The influence of substrate kinetics on the microbial community structure in granular anaerobic biomass

The development of a strong, active granular sludge bed is necessary for optimal operation of upflow anaerobic sludge blanket reactors. The microbial and mechanical structure of the granules may have a strong influence on desirable properties such as growth rate, settling velocity and shear strength. Theories have been proposed for granule microbial structure based on the relative kinetics of substrate degradation, but contradict some observations from both modelling and microscopic studies. In this paper, the structures of four granule types were examined from full-scale UASB reactors, treating wastewater from a cannery, a slaughterhouse, and two breweries. Microbial structure was determined using fluorescence in situ hybridisation probing with 16S rRNA-directed oligonucleotide probes, and superficial structure and microbial density (volume occupied by cells and microbial debris) assessed using scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The granules were also modelled using a distributed parameter biofilm model, with a previously published biochemical model structure, biofilm modelling approach, and model parameters. The model results reflected the trophic structures observed, indicating that the structures were possibly determined by kinetics. Of particular interest were results from simulations of the protein grown granules, which were predicted to have slow growth rates, low microbial density, and no trophic layers, the last two of which were reflected by microscopic observations. The primary cause of this structure, as assessed by modelling, was the particulate nature of the wastewater, and the slow rate of particulate hydrolysis, rather than the presence of proteins in the wastewater. Because solids hydrolysis was rate limiting, soluble substrate concentrations were very low (below Monod half saturation concentration), which caused low growth rates. (C) 2003 Elsevier Ltd. All rights reserved.

Design and implementation of a windows-based parallel computing environment for large scale optimization

A parallel computing environment to support optimization of large-scale engineering systems is designed and implemented on Windows-based personal computer networks, using the master-worker model and the Parallel Virtual Machine (PVM). It is involved in decomposition of a large engineering system into a number of smaller subsystems optimized in parallel on worker nodes and coordination of subsystem optimization results on the master node. The environment consists of six functional modules, i.e. the master control, the optimization model generator, the optimizer, the data manager, the monitor, and the post processor. Object-oriented design of these modules is presented. The environment supports steps from the generation of optimization models to the solution and the visualization on networks of computers. User-friendly graphical interfaces make it easy to define the problem, and monitor and steer the optimization process. It has been verified by an example of a large space truss optimization. (C) 2004 Elsevier Ltd. All rights reserved.

Coherent-state linear optical quantum computing gates using simplified diagonal superposition resource states

In this paper we explore the possibility of fundamental tests for coherent-state optical quantum computing gates [ T. C. Ralph et al. Phys. Rev. A 68 042319 (2003)] using sophisticated but not unrealistic quantum states. The major resource required in these gates is a state diagonal to the basis states. We use the recent observation that a squeezed single-photon state [S(r)∣1⟩] approximates well an odd superposition of coherent states (∣α⟩−∣−α⟩) to address the diagonal resource problem. The approximation only holds for relatively small α, and hence these gates cannot be used in a scalable scheme. We explore the effects on fidelities and probabilities in teleportation and a rotated Hadamard gate.

Frequency and temporal effects in linear optical quantum computing

Typically linear optical quantum computing (LOQC) models assume that all input photons are completely indistinguishable. In practice there will inevitably be nonidealities associated with the photons and the experimental setup which will introduce a degree of distinguishability between photons. We consider a nondeterministic optical controlled-NOT gate, a fundamental LOQC gate, and examine the effect of temporal and spectral distinguishability on its operation. We also consider the effect of utilizing nonideal photon counters, which have finite bandwidth and time response.

Global control and fast solid-state donor electron spin quantum computing

We propose a scheme for quantum information processing based on donor electron spins in semiconductors, with an architecture complementary to the original Kane proposal. We show that a naive implementation of electron spin qubits provides only modest improvement over the Kane scheme, however through the introduction of global gate control we are able to take full advantage of the fast electron evolution timescales. We estimate that the latent clock speed is 100-1000 times that of the nuclear spin quantum computer with the ratio T-2/T-ops approaching the 10(6) level.

Pyramidal neurons of granular prefrontal cortex of the galago: Complexity in evolution of the psychic cell in primates

Typically, cognitive abilities of humans have been attributed to their greatly expanded cortical mantle, granular prefrontal cortex (gPFC) in particular. Recently we have demonstrated systematic differences in microstructure of gPFC in different species. Specifically, pyramidal cells in adult human gPFC are considerably more spinous than those in the gPFC of the macaque monkey, which are more spinous than those in the gPFC of marmoset and owl monkeys. As most cortical dendritic spines receive at least one excitatory input, pyramidal cells in these different species putatively receive different numbers of inputs. These differences in the gPFC pyramidal cell phenotype may be of fundamental importance in determining the functional characteristics of prefrontal circuitry and hence the cognitive styles of the different species. However, it remains unknown as to why the gPFC pyramidal cell phenotype differs between species. Differences could be attributed to, among other things, brain size, relative size of gPFC, or the lineage to which the species belong. Here we investigated pyramidal cells in the dorsolateral gPFC of the prosimian galago to extend the basis for comparison. We found these cells to be less spinous than those in human, macaque, and marmoset. (c) 2005 Wiley-Liss, Inc.

Quantum computing and polynomial equations over the finite field Z(2)

What is the computational power of a quantum computer? We show that determining the output of a quantum computation is equivalent to counting the number of solutions to an easily computed set of polynomials defined over the finite field Z(2). This connection allows simple proofs to be given for two known relationships between quantum and classical complexity classes, namely BQP subset of P-#P and BQP subset of PP.

Solid transport in a pyrolysis pilot-scale rotary kiln: Preliminary results?stationary and dynamic results

Experiments for the investigation of the flow of granular solids in a pyrolysis pilot-scale rotary kiln are presented. These experiments consisted first in measuring the volumetric filling ratio (steady-state experiences) for several operating conditions and second in recording the exit flow rates after a positive or negative step in one of the operating parameters (dynamic experiences). A dynamical model computing the evolution of the flow rate of granular solids through the kiln has been developed based on Saeman model [Chem. Eng. Prog. 47 (1951) 508]. The simulations are compared with experimental results; the model gives good results for the rolling mode, but for the slipping mode too. (C) 2004 Elsevier B.V. All rights reserved.

Optimal control, geometry, and quantum computing

We prove upper and lower bounds relating the quantum gate complexity of a unitary operation, U, to the optimal control cost associated to the synthesis of U. These bounds apply for any optimal control problem, and can be used to show that the quantum gate complexity is essentially equivalent to the optimal control cost for a wide range of problems, including time-optimal control and finding minimal distances on certain Riemannian, sub-Riemannian, and Finslerian manifolds. These results generalize the results of [Nielsen, Dowling, Gu, and Doherty, Science 311, 1133 (2006)], which showed that the gate complexity can be related to distances on a Riemannian manifold.

Specializations of the granular prefrontal cortex of primates: Implications for cognitive processing

The biological underpinnings of human intelligence remain enigmatic. There remains the greatest confusion and controversy regarding mechanisms that enable humans to conceptualize, plan, and prioritize, and why they are set apart from other animals in their cognitive abilities. Here we demonstrate that the basic neuronal building block of the cerebral cortex, the pyramidal cell, is characterized by marked differences in structure among primate species. Moreover, comparison of the complexity of neuron structure with the size of the cortical area/region in which the cells are located revealed that trends in the granular prefrontal cortex (gPFC) were dramatically different to those in visual cortex. More specifically, pyramidal cells in the gPFC of humans had a disproportionately high number of spines. As neuron structure determines both its biophysical properties and connectivity, differences in the complexity in dendritic structure observed here endow neurons with different computational abilities. Furthermore, cortical circuits composed of neurons with distinguishable morphologies will likely be characterized by different functional capabilities. We propose that 1. circuitry in V1, V2, and gPFC within any given species differs in its functional capabilities and 2. there are dramatic differences in the functional capabilities of gPFC circuitry in different species, which are central to the different cognitive styles of primates. In particular, the highly branched, spinous neurons in the human gPFC may be a key component of human intelligence. (C) 2005 Wiley-Liss, Inc.

Treatment of naphthalene-2-sulfonic acid from tannery wastewater by a granular activated carbon fixed bed inoculated with bacterial isolates Arthrobacter globiformis and Comamonas testosteroni

The kinetics of naphthalene-2-sulfonic acid (2-NSA) adsorption by granular activated carbon (GAC) were measured and the relationships between adsorption, desorption, bioavailability and biodegradation assessed. The conventional Langmuir model fitted the experimental sorption isotherm data and introduced 2-NSA degrading bacteria, established on the surface of the GAC, did not interfere with adsorption. The potential value of GAC as a microbial support in the aerobic degradation of 2-NSA by Arthrobacter globiformis and Comamonas testosteroni was investigated. Using both virgin and microbially colonised GAC, adsorption removed 2-NSA from the liquid phase up to its saturation capacity of 140 mg/g GAC within 48 h. However, between 83.2% and 93.3% of the adsorbed 2-NSA was bioavailable to both bacterial species as a source of carbon for growth. In comparison to the non-inoculated GAC, the combination of rapid adsorption and biodegradation increased the amount (by 70–93%) of 2-NSA removal from the influent phase as well as the bed-life of the GAC (from 40 to >120 d). A microbially conditioned GAC fixed-bed reactor containing 15 g GAC removed 100% 2-NSA (100 mg/l) from tannery wastewater at an empty bed contact time of 22 min for a minimum of 120 d without the need for GAC reconditioning or replacement. This suggests that small volume GAC bioreactors could be used for tannery wastewater recycling.