Ocean color, a three component system?

This study measures the concentrations of phytoplankton chlorophyll and yellow substance in the coastal waters of the Gulf of Maine. Sea surface observations attempt to delineate the principal biochemical parameters responsible for sea surface color. It is shown that the reddish-brown water changed to a blue-green in the open gulf

Non-parametric statistical thresholding for sparse magnetoencephalography source reconstructions.

Uncovering brain activity from magnetoencephalography (MEG) data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources. Sparse reconstruction algorithms, such as Champagne, show great promise in that they provide focal brain activations robust to these confounds. In this paper, we address the technical considerations of statistically thresholding brain images obtained from sparse reconstruction algorithms. The source power distribution of sparse algorithms makes this class of algorithms ill-suited to "conventional" techniques. We propose two non-parametric resampling methods hypothesized to be compatible with sparse algorithms. The first adapts the maximal statistic procedure to sparse reconstruction results and the second departs from the maximal statistic, putting forth a less stringent procedure that protects against spurious peaks. Simulated MEG data and three real data sets are utilized to demonstrate the efficacy of the proposed methods. Two sparse algorithms, Champagne and generalized minimum-current estimation (G-MCE), are compared to two non-sparse algorithms, a variant of minimum-norm estimation, sLORETA, and an adaptive beamformer. The results, in general, demonstrate that the already sparse images obtained from Champagne and G-MCE are further thresholded by both proposed statistical thresholding procedures. While non-sparse algorithms are thresholded by the maximal statistic procedure, they are not made sparse. The work presented here is one of the first attempts to address the problem of statistically thresholding sparse reconstructions, and aims to improve upon this already advantageous and powerful class of algorithm

How Many Templates for GW Chirp Detection? The Minimal-Match Issue Revisited

In a recent paper dealing with maximum likelihood detection of gravitational wave chirps from coalescing binaries with unknown parameters we introduced an accurate representation of the no-signal cumulative distribution of the supremum of the whole correlator bank. This result can be used to derive a refined estimate of the number of templates yielding the best tradeoff between detector's performance (in terms of lost signals among those potentially detectable) and computational burden.Comment: submitted to Class. Quantum Grav. Typing error in eq. (4.8) fixed; figure replaced in version

Deep-space navigation applications of improved ground-based optical astrometry

Improvements in ground-based optical astrometry will eventually be required for navigation of interplanetary spacecraft when these spacecraft communicate at optical wavelengths. Although such spacecraft may be some years off, preliminary versions of the astrometric technology can also be used to obtain navigational improvements for the Galileo and Cassini missions. This article describes a technology-development and observational program to accomplish this, including a cooperative effort with U.S. Naval Observatory Flagstaff Station. For Galileo, Earth-based astrometry of Jupiter's Galilean satellites may improve their ephemeris accuracy by a factor of 3 to 6. This would reduce the requirements for onboard optical navigation pictures, so that more of the data transmission capability (currently limited by high-gain antenna deployment problems) can be used for science data. Also, observations of European Space Agency (ESA) Hipparcos stars with asteroid 243 Ida may provide significantly improved navigation accuracy for a planned August 1993 Galileo spacecraft encounter

Systems analysis for ground-based optical navigation

Deep-space telecommunications systems will eventually operate at visible or near-infrared regions to provide increased information return from interplanetary spacecraft. This would require an onboard laser transponder in place of (or in addition to) the usual microwave transponder, as well as a network of ground-based and/or space-based optical observing stations. This article examines the expected navigation systems to meet these requirements. Special emphasis is given to optical astrometric (angular) measurements of stars, solar system target bodies, and (when available) laser-bearing spacecraft, since these observations can potentially provide the locations of both spacecraft and target bodies. The role of astrometry in the navigation system and the development options for astrometric observing systems are also discussed

Outlier Detection Using Nonconvex Penalized Regression

This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the $n$ data points. We then apply a regularization favoring a sparse vector of mean shift parameters. The usual $L_1$ penalty yields a convex criterion, but we find that it fails to deliver a robust estimator. The $L_1$ penalty corresponds to soft thresholding. We introduce a thresholding (denoted by $\Theta$) based iterative procedure for outlier detection ($\Theta$-IPOD). A version based on hard thresholding correctly identifies outliers on some hard test problems. We find that $\Theta$-IPOD is much faster than iteratively reweighted least squares for large data because each iteration costs at most $O(np)$ (and sometimes much less) avoiding an $O(np^2)$ least squares estimate. We describe the connection between $\Theta$-IPOD and $M$-estimators. Our proposed method has one tuning parameter with which to both identify outliers and estimate regression coefficients. A data-dependent choice can be made based on BIC. The tuned $\Theta$-IPOD shows outstanding performance in identifying outliers in various situations in comparison to other existing approaches. This methodology extends to high-dimensional modeling with $p\gg n$, if both the coefficient vector and the outlier pattern are sparse

Analysis of heteroantisera to cells from human malignant effusions by immunofluorescence and protein A binding.

Using cultured cells derived from human malignant effusions, hetero-antisera were raised in rabbits. The antisera were sequentially absorbed on various human non-tumour cells, reactivity being monitored by immunofluorescence and 125I-labelled staphylococcal protein A assays. The absorbed antisera possessed common reactivity to all tumour cells assayed. This reactivity was not histogenically determined, and our data suggest that it was not directed to oncofoetal antigens

Coating thermal noise for arbitrary shaped beams

Advanced LIGO's sensitivity will be limited by coating noise. Though this noise depends on beam shape, and though nongaussian beams are being seriously considered for advanced LIGO, no published analysis exists to compare the quantitative thermal noise improvement alternate beams offer. In this paper, we derive and discuss a simple integral which completely characterizes the dependence of coating thermal noise on shape. The derivation used applies equally well, with minor modifications, to all other forms of thermal noise in the low-frequency limit.Comment: 3 pages. Originally performed in August 2004. Submitted to CQG. (v2) : Corrections from referee and other