Evaluation of several modifications of an ecometric technique for assessment of media performance

Recovery of Listeria monocytogenes 101M, Jonesia denitrificans, salmonellae, and Pediococcus sp. NRRL B-2354 across nine media was evaluated with three modified versions of an ecometric method. Two approaches involved the use of broth cultures (10(8) to 10(9) CFU/ml) of individual strains and either large (10-microl) or small (1-microl) presterilized plastic loops. The third approach involved precultured slants and the inoculation of media with presterilized plastic inoculating needles (10(4) CFU per needle). Absolute growth indices (AGIs) were compared. No significant differences (P < 0.05) between methods were found when tryptic soy agar supplemented with 0.6% yeast extract (TSAYE) was used for the recovery of L. monocytogenes, J. denitrificans, Pediococcus sp. NRRL B-2354, and Salmonella spp. However, the small loop-broth technique recovered significantly fewer Salmonella enterica Typhimurium DT104 and Salmonella Senftenberg 775W cells than the other two techniques did. The performance of each individual bacterial strain on each of nine media was assayed. The recovery of L. monocytogenes was excellent (AGI > 4.8) with TSAYE, PALCAM, modified Oxford medium (MOX), and Baird-Parker agar and slight with modified PRAB (AGI = 0.4) and deMan Rogosa Sharpe (MRS) agar (< 0.1), and the organism was not recovered with the remaining media (modified lysine iron agar [MLIA], xylose lysine desoxycholate [XLD] agar, and xylose lysine tergitol 4 [XLT4] agar). The recovery of J. denitrificans with TSAYE and MOX was excellent, significantly better than that achieved with PALCAM (AGI = 3.0), but the organism was not recovered with Baird-Parker agar or with the other media tested. The recovery of Pediococcus sp. NRRL B-2354 was excellent with TSAYE and modified PRAB medium > Baird-Parker agar > acidified MRS agar, but the organism was not recovered with any of the other media tested. The best recovery of S. enterica Typhimurium DT104 was achieved with TSAYE > MLIA > or = XLD agar > or = XLT4 agar > Baird-Parker > PALCAM, MOX, acidified MRS agar, modified PRAB, and MRS agar. The best recovery of Salmonella Senftenberg 775W was achieved with TSAYE, MLIA, and XLD agar > XLT4 agar, but the organism was not recovered with the other media evaluated.     

Fast-Fourier-domain delay line for in vivo optical coherence tomography with a polygonal scanner

We demonstrate in vivo optical coherence tomography using a Fourier-domain optical delay line constructed with a commercially available polygonal scanner. The 20-faceted polygonal mirror array, capable of scanning at rates up to 15 kHz, is implemented at 4 kHz to acquire 500 x 500 pixel images at 8 frames/s with a signal-to-noise ratio of 80 dB. Features of this delay line include scalability to high repetition rates, 98.6% linearity in group delay over 2 mm, and bandwidth support exceeding 150 nm. Images are obtained in an animal model (Xenopus laevis), and limitations due to phase-delay nonlinearity and polygon asymmetry are discussed.     

Genomic mining for complex disease traits with “random chemistry”

Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease. This, in turn, could revolutionize detection, treatment, and in some cases prevention of disease. While genes for most of the rare monogenic diseases have already been discovered, most common diseases are complex traits, resulting from multiple gene–gene and gene-environment interactions. Detecting epistatic genetic interactions that predispose for disease is an important, but computationally daunting, task currently facing bioinformaticists. Here, we propose a new evolutionary approach that attempts to hill-climb from large sets of candidate epistatic genetic features to smaller sets, inspired by Kauffman’s “random chemistry” approach to detecting small auto-catalytic sets of molecules from within large sets. Although the algorithm is conceptually straightforward, its success hinges upon the creation of a fitness function able to discriminate large sets that contain subsets of interacting genetic features from those that don’t. Here, we employ an approximate and noisy fitness function based on the ReliefF data mining algorithm. We establish proof-of-concept using synthetic data sets, where individual features have no marginal effects. We show that the resulting algorithm can successfully detect epistatic pairs from up to 1,000 candidate single nucleotide polymorphisms in time that is linear in the size of the initial set, although success rate degrades as heritability declines. Research continues into seeking a more accurate fitness approximator for large sets and other algorithmic improvements that will enable us to extend the approach to larger data sets and to lower heritabilities.     

Optimal choice of intermediate frequency for zero-crossing detectors

It is illustrated that the intermediate frequency (IF) in an IF zero-crossing detector (ZXD) for Bluetooth basic rate transmission affects the transmission quality. A simple optimisation strategy is presented and it is shown that simple IF ZXD structures benefit more from the optimal choice of the IF than hypothesis detectors     

An improved topographic mapping technique from airborne lidar: application in a forested hillside

We developed a robust method to reconstruct a digital terrain model (DTM) by classifying raw light detection and ranging (lidar) points into ground and non-ground points with the help of the Progressive Terrain Fragmentation (PTF) method. PTF applies iterative steps for searching terrain points by approximating terrain surfaces using the triangulated irregular network (TIN) model constructed from ground return points. Instead of using absolute slope or offset distance, PTF uses orthogonal distance and relative angle between a triangular plane and a node. Due to this characteristic, PTF was able to classify raw lidar points into ground and non-ground points on a heterogeneous steep forested area with a small number of parameters. We tested this approach by using a lidar data set covering a part of the Angelo Coast Range Reserve on the South Fork of the Eel River in Mendocino County, California, USA. We used systematically positioned 16 reference plots to determine the optimal parameter that can be used to separate ground and non-ground points from raw lidar point clouds. We tested at different admissible hillslope angles (15° to 20°), and the minimum total error (1.6%) was acquired at the angle value of 18°. Because classifying raw lidar points into ground and non-ground points is the basis for other types of analyses, we expect that our study will provide more accurate terrain approximation and contribute to improving the extraction of other forest biophysical parameters.     

Chester Rapkin,Policy Maker

One of the most significant developments in the advancement of comprehensive land use planning in the United States has been the enactment by some state legislatures of programs designed to foster statewide local or local-regional growth management. A comparison of eight state-sponsored growth management systems reveals wide diversity in program features and provisions. Yet, four distinct paradigms emerge, each suggesting different paths to accommodating growth in varying political, economic, social, and environmental settings.     

An interleaved sampling scheme for the characterization of single qubit dynamics

In this paper, we demonstrate that interleaved sampling techniques can be used to characterize the Hamiltonian of a qubit and its environmental decoherence rate. The technique offers a significant advantage in terms of the number of measurements that are required to characterize a qubit. When compared to the standard Nyquist?CShannon sampling rate, the saving in the total measurement time for the interleaved method is approximately proportional to the ratio of the sample rates.     

A Bayesian nonparametric approach to modeling motion patterns

The most difficult??and often most essential??aspect of many interception and tracking tasks is constructing motion models of the targets. Experts rarely can provide complete information about a target??s expected motion pattern, and fitting parameters for complex motion patterns can require large amounts of training data. Specifying how to parameterize complex motion patterns is in itself a difficult task. In contrast, Bayesian nonparametric models of target motion are very flexible and generalize well with relatively little training data. We propose modeling target motion patterns as a mixture of Gaussian processes (GP) with a Dirichlet process (DP) prior over mixture weights. The GP provides an adaptive representation for each individual motion pattern, while the DP prior allows us to represent an unknown number of motion patterns. Both automatically adjust the complexity of the motion model based on the available data. Our approach outperforms several parametric models on a helicopter-based car-tracking task on data collected from the greater Boston area.     

Enhanced ionic conductivity and phase meta-stability of nano-sized thin film yttria-doped zirconia (YDZ)

Yttria-doped zirconia (YDZ) thin films with nanometric sized grains were prepared by reactive RF sputtering and their oxygen ion conductivities were systematically measured as a function of yttria doping with levels in the range 0.5–9.1 mol.% Y₂O₃. Enhanced oxygen ion conductivities, as derived from impedance spectra, were observed when compared with values reported for bulk YSZ. Furthermore, the peak conductivity for the YDZ films was observed to occur at considerably reduced yttria levels, i.e., at 6.5 mol.% Y₂O₃ (for T > ～400 °C) and at 3.2 mol.% Y₂O₃ (for T < ～300 °C) vs. 9 mol.% Y₂O₃ in bulk YSZ. Based on an analysis of the Raman spectra, these results are believed to result from the extended meta-stability of the cubic phase to reduced yttria levels at nanometric grain sizes.     

审慎校正功率因子

通用电源设计（即那些适应低于100V至高于240V交流输入的设计）的一个期望结果是，功率管理电路与电源无关，且设计者只需考虑那些与预期负载有关的问题。这种功率管理方法通过减少为全球客户群体服务所需的电源种类而能产生相当大的规模经济。类似的优势还能扩展到供应链、制造业与库存管理运作。