Attitude angle effects on Nimbus-7 Scanning Multichannel Microwave Radiometer radiances and geophysical parameter retrievals

The attitude of the Nimbus-7 spacecraft has varied significantly over its lifetime. A summary of the orbital and long-term behavior of the attitude angles and the effects of attitude variations on Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures is presented. One of the principal effects of these variations is to change the incident angle at which the SMMR views the Earth's surface. The brightness temperatures depend upon the incident angle sensitivities of both the ocean surface emissivity and the atmospheric path length. Ocean surface emissivity is quite sensitive to incident angle variation near the SMMR incident angle, which is about 50 degrees. This sensitivity was estimated theoretically for a smooth ocean surface and no atmosphere. A 1-degree increase in the angle of incidence produces a 2.9 C increase in the retrieved sea surface temperature and a 5.7 m/sec decrease in retrieved sea surface wind speed. An incident angle correction is applied to the SMMR radiances before using them in the geophysical parameter retrieval algorithms. The corrected retrieval data is compared with data obtained without applying the correction

Soft Null Hypotheses: A Case Study of Image Enhancement Detection in Brain Lesions

This work is motivated by a study of a population of multiple sclerosis (MS) patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to identify active brain lesions. At each visit, a contrast agent is administered intravenously to a subject and a series of images is acquired to reveal the location and activity of MS lesions within the brain. Our goal is to identify and quantify lesion enhancement location at the subject level and lesion enhancement patterns at the population level. With this example, we aim to address the difficult problem of transforming a qualitative scientific null hypothesis, such as "this voxel does not enhance", to a well-defined and numerically testable null hypothesis based on existing data. We call the procedure "soft null hypothesis" testing as opposed to the standard "hard null hypothesis" testing. This problem is fundamentally different from: 1) testing when a quantitative null hypothesis is given; 2) clustering using a mixture distribution; or 3) identifying a reasonable threshold with a parametric null assumption. We analyze a total of 20 subjects scanned at 63 visits (~30Gb), the largest population of such clinical brain images

Improved Noisy Student Training for Automatic Speech Recognition

Recently, a semi-supervised learning method known as "noisy student training" has been shown to improve image classification performance of deep networks significantly. Noisy student training is an iterative self-training method that leverages augmentation to improve network performance. In this work, we adapt and improve noisy student training for automatic speech recognition, employing (adaptive) SpecAugment as the augmentation method. We find effective methods to filter, balance and augment the data generated in between self-training iterations. By doing so, we are able to obtain word error rates (WERs) 4.2%/8.6% on the clean/noisy LibriSpeech test sets by only using the clean 100h subset of LibriSpeech as the supervised set and the rest (860h) as the unlabeled set. Furthermore, we are able to achieve WERs 1.7%/3.4% on the clean/noisy LibriSpeech test sets by using the unlab-60k subset of LibriLight as the unlabeled set for LibriSpeech 960h. We are thus able to improve upon the previous state-of-the-art clean/noisy test WERs achieved on LibriSpeech 100h (4.74%/12.20%) and LibriSpeech (1.9%/4.1%).Comment: 5 pages, 5 figures, 4 tables; v2: minor revisions, reference adde

Evaluation Of Dye-micelle Binding Constants Using Diffusion Sensitive Band Broadening Effects

The diffusion coefficients of small solutes can be significantly altered by the presence of association colloids such as micelles. A relationship is utilized that relates the diffusion coefficient of a solute to its partitioning or binding behavior to a micellar pseudo phase. The Taylor-Aris dispersion method was used to evaluate the diffusion coefficient of several dyes in the presence and absence of sodium dodecyl sulfate micelles. With this approach, all binding constants can be determined easily and reproducibly. The theory, experimental approach, and advantages of this technique are discussed. © 1988

Spatial Effects in Energy-Efficient Residential HVAC Technology Adoption

Preprint; final version published as: Noonan, D. S., Hsieh, L.-H. C., & Matisoff, D. (2013). Spatial Effects in Energy-Efficient Residential HVAC Technology Adoption. Environment and Behavior, 45(4), 476–503. doi:10.1177/0013916511421664If your neighborhood adopts greener, energy-efficient residential heating, ventilating, and air conditioning (HVAC) systems, will your proenvironmental behavior become contagious, spilling over into adjacent neighborhoods’ HVAC adoptions? Objective data on more than 300,000 detailed single-family house sale records in the Greater Chicago area from 1992 to 2004 are aggregated to census block-group neighborhoods to answer that question. Spatial lag regression models show that spatial dependence or “contagion” exists for neighborhood adoption of energy-efficient HVACs. Specifically, if 625 of 726 homes in a demonstration neighborhood upgraded to green HVAC, data of this study predict that at least 98 upgrades would occur in adjacent neighborhoods, more than doubling their baseline adoption rates. This spatial multiplier substantially magnifies the effects of factors affecting adoption rates. These results have important policy implications, especially in the context of new standards for neighborhood development, such as Leadership in Energy and Environmental Design (LEED) or Low-Impact Development standards

Economic, sociological, and neighbor dimensions of energy efficiency adoption behaviors: Evidence from the U.S. residential heating and air conditioning market

This study identifies factors that affect the adoption behavior for residential Heating, Ventilating, and Air Conditioning (HVAC) systems, including a spatial and temporal contagion effect, house characteristics, and other economic and contextual factors. The study draws on a dataset of house sale records in the greater Chicago area, spanning 1992–2004. First-differenced models and restricting the sample to new construction allow separate identification of adoption determinants for homeowners and for developers, respectively. We show that attributes of the building stock and demographics influence adoption decisions of both homeowners and developers. This includes a strong influence of square footage, a modest spatial clustering effect for existing homes, a consistent deterrent effect of higher property tax rates, and a positive influence of neighborhood education levels. Adoption decisions for existing homeowners appear to be driven by different factors than sellers of newly constructed homes. Adoption coincided with multi-story homes for developers, and neighbor adoption rates predicted adoption by existing homeowners but not developers. The results highlight the need for more research into the social context of energy efficiency investment