Robust Classification of Functional and Quantitative Image Data Using Functional Mixed Models

This paper describes how to perform classification of complex, high-dimensional functional data using the functional mixed model (FMM) framework. The FMM relates a functional response to a set of predictors through functional fixed and random effects, which allows it to account for various factors and between-function correlations. Classification is performed through training the model treating class as one of the fixed effects, and then predicting on the test data using posterior predictive probabilities of class. Through a Bayesian scheme, we are able to adjust for factors affecting both the functions and the class designations. While the method we present can be applied to any FMM-based method, we provide details for two specific Bayesian approaches: the Gaussian, wavelet-based functional mixed model (G-WFMM) and the robust, wavelet-based functional mixed model (R-WFMM). Both methods perform modeling in the wavelet space, which yields parsimonious representations for the functions, and can naturally adapt to local features and complex nonstationarities in the functions. The R-WFMM allows potentially heavier tails for features of the functions indexed by particular wavelet coefficients, leading to a down weighting of outliers that makes the method robust to outlying functions or regions of functions. The models are applied to a pancreatic cancer mass spectroscopy data set and compared with some other recently developed functional classification methods

Ultrasonic Attenuation and Backscatter Coefficient Estimates of Rodent-Tumor-Mimicking Structures: Comparison of Results among Clinical Scanners

In vivo estimations of the frequency-dependent acoustic attenuation (α) and backscatter (η) coefficients using radiofrequency (rf) echoes acquired with clinical ultrasound systems must be independent of the data acquisition setup and the estimation procedures. In a recent in vivo assessment of these parameters in rodent mammary tumors, overall agreement was observed among α and η estimates using data from four clinical imaging systems. In some cases, particularly in highly-attenuating heterogeneous tumors, multisystem variability was observed. This paper compares α and η estimates of a well-characterized rodent-tumor-mimicking homogeneous phantom scanned using seven transducers with the same four clinical imaging systems: a Siemens Acuson S2000, an Ultrasonix RP, a Zonare Z.one and a VisualSonics Vevo2100. α and η estimates of lesion-mimicking spheres in the phantom were independently assessed by three research groups, who analyzed their system\u27s rf echo signals. Imaging-system-based estimates of α and η of both lesion-mimicking spheres were comparable to through-transmission laboratory estimates and to predictions using Faran\u27s theory, respectively. A few notable variations in results among the clinical systems were observed but the average and maximum percent difference between α estimates and laboratory-assessed values was 11% and 29%, respectively. Excluding a single outlier dataset, the average and maximum average difference between η estimates for the clinical systems and values predicted from scattering theory was 16% and 33%, respectively. These results were an improvement over previous interlaboratory comparisons of attenuation and backscatter estimates. Although the standardization of our estimation methodologies can be further improved, this study validates our results from previous rodent breast-tumor model studies

A Comprehensive GC–MS Sub-Microscale Assay for Fatty Acids and its Applications

Fatty acid analysis is essential to a broad range of applications including those associated with the nascent algal biofuel and algal bioproduct industries. Current fatty acid profiling methods require lengthy, sequential extraction and transesterification steps necessitating significant quantities of analyte. We report the development of a rapid, microscale, single-step, in situ protocol for GC–MS lipid analysis that requires only 250 μg dry mass per sample. We furthermore demonstrate the broad applications of this technique by profiling the fatty acids of several algal species, small aquatic organisms, insects and terrestrial plant material. When combined with fluorescent techniques utilizing the BODIPY dye family and flow cytometry, this micro-assay serves as a powerful tool for analyzing fatty acids in laboratory and field collected samples, for high-throughput screening, and for crop assessment. Additionally, the high sensitivity of the technique allows for population analyses across a wide variety of taxa

Association of Different Iowa Livestock Truck Wash Stations Service Levels with Enterobacteriaceae Counts

Data from eighteen different truck washes were used to compare the association of different service levels with Enterobacteriaceae counts. Service levels were classified into three different categories; prewash (n=78), post wash with disinfectant (n=78), and post wash without disinfectant (n=12). A total of 168 drag swabs were used for collection for the purpose of this study. Prewash services were defined as trailers before they were scraped out and washed. Post wash with or without disinfectant services were defined as after the trailers were washed and disinfectant was or was not applied. Prewash trailers tended to have higher Enterobacteriaceae counts of around 5.0 Log10CFU/m2when compared to post wash with disinfectantEnterobacteriaceae counts of around 2.2 Log10CFU/m2 and post wash without disinfectant Enterobacteriaceae counts of around 2.7 Log10CFU/m2

Home Insulation for a Sustainable Future

Home Insulation for a Sustainable Future James Bigelow, Kalil Davis, David Breaux Home Innovation Research Labs reported that 71% of all insulation used by United States’ residential contractors is fiberglass based. This makes sense since fiberglass insulation is affordable, readily available, and easy to install. However, fiberglass has a negative impact on indoor air quality during construction; according to multiple reputable sources such as The Centers for Disease Control and Prevention (C.D.C.), this can lead to skin, eye, and airway irritation. Additionally, the manufacturing process for fiberglass insulation produces greenhouse gasses that are harmful to the environment. Herein, a case study will be conducted on a residential building that is under construction in Volusia County, Florida. When the constraints are defined, the use of alternative materials will be explored. This exploration will be referenced to three major factors, economics, effectiveness, and environmental effect. Along with the three factors listed, the project will be guided by the three overlapping circles model of sustainability. Initially, a research phase will be conducted to report alternate options for the replacement of fiberglass insulation. Then decision matrices will be used to determine the best alternative to fiberglass insulation. Each decision matrix will provide different criteria for the alternative insulations; economy, environment, and effectiveness. The alternative insulation will be evaluated based on sales data, impacts on human health and safety, and residential energy consumption. Sales will be analyzed using business data analytics, including profit, production costs, and units sold. Human health and safety will be measured through air quality tests and assessing any acute or chronic health effects or necessary personal protective equipment. Energy consumption will be determined by monthly gas and electricity usage for heating and cooling the building. These assessments are meant to represent the three primary dimensions of sustainability; Society, Economy, and Environment. To ensure the efficient use of resources and to meet stakeholder needs, a stakeholder analysis will be conducted. This involves identifying all parties impacted by the project and evaluating their level of influence and interest in the project. To conclude, the aim of this study is to identify and evaluate sustainable options of insulating residential homes. Currently the results are unclear and more research is required to determine a solution

Ethofumesate-resistant annual bluegrass (Poa annua) in grass seed production systems

The prolific seed production and polyploidy of annual bluegrass allow for the rapid development of herbicide resistance. Ethofumesate-resistant annual bluegrass plants were identified in the 1990s in grass seed production in Oregon, but their prevalence and distribution are not well documented. Therefore a dose–response experiment was initiated to determine the potential level of ethofumesate resistance in seed production systems. Seeds from 55 annual bluegrass populations were obtained from three sources: seed production fields (31 populations), the seed cleaning process (6 populations), and seed testing lots prior to retail distribution (18 populations). Additionally, two populations, one with known ethofumesate resistance and one with known susceptibility, were identified in preliminary testing and used as controls in this experiment. Seed from each collected population was increased. Individual seedlings were then transplanted into separate cone-tainers, grown to a size of 2 to 3 tillers in the greenhouse, and then sprayed using a compressed air track spray chamber with 10 doses of ethofumesate at 0, 0.56, 1.1, 2.8, 5.6, 8.4, 11.2, 16.8, 22.4, and 44.8 kg ai ha−1, with 0.84 to 2.2 kg ha−1 as the label application rate for perennial ryegrass. The resistant to susceptible ratio of populations across all sources ranged from 0.5 to 5.5. The most resistant populations found in production fields, seed cleaning, and seed testing lots had the effective dose necessary to kill 50% of the population (ED50) of 12.1, 9.4, and 13.1 kg ha−1, respectively. Furthermore, 68% of the populations found in production fields had ED50 higher than 6 kg ha−1, indicating common annual bluegrass resistance in grass seed production. As such, growers should implement integrated weed management strategies, as herbicides alone will likely be ineffective at controlling annual bluegrass

Radio Astronomy

Contains reports on seven research projects and research objectives.National Science Foundation (Grant AST77-06052)Joint Services Electronics Program (Contract DAAG29-78-C-0020)National Aeronautics and Space Administration (Contract NAS5-21980)U.S. Department of Commerce - National Oceanic and Atmospheric Administration (Grant 04-8-M01-1)National Aeronautics and Space Administration (Contract NAS5-22929)National Aeronautics and Space Administration (Contract NAS5-25091)National Science Foundation (Grant AST77-12960)National Science Foundation (Grant AST77-26896