Energy and number of collisions fluctuations in inelastic gases

We study by numerical simulations the two-dimensional Inelastic Maxwell Model (IMM), and show how the inelasticity of collisions together with the fluctuations of the number of collisions undergone by a particle lead to energy fluctuations that decay like a power-law. These fluctuations are associated to a shrinking of the available phase space. We find the asymptotic scaling of these energy fluctuations and show how they affect the tail of the velocity distribution during long time intervals.Comment: 4 pages, 3 figure

Microstructural Characterization of Silver Nanoparticles for Bioimaging Applications

Junta de Andalucía FQM-6615, PI0070, FQM31

O programa nacional de fortalecimento da agricultura familiar no Brasil: uma análise sobre a distribuição regional e setorial dos recursos.

No Brasil, as políticas públicas para o espaço rural sempre tenderam a priorizar a agricultura patronal, em detrimento dos agricultores familiares. Todavia, os estudos realizados pelos órgãos FAO - INCRA deram subsídio para a criação do Programa Nacional de Fortalecimento da Agricultura Familiar (PRONAF), resultando em um novo direcionamento dos investimentos públicos, os quais passaram a contemplar o segmento dos agricultores familiares. Entende-se o PRONAF como uma política não-compensatória, que, apesar de seus problemas, tem contribuído de fato para mudanças e melhorias no espaço agrário brasileiro. Desde sua criação no final da década de 1990, o PRONAF passou por várias mudanças em sua estrutura administrativa e operacional, a fim de alcançar seus objetivos e adequar-se face a complexa realidade social agrária brasileira. Sendo assim, o presente estudo visa discutir as ações do Estado por meio desse Programa, a partir de suas linhas de atuação, bem como analisar a distribuição de suas concessões de crédito regional e setorialmente. Assim, os procedimentos metodológicos utilizados para a realização deste trabalho compreendem pesquisa bibliográfica e documental, além de pesquisa em fontes secundárias, no intuito de obter dados e informações relevantes para a análise das relações sociais estabelecidas em meio a esse processo de concretização e espacialização desse Programa. Dentre as implicações do PRONAF pode-se notar em âmbito nacional, uma diminuição da disparidade regional brasileira, bem como a preocupação que o Programa tem demonstrado com os aspectos socioculturais locais e regionais, como forma de garantir que seus investimentos perpassem a dimensão econômica, mas valorize outras dimensões, a exemplo dos elementos culturais

Stereometry of Crystalline Phases Observed in Scanning Electron Microscopy

A study of edges and angles of known samples has been performed by means of stereoscopic pairs with electron microscopy in two and three dimensional systems. The derived equations have been included in a computer program. Measurements on stereoscopic pairs with different tilt angles using several crystals of galena, calcite and other objects with known dimensions have been performed. The optimum tilt angles have been obtained by comparison with the actual values, and a logarithmic ratio between these angles and the stereoscopic pairs magnification has been found. The errors obtained using this system of calculation are lower than 6% in the measure of angles and 15% in the case of edges

Estimating lengths-of-stay of hospitalised COVID-19 patients using a non-parametric model: a case study in Galicia (Spain)

Estimating the lengths-of-stay (LoS) of hospitalised COVID-19 patients is key for predicting the hospital beds' demand and planning mitigation strategies, as overwhelming the healthcare systems has critical consequences for disease mortality. However, accurately mapping the time-to-event of hospital outcomes, such as the LoS in the intensive care unit (ICU), requires understanding patient trajectories while adjusting for covariates and observation bias, such as incomplete data. Standard methods, such as the Kaplan-Meier estimator, require prior assumptions that are untenable given current knowledge. Using real-time surveillance data from the first weeks of the COVID-19 epidemic in Galicia (Spain), we aimed to model the time-to-event and event probabilities of patients' hospitalised, without parametric priors and adjusting for individual covariates. We applied a non-parametric mixture cure model and compared its performance in estimating hospital ward (HW)/ICU LoS to the performances of commonly used methods to estimate survival. We showed that the proposed model outperformed standard approaches, providing more accurate ICU and HW LoS estimates. Finally, we applied our model estimates to simulate COVID-19 hospital demand using a Monte Carlo algorithm. We provided evidence that adjusting for sex, generally overlooked in prediction models, together with age is key for accurately forecasting HW and ICU occupancy, as well as discharge or death outcomes.Comment: 14 pages, 4 figure

Stochastic model for the dynamics of interacting Brownian particles

Using the scheme of mesoscopic nonequilibrium thermodynamics, we construct the one- and two- particle Fokker-Planck equations for a system of interacting Brownian particles. By means of these equations we derive the corresponding balance equations. We obtain expressions for the heat flux and the pressure tensor which enable one to describe the kinetic and potential energy interchange of the particles with the heat bath. Through the momentum balance we analyze in particular the diffusion regime to obtain the collective diffusion coefficient in terms of the hydrodynamic and the effective forces acting on the Brownian particles.Comment: latex fil

Estimating Lengths-Of-Stay of Hospitalized COVID-19 Patients Using a Non-parametric Model: A Case Study in Galicia (Spain)

[Abstract:] Estimating the lengths-of-stay (LoS) of hospitalised COVID-19 patients is key for predicting the hospital beds’ demand and planning mitigation strategies, as overwhelming the healthcare systems has critical consequences for disease mortality. However, accurately mapping the time-to-event of hospital outcomes, such as the LoS in the intensive care unit (ICU), requires understanding patient trajectories while adjusting for covariates and observation bias, such as incomplete data. Standard methods, such as the Kaplan-Meier estimator, require prior assumptions that are untenable given current knowledge. Using real-time surveillance data from the first weeks of the COVID-19 epidemic in Galicia (Spain), we aimed to model the time-to-event and event probabilities of patients’ hospitalised, without parametric priors and adjusting for individual covariates. We applied a non-parametric mixture cure model and compared its performance in estimating hospital ward (HW)/ICU LoS to the performances of commonly used methods to estimate survival. We showed that the proposed model outperformed standard approaches, providing more accurate ICU and HW LoS estimates. Finally, we applied our model estimates to simulate COVID-19 hospital demand using a Monte Carlo algorithm. We provided evidence that adjusting for sex, generally overlooked in prediction models, together with age is key for accurately forecasting HW and ICU occupancy, as well as discharge or death outcomes.ALC was sponsored by the BEATRIZ GALINDO JUNIOR Spanish from MICINN (Ministerio de Ciencia, Innovación y Universidades) with reference BGP18/00154. ALC, MAJ and RC acknowledge partial support by the MINECO (Ministerio de Economía y Competitividad) Grant MTM2014-52876-R (EU ERDF support included) and the MICINN Grant MTM2017-82724-R (EU ERDF support included) and partial support of Xunta de Galicia (Centro Singular de Investigación de Galicia accreditation ED431G 2019/01 and Grupos de Referencia Competitiva ED431C-2020-14 and ED431C2016-015) and the European Union (European Regional Development Fund - ERDF). PMD is a current recipient of the Grant of Excellence for postdoctoral studies by the Ramón Areces FoundationXunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431C 2020/14Xunta de Galicia; ED431C 2016/01

Three-dimensional particle size and position measurement by linear complex amplitude Wiener filtering; 35473233

Digital in-line holography (DIH) combined with a Wiener filter has been applied to measure particle size and position in the flow inside a capillary model, seeded with magnetic particles (3µm) and with solid opaque particles that simulated red and white cells. The proposed filtering process takes advantage of the linearity implicit in the numerical reconstruction of the object complex amplitude. A modified DIH set-up, with a tilted illumination beam, was used as it presents two main advantages: it solves the twin image issue associated to in-line holography and increases the out-of-plane resolution. Experiments show that the proposed method discriminates particles within a range from 3 to 30µm with a sensitivity of 0.5µm. © 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreemen

Multilinear Wavelets: A Statistical Shape Space for Human Faces

We present a statistical model for $3$D human faces in varying expression, which decomposes the surface of the face using a wavelet transform, and learns many localized, decorrelated multilinear models on the resulting coefficients. Using this model we are able to reconstruct faces from noisy and occluded $3$D face scans, and facial motion sequences. Accurate reconstruction of face shape is important for applications such as tele-presence and gaming. The localized and multi-scale nature of our model allows for recovery of fine-scale detail while retaining robustness to severe noise and occlusion, and is computationally efficient and scalable. We validate these properties experimentally on challenging data in the form of static scans and motion sequences. We show that in comparison to a global multilinear model, our model better preserves fine detail and is computationally faster, while in comparison to a localized PCA model, our model better handles variation in expression, is faster, and allows us to fix identity parameters for a given subject.Comment: 10 pages, 7 figures; accepted to ECCV 201