Mortality in the l'aquila (central Italy) earthquake of 6 april 2009.

This paper presents the results of an analysis of data on mortality in the magnitude 6.3 earthquake that struck the central Italian city and province of L'Aquila during the night of 6 April 2009. The aim is to create a profile of the deaths in terms of age, gender, location, behaviour during the tremors, and other aspects. This could help predict the pattern of casualties and priorities for protection in future earthquakes. To establish a basis for analysis, the literature on seismic mortality is surveyed. The conclusions of previous studies are synthesised regarding patterns of mortality, entrapment, survival times, self-protective behaviour, gender and age. These factors are investigated for the data set covering the 308 fatalities in the L'Aquila earthquake, with help from interview data on behavioural factors obtained from 250 survivors. In this data set, there is a strong bias towards victimisation of young people, the elderly and women. Part of this can be explained by geographical factors regarding building performance: the rest of the explanation refers to the vulnerability of the elderly and the relationship between perception and action among female victims, who tend to be more fatalistic than men and thus did not abandon their homes between a major foreshock and the main shock of the earthquake, three hours later. In terms of casualties, earthquakes commonly discriminate against the elderly and women. Age and gender biases need further investigation and should be taken into account in seismic mitigation initiatives

Communicating with communities (CwC) during post-disaster reconstruction: an initial analysis

International organisations have acknowledged that providing information to and communicating with communities affected by disasters should be considered as an integral part of the humanitarian aid. Yet little is known on the information and communication needs of the population during the disaster reconstruction phase. This paper presents a case study of the information and communication needs of the population and the role of social media during the reconstruction process after the earthquake that struck Emilia-Romagna (Northern Italy) in 2012. Data were collected through field notes and a multiple choices questionnaire distributed online and by hand to community-based groups. Results show that the most sought information concerns housing and infrastructure reconstruction, funds/refunds, business recovery and damage assessment and that city councils and regional council are considered as the main source of the information. Communication channels used to search for reconstruction-related information vary between online and offline respondents. Social media technology is used by citizens affected as a platform to read and share recovery information and post queries rather than as an engagement tool with recovery agencies. Main barriers to engagement are lack of trust towards the authorities and the belief that authorities do not use social media to communicate with citizens. In this context, community-based groups, especially those supported by social media, play an important role in sharing recovery-related information to other residents, clarifying legal acts and regulations and providing informational support to the affected population

Fast model predictive control for hydrogen outflow regulation in ethanol steam reformers

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In the recent years, the presence of alternative power sources, such as solar panels, wind farms, hydropumps and hydrogen-based devices, has significantly increased. The reasons of this trend are clear: contributing to a reduction of gas emissions and dependency on fossil fuels. Hydrogen-based devices are of particular interest due to their significant efficiency and reliability. Reforming technologies are among the most economic and efficient ways of producing hydrogen. In this paper we consider the regulation of hydrogen outflow in an ethanol steam reformer (ESR). In particular, a fast model predictive control approach based on a finite step response model of the process is proposed. Simulations performed using a more realistic non-linear model show the effectiveness of the proposed approach in driving the ESR to different operating conditions while fulfilling input and output constraints.Peer ReviewedPostprint (author's final draft

A nonparametric approach for model individualization in an artificial pancreas

The identification of patient-tailored linear time invariant glucose-insulin models is investigated for type 1 diabetic patients, that are characterized by a substantial inter-subject variability. The individualized linear models are identified by considering a novel kernel-based nonparametric approach and are compared with a linear time invariant average model in terms of prediction performance by means of the coefficient of determination, fit, positive and negative max errors, and root mean squared error. Model identification and validation are based on in-silico data collected from the adult virtual population of the UVA/Padova simulator. The data generation involves a protocol designed to produce a sufficient input excitation without compromising patient safety, compatible also with real life scenarios. The identified models are exploited to synthesize an individualized Model Predictive Controller (MPC) for each patient, which is used in an Artificial Pancreas to maintain the blood glucose concentration within an euglycemic range. The MPC used in several clinical studies, synthesized on the basis of a non-individualized average linear time invariant model, is also considered as reference. The closed-loop control performance is evaluated in an in-silico study on the adult virtual population of the UVA/Padova simulator in a perturbed scenario, in which the MPC is blind to random variations of insulin sensitivity in each virtual patient. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

On the formation of hot DQ white dwarfs

We present the first full evolutionary calculations aimed at exploring the origin of hot DQ white dwarfs. These calculations consistently cover the whole evolution from the born-again stage to the white dwarf cooling track. Our calculations provide strong support to the diffusive/convective-mixing picture for the formation of hot DQs. We find that the hot DQ stage is a short-lived stage and that the range of effective temperatures where hot DQ stars are found can be accounted for by different masses of residual helium and/or different initial stellar masses. In the frame of this scenario, a correlation between the effective temperature and the surface carbon abundance in DQs should be expected, with the largest carbon abundances expected in the hottest DQs. From our calculations, we suggest that most of the hot DQs could be the cooler descendants of some PG1159 stars characterized by He-rich envelopes markedly smaller than those predicted by the standard theory of stellar evolution. At least for one hot DQ, the high-gravity white dwarf SDSS J142625.70+575218.4, an evolutionary link between this star and the massive PG1159 star H1504+65 is plausible.Comment: 4 pages, 2 figures. To be published in The Astrophysical Journal Letter

Ground state optimization and hysteretic demagnetization: the random-field Ising model

We compare the ground state of the random-field Ising model with Gaussian distributed random fields, with its non-equilibrium hysteretic counterpart, the demagnetized state. This is a low energy state obtained by a sequence of slow magnetic field oscillations with decreasing amplitude. The main concern is how optimized the demagnetized state is with respect to the best-possible ground state. Exact results for the energy in d=1 show that in a paramagnet, with finite spin-spin correlations, there is a significant difference in the energies if the disorder is not so strong that the states are trivially almost alike. We use numerical simulations to better characterize the difference between the ground state and the demagnetized state. For d>=3 the random-field Ising model displays a disorder induced phase transition between a paramagnetic and a ferromagnetic state. The locations of the critical points R_c(DS), R_c(GS) differ for the demagnetized state and ground state. Consequently, it is in this regime that the optimization of the demagnetized stat is the worst whereas both deep in the paramagnetic regime and in the ferromagnetic one the states resemble each other to a great extent. We argue based on the numerics that in d=3 the scaling at the transition is the same in the demagnetized and ground states. This claim is corroborated by the exact solution of the model on the Bethe lattice, where the R_c's are also different.Comment: 13 figs. Submitted to Phys. Rev.

Thermo-statistical description of gas mixtures from space partitions

The new mathematical framework based on the free energy of pure classical fluids presented in [R. D. Rohrmann, Physica A 347, 221 (2005)] is extended to multi-component systems to determine thermodynamic and structural properties of chemically complex fluids. Presently, the theory focuses on $D$-dimensional mixtures in the low-density limit (packing factor $\eta < 0.01$). The formalism combines the free-energy minimization technique with space partitions that assign an available volume $v$ to each particle. $v$ is related to the closeness of the nearest neighbor and provides an useful tool to evaluate the perturbations experimented by particles in a fluid. The theory shows a close relationship between statistical geometry and statistical mechanics. New, unconventional thermodynamic variables and mathematical identities are derived as a result of the space division. Thermodynamic potentials $\mu_{il}$, conjugate variable of the populations $N_{il}$ of particles class $i$ with the nearest neighbors of class $l$ are defined and their relationships with the usual chemical potentials $\mu_i$ are established. Systems of hard spheres are treated as illustrative examples and their thermodynamics functions are derived analytically. The low-density expressions obtained agree nicely with those of scaled-particle theory and Percus-Yevick approximation. Several pair distribution functions are introduced and evaluated. Analytical expressions are also presented for hard spheres with attractive forces due to K\^ac-tails and square-well potentials. Finally, we derive general chemical equilibrium conditions.Comment: 14 pages, 8 figures. Accepted for publication in Physical Review