Evaluation and application of micro-sampling system for inductively coupled plasma mass spectrometry

Two Meinhard microconcentric nebulizers, model AR30-07-FM02 and AR 30-07-FM005, were employed as a self-installed micro-sampling system for inductively coupled plasma-mass spectrometry (ICP-MS). The FM02 nebulizer at 22 muL/min of solution uptake rate gave the relative standard deviations of 7.6%, 3.0%, 2.7%, 1.8% for determinations (n = 10) of 20 mug/L Be, Co, In and Bi, respectively, and the detection limits (3s) of 0.14, 0.10, 0.02 and 0.01 mug/L for Be, Co In and Bi, respectively. The mass intensity of In-115 obtained by this micro-sampling system was 60% of that by conventional pneumatic nebulizer system at 1.3 mL/min. The analytical results for La, Ce, Pr and Nd in 20 muL Wistar rat amniotic fluid obtained by the present micro-sampling system were precisely in good agreement with those obtained using conventional pneumatic nebulization system.

Approximately Uniform Random Sampling in Sensor Networks

Recent work in sensor databases has focused extensively on distributed query problems, notably distributed computation of aggregates. Existing methods for computing aggregates broadcast queries to all sensors and use in-network aggregation of responses to minimize messaging costs. In this work, we focus on uniform random sampling across nodes, which can serve both as an alternative building block for aggregation and as an integral component of many other useful randomized algorithms. Prior to our work, the best existing proposals for uniform random sampling of sensors involve contacting all nodes in the network. We propose a practical method which is only approximately uniform, but contacts a number of sensors proportional to the diameter of the network instead of its size. The approximation achieved is tunably close to exact uniform sampling, and only relies on well-known existing primitives, namely geographic routing, distributed computation of Voronoi regions and von Neumann's rejection method. Ultimately, our sampling algorithm has the same worst-case asymptotic cost as routing a point-to-point message, and thus it is asymptotically optimal among request/reply-based sampling methods. We provide experimental results demonstrating the effectiveness of our algorithm on both synthetic and real sensor topologies.

Periodic Motion Detection and Estimation via Space-Time Sampling

A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.

Sampling Biases in IP Topology Measurements

Considerable attention has been focused on the properties of graphs derived from Internet measurements. Router-level topologies collected via traceroute studies have led some authors to conclude that the router graph of the Internet is a scale-free graph, or more generally a power-law random graph. In such a graph, the degree distribution of nodes follows a distribution with a power-law tail. In this paper we argue that the evidence to date for this conclusion is at best insufficient. We show that graphs appearing to have power-law degree distributions can arise surprisingly easily, when sampling graphs whose true degree distribution is not at all like a power-law. For example, given a classical Erdös-Rényi sparse, random graph, the subgraph formed by a collection of shortest paths from a small set of random sources to a larger set of random destinations can easily appear to show a degree distribution remarkably like a power-law. We explore the reasons for how this effect arises, and show that in such a setting, edges are sampled in a highly biased manner. This insight allows us to distinguish measurements taken from the Erdös-Rényi graphs from those taken from power-law random graphs. When we apply this distinction to a number of well-known datasets, we find that the evidence for sampling bias in these datasets is strong.

MosaicShape: Stochastic Region Grouping with Shape Prior

A novel method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multi-scale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework and solved by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. By this means, object segmentation and recognition are accomplished simultaneously. Within each sampling move during the simulation process,probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized parallel algorithm by Barbu and Zhu,combined with a large sampling jump and other implementation improvements, greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.

Generalized sampling using a compound-eye imaging system for multi-dimensional object acquisition.

In this paper, we propose generalized sampling approaches for measuring a multi-dimensional object using a compact compound-eye imaging system called thin observation module by bound optics (TOMBO). This paper shows the proposed system model, physical examples, and simulations to verify TOMBO imaging using generalized sampling. In the system, an object is modulated and multiplied by a weight distribution with physical coding, and the coded optical signal is integrated on to a detector array. A numerical estimation algorithm employing a sparsity constraint is used for object reconstruction.

A GLOBAL SAMPLING OF PIANO MUSIC FROM 1978 TO 2005

Pianists of the twenty-first century have a wealth of repertoire at their fingertips. They busily study music from the different periods -- Baroque, Classical, Romantic, and some of the twentieth century -- trying to understand the culture and performance practice of the time and the stylistic traits of each composer so they can communicate their music effectively. Unfortunately, this leaves little time to notice the composers who are writing music today. Whether this neglect proceeds from lack of time or lack of curiosity, I feel we should be connected to music that was written in our own lifetime, when we already understand the culture and have knowledge of the different styles that preceded us. Therefore, in an attempt to promote today’s composers, I have selected piano music written during my lifetime, to show that contemporary music is effective and worthwhile and deserves as much attention as the music that preceded it. This dissertation showcases piano music composed from 1978 to 2005. A point of departure in selecting the pieces for this recording project is to represent the major genres in the piano repertoire in order to show a variety of styles, moods, lengths, and difficulties. Therefore, from these recordings, there is enough variety to successfully program a complete contemporary recital from the selected works, and there is enough variety to meet the demands of pianists with different skill levels and recital programming needs. Since we live in an increasingly global society, music from all parts of the world is included to offer a fair representation of music being composed everywhere. Half of the music in this project comes from the United States. The other half comes from Australia, Japan, Russia, and Argentina. The composers represented in these recordings are: Lowell Liebermann, Richard Danielpour, Frederic Rzewski, Judith Lang Zaimont, Samuel Adler, Carl Vine, Nikolai Kapustin, Akira Miyoshi and Osvaldo Golijov. With the exception of one piano concerto, all the works are for solo piano. This recording project dissertation consists of two 60 minute CDs of selected repertoire, accompanied by a substantial document of in-depth program notes. The recordings are documented on compact discs that are housed within the University of Maryland Library System.

The ocean sampling day consortium.

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.

Book Review Sharon L. Lohr Sampling: Design and Analysis

There is no abstract for this record.

Distribution and abundance of sardine (Sardina pilchardus) eggs in the English Channel from Continuous Plankton Recorder sampling

Continuous Plankton Recorder (CPR) samples from the English Channel and adjacent Celtic shelf, taken over the period 1958-1980, were analysed for sardine (Sardina pilchardus) eggs. Results showed the progression of sardine spawning along the English Channel from west to east from March to August and a return from east to west from September to November. This corresponds with the two seasonal peaks of sardine egg abundance in the western Channel: the main summer peak being in May/June, with a smaller autumn peak in October/November. Long-term changes in sardine egg abundance in CPR samples showed a decline in summer spawning from the late 1960s, but no clear trend in autumn-spawned egg abundance. Similar patterns were observed in the numbers of sardine eggs sampled by conventional plankton net tows at the time-series Station L5 off Plymouth. This supports the use of the longer time-series of sardine egg data at L5 as being representative of a wider area and emphasizes the importance in continuation of the L5 time-series.