Matlab application for fitting progress curves to the Equilibrium Model

The general procedures for carrying out the necessary rate determinations required for accurate determination of the Equilibrium Model parameters, and fitting this data to the mathematical model to generate the parameters, are described in "Peterson, M.E., Daniel, R.M., Danson, M.J. & Eisenthal, R. (2007) The dependence of enzyme activity on temperature: determination and validation of parameters. Biochemical Journal, 402, 331-337". It should be borne in mind that the Equilibrium Model equation contains exponentials of exponentials – quite small deviations from ideal behaviour, or a failure to obtain true Vmax values, may lead to difficulty in obtaining reliable Equilibrium Model parameters

Optical Continuum and Emission-Line Variability of Seyfert 1 Galaxies

We present the light curves obtained during an eight-year program of optical spectroscopic monitoring of nine Seyfert 1 galaxies: 3C 120, Akn 120, Mrk 79, Mrk 110, Mrk 335, Mrk 509, Mrk 590, Mrk 704, and Mrk 817. All objects show significant variability in both the continuum and emission-line fluxes. We use cross-correlation analysis to derive the sizes of the broad Hbeta-emitting regions based on emission-line time delays, or lags. We successfully measure time delays for eight of the nine sources, and find values ranging from about two weeks to a little over two months. Combining the measured lags and widths of the variable parts of the emission lines allows us to make virial mass estimates for the active nucleus in each galaxy. The virial masses are in the range 10^{7-8} solar masses.Comment: 24 pages, 16 figures. Accepted for publication in Ap

Using Regional Economic Analysis Tools to Address Land Use Planning Issues

This article presents an example of how Extension economists and local Extension educators can use local economic information along with readily available data and tools to provide relevant factual information to help contextualize problems and evaluate alternative outcomes related to land use planning (especially land use planning focused on farmland preservation). The focus of this article is on how such information was developed, delivered, and used to help local policy makers and citizens make better informed decisions in a county with highly productive agriculture and heavy pressure from suburban and rural residential sprawl

Time-averaged aerodynamic loads on the vane sets of the 40- by 80-foot and 80- by 120-foot wind tunnel complex

Time-averaged aerodynamic loads are estimated for each of the vane sets in the National Full-Scale Aerodynamic Complex (NFAC). The methods used to compute global and local loads are presented. Experimental inputs used to calculate these loads are based primarily on data obtained from tests conducted in the NFAC 1/10-Scale Vane-Set Test Facility and from tests conducted in the NFAC 1/50-Scale Facility. For those vane sets located directly downstream of either the 40- by 80-ft test section or the 80- by 120-ft test section, aerodynamic loads caused by the impingement of model-generated wake vortices and model-generated jet and propeller wakes are also estimated

Optimal band selection for dimensionality reduction of hyperspectral imagery

Hyperspectral images have many bands requiring significant computational power for machine interpretation. During image pre-processing, regions of interest that warrant full examination need to be identified quickly. One technique for speeding up the processing is to use only a small subset of bands to determine the 'interesting' regions. The problem addressed here is how to determine the fewest bands required to achieve a specified performance goal for pixel classification. The band selection problem has been addressed previously Chen et al., Ghassemian et al., Henderson et al., and Kim et al.. Some popular techniques for reducing the dimensionality of a feature space, such as principal components analysis, reduce dimensionality by computing new features that are linear combinations of the original features. However, such approaches require measuring and processing all the available bands before the dimensionality is reduced. Our approach, adapted from previous multidimensional signal analysis research, is simpler and achieves dimensionality reduction by selecting bands. Feature selection algorithms are used to determine which combination of bands has the lowest probability of pixel misclassification. Two elements required by this approach are a choice of objective function and a choice of search strategy

A Comparison of Static Stretching Versus Combined Static and Ballistic Stretching in Active Knee Range of Motion

Background: There is continued controversy related to flexibility gains from different stretching protocols and within single protocols. Stretching methods include static, ballistic, dynamic, and proprioceptive neuromuscular facilitation (PNF). A combination of stretching methods may be an improved way to increase active knee range of motion (ROM). This study evaluated a single program formulated with static and ballistic components. Objective: To compare active knee ROM following stretching programs which either included combined static and ballistic stretching (CSBS) or static stretching (SS) alone. It was hypothesized that CSBS would show a greater increase in active knee ROM than SS. Setting: The pre- and post- measurements were performed in a laboratory. Subjects were randomly assigned to either treatment group or a non-stretching control group and given written instructions on how to perform their designated protocol at home. Subjects: Forty-three (33M, 10F) healthy collegiate aged participants (24.0 + 3.69 yrs, 176.21 + 10.0 cm, 78.15 + 12.93 kg) with no history of injury to the lower extremity or low back for the previous 6 months were eligible to participate in the study. Interventions: Two treatment groups either performed SS or CSBS for 30 seconds on each leg, twice a day for 2 weeks. All subjects but 3 provided both legs, and each leg was evaluated separately, providing 83 total measurements. Main Outcome Measures: A Johnson Digital Inclinometer was used to measure active knee extension. A mixed ANOVA with a Tukey post hoc test was used for statistical analysis. Results: There was no statistically significant difference in active knee ROM between groups at the pre-test, F(2,80)=1.062, p=.351, partial ƞ2=.026 (SS: 52.56 + 7.50º, CSBS: 49.84 + 8.91⁰, control: 49.39 + 10.09⁰). There was a statistically significant difference in active knee ROM between groups at the post-test, F(2,80)=29.034, p .05). There was homogeneity of covariance’s, as assessed by Box\u27s test of equality of covariance matrices (p = .076). There was homogeneity of variances, as assessed by Levene\u27s test of homogeneity of variance (p\u3e.05). Conclusions: SS and CSBS are equally effective for improving active knee ROM. A trend indicating CSBS showing only slightly greater differences may be due to limited time allowed to master the CSBS method, with no supervision during stretching sessions

Sequence Pattern Mining with Variables

Sequence pattern mining (SPM) seeks to find multiple items that commonly occur together in a specific order. One common assumption is that all of the relevant differences between items are captured through creating distinct items, e.g., if color matters then the same item in two different colors would have two items created, one for each color. In some domains, that is unrealistic. This paper makes two contributions. The first extends SPM algorithms to allow item differentiation through attribute variables for domains with large numbers of items, e.g, by having one item with a variable with a color attribute rather than distinct items for each color. It demonstrates this by incorporating variables into Discontinuous Varied Order Sequence Mining (DVSM). The second contribution is the creation of Sequence Mining of Temporal Clusters (SMTC), a new SPM that addresses the interleaving issue common to SPM algorithms. Most SPM algorithms address interleaving by using a distance measure to separate co-occurring sequences. SMTC addresses interleaving by clustering all subsets of temporally close items and deferring the sequencing of mined patterns until the entire dataset if examined. Evaluation of the SPM algorithms on a digital forensics media analysis task results in a 96% reduction in terms to review, 100% detection of true positives and no false positives