2D Particle Transport in a Full Dilution Tunnel of Diesel Vehicle Emissions

Current EU legislation establishes particulate-mass emission limits for diesel vehicles, but limits on particle number emissions are also under consideration due to concerns about the adverse health effects of fine particles. We study the turbulent transport of light-duty diesel exhaust particles in a standard emission facility.JRC.H.4-Transport and air qualit

On the friction coefficient of straight-chain aggregates

A methodology to calculate the friction coefficient of an aggregate in the continuum regime is proposed. The friction coefficient and the monomer shielding factors, aggregate-average or individual, are related to the molecule-aggregate collision rate that is obtained from the molecular diffusion equation with an absorbing boundary condition on the aggregate surface. Calculated friction coefficients of straight chains are in very good agreement with previous results, suggesting that the friction coefficients may be accurately calculated from the product of the collision rate and an average momentum transfer,the latter being independent of aggregate morphology. Langevin-dynamics simulations show that the diffusive motion of straight-chain aggregates may be described either by a monomer-dependent or an aggregate-average random force, if the shielding factors are appropriately chosen.Comment: 22 pages, 6 figures, revised version. To appear in the Journal of Colloid and Interface Scienc

The Friction Coefficient of Fractal Aggregates in the Continuum and Transition Regimes

A methodology is introduced for friction-coefficient calculations of fractal-like aggregates that relates the friction coefficient to a solution of the diffusion equation. Synthetic fractal aggregates were created with a cluster-cluster aggregation algorithm. Their fiction coefficients were obtained from gas molecule-aggregate collision rates that were calculated with the COMSOL Multiphysics software. Results were compared and validated with literature values. The effect of aggregate structure on dynamical properties of the aggregate, in particular mobility, was also studied. Both the fractal dimension and the fractal prefactor are required to characterize fully an aggregate.JRC.F.8-Sustainable Transpor

Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

The spread of infectious diseases crucially depends on the pattern of contacts among individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. Few empirical studies are however available that provide estimates of the number and duration of contacts among social groups. Moreover, their space and time resolution are limited, so that data is not explicit at the person-to-person level, and the dynamical aspect of the contacts is disregarded. Here, we want to assess the role of data-driven dynamic contact patterns among individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. We consider high resolution data of face-to-face interactions between the attendees of a conference, obtained from the deployment of an infrastructure based on Radio Frequency Identification (RFID) devices that assess mutual face-to-face proximity. The spread of epidemics along these interactions is simulated through an SEIR model, using both the dynamical network of contacts defined by the collected data, and two aggregated versions of such network, in order to assess the role of the data temporal aspects. We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation which retains only the topology of the contact network fails in reproducing the size of the epidemic. These results have important implications in understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics

What's in a crowd? Analysis of face-to-face behavioral networks

The availability of new data sources on human mobility is opening new avenues for investigating the interplay of social networks, human mobility and dynamical processes such as epidemic spreading. Here we analyze data on the time-resolved face-to-face proximity of individuals in large-scale real-world scenarios. We compare two settings with very different properties, a scientific conference and a long-running museum exhibition. We track the behavioral networks of face-to-face proximity, and characterize them from both a static and a dynamic point of view, exposing important differences as well as striking similarities. We use our data to investigate the dynamics of a susceptible-infected model for epidemic spreading that unfolds on the dynamical networks of human proximity. The spreading patterns are markedly different for the conference and the museum case, and they are strongly impacted by the causal structure of the network data. A deeper study of the spreading paths shows that the mere knowledge of static aggregated networks would lead to erroneous conclusions about the transmission paths on the dynamical networks

High-resolution measurements of face-to-face contact patterns in a primary school

Little quantitative information is available on the mixing patterns of children in school environments. Describing and understanding contacts between children at school would help quantify the transmission opportunities of respiratory infections and identify situations within schools where the risk of transmission is higher. We report on measurements carried out in a French school (6-12 years children), where we collected data on the time-resolved face-to-face proximity of children and teachers using a proximity-sensing infrastructure based on radio frequency identification devices. Data on face-to-face interactions were collected on October 1st and 2nd, 2009. We recorded 77,602 contact events between 242 individuals. Each child has on average 323 contacts per day with 47 other children, leading to an average daily interaction time of 176 minutes. Most contacts are brief, but long contacts are also observed. Contacts occur mostly within each class, and each child spends on average three times more time in contact with classmates than with children of other classes. We describe the temporal evolution of the contact network and the trajectories followed by the children in the school, which constrain the contact patterns. We determine an exposure matrix aimed at informing mathematical models. This matrix exhibits a class and age structure which is very different from the homogeneous mixing hypothesis. The observed properties of the contact patterns between school children are relevant for modeling the propagation of diseases and for evaluating control measures. We discuss public health implications related to the management of schools in case of epidemics and pandemics. Our results can help define a prioritization of control measures based on preventive measures, case isolation, classes and school closures, that could reduce the disruption to education during epidemics

Prognostic value of normal sodium levels in patients with metastatic renal cell carcinoma receiving tyrosine kinase inhibitors

Background: Although serum sodium concentration, particularly hyponatremia, has been shown to be a prognostic marker of survival in metastatic renal cell carcinoma (mRCC), the impact of normal sodium levels has not been investigated. Herein, we investigate the influence of normonatremia in mRCC patients treated with tyrosine kinase inhibitors (TKIs). Materials and methods: For this retrospective study, the clinical and biochemical data of patients treated with first-line TKIs for mRCC were available from seven Italian cancer centers. We collected natremia levels at baseline and first evaluation after treatment excluding patients with sodium levels outside the normal range (<135 or >145 mEq/L). The remaining patients were subdivided into two groups according to the median sodium value: natremia patients with <140 mEq/L (n = 132) and baseline natremia patients with ≥140 mEq/L (n = 185). Subsequently, we analyzed the impact of sodium levels on response rate (RR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS). PFS and OS were estimated through the Kaplan–Meier method, and differences between groups were examined by the log-rank test. Univariate and multivariate Cox regression analyses were applied to evaluate the prognostic factors for PFS and OS. Results: Of the 368 patients, 317 were included in the analysis, 73.1% were men, and the median age was 67 years (range 36–89). When comparing patients with baseline natremia ≥140 mEq/L (n = 185) to patients with natremia <140 mEq/L (n = 132), the PFS was 15 vs. 10 months (p < 0.01) and the OS was 63 vs. 36 months, respectively (p = 0.02). On the first evaluation, patients with serum sodium ≥140 mEq/L had longer PFS (15 vs. 10 months, p < 0.01) and OS (70 vs. 32 months, p < 0.01) than patients with levels <140 mEq/L. Moreover, clinical outcomes showed a significant improvement in patients with natremia ≥140 mEq/L compared with patients with levels <140 mEq/L both at baseline and first evaluation: PFS was 19 vs. 11 months (p < 0.01) and OS was 70 vs. 36 months (p < 0.01), respectively. Conclusions: To the best of our knowledge, this is the first study to investigate the impact of normonatremia in mRCC. We found that serum sodium levels <140 mEq/L at baseline and first assessment are independently associated with worse PFS and OS in mRCC patients treated with TKIs in the first-line setting