A mean field game model for COVID-19 with human capital accumulation

In this manuscript, we study a model of human capital accumulation during the spread of disease following an agent-based approach, where agents behave maximising their intertemporal utility. We assume that the agent interaction is of mean field type, yielding a mean field game description of the problem. We discuss how the analysis of a model including both the mechanism of change of species from one epidemiological state to the other and an optimisation problem for each agent leads to an aggregate behaviour that is not easy to describe, and that sometimes exhibits structural issues. Therefore we eventually propose and study numerically a SEIRD model in which the rate of infection depends on the distribution of the population, given exogenously as the solution to the mean field game system arising as the macroscopic description of the discrete multi-agent economic model for the accumulation of human capital. Such a model arises in fact as a simplified but tractable version of the initial one

A simple planning problem for COVID-19 lockdown: a dynamic programming approach

A large number of recent studies consider a compartmental SIR model to study optimal control policies aimed at containing the diffusion of COVID-19 while minimizing the economic costs of preventive measures. Such problems are non-convex and standard results need not to hold. We use a Dynamic Programming approach and prove some continuity properties of the value function of the associated optimization problem. We study the corresponding Hamilton-Jacobi-Bellman equation and show that the value function solves it in the viscosity sense. Finally, we discuss some optimality conditions. Our paper represents a first contribution towards a complete analysis of non-convex dynamic optimization problems, within a Dynamic Programming approach

Data-driven extraction of uniformly stable and passive parameterized macromodels

A Robust algorithm for the extraction of reduced-order behavioral models from sampled frequency responses is proposed. The system under investigation can be any Linear and Time Invariant structure, although the main emphasis is on devices that are relevant for Signal and Power Integrity and RF design, such as electrical interconnects and integrated passive components. We assume that the device under modeling is parameterized by one or more design variables, which can be related to geometry or materials. Therefore, we seek for multivariate macromodels that reproduce the dynamic behavior over a predefined frequency band, with an explicit embedded dependence of the model equations on these external parameters. Such parameterized macromodels may be used to construct component libraries and prove very useful in fast system-level numerical simulations in time or frequency domain, including optimization, what-if, and sensitivity analysis. The main novel contribution is the formulation of a finite set of convex constraints that are applied during model identification, which provide sufficient conditions for uniform model stability and passivity throughout the parameter space. Such constraints are characterized by an explicit control allowing for a trade-off between model accuracy and runtime, thanks to some special properties of Bernstein polynomials. In summary, we solve the longstanding problem of multivariate stability and passivity enforcement in data-driven model order reduction, which insofar has been tackled only via either overconservative or heuristic and possibly unreliable methods

Structured black-box parameterized macromodels of integrated passive components

A novel black-box model representation and identification process is introduced, specifically designed to extract layout-scalable behavioral macromodels of passive integrated devices from sampled frequency-domain responses. An automated choice of structured frequency-domain basis functions enables extremely accurate approximations for responses characterized by high dynamic ranges over extended frequency bands, overcoming the main limitations of standard approaches. Numerical results confirm that the proposed structured approach provides robust and reliable scalable models, with guaranteed stability and passivity over the frequency band and parameter space of interest

Fast Simulation of Analog Circuit Blocks under Nonstationary Operating Conditions

This paper proposes a black-box behavioral modeling framework for analog circuit blocks operating under small-signal conditions around non-stationary operating points. Such variations may be induced either by changes in the loading conditions or by event-driven updates of the operating point for system performance optimization, e.g., to reduce power consumption. An extension of existing data-driven parameterized reduced-order modeling techniques is proposed that considers the time-varying bias components of the port signals as non-stationary parameters. These components are extracted at runtime by a lowpass filter and used to instantaneously update the matrices of the reduced-order state-space model realized as a SPICE netlist. Our main result is a formal proof of quadratic stability of such Linear Parameter Varying (LPV) models, enabled by imposing a specific model structure and representing the transfer function in a basis of positive functions whose elements constitute a partition of unity. The proposed quadratic stability conditions are easily enforced through a finite set of small-size Linear Matrix Inequalities (LMI), used as constraints during model construction. Numerical results on various circuit blocks including voltage regulators confirm that our approach not only ensures the model stability, but also provides speedup in runtime up to 2 orders of magnitude with respect to full transistor-level circuits

Densidade e caracterização morfológica de bactérias em sistemas de produção integrados e exclusivos.

Resumo: Os diferentes sistemas integrados de produção podem interferir diretamente na comunidade bacteriana presente nestes ambientes. Assim, o presente estudo teve como objetivo analisar a ocorrência e a diversidade bacteriana, e a influência dos períodos seco e chuvoso sistemas integrados e exclusivos de produção. Também foram avaliadas uma área de pousio e uma de mata nativa. As amostras foram coletadas em março e setembro de 2012. Os isolamentos foram realizados em placas de Petri com meio DYGS. Após 48h foram quantificadas as Unidades Formadoras de Colônias (UFC) e realizada caracterização fenotípica. A densidade de bactérias variou entre 106 e 107 UFC g-1 solo. O sistema de cultivo afetou a quantidade de UFC bacteriana apenas no período chuvoso, sendo que a maior quantidade observada na área com lavoura. Foi observado maior quantidade de UFC no período da chuva, independente do sistema de cultivo. A similaridade dos isolados, a 80%, promoveu a formação de 13 grupos durante a época de chuva e 14 no período seco. Isolados com capacidade de solubilizar fosfato in vitro foram obtidos de todas as áreas nas duas épocas avaliadas, embora esta característica tenha sido predominante nas bactérias isoladas no período chuvoso. | Abstract: The different integrated production systems can directly interfere with its bacterial community. The present study aimed to assess density, bacterial diversity and the influence of dry and rainy season in different integrated and an exclusive production system. The fallow and a native forest area was assessed to. Samples were collected in 2012 March and September. The isolation were carried out into Petri dishes containing DYGS medium. The number of colony forming units (CFU) was counted after 48 hours and. The bacterial density ranged between 106 and 107 CFU g-1 soil. The crop system affected the dynamics of the bacterial community only in the rainy season. The rainy season showed greater density of total bacteria when compared to the dry period regardless of the cropping system. The dendrograms with 80 % similarity showed thirteen and fourteen groups in the rainy and dry seasons. Isolates with the capacity to solubilize phosphate in vitro were obtained from all areas in the two seasons, but this feature has been prevalent in bacteria isolated during the rainy season.Título em inglês: Density and morphological characterization of bacteria in integrated and exclusive production system

Análise sorológica para alpha herpesvírus em rebanhos bubalinos do Estado de São Paulo. Resultados preliminares

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Spatio-temporal variability in underwater light climate in a turbid river-floodplain system. Driving factors and estimation using Secchi disc

The underwater light climate has important effects on primary producers. The aim of this research was to evaluate its variability in a turbid river-floodplain system. Photosynthetically active radiation (PAR) was measured in the Middle Paraná River during different hydrological phases to (a) analyse the photosynthetically active radiation attenuation coefficient (k) and euphotic depth (Zeu) as well as their associations with optically active components and (b) develop and evaluate indices and regression models based on Secchi disc (SD) measurements to estimate k and Zeu. Values of k were higher in the fluvial system than in the floodplain and during low-water stage than high-water stage. Particulate components controlled the light climate variability. Chromophoric dissolved organic matter and chlorophyll-a had significant effects during floods. The estimation of k and Zeu was sensitive to temporal but not to spatial variations. The highest prediction accuracy was observed when using specific non-linear regressions for each hydrological phase, especially for Zeu estimation (low stage: k = 1.76 × SD−0.80, Zeu = 2.62 × 1/SD−0.80; high stage: k = 2.04 × SD−0.53, Zeu = 2.26 × 1/SD−0.53). The indices k × SD and Zeu/SD were significantly different from those proposed for clear water environments. It is concluded that temporal variations should be considered when estimating k and Zeu in turbid river-floodplain systems because of the temporal heterogeneity in optically active components. Considering that ecological implication of the light climate depends on Zeu:depth ratio, we propose to estimate Zeu instead of k. Finally, indices proposed for clear water environments are not recommended to be applied to turbid environments.Fil: Mayora, Gisela Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; ArgentinaFil: Devercelli, Melina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; Argentin