Detection and quantitative analysis of polychlorinated biphenyls in tilapia from Hawaiian waters

The purpose of this study was to investigate polychlorinated biphenyls (PCBs) contamination in tilapia (Oreochromis mossambicus) collected from the Manna stream and Ala Wai Canal of O'ahu, an island of the geographically isolated Hawaiian archipelago. Our results show that the average concentrations of PCBs varied from 51.90 to 89.42 ng g(-1) lipid weight for the sampling sites. Relative toxic potencies (RTPs) and toxic equivalencies (TEQs) were determined to be 20.38-40.60 ng TCDD g(-1) lipid weight and 2.89-4.17 ng TEQ g(-1) lipid weight by 7-ethoxy-resorufin-O-deethylase (EROD) activity analysis and calculation of PCB concentrations based on toxic equivalency factors (TEFs), respectively. Penta-chlorinated congeners were found to be predominant, which revealed that Aroclor 1254 was a possible major source of PCBs in our fish samples. PCB 118, an indicator PCBs, constituted more than 55% and 30% of the total PCBs and TEQs, respectively. In addition, PCB 118 was found to have a linear correlation to the total PCBs (R = 0.975) and TEQs (R = 0.782). Detection of concentrated PCBs in Hawaiian waters suggests a potentially adverse impact of this pollutant on human health, as well as ecological systems, and suggests the necessity of environmental monitoring and hazard assessment of PCBs within the Hawaiian Islands. (c) 2008 Published by Elsevier Ltd.

Detection of polybrominated diphenyl ethers in tilapia (Oreochromis mossambicus) from O'ahu, Hawai'i

Polybrominated diphenyl ethers (PBDEs) have been detected for the first time at a range from 231.58 to 685.61 ng g(-1) lipid weight in the muscles of tilapia ( Oreochromis mossambicus) collected from O'ahu, an island of the geographically isolated Hawaiian archipelago.

When Does a Polynomial Over a Finite Field Permute the Elements of the Field?

We present a class of indecomposable polynomials of non prime-power degree over the finite field of two elements which are permutation polynomials on infinitely many finite extensions of the field. The associated geometric monodromy groups are the simple ...

A Global Crisis for Seagrass Ecosystems

Seagrasses, marine flowering plants, have a long evolutionary history but are now challenged with rapid environmental changes as a result of coastal human population pressures. Seagrasses provide key ecological services, including organic carbon production and export, nutrient cycling, sediment stabilization, enhanced biodiversity, and trophic transfers to adjacent habitats in tropical and temperate regions. They also serve as “coastal canaries,” global biological sentinels of increasing anthropogenic influences in coastal ecosystems, with large-scale losses reported worldwide. Multiple stressors, including sediment and nutrient runoff, physical disturbance, invasive species, disease, commercial fishing practices, aquaculture, overgrazing, algal blooms, and global warming, cause seagrass declines at scales of square meters to hundreds of square kilometers. Reported seagrass losses have led to increased awareness of the need for seagrass protection, monitoring, management, and restoration. However, seagrass science, which has rapidly grown, is disconnected from public awareness of seagrasses, which has lagged behind awareness of other coastal ecosystems. There is a critical need for a targeted global conservation effort that includes a reduction of watershed nutrient and sediment inputs to seagrass habitats and a targeted educational program informing regulators and the public of the value of seagrass meadows.

Transition Space

Informal causal descriptions of physical systems abound in sources such as encyclopedias, reports and user's manuals. Yet these descriptions remain largely opaque to computer processing. This paper proposes a representational framework in which such descriptions are viewed as providing partial specifications of paths in a space of possible transitions, or transition space. In this framework, the task of comprehending informal causal descriptions emerges as one of completing the specifications of paths in transition space---filling causal gaps and relating accounts of activity varied by analogy and abstraction. The use of the representation and its operations is illustrated in the context of a simple description concerning rocket propulsion.

Early-Holocene environments in the Wadi Faynan, Jordan

Hunt, C. Elrishi, H. Gilbertson, D. Grattan, J. McLaren, S. Pyatt, B. Rushworth, G. Barker, G. Early-Holocene environments in the Wadi Faynan, Jordan. The Holocene. 2004. 14,6 pp 921-930

Debugging: the good, the bad, and the quirky -- a qualitative analysis of novices' strategies

Murphy, L., Lewandowski, G., McCauley, R., Simon, B., Thomas, L., and Zander, C. 2008. Debugging: the good, the bad, and the quirky -- a qualitative analysis of novices' strategies. SIGCSE Bull. 40, 1 (Feb. 2008), 163-167

3'-UTR SIRF: A database for identifying clusters of short interspersed repeats in 3' untranslated regions

BACKGROUND:Short (~5 nucleotides) interspersed repeats regulate several aspects of post-transcriptional gene expression. Previously we developed an algorithm (REPFIND) that assigns P-values to all repeated motifs in a given nucleic acid sequence and reliably identifies clusters of short CAC-containing motifs required for mRNA localization in Xenopus oocytes.DESCRIPTION:In order to facilitate the identification of genes possessing clusters of repeats that regulate post-transcriptional aspects of gene expression in mammalian genes, we used REPFIND to create a database of all repeated motifs in the 3' untranslated regions (UTR) of genes from the Mammalian Gene Collection (MGC). The MGC database includes seven vertebrate species: human, cow, rat, mouse and three non-mammalian vertebrate species. A web-based application was developed to search this database of repeated motifs to generate species-specific lists of genes containing specific classes of repeats in their 3'-UTRs. This computational tool is called 3'-UTR SIRF (Short Interspersed Repeat Finder), and it reveals that hundreds of human genes contain an abundance of short CAC-rich and CAG-rich repeats in their 3'-UTRs that are similar to those found in mRNAs localized to the neurites of neurons. We tested four candidate mRNAs for localization in rat hippocampal neurons by in situ hybridization. Our results show that two candidate CAC-rich (Syntaxin 1B and Tubulin beta4) and two candidate CAG-rich (Sec61alpha and Syntaxin 1A) mRNAs are localized to distal neurites, whereas two control mRNAs lacking repeated motifs in their 3'-UTR remain primarily in the cell body.CONCLUSION:Computational data generated with 3'-UTR SIRF indicate that hundreds of mammalian genes have an abundance of short CA-containing motifs that may direct mRNA localization in neurons. In situ hybridization shows that four candidate mRNAs are localized to distal neurites of cultured hippocampal neurons. These data suggest that short CA-containing motifs may be part of a widely utilized genetic code that regulates mRNA localization in vertebrate cells. The use of 3'-UTR SIRF to search for new classes of motifs that regulate other aspects of gene expression should yield important information in future studies addressing cis-regulatory information located in 3'-UTRs.

The Least of These: American Evangelical Parachurch Missions to the Poor, 1947-2005

This dissertation narrates the historical development of American evangelical missions to the poor from 1947-2005 and analyzes the discourse of its main parachurch proponents, especially World Vision, Compassion International, Food for the Hungry, Samaritan's urse, Sojourners, Evangelicals for Social Action, and the Christian Community Development Association. Although recent scholarship on evangelicalism has been prolific, much of the historical work has focused on earlier periods. Sociological and political scientific scholarship on the postwar period has been attracted mostly to controversies surrounding the Religious Right, leaving evangelicalism's resurgent concern for the poor relatively understudied. This dissertation addresses these lacunae. The study consists of three chronological parts, each marked by a distinctive model of mission to the poor. First, the 1950s were characterized by compassionate charity for individual emergencies, a model that cohered neatly with evangelicalism's individualism and emotionalism. This model should be regarded as the quintessential, bedrock evangelical theory of mission to the poor. It remained strong throughout the entire postwar period. Second, in the 1970s, a strong countercurrent emerged that advocated for penitent protest against structural injustice and underdevelopment. In contrast to the first model, it was distinguished by going against the grain of many aspects of evangelical culture, especially its reflexive patriotism and individualism. Third, in the 1990s, an important movement towards developing potential through hopeful holism gained prominence. Its advocates were confident that their integration of biblical principles with insights from contemporary economic development praxis would contribute to drastic, widespread reductions in poverty. This model signaled a new optimism in evangelicalism's engagement with the broader world. The increasing prominence of missions to the poor within American evangelicalism led to dramatic changes within the movement's worldview: by 2005, evangelicals were mostly unified in their expressed concern for the physical and social needs of the poor, a position that radically reversed their immediate postwar worldview of near-exclusive focus on the spiritual needs of individuals. Nevertheless, missions to the poor also paralleled, reinforced, and hastened the increasing fragmentation of evangelicalism's identity, as each missional model advocated for highly variant approaches to poverty amelioration that were undergirded by diverse sociological, political, and theological assumptions.

Generalized Methods for Discovering Frequent Poly-Regions in DNA

The problem of discovering frequent poly-regions (i.e. regions of high occurrence of a set of items or patterns of a given alphabet) in a sequence is studied, and three efficient approaches are proposed to solve it. The first one is entropy-based and applies a recursive segmentation technique that produces a set of candidate segments which may potentially lead to a poly-region. The key idea of the second approach is the use of a set of sliding windows over the sequence. Each sliding window covers a sequence segment and keeps a set of statistics that mainly include the number of occurrences of each item or pattern in that segment. Combining these statistics efficiently yields the complete set of poly-regions in the given sequence. The third approach applies a technique based on the majority vote, achieving linear running time with a minimal number of false negatives. After identifying the poly-regions, the sequence is converted to a sequence of labeled intervals (each one corresponding to a poly-region). An efficient algorithm for mining frequent arrangements of intervals is applied to the converted sequence to discover frequently occurring arrangements of poly-regions in different parts of DNA, including coding regions. The proposed algorithms are tested on various DNA sequences producing results of significant biological meaning.

Comparison of K-ary N-cube and de Bruijn Overlays in QoS-Constrained Multicast Applications

Research on the construction of logical overlay networks has gained significance in recent times. This is partly due to work on peer-to-peer (P2P) systems for locating and retrieving distributed data objects, and also scalable content distribution using end-system multicast techniques. However, there are emerging applications that require the real-time transport of data from various sources to potentially many thousands of subscribers, each having their own quality-of-service (QoS) constraints. This paper primarily focuses on the properties of two popular topologies found in interconnection networks, namely k-ary n-cubes and de Bruijn graphs. The regular structure of these graph topologies makes them easier to analyze and determine possible routes for real-time data than complete or irregular graphs. We show how these overlay topologies compare in their ability to deliver data according to the QoS constraints of many subscribers, each receiving data from specific publishing hosts. Comparisons are drawn on the ability of each topology to route data in the presence of dynamic system effects, due to end-hosts joining and departing the system. Finally, experimental results show the service guarantees and physical link stress resulting from efficient multicast trees constructed over both kinds of overlay networks.

Cuckoo: a Language for Implementing Memory- and Thread-safe System Services

This paper is centered around the design of a thread- and memory-safe language, primarily for the compilation of application-specific services for extensible operating systems. We describe various issues that have influenced the design of our language, called Cuckoo, that guarantees safety of programs with potentially asynchronous flows of control. Comparisons are drawn between Cuckoo and related software safety techniques, including Cyclone and software-based fault isolation (SFI), and performance results suggest our prototype compiler is capable of generating safe code that executes with low runtime overheads, even without potential code optimizations. Compared to Cyclone, Cuckoo is able to safely guard accesses to memory when programs are multithreaded. Similarly, Cuckoo is capable of enforcing memory safety in situations that are potentially troublesome for techniques such as SFI.

Discovering Frequent Poly-Regions in DNA Sequences

The problem of discovering frequent arrangements of regions of high occurrence of one or more items of a given alphabet in a sequence is studied, and two efficient approaches are proposed to solve it. The first approach is entropy-based and uses an existing recursive segmentation technique to split the input sequence into a set of homogeneous segments. The key idea of the second approach is to use a set of sliding windows over the sequence. Each sliding window keeps a set of statistics of a sequence segment that mainly includes the number of occurrences of each item in that segment. Combining these statistics efficiently yields the complete set of regions of high occurrence of the items of the given alphabet. After identifying these regions, the sequence is converted to a sequence of labeled intervals (each one corresponding to a region). An efficient algorithm for mining frequent arrangements of temporal intervals on a single sequence is applied on the converted sequence to discover frequently occurring arrangements of these regions. The proposed algorithms are tested on various DNA sequences producing results with significant biological meaning.

Fast Learning VIEWNET Architectures for Recognizing 3-D Objects from Multiple 2-D Views

The recognition of 3-D objects from sequences of their 2-D views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With NETworks. VIEWNET incorporates a preprocessor that generates a compressed but 2-D invariant representation of an image, a supervised incremental learning system that classifies the preprocessed representations into 2-D view categories whose outputs arc combined into 3-D invariant object categories, and a working memory that makes a 3-D object prediction by accumulating evidence from 3-D object category nodes as multiple 2-D views are experienced. The simplest VIEWNET achieves high recognition scores without the need to explicitly code the temporal order of 2-D views in working memory. Working memories are also discussed that save memory resources by implicitly coding temporal order in terms of the relative activity of 2-D view category nodes, rather than as explicit 2-D view transitions. Variants of the VIEWNET architecture may also be used for scene understanding by using a preprocessor and classifier that can determine both What objects are in a scene and Where they are located. The present VIEWNET preprocessor includes the CORT-X 2 filter, which discounts the illuminant, regularizes and completes figural boundaries, and suppresses image noise. This boundary segmentation is rendered invariant under 2-D translation, rotation, and dilation by use of a log-polar transform. The invariant spectra undergo Gaussian coarse coding to further reduce noise and 3-D foreshortening effects, and to increase generalization. These compressed codes are input into the classifier, a supervised learning system based on the fuzzy ARTMAP algorithm. Fuzzy ARTMAP learns 2-D view categories that are invariant under 2-D image translation, rotation, and dilation as well as 3-D image transformations that do not cause a predictive error. Evidence from sequence of 2-D view categories converges at 3-D object nodes that generate a response invariant under changes of 2-D view. These 3-D object nodes input to a working memory that accumulates evidence over time to improve object recognition. ln the simplest working memory, each occurrence (nonoccurrence) of a 2-D view category increases (decreases) the corresponding node's activity in working memory. The maximally active node is used to predict the 3-D object. Recognition is studied with noisy and clean image using slow and fast learning. Slow learning at the fuzzy ARTMAP map field is adapted to learn the conditional probability of the 3-D object given the selected 2-D view category. VIEWNET is demonstrated on an MIT Lincoln Laboratory database of l28x128 2-D views of aircraft with and without additive noise. A recognition rate of up to 90% is achieved with one 2-D view and of up to 98.5% correct with three 2-D views. The properties of 2-D view and 3-D object category nodes are compared with those of cells in monkey inferotemporal cortex.