteremia: A cohort study

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    BACKGROUND: We hypothesized that among septic ICU patients with Acinetobacter spp. bacteremia (Ac-BSI), carbapenem-resistant Acinetobacter spp. (CRAc) increase risk for inappropriate initial antibiotic therapy (non-IAAT), and non-IAAT is a predictor of hospital death. METHODS: We conducted a retrospective cohort study of adult septic ICU patients with Ac-BSI. Non-IAAT was defined as exposure to initially prescribed antibiotics not active against the pathogen based on in vitro susceptibility testing, and having no exposure to appropriate antimicrobial treatment within 24 hours of drawing positive culture. We compared patients who died to those who survived, and derived regression models to identify predictors of hospital mortality and of non-IAAT. RESULTS: Out of 131 patients with Ac-BSI, 65 (49.6%) died (non-survivors, NS). NS were older (63 [51, 76] vs. 56 [45, 66] years, p = 0.014), and sicker than survivors (S): APACHE II (24 [19, 31] vs. 18 [13, 22], p < 0.001) and Charlson (5 [2, 8] vs. 3 [1, 6], p = 0.009) scores. NS were also more likely than S to require pressors (75.4% vs. 42.4%, p < 0.001) and mechanical ventilation (75.4% vs. 53.0%, p = 0.008). Both CRAc (69.2% vs. 47.0%, p = 0.010) and non-IAAT (83.1% vs. 59.1%, p = 0.002) were more frequent among NS than S. In multivariate analyses, non-IAAT emerged as an independent predictor of hospital death (risk ratio [RR] 1.42, 95% confidence interval [CI] 1.10-1.58), while CRAc was the single strongest predictor of non-IAAT (RR 2.66, 95% CI 2.43-2.72). CONCLUSIONS: Among septic ICU patients with Ac-BSI, non-IAAT predicts mortality. Carbapenem resistance appears to mediate the relationship between non-IAAT and mortality
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