Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

Detection of lead(II) and silver(I) in aqueous solution using a piezoelectric device

The gold surface of a quartz crystal microbalance was modified by the attachment of silica particles derivatised with N-[(3-trimethoxysilyl)propyl] ethylenediaminetriacetic acid. The device was employed to study the kinetics of the interaction of aqueous solutions of lead(II) nitrate and silver(I) nitrate with the surface and for the selective separation of the metal ions.

Detection of dimethyl sulfone in the human brain by in vivo proton magnetic resonance spectroscopy

We wish to report the detection of dimethyl sulfone (methylsulfonylmethane, C2H6O2S) in the brain of a normal 62-year-old male using in vivo proton magnetic resonance spectroscopy. The presence of this exogenous metabolite resulted from ingestion of a dietary supplement containing dimethyl sulfone. The concentration of this compound in the brain was measured to be 2.4 mmol, with a washout half life of approximately 7.5 days. The in vivo T-1 and T-2 relaxation times of dimethyl sulfone were measured to be 2180 ms and 385 ms, respectively. The concentration of major brain metabolites, namely N-acetylaspartate, total Creatine and Choline, and myo-Inositol were within normal limits. (C) 2000 Elsevier Science Inc. All rights reserved.

An object-oriented neural network approach to short-term traffic forecasting

This paper discusses an object-oriented neural network model that was developed for predicting short-term traffic conditions on a section of the Pacific Highway between Brisbane and the Gold Coast in Queensland, Australia. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. The results obtained indicate that the TLRN is capable of predicting speed up to 5 minutes into the future with a high degree of accuracy (90-94%). Similar models, which were developed for predicting freeway travel times on the same facility, were successful in predicting travel times up to 15 minutes into the future with a similar degree of accuracy (93-95%). These results represent substantial improvements on conventional model performance and clearly demonstrate the feasibility of using the object-oriented approach for short-term traffic prediction. (C) 2001 Elsevier Science B.V. All rights reserved.

Weak-force detection with superposed coherent states

We investigate the utility of nonclassical states of simple harmonic oscillators, particularly a superposition of coherent states, for sensitive force detection. We find that like squeezed states, a superposition of coherent states allows displacement measurements at the Heisenberg limit. Entangling many superpositions of coherent states offers a significant advantage over a single-mode superposition state with the same mean photon number.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs

An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data. (C) 2003 Elsevier Science B.V. All rights reserved.

Characterization of a microcystin and detection of microcystin synthetase genes from a Brazilian isolate of Nostoc

A nostocalean nitrogen-fixing cyanobacterium isolated from an eutrophic freshwater reservoir located in Piracicaba, Sao Paulo, Brazil, was evaluated for the production of hepatotoxic cyclic heptapeptides, microcystins. Morphologically this new cyanobacterium strain appears closest to Nostoc, however, in the phylogenetic analysis of 165 rRNA gene it falls into a highly stable cluster distantly only related to the typical Nostoc cluster. Extracts of Nostoc sp. CENA88 cultured cells, investigated using ELISA assay, gave positive results and the microcystin profile revealed by ESI-Q-TOF/MS/MS analysis confirmed the production of [Dha(7)]MCYST-YR. Further, Nostoc sp. CENA88 genomic DNA was analyzed by PCR for sequences of mcyD, mcyE and mcyG genes of microcystin synthetase (mcy) cluster. The result revealed the presence of mcyD, mcyE and mcyG genes with similarities to those from mcy of Nostoc sp. strains 152 and IO-102-I and other cyanobacterial genera. The phylogenetic tree based on concatenated McyG, McyD and McyE amino acids clustered the sequences according to cyanobacterial genera, with exception of the Nostoc sp. CENA88 sequence, which was placed in a clade distantly related from other Nostoc strains, as previously observed also in the 165 rRNA phylogenetic analysis. The present study describes for the first time a Brazilian Nostoc microcystin producer and also the occurrence of demethyl MCYST-YR variant in this genus. The sequenced Nostoc genes involved in the microcystin synthesis can contribute to a better understanding of the toxigenicity and evolution of this cyanotoxin. (C) 2009 Elsevier Ltd. All rights reserved.

Solid-phase microextraction using poly(pyrrole) film and liquid chromatography with UV detection for analysis of antidepressants in plasma samples

Poly(pyrrole) (PPY) coating was prepared on a stainless-steel (SS) wire for solid-phase microextraction (SPME) by electrochemical deposition (cyclic voltammetric). The PPY was evaluated by analyzing new-generation antidepressants (mirtazapine, citalopram, paroxetine, duloxetine, fluoxetine, and sertraline) in plasma sample by SPME and liquid chromatography with UV detection (LC-UV). The effect of electrolyte Solution (lithium perchlorate or tetrabutylammonium perchlorate) and the number of cycles (50, 100 or 200) applied during the polymerization process on the SPME performance was evaluated. Important factors in the optimization of SPME efficiency such as extraction time, temperature, pH, influence of plasma proteins on sorption mechanisms, and desorption conditions are discussed. The SPME-PPY/LC method showed to be linear in concentrations ranging from the limit of quantification (LOQ) to 1200 ng mL(-1). The LOQ values range from 16 to 25 ng mL-1. The inter-day precision of the SPME-PPY/LC method presented coefficient of variation (CV) lower than 15%. Based on analytical validation results, the SPME-PPY/LC methodology showed to be adequate for antidepressant analysis, from therapeutic to toxic levels. In order to evaluate the proposed method for clinical use, the SPME-PPY/LC method was applied to the analysis of plasma samples from elderly depressed patients. (c) 2009 Elsevier B.V. All rights reserved,