Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces

Combinatorial optimization problems share an interesting property with spin glass systems in that their state spaces can exhibit ultrametric structure. We use sampling methods to analyse the error surfaces of feedforward multi-layer perceptron neural networks learning encoder problems. The third order statistics of these points of attraction are examined and found to be arranged in a highly ultrametric way. This is a unique result for a finite, continuous parameter space. The implications of this result are discussed.

Use of liquid phase adsorption for characterizing pore network connectivity in activated carbon

A simple percolation theory-based method for determination of the pore network connectivity using liquid phase adsorption isotherm data combined with a density functional theory (DFT)-based pore size distribution is presented in this article. The liquid phase adsorption experiments have been performed using eight different esters as adsorbates and microporous-mesoporous activated carbons Filtrasorb-400, Norit ROW 0.8 and Norit ROX 0.8 as adsorbents. The density functional theory (DFT)-based pore size distributions of the carbons were obtained using DFT analysis of argon adsorption data. The mean micropore network coordination numbers, Z, of the carbons were determined based on DR characteristic plots and fitted saturation capacities using percolation theory. Based on this method, the critical molecular sizes of the model compounds used in this study were also obtained. The incorporation of percolation concepts in the prediction of multicomponent adsorption equilibria is also investigated, and found to improve the performance of the ideal adsorbed solution theory (IAST) model for the large molecules utilized in this study. (C) 2002 Elsevier Science B.V. All rights reserved.

Using siting algorithms in the design of marine reserve networks

Using benthic habitat data from the Florida Keys (USA), we demonstrate how siting algorithms can help identify potential networks of marine reserves that comprehensively represent target habitat types. We applied a flexible optimization tool-simulated annealing-to represent a fixed proportion of different marine habitat types within a geographic area. We investigated the relative influence of spatial information, planning-unit size, detail of habitat classification, and magnitude of the overall conservation goal on the resulting network scenarios. With this method, we were able to identify many adequate reserve systems that met the conservation goals, e.g., representing at least 20% of each conservation target (i.e., habitat type) while fulfilling the overall aim of minimizing the system area and perimeter. One of the most useful types of information provided by this siting algorithm comes from an irreplaceability analysis, which is a count of the number of, times unique planning units were included in reserve system scenarios. This analysis indicated that many different combinations of sites produced networks that met the conservation goals. While individual 1-km(2) areas were fairly interchangeable, the irreplaceability analysis highlighted larger areas within the planning region that were chosen consistently to meet the goals incorporated into the algorithm. Additionally, we found that reserve systems designed with a high degree of spatial clustering tended to have considerably less perimeter and larger overall areas in reserve-a configuration that may be preferable particularly for sociopolitical reasons. This exercise illustrates the value of using the simulated annealing algorithm to help site marine reserves: the approach makes efficient use of;available resources, can be used interactively by conservation decision makers, and offers biologically suitable alternative networks from which an effective system of marine reserves can be crafted.

Segmenting the market of West Australian senior tourists using an artificial neural network

Measuring perceptions of customers can be a major problem for marketers of tourism and travel services. Much of the problem is to determine which attributes carry most weight in the purchasing decision. Older travellers weigh many travel features before making their travel decisions. This paper presents a descriptive analysis of neural network methodology and provides a research technique that assesses the weighting of different attributes and uses an unsupervised neural network model to describe a consumer-product relationship. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalised linear models. Artificial neural networks or neural networks are, however, nonlinear and do not require the same restrictive assumptions about the relationship between the independent variables and dependent variables. Using neural networks is one way to determine what trade-offs older travellers make as they decide their travel plans. The sample of this study is from a syndicated data source of 200 valid cases from Western Australia. From senior groups, active learner, relaxed family body, careful participants and elementary vacation were identified and discussed. (C) 2003 Published by Elsevier Science Ltd.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

GLUT4 recycles via a trans-Golgi network (TGN) subdomain enriched in Syntaxins 6 and 16 but not TGN38: Involvement of an acidic targeting motif

Insulin stimulates glucose transport in fat and muscle cells by triggering exocytosis of the glucose transporter GLUT4. To define the intracellular trafficking of GLUT4, we have studied the internalization of an epitope-tagged version of GLUT4 from the cell surface. GLUT4 rapidly traversed the endosomal system en route to a perinuclear location. This perinuclear GLUT4 compartment did not colocalize with endosomal markers (endosomal antigen I protein, transferrin) or TGN38, but showed significant overlap with the TGN target (t)-soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) Syntaxins 6 and 16. These results were confirmed by vesicle immunoisolation. Consistent with a role for Syntaxins 6 and 16 in GLUT4 trafficking we found that their expression was up-regulated significantly during adipocyte differentiation and insulin stimulated their movement to the cell surface. GLUT4 trafficking between endosomes and trans-Golgi network was regulated via an acidic targeting motif in the carboxy terminus of GLUT4, because a mutant lacking this motif was retained in endosomes. We conclude that GLUT4 is rapidly transported from the cell surface to a subdomain of the trans-Golgi network that is enriched in the t-SNAREs Syntaxins 6 and 16 and that an acidic targeting motif in the C-terminal tail of GLUT4 plays an important role in this process.

GRIP domain-mediated targeting of two new coiled-coil proteins, GCC88 and GCC185, to subcompartments of the trans-Golgi network

The GRIP domain is a targeting sequence found in a family of coiled-coil peripheral Golgi proteins. Previously we demonstrated that the GRIP domain of p230/golgin245 is specifically recruited to tubulovesicular structures of the traps-Golgi network (TGN). Here we have characterized two novel Golgi proteins with functional GRIP domains, designated GCC88 and GCC185. GCC88 cDNA encodes a protein of 88 kDa, and GCC185 cDNA encodes a protein of 185 kDa. Both molecules are brefeldin A-sensitive peripheral membrane proteins and are predicted to have extensive coiled-coil regions with the GRIP domain at the C terminus. By immunofluorescence and immunoelectron microscopy GCC88 and GCC185, and the GRIP protein golgin97, are all localized to the TGN of Hela cells. Overexpression of full-length GCC88 leads to the formation of large electron dense structures that extend from the traps-Golgi. These de novo structures contain GCC88 and co-stain for the TGN markers syntaxin 6 and TGN38 but not for alpha2,6-sialyltransferase, beta-COP, or cis-Golgi GM130. The formation of these abnormal structures requires the N-terminal domain of GCC88. TGN38, which recycles between the TGN and plasma membrane, was transported into and out of the GCC88 decorated structures. These data introduce two new GRIP domain proteins and implicate a role for GCC88 in the organization of a specific TGN subcompartment involved with membrane transport.

GAIP participates in budding of membrane carriers at the trans-Golgi network

Galpha interacting protein (GAIP) is a regulator of G protein signaling protein that associates dynamically with vesicles and has been implicated in membrane trafficking, although its specific role is not yet known. Using an in vitro budding assay, we show that GAIP is recruited to a specific population of trans-Golgi network-derived vesicles and that these are distinct from coatomer or clathrin-coated vesicles. A truncation mutant (NT-GAIP) encoding only the N-terminal half of GAIP is recruited to trans -Golgi network membranes during the formation of vesicle carriers. Overexpression of NT-GAIP induces the formation of long, coated tubules, which are stabilized by microtubules. Results from the budding assay and from imaging in live cells show that these tubules remain attached to the Golgi stack rather than being released as carrier vesicles. NT-GAIP expression blocks membrane budding and results in the accumulation of tubular carrier intermediates. NT-GAIP-decorated tubules are competent to load vesicular stomatitis virus protein G-green fluorescent protein as post-Golgi, exocytic cargo and in cells expressing NT-GAIP there is reduced surface delivery of vesicular stomatitis virus protein G-green fluorescent protein. We conclude that GAIP functions as an essential part of the membrane budding machinery for a subset of post-Golgi exocytic carriers derived from the trans-Golgi network.

A reduced load approximation accounting for link interactions in a loss network

This paper is concerned with evaluating the performance of loss networks. Accurate determination of loss network performance can assist in the design and dimen- sioning of telecommunications networks. However, exact determination can be difficult and generally cannot be done in reasonable time. For these reasons there is much interest in developing fast and accurate approximations. We develop a reduced load approximation that improves on the famous Erlang fixed point approximation (EFPA) in a variety of circumstances. We illustrate our results with reference to a range of networks for which the EFPA may be expected to perform badly.

Effect of pore-network connectivity on multicomponent adsorption of large molecules

The effect of pore-network connectivity on binary liquid-phase adsorption equilibria using the ideal adsorbed solution theory (LAST) was studied. The liquid-phase binary adsorption experiments used ethyl propionate, ethyl butyrate, and ethyl isovalerate as the adsorbates and commercial activated carbons Filtrasorb-400 and Norit ROW 0.8 as adsorbents. As the single-component isotherm, a modified Dubinin-Radushkevich equation was used. A comparison with experimental data shows that incorporating the connectivity of the pore network and considering percolation processes associated with different molecular sizes of the adsorptives in the mixture, as well as their different corresponding accessibility, can improve the prediction of binary adsorption equilibria using the LAST Selectivity of adsorption for the larger molecule in binary systems increases with an increase in the pore-network coordination number, as well with an increase in the mean pore width and in the spread of the pore-size distribution.