1,707 research outputs found
A Modified Environmental Kuznets Curve for Sustainable Development Assessment Using Panel Data
Sustainable development is a concept strictly connected with basic needs of the individuals. During the last years a number of empirical studies have tried to discover and quantify the causal relations between economic growth and environmental consumption and degradation. The most widely used empirical model is the so-called Environmental Kuznets Curve (EKC), nowadays applied to different polluting elements. Despite the huge diffusion of EKC studies, this model has been criticised for incompleteness of a sustainable development analysis. The aim of this paper is to build a Modified EKC (MEKC) in order to consider a wider concept of development rather than pure economic growth, including well-being aspects and sustainability of the development process. Using a macroeconomic measure of sustainability such as the World Bank’s Genuine Saving and a measure of well-being such as the United Nations’ Human Development Index, we build a model in order to analyse linkages between higher welfare levels and natural resources consumption, verifying the sustainability of human development. A panel analysis for three years (1990-1995-2000) for a wide range of countries (including developed and developing countries) has been applied in order to respond to criticisms related to conjunctural results linked to pure cross-section studies. Comparisons among alternative pollutants (i.e., CO2, NOX, and SOX) and GS are described, and the robustness of the MEKC clearly emerges. Furthermore, in order to respond to criticisms for the reduced form of the EKC, an Instrumental Variables model has been tested both on CO2 and GS, while a system of equations has been tested considering simultaneously a traditional EKC and a MEKC for a longer time period (1996-2004). Unit root tests for non-stationary series have been computed, showing that the IV model gives satisfactory results. An indicator for technological capabilities has been added at this stage, accounting for diffusion of technical progress and import technology as suggested by Archibugi and Coco (2004). Causal relations identified within a MEKC allow to identify correlation between human development and sustainable development, following the classic inverted U-shaped curve of the EKC. Nonetheless, comparing the turning points of the MEKC and EKC, respectively, it seems that using this alternative specification some useful policy implications apply. The threshold level of human development in the MEKC corresponds to an income per capita level lower than the threshold level for the EKC, confirming the possibility of “tunnelling through the curve” as suggested in Munasinghe (1999). Our results show that human development should be the first objective of international development policies, and an increase in human well-being is necessary to provide a sustainability path.Environmental Kuznets Curve, Sustainable development, Human development, Genuine saving, Panel data
The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data
The increasing attention given to global energy issues and the international policies needed to reduce greenhouse gas emissions have given a renewed stimulus to research interest in the linkages between the energy sector and economic performance at country level. In this paper, we analyse the causal relationship between economy and energy by adopting a Vector Error Correction Model for non-stationary and cointegrated panel data with a large sample of developed and developing countries and four distinct energy sectors. The results show that alternative country samples hardly affect the causality relations, particularly in a multivariate multi-sector frameworkEnergy Sector, Panel Unit Roots, Panel Cointegration, Vector Error Correction Models, Granger Causality
A protected discharge facility for the elderly: design and validation of a working proof-of-concept
With the increasing share of elderly population worldwide, the need for assistive
technologies to support clinicians in monitoring their health conditions is becoming
more and more relevant. As a quantitative tool, geriatricians recently proposed the
notion of frail elderly, which rapidly became a key element of clinical practices for the
estimation of well-being in aging population. The evaluation of frailty is commonly
based on self-reported outcomes and occasional physicians evaluations, and may
therefore contain biased results.
Another important aspect in the elderly population is hospitalization as a risk factor
for patient\u2019s well being and public costs. Hospitalization is the main cause of functional
decline, especially in older adults. The reduction of hospitalization time may
allow an improvement of elderly health conditions and a reduction of hospital costs.
Furthermore, a gradual transition from a hospital environment to a home-like one,
can contribute to the weaning of the patient from a condition of hospitalization to a
condition of discharge to his home. The advent of new technologies allows for the
design and implementation of smart environments to monitor elderly health status
and activities, fulfilling all the requirements of health and safety of the patients.
From these starting points, in this thesis I present data-driven methodologies to
automatically evaluate one of the main aspects contributing to the frailty estimation,
i.e., the motility of the subject. First I will describe a model of protected discharge
facility, realized in collaboration and within the E.O. Ospedali Galliera (Genoa, Italy),
where patients can be monitored by a system of sensors while physicians and nurses
have the opportunity to monitor them remotely. This sensorised facility is being
developed to assist elderly users after they have been dismissed from the hospital
and before they are ready to go back home, with the perspective of coaching them
towards a healthy lifestyle. The facility is equipped with a variety of sensors (vision,
depth, ambient and wearable sensors and medical devices), but in my thesis I primarily
focus on RGB-D sensors and present visual computing tools to automatically
estimate motility features. I provide an extensive system assessment I carried out onthree different experimental sessions with help of young as well as healthy aging volunteers. The results I present are in agreement with the assessment manually
performed by physicians, showing the potential capability of my approach to complement
current protocols of evaluation
Measurement-induced quantum operations on multiphoton states
We investigate how multiphoton quantum states obtained through optical
parametric amplification can be manipulated by performing a measurement on a
small portion of the output light field. We study in detail how the macroqubit
features are modified by varying the amount of extracted information and the
strategy adopted at the final measurement stage. At last the obtained results
are employed to investigate the possibility of performing a
microscopic-macroscopic non-locality test free from auxiliary assumptions.Comment: 13 pages, 13 figure
Entanglement criteria for microscopic-macroscopic systems
We discuss the conclusions that can be drawn on a recent experimental
micro-macro entanglement test [F. De Martini, F. Sciarrino, and C. Vitelli,
Phys. Rev. Lett. 100, 253601 (2008). The system under investigation is
generated through optical parametric amplification of one photon belonging to
an entangled pair. The adopted entanglement criterion makes it possible to
infer the presence of entanglement before losses, that occur on the macrostate,
under a specific assumption. In particular, an a priori knowledge of the system
that generates the micro-macro pair is necessary to exclude a class of
separable states that can reproduce the obtained experimental results. Finally,
we discuss the feasibility of a micro-macro "genuine" entanglement test on the
analyzed system by considering different strategies, which show that in
principle a fraction epsilon, proportional to the number of photons that
survive the lossy process, of the original entanglement persists in any losses
regime.Comment: 11 pages, 10 figure
Cooperative and non-cooperative solutions to carbon leakage
A modified version of the CGE GTAP-E model is developed for assessing the economic and carbon emissions effects related to alternative policy measures implemented with the aim of reducing carbon leakage. We explore a set of scenarios, comparing solutions where Annex I countries introduce exogenously or endogenously determined carbon border taxes in order to solve the carbon leakage problem unilaterally. Results provide evidence on the scarce effectiveness of carbon tariffs in reducing carbon leakage and enhancing economic competitiveness, while they have large negative welfare effects not only on the Non-Annex countries, but also on certain Annex I countriesCarbon Leakage, Carbon Border Tax, GTAP-E model
Coherent scattering of a Multiphoton Quantum Superposition by a Mirror-BEC
We present the proposition of an experiment in which the multiphoton quantum
superposition consisting of N= 10^5 particles generated by a quantum-injected
optical parametric amplifier (QI-OPA), seeded by a single-photon belonging to
an EPR entangled pair, is made to interact with a Mirror-BEC shaped as a Bragg
interference structure. The overall process will realize a Macroscopic Quantum
Superposition (MQS) involving a microscopic single-photon state of polarization
entangled with the coherent macroscopic transfer of momentum to the BEC
structure, acting in space-like separated distant places.Comment: 4 pages, 4 figure
Cytokine secretion responsiveness of lymphomonocytes following cortisol cell exposure: Sex differences
The stress hormone cortisol has been recognized as a coordinator of immune response. However, its different ability to modulate the release of inflammatory mediators in males and females has not been clarified yet. Indeed, the dissection of cortisol specific actions may be difficult due to the complex hormonal and physio-pathological individual status. Herein, the release of inflammatory mediators following increasing cortisol concentrations was investigated in an in vitro model of primary human male and female lymphomonocytes. The use of a defined cellular model to assess sex differences in inflammatory cytokine secretion could be useful to exclude the effects of divergent and fluctuating sex hormone levels occurring in vivo. Herein, the cells were challenged with cortisol concentrations resembling the plasma levels achieving in physiological and stressful conditions. The production of cytokines and other molecules involved in inflammatory process was determined. In basal conditions, male cells presented higher levels of some pro-inflammatory molecules (NF-kB and IDO-1 mRNAs, IL-6 and kynurenine) than female cells. Following cortisol exposure, the levels of the pro-inflammatory cytokines, IL-6 and IL-8, were increased in male cells. Conversely, in female cells IL-6 release was unchanged and IL-8 levels were decreased. Anti-inflammatory cytokines, IL-4 and IL-10, did not change in male cells and increased in female cells. Interestingly, kynurenine levels were higher in female cells than in male cells following cortisol stimulus. These results highlighted that cortisol differently affects male and female lymphomonocytes, shifting the cytokine release in favour of a pro-inflammatory pattern in male cells and an anti-inflammatory secretion profile in female cells, opening the way to study the influences of other stressful factors involved in the neurohumoral changes occurring in the response to stress conditions
Potential biomarkers and novel pharmacological targets in protein aggregation-related neurodegenerative diseases
The aggregation of specific proteins plays a pivotal role in the etiopathogenesis of several neurodegenerative diseases (NDs). β-Amyloid (Aβ) peptide-containing plaques and intraneuronal neurofibrillary tangles composed of hyperphosphorylated protein tau are the two main neuropathological lesions in Alzheimer's disease. Meanwhile, Parkinson's disease is defined by the presence of intraneuronal inclusions (Lewy bodies), in which α-synuclein (α-syn) has been identified as a major protein component. The current literature provides considerable insights into the mechanisms underlying oligomeric-related neurodegeneration, as well as the relationship between protein aggregation and ND, thus facilitating the development of novel putative biomarkers and/or pharmacological targets. Recently, α-syn, tau and Aβ have been shown to interact each other or with other "pathological proteins" to form toxic heteroaggregates. These latest findings are overcoming the concept that each neurodegenerative disease is related to the misfolding of a single specific protein. In this review, potential opportunities and pharmacological approaches targeting α-syn, tau and Aβ and their oligomeric forms are highlighted with examples from recent studies. Protein aggregation as a biomarker of NDs, in both the brain and peripheral fluids, is deeply explored. Finally, the relationship between biomarker establishment and assessment and their use as diagnostics or therapeutic targets are discussed
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