A smartphone agent for QoE evaluation and user classification over mobile networks

The continuous growth of mobile users and bandwidth-consuming applications and the shortage of radio resources put a serious challenge on how to efficiently exploit existing networks and contemporary improve Quality of Experience. One of the most relevant problem for network operators is thus to find an explicit relationship between QoS and QoE, for the purpose of maximizing the latter while saving precious resources. In order to accomplish this challenging task, we present TeleAbarth, an innovative Android application entirely developed at TelecomItalia Laboratories, able to contemporary collect network measurements and end-users quality feedback regarding the use of smartphone applications. We deployed TeleAbarth in a field experimentation in order to study the relationship between QoS and QoE for video streaming applications, in terms of downstream bandwidth and video loading time. On the basis of the results obtained, we propose a technique to classify user behavior through his or her reliability, sensibility and fairness

The Future Prospect of PV and CSP Solar Technologies: An Expert Elicitation Survey

In this paper we present and discuss the results of an expert elicitation survey on solar technologies. Sixteen leading European experts from the academic world, the private sector and international institutions took part in this expert elicitation survey on Photovoltaic (PV) and Concentrated Solar Power (CSP) technologies. The survey collected probabilistic information on (1) how Research, Development and Demonstration (RD&D) investments will impact the future costs of solar technologies and (2) the potential for solar technology deployment both in OECD and non-OECD countries. Understanding the technological progress and the potential of solar PV and CPS technologies is crucial to draft appropriate energy policies. The results presented in this paper are thus relevant for the policy making process and can be used as better input data in integrated assessment and energy models.Expert Elicitation, Research, Development and Demonstration, Solar Technologies

At Home and Abroad: An Empirical Analysis of Innovation and Diffusion in Energy-Efficient Technologies

This paper contributes to the induced innovation literature by extending the analysis of supply and demand determinants of innovation in energy-efficient technologies to account for international knowledge flows and spillovers. In the first part of the paper we select a sample of 38 innovating countries and we study how knowledge related to energy-efficient technologies flows across geographical and technological space. We demonstrate that higher geographical and technological distances are associated with a lower probability of knowledge flow. In the second part of the paper, we use our previous estimates to construct stocks of internal and external knowledge for a panel of 17 countries and present an econometric analysis of the supply and demand determinants of innovation accounting for international knowledge spillovers. Our results confirm the role of demand-pull effects, as proxied by energy prices, as well as that of technological opportunity, as proxied by the knowledge stocks. In particular, this paper provides evidence that spillovers between countries have a significant positive impact on further innovation in energy-efficient technologies.Innovation, Technology Diffusion, Knowledge Spillovers, Energy-Efficient Technologies

Threshold policy effects and directed technical change in Energy Innovation

This paper analyzes the effect of environmental policies on the direction of energy innovation across countries over the period 1990-2012. Our novelty is to use threshold regression models to allow for discontinuities in policy effectiveness depending on a country's relative competencies in renewable and fossil fuel technologies. We show that the dynamic incentives of environmental policies become effective just above the median level of relative competencies. In this critical second regime, market-based policies are moderately effective in promoting renewable innovation, while commandand-control policies depress fossil based innovation. Finally, market-based policies are more effective to consolidate a green comparative advantage in the last regime. We illustrate how our approach can be used for policy design in laggard countries

Bending the learning curve

This paper aims at improving the application of the learning curve, a popular tool used for forecasting future costs of renewable technologies in integrated assessment models (IAMs). First, we formally discuss under what assumptions the traditional (OLS) estimates of the learning curve can deliver meaningful predictions in IAMs. We argue that the most problematic of them is the absence of any effect of technology cost on its demand (reverse causality). Next, we show that this assumption can be relaxed by modifying the traditional econometric method used to estimate the learning curve. The new estimation approach presented in this paper is robust to the reverse causality problem but preserves the reduced form character of the learning curve. Finally, we provide new estimates of learning curves for wind turbines and PV technologies which are tailored for use in IAMs. Our results suggest that the learning rate should be revised downward for wind power, but possibly upward for solar PV

The Future Costs of Nuclear Power Using Multiple Expert Elicitations: Effects of RD&D and Elicitation Design

Characterization of the anticipated performance of energy technologies to inform policy decisions increasingly relies on expert elicitation. Knowledge about how elicitation design factors impact the probabilistic estimates emerging from these studies is, however, scarce. We focus on nuclear power, a large-scale low-carbon power option, for which future cost estimates are important for the design of energy policies and climate change mitigation efforts. We use data from three elicitations in the USA and in Europe and assess the role of government research, development, and demonstration (RD&D) investments on expected nuclear costs in 2030. We show that controlling for expert, technology, and design characteristics increases experts' implied public RD&D elasticity of expected costs by 25%. Public sector and industry experts' cost expectations are 14% and 32% higher, respectively than academics. US experts are more optimistic than their EU counterparts, with median expected costs 22% lower. On average, a doubling of public RD&D is expected to result in an 8% cost reduction, but the uncertainty is large. The difference between the 90th and 10th percentile estimates is on average 58% of the experts' median estimates. Public RD&D investments do not affect uncertainty ranges, but US experts are less confident about costs than Europeans

Energy intensity developments in 40 major economies: structural change or technology improvement?

This study analyzes energy intensity trends and drivers in 40 major economies using the WIOD database, a novel harmonized and consistent dataset of input-output table time series accompanied by environmental satellite data. We use logarithmic mean Divisia index decomposition to (1) study trends in global energy intensity between 1995 and 2007, (2) attribute efficiency changes to either changes in technology or changes in the structure of the economy, and (3) highlight sectoral and regional differences. We first show that heterogeneity within each sector across countries is high. These general trends within the sectors are dominated by large economies, first and foremost the United States. In most cases, heterogeneity is lower within each country across the different sectors. Regarding changes of energy intensity at the country level, improvements between 1995 and 2007 are largely attributable to technological change while structural change is less important in most countries. Notable exceptions are Japan, the United States, Australia, Taiwan, Mexico and Brazil where a change in the industry mix was the main driver behind the observed energy intensity reduction

Obtainment of chitosan with different molecular weight by varying chitin decarbonation conditions and study of a mathematical model representing the process

The effects of different chitin decarbonation conditions on chitosan molecular weight have been studied. The factors that could affect chitosan molecular weight and that have been studied in this work are temperature, time and hydrochloric acid concentration; the factor that proved to mostly affect the chitosan molecular weight is the temperature, followed by time and acid concentration. The effect of chitin molecular weight on the finally obtained deacetylation degree has also been studied, and proved to be almost irrelevant. The effect on chitosan molecular weight given by deacetylation carried out with different NaOH concentration has been analyzed; this factor proved to give inversely proportional effect on chitosan molecular weight

Interlinkages between the just ecological transition and the digital transformation

Notwithstanding increasing policy and academic debate around the 'twin' digital and ecological transitions, there is no systematic assessment of their linkages, potential synergies and trade-offs. Most fundamentally, the full extent of challenges that their interaction poses for the prospects of a 'just transition' is not fully understood. This paper discusses the role and impact of digital technologies on two key objectives of a just sustainability transition, namely (1) the creation of decent-quality employment in (2) the pursuit of climate change mitigation and, more broadly, sustainability. In addition, it also discusses (3) whether and how digitalisation affects society more broadly, with a particular focus on how digital technologies can contribute to or reduce existing inequalities, as well as promote social dialogue at all levels. For each of these three aspects, evidence is presented regarding either the negative or positive effects of a number of digital technologies in several key sectors. Based on this evidence, the rationale for jointly addressing these transformations is explained and key policy implications are put forward

THE CAMBRIDGE-PERUGIA INVENTORY FOR ASSESSMENT OF BIPOLAR DISORDER

It is well known that Bipolar Disorder is a condition which is often under diagnosed or misdiagnosed. We propose an inventory of questions which will help assess the longitutinal history of the patient’s illness, and to evaluate the presence of mixed affective states, rapid cycling, and comorbidities, all of which have an important bearing on prognosis