Two-Stage Change Detection for Synthetic Aperture Radar

Coherent change detection using paired synthetic aperture radar (SAR) images is often performed using a classical coherence estimator that is invariant to the true variances of the populations underlying each paired sample. While attractive, this estimator is biased and requires a significant number of samples to yield good performance. Increasing sample size often results in decreased image resolution. Thus, we propose the use of Berger's coherence estimate because, with the same number of pixels, the estimator effectively doubles the sample support without sacrificing resolution when the underlying population variances are equal or near equal. A potential drawback of this approach is that it is not invariant since its distribution depends on the pixel pair population variances. While Berger's estimator is inherently sensitive to the inequality of population variances, we propose a method of insulating the detector from this acuity. A two-stage change statistic is introduced to combine a noncoherent intensity change statistic given by the sample variance ratio, followed by the alternative Berger estimator, which assumes equal population variances. The first-stage detector identifies pixel pairs that have nonequal variances as changes caused by the displacement of sizeable object. The pixel pairs that are identified to have equal or near-equal variances in the first stage are used as an input to the second stage. The second-stage test uses the alternative Berger coherence estimator to detect subtle changes such as tire tracks and footprints. We show experimentally that the proposed method yields higher contrast SAR change detection images than the classical coherent change detector (state of the art), the alternative coherent change detector, and the intensity change detector. Experimental results are presented to show the effectiveness and robustness of the proposed algorithm for SAR change detection

Ghost crab burrow density at Watamu Marine National Park: an indicator of the impact of urbanisation and associated disturbance?

Ghost crab (Ocypode species) burrow densities have previously been used as an indicator of anthropogenic impact. This study aimed to assess the burrow density of Ocypode species (O. ryderi and O. cordimanus) at four sites across Watamu Marine National Park, Kenya. Two sites were in front of hotel complexes (denoting a high degree of urbanisation), and two were in front of residential housing among coastal scrub (denoting a low degree of urbanisation). The findings reveal significantly higher burrow densities at sites in front of residential housing, which was the less developed area. This provides further evidence that Ocypode burrow densities can be used, where other methods would be impractical, to estimate the impact of some human activities along beach fronts, such as at Watamu Marine National Park

Effects of Screening and Brief Intervention Training on Resident and Faculty Alcohol Intervention Behaviours: A Pre- Post-Intervention Assessment

Background: Many hazardous and harmful drinkers do not receive clinician advice to reduce their drinking. Previous studies suggest under-detection and clinician reluctance to intervene despite awareness of problem drinking (PD). The Healthy Habits Project previously reported chart review data documenting increased screening and intervention with hazardous and harmful drinkers after training clinicians and implementing routine screening. This report describes the impact of the Healthy Habits training program on clinicians\u27 rates of identification of PD, level of certainty in identifying PD and the proportion of patients given advice to reduce alcohol use, based on self-report data using clinician exit questionnaires. Methods: 28 residents and 10 faculty in a family medicine residency clinic completed four cycles of clinician exit interview questionnaires before and after screening and intervention training. Rates of identifying PD, level of diagnostic certainty, and frequency of advice to reduce drinking were compared across intervention status (pre vs. post). Findings were compared with rates of PD and advice to reduce drinking documented on chart review. Results: 1,052 clinician exit questionnaires were collected. There were no significant differences in rates of PD identified before and after intervention (9.8% vs. 7.4%, p = .308). Faculty demonstrated greater certainty in PD diagnoses than residents (p = .028) and gave more advice to reduce drinking (p = .042) throughout the program. Faculty and residents reported higher levels of diagnostic certainty after training (p = .039 and .030, respectively). After training, residents showed greater increases than faculty in the percentage of patients given advice to reduce drinking (p = .038), and patients felt to be problem drinkers were significantly more likely to receive advice to reduce drinking by all clinicians (50% vs. 75%, p = .047). The number of patients receiving advice to reduce drinking after program implementation exceeded the number of patients felt to be problem drinkers. Recognition rates of PD were four to eight times higher than rates documented on chart review (p = .028). Conclusion: This program resulted in greater clinician certainty in diagnosing PD and increases in the number of patients with PD who received advice to reduce drinking. Future programs should include booster training sessions and emphasize documentation of PD and brief intervention

Functional Group and Substructure Searching as a Tool in Metabolomics

BACKGROUND: A direct link between the names and structures of compounds and the functional groups contained within them is important, not only because biochemists frequently rely on literature that uses a free-text format to describe functional groups, but also because metabolic models depend upon the connections between enzymes and substrates being known and appropriately stored in databases. METHODOLOGY: We have developed a database named "Biochemical Substructure Search Catalogue" (BiSSCat), which contains 489 functional groups, >200,000 compounds and >1,000,000 different computationally constructed substructures, to allow identification of chemical compounds of biological interest. CONCLUSIONS: This database and its associated web-based search program (http://bisscat.org/) can be used to find compounds containing selected combinations of substructures and functional groups. It can be used to determine possible additional substrates for known enzymes and for putative enzymes found in genome projects. Its applications to enzyme inhibitor design are also discussed

Reduced occupancy of hedgehogs (Erinaceus europaeus) in rural England and Wales: the influence of habitat and an asymmetric intra-guild predator

Agricultural landscapes have become increasingly intensively managed resulting in population declines across a broad range of taxa, including insectivores such as the hedgehog (Erinaceus europaeus). Hedgehog declines have also been attributed to an increase in the abundance of badgers (Meles meles), an intra-guild predator. The status of hedgehogs across the rural landscape at large spatial scales is, however, unknown. In this study, we used footprint tracking tunnels to conduct the first national survey of rural hedgehog populations in England and Wales. Single and two-species occupancy modelling was used to quantify hedgehog occupancy in relation to habitat and predator covariates. Hedgehog occupancy was low (22% nationally), and significantly negatively related to badger sett density and positively related to the built environment. Hedgehogs were also absent from 71% of sites that had no badger setts, indicating that large areas of the rural landscape are not occupied by hedgehogs. Our results provide the first field based national survey of hedgehogs, providing a robust baseline for future monitoring. Furthermore, the combined effects of increasing badger abundance and intensive agriculture may have provided a perfect storm for hedgehogs in rural Britain, leading to worryingly low levels of occupancy over large spatial scales

RNA Is an Integral Component of Chromatin that Contributes to Its Structural Organization

Chromatin structure is influenced by multiples factors, such as pH, temperature, nature and concentration of counterions, post-translational modifications of histones and binding of structural non-histone proteins. RNA is also known to contribute to the regulation of chromatin structure as chromatin-induced gene silencing was shown to depend on the RNAi machinery in S. pombe, plants and Drosophila. Moreover, both in Drosophila and mammals, dosage compensation requires the contribution of specific non-coding RNAs. However, whether RNA itself plays a direct structural role in chromatin is not known. Here, we report results that indicate a general structural role for RNA in eukaryotic chromatin. RNA is found associated to purified chromatin prepared from chicken liver, or cultured Drosophila S2 cells, and treatment with RNase A alters the structural properties of chromatin. Our results indicate that chromatin-associated RNAs, which account for 2%–5% of total chromatin-associated nucleic acids, are polyA− and show a size similar to that of the DNA contained in the corresponding chromatin fragments. Chromatin-associated RNA(s) are not likely to correspond to nascent transcripts as they are also found bound to chromatin when cells are treated with α-amanitin. After treatment with RNase A, chromatin fragments of molecular weight >3.000 bp of DNA showed reduced sedimentation through sucrose gradients and increased sensitivity to micrococcal nuclease digestion. This structural transition, which is observed both at euchromatic and heterochromatic regions, proceeds without loss of histone H1 or any significant change in core-histone composition and integrity

Kernel bandwidth optimization in spike rate estimation

Kernel smoother and a time-histogram are classical tools for estimating an instantaneous rate of spike occurrences. We recently established a method for selecting the bin width of the time-histogram, based on the principle of minimizing the mean integrated square error (MISE) between the estimated rate and unknown underlying rate. Here we apply the same optimization principle to the kernel density estimation in selecting the width or “bandwidth” of the kernel, and further extend the algorithm to allow a variable bandwidth, in conformity with data. The variable kernel has the potential to accurately grasp non-stationary phenomena, such as abrupt changes in the firing rate, which we often encounter in neuroscience. In order to avoid possible overfitting that may take place due to excessive freedom, we introduced a stiffness constant for bandwidth variability. Our method automatically adjusts the stiffness constant, thereby adapting to the entire set of spike data. It is revealed that the classical kernel smoother may exhibit goodness-of-fit comparable to, or even better than, that of modern sophisticated rate estimation methods, provided that the bandwidth is selected properly for a given set of spike data, according to the optimization methods presented here