Predicting detection probabilities for gas mixtures over HSI backgrounds

Detecting and identifying weak gaseous plumes using thermal image data acquired by airborne detectors is an area of ongoing research. This contribution investigates the relative detectability of gas mixtures over different backgrounds and a range of plume temperatures that are warmer and cooler than the ground. The focus of this analysis to support mission planning. When the mission is intended to collect evidence of particular chemicals, the analysis presented is this report can be used to determine conditions under which useful data can be acquired. Initial analyses can be used to determine whether LWIR is useful for the anticipated gas, temperature, and background combination

Predicting the Detectability of Thin Gaseous Plumes in Hyperspectral Images Using Basis Vectors

This paper describes a new method for predicting the detectability of thin gaseous plumes in hyperspectral images. The novelty of this method is the use of basis vectors for each of the spectral channels of a collection instrument to calculate noise-equivalent concentration-pathlengths instead of matching scene pixels to absorbance spectra of gases in a library. This method provides insight into regions of the spectrum where gas detection will be relatively easier or harder, as influenced by ground emissivity, temperature contrast, and the atmosphere. Our results show that data collection planning could be influenced by information about when potential plumes are likely to be over background segments that are most conducive to detection

Effect of Background Emissivity on Gas Detection in Thermal Hyperspectral Imagery

Detecting and identifying weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temper- ature, and background clutter. This paper presents an analysis of one formulation of the physics-based radiance model, which describes at-sensor observed radiance. The background emissivity and plume/ground temperatures are isolated, and their effects on net chemical signal are described. This analysis shows that the plume’s physical state, emission or absorption, is directly dependent on the background emissivity. It then describes what conditions on the background emissivity have inhibiting effects on the net chemical signal. These claims are illustrated by analyzing synthetic hyperspectral imaging data with the Adaptive Matched Filter using four chemicals and three distinct background emissivities. Two chemicals (Carbontetrachloride and Tetraflourosilane) in the analysis had a very strong relationship with the background emissivities: they exhibited absorbance over a small range of wavenumbers and the background emissivities showed a consistent ordering at these wavenumbers. Analysis of simulated hyperspectral images containing these chemicals showed complete agreement with the analysis of the physics-based model that described when the background emissivities would have inhibiting effects on gas detection. The other chemicals considered (Ammonia and Tributylphosphate) exhibited very complex absorbance structure across the longwave infrared spectrum. Analysis of images containing these chemicals revealed that the the analysis of the physics-based model did not hold completely for these complex chemicals but did suggest that gas detection was dominated by their dominant absorbance features. These results provide some explanation of the effect of the background emissivity on gas detection and a more general exploration of gas absorbance/background emissivity variability and their effects on gas detection is warranted.

An Approach for Assessing the Signature Quality of Various Chemical Assays when Predicting the Culture Media Used to Grow Microorganisms

We demonstrate an approach for assessing the quality of a signature system designed to predict the culture medium used to grow a microorganism. The system was comprised of four chemical assays designed to identify various ingredients that could be used to produce the culture medium. The analytical measurements resulting from any combination of these four assays can be used in a Bayesian network to predict the probabilities that the microorganism was grown using one of eleven culture media. We evaluated combinations of the signature system by removing one or more of the assays from the Bayes network. We measured and compared the quality of the various Bayes nets in terms of fidelity, cost, risk, and utility, a method we refer to as Signature Quality Metric

Individual exposures to drinking water trihalomethanes, low birth weight and small for gestational age risk: a prospective Kaunas cohort study

<p>Abstract</p> <p>Background</p> <p>Evidence for an association between exposure during pregnancy to trihalomethanes (THMs) in drinking water and impaired fetal growth is still inconsistent and inconclusive, in particular, for various exposure routes. We examined the relationship of individual exposures to THMs in drinking water on low birth weight (LBW), small for gestational age (SGA), and birth weight (BW) in singleton births.</p> <p>Methods</p> <p>We conducted a cohort study of 4,161 pregnant women in Kaunas (Lithuania), using individual information on drinking water, ingestion, showering and bathing, and uptake factors of THMs in blood, to estimate an internal dose of THM. We used regression analysis to evaluate the relationship between internal THM dose and birth outcomes, adjusting for family status, education, smoking, alcohol consumption, body mass index, blood pressure, ethnic group, previous preterm, infant gender, and birth year.</p> <p>Results</p> <p>The estimated internal dose of THMs ranged from 0.0025 to 2.40 mg/d. We found dose-response relationships for the entire pregnancy and trimester-specific THM and chloroform internal dose and risk for LBW and a reduction in BW. The adjusted odds ratio for third tertile vs. first tertile chloroform internal dose of entire pregnancy was 2.17, 95% CI 1.19-3.98 for LBW; the OR per every 0.1 μg/d increase in chloroform internal dose was 1.10, 95% CI 1.01-1.19. Chloroform internal dose was associated with a slightly increased risk of SGA (OR 1.19, 95% CI 0.87-1.63 and OR 1.22, 95% CI 0.89-1.68, respectively, for second and third tertile of third trimester); the risk increased by 4% per every 0.1 μg/d increase in chloroform internal dose (OR 1.04, 95% CI 1.00-1.09).</p> <p>Conclusions</p> <p>THM internal dose in pregnancy varies substantially across individuals, and depends on both water THM levels and water use habits. Increased internal dose may affect fetal growth.</p

Myocardial energy depletion and dynamic systolic dysfunction in hypertrophic cardiomyopathy

Evidence indicates that anatomical and physiological phenotypes of hypertrophic cardiomyopathy (HCM) stem from genetically mediated, inefficient cardiomyocyte energy utilization, and subsequent cellular energy depletion. However, HCM often presents clinically with normal left ventricular (LV) systolic function or hyperkinesia. If energy inefficiency is a feature of HCM, why is it not manifest as resting LV systolic dysfunction? In this Perspectives article, we focus on an idiosyncratic form of reversible systolic dysfunction provoked by LV obstruction that we have previously termed the 'lobster claw abnormality' — a mid-systolic drop in LV Doppler ejection velocities. In obstructive HCM, this drop explains the mid-systolic closure of the aortic valve, the bifid aortic pressure trace, and why patients cannot increase stroke volume with exercise. This phenomenon is characteristic of a broader phenomenon in HCM that we have termed dynamic systolic dysfunction. It underlies the development of apical aneurysms, and rare occurrence of cardiogenic shock after obstruction. We posit that dynamic systolic dysfunction is a manifestation of inefficient cardiomyocyte energy utilization. Systolic dysfunction is clinically inapparent at rest; however, it becomes overt through the mechanism of afterload mismatch when LV outflow obstruction is imposed. Energetic insufficiency is also present in nonobstructive HCM. This paradigm might suggest novel therapies. Other pathways that might be central to HCM, such as myofilament Ca2+ hypersensitivity, and enhanced late Na+ current, are discussed

Aggression, anxiety and vocalizations in animals: GABA A and 5-HT anxiolytics

A continuing challenge for preclinical research on anxiolytic drugs is to capture the affective dimension that characterizes anxiety and aggression, either in their adaptive forms or when they become of clinical concern. Experimental protocols for the preclinical study of anxiolytic drugs typically involve the suppression of conditioned or unconditioned social and exploratory behavior (e.g., punished drinking or social interactions) and demonstrate the reversal of this behavioral suppression by drugs acting on the benzodiazepine-GABA A complex. Less frequently, aversive events engender increases in conditioned or unconditioned behavior that are reversed by anxiolytic drugs (e.g., fear-potentiated startle). More recently, putative anxiolytics which target 5-HT receptor subtypes produced effects in these traditional protocols that often are not systematic and robust. We propose ethological studies of vocal expressions in rodents and primates during social confrontations, separation from social companions, or exposure to aversive environmental events as promising sources of information on the affective features of behavior. This approach focusses on vocal and other display behavior with clear functional validity and homology. Drugs with anxiolytic effects that act on the benzodiazepine-GABA A receptor complex and on 5-HT 1A receptors systematically and potently alter specific vocalizations in rodents and primates in a pharmacologically reversible manner; the specificity of these effects on vocalizations is evident due to the effectiveness of low doses that do not compromise other physiological and behavioral processes. Antagonists at the benzodiazepine receptor reverse the effects of full agonists on vocalizations, particularly when these occur in threatening, startling and distressing contexts. With the development of antagonists at 5-HT receptor subtypes, it can be anticipated that similar receptor-specificity can be established for the effects of 5-HT anxiolytics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46351/1/213_2005_Article_BF02245590.pd

Predicting detection probabilities for gas mixtures over HSI backgrounds

Detecting and identifying weak gaseous plumes using thermal image data acquired by airborne detectors is an area of ongoing research. This contribution investigates the relative detectability of gas mixtures over different backgrounds and a range of plume temperatures that are warmer and cooler than the ground. The focus of this analysis to support mission planning. When the mission is intended to collect evidence of particular chemicals, the analysis presented is this report can be used to determine conditions under which useful data can be acquired. Initial analyses can be used to determine whether LWIR is useful for the anticipated gas, temperature, and background combination

Statistics for the Relative Detectability of Chemicals in Weak Gaseous Plumes in LWIR Hyperspectral Imagery

The detection and identification of weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based model that describes the at-sensor observed radiance. The motivating question for the analyses performed in this paper is as follows. Given a set of backgrounds, is there a way to predict the background over which the probability of detecting a given chemical will be the highest? Two statistics were developed to address this question. These statistics incorporate data from the long-wave infrared band to predict the background over which chemical detectability will be the highest. These statistics can be computed prior to data collection. As a preliminary exploration into the predictive ability of these statistics, analyses were performed on synthetic hyperspectral images. Each image contained one chemical (either carbon tetrachloride or ammonia) spread across six distinct background types. The statistics were used to generate predictions for the background ranks. Then, the predicted ranks were compared to the empirical ranks obtained from the analyses of the synthetic images. For the simplified images under consideration, the predicted and empirical ranks showed a promising amount of agreement. One statistic accurately predicted the best and worst background for detection in all of the images. Future work may include explorations of more complicated plume ingredients, background types, and noise structures