Ignorance is not always Bliss: Feedback and Dynamics in Public Good Experiments

In this paper we study the effects of providing additional feedback about individual contributions and earnings on the dynamics of contributions in a repeated public good game. We include treatments where subjects can freely choose whether to obtain additional information about individual contributions or individual earnings. We find that, in the aggregate, contributions decline less fast when additional information about contributions and earnings is provided on top of aggregate information. We also find that there exist substantial but intuitively appealing differences in the way individuals react to feedback. Particularly, individuals with a high propensity to contribute tend to imitate the highest contributor more often and are more inclined to obtain feedback about individual contributions than about individual earnings than individuals with a lower propensity to contribute.voluntary contributions;experiment;repeated interaction;feedback;imitation

Implicit yield function formulation for granular and rock-like materials

The constitutive modelling of granular, porous and quasi-brittle materials is based on yield (or damage) functions, which may exhibit features (for instance, lack of convexity, or branches where the values go to infinity, or false elastic domains) preventing the use of efficient return-mapping integration schemes. This problem is solved by proposing a general construction strategy to define an implicitly defined convex yield function starting from any convex yield surface. Based on this implicit definition of the yield function, a return-mapping integration scheme is implemented and tested for elastic-plastic (or -damaging) rate equations. The scheme is general and, although it introduces a numerical cost when compared to situations where the scheme is not needed, is demonstrated to perform correctly and accurately.Comment: 19 page

Adaptive WENO methods based on radial basis functions reconstruction

We explore the use of radial basis functions (RBF) in the weighted essentially non-oscillatory (WENO) reconstruction process used to solve hyperbolic conservation laws, resulting in a numerical method of arbitrarily high order to solve problems with discontinuous solutions. Thanks to the mesh-less property of the RBFs, the method is suitable for non uniform grids and mesh adaptation. We focus on multiquadric radial basis functions and propose a simple strategy to choose the inherent shape parameter to control the balance between theoretical achievable accuracy and the numerical stability. We also develop an original smoothness indicator independent of the chosen RBF for the WENO reconstruction step. Moreover, we introduce type I and type II RBF-WENO methods by computing specific linear weights. The RBF-WENO method is used to solve linear and nonlinear problems for both scalar conservation laws and systems of conservation laws, including Burgers equation, the Buckley-Leverett equation, and the Euler equations. Numerical results confirm the performance of the proposed method. We finally consider an effective conservative adaptive algorithm that captures moving shocks and rapidly varying solutions well. Numerical results on moving grids are presented for both Burgers equation and the more complex Euler equations

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

We propose a simulation-based decision strategy for the proactive maintenance of complex structures with a particular application to structural health monitoring (SHM). The strategy is based on a data-driven approach which exploits an offine-online decomposition. A synthetic dataset is constructed offine by solving a parametric time-dependent partial differential equation for multiple input parameters, sampled from their probability distributions of natural variation. The collected time-signals, extracted at sensor locations, are used to train classiffiers at such sensor locations, thus constructing multiple databases of healthy configurations. These datasets are then used to train one class Support Vector Machines (OC-SVMs) to detect anomalies. During the online stage, a new measurement, possibly obtained from a damaged configuration, is evaluated using the classiffiers. Information on damage is provided in a hierarchical manner: first, using a binary feedback, the entire structure response is either classifiied as inlier (healthy) or outlier (damaged). Then, for the outliers, we exploit the outputs of multiple classiffiers to retrieve information both on the severity and the spatial location of the damages. Because of the large number of signals needed to construct the datasets offline, a model order reduction strategy is implemented to reduce the computational burden. We apply this strategy to both 2D and 3D problems to mimic the vibrational behavior of complex structures under the effect of an active source and show the effectiveness of the approach for detecting and localizing cracks

Osteochondritis dissecans of the knee: Epidemiology, etiology, and natural history.

Osteochondritis dissecans of the knee is a disease that typically affects skeletally immature patients. Clinically manifested with knee pain, limping, and joint disfunction, this condition has remained misunderstood and undervalued for a long period. Although being a rare condition, its awareness is of utmost clinical interest because of the possible severe consequences it can bring when misrecognized or inadequately treated. Its etiology remains unclear and is still debated. Many theories have been proposed, including inflammation, local ischemia, subchondral ossification abnormalities, genetic factors, and repetitive mechanical microtrauma, with a likely interplay of the same. This review article aims to deliver and discuss current and up-to-date concepts on epidemiology, etiology, and natural history of this pediatric condition. Level of evidence: level V