A Hybrid Forward Algorithm for RBF Neural Network Construction

This paper proposes a novel hybrid forward algorithm (HFA) for the construction of radial basis function (RBF) neural networks with tunable nodes. The main objective is to efficiently and effectively produce a parsimonious RBF neural network that generalizes well. In this study, it is achieved through simultaneous network structure determination and parameter optimization on the continuous parameter space. This is a mixed integer hard problem and the proposed HFA tackles this problem using an integrated analytic framework, leading to significantly improved network performance and reduced memory usage for the network construction. The computational complexity analysis confirms the efficiency of the proposed algorithm, and the simulation results demonstrate its effectiveness

Kinematic Design of a 6-DOF Parallel Manipulator with Decoupled Translation and Rotation

A new three-limb, six-degree-of-freedom (DOF) parallel manipulator (PM), termed a selectively actuated PM (SA-PM), is proposed. The end-effector of the manipulator can produce 3-DOF spherical motion, 3-DOF translation, 3-DOF hybrid motion, or complete 6-DOF spatial motion, depending on the types of the actuation (rotary or linear) chosen for the actuators. The manipulator architecture completely decouples translation and rotation of the end-effector for individual control. The structure synthesis of SA-PM is achieved using the line geometry. Singularity analysis shows that the SA-PM is an isotropic translation PM when all the actuators are in linear mode. Because of the decoupled motion structure, a decomposition method is applied for both the displacement analysis and dimension optimization. With the index of maximal workspace satisfying given global conditioning requirements, the geometrical parameters are optimized. As a result, the translational workspace is a cube, and the orientation workspace is nearly unlimited.

The Burkholderia cenocepacia sensor kinase hybrid AtsR is a global regulator modulating quorum-sensing signalling

Burkholderia cenocepacia is commonly found in the environment and also as an important opportunistic pathogen infecting patients with cystic fibrosis. Successful infection by this bacterium requires coordinated expression of virulence factors, which is achieved through different quorum sensing (QS) regulatory systems. Biofilm formation and Type 6 secretion system (T6SS) expression in B. cenocepacia K56-2 are positively regulated by QS and negatively regulated by the sensor kinase hybrid AtsR. This study reveals that in addition to affecting biofilm and T6SS activity, the deletion of atsR in B. cenocepacia leads to overproduction of other QS-regulated virulence determinants including proteases and swarming motility. Expression of the QS genes, cepIR and cciIR, was upregulated in the ?atsR mutant and resulted in early and increased N-acylhomoserine lactone (AHL) production, suggesting that AtsR plays a role in controlling the timing and fine-tuning of virulence gene expression by modulating QS signalling. Furthermore, a ?atsR?cepI?cciI mutant could partially upregulate the same virulence determinants indicating that AtsR also modulates the expression of virulence genes by a second mechanism, independently of any AHL production. Together, our results strongly suggest that AtsR is a global virulence regulator in B. cenocepacia.

Hybrid FIB milling strategy for the fabrication of plasmonic nanostructures on semiconductor substrates

The optical properties of plasmonic semiconductor devices fabricated by focused ion beam (FIB) milling deteriorate because of the amorphisation of the semiconductor substrate. This study explores the effects of combining traditional 30 kV FIB milling with 5 kV FIB patterning to minimise the semiconductor damage and at the same time maintain high spatial resolution. The use of reduced acceleration voltages is shown to reduce the damage from higher energy ions on the example of fabrication of plasmonic crystals on semiconductor substrates leading to 7-fold increase in transmission. This effect is important for focused-ion beam fabrication of plasmonic structures integrated with photodetectors, light-emitting diodes and semiconductor lasers.

Efficient modelling and optimisation of hybrid multilayered plates subject to ballistic impact

Among the key challenges present in the modelling and optimisation of composite structures against impact is the computational expense involved in setting up accurate simulations of the impact event and then performing the iterations required to optimise the designs. It is of more interest to find good designs given the limitations of the resources and time available rather than the best possible design. In this paper, low cost but sufficiently accurate finite element (FE) models were generated in LS Dyna for several experimentally characterised materials by semi-automating the modelling process and using existing material models. These models were then used by an optimisation algorithm to generate new hybrid offspring, leading to minimum weight and/or cost designs from a selection of isotropic metals, polymers and orthotropic fibre-reinforced laminates that countered a specified impact threat. Experimental validation of the optimal designs thus identified was then successfully carried out using a single stage gas gun. With sufficient computational hardware, the techniques developed in this pilot study can further utilise fine meshes, equations of state and sophisticated material models, so that optimal hybrid systems can be identified from a wide range of materials, designs and threats.

Intralaminar toughness characterisation of unbalanced hybrid plain weave laminates

A numerical and experimental investigation on the mode-I intralaminar toughness of a hybrid plain weave composite laminate manufactured using resin infusion under flexible tooling (RIFT) process is presented in this paper. The pre-cracked geometries consisted of overheight compact tension (OCT), double edge notch (DEN) and centrally cracked four-point-bending (4PBT) test specimens. The position as well as the strain field ahead of the crack tip during the loading stage was determined using a digital speckle photogrammetry system. The limitation on the applicability of the standard data reduction schemes for the determination of intralaminar toughness of composite materials is presented and discussed. A methodology based on the numerical evaluation of the strain energy release rate using the J-integral method is proposed to derive new geometric correction functions for the determination of the stress intensity factor for composites. The method accounts for material anisotropy and finite specimen dimension effects regardless of the geometry. The approach has been validated for alternative non-standard specimen geometries. A comparison between different methods currently available for computing the intralaminar fracture toughness in composite laminates is presented and a good agreement between numerical and experimental results using the proposed methodology was obtained. 

Characterization of the AtsR Hybrid Sensor Kinase Phosphorelay Pathway and Identification of Its Response Regulator in Burkholderia cenocepacia

AtsR is a membrane-bound hybrid sensor kinase of Burkholderia cenocepacia that negatively regulates quorum sensing and virulence factors such as biofilm production, type 6-secretion and protease secretion. Here, we elucidate the mechanism of AtsR phosphorelay by site-directed mutagenesis of predicted histidine and aspartic acid phosphoacceptor residues. We demonstrate by in vitro phosphorylation that histidine-245 and aspartic acid-536 are conserved sites of phosphorylation in AtsR, and we also identify the cytosolic response regulator AtsT (BCAM0381) as a key component of the AtsR phosphorelay pathway. Monitoring the function of AtsR and its derivatives in vivo by measuring extracellular protease activity and swarming motility confirmed the in vitro phosphorylation results. Together, we find that the AtsR receiver domain plays a fine-tuning role in determining the levels of phosphotransfer from its sensor kinase domain to the AtsT response regulator.

Electrochemical sensor for catechol and dopamine based on a catalytic molecularly imprinted polymer-conducting polymer hybrid recognition element

One of the difficulties with using molecularly imprinted polymers (MIPs) and other electrically insulating materials as the recognition element in electrochemical sensors is the lack of a direct path for the conduction of electrons from the active sites to the electrode. We have sought to address this problem through the preparation and characterization of novel hybrid materials combining a catalytic MIP, capable of oxidizing the template, catechol, with an electrically conducting polymer. In this way a network of "molecular wires" assists in the conduction of electrons from the active sites within the MIP to the electrode surface. This was made possible by the design of a new monomer that combines orthogonal polymerizable functionality; comprising an aniline group and a methacrylamide. Conducting films were prepared on the surface of electrodes (Au on glass) by electropolymerization of the aniline moiety. A layer of MIP was photochemically grafted over the polyaniline, via N,N'-diethyldithiocarbamic acid benzyl ester (iniferter) activation of the methacrylamide groups. Detection of catechol by the hybrid-MIP sensor was found to be specific, and catechol oxidation was detected by cyclic voltammetry at the optimized operating conditions: potential range -0.6 V to +0.8 V (vs Ag/AgCl), scan rate 50 mV/s, PBS pH 7.4. The calibration curve for catechol was found to be linear to 144 µM, with a limit of detection of 228 nM. Catechol and dopamine were detected by the sensor, whereas analogues and potentially interfering compounds, including phenol, resorcinol, hydroquinone, serotonin, and ascorbic acid, had minimal effect (=3%) on the detection of either analyte. Nonimprinted hybrid electrodes and bare gold electrodes failed to give any response to catechol at concentrations below 0.5 mM. Finally, the catalytic properties of the sensor were characterized by chronoamperometry and were found to be consistent with Michaelis-Menten kinetics. © 2009 American Chemical Society.

Self-assembly of hybrid organic–inorganic polyoxovanadates: functionalised mixed-valent clusters and molecular cages’

Herein we report the intra- and inter-molecular assembly of a {V5O9} subunit. This mixed-valent structural motif can be stabilised as [V5O9(L1–3)4]5−/9− (1–3) by a range of organoarsonate ligands (L1–L3) whose secondary functionalities influence its packing arrangement within the crystal structures. Variation of the reaction conditions results in the dodecanuclear cage structure [V12O14(OH)4(L1)10]4− (4) where two modified convex building units are linked via two dimeric {O4VIV(OH)2VIVO4} moieties. Bi-functional phosphonate ligands, L4–L6 allow the intramolecular connectivity of the {V5O9} subunit to give hybrid capsules [V10O18(L4–6)4]10− (5–7). The dimensions of the electrophilic cavities of the capsular entities are determined by the incorporated ligand type. Mass spectrometry experiments confirm the stability of the complexes in solution. We investigate and model the temperature-dependent magnetic properties of representative complexes 1, 4, 6 and 7 and provide preliminary cell-viability studies of three different cancer cell lines with respect to Na8H2[6]·36H2O and Na8H2[7]·2DMF·29H2O.

The Engine of Thought Is a Hybrid: Roles of Associative and Structured Knowledge in Reasoning

Across a range of domains in psychology different theories assume different mental representations of knowledge. For example, in the literature on category-based inductive reasoning, certain theories (e.g., Rogers & McClelland, 2004; Sloutsky & Fisher, 2008) assume that the knowledge upon which inductive inferences are based is associative, whereas others (e.g., Heit & Rubinstein, 1994; Kemp & Tenenbaum, 2009; Osherson, Smith, Wilkie, López, & Shafir, 1990) assume that knowledge is structured. In this article we investigate whether associative and structured knowledge underlie inductive reasoning to different degrees under different processing conditions. We develop a measure of knowledge about the degree of association between categories and show that it dissociates from measures of structured knowledge. In Experiment 1 participants rated the strength of inductive arguments whose categories were either taxonomically or causally related. A measure of associative strength predicted reasoning when people had to respond fast, whereas causal and taxonomic knowledge explained inference strength when people responded slowly. In Experiment 2, we also manipulated whether the causal link between the categories was predictive or diagnostic. Participants preferred predictive to diagnostic arguments except when they responded under cognitive load. In Experiment 3, using an open-ended induction paradigm, people generated and evaluated their own conclusion categories. Inductive strength was predicted by associative strength under heavy cognitive load, whereas an index of structured knowledge was more predictive of inductive strength under minimal cognitive load. Together these results suggest that associative and structured models of reasoning apply best under different processing conditions and that the application of structured knowledge in reasoning is often effortful.