The Takayama and Judge Price and Allocation Models and its application in non-linear Price Transmission Analysis Approaches

Demand and Price Analysis, Research Methods/ Statistical Methods, C15, C18, C62,

The Takayama and Judge Price and Allocation Model and its Application in Non-linear Techniques for Spatial Market Integration

The Takayama and Judge Allocation models serve as the theoretical foundation for spatial market integration analysis, and despite the large number of papers devoted to the topic, still the knowledge and understanding of the economic phenomena is fragile. By generating artificial economic data under an economic framework, it is expected to contribute to a better understanding of the topic and revise if the current econometric (threshold vector error correction models) techniques are suitable for the analysis or not. Following the static and equilibrium nature of the Takayama and Judge models, it was possible to introduce dynamics and disequilibrium in the model to generate artificial data: prices. Such artificial prices were used to get a first insight on how to address further research.International Relations/Trade, Marketing,

Socioeconomic Factors and Its Influence in Vertical Price Transmission: The Case of the Mexican Tortilla Industry

The present document provides evidence of how prices along the Mexican Tortilla Industry are related and co-integrated, furthermore it attempts to derive a formal relationship between market integration and socioeconomic variables that affects transaction costs and therefore price transmission. Although not conclusive, it sets the ground for further steps on achieving such objective by implementing more advanced techniques.maize tortilla industry, vertical price transmission, socioeconomic variables., Agribusiness, Agricultural and Food Policy, Community/Rural/Urban Development, Food Consumption/Nutrition/Food Safety, Labor and Human Capital,

O problema do ethos da escrita de si em Montaigne e em Petrarca: do ensaio à epístola

Montaigne insists throughout the course of the Essays on his disdain for rhetoric. But as we try to expose here, his natural form includes itself to a large extent in the terms of rhetoric itself, under a particular usage of the precepts and conventions traditionally appropriate to the discourse in first person, especially those which regulated the sermo familiaris, genre recuperated for the first time in the Renaissance by Petrarch. We retake, in order to develop it, the fruitful intuition of Hugo Friedrich in his classical work about Montaigne's Essays, indicating its kinship with Petrarch's epistolary form, without, however, following him when he moves the essay away from the familiar epistle by interpreting the essay as a rupture with the rhetorical procedures and therefore with all the artistically worked prose of humanism.Montaigne insiste ao longo dos Ensaios em seu desprezo pela retórica. Mas como procuraremos mostrar aqui, sua forma natural inscreve-se em grande medida dentro dos termos da própria retórica, sob uma mobilização particular dos preceitos e convenções tradicionalmente apropriados à escrita em primeira pessoa, especialmente aqueles que regulavam o sermo familiaris, gênero recuperado pela primeira vez na Renascença por Petrarca. Retomamos assim, para desenvolvê-la, a fecunda intuição de Hugo Friedrich que, em sua clássica obra sobre os Ensaios de Montaigne, aponta o seu parentesco com a forma epistolar de Petrarca, sem, porém, acompanhá-lo quando distancia o ensaio da epístola familiar, por entendê-lo como marco de ruptura com os procedimentos da retórica e, assim, com toda a prosa artisticamente trabalhada do humanismo.Universidade Federal de São Paulo (UNIFESP) Departamento de FilosofiaUNIFESP, Depto. de FilosofiaSciEL

Artificial Neural Network-Based Flight Control Using Distributed Sensors on Fixed-Wing Unmanned Aerial Vehicles

Conventional control systems for autonomous aircraft use a small number of precise sensors in combination with classical control laws to maintain flight. The sensing systems encode center of mass motion and generally are set-up for flight regimes where rigid body assumptions and linear flight dynamics models are valid. Gain scheduling is used to overcome some of the limitations from these assumptions, taking advantage of well-tuned controllers over a range of design points. In contrast, flying animals achieve efficient and robust flight control by taking advantage of highly non-linear structural dynamics and aerodynamics. It has been suggested that the distributed arrays of flow and force sensors found in flying animals could be behind their remarkable flight control. Using a wind tunnel aircraft model instrumented with distributed arrays of load and flow sensors, we developed Artificial Neural Network flight control algorithms that use signals from the sensing array as well as the signals available in conventional sensing suites to control angle-of-attack. These controllers were trained to match the response from a conventional controller, achieving a level of performance similar to the conventional controller over a wide range of angle-of-attack and wind speed values. Wind tunnel testing showed that by using an ANN-based controller in combination with signals from a distributed array of pressure and strain sensors on a wing, it was possible to control angle-of-attack. The End-to-End learning approach used here was able to control angle-of-attack by directly learning the mapping between control inputs and system outputs without explicitly estimating or being given the angle-of-attack.</p

Physical measures for mostly sectional expanding flows

We prove that a partially hyperbolic attracting set for a $C^2$ vector field supports an ergodic physical/SRB measure if, and only if, the trapping region admits non-uniform sectional expansion on a positive Lebesgue measure subset. Moreover, in this case, the attracting set supports at most finitely many ergodic physical/SRB measures, which are also Gibbs states along the central-unstable direction. This extends to continuous time systems a similar well-known result obtained for diffeomorphisms, encompassing the presence of equilibria accumulated by regular orbits within the attracting set, since it is shown that slow recurrence to hyperbolic saddle-type equilibria is automatic for Lebesgue almost every point. We present several examples of application, including the existence of physical measures for asymptotically sectional hyperbolic attracting sets.Comment: 50 pages, 9 figures; improved presentation, shortened title, included (counter-)examples, improved results showing that slow recurrence to saddle-type hyperbolic equilibria is automatic thus dropping a crucial sufficient condition from the main theorem

Aerodynamic State and Loads Estimation Using Bio-Inspired Distributed Sensing

Flying animals exploit highly nonlinear dynamics to achieve efficient and robust flight control. It appears that the distributed flow and force sensor arrays found in flying animals are instrumental in enabling this performance. Using a wind-tunnel wing model instrumented with distributed arrays of strain and pressure sensors, we characterized the relationship between the distributed sensor signals and aerodynamic and load-related variables. Estimation approaches based on nonlinear artificial neural networks (ANNs) and linear partial least squares were tested with different combinations of sensor signals. The ANN estimators were accurate and robust, giving good estimates for all variables, even in the stall region when the distributed array pressure and strain signals became unsteady. The linear estimator performed well for load estimates but was less accurate for aerodynamic variables such as angle of attack and airspeed. Future applications based on distributed sensing could include enhanced flight control systems that directly use measurements of aerodynamic states and loads, allowing for increase maneuverability and improved control of unmanned aerial vehicles with high degrees of freedom such as highly flexible or morphing wings.</p

Reinforcement Learning to Control Lift Coefficient Using Distributed Sensors on a Wind Tunnel Model

Arrays of sensors distributed on the wing of fixed-wing vehicles can provide information not directly available to conventional sensor suites. These arrays of sensors have the potential to improve flight control and overall flight performance of small fixed-wing uninhabited aerial vehicles (UAVs). This work investigated the feasibility of estimating and controlling aerodynamic coefficients using the experimental readings of distributed pressure and strain sensors across a wing. The study was performed on a one degree-of-freedom model about pitch of a fixed-wing platform instrumented with the distributed sensing system. A series of reinforcement learning (RL) agents were trained in simulation for lift coefficient control, then validated in wind tunnel experiments. The performance of RL-based controllers with different sets of inputs in the observation space were compared with each other and with that of a manually tuned PID controller. Results showed that hybrid RL agents that used both distributed sensing data and conventional sensors performed best across the different tests.</p

Unmanned aerial vehicle control costs mirror bird behaviour when soaring close to buildings

Small unmanned aerial vehicles (SUAVs) are suitable for many low-altitude operations in urban environments due to their manoeuvrability; however, their flight performance is limited by their on-board energy storage and their ability to cope with high levels of turbulence. Birds exploit the atmospheric boundary layer in urban environments, reducing their energetic flight costs by using orographic lift generated by buildings. This behaviour could be mimicked by fixed-wing SUAVs to overcome their energy limitations if flight control can be maintained in the increased turbulence present in these conditions. Here, the control effort required and energetic benefits for a SUAV flying parallel to buildings whilst using orographic lift was investigated. A flight dynamics and control model was developed for a powered SUAV and used to simulate flight control performance in different turbulent wind conditions. It was found that the control effort required decreased with increasing altitude and that the mean throttle required increased with greater radial distance to the buildings. However, the simulations showed that flying close to the buildings in strong wind speeds increased the risk of collision. Overall, the results suggested that a strategy of flying directly over the front corner of the buildings appears to minimise the control effort required for a given level of orographic lift, a strategy that mirrors the behaviour of gulls in high wind speeds