Mapping average equivalized income using robust small area methods

Measures of economic well‐being are often needed for geographically small areas, as economic indicators may be distributed unevenly among the subsets of relatively small regions. We consider small area estimation of average equivalized income. Disposable household income data are usually available only for a sample of households, typically too small to provide reliable estimates for small regions. We consider a small area estimation technique that is robust to outliers, produces results consistent with design weighted estimates obtained for larger areas and yield maps with approximately no shrinkage. The proposed methodology is applied to the Local Labour Systems in Tuscany (Italy).     

Coqoon

International Journal on Software Tools for Technology Transfer - User interfaces for interactive proof assistants have always lagged behind those for mainstream programming languages. Whereas...     

Formal Metatheory of Programming Languages in the Matita Interactive Theorem Prover

This paper is a report about the use of Matita, an interactive theorem prover under development at the University of Bologna, for the solution of the POPLmark Challenge, part 1a. We provide three different formalizations, including two direct solutions using pure de Bruijn and locally nameless encodings of bound variables, and a formalization using named variables, obtained by means of a sound translation to the locally nameless encoding. According to this experience, we also discuss some of the proof principles used in our solutions, which have led to the development of a generalized inversion tactic for Matita.     

Thermodynamic modeling of hydrogen refueling for heavy-duty fuel cell buses and comparison with aggregated real data

The foreseen uptake of hydrogen mobility is a fundamental step towards the decarbonization of the transport sector. Under such premises, both refueling infrastructure and vehicles should be deployed together with improved refueling protocols. Several studies focus on refueling the light-duty vehicles with 10 kg_H2 up to 700 bar, however less known effort is reported for refueling heavy-duty vehicles with 30–40 kg_H2 at 350 bar. The present study illustrates the application of a lumped model to a fuel cell bus tank-to-tank refueling event, tailored upon the real data acquired in the 3Emotion Project. The evolution of the main refueling quantities, such as pressure, temperature, and mass flow, are predicted dynamically throughout the refueling process, as a function of the operating parameters, within the safety limits imposed by SAE J2601/2 technical standard. The results show to refuel the vehicle tank from half to full capacity with an Average Pressure Ramp Rate (APRR) equal to 0.03 MPa/s are needed about 10 min. Furthermore, it is found that the effect of varying the initial vehicle tank pressure is more significant than changing the ambient temperature on the refueling performances. In conclusion, the analysis of the effect of different APRR, from 0.03 to 0.1 MPa/s, indicate that is possible to safely reduce the duration of half-to-full refueling by 62% increasing the APRR value from 0.03 to 0.08 MPa/s.     

Classification of drivers for industrial energy efficiency and their effect on the barriers affecting the investment decision-making process

Industrial energy efficiency represents a priority for European industrial competitiveness. Many studies offer contributions providing evidence of the existence of driving forces supporting the adoption of energy efficiency measures, but a structured approach to drivers for industrial energy efficiency is still lacking. Therefore, in the present study, we propose a definition of drivers, making emphasis on the industrial decision-maker perspective, that is needed for their classification here proposed. Focus is given to point out the difference between internal and external drivers, highlighting the major stakeholders responsible for their promotion. Drivers are further categorized into: regulatory, economic, informative, and vocational training. Moreover, we propose a framework describing the effect of drivers on barriers in the decision-making process, as well as a preliminary identification of the major stakeholders to promote drivers. The study opens several opportunities for further research in the area of industrial energy efficiency.     

Data Work: How Energy Advisors and Clients Make IoT Data Accountable

We present fieldwork findings from the deployment of an interactive sensing system that supports the work of energy advisors who give face-to-face advice to low-income households in the UK. We focus on how the system and the data it produced are articulated in the interactions between professional energy advisors and their clients, and how they collaboratively anticipate, rehearse, and perform data work. In addition to documenting how the system was appropriated in advisory work, we elaborate the ‘overhead cost’ of building collaborative action into connected devices and sensing systems, and the commensurate need to support discrete workflows and accountability systems to enable the methodical incorporation of the IoT into collaborative action. We contribute an elaboration of the social, collaborative methods of data work relevant to those who seek to design and study collaborative IoT systems.