Fodor and Pylyshyn on connectionism

Fodor and Pylyshyn (1988) have argued that the cognitive architecture is not Connectionist. Their argument takes the following form: (1) the cognitive architecture is Classical; (2) Classicalism and Connectionism are incompatible; (3) therefore the cognitive architecture is not Connectionist. In this essay I argue that Fodor and Pylyshyn's defenses of (1) and (2) are inadequate. Their argument for (1), based on their claim that Classicalism best explains the systematicity of cognitive capacities, is an invalid instance of inference to the best explanation. And their argument for (2) turns out to be question-begging. The upshot is that, while Fodor and Pylyshyn have presented Connectionists with the important empirical challenge of explaining systematicity, they have failed to provide sufficient reason for inferring that the cognitive architecture is Classical and not Connectionist.     

Foley catheters functionalised with a synergistic combination of antibiotics and silver nanoparticles resist biofilm formation

Foley catheters are inevitable in health care unit. Pathogens colonise and form biofilm on catheter causing catheter‐associated urinary tract infection. Therefore, the authors aimed to functionalise catheter to resist biofilm formation. The authors impregnated urinary catheters with a synergistic combination of antibiotics and silver nanoparticles (SNPs) to evaluate antibiofilm efficacy in vitro and in vivo. SNPs were synthesised using Spirulina platensis. Synergy between the SNPs and antibiotics was determined by the checker‐board method. In vivo efficacy of the functionalised catheters was assessed in mice. Liver and kidney function tests of mice were performed. The in vitro anti‐adherence activity of the functionalised catheters was evaluated after 2 years. Nanoparticle sizes were 42–75 nm. Synergistic activity was observed among SNPs (2 µg/ml), amikacin (6.25 µg/ml), and nitrofurantoin (31.25 µg/ml). In mice, catheters functionalised with combinations of antibiotics and SNPs exhibited no colonisation until Day 14. Blood, liver, and kidney tests were normal. After 2 years, catheters functionalised with antibiotics exhibited 25% inhibition of bacterial adhesion, and catheters functionalised with the nanoparticle‐antibiotic combination exhibited 90% inhibition. Impregnation of urinary catheters with a synergistic combination of antibiotics and SNPs is an efficient and promising method for preventing biofilm formation.Inspec keywords: catheters, drugs, silver, nanoparticles, nanomedicine, liver, kidney, blood, microorganisms, adhesion, biomechanics, cellular biophysicsOther keywords: Foley catheters, synergistic nanoparticle‐antibiotics combination, silver nanoparticles, biofilm formation resitance, health care unit, pathogens, urinary tract infection, SNP, Spirulina platensis, checker‐board method, liver function, kidney function, vitro antiadherence activity, amikacin, nitrofurantoin, blood, bacterial adhesion, size 42 nm to 75 nm, Ag     

A new method preserving the positive definiteness of a second order tensor variable in flow simulations with application to viscoelastic turbulence

We present a new numerical method for the simulation of the flow of complex fluids with internal microstructure that is described by a second order, positive definite, internal structural parameter, so that its positive definiteness is preserved in the simulations. An example of such an internal structural parameter is the conformation tensor, used in the modeling of viscoelastic flows, which characterizes the flow-induced molecular deformation. Numerical methods that guarantee the preservation of the positive definiteness of the conformation tensor help both the physical interpretation of the results and the numerical stability of the simulations. The new method presented here is based on the log-conformation representation of a second order tensor. It is implemented through the application of the Cayley-Hamilton theorem for second order tensors. When necessary, we also use an additional mapping that ensures the boundness of the conformation tensor. This approach has been applied in Direct Numerical Simulations (DNS) of viscoelastic turbulent channel flow, which has received great attention since the mid 1990s with ultimate goal to understand the phenomenon of maximum drag reduction. The algorithm uses a full 3D spectral representation of the spatial dependence for the flow and conformation variables and a second order accurate backward differentiation formula for the integration of the governing equations in time. The key issue for the successful implementation of the proposed scheme is a second order finite difference multigrid diffusion applied to the conformation field. Numerical diffusion has been always added to the hyperbolic evolution equations for the conformation tensor in spectral DNS of viscoelastic turbulent flows in order to remove a-physical high wavenumber instabilities induced due to the chaotic nature of the flow. The main advantage of the finite-difference implementation (as opposed to a spectral implementation as done before) is that it allows for the preservation of the positive definiteness of the conformation tensor.     

PLISS: labeling places using online changepoint detection

A shared vocabulary between humans and robots for describing spatial concepts is essential for effective human robot interaction. Towards this goal, we present a novel technique for place categorization from visual cues called PLISS (Place Labeling through Image Sequence Segmentation). PLISS is different from existing place categorization systems in two major ways—it inherently works on video and image streams rather than single images, and it can detect “unknown” place labels, i.e. place categories that it does not know about. PLISS uses changepoint detection to temporally segment image sequences which are subsequently labeled. Changepoint detection and labeling are performed inside a systematic probabilistic framework. Unknown place labels are detected by using a probabilistic classifier and keeping track of its label uncertainty. We present experiments and comparisons on the large and extensive VPC dataset. We also demonstrate results using models learned from images downloaded from Google’s image search.     

A genetic algorithm for solving the fixed-charge transportation model: Two-stage problem

Transportation of goods in a supply chain from plants to customers through distribution centers (DCs) is modeled as a two-stage distribution problem in the literature. In this paper we propose genetic algorithms to solve a two-stage transportation problem with two different scenarios. The first scenario considers the per-unit transportation cost and the fixed cost associated with a route, coupled with unlimited capacity at every DC. The second scenario considers the opening cost of a distribution center, per-unit transportation cost from a given plant to a given DC and the per-unit transportation cost from the DC to a customer. Subsequently, an attempt is made to represent the two-stage fixed-charge transportation problem (Scenario-1) as a single-stage fixed-charge transportation problem and solve the resulting problem using our genetic algorithm. Many benchmark problem instances are solved using the proposed genetic algorithms and performances of these algorithms are compared with the respective best existing algorithms for the two scenarios. The results from computational experiments show that the proposed algorithms yield better solutions than the respective best existing algorithms for the two scenarios under consideration.     

The Impact of Infostation Density on Vehicular Data Dissemination

Vehicle-to-Vehicle and Vehicle-to-Roadside communications are going to become an indispensable part of the modern day automotive experience. For people on the move, vehicular networks can provide critical network connectivity and access to real-time information. Infostations play a vital role in these networks by acting as gateways to the Internet and by extending network connectivity. In this context, an important question is “What is the minimum number of infostations that need to be deployed in an area in order to support vehicular applications?” Optimizing infostation density is vital to understanding and reducing the cost of deployment and management. In this paper, we examine the required infostation density in a highway scenario using different data dissemination models. We start from a simple analysis that captures the required density under idealized assumptions. These models are validated by an event-driven simulator. We then run detailed QualNet simulations on both controlled and realistic vehicular traces to observe the information density trends in practical environments, and consequently propose techniques to improve dissemination performance and reduce the required infostation density.     

Tensile and Fracture Properties of Aluminium Alloy AA2219-T87 Friction Stir Weld Joints for Aerospace Applications

Metallurgical and Materials Transactions A - The purpose of the present work is to study the mechanical behaviour of AA2219-T87 friction stir weld (FSW) joints at different temperatures (Room...