Dynamics of bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna in Hawaii’s pelagic fisheries: analysis of tagging data with a bulk transfer model incorporating size-specific attrition

Tag release and recapture data of bigeye (Thunnus obesus) and yellowfin tuna (T. albacares) from the Hawaii Tuna Tagging Project (HTTP) were analyzed with a bulk transfer model incorporating size-specific attrition to infer population dynamics and transfer rates between various fishery components. For both species, the transfer rate estimates from the offshore handline fishery areas to the longline fishery area were higher than the estimates of transfer from those same areas into the inshore fishery areas. Natural and fishing mortality rates were estimated over three size classes: yellowfin 20–45, 46–55, and ≥56 cm and bigeye 29–55, 56–70, and ≥71 cm. For both species, the estimates of natural mortality were highest in the smallest size class. For bigeye tuna, the estimates decreased with increasing size and for yellowfin tuna there was a slight increase in the largest size class. In the Cross Seamount fishery, the fishing mortality rate of bigeye tuna was similar for all three size classes and represented roughly 12% of the gross attrition rate (includes fishing and natural mortality and emigration rates). For yellowfin tuna, fishing mortality ranged between 7% and 30%, the highest being in the medium size class. For both species, the overall attrition rate from the entire fishery area was nearly the same. However, in the specific case of the Cross Seamount fishery, the attrition rate for yellowfin tuna was roughly twice that for bigeye. This result indicates that bigeye tuna are more resident at the Seamount than yellowfin tuna, and larger bigeye tunas tend to reside longer than smaller individuals. This may result in larger fish being more vulnerable to capture in the Seamount fishery. The relatively low level of exchange between the Sea-mount and the inshore and longline fisheries suggests that the fishing activity at the Seamount need not be of great management concern for either species. However, given that the current exploitation rates are considered moderate (10–30%), and that Seamount aggregations of yellowfin and bigeye tuna are highly vulnerable to low-cost gear types, it is recommended that further increases in fishing effort for these species be monitored at Cross Seamount.

Spatial correlation of heat release rate and sound emission from turbulent premixed flames

The two-point spatial correlation of the rate of change of fluctuating heat release rate is central to the sound emission from open turbulent flames, and a few attempts have been made to address this correlation in recent studies. In this paper, the two-point correlation and its role in combustion noise are studied by analysing direct numerical simulation (DNS) data of statistically multi-dimensional turbulent premixed flames. The results suggest that this correlation function depends on the separation distance and direction but, not on the positions inside the flame brush. This correlation can be modelled using a combination of Hermite-Gaussian functions of zero and second order, i.e. functions of the form (1-Ax2)e-Bx2 for constants A and B, to include its possible negative values. The integral correlation volume obtained using this model is about 0.2δL3 with the length scale obtained from its cube root being about 0.6δ L, where δ L is the laminar flame thermal thickness. Both of the values are slightly larger than the values reported in an earlier study because of the anisotropy observed for the correlation. This model together with the turbulence-dependent parameter K, the ratio of the root-mean-square (RMS) value of the rate of change of reaction rate to the mean reaction rate, derived from the DNS data is applied to predict the far-field sound emitted from open flames. The calculated noise levels agree well with recently reported measurements and show a sensitivity to K values. © 2012 The Combustion Institute.

A preliminary study on methods for retaining data quality problems in automatically generated test data

Data in an organisation often contains business secrets that organisations do not want to release. However, there are occasions when it is necessary for an organisation to release its data such as when outsourcing work or using the cloud for Data Quality (DQ) related tasks like data cleansing. Currently, there is no mechanism that allows organisations to release their data for DQ tasks while ensuring that it is suitably protected from releasing business related secrets. The aim of this paper is therefore to present our current progress on determining which methods are able to modify secret data and retain DQ problems. So far we have identified the ways in which data swapping and the SHA-2 hash function alterations methods can be used to preserve missing data, incorrectly formatted values, and domain violations DQ problems while minimising the risk of disclosing secrets. © (2012) by the AIS/ICIS Administrative Office All rights reserved.

BU Computer Science 1998 Proxy Trace: Release Notes

In a recent paper (Changes in Web Client Access Patterns: Characteristics and Caching Implications by Barford, Bestavros, Bradley, and Crovella) we performed a variety of analyses upon user traces collected in the Boston University Computer Science department in 1995 and 1998. A sanitized version of the 1995 trace has been publicly available for some time; the 1998 trace has now been sanitized, and is available from: http://www.cs.bu.edu/techreports/1999-011-usertrace-98.gz ftp://ftp.cs.bu.edu/techreports/1999-011-usertrace-98.gz This memo discusses the format of this public version of the log, and includes additional discussion of how the data was collected, how the log was sanitized, what this log is and is not useful for, and areas of potential future research interest.

Isoperimetric Graph Partitioning for Data Clustering and Image Segmentation

Spectral methods of graph partitioning have been shown to provide a powerful approach to the image segmentation problem. In this paper, we adopt a different approach, based on estimating the isoperimetric constant of an image graph. Our algorithm produces the high quality segmentations and data clustering of spectral methods, but with improved speed and stability.

Fusion Artmap: A Neural Network Architecture for Multi-Channel Data Fusion and Classification

Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi-sensor, data fusion. Single-channel Fusion ARTMAP is functionally equivalent to Fuzzy ART during unsupervised learning and to Fuzzy ARTMAP during supervised learning. The network has a symmetric organization such that each channel can be dynamically configured to serve as either a data input or a teaching input to the system. An ART module forms a compressed recognition code within each channel. These codes, in turn, become inputs to a single ART system that organizes the global recognition code. When a predictive error occurs, a process called paraellel match tracking simultaneously raises vigilances in multiple ART modules until reset is triggered in one of them. Parallel match tracking hereby resets only that portion of the recognition code with the poorest match, or minimum predictive confidence. This internally controlled selective reset process is a type of credit assignment that creates a parsimoniously connected learned network. Fusion ARTMAP's multi-channel coding is illustrated by simulations of the Quadruped Mammal database.

Eliminating Redundant Training Data Using Unsupervised Clustering Techniques

Training data for supervised learning neural networks can be clustered such that the input/output pairs in each cluster are redundant. Redundant training data can adversely affect training time. In this paper we apply two clustering algorithms, ART2 -A and the Generalized Equality Classifier, to identify training data clusters and thus reduce the training data and training time. The approach is demonstrated for a high dimensional nonlinear continuous time mapping. The demonstration shows six-fold decrease in training time at little or no loss of accuracy in the handling of evaluation data.

ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network

This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.

Serotonin synthesis, release and reuptake in terminals: a mathematical model.

BACKGROUND: Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding of serotonergic systems in the central nervous system involves genomics, neurochemistry, electrophysiology, and behavior. Though associations have been found between functions at these different levels, in most cases the causal mechanisms are unknown. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders in the serotonergic signaling system. METHODS: We construct a mathematical model of serotonin synthesis, release, and reuptake in a single serotonergic neuron terminal. The model includes the effects of autoreceptors, the transport of tryptophan into the terminal, and the metabolism of serotonin, as well as the dependence of release on the firing rate. The model is based on real physiology determined experimentally and is compared to experimental data. RESULTS: We compare the variations in serotonin and dopamine synthesis due to meals and find that dopamine synthesis is insensitive to the availability of tyrosine but serotonin synthesis is sensitive to the availability of tryptophan. We conduct in silico experiments on the clearance of extracellular serotonin, normally and in the presence of fluoxetine, and compare to experimental data. We study the effects of various polymorphisms in the genes for the serotonin transporter and for tryptophan hydroxylase on synthesis, release, and reuptake. We find that, because of the homeostatic feedback mechanisms of the autoreceptors, the polymorphisms have smaller effects than one expects. We compute the expected steady concentrations of serotonin transporter knockout mice and compare to experimental data. Finally, we study how the properties of the the serotonin transporter and the autoreceptors give rise to the time courses of extracellular serotonin in various projection regions after a dose of fluoxetine. CONCLUSIONS: Serotonergic systems must respond robustly to important biological signals, while at the same time maintaining homeostasis in the face of normal biological fluctuations in inputs, expression levels, and firing rates. This is accomplished through the cooperative effect of many different homeostatic mechanisms including special properties of the serotonin transporters and the serotonin autoreceptors. Many difficult questions remain in order to fully understand how serotonin biochemistry affects serotonin electrophysiology and vice versa, and how both are changed in the presence of selective serotonin reuptake inhibitors. Mathematical models are useful tools for investigating some of these questions.

Comparative genomic data of the Avian Phylogenomics Project.

BACKGROUND: The evolutionary relationships of modern birds are among the most challenging to understand in systematic biology and have been debated for centuries. To address this challenge, we assembled or collected the genomes of 48 avian species spanning most orders of birds, including all Neognathae and two of the five Palaeognathae orders, and used the genomes to construct a genome-scale avian phylogenetic tree and perform comparative genomics analyses (Jarvis et al. in press; Zhang et al. in press). Here we release assemblies and datasets associated with the comparative genome analyses, which include 38 newly sequenced avian genomes plus previously released or simultaneously released genomes of Chicken, Zebra finch, Turkey, Pigeon, Peregrine falcon, Duck, Budgerigar, Adelie penguin, Emperor penguin and the Medium Ground Finch. We hope that this resource will serve future efforts in phylogenomics and comparative genomics. FINDINGS: The 38 bird genomes were sequenced using the Illumina HiSeq 2000 platform and assembled using a whole genome shotgun strategy. The 48 genomes were categorized into two groups according to the N50 scaffold size of the assemblies: a high depth group comprising 23 species sequenced at high coverage (>50X) with multiple insert size libraries resulting in N50 scaffold sizes greater than 1 Mb (except the White-throated Tinamou and Bald Eagle); and a low depth group comprising 25 species sequenced at a low coverage (~30X) with two insert size libraries resulting in an average N50 scaffold size of about 50 kb. Repetitive elements comprised 4%-22% of the bird genomes. The assembled scaffolds allowed the homology-based annotation of 13,000 ~ 17000 protein coding genes in each avian genome relative to chicken, zebra finch and human, as well as comparative and sequence conservation analyses. CONCLUSIONS: Here we release full genome assemblies of 38 newly sequenced avian species, link genome assembly downloads for the 7 of the remaining 10 species, and provide a guideline of genomic data that has been generated and used in our Avian Phylogenomics Project. To the best of our knowledge, the Avian Phylogenomics Project is the biggest vertebrate comparative genomics project to date. The genomic data presented here is expected to accelerate further analyses in many fields, including phylogenetics, comparative genomics, evolution, neurobiology, development biology, and other related areas.

Release of outer membrane vesicles by Gram-negative bacteria is a novel envelope stress response.

Conditions that impair protein folding in the Gram-negative bacterial envelope cause stress. The destabilizing effects of stress in this compartment are recognized and countered by a number of signal transduction mechanisms. Data presented here reveal another facet of the complex bacterial stress response, release of outer membrane vesicles. Native vesicles are composed of outer membrane and periplasmic material, and they are released from the bacterial surface without loss of membrane integrity. Here we demonstrate that the quantity of vesicle release correlates directly with the level of protein accumulation in the cell envelope. Accumulation of material occurs under stress, and is exacerbated upon impairment of the normal housekeeping and stress-responsive mechanisms of the cell. Mutations that cause increased vesiculation enhance bacterial survival upon challenge with stressing agents or accumulation of toxic misfolded proteins. Preferential packaging of a misfolded protein mimic into vesicles for removal indicates that the vesiculation process can act to selectively eliminate unwanted material. Our results demonstrate that production of bacterial outer membrane vesicles is a fully independent, general envelope stress response. In addition to identifying a novel mechanism for alleviating stress, this work provides physiological relevance for vesicle production as a protective mechanism.

Chitosan derivatives alter release profiles of model compounds from calcium phosphate implants

The aim of the current study was to evaluate the impact of chitosan derivatives, namely N-octyl-chitosan and N-octyl-O-sulfate chitosan, incorporated in calcium phosphate implants to the release profiles of model drugs. The rate and extent of calcein (on M.W. 650 Da) ED, and FITC-dextran (M.W. 40 kDa) on in vitro release were monitored by fluorescence spectroscopy. Results show that calcein release is affected by the type of chitosan derivative used. A higher percentage of model drug was released when the hydrophilic polymer N-octyl-sulfated chitosan was present in the tablets compared with the tablets containing the hydrophobic polymer N-octyl-chitosan. The release profiles of calcein or FD from tablets containing N-octyl-O-sulfate revealed a complete release for FD after 120 h compared with calcein where 20% of the drug was released over the same time period. These results suggest that the difference in the release profiles observed from the implants is dependent on the molecular weight of the model drugs. These data indicate the potential of chitosan derivatives in controlling the release profile of active compounds from calcium phosphate implants. (C) 2009 Elsevier Ltd. All rights reserved.

Local perceptions of the QICS experimental offshore CO2 release: Results from social science research

This paper explores the social dimensions of an experimental release of carbon dioxide (CO2) carried out in Ardmucknish Bay, Argyll, United Kingdom. The experiment, which aimed to understand detectability and potential effects on the marine environment should there be any leakage from a CO2 storage site, provided a rare opportunity to study the social aspects of a carbon dioxide capture and storage-related event taking place in a lived-in environment. Qualitative research was carried out in the form of observation at public information events about the release, in-depth interviews with key project staff and local stakeholders/community members, and a review of online media coverage of the experiment. Focusing mainly on the observation and interview data, we discuss three key findings: the role of experience and analogues in learning about unfamiliar concepts like CO2 storage; the challenge of addressing questions of uncertainty in public engagement; and the issue of when to commence engagement and how to frame the discussion. We conclude that whilst there are clearly slippages between a small-scale experiment and full-scale CCS, the social research carried out for this project demonstrates that issues of public and stakeholder perception are as relevant for offshore CO2 storage as they are for onshore.

Influence of silicone elastomer solubility and diffusivity on the in vitro release of drugs from intravaginal rings

The in vitro release characteristics of eight low-molecular-weight drugs (clindamycin, 17beta-estradiol, 17beta-estradiol-3-acetate, 17beta-estradiol diacetate, metronidazole, norethisterone, norethisterone acetate and oxybutynin) from silicone matrixtype intravaginal rings of various drug loadings have been evaluated under sink conditions. Through modelling of the release data using the Higuchi equation, and determination of the silicone solubility of the drugs, the apparent silicone elastomer diffusion coefficients of the drugs have been calculated. Furthermore, in an attempt to develop a quantitative model for predicting release rates of new drug substances from these vaginal ring devices, it has been observed that linear relationships exist between the log of the silicone solubility of the drug (mg ml(-1)) and the reciprocal of its melting point (K-1) (y = 3.558x - 9.620, R = 0.77), and also between the log of the diffusion coefficient (cm(2) s(-1)) and the molecular weight of the drug molecule (g mol(-1)) (y = - 0.0068x - 4.0738, R = 0.95). Given that the silicone solubility and silicone diffusion coefficient are the major parameters influencing the permeation of drugs through silicone elastomers, it is now possible to predict through use of the appropriate mathematical equations both matrix-type and reservoir-type intravaginal ring release rates simply from a knowledge of drug melting temperature and molecular weight. (C) 2003 Elsevier Science B.V. All rights reserved.

Effects of the novel (Pro(3))GIP antagonist and exendin(9-39)amide on GIP- and GLP-1-induced cyclic AMP generation, insulin secretion and postprandial insulin release in obese diabetic (ob/ob) mice: evidence that GIP is the major physiological incretin

AIMS/HYPOTHESIS: This study examined the biological effects of the GIP receptor antagonist, (Pro3)GIP and the GLP-1 receptor antagonist, exendin(9-39)amide.

METHODS: Cyclic AMP production was assessed in Chinese hamster lung fibroblasts transfected with human GIP or GLP-1 receptors, respectively. In vitro insulin release studies were assessed in BRIN-BD11 cells while in vivo insulinotropic and glycaemic responses were measured in obese diabetic ( ob/ ob) mice.

RESULTS: In GIP receptor-transfected fibroblasts, (Pro(3))GIP or exendin(9-39)amide inhibited GIP-stimulated cyclic AMP production with maximal inhibition of 70.0+/-3.5% and 73.5+/-3.2% at 10(-6) mol/l, respectively. In GLP-1 receptor-transfected fibroblasts, exendin(9-39)amide inhibited GLP-1-stimulated cyclic AMP production with maximal inhibition of 60+/-0.7% at 10(-6) mol/l, whereas (Pro(3))GIP had no effect. (Pro(3))GIP specifically inhibited GIP-stimulated insulin release (86%; p<0.001) from clonal BRIN-BD11 cells, but had no effect on GLP-1-stimulated insulin release. In contrast, exendin(9-39)amide inhibited both GIP and GLP-1-stimulated insulin release (57% and 44%, respectively; p<0.001). Administration of (Pro(3))GIP, exendin(9-39)amide or a combination of both peptides (25 nmol/kg body weight, i.p.) to fasted (ob/ob) mice decreased the plasma insulin responses by 42%, 54% and 49%, respectively (p<0.01 to p<0.001). The hyperinsulinaemia of non-fasted (ob/ob) mice was decreased by 19%, 27% and 18% (p<0.05 to p<0.01) by injection of (Pro3)GIP, exendin(9-39)amide or combined peptides but accompanying changes of plasma glucose were small.

CONCLUSIONS/INTERPRETATION: These data show that (Pro(3))GIP is a specific GIP receptor antagonist. Furthermore, feeding studies in one commonly used animal model of obesity and diabetes, (ob/ob) mice, suggest that GIP is the major physiological component of the enteroinsular axis, contributing approximately 80% to incretin-induced insulin release.