Magnetic Nernst effect

The thermodynamics of irreversible processes in continuous media predicts the existence of a Magnetic Nernst effect that results from a magnetic analog to the Seebeck effect in a ferromagnet and magnetophoresis occurring in a paramagnetic electrode in contact with the ferromagnet. Thus, a voltage that has DC and AC components is expected across a Pt electrode as a response to the inhomogeneous magnetic induction field generated by magnetostatic waves of an adjacent YIG slab subject to a temperature gradient. The voltage frequency and dependence on the orientation of the applied magnetic induction field are quite distinct from that of spin pumping.Comment: 4 pages, 1 figur

Should central banks lean against changes in asset prices?

How should monetary policy be conducted in the presence of endogenous feedback loops between asset prices, firms’ financial health, and economic activity? We reconsider this question in the context of the financial accelerator model and show that, when the level of natural output is inefficient, the optimal monetary policy under commitment leans considerably against movements in asset prices and risk premia. We demonstrate that an endogenous feedback loop is crucial for this result and that price stability is otherwise quasi-optimal absent this feature. We also show that the optimal policy can be closely approximated and implemented using a speed-limit rule that places a substantial weight on the growth of financial variables.Monetary policy ; Asset pricing

Motion Planning of Legged Robots

We study the problem of computing the free space F of a simple legged robot called the spider robot. The body of this robot is a single point and the legs are attached to the body. The robot is subject to two constraints: each leg has a maximal extension R (accessibility constraint) and the body of the robot must lie above the convex hull of its feet (stability constraint). Moreover, the robot can only put its feet on some regions, called the foothold regions. The free space F is the set of positions of the body of the robot such that there exists a set of accessible footholds for which the robot is stable. We present an efficient algorithm that computes F in O(n2 log n) time using O(n2 alpha(n)) space for n discrete point footholds where alpha(n) is an extremely slowly growing function (alpha(n) <= 3 for any practical value of n). We also present an algorithm for computing F when the foothold regions are pairwise disjoint polygons with n edges in total. This algorithm computes F in O(n2 alpha8(n) log n) time using O(n2 alpha8(n)) space (alpha8(n) is also an extremely slowly growing function). These results are close to optimal since Omega(n2) is a lower bound for the size of F.Comment: 29 pages, 22 figures, prelininar results presented at WAFR94 and IEEE Robotics & Automation 9

Fast Damage Recovery in Robotics with the T-Resilience Algorithm

Damage recovery is critical for autonomous robots that need to operate for a long time without assistance. Most current methods are complex and costly because they require anticipating each potential damage in order to have a contingency plan ready. As an alternative, we introduce the T-resilience algorithm, a new algorithm that allows robots to quickly and autonomously discover compensatory behaviors in unanticipated situations. This algorithm equips the robot with a self-model and discovers new behaviors by learning to avoid those that perform differently in the self-model and in reality. Our algorithm thus does not identify the damaged parts but it implicitly searches for efficient behaviors that do not use them. We evaluate the T-Resilience algorithm on a hexapod robot that needs to adapt to leg removal, broken legs and motor failures; we compare it to stochastic local search, policy gradient and the self-modeling algorithm proposed by Bongard et al. The behavior of the robot is assessed on-board thanks to a RGB-D sensor and a SLAM algorithm. Using only 25 tests on the robot and an overall running time of 20 minutes, T-Resilience consistently leads to substantially better results than the other approaches

Evidence for postseismic deformation of the lower crust following the 2004 Mw6.0 Parkfield earthquake

Previous studies have shown that postseismic relaxation following the 2004 Mw6.0 Parkfield, CA, earthquake is dominated by afterslip. However, we show that some fraction of the afterslip inferred from kinematic inversion to have occurred immediately below the seismically ruptured area may in fact be a substitute for viscous postseismic deformation of the lower crust. Using continuous GPS and synthetic aperture radar interferometry, we estimate the relative contribution of shallow afterslip (at depth less than 20km) and deeper seated deformation required to account for observed postseismic surface displacements. Exploiting the possible separation in space and time of the time series of displacements predicted from viscoelastic relaxation, we devise a linear inversion scheme that allows inverting jointly for the contribution of afterslip and viscoelastic flow as a function of time. We find that a wide range of models involving variable amounts of viscoelastic deformation can fit the observations equally well provided that they allow some fraction of deep-seated deformation (at depth larger than ∼20 km). These models require that the moment released by postseismic relaxation over 5 years following the earthquake reached nearly as much as 200% of the coseismic moment. All the models show a remarkable complementarity of coseismic and shallow afterslip distributions. Some significant deformation at lower crustal depth (20–26 km) is required to fit the geodetic data. The condition that postseismic deformation cannot exceed complete relaxation places a constraint on the amount of deep seated deformation. The analysis requires an effective viscosity of at least ~10^(18) Pa s of the lower crust (assuming a semi-infinite homogeneous viscous domain). This deep-seated deformation is consistent with the depth range of tremors which also show a transient postseismic response and could explain as much as 50% of the total postseismic geodetic moment (the remaining fraction being due to afterslip at depth shallower than 20 km). Lower crustal postseismic deformation could reflect a combination of localized ductile deformation and aseismic frictional sliding

Towards Zero-Waste Furniture Design

In traditional design, shapes are first conceived, and then fabricated. While this decoupling simplifies the design process, it can result in inefficient material usage, especially where off-cut pieces are hard to reuse. The designer, in absence of explicit feedback on material usage remains helpless to effectively adapt the design -- even though design variabilities exist. In this paper, we investigate {\em waste minimizing furniture design} wherein based on the current design, the user is presented with design variations that result in more effective usage of materials. Technically, we dynamically analyze material space layout to determine {\em which} parts to change and {\em how}, while maintaining original design intent specified in the form of design constraints. We evaluate the approach on simple and complex furniture design scenarios, and demonstrate effective material usage that is difficult, if not impossible, to achieve without computational support

Assessing the role of the research in the transition to organic farming by using the Actor Network Theory: lessons from two case studies in France and Bulgaria

This paper explores the potential of Actor Network Theory (ANT) in understanding how the process of interaction and translation between human and non-human actors contribute to the development, adoption and diffusion of science-based innovations linked to the transition to organic farming. The study relies on two case studies, the French Camargue case covering a range of technical and social innovations, and the case from Bulgaria focusing on the development of a technical and product innovation, i.e. a veterinary product for organic beekeeping. The paper shows the limitations of classical approaches in studying innovations since they underestimate the role of heterogeneous actors, their status, and how they interact with each other. We argue that focusing on actors’ interactions helps to better understand the so-called “uncertainties” and “turning points” in the innovation development, as well as to interpret them as natural elements. Moreover we argue that challenges to tackle should be problematized to increase the success of research programs. We also stress the importance of opinion leaders during the implementation and diffusion phase of the innovation

Assessing Investment in Precision Farming for Reducing Pesticide Use in French Viticulture

The paper develops a mathematical programming model for assessing the impact of Environmental Policy instruments on French winegrowing farm’s adoption of pesticides-saving technologies. We model choices with regards to investment in precision farming and plant protection practices, in a multi-periodic framework with sequential decision, integrating uncertainty on fungal disease pressure and imperfect information on equipment performance. We focus on recursive models maximizing a Utility function. These models are applied on a representative sample of 534 winegrowers from the French Farm Accountancy Data Network (FADN). As expected, both ecotaxes and green subsidies make precision farming equipment more profitable, but the investment rate remains however low and concentrated on basic systems. One explanation is grower’s financial constraint in a context of market crisis and farm indebtedness. Shortcomings and further development of the models are discussed.Discrete Stochastic Programming, Precision Farming, Viticulture, Pesticides, Environmental Policy, Crop Production/Industries, Farm Management,