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To evaluate the effects of rehabilitation (physical and cognitive) treatments on the diagnosis severity and Disability Rating Scale (DRS) scores, adjusted for a number of potential confounders measured at baseline, in a large cohort of patients with disorders of consciousness across time.An observational, longitudinal (2 evaluations), multicenter project was made in 90 Italian centers.Patients (N=364) with a diagnosis of disorders of consciousness.Primary outcome was the severity of diagnosis, expressed on an ordinal scale (OtherMCSVSdeath). In the Other group were included patients who emerged from an MCS and recovered consciousness. The secondary outcome was the DRS score (range of 0-30 with 30 being the worst value). The DRS is a tool used to define the level of residual disability, commonly used to classify the level of functional impairment in patients with acquired brain injury. Both outcomes were measured for each wave.A total of 364 subjects having a complete set of demographic, clinical, and pharmacologic data were included in the propensity score (PS) analysis. Results showed that the rehabilitation treatments (physical and cognitive) reduced the clinical worsening over time in both severity diagnosis and DRS (around 6.5 points) in patients with disorders of consciousness across different propensity score strategies (ie, PS matching, PS adjustment, and PS-weighted procedures). In addition, cognitive protocols seem to be limited to patients with a median value of DRS=23.Our propensity score analysis suggests that rehabilitation treatment protocols seem effective and should be applied to a broader spectrum of patients with disorders of consciousness.

We study how oil supply shocks affect the output growth of selected countries in the Mediterranean region. We focus on the effects of oil supply shocks on economic activity, as measured by real gross value added, for the whole economy, as well as for specific industries. We show that the response of real gross value added growth is negative and often statistically significant for net energy importers, while for net energy exporters it is not distinguishable from zero. This result holds for the aggregate economies, as well as for the selected industries. Moreover, the effects of oil supply shocks increase with the degree of energy dependence in the Mediterranean countries belonging to the European Union. Our results have several policy implications. First, the European Union should encourage projects on the efficient use of energy in the Mediterranean area. Second, European financial markets should promote appropriate financial instruments to stimulate investments in the Mediterranean energy sector. Third, international investors should consider the country-specific reactions to major macroeconomic shocks in the Mediterranean region.

This work reports on the spectroscopic properties and gas sensing performances of cobalt bis-porphyrin derivative ((Co-H)Por2) in a thin films form obtained by Langmuir–Schafer (LS) method towards Volatile Organic Compounds (VOCs) and an oxidizing gas in a Magneto-Optical Surface Plasmon Resonance (MO-SPR) configuration. In particular the optical and spectroscopic properties of (Co-H)Por2 multilayers deposited onto proper Au/Co/Au magneto-plasmonic (MP) transducers were inspected in dry air conditions and after exposure to different analyte gas concentrations. The molecular organization of these thin films deposited by Langmuir–Schafer technique has been investigated and a comparison between the MOSPR experimental data and simulation has been also reported. In order to validate our experimental results and obtain further insight into the physical mechanism of interaction between the organometallic molecules and magneto plasmonic nanostructured systems, numerical simulations based on Finite Element Method (FEM) techniques, have been performed. The optical and magneto-optical properties of these hybrid systems have been theoretically analyzed to confirm the experimental outcomes. Finally, a peculiar sensitivity of the MOSPR sensing probe in respect to investigated analytes has been recorded.

We present an experimental method for measuring “realistically” the swelling ratio in terms of weight (SR W ) of PDMS, where “realistically” means without the underestimation involved by the standard protocol (weight-measurements in open environment with time-delay incompatible with fast solvent evaporation rate). Comparison with the literature demonstrates that misleading conclusions can result under application of the standard protocol to very volatile solvents. To discuss this point, we develop a mathematical expression of SR W including solvent properties and the effective amount of sorbed solvent determining a weight gain, consider two solvents with different volatility that severely swell PDMS (i.e., toluene and dichloromethane), check that the results of our measurements are consistent with theoretical predictions, demonstrate that our protocol rules out any dependence of SR W on the solvent volatility and its reliability to measure and compare SR W values of PDMS (or any swelling polymer/soft material) in the case of solvents with very different volatility.

The work reports on theoretical and nanoscale characterization of Au/Co/Au multilayers used as transducers in Magneto-optical Surface Plasmon Resonance (MOSPR) biosensors. Different aspects related to the optimization of transducers are discussed. In particular, optimized sensitivity is demonstrated to depend on the full multilayer total thickness, on the Co layer thickness and its position within the film, as well as on the discrepancy between the optical constants in very thin layers with respect to bulk values. Co layer thickness and position in the trilayer are optimized to provide the best compromise between magneto-optic (MO) activity and optical losses as well as to ensure large electromagnetic (EM) fields at the Au-dielectric interface. In this sense surface sensitivity can be maximized with respect to variations in the bulk properties of the measuring fluid and ensure higher performances with respect to traditional SPR biosensors. In parallel, a comprehensive study on the structural, morphological, chemical, magnetic and optical properties of layers composing the realized magneto-plasmonic (MP) transducers is reported by comparing the results of experimental and theoretical investigations. High resolution TEM (HR-TEM) images provided a deep insight on the interfaces morphologies thus revealing a significant discrepancy between modelled and real samples basically due to sizable roughness at each metal interface. As highlighted by hysteresis loop measurements, this parameter results having a critical role in tailoring the magnetic and consequently magneto-plasmonic properties of the trilayer transducers. As a proof of concept, a simple immunoassay relative to the study of an antibody-antigen interaction in liquid phase has been investigated.

We study the performance of tests of distributional symmetry based on the coefficient of skewness and on L-moments and present a bootstrap implementation of such tests that is suitable in time series applications. We show with Monte Carlo simulations that both tests are correctly sized – provided that their null distribution is approximated with the bootstrap – and that the procedure based on L-moments has more power than that based on the conventional coefficient of skewness. An empirical application analyses the symmetry of business cycles for the G7 countries implementing tests of symmetry as tools to investigate time reversibility.

This study investigates the effects of oil price shocks on volatility of agricultural and metal commodities. We decompose an oil price shock to its underlying components, including macroeconomics and oil specific shocks. The applied method is the structural vector autoregressive (SVAR) model and the time span is from April 1983 to May 2014. The investigation is divided into two subsamples, before and after May 2006 for agriculture taking into account the 2006–2008 food crisis and change in U.S. ethanol production policy , and before and after January 2008 for metals considering the recent global financial crisis. We find that, based on impulse response functions, the response of volatility of each commodity to an oil price shock differs significantly depending on the underlying cause of the shock for the both periods. Moreover, according to variance decomposition the explanatory power of oil shocks becomes stronger after the crisis. The different responses of commodities are described in detail by investigating market characteristics in each period.

We analyze the relationship between the prices of ethanol, corn, soybeans, wheat and cattle in Nebraska, U.S. We focus on long-run price relations, short-run Granger causality, in-sample and out-of-sample predictability linkages between returns on ethanol, field crops and cattle. Since the ethanol market has been subject to many policy interventions, our analysis takes structural breaks and parameter instabilities into account using modern statistical techniques. We find no evidence that ethanol returns Granger cause food price variations. Conversely, both in-sample and out-of-sample results suggest that ethanol is Granger caused and can be predicted by returns on corn. No linkages between ethanol and cattle are found.

This study investigates the price volatility of metals, using GARCH and GJR models. First, we examine the persistence of volatility and the leverage effect across metal markets taking into account the presence of outliers. Second, we estimate the effects of oil price shocks on the price volatility of metals, allowing for asymmetric responses. We use daily spot prices for aluminum, copper, lead, nickel, tin, zinc, gold, silver, palladium and platinum. We find that returns have a high degree of volatility persistence before and after correcting for outliers, outliers bias the estimation of GARCH and GJR models, and removing outliers improves volatility modelling. However, Student-t-based specifications outperform outliers correction in capturing volatility. Moreover, we document inverse leverage effects for seven metals, leverage effect for copper and no leverage effects for nickel and palladium. Finally, price volatility of metals reacts differently and asymmetrically to oil price shocks.

In this paper we investigate heavy crude oil and product price dynamics. We present a comparison among ten prices series of heavy crude oils and fourteen price series of petroleum products in two distinct areas (Europe and Americas) over the period 1994-2002. We provide a complete analysis of crude oil and product price dynamics using cointegration and error correction models (ECM). Subsequently we use the ECM specification to predict crude oil prices over the horizon January 2002-June 2002. Finally we compare the forecasting performance of ECM with a naive model in first differences which does not exploit any cointegrating relation. (c) 2005 Elsevier B.V. All rights reserved.

The identification of the forces that drive oil stock prices is extremely important given the size of the Oil & Gas industry and its links with the energy sector and the environment. In the next decade oil companies will have to deal with international policies to contrast climate change. This issue is likely to affect companies' shareholder values. In this paper we focus on the long-run financial determinants of the stock prices of six major oil companies (Bp, Chevron-Texaco, Eni, Exxon-Mobil, Royal Dutch Shell, Total-Fina-Elf) using multivariate cointegration techniques and vector error correction models. Weekly oil stock prices are analyzed together with the relevant stock market indexes, exchange rates, spot and future oil prices over the period January 1998-April 2003. The empirical results confirm the statistical significance of the major financial variables in explaining the long-run dynamics of oil companies' stock values. (c) 2004 Elsevier Ltd. All rights reserved.

Since oil is a non-renewable resource with a high environmental impact, and its most common use is to produce combustibles for electricity, reliable methods for modelling electricity consumption can contribute to a more rational employment of this hydrocarbon fuel. In this paper we apply the Principal Components (PC) method to modelling the load curves of Italy, France and Greece on hourly data of aggregate electricity consumption. The empirical results obtained with the PC approach are compared with those produced by the Fourier and Constrained Smoothing Spline estimators. The PC method represents a much simpler and attractive alternative to modelling electricity consumption since it is extremely easy to compute, significantly reduces the number of variables to be considered, and generally increases the accuracy of electricity consumption forecasts. As an additional advantage, the PC method is able to accommodate relevant exogenous variables such as daily temperature and environmental factors, and is extremely versatile in computing out-of-sample forecasts. (c) 2004 Elsevier Ltd. All rights reserved.

This paper uses the dynamic duality approach to build a closed-form factor demand equation system which is consistent with the intertemporal problem faced by the representative firm, aiming at minimizing the present value of its expected future costs. The technology is characterized by convex internal costs in adjusting the quasi-fixed capital input with no constraints on the degree of returns to scale. A model imposing long-run constant returns is also estimated. The two models are non-nested because of the functional form used to specify the underlying technology. In both models the hypotheses of existence and separability of adjustment costs are tested. Non-nested tests are used to discriminate between the assumptions of non-constant and constant returns to scale. Finally, the production structure for the Italian total manufacturing sector over the period 1954–1983 is analysed.