Radiative feedback and cosmic molecular gas: the role of different radiative sources

We present results from multifrequency radiative hydrodynamical chemistry simulations addressing primordial star formation and related stellar feedback from various populations of stars, stellar energy distributions (SEDs) and initial mass functions. Spectra for massive stars, intermediate-mass stars and regular solar-like stars are adopted over a grid of 150 frequency bins and consistently coupled with hydrodynamics, heavy-element pollution and non-equilibrium species calculations. Powerful massive population III stars are found to be able to largely ionize H and, subsequently, He and He$^+$, causing an inversion of the equation of state and a boost of the Jeans masses in the early intergalactic medium. Radiative effects on star formation rates are between a factor of a few and 1 dex, depending on the SED. Radiative processes are responsible for gas heating and photoevaporation, although emission from soft SEDs has minor impacts. These findings have implications for cosmic gas preheating, primordial direct-collapse black holes, the build-up of "cosmic fossils" such as low-mass dwarf galaxies, the role of AGNi during reionization, the early formation of extended disks and angular-momentum catastrophe.Comment: 19 pages on MNRA

Immigration as pathogenic: a systematic review of the health of immigrants to Canada

This review investigates the health of immigrants to Canada by critically examining differences in health status between immigrants and the native-born population and by tracing how the health of immigrants changes after settling in the country. Fifty-one published empirical studies met the inclusion criteria for this review. The analysis focuses on four inter-related questions: (1) Which health conditions show transition effects and which do not? (2) Do health transitions vary by ethnicity/racialized identity? (3) How are health transitions influenced by socioeconomic status? and (4) How do compositional and contextual factors interact to affect the health of immigrants? Theoretical and methodological challenges facing this area of research are discussed and future directions are identified. This area of research has the potential to develop into a complex, nuanced, and useful account of the social determinants of health as experienced by different groups in different places

Parametric Macromodels of Drivers for SSN Simulations

This paper addresses the modeling of output and power supply ports of digital drivers for accurate and efficient SSN simulations. The proposed macromodels are defined by parametric relations, whose parameters are estimated from measured or simulated port transient responses, and are implemented as SPICE subcircuits. The modeling technique is applied to commercial high-speed devices and a realistic simulation example is shown

Understanding chronic non-communicable diseases in Latin America: towards an equity-based research agenda

Although chronic non-communicable diseases are traditionally depicted as diseases of affluence, growing evidence suggests they strike along the fault lines of social inequality. The challenge of understanding how these conditions shape patterns of population health in Latin America requires an inter-disciplinary lens. This paper reviews the burden of chronic non-communicable diseases in the region and examines key myths surrounding their prevalence and distribution. It argues that a social justice approach rooted in the idea of health inequity needs to be at the core of research in this area, and concludes with discussion of a new approach to guide empirical research, the 'average/deprivation/inequality' framework

Early warning system for the prevention and control of unauthorized accesses to air navigation services infrastructures

Early warning systems are fundamental instruments for the management of critical situations since they are able to signal in advance any anomaly with respect to ordinary situations. The purpose of this paper is to present an early warning system, based on artificial neural networks, for the prevention and control of unauthorized accesses to the air navigation services infrastructure in Italy

Parametric thermal analysis for the optimization of Double Walled Tubes layout in the Water Cooled Lithium Lead inboard blanket of DEMO fusion reactor

Within the roadmap that will lead to the nuclear fusion exploitation for electric energy generation, the construction of a DEMOnstration (DEMO) reactor is, probably, the most important milestone to be reached since it will demonstrate the technological feasibility and economic competitiveness of an industrial-scale nuclear fusion reactor. In order to reach this goal, several European universities and research centres have joined their efforts in the EUROfusion action, funded by HORIZON 2020 UE programme. Within the framework of EUROfusion research activities, ENEA and University of Palermo are involved in the design of the Water-Cooled Lithium Lead Breeding Blanket (WCLL BB), that is one of the two BB concepts under consideration to be adopted in the DEMO reactor. It is mainly characterized by a liquid lithium-lead eutectic alloy acting as breeder (lithium) and neutron multiplier (lead), as well as by subcooled pressurized water as coolant. Two separate circuits, both characterized by a pressure of 15.5 MPa and inlet/outlet temperatures of 295 °C/328 °C, are deputed to cool down the First Wall (FW) and the Breeder Zone (BZ). The former consists in a system of radial-toroidal-radial C-shaped squared channels where countercurrent water flow occurs while the latter relies in the use of bundles of poloidal-radial Double Walled Tubes (DWTs) housed within the breeder. A parametric thermal study has been carried out in order to assess the best DWTs' layout assuring that the structural material maximum temperature does not overcome the allowable limit of 550 °C and that the overall coolant thermal rise fulfils the design target value of 33 °C. The study has been performed following a theoretical-numerical approach based on the Finite Element Method (FEM) and adopting the quoted Abaqus FEM code. Main assumptions and models together with results obtained are herewith reported and critically discussed

Parametric Macromodels of Differential Drivers and Receivers

This paper addresses the modeling of differential drivers and receivers for the analog simulation of high-speed interconnection systems. The proposed models are based on mathematical expressions, whose parameters can be estimated from the transient responses of the modeled devices. The advantages of this macromodeling approach are: improved accuracy with respect to models based on simplified equivalent circuits of devices; improved numerical efficiency with respect to detailed transistor-level models of devices; hiding of the internal structure of devices; straightforward circuit interpretation; or implementations in analog mixed-signal simulators. The proposed methodology is demonstrated on example devices and is applied to the prediction of transient waveforms and eye diagrams of a typical low-voltage differential signaling (LVDS) data link

Behavioral modeling of digital IC input and output ports

This paper addresses the development of accurate and efficient behavioral models of digital integrated circuit input and output ports for signal integrity simulations and timing analyses. The modeling process is described and applied to the characterization of actual device

Behavioral Modeling of IC Ports Including Temperature Effects

The development of temperature-dependent macromodels for digital IC ports is addressed. The proposed modeling approach is based on the theory of discrete-time parametric models and allows one to estimate the model parameters from voltage and current waveforms observed at the ports and to implement the model as a SPICE subcircuit. The proposed technique is validated by applying it to commercial devices described by detailed transistor-level models. The obtained models perform at a good accuracy level and are more efficient than the original transistor-level models