Optimal Content Placement in ICN Vehicular Networks

Information Centric Networking (ICN) is a networking framework for content distribution. The communication is based on a request/response model where the attention is centered on the content. The user sends interest messages naming the content it desires and the network chooses the best node from which delivers the content. This way for retrieving contents naturally fits a context where users continuously change their location. One of the main problems of user mobility is the intermittent connectivity that causes loss of packets. This work shows how in a Vehicle-to-Infrastructure scenario, the network can exploit the ICN architecture with content pre-distribution to maximize the probability that the user retrieves the desired content. We give an ILP formulation of the problem of optimally distributing the contents in the network nodes and discuss how the system assumptions impact the success probability. Moreover, we validate our model by means of simulations with ndnSIM

Effects of solar activity on noise in CALIOP profiles above the South Atlantic Anomaly

We show that nighttime dark noise measurements from the spaceborne lidar CALIOP contain valuable information about the evolution of upwelling high-energy radiation levels. Above the South Atlantic Anomaly (SAA), CALIOP dark noise levels fluctuate by ±6% between 2006 and 2013, and follow the known anticorrelation of local particle flux with the 11-year cycle of solar activity (with a 1-year lag). By analyzing the geographic distribution of noisy profiles, we are able to reproduce known findings about the SAA region. Over the considered period, it shifts westward by 0.3° year⁻¹, and changes in size by 6° meridionally and 2° zonally, becoming larger with weaker solar activity. All results are in strong agreement with previous works. We predict SAA noise levels will increase anew after 2014, and will affect future spaceborne lidar missions most near 2020

The contribution of major risk factors and job strain to occupational class differences in coronary heart disease incidence: the MONICA Brianza and PAMELA population-based cohorts

Objectives We investigated the contribution of major coronary heart disease (CHD) risk factors and job strain to occupational class differences in CHD incidence in a pooled-cohort prospective study in northern Italy. Methods 2964 men aged 25-74 from four northern Italian population-based cohorts were investigated at baseline and followed for first fatal or non-fatal CHD event (171 events). Standardised procedures were used for baseline risk factor measurements, follow-up and validation of CHD events. Four occupational classes were derived from the Erikson-Goldthorpe-Portocarero social class scheme: higher and lower professionals and administrators, non-manual workers, skilled and unskilled manual workers, and the self-employed. HRs were estimated with Cox models. Results Among CHD-free subjects, with non-manual workers as the reference group, age-adjusted excess risks were found for professionals and administrators (+84%, p=0.02), the self-employed (+72%, p=0.04) and manual workers (+63%, p=0.04). The relationship was consistent across different CHD diagnostic categories. Adjusting for major risk factors only slightly reduced the reported excess risks. In a sub-sample of currently employed subjects, adjusting for major risk factors, sport physical activity and job strain reduced the excess risk for manual workers (relative change = -71.4%) but did not substantially modify the excess risks of professionals and administrators and the self-employed. Conclusions In our study, we found higher CHD incidence rates for manual workers, professionals and administrators, and the self-employed, compared to non-manual workers. When the entire spectrum of job categories is considered, the job strain model helped explain the CHD excess risk for manual workers but not for other occupational classes

Rate-energy-accuracy optimization of convolutional architectures for face recognition

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Face recognition systems based on Convolutional Neural Networks (CNNs) or convolutional architectures currently represent the state of the art, achieving an accuracy comparable to that of humans. Nonetheless, there are two issues that might hinder their adoption on distributed battery-operated devices (e.g., visual sensor nodes, smartphones, and wearable devices). First, convolutional architectures are usually computationally demanding, especially when the depth of the network is increased to maximize accuracy. Second, transmitting the output features produced by a CNN might require a bitrate higher than the one needed for coding the input image. Therefore, in this paper we address the problem of optimizing the energy-rate-accuracy characteristics of a convolutional architecture for face recognition. We carefully profile a CNN implementation on a Raspberry Pi device and optimize the structure of the neural network, achieving a 17-fold speedup without significantly affecting recognition accuracy. Moreover, we propose a coding architecture custom-tailored to features extracted by such model. (C) 2015 Elsevier Inc. All rights reserved.Face recognition systems based on Convolutional Neural Networks (CNNs) or convolutional architectures currently represent the state of the art, achieving an accuracy comparable to that of humans. Nonetheless, there are two issues that might hinder their a36142148CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)sem informação2013/11359-0sem informaçã

Gender differences in the association between education and the incidence of cardiovascular events in Northern Italy.

Background: The educational differences in the incidence of major cardiovascular events are under-studied in Southern Europe and among women. Methods: The study sample includes n\u2009=\u20095084 participants to 4 population-based Northern Italian cohorts, aged 35-74 at baseline and with no previous cardiovascular events. The follow-up to ascertain the first onset of coronary heart disease (CHD) or ischaemic stroke ended in 2002. At baseline, major cardiovascular risk factors were investigated adopting the standardized MONICA procedures. Two educational classes were obtained from years of schooling. Age- and risk factors-adjusted hazard ratios of first CHD or ischaemic stroke were estimated through sex-specific separate Cox models (high education as reference). RESULTS: Median follow-up time was 12 years. Event rates were 6.38 (CHD) and 2.12 (ischaemic stroke) per 1000 person-years in men; and 1.59 and 0.94 in women. In men, low education was associated with higher mean Body Mass Index and prevalence of diabetes and cigarette smokers; but also with higher HDL cholesterol and a more favourable alcohol intake pattern. Less-educated women had higher mean systolic blood pressure, Body Mass Index and HDL cholesterol and were more likely to have diabetes. Men and women in the low educational class had a 2-fold increase in ischaemic stroke and CHD incidence, respectively, after controlling for major risk factors. Education was not associated with CHD incidence in men. Higher ischaemic stroke rates were observed among more educated women. Conclusion: In this northern Italian population, the association between education and cardiovascular risk seems to vary by gender

Unraveling the effect of proliferative stress in vivo in hematopoietic stem cell gene therapy mouse study

The hematopoietic system of patients enrolled in hematopoietic stem cells (HSC) gene therapy (GT) treatments is fully reconstituted upon autologous transplantation of engineered stem cells. HSCs highly proliferate up to full restoration of homeostasis and compete for niche homing and engraftment. The impact of the proliferation stress in HSC on genetic instability remains an open question that cured patients advocate for characterizing long-term safety and efficacy. The accumulation of somatic mutations has been widely used as a sensor of proliferative stress. Vector integration site (IS) can be used as a molecular tool for clonal identity, inherited by all HSC progeny, to uncover lineage dynamics in vivo at single-cell level. Here we characterized at single-clone granularity the proliferative stress of HSCs and their progeny over time by measuring the accumulation of mutations from the DNA of each IS. To test the feasibility of the approach, we set-up an experimental framework that combines tumor-prone Cdkn2a-/- and wild type (WT) mouse models of HSC-GT and molecular analyses on different hematopoietic cell lineages after transplantation of HSCs transduced with genotoxic LV (LV.SF.LTR) or GT-like non-genotoxic LV (SIN.LV.PGK). The Cdkn2a-/- mouse model provided the experimental conditions to detect the accumulation of somatic mutations, since the absence of p16INK4A and p19ARF enhances the proliferative potential of cells that have acquired oncogenic mutations. As expected, mice transplanted with Cdkn2a-/- Lin- cells marked with LV.SF.LTR (N=24) developed tumors significantly earlier compared to mock (N=20, p<0.0001), while mice treated with SIN. LV.PGK (N=23) did not. On the other side, mice that received WT Lin- cells treated with LV.SF.LTR (N=25) or SIN.LV.PGK (N=24) vector have not developed tumors. Given this scenario, we expect that Cdkn2a-/- Lin- cells transduced with LV.SF.LTR are associated with higher mutation rates compared to the SIN.LV.PGK group and wild type control mice. The composition of peripheral blood, lymphoid (B and T) and myeloid compartments was assessed by FACS on samples collected every 4 weeks and IS identification. More than 200,000 IS have been recovered. To identify the presence of somatic mutations, the genomic portions of sequencing reads flanking each different IS were analyzed with VarScan2. The accumulation rates of mutations have been evaluated by our new Mutation Index (MI) which normalizes the number of mutations by clones and coverage. Considering that a large portion of IS has been discarded since not covered by a minimum number of 5 unique reads (genomes), the remaining number of IS contained >90% of reads in each group. The MI increased over time in both LV.SF.LTR groups, with higher values for the Cdkn2a-/-. On the other hand, treatment with SIN.LV.PGK resulted in lower MI in both groups compared to LV.SF.LTR groups, reflecting the higher clonal composition of the cells treated with the SIN.LV.PGK and the phenomenon of insertional mutagenesis in the LV.SF.LTR. Moreover, the higher MI values of the SIN.LV.PGK Cdkn2a-/- group compared with the WT group proved the induction of DNA fragility. Our results showed that the analysis of the accumulation of somatic mutations at single clone unraveled HSC proliferation stress in vivo, combining for the first time the analysis of acquired mutations with IS. We are now applying our model to different clinical trials, and studying HSCs sub- clonal trees by symmetric divisions, previously indistinguishable by IS only. Our study will open the doors to in vivo long-term non-invasive studies of HSC stability in patients

Lidar signal simulation for the evaluation of aerosols in chemistry transport models

International audienceWe present an adaptable tool, the OPTSIM (OPTical properties SIMulation) software, for the simulation of optical properties and lidar attenuated backscattered profiles (beta') from aerosol concentrations calculated by chemistry transport models (CTM). It was developed to model both Level 1 observations and Level 2 aerosol lidar retrievals in order to compare model results to measurements: the level 2 enables to estimate the main properties of aerosols plume structures, but may be limited due to specific assumptions. The level 1, originally developed for this tool, gives access to more information about aerosols properties (beta') requiring, at the same time, less hypothesis on aerosols types. In addition to an evaluation of the aerosol loading and optical properties, active remote sensing allows the analysis of aerosols' vertical structures. An academic case study for two different species (black carbon and dust) is presented and shows the consistency of the simulator. Illustrations are then given through the analysis of dust events in the Mediterranean region during the summer 2007. These are based on simulations by the CHIMERE regional CTM and observations from the CALIOP space-based lidar, and highlight the potential of this approach to evaluate the concentration, size and vertical structure of the aerosol plumes