777 research outputs found
Evaporation and clustering of ammonia droplets in a hot environment
Recent developments in the transition to zero-carbon fuels show that ammonia is a valid candidate for combustion. However, liquid ammonia combustion is difficult to stabilize due to a large latent heat of evaporation, which generates a strong cooling effect that adversely affects the flame stabilization and combustion efficiency. In addition, the slow burning rate of ammonia enhances the undesired production of NOx and N2O. To increase the flame speed, ammonia must be blended with a gaseous fuel having a high burning rate. In this context, a deeper understanding of the droplet dynamics is required to optimize the combustor design. To provide reliable physical insights into diluted ammonia sprays blended with gaseous methane, direct numerical simulations are employed. Three numerical experiments were performed with cold, standard, and hot ambient in nonreactive conditions. The droplet radius and velocity distribution, as well as the mass and heat coupling source terms are compared to study the effects on the evaporation. Since the cooling effect is stronger than the heat convection between the droplet and the environment in each case, ammonia droplets do not experience boiling. On the other hand, the entrainment of dry air into the ammonia-methane mixture moves the saturation level beyond 100% and droplets condense. The aforementioned phenomena are found to strongly affect the droplet evolution. Finally, a three-dimensional Voronoi analysis is performed to characterize the dispersive or clustering behavior of droplets by means of the definition of a clustering index
Portfolio selection problems in practice: a comparison between linear and quadratic optimization models
Several portfolio selection models take into account practical limitations on
the number of assets to include and on their weights in the portfolio. We
present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset
Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional
Value-at-Risk (LACVaR) models, where the assets are limited with the
introduction of quantity and cardinality constraints. We propose a completely
new approach for solving the LAM model, based on reformulation as a Standard
Quadratic Program and on some recent theoretical results. With this approach we
obtain optimal solutions both for some well-known financial data sets used by
several other authors, and for some unsolved large size portfolio problems. We
also test our method on five new data sets involving real-world capital market
indices from major stock markets. Our computational experience shows that,
rather unexpectedly, it is easier to solve the quadratic LAM model with our
algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of
the best commercial codes for mixed integer linear programming (MILP) problems.
Finally, on the new data sets we have also compared, using out-of-sample
analysis, the performance of the portfolios obtained by the Limited Asset
models with the performance provided by the unconstrained models and with that
of the official capital market indices
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
TP53-binding protein variants and breast cancer risk: a case-control study
INTRODUCTION: The TP53-binding protein (53BP1) has been shown to influence TP53-mediated transcriptional activation, thus playing a pivotal role in DNA damage signalling. Genetic aberrations in TP53 and in ATM and CHEK2 predispose to cancer. We have therefore examined the effects of 53BP1 single nucleotide polymorphisms (D353E, G412S, and K1136Q) and the novel 53BP1 6bp deletion (1347_1352delTATCCC) on breast cancer risk. METHODS: Allelic discrimination was performed to investigate the frequencies of 53BP1 D353E, G412S, and K1136Q and of 1347_1352delTATCCC in 353 patients with breast cancer and 960 control individuals. RESULTS: No significant association of 53BP1 D353E, G412S, or K1136Q with breast cancer risk was detected. 53BP1 1347_1352delTATCCC, leading to the loss of an isoleucine and a proline residue, showed a nonsignificant inverse association with breast cancer risk (odds ratio = 0.61, 95% confidence interval = 0.22 to 1.68, P = 0.34). CONCLUSION: The lack of association casts doubt on the putative effects of D353E, G412S, and K1136Q on breast cancer risk. Investigating a larger study cohort might elucidate the influence of the 6bp deletion 1347_1352delTATCCC. Studying the functional effect and the impact of this variant on the risk of other cancers may be revealing
Close Encounters in a Pediatric Ward: Measuring Face-to-Face Proximity and Mixing Patterns with Wearable Sensors
International audienceBackground Nosocomial infections place a substantial burden on health care systems and represent one of the major issues in current public health, requiring notable efforts for its prevention. Understanding the dynamics of infection transmission in a hospital setting is essential for tailoring interventions and predicting the spread among individuals. Mathematical models need to be informed with accurate data on contacts among individuals. Methods and Findings We used wearable active Radio-Frequency Identification Devices (RFID) to detect face-to-face contacts among individuals with a spatial resolution of about 1.5 meters, and a time resolution of 20 seconds. The study was conducted in a general pediatrics hospital ward, during a one-week period, and included 119 participants, with 51 health care workers, 37 patients, and 31 caregivers. Nearly 16,000 contacts were recorded during the study period, with a median of approximately 20 contacts per participants per day. Overall, 25% of the contacts involved a ward assistant, 23% a nurse, 22% a patient, 22% a caregiver, and 8% a physician. The majority of contacts were of brief duration, but long and frequent contacts especially between patients and caregivers were also found. In the setting under study, caregivers do not represent a significant potential for infection spread to a large number of individuals, as their interactions mainly involve the corresponding patient. Nurses would deserve priority in prevention strategies due to their central role in the potential propagation paths of infections. Conclusions Our study shows the feasibility of accurate and reproducible measures of the pattern of contacts in a hospital setting. The obtained results are particularly useful for the study of the spread of respiratory infections, for monitoring critical patterns, and for setting up tailored prevention strategies. Proximity-sensing technology should be considered as a valuable tool for measuring such patterns and evaluating nosocomial prevention strategies in specific settings
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
Measurement of the Forward-Backward Asymmetry in the B -> K(*) mu+ mu- Decay and First Observation of the Bs -> phi mu+ mu- Decay
We reconstruct the rare decays , , and in a data sample
corresponding to collected in collisions at
by the CDF II detector at the Fermilab Tevatron
Collider. Using and decays we report the branching ratios. In addition, we report
the measurement of the differential branching ratio and the muon
forward-backward asymmetry in the and decay modes, and the
longitudinal polarization in the decay mode with respect to the squared
dimuon mass. These are consistent with the theoretical prediction from the
standard model, and most recent determinations from other experiments and of
comparable accuracy. We also report the first observation of the {\mathcal{B}}(B^0_s \to
\phi\mu^+\mu^-) = [1.44 \pm 0.33 \pm 0.46] \times 10^{-6}27 \pm 6B^0_s$ decay observed.Comment: 7 pages, 2 figures, 3 tables. Submitted to Phys. Rev. Let
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