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.     

LSB Dithering in MASH Delta–Sigma D/A Converters

Theoretical sufficient conditions are presented that ensure that the quantization noise from every constituent digital delta-sigma (DeltaSigma) modulator in a multistage digital DeltaSigma modulator is asymptotically white and uncorrelated with the input. The conditions also determine if spectral shape can be imparted to the dither's contribution to the power spectral density of the multistage digital DeltaSigma modulator's output. A large class of popular multistage digital DeltaSigma modulators that satisfy the conditions are identified and tabulated for easy reference     

Corrosion of 2205 duplex stainless steel in chloride medium containing sulfate-reducing bacteria

Sulfate-reducing bacteria (SRB) play significant role in the corrosion of stainless steels exposed to marine and soil environment. Sulfate reduction by bacterial species results in the production of H₂S, which can significantly influence the anodic and cathodic processes and ultimately enhances the corrosion of materials. In the present study, 2205 type duplex stainless steel (DSS) coupons in solution-annealed condition were exposed to chloride medium containing SRB species, Desulfovibrio desulfuricans, for 40 days and examined by microscopy. Etching of the duplex structure, pitting as well as crevice attack were noticed. Similar results were obtained by microscopic studies with coupons exposed for 14 days in medium containing SRB followed by anodic polarization. SEM studies, of crevices observed after anodic polarization, indicated that the attack was initiated at the grain boundaries and slowly encroached into austenite grains. The initiation of attack was also evident from AFM studies of coupon exposed under freely corroding conditions for 7 days. ESCA studies reveal that under anaerobic conditions of SRB growth sulfidation of passive film occurs. The modified passive film found to depolarize the cathodic reactions. The nature and mechanism of SRB attack on DSS and possibility of detection at early stages were discussed.     

Cellulose-binding domains: potential for purification of complex proteins

The endoglucanase CenA and the exoglucanase Cex from Cellulomonasfimi each contain a discrete cellulose-binding domain (CBD),at the amino-terminus or carboxyl-terminus respectively. Thegene fragment encoding the CBD can be fused to the gene of aprotein of interest. Using this approach hybrid proteins canbe engineered which bind reversibly to cellulose and exhibitthe biological activity of the protein partner. Alkaline phosphatase(PhoA) from Escherichia coli, and a ß-glucosidase(Abg) from an Agrobacterium sp. are dimeric proteins. The fusionpolypeptides CenA-PhoA and Abg-CBC_cex are sensitive to proteolysisat the junctions between the fusion partners. Proteolysis resultsin a mixture of homo- and heterodimers; these bind to celluloseif one or both of the monomers carry a CBD, e.g. CenA-PhoA/CenA-PhoAand CenA-PhoA/PhoA. CBD fusion polypeptides could be used inthis way to purify polypeptides which associate with the fusionpartner.     

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.     

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.