Structure and Recognition of Graphs with No 6-wheel Subdivision

The subgraph homeomorphism problem has been shown by Robertson and Seymour to be polynomial-time solvable for any fixed pattern graph H. The result, however, is not practical, involving constants that are worse than exponential in |H|. Practical algorithms have only been developed for a few specific pattern graphs, the most recent of these being the wheels with four and five spokes. This paper looks at the subgraph homeomorphism problem where the pattern graph is a wheel with six spokes. The main result is a theorem characterizing graphs that do not contain subdivisions of W ₆. We give an efficient algorithm for solving the subgraph homeomorphism problem for W ₆. We also give a strengthening of the previous W ₅ result.     

Benchmarking stereo-derived DSMs to lidar by land cover and slope for resource development in northern Ontario,Canada

Topographic and elevation data are essential in the development of supporting infrastructure around mining sites. The de facto standard for acquiring elevation data is through light detection and ranging (lidar). The high labour and monetary cost of acquiring lidar has fostered more cost-effective approaches for creating elevation models that use stereo photogrammetry. To assess the accuracy of stereo-photogrammetry-derived elevation models and their potential application, we benchmark satellite (Worldview-2) and aircraft (South Central Ontario Orthoimagery Project; SCOOP) stereo-derived digital surface models (DSMs) against a lidar-derived DSM. Our results show that both stereo-derived DSMs have strong monotonic correlations with lidar across a range of land-cover types and slopes. The overall vertical accuracy of Worldview-2 and SCOOP DSMs are similar and do not meet the United States National Digital Elevation Program (NDEP) standards. However, accuracy assessment across land-cover types and slope categories show that specific land cover types (i.e. grass, row crops/pasture, sparse vegetation and marsh) on gently sloping terrain compare well to lidar data and meet NDEP accuracy standards. We situate the presented research in the context of northern resource development and discuss opportunities to improve the vertical accuracy of stereo-derived DSMs, for example, through unmanned aerial systems.     

An alternative objective function for fitting regression trees to functional response variables

Analyses of systems that can be represented by functional responses are becoming common in many scientific disciplines. Functional regression trees (FRT) provide a methodology for modelling such systems. Recent work has focused on fitting models where the response variable is a probability density function, using a splitting criterion that is based on the sum of dissimilarities between the densities. We suggest a different criterion based on deviations of the densities from their mean. We provide motivation and justification for this criterion, and demonstrate its superior performance using an extensive simulation exercise. We discuss the computational aspects of the FRT procedure and show that substantial speed gains can be made through use of a dissimilarity matrix. Our results show that the proposed splitting criterion outperforms both the original and a splitting criterion based on Euclidean distance. Pointwise standard error curves for a predicted functional response can be generated through the fitting procedure, which we demonstrate in a case study with a forestry data set. Supplementary materials are available.     

Neuroproteomics and systems biology-based discovery of protein biomarkers for traumatic brain injury and clinical validation

The rapidly growing field of neuroproteomics has expanded to track global proteomic changes underlying various neurological conditions such as traumatic brain injury (TBI), stroke, and Alzheimer's disease. TBI remains a major health problem with approximately 2?million incidents occurring annually in the United States, yet no affective treatment is available despite several clinical trials. The absence of brain injury diagnostic biomarkers was identified as a significant road-block to therapeutic development for brain injury. Recently, the field of neuroproteomics has undertaken major advances in the area of neurotrauma research, where several candidate markers have been identified and are being evaluated for their efficacy as biological biomarkers in the field of TBI. One scope of this review is to evaluate the current status of TBI biomarker discovery using neuroproteomics techniques, and at what stage we are at in their clinical validation. In addition, we will discuss the need for strengthening the role of systems biology and its application to the field of neuroproteomics due to its integral role in establishing a comprehensive understanding of specific brain disorder and brain function in general. Finally, to achieve true clinical input of these neuroproteomic findings, these putative biomarkers should be validated using preclinical and clinical samples and linked to clinical diagnostic assays including ELISA or other high-throughput assays.     

Electrical reflection coefficient and velocity shift for groove gratings

The electrical reflection coefficient r(e) and velocity shift (Deltanu/nu)(e) for grooves has never been formulated. All previous calculations for r(e) and (Deltanu/nu)(e) have used formulas valid for the reflection of a surface acoustic wave (SAW) from an array of conducting strips. However, the discontinuity in electrical boundary conditions leading to these formulas does not exist in groove gratings. A new expression for the electrical reflection coefficient and velocity shift for some material overlays is derived from both the variational principle and perturbation theory. The results for various substrates are compared to show the agreement between the two approaches. The implications of this new formulation for the design of grooved arrays on various materials are discussed, effectively resolving the discrepancy between theory and experiment.     

Identifying Outliers in Correlated Water Quality Data

Evaluating water quality data for outliers is a good quality control/quality assessment procedure whether the data are used for monitoring or for modeling. Often water quality data are correlated, e.g., carbonaceous biochemical oxygen demand (CBOD) has some correlation with NH3. Univariate methods for identifying outliers do not consider the correlation between variables and may identify too many data points as outliers or miss observations which have extreme ratios between variables, e.g., a raw wastewater sample with relatively low CBOD but high NH3. Testing for outliers using multivariate methods such as the Mahalanobis distance, Jackknife distance, p-values, or Hadi’s automatically incorporates the correlation or covariance between variables and is fundamentally more correct. Such multivariate methods can better identify potential outliers and avoid eliminating valid data.     

The Serotonergic Agonists Quipazine, CGS-12066A, and α-Methylserotonin Alter Motor Activity and Induce Hindlimb Stepping in the Intact and Spinal Rat Fetus.

The effects of serotonergic agonists were examined in intact and spinal fetuses, using an in vivo fetal rat preparation. On Gestational Day 20, fetuses were prepared with a midthoracic or sham spinal transection. Dose-response curves were obtained for quipazine (nonselective 5-hydroxytryptamine [5-HT] agonist; 1.0-10.0 mg/kg), CGS-12066A (5-HT1B agonist; 1.0-30.0 mg/kg), and α-methylserotonin (α-Me-5-HT; 5-HT? agonist; 0.2-15.0 mg/kg). During a 10-min test, each of the agonists (delivered via intraperitoneal injection) influenced fetal behavior: They increased the occurrence of head movements, mouthing, and hindlimb stepping. Quipazine and α-Me-5-HT also promoted hindlimb activity in spinal fetuses. Thus, stimulation of the fetal 5-HT system modulates motor activity at multiple levels of the developing central nervous system. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Computer user verification using login string keystroke dynamics

The keystroke dynamics of a computer user's login string provide a characteristic pattern that can be used for identity verification. Timing vectors for several hundred login attempts were collected for ten “valid” users and ten “forgers”, and classification analysis was applied to discriminate between them. Three different classifiers were applied, and in each case the key hold times were more effective features for discrimination than the interkey times. Best performance was achieved by an inductive learning classifier using both interkey and hold times. A high rate of typographical errors during login entry is reported. In practice, these are usually corrected errors-that is, they are strings which include backspaces to correct earlier errors-but their presence confounds the use of typing-style analysis as a practical means of securing access to computer systems     

以公共结构及语言进行应用系统一体化

介绍了美国佛罗里达电力照明公司对主要业务系统基于公共结构及语言,进行信息集成的工作过程和经验,对企业信息一体化的技术内容和框架结构做了总体介绍,并根据应用实际阐述了公共信息模型的扩展,对其他企业开展信息系统一体化工作具有一定的借鉴作用.