Incompetence and impact of training in bimatrix games

The concept of games with incompetence has been introduced to better represent games where players may not be capable of executing strategies that they select. In particular this paper introduces incompetence into bimatrix games and investigates the properties of such games. The results obtained describe both the general dependence of “extreme Nash equilibrium payoffs” on incompetence and special behaviour arising in particular cases. The dependence of the payoffs can be complex and include non-linearities and transition points. Transition points occur when kernels change and may result in the number of “extreme Nash equilibria” changing. Understanding these changes allows the determination of the benefits of regimes that seek to decrease a player’s incompetence. While the games we consider are normally static, in our context there is a hidden dynamics resulting from the fact that players will strive to improve their equilibrium payoffs by changing their incompetence levels. This might require training, in the case of games like tennis, or it might require the purchase of new equipment costing billions of dollars, in the case of military applications.     

Thermal explosion in a hot gas mixture with organic gel fuel droplets

Recent experimental evidence has uncovered the peculiar behavior of certain gel droplets which, under appropriate ambient thermal conditions, evaporate and burn in an oscillatory fashion. In this work a preliminary foray is made into the theoretical analysis of the nature of the evolution of a hot gas mixture containing organic gel fuel droplets with oscillatory evaporation within the context of thermal-explosion theory. The problem is modeled as a system of highly nonlinear singularly perturbed ordinary differential equations. Non-dimensionalization of the equations enables identification of the parameters that play a major role in determining the dynamical regimes of the system of equations. The method of integral manifolds is exploited for the analysis and it is found, that for certain parametric regions, the system exhibits new dynamical behavior that is quite different from that found for conventional liquid droplets.     

An advanced numerical method for computing elastodynamic fracture parameters in functionally graded materials

A new meshless method for computing the dynamic stress intensity factors (SIFs) in continuously non-homogeneous solids under a transient dynamic load is presented. The method is based on the local boundary integral equation (LBIE) formulation and the moving least squares (MLS) approximation. The analyzed domain is divided into small subdomains, in which a weak solution is assumed to exist. Nodal points are randomly spread in the analyzed domain and each one is surrounded by a circle centered at the collocation point. The boundary-domain integral formulation with elastostatic fundamental solutions for homogeneous solids in Laplace-transformed domain is used to obtain the weak solution for subdomains. On the boundary of the subdomains, both the displacement and the traction vectors are unknown generally. If modified elastostatic fundamental solutions vanishing on the boundary of the subdomain are employed, the traction vector is eliminated from the local boundary integral equations for all interior nodal points. The spatial variation of the displacements is approximated by the MLS scheme.     

Assessment of oxygen levels in convenience‐style muscle‐based sous vide products through optical means and impact on shelf‐life stability

An optical oxygen analyser was used in two small‐scale industrial trials to non‐destructively assess the quality of packaged convenience foods and packaging process. Beef lasagne packed under 70% vacuum and cooked under standard sous vide conditions was monitored for residual oxygen, using disposable sensors incorporated in each pack and a benchtop optical oxygen analyser. High levels of residual oxygen close to ambient were determined in the majority of packs after packaging, as opposed to anticipated levels of 4–5%. Residual oxygen was monitored over product shelf‐life (4 weeks at +4–10°C) along with measurement of microbial growth and lipid oxidation in food by conventional destructive methods. Oxygen levels in packs went down to almost zero between weeks 2 and 3 indicating deterioration of packaged product. Correlation between oxygen profiles and the rate of microbial growth and lipid oxidation was established. The optical oxygen sensor system was shown to provide valuable information about performance of the packaging process, product storage conditions and food quality in a convenient and cost‐efficient fashion and non‐destructively. Copyright © 2004 John Wiley & Sons, Ltd.     

Velocity Distribution in the Roughness Layer of Rough-Bed Flows

Several models for the vertical distribution of the double-averaged (in time and in the plane parallel to the mean bed) longitudinal velocity in the flow region between roughness troughs and roughness tops are suggested. We found that the same model for velocity distribution may be applicable to a range of flow conditions and roughness types, which share some common features. The suggested models for velocity distribution in the near-bed region are: (1) Constant velocity; (2) exponential velocity distribution; and (3) linear velocity distribution. The measured velocity distributions may be approximated by a single model or by a combination of models depending on roughness geometry and flow conditions. The validity of these models for velocity distribution is supported by laboratory data.     

Human-Robot Interaction Through Gesture-Free Spoken Dialogue

We present an approach to human-robot interaction through gesture-free spoken dialogue. Our approach is based on passive knowledge rarefication through goal disambiguation, a technique that allows a human operator to collaborate with a mobile robot on various tasks through spoken dialogue without making bodily gestures. A key assumption underlying our approach is that the operator and the robot share a common set of goals. Another key idea is that language, vision, and action share common memory structures.We discuss how our approach achieves four types of human-robot interaction: command, goal disambiguation, introspection, and instruction-based learning. We describe the system we developed to implement our approach and present experimental results.     

A fast compound algorithm for mining generators,closed itemsets,and computing links between equivalence classes

In pattern mining and association rule mining, there is a variety of algorithms for mining frequent closed itemsets (FCIs) and frequent generators (FGs), whereas a smaller part further involves the precedence relation between FCIs. The interplay of these three constructs and their joint computation have been studied within the formal concept analysis (FCA) field yet none of the proposed algorithms is scalable. In frequent pattern mining, at least one suite of efficient algorithms has been designed that exploits basically the same ideas and follows the same overall computational schema. Based on an in-depth analysis of the aforementioned interplay that is rooted in a fundamental duality from hypergraph theory, we propose a new schema that should enable for a more parsimonious computation. We exemplify the new schema in the design of Snow-Touch, a concrete FCI/FG/precedence miner that reuses an existing algorithm, Charm, for mining FCIs, and completes it with two original methods for mining FGs and precedence, respectively. The performance of Snow-Touch and of its closest competitor, Charm-L, were experimentally compared using a large variety of datasets. The outcome of the experimental study suggests that our method outperforms Charm-L on dense data while on sparse one the trend is reversed. Furthermore, we demonstrate the usefulness of our method and the new schema through an application to the analysis of a genome dataset. The initial results reported here confirm the capacity of the method to focus on significant associations.     

Protein Misfolding and Aggregation in the Brain: Common Pathogenetic Pathways in Neurodegenerative and Mental Disorders

Mental disorders represent common brain diseases characterized by substantial impairments of social and cognitive functions. The neurobiological causes and mechanisms of psychopathologies still have not been definitively determined. Various forms of brain proteinopathies, which include a disruption of protein conformations and the formation of protein aggregates in brain tissues, may be a possible cause behind the development of psychiatric disorders. Proteinopathies are known to be the main cause of neurodegeneration, but much less attention is given to the role of protein impairments in psychiatric disorders’ pathogenesis, such as depression and schizophrenia. For this reason, the aim of this review was to discuss the potential contribution of protein illnesses in the development of psychopathologies. The first part of the review describes the possible mechanisms of disruption to protein folding and aggregation in the cell: endoplasmic reticulum stress, dysfunction of chaperone proteins, altered mitochondrial function, and impaired autophagy processes. The second part of the review addresses the known proteins whose aggregation in brain tissue has been observed in psychiatric disorders (amyloid, tau protein, α-synuclein, DISC-1, disbindin-1, CRMP1, SNAP25, TRIOBP, NPAS3, GluA1, FABP, and ankyrin-G).