1,924 research outputs found
Innovative airplane ground handling system for green operations
The aim of this work is to develop a new concept of taxiing, in order to reduce the pollution in terms of noise and gas emission and to introduce a higher level of safety during ground operations.
In the area close to the airport gates, the airplane ground handlings are currently performed through the airplane engines, which have the task of providing the trust necessary to move the airplane to the runway.
Pollutant emissions and the noise level near the gates, however, could be drastically reduced by introducing an innovative autonomous tractor called CHAT (Clean Hydrogen Autonomous Tractor), developed from the standard pushback tractor.
The ground operations could be basically modified by extending the time in which the airplane engines are idle and the airplane is towed by the tractors powered by renewable energy
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Exchange Rates and Sovereign Risk
We empirically investigate the relation between currency excess returns and sovereign risk, as measured by credit default swap (CDS) spreads. An increase in a country’s CDS spread is accompanied by a contemporaneous depreciation of its exchange rate as well as an increase of its currency volatility and crash risk. The link between currency excess returns and sovereign risk is mainly driven by exposure to global sovereign risk shocks and also emerges in a predictive setting for currency risk premia. Sovereign risk forecasts excess returns to trading exchange rates, volatility and skewness, and is strongly priced in the cross-section of currencies. Moreover, we find that sovereign risk accounts for a large share of carry trade returns, and that carry and momentum strategies generate high (low) returns across countries with high (low) sovereign risk
Atherosclerosis and Its Related Laboratory Biomarkers
Atherosclerosis constitutes a persistent inflammatory ailment, serving as the predominant underlying condition for coronary artery disease (CAD), peripheral artery disease (PAD), and cerebrovascular disease. The progressive buildup of plaques within the walls of medium- and large-caliber arteries characterizes the atherosclerotic process. This accumulation results in significant narrowing that impedes blood flow, leading to critical tissue oxygen deficiency. Spontaneous blockage of thrombotic vessels can precipitate stroke and myocardial infarction, which are complications representing the primary global causes of mortality. Present-day models for predicting cardiovascular risk incorporate conventional risk factors to gauge the likelihood of cardiovascular events over a ten-year span. In recent times, researchers have identified serum biomarkers associated with an elevated risk of atherosclerotic events. Many of these biomarkers, whether used individually or in combination, have been integrated into risk prediction models to assess whether their inclusion enhances predictive accuracy. In this review, we have conducted a comprehensive analysis of the most recently published literature concerning serum biomarkers associated with atherosclerosis. We have explored the potential utility of incorporating these markers in guiding clinical decisions
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Exchange rates and sovereign risk
An increase in a country's sovereign risk, as measured by credit default swap spreads, is accompanied by a contemporaneous depreciation of its currency and an increase of its volatility. The relation between currency excess returns and sovereign risk is mainly driven by default expectations (rather than distress risk premia) and exposure to global sovereign risk shocks, and also emerges in a predictive setting for currency risk premia. We show that a sovereign risk factor is priced in the cross-section of currency returns and that it is not subsumed by the carry factor.Christian Wagner acknowledges support from the Center for Financial Frictions (FRIC), grant no. DNRF10
Photometry of the Oort Cloud comet C/2009 P1(Garradd): pre-perihelion observations at 5.7 and 2.5 AU
The aim of this paper is to contribute to the characterization of the general properties of the Long Period Comets (LPCs) family, and in particular to report on the dust environment of comet C/2009 P1 (Garradd).
The comet was observed at two epochs pre-perihelion, at ~6 AU and at ~2.5 AU: broad-band images have been used to investigate its coma morphology and properties and to model the dust production rate.
Comet C/2009 P1 (Garradd) is one of the most active and “dust producing” LPCs ever observed, even at the large heliocentric distance rh~6 AU. Its coma presents a complex morphology, with subtle structures underlying the classical fan-shaped tail, and, at rh~2.5 AU, also jet-like structures and spiralling outflows. In the reference aperture of radius ρ=5°×104 km, the R-Afρ is 3693±156 cm and 6368±412 cm, in August 2010 (rh~6 AU) and July 2011 (rh~2.5 AU), respectively. The application of a first order photometric model, under realistic assumptions on grain geometric albedo, power-law dust size distribution, phase darkening function and grain dust outflow velocity, yielded a measure of the dust production rate for the two epochs of observation of Qd=7.27×102 kg/s and Qd=1.37×103 kg/s, respectively, for a reference outflow dust velocity of vsmall=25 m/s for small (0.1–10 µm) grains and vlarge=1 m/s for large (10 µm–1 cm) grains.
These results suggest that comet Garradd is one of the most active minor bodies observed in recent years, highly contributing to the continuous replenishment of the Interplanetary Dust Complex also in the outer Solar System, and pose important constraints on the mechanism(s) driving the cometary activity at large heliocentric distances
The dust environment of comet 67P/Churyumov–Gerasimenko: results from Monte Carlo dust tail modelling applied to a large ground-based observation data set
We present an extensive data set of ground-based observations and models of the dust environment of comet 67P/Churyumov–Gerasimenko covering a large portion of the orbital arc from about 4.5 au pre-perihelion through 3.0 au post-perihelion, acquired during the current orbit. In addition, we have also applied the model to a dust trail image acquired during this orbit, as well as to dust trail observations obtained during previous orbits, in both the visible and the infrared. The results of the Monte Carlo modelling of the dust tail and trail data are generally consistent with the in situ results reported so far by the Rosetta instruments Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) and Grain Impact Analyser and Dust
Accumulator (GIADA). We found the comet nucleus already active at 4.5 au pre-perihelion, with a dust production rate increasing up to ∼3000 kg s−1 some 20 d after perihelion passage. The dust size distribution at sizes smaller than r = 1 mm is linked to the nucleus seasons, being described by a power law of index −3.0 during the comet nucleus southern hemisphere winter but becoming considerably steeper, with values between −3.6 and −4.3, during the nucleus southern hemisphere summer, which includes perihelion passage (from about 1.7 au inbound to 2.4 au outbound). This agrees with the increase of the steepness of the dust size distribution found from GIADA measurements at perihelion showing a power index of −3.7. The size distribution at sizes larger than 1 mm for the current orbit is set to a power law of index −3.6, which is near the average value of in situ measurements by OSIRIS on large particles. However, in order to fit the trail data acquired during past orbits previous to the 2009 perihelion passage, a steeper power-law index of −4.1 has been set at those dates, in agreement with previous trail modelling. The particle sizes are set at a minimum of r = 10 μm, and a maximum size, which increases with decreasing heliocentric distance, in the 1–40 cm radius domain. The particle terminal velocities are found to be consistent with the in situ measurements as derived from the instrument GIADA on board Rosetta
Individualized hepatocellular carcinoma risk : the challenges for designing successful chemoprevention strategies
Hepatocellular carcinoma (HCC) develops in the context of environmental risk factors like chronic viral hepatitis, diabetes and alcohol exposure, often associated to an increased risk of cirrhosis. Antiviral treatments that are effective to counteract hepatitis B and C may also attenuate the risk of tumor development. However, since hepatitis B-related carcinogenesis is promoted independently of the onset of cirrhosis, such antiviral treatments as nucleo(t)side analogs can promote regression of cirrhosis, prevent clinical decompensation and variceal bleeding but not HCC. This means that in successfully treated patients with cirrhosis, HCC is often the consequence of their extended survival. In hepatitis C patients, a sustained virological response to interferon-based therapies can reduce the rate of HCC development, even in patients with cirrhosis who experience histological regression of their liver disease. Future therapies aimed at this endpoint in at risk populations should take into consideration pretreatment patient stratification for host, viral and environmental risk factors. In this context the recent discovery of single nucleotide polymorphisms involved in the immune system function and tumorigenesis, might permit enrollment of populations of patients enriched with HCC risk factors for targeted chemopreventive therapies. This could finally pave the way to personalized algorithms, as already seen in the diagnosis and treatment schemes for chemoprevention
Least squares optimization: From theory to practice
Nowadays, Nonlinear Least-Squares embodies the foundation of many Robotics and Computer Vision systems. The research community deeply investigated this topic in the last few years, and this resulted in the development of several open-source solvers to approach constantly increasing classes of problems. In this work, we propose a unified methodology to design and develop efficient Least-Squares Optimization algorithms, focusing on the structures and patterns of each specific domain. Furthermore, we present a novel open-source optimization system that addresses problems transparently with a different structure and designed to be easy to extend. The system is written in modern C++ and runs efficiently on embedded systemsWe validated our approach by conducting comparative experiments on several problems using standard datasets. The results show that our system achieves state-of-the-art performances in all tested scenarios
How should eosinophilic cystitis be treated in patients with chronic granulomatous disease?
Chronic granulomatous disease (CGD) is a primary immunodeficiency resulting from the absence or malfunction of oxidative mechanism in phagocytic cells. The disease is due to a mutation in one of four genes that encode subunits of the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex. Affected patients experience severe infections and granuloma formation due to exuberant inflammatory responses. Some evidence suggests that eosinophilic cystitis (EC) is included in the spectrum of inflammatory manifestations. EC is an inflammatory disease, rare in childhood, which may require different, nonstandardized therapeutic approaches, ranging from antihistamines to cyclosporine
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