Combining data from different algorithms to segment the skin-air interface in mammograms

This paper presents a method for combining several different estimates of the mammographic skin-air interface in order to eliminate noise inherent to each individual segmentation algorithm. Given that each algorithm provides a binary mask of the breast, the first step is to isolate pixels adjacent to the skin-air interface. A final estimate of the skin-air interface for each point results from the combination of skin-air interface location data from each procedure. Data for each point is grouped as a set, upon which statistical operators, such as the elimination of outliers, are applied. Since the skin-air interface is a continuous line, data from prior points is also used as an estimate of points that follow. Results are evaluated in terms of success with the combination of two skin-air interface segmentation algorithms. The resulting `hybrid' technique overcomes several problems that beset each individual algorith

An Introduction to the Source Concept for Antennas

Antenna parameters particularly relevant to electrically small antenna design are reviewed in this paper. Source current definitions are accentuated leading to the introduction of the source concept which advantageously utilize only spatially bounded quantities. The framework of the source concept incorporates powerful techniques such as structural and modal decomposition, operator’s inversion and current optimization, thus opening new, challenging possibilities for antenna design, analysis and synthesis

The DRIFT Project: Searching for WIMPS with a Directional Detector

A low pressure time projection chamber for the detection of WIMPs is discussed. Discrimination against Compton electron background in such a device should be very good, and directional information about the recoil atoms would be obtainable. If a full 3-D reconstruction of the recoil tracks can be achieved, Monte Carlo studies indicate that a WIMP signal could be identified with high confidence from as few as 30 detected WIMP-nucleus scattering events.Comment: 5 pages, 3 figures. Presented at Dark 98, Heidelberg, July 1998, and to appear in conference proceeding

Estimating the value of watershed services following forest restoration

Declining forest health, climate change, and development threaten the sustainability of water supplies in the western United States. While forest restoration may buffer threats to watershed services, funding shortfalls for landscape-scale restoration efforts limit management action. The hydrologic response and reduction in risk to watersheds following forest restoration treatments could create significant nonmarket benefits for downstream water users. Historic experimental watershed studies indicate a significant and positive response from forest thinning by a reallocation of water from evapotranspiration to surface-water yield. In this study, we estimate the willingness to pay (WTP) for improved watershed services for one group of downstream users, irrigators, following forest restoration activities. We find a positive and statistically significant WTP within our sample of $183.50 per household, at an aggregated benefit of more than$400,000 annually for 2181 irrigators. Our benefit estimate provides evidence that downstream irrigators may be willing to invest in landscape-scale forest restoration to maintain watershed services

ncRNA BC1 influences translation in the oocyte

Regulation of translation is essential for the diverse biological processes involved in development. Particularly, mammalian oocyte development requires the precisely controlled translation of maternal transcripts to coordinate meiotic and early embryo progression while transcription is silent. It has been recently reported that key components of mRNA translation control are short and long noncoding RNAs (ncRNAs). We found that the ncRNABrain cytoplasmic 1 (BC1) has a role in the fully grown germinal vesicle (GV) mouse oocyte, where is highly expressed in the cytoplasm associated with polysomes. Overexpression of BC1 in GV oocyte leads to a minute decrease in global translation with a significant reduction of specific mRNA translation via interaction with the Fragile X Mental Retardation Protein (FMRP). BC1 performs a repressive role in translation only in the GV stage oocyte without forming FMRP or Poly(A) granules. In conclusion, BC1 acts as the translational repressor of specific mRNAs in the GV stage via its binding to a subset of mRNAs and physical interaction with FMRP. The results reported herein contribute to the understanding of the molecular mechanisms of developmental events connected with maternal mRNA translation

Large Area Scene Selection Interface (LASSI). Methodology of Selecting Landsat Imagery for the Global Land Survey 2005

The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004-2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat 7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm's sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005

Faster subsequence recognition in compressed strings

Computation on compressed strings is one of the key approaches to processing massive data sets. We consider local subsequence recognition problems on strings compressed by straight-line programs (SLP), which is closely related to Lempel--Ziv compression. For an SLP-compressed text of length $\bar m$, and an uncompressed pattern of length $n$, C{\'e}gielski et al. gave an algorithm for local subsequence recognition running in time $O(\bar mn^2 \log n)$. We improve the running time to $O(\bar mn^{1.5})$. Our algorithm can also be used to compute the longest common subsequence between a compressed text and an uncompressed pattern in time $O(\bar mn^{1.5})$; the same problem with a compressed pattern is known to be NP-hard