Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: What controls light?

NASA Astrophysics Data System (ADS)

Le, Chengfeng; Hu, Chuanmin; English, David; Cannizzaro, Jennifer; Chen, Zhiqiang; Kovach, Charles; Anastasiou, Christopher J.; Zhao, Jun; Carder, Kendall L.

2013-01-01

Inherent and apparent optical properties (IOPs and AOPs) of Tampa Bay (Florida, USA) were measured during fourteen cruises between February 1998 and October 2010 to understand how these properties relate to one another and what controls light absorption and diffuse attenuation in this moderately sized (˜1000 km2), shallow estuary (average depth ˜4 m). The IOPs and AOPs included: 1) absorption coefficients of three optically significant constituents: phytoplankton pigments, detrital particles, and colored dissolved organic matter (CDOM); 2) particulate backscattering coefficients; 3) chlorophyll-a concentrations; 4) above-water remote sensing reflectance; 5) downwelling diffuse attenuation coefficients (Kd) at eight wavelengths and photosynthetically active radiation (PAR). Results showed substantial variability in all IOPs and AOPs in both space and time, with most IOPs spanning more than two orders of magnitude and showing strong co-variations. Of all four bay segments, Old Tampa Bay showed unique optical characteristics. During the wet season, the magnitude of blue-green-light absorption was dominated by CDOM, while during the dry season all three constituents contributed significantly. However, the variability in Kd (PAR, 490 nm, 555 nm) was driven mainly by the variability of detrital particles and phytoplankton as opposed to CDOM. This observation explained, at least to first order, why a nutrient reduction management strategy used by the Tampa Bay Estuary Program since the 1990s led to improved water clarity in most of Tampa Bay. The findings of this study provided the optical basis to fine tune existing or develop new algorithms to estimate the various optical water quality parameters from space.

Modified Mahalanobis Taguchi System for Imbalance Data Classification

PubMed Central

2017-01-01

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA). PMID:28811820

Pb’s high sedimentation inside the bay mouth of Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming

2017-12-01

Sedimentation is one of the key environmental behaviors of pollutants in the ocean. This paper analyzed the seasonal and temporal variations of Pb’s sedimentation process in Jiaozhou Bay in 1987. Results showed that Pb contents in bottom waters in Jiaozhou Bay in May, July and November 1987 were 1.87-2.60 μg L-1, 15.11-19.68 μg L-1 and 11.08-15.18 μg L-1, and the pollution levels of Pb in May, July and November 1987 were slight, heavy and heavy, respectively. In May 1987, there was low sedimentation process in waters in the outside of the bay mouth, yet were high sedimentation process in waters in the middle and inside of the bay mouth. In July and November 1987, there was low sedimentation process in waters in the outside of the bay mouth, yet were high sedimentation process in waters in the inside of the bay mouth. The seasonal-temporal variation of sedimentation processes of Pb were determined by the variations of sources input and the vertical water’s effect.

Variation in susceptibility of Umbellularia californica (Bay Laurel) to Phytophthora ramorum

Treesearch

Matthew Meshriy; Daniel Hüberli; Tamar Harnik; Lori Miles; Keefe Reuther; Matteo Garbelotto

2006-01-01

Bay laurel (Umbellularia californica) is an important foliar host in terms of spore production and transmission of disease. We designed a bioassay to screen for variation in susceptibility to Phytophthora ramorum among populations of bay laurel collected along the coast of California to southern Oregon and also from Yosemite....

Analysis of Air Traffic Track Data with the AutoBayes Synthesis System

NASA Technical Reports Server (NTRS)

Schumann, Johann Martin Philip; Cate, Karen; Lee, Alan G.

2010-01-01

The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.

Analysis of Naïve Bayes Algorithm for Email Spam Filtering across Multiple Datasets

NASA Astrophysics Data System (ADS)

Fitriah Rusland, Nurul; Wahid, Norfaradilla; Kasim, Shahreen; Hafit, Hanayanti

2017-08-01

E-mail spam continues to become a problem on the Internet. Spammed e-mail may contain many copies of the same message, commercial advertisement or other irrelevant posts like pornographic content. In previous research, different filtering techniques are used to detect these e-mails such as using Random Forest, Naïve Bayesian, Support Vector Machine (SVM) and Neutral Network. In this research, we test Naïve Bayes algorithm for e-mail spam filtering on two datasets and test its performance, i.e., Spam Data and SPAMBASE datasets [8]. The performance of the datasets is evaluated based on their accuracy, recall, precision and F-measure. Our research use WEKA tool for the evaluation of Naïve Bayes algorithm for e-mail spam filtering on both datasets. The result shows that the type of email and the number of instances of the dataset has an influence towards the performance of Naïve Bayes.

Linear dimension reduction and Bayes classification

NASA Technical Reports Server (NTRS)

Decell, H. P., Jr.; Odell, P. L.; Coberly, W. A.

1978-01-01

An explicit expression for a compression matrix T of smallest possible left dimension K consistent with preserving the n variate normal Bayes assignment of X to a given one of a finite number of populations and the K variate Bayes assignment of TX to that population was developed. The Bayes population assignment of X and TX were shown to be equivalent for a compression matrix T explicitly calculated as a function of the means and covariances of the given populations.

Genomic prediction using an iterative conditional expectation algorithm for a fast BayesC-like model.

PubMed

Dong, Linsong; Wang, Zhiyong

2018-06-11

Genomic prediction is feasible for estimating genomic breeding values because of dense genome-wide markers and credible statistical methods, such as Genomic Best Linear Unbiased Prediction (GBLUP) and various Bayesian methods. Compared with GBLUP, Bayesian methods propose more flexible assumptions for the distributions of SNP effects. However, most Bayesian methods are performed based on Markov chain Monte Carlo (MCMC) algorithms, leading to computational efficiency challenges. Hence, some fast Bayesian approaches, such as fast BayesB (fBayesB), were proposed to speed up the calculation. This study proposed another fast Bayesian method termed fast BayesC (fBayesC). The prior distribution of fBayesC assumes that a SNP with probability γ has a non-zero effect which comes from a normal density with a common variance. The simulated data from QTLMAS XII workshop and actual data on large yellow croaker were used to compare the predictive results of fBayesB, fBayesC and (MCMC-based) BayesC. The results showed that when γ was set as a small value, such as 0.01 in the simulated data or 0.001 in the actual data, fBayesB and fBayesC yielded lower prediction accuracies (abilities) than BayesC. In the actual data, fBayesC could yield very similar predictive abilities as BayesC when γ ≥ 0.01. When γ = 0.01, fBayesB could also yield similar results as fBayesC and BayesC. However, fBayesB could not yield an explicit result when γ ≥ 0.1, but a similar situation was not observed for fBayesC. Moreover, the computational speed of fBayesC was significantly faster than that of BayesC, making fBayesC a promising method for genomic prediction.

Temporal variations of Cu in Jiaozhou Bay 1982-1986

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Zhu, Sixi; Wang, Zhikang; Su, Chunhua; Wang, Qiang

2017-12-01

This paper analyzed the temporal variations of Cu in Jiaozhou Bay during 1982-1986. Results showed that Cu contents in study years were 0.15-5.31 μg L-1, 0.77-20.60 μg L-1, 0.11-4.00 μg L-1, 0.10-0.43 μg L-1 and 0.18-0.77 μg L-1, respectively. The Cu pollution level in this bay was moderate during 1982-1983, yet for temporal variations Cu contents in surface waters were showing decreasing trend. Cu contents in spring, summer and autumn were 0.11-20.60 μg L-1, 0.10-4.86 μg L-1 and 0.11-3.56 μg L-1, respectively. This bay was moderate pollution in spring in 1982-1983, while in other seasons in study years was still slight. These indicated that the temporal variations of Cu pollution in this bay should be taken in to account in decision-making of pollution control practice.

Influence of net freshwater supply on salinity in Florida Bay

USGS Publications Warehouse

Nuttle, William K.; Fourqurean, James W.; Cosby, Bernard J.; Zieman, Joseph C.; Robblee, Michael B.

2000-01-01

An annual water budget for Florida Bay, the large, seasonally hypersaline estuary in the Everglades National Park, was constructed using physically based models and long‐term (31 years) data on salinity, hydrology, and climate. Effects of seasonal and interannual variations of the net freshwater supply (runoff plus rainfall minus evaporation) on salinity variation within the bay were also examined. Particular attention was paid to the effects of runoff, which are the focus of ambitious plans to restore and conserve the Florida Bay ecosystem. From 1965 to 1995 the annual runoff from the Everglades into the bay was less than one tenth of the annual direct rainfall onto the bay, while estimated annual evaporation slightly exceeded annual rainfall. The average net freshwater supply to the bay over a year was thus approximately zero, and interannual variations in salinity appeared to be affected primarily by interannual fluctuations in rainfall. At the annual scale, runoff apparently had little effect on the bay as a whole during this period. On a seasonal basis, variations in rainfall, evaporation, and runoff were not in phase, and the net freshwater supply to the bay varied between positive and negative values, contributing to a strong seasonal pattern in salinity, especially in regions of the bay relatively isolated from exchanges with the Gulf of Mexico and Atlantic Ocean. Changes in runoff could have a greater effect on salinity in the bay if the seasonal patterns of rainfall and evaporation and the timing of the runoff are considered. One model was also used to simulate spatial and temporal patterns of salinity responses expected to result from changes in net freshwater supply. Simulations in which runoff was increased by a factor of 2 (but with no change in spatial pattern) indicated that increased runoff will lower salinity values in eastern Florida Bay, increase the variability of salinity in the South Region, but have little effect on salinity in the Central and West Regions.

Comparison of Naive Bayes and Decision Tree on Feature Selection Using Genetic Algorithm for Classification Problem

NASA Astrophysics Data System (ADS)

Rahmadani, S.; Dongoran, A.; Zarlis, M.; Zakarias

2018-03-01

This paper discusses the problem of feature selection using genetic algorithms on a dataset for classification problems. The classification model used is the decicion tree (DT), and Naive Bayes. In this paper we will discuss how the Naive Bayes and Decision Tree models to overcome the classification problem in the dataset, where the dataset feature is selectively selected using GA. Then both models compared their performance, whether there is an increase in accuracy or not. From the results obtained shows an increase in accuracy if the feature selection using GA. The proposed model is referred to as GADT (GA-Decision Tree) and GANB (GA-Naive Bayes). The data sets tested in this paper are taken from the UCI Machine Learning repository.

Mono-isotope Prediction for Mass Spectra Using Bayes Network.

PubMed

Li, Hui; Liu, Chunmei; Rwebangira, Mugizi Robert; Burge, Legand

2014-12-01

Mass spectrometry is one of the widely utilized important methods to study protein functions and components. The challenge of mono-isotope pattern recognition from large scale protein mass spectral data needs computational algorithms and tools to speed up the analysis and improve the analytic results. We utilized naïve Bayes network as the classifier with the assumption that the selected features are independent to predict mono-isotope pattern from mass spectrometry. Mono-isotopes detected from validated theoretical spectra were used as prior information in the Bayes method. Three main features extracted from the dataset were employed as independent variables in our model. The application of the proposed algorithm to publicMo dataset demonstrates that our naïve Bayes classifier is advantageous over existing methods in both accuracy and sensitivity.

AutoBayes Program Synthesis System System Internals

NASA Technical Reports Server (NTRS)

Schumann, Johann Martin

2011-01-01

This lecture combines the theoretical background of schema based program synthesis with the hands-on study of a powerful, open-source program synthesis system (Auto-Bayes). Schema-based program synthesis is a popular approach toward program synthesis. The lecture will provide an introduction into this topic and discuss how this technology can be used to generate customized algorithms. The synthesis of advanced numerical algorithms requires the availability of a powerful symbolic (algebra) system. Its task is to symbolically solve equations, simplify expressions, or to symbolically calculate derivatives (among others) such that the synthesized algorithms become as efficient as possible. We will discuss the use and importance of the symbolic system for synthesis. Any synthesis system is a large and complex piece of code. In this lecture, we will study Autobayes in detail. AutoBayes has been developed at NASA Ames and has been made open source. It takes a compact statistical specification and generates a customized data analysis algorithm (in C/C++) from it. AutoBayes is written in SWI Prolog and many concepts from rewriting, logic, functional, and symbolic programming. We will discuss the system architecture, the schema libary and the extensive support infra-structure. Practical hands-on experiments and exercises will enable the student to get insight into a realistic program synthesis system and provides knowledge to use, modify, and extend Autobayes.

Temporal variations in the benthic communities at four intertidal sites in San Francisco Bay, California, 1983-85

USGS Publications Warehouse

Hopkins, D.R.

1987-01-01

Benthic core samples were collected monthly from January 1983 through January 1985 at four intertidal sites in San Francisco Bay, California, two in the northern part of the bay (North Bay) and two in the southern part of the bay (South Bay). Considerable variation was observed in numbers of species and individuals at the four sites, and abundances within species varied widely. Temporal changes in species abundances appeared to be related to freshwater inflow patterns and resultant salinity variations in the estuary. The 1982-83 winter season was extremely wet, with heavy freshwater inflow to the bay from January through March, whereas the 1983-84 winter was closer to a normal pattern, with most rainfall occurring from November through January. Species were grouped into four categories depending on their patterns of abundance during the 2-yr period. Species that showed an abundance peak in the North Bay in 1983 only were Corophium sp.B and a Chironomidae larva, apparently responding to the extended period of lowered salinity throughout spring and early summer. Species with an abundance peak only in 1984 included Corophium Acherusicum, Eteone californica, Nereis succinea, and Grandidierella japonica, typical estuarine species that might have been suppressed during the extended freshwater inflows in 1983. Species with peaks in both years were Gemma gemma and Ampelisca abdita in the South Bay; both showed strong seasonal variations. A number of species in both North and South Bays, including dominant members of the intertidal community such as Macoma balthical and Streblospio benedicti, did not show any consistent seasonal or year-to-year trends. Results of this study suggest that the intensity and timing of freshwater inflow to San Francisco Bay, particularly higher-than-normal inflow during late spring and early summer, may be an important factor in determining the composition of the intertidal benthic communities. (Author 's abstract)

Surface (sea floor) and near-surface (box cores) sediment mineralogy in Baffin Bay as a key to sediment provenance and ice sheet variations

USGS Publications Warehouse

Andrews, John T.; Eberl, D.D.

2011-01-01

To better understand the glacial history of the ice sheets surrounding Baffin Bay and to provide information on sediment pathways, samples from 82 seafloor grabs and core tops, and from seven box cores were subjected to quantitative X-ray diffraction weight percent (wt.%) analysis of the 2000 m) all show an abrupt drop in calcite wt.% (post-5 cal ka BP?) following a major peak in detrital carbonate (mainly dolomite). This dolomite-rich detrital carbonate (DC) event in JR175BC06 is possibly coeval with the Younger Dryas cold event. Four possible glacial-sourced end members were employed in a compositional unmixing algorithm to gain insight into down core changes in sediment provenance at the deep central basin. Estimates of the rates of sediment accumulation in the central basin are only in the range of 2 to 4 cm/cal ka, surprisingly low given the glaciated nature of the surrounding land.

Make It Short and Easy: Username Complexity Determines Trustworthiness Above and Beyond Objective Reputation

PubMed Central

Silva, Rita R.; Chrobot, Nina; Newman, Eryn; Schwarz, Norbert; Topolinski, Sascha

2017-01-01

Can the mere name of a seller determine his trustworthiness in the eye of the consumer? In 10 studies (total N = 608) we explored username complexity and trustworthiness of eBay seller profiles. Name complexity was manipulated through variations in username pronounceability and length. These dimensions had strong, independent effects on trustworthiness, with sellers with easy-to-pronounce or short usernames being rated as more trustworthy than sellers with difficult-to-pronounce or long usernames, respectively. Both effects were repeatedly found even when objective information about seller reputation was available. We hypothesized the effect of name complexity on trustworthiness to be based on the experience of high vs. low processing fluency, with little awareness of the underlying process. Supporting this, participants could not correct for the impact of username complexity when explicitly asked to do so. Three alternative explanations based on attributions of the variations in name complexity to seller origin (ingroup vs. outgroup), username generation method (seller personal choice vs. computer algorithm) and age of the eBay profiles (10 years vs. 1 year) were tested and ruled out. Finally, we show that manipulating the ease of reading product descriptions instead of the sellers’ names also impacts the trust ascribed to the sellers. PMID:29312062

Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures.

PubMed

Yamazaki, Keisuke; Kaji, Daisuke

2013-08-01

Hierarchical learning models are ubiquitously employed in information science and data engineering. The structure makes the posterior distribution complicated in the Bayes method. Then, the prediction including construction of the posterior is not tractable though advantages of the method are empirically well known. The variational Bayes method is widely used as an approximation method for application; it has the tractable posterior on the basis of the variational free energy function. The asymptotic behavior has been studied in many hierarchical models and a phase transition is observed. The exact form of the asymptotic variational Bayes energy is derived in Bernoulli mixture models and the phase diagram shows that there are three types of parameter learning. However, the approximation accuracy or interpretation of the transition point has not been clarified yet. The present paper precisely analyzes the Bayes free energy function of the Bernoulli mixtures. Comparing free energy functions in these two Bayes methods, we can determine the approximation accuracy and elucidate behavior of the parameter learning. Our results claim that the Bayes free energy has the same learning types while the transition points are different. Copyright © 2013 Elsevier Ltd. All rights reserved.

BayesMotif: de novo protein sorting motif discovery from impure datasets.

PubMed

Hu, Jianjun; Zhang, Fan

2010-01-18

Protein sorting is the process that newly synthesized proteins are transported to their target locations within or outside of the cell. This process is precisely regulated by protein sorting signals in different forms. A major category of sorting signals are amino acid sub-sequences usually located at the N-terminals or C-terminals of protein sequences. Genome-wide experimental identification of protein sorting signals is extremely time-consuming and costly. Effective computational algorithms for de novo discovery of protein sorting signals is needed to improve the understanding of protein sorting mechanisms. We formulated the protein sorting motif discovery problem as a classification problem and proposed a Bayesian classifier based algorithm (BayesMotif) for de novo identification of a common type of protein sorting motifs in which a highly conserved anchor is present along with a less conserved motif regions. A false positive removal procedure is developed to iteratively remove sequences that are unlikely to contain true motifs so that the algorithm can identify motifs from impure input sequences. Experiments on both implanted motif datasets and real-world datasets showed that the enhanced BayesMotif algorithm can identify anchored sorting motifs from pure or impure protein sequence dataset. It also shows that the false positive removal procedure can help to identify true motifs even when there is only 20% of the input sequences containing true motif instances. We proposed BayesMotif, a novel Bayesian classification based algorithm for de novo discovery of a special category of anchored protein sorting motifs from impure datasets. Compared to conventional motif discovery algorithms such as MEME, our algorithm can find less-conserved motifs with short highly conserved anchors. Our algorithm also has the advantage of easy incorporation of additional meta-sequence features such as hydrophobicity or charge of the motifs which may help to overcome the limitations of PWM (position weight matrix) motif model.

Geographic variation in marine invasions among large estuaries: effects of ships and time.

PubMed

Ruiz, Gregory M; Fofonoff, Paul W; Ashton, Gail; Minton, Mark S; Miller, A Whitman

2013-03-01

Coastal regions exhibit strong geographic patterns of nonnative species richness. Most invasions in marine ecosystems are known from bays and estuaries, where ship-mediated transfers (on hulls or in ballasted materials) have been a dominant vector of species introductions. Conspicuous spatial differences in nonnative species richness exist among bays, but the quantitative relationship between invasion magnitude and shipping activity across sites is largely unexplored. Using data on marine invasions (for invertebrates and algae) and commercial shipping across 16 large bays in the United States, we estimated (1) geographic variation in nonnative species richness attributed to ships, controlling for effects of salinity and other vectors, (2) changes through time in geographic variation of these ship-mediated invasions, and (3) effects of commercial ship traffic and ballast water discharge magnitude on nonnative species richness. For all nonnative species together (regardless of vector, salinity, or time period), species richness differed among U.S. coasts, being significantly greater for Pacific Coast bays than Atlantic or Gulf Coast bays. This difference also existed when considering only species attributed to shipping (or ballast water), controlling for time and salinity. Variation in nonnative species richness among Pacific Coast bays was strongly affected by these same criteria. San Francisco Bay, California, had over 200 documented nonnative species, more than twice that reported for other bays, but many species were associated with other (non-shipping) vectors or the extensive low-salinity habitats (unavailable in some bays). When considering only ship- or ballast-mediated introductions in high-salinity waters, the rate of newly detected invasions in San Francisco Bay has converged increasingly through time on that for other Pacific Coast bays, appearing no different since 1982. Considering all 16 bays together, there was no relationship between either (1) number of ship arrivals (from foreign ports) and number of introductions attributed to ships since 1982 or (2) volume of foreign ballast water discharge and number of species attributed to ballast water since 1982. These shipping measures are likely poor proxies for propagule supply, although they are sometimes used as such, highlighting a fundamental gap in data needed to evaluate invasion dynamics and management strategies.

A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José Cricelio; Luna-Vázquez, Francisco Javier; Salinas-Ruiz, Josafhat; Herrera-Morales, José R.; Buenrostro-Mariscal, Raymundo

2017-01-01

There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD) term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments. PMID:28391241

A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José Cricelio; Luna-Vázquez, Francisco Javier; Salinas-Ruiz, Josafhat; Herrera-Morales, José R; Buenrostro-Mariscal, Raymundo

2017-06-07

There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD) term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments. Copyright © 2017 Montesinos-López et al.

Remote Sensing Reflectance and Inherent Optical Properties in the Mid-mesohaline Chesapeake Bay

NASA Technical Reports Server (NTRS)

Tzortziou, Maria; Subramaniam, Ajit; Herman, Jay R.; Gallegos, Charles L.; Neal, Patrick J.; Harding, Lawrence W., Jr.

2006-01-01

We used an extensive set of bio-optical data and radiative transfer (RT) model simulations of radiation fields to investigate relationships between inherent optical properties and remotely sensed quantities in the optically complex, mid-mesohaline Chesapeake Bay waters. Field observations showed that the chlorophyll algorithms used by the MODIS (MODerate resolution Imaging Spectroradiometer) ocean color sensor (i.e. Chlor_a, chlor_MODIS, chlor_a_3 products) do not perform accurately in these Case 2 waters. This is because, when applied to waters with high concentrations of chlorophyll, all MODIS algorithms are based on empirical relationships between chlorophyll concentration and blue-green wavelength remote sensing reflectance (Rrs) ratios that do not account for the typically strong blue-wavelength absorption by non-covarying, dissolved and non-algal particulate components. Stronger correlation was observed between chlorophyll concentration and Rrs ratios in the red (i.e. Rrs(677)/Rrs(554)) where dissolved and non-algal particulate absorption become exponentially smaller. Regionally-specific algorithms that are based on the phytoplankton optical properties in the red wavelength region provide a better basis for satellite monitoring of phytoplankton blooms in these Case 2 waters. Good optical closure was obtained between independently measured Rrs spectra and the optical properties of backscattering, b(sub b), and absorption, a, over the wide range of in-water conditions observed in the Chesapeake Bay. Observed variability in the quantity f/Q (proportionality factor in the relationship between Rrs and the water inherent optical properties ratio b(sub b)/(a+b(sub b)) was consistent with RT model calculations for the specific measurement geometry and water bio-optical characteristics. Data and model results showed that f/Q values in these Case 2 coastal waters are not considerably different from those estimated in previous studies for Case 1 waters. Variation in surface backscattering significantly affected Rrs magnitude across the visible spectrum and was most strongly correlated (R(sup 2)=0.88) with observed variability in Rrs at 670 nm. Surface values of particulate backscattering were strongly correlated with non-algal particulate absorption, a(sub nap), in the blue wavelengths (R(sup 2)=0.83). These results, along with the measured values of backscattering fraction magnitude and non-algal particulate absorption spectral slope, suggest that suspended non-algal particles with high inorganic content are the major water constituents regulating b(sub b) variability in the mid-mesohaline Chesapeake Bay. Remote retrieval of surface b(sub b) and (a(sub nap), from Rrs(670) can be used in regionally-specific satellite algorithms to separate contribution by non-algal particles and dissolved organic matter to total light absorption in the blue, and monitor non-algal suspended particle concentration and distribution in these Case 2 waters.

A variational Bayes discrete mixture test for rare variant association

PubMed Central

Logsdon, Benjamin A.; Dai, James Y.; Auer, Paul L.; Johnsen, Jill M.; Ganesh, Santhi K.; Smith, Nicholas L.; Wilson, James G.; Tracy, Russell P.; Lange, Leslie A.; Jiao, Shuo; Rich, Stephen S.; Lettre, Guillaume; Carlson, Christopher S.; Jackson, Rebecca D.; O’Donnell, Christopher J.; Wurfel, Mark M.; Nickerson, Deborah A.; Tang, Hua; Reiner, Alexander P.; Kooperberg, Charles

2014-01-01

Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that “aggregate” tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute’s Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans. PMID:24482836

A variational Bayes discrete mixture test for rare variant association.

PubMed

Logsdon, Benjamin A; Dai, James Y; Auer, Paul L; Johnsen, Jill M; Ganesh, Santhi K; Smith, Nicholas L; Wilson, James G; Tracy, Russell P; Lange, Leslie A; Jiao, Shuo; Rich, Stephen S; Lettre, Guillaume; Carlson, Christopher S; Jackson, Rebecca D; O'Donnell, Christopher J; Wurfel, Mark M; Nickerson, Deborah A; Tang, Hua; Reiner, Alexander P; Kooperberg, Charles

2014-01-01

Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that "aggregate" tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute's Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans.

ASSESSING HABITAT QUALITY OF MOUNT HOPE BAY AND NARRAGANSETT BAY USING GROWTH, RNA:DNA, AND FEDDING HABITS OF CAGED JUVENILE WINTER FLOUNDER

EPA Science Inventory

Somatic growth rates, RNA:DNA, and feeding habits of juvenile Pseudopleuronectes americanus (Winter Flounder) were used to asses small-scale spatio-temporal variations in the habitat quality of Mount Hope Bay and Narragan-sett Bay, RI. Three successive caging experiments (14–16 d...

A Novel Feature Selection Technique for Text Classification Using Naïve Bayes.

PubMed

Dey Sarkar, Subhajit; Goswami, Saptarsi; Agarwal, Aman; Aktar, Javed

2014-01-01

With the proliferation of unstructured data, text classification or text categorization has found many applications in topic classification, sentiment analysis, authorship identification, spam detection, and so on. There are many classification algorithms available. Naïve Bayes remains one of the oldest and most popular classifiers. On one hand, implementation of naïve Bayes is simple and, on the other hand, this also requires fewer amounts of training data. From the literature review, it is found that naïve Bayes performs poorly compared to other classifiers in text classification. As a result, this makes the naïve Bayes classifier unusable in spite of the simplicity and intuitiveness of the model. In this paper, we propose a two-step feature selection method based on firstly a univariate feature selection and then feature clustering, where we use the univariate feature selection method to reduce the search space and then apply clustering to select relatively independent feature sets. We demonstrate the effectiveness of our method by a thorough evaluation and comparison over 13 datasets. The performance improvement thus achieved makes naïve Bayes comparable or superior to other classifiers. The proposed algorithm is shown to outperform other traditional methods like greedy search based wrapper or CFS.

RELATIONSHIPS BETWEEN JUVENILE WINTER FLOUNDER AND MULTIPLE-SCALE HABITAT VARIATION IN NARRAGANSETT BAY, RHODE ISLAND

EPA Science Inventory

A rapid random-sampling method was used to relate densities of juvenile winter flounder to multiple scales of habitat variation in Narragansett Bay and two nearby coastal lagoons in Rhode Island. We used a 1-m beam trawl with attached video camera, continuous GPS track overlay, ...

Model and algorithm for container ship stowage planning based on bin-packing problem

NASA Astrophysics Data System (ADS)

Zhang, Wei-Ying; Lin, Yan; Ji, Zhuo-Shang

2005-09-01

In a general case, container ship serves many different ports on each voyage. A stowage planning for container ship made at one port must take account of the influence on subsequent ports. So the complexity of stowage planning problem increases due to its multi-ports nature. This problem is NP-hard problem. In order to reduce the computational complexity, the problem is decomposed into two sub-problems in this paper. First, container ship stowage problem (CSSP) is regarded as “packing problem”, ship-bays on the board of vessel are regarded as bins, the number of slots at each bay are taken as capacities of bins, and containers with different characteristics (homogeneous containers group) are treated as items packed. At this stage, there are two objective functions, one is to minimize the number of bays packed by containers and the other is to minimize the number of overstows. Secondly, containers assigned to each bays at first stage are allocate to special slot, the objective functions are to minimize the metacentric height, heel and overstows. The taboo search heuristics algorithm are used to solve the subproblem. The main focus of this paper is on the first subproblem. A case certifies the feasibility of the model and algorithm.

Bio-optical water quality dynamics observed from MERIS in Pensacola Bay, Florida

EPA Science Inventory

Observed bio-optical water quality data collected from 2009 to 2011 in Pensacola Bay, Florida were used to develop empirical remote sensing retrieval algorithms for chlorophyll a (Chla), colored dissolved organic matter (CDOM), and suspended particulate matter (SPM). Time-series ...

AutoBayes Program Synthesis System Users Manual

NASA Technical Reports Server (NTRS)

Schumann, Johann; Jafari, Hamed; Pressburger, Tom; Denney, Ewen; Buntine, Wray; Fischer, Bernd

2008-01-01

Program synthesis is the systematic, automatic construction of efficient executable code from high-level declarative specifications. AutoBayes is a fully automatic program synthesis system for the statistical data analysis domain; in particular, it solves parameter estimation problems. It has seen many successful applications at NASA and is currently being used, for example, to analyze simulation results for Orion. The input to AutoBayes is a concise description of a data analysis problem composed of a parameterized statistical model and a goal that is a probability term involving parameters and input data. The output is optimized and fully documented C/C++ code computing the values for those parameters that maximize the probability term. AutoBayes can solve many subproblems symbolically rather than having to rely on numeric approximation algorithms, thus yielding effective, efficient, and compact code. Statistical analysis is faster and more reliable, because effort can be focused on model development and validation rather than manual development of solution algorithms and code.

BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations

PubMed Central

Wang, Junbai; Batmanov, Kirill

2015-01-01

Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein–DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein–DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions. PMID:26202972

Bayesian design of decision rules for failure detection

NASA Technical Reports Server (NTRS)

Chow, E. Y.; Willsky, A. S.

1984-01-01

The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one.

Spatial and seasonal patterns of ichthyoplankton assemblages in the Haizhou Bay and its adjacent waters of China

NASA Astrophysics Data System (ADS)

Li, Zengguang; Ye, Zhenjiang; Wan, Rong

2015-12-01

Surveys were conducted in five voyages in Haizhou Bay and its adjacent coastal area from March to December 2011 during full moon spring tides. The ichthyoplankton assemblages and the environmental factors that affect their spatial and seasonal patterns were determined. Totally 35 and 12 fish egg and larvae taxa were identified, respectively. Over the past several decades, the egg and larval species composition has significantly changed in Haizhou Bay and its adjacent waters, most likely corresponding with the alteration of fishery resources, which are strongly affected by anthropogenic activities and climate change. The Bray-Curtis dissimilarity index identified four assemblages: near-shore bay assemblage, middle bay assemblage and two closely related assemblages (near-shore/middle bay assemblage and middle/edge of bay assemblage). The primary species of each assemblage principally reflected the spawning strategies of adult fish. The near-shore bay assemblage generally occurred in near-shore bay, with depths measuring <20 m, and the middle bay assemblage generally occurred in the middle of bay, with depths measuring 20 to 40 m. Spatial and seasonal variations in ichthyoplankton in each assemblage were determined by interactions between biological behavioral traits and oceanographic features, particularly the variation of local conditions within the constraint of a general reproductive strategy. The results of Spearman's rank correlation analysis indicated that both fish egg and larval abundance were positively correlated with depth, which is critical to the oceanographic features in Haizhou Bay.

Spatial and temporal characterizations of water quality in Kuwait Bay.

PubMed

Al-Mutairi, N; Abahussain, A; El-Battay, A

2014-06-15

The spatial and temporal patterns of water quality in Kuwait Bay have been investigated using data from six stations between 2009 and 2011. The results showed that most of water quality parameters such as phosphorus (PO4), nitrate (NO3), dissolved oxygen (DO), and Total Suspended Solids (TSS) fluctuated over time and space. Based on Water Quality Index (WQI) data, six stations were significantly clustered into two main classes using cluster analysis, one group located in western side of the Bay, and other in eastern side. Three principal components are responsible for water quality variations in the Bay. The first component included DO and pH. The second included PO4, TSS and NO3, and the last component contained seawater temperature and turbidity. The spatial and temporal patterns of water quality in Kuwait Bay are mainly controlled by seasonal variations and discharges from point sources of pollution along Kuwait Bay's coast as well as from Shatt Al-Arab River. Copyright © 2014 Elsevier Ltd. All rights reserved.

Machine Learning for Information Extraction in Informal Domains

DTIC Science & Technology

1998-11-01

Bayes algorithm (BayeslDF), a hybrid of BayeslDF and the grammatical inference algo- rithm Alergia (BayesGI), and a relational learner (SRV). It...State-Merging Methods 59 4.1.3 Alergia 61 4.2 Inferring Transducers 62 4.3 Experiments 66 4.4 Discussion 72 Relational Learning for...65 4.5 Precision/recall results for Alergia and BayesG I on the speaker field, with the alphabet transducer produced using m-estimates, at various

Recent Trends in Suspended Sediment Load & Water Quality in the Upper Chesapeake Bay

NASA Astrophysics Data System (ADS)

Freeman, L. A.; Ackleson, S. G.

2016-02-01

The Chesapeake Bay spans several major cities on the US east coast and drains a large watershed (164,200 km2) to the Atlantic Ocean. Upstream deforestation and agriculture have led to a major decline in water quality (increased sediment and nutrient load) of the Bay over the past century. Sediment flux into the Chesapeake Bay is a natural process, but has become an environmental concern as land use changes have exacerbated natural suspended sediment loads and saturated the capacity of the estuary to filter and remove sediments. In situ measurements of suspended sediments and surface reflectance from the Potomac, Patapsco, and Severn River were used to develop algorithms that convert surface reflectance from Landsat (1-3, 4-5, 7, 8) imagery to suspended sediment concentration for the entire Chesapeake Bay. A unique time series of suspended sediment load in the Chesapeake Bay was compiled from Landsat imagery dating from 1977-2015. Particular focus is given to the upper Chesapeake Bay near Washington, DC and Baltimore, MD to understand urban effects. In particular, the Potomac, Patapsco, and Severn River are examined from both remote sensing and in situ measurements. Landsat imagery combined with in situ monitoring provides environmental scientists and resource managers with detailed trends in sediment distribution and concentration, a key measure of water quality. Trends of suspended sediment load in several rivers and the upper Chesapeake Bay will be presented, along with a discussion of suspended sediment algorithms for Landsat imagery. Advantages of Landsat 8 (improved signal-to-noise performance and more bands) versus previous sensors will be examined for suspended sediment applications.

Seasonal and spatial variations in surface pCO2 and air-sea CO2 flux in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Cai, W. J.; Chen, B.

2017-12-01

Bay-wide observations of surface water partial pressure of carbon dioxide (pCO2) were conducted in May, June, August, and October 2016 to study the spatial and seasonal variations in surface pCO2 and to estimate air-sea CO2 flux in the Chesapeake Bay. Overall, high surface pCO2 in the upper-bay decreased downstream rapidly below the atmospheric value near the bay bridge in the mid-bay and then increased slightly to the lower-bay where pCO2 approached the atmospheric level. Over the course of a year, pCO2 was higher than 1000 µatm in the upper bay and the highest pCO2 (2500 µatm) was observed in August. Significant biologically-induced pCO2 undersaturation was observed at the upper part of the mid-bay in August with pCO2 as low as 50 µatm and oversaturated DO% of 200%. In addition to biological control, vertical mixing and upwelling controlled by wind direction and tidal stage played an important role in controlling surface pCO2 in the mid-bay as is evidenced by co-occurrence of high pCO2 with low temperature and low oxygen or high salinity from the subsurface. These physical processes occurred regularly and in short time scale of hours, suggesting they must be considered in the assessment of annual air-sea CO2 flux. Seasonally, the upper-bay acted as a source for atmospheric CO2 over the course of a year. The boundary of upper and mid bay transited from a CO2 source to a sink from May to August and was a source again in October due to strong biological production in summer. In contrast, the mid-bay represented as a CO2 source with large temporal variation due to dynamic hydrographic settings. The lower-bay transited from a weak sink in May to equilibrated with the atmosphere from June to August, while became a source again in October. Moreover, the CO2 flux could be reversed very quickly under episodic severe weather events. Thus further research, including the influence of severe weather and subsequent bloom, is needed to get better understanding of the carbon cycling in the Chesapeake Bay.

Seasonal and spatial variations in fish and macrocrustacean assemblage structure in Mad Island Marsh estuary, Texas

NASA Astrophysics Data System (ADS)

Akin, S.; Winemiller, K. O.; Gelwick, F. P.

2003-05-01

Fish and macrocrustacean assemblage structure was analyzed along an estuarine gradient at Mad Island Marsh (MIM), Matagorda Bay, TX, during March 1998-August 1999. Eight estuarine-dependent fish species accounted for 94% of the individual fishes collected, and three species accounted for 96% of macrocrustacean abundance. Consistent with evidence from other Gulf of Mexico estuarine studies, species richness and abundance were highest during late spring and summer, and lowest during winter and early spring. Sites near the bay supported the most individuals and species. Associations between fish abundance and environmental variables were examined with canonical correspondence analysis. The dominant gradient was associated with water depth and distance from the bay. The secondary gradient reflected seasonal variation and was associated with temperature, salinity, dissolved oxygen, and vegetation cover. At the scales examined, estuarine biota responded to seasonal variation more than spatial variation. Estuarine-dependent species dominated the fauna and were common throughout the open waters of the shallow lake during winter-early spring when water temperature and salinity were low and dissolved oxygen high. During summer-early fall, sub-optimal environmental conditions (high temperature, low DO) in upper reaches accounted for strong spatial variation in assemblage composition. Small estuarine-resident fishes and the blue crab ( Callinectes sapidus) were common in warm, shallow, vegetated inland sites during summer-fall. Estuarine-dependent species were common at deeper, more saline locations near the bay during this period. During summer, freshwater species, such as gizzard shad ( Dorosoma cepedianum) and gars ( Lepisosteus spp.), were positively associated with water depth and proximity to the bay. The distribution and abundance of fishes in MIM appear to result from the combined effects of endogenous, seasonal patterns of reproduction and migration operating on large spatial scales, and species-specific response to local environmental variation.

Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

PubMed

Awaysheh, Abdullah; Wilcke, Jeffrey; Elvinger, François; Rees, Loren; Fan, Weiguo; Zimmerman, Kurt L

2016-11-01

Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. We tested the use of supervised machine-learning algorithms to differentiate between the 2 diseases using data generated from noninvasive diagnostic tests. Three prediction models were developed using 3 machine-learning algorithms: naive Bayes, decision trees, and artificial neural networks. The models were trained and tested on data from complete blood count (CBC) and serum chemistry (SC) results for the following 3 groups of client-owned cats: normal, inflammatory bowel disease (IBD), or alimentary lymphoma (ALA). Naive Bayes and artificial neural networks achieved higher classification accuracy (sensitivities of 70.8% and 69.2%, respectively) than the decision tree algorithm (63%, p < 0.0001). The areas under the receiver-operating characteristic curve for classifying cases into the 3 categories was 83% by naive Bayes, 79% by decision tree, and 82% by artificial neural networks. Prediction models using machine learning provided a method for distinguishing between ALA-IBD, ALA-normal, and IBD-normal. The naive Bayes and artificial neural networks classifiers used 10 and 4 of the CBC and SC variables, respectively, to outperform the C4.5 decision tree, which used 5 CBC and SC variables in classifying cats into the 3 classes. These models can provide another noninvasive diagnostic tool to assist clinicians with differentiating between IBD and ALA, and between diseased and nondiseased cats. © 2016 The Author(s).

Still Bay Point-Production Strategies at Hollow Rock Shelter and Umhlatuzana Rock Shelter and Knowledge-Transfer Systems in Southern Africa at about 80-70 Thousand Years Ago

PubMed Central

Lombard, Marlize

2016-01-01

It has been suggested that technological variations associated with Still Bay assemblages of southern Africa have not been addressed adequately. Here we present a study developed to explore regional and temporal variations in Still Bay point-production strategies. We applied our approach in a regional context to compare the Still Bay point assemblages from Hollow Rock Shelter (Western Cape) and Umhlatuzana Rock Shelter (KwaZulu-Natal). Our interpretation of the point-production strategies implies inter-regional point-production conventions, but also highlights variability and intra-regional knapping strategies used for the production of Still Bay points. These strategies probably reflect flexibility in the organisation of knowledge-transfer systems at work during the later stages of the Middle Stone Age between about 80 ka and 70 ka in South Africa. PMID:27942012

Still Bay Point-Production Strategies at Hollow Rock Shelter and Umhlatuzana Rock Shelter and Knowledge-Transfer Systems in Southern Africa at about 80-70 Thousand Years Ago.

PubMed

Högberg, Anders; Lombard, Marlize

2016-01-01

It has been suggested that technological variations associated with Still Bay assemblages of southern Africa have not been addressed adequately. Here we present a study developed to explore regional and temporal variations in Still Bay point-production strategies. We applied our approach in a regional context to compare the Still Bay point assemblages from Hollow Rock Shelter (Western Cape) and Umhlatuzana Rock Shelter (KwaZulu-Natal). Our interpretation of the point-production strategies implies inter-regional point-production conventions, but also highlights variability and intra-regional knapping strategies used for the production of Still Bay points. These strategies probably reflect flexibility in the organisation of knowledge-transfer systems at work during the later stages of the Middle Stone Age between about 80 ka and 70 ka in South Africa.

The effect of long-term spatiotemporal variations in urbanization-induced eutrophication on a benthic ecosystem, Osaka Bay, Japan

USGS Publications Warehouse

Yasuhara, Moriaki; Yamazaki, Hideo; Tsujimoto, Akira; Hirose, K.

2007-01-01

Detailed spatiotemporal patterns of the influence of urbanization-induced eutrophication on a metazoan benthic community in Osaka Bay were determined using sediment cores and fossil ostracode assemblages from the last 200 yr. Results suggest that total abundance of ostracodes increased in the middle part of the bay as a result of the increase of food supply by eutrophication. Conversely, abundance decreased in the inner bay, likely because of bottom-water hypoxia by eutrophication. The variation in species composition among sites within the bay may have decreased because of the effect of eutrophication, i.e., the dominance of species that prefer food-rich environments throughout all sites. These eutrophication-induced changes occurred around 1900 as a result of Japan's industrial revolution and around 1960 as a result of rapid urbanization, depending upon location. ?? 2007, by the American Society of Limnology and Oceanography, Inc.

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

NASA Technical Reports Server (NTRS)

Fischer, Bernd

2004-01-01

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Learning topic models by belief propagation.

PubMed

Zeng, Jia; Cheung, William K; Liu, Jiming

2013-05-01

Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications in text mining, computer vision and computational biology. This paper represents the collapsed LDA as a factor graph, which enables the classic loopy belief propagation (BP) algorithm for approximate inference and parameter estimation. Although two commonly used approximate inference methods, such as variational Bayes (VB) and collapsed Gibbs sampling (GS), have gained great success in learning LDA, the proposed BP is competitive in both speed and accuracy, as validated by encouraging experimental results on four large-scale document datasets. Furthermore, the BP algorithm has the potential to become a generic scheme for learning variants of LDA-based topic models in the collapsed space. To this end, we show how to learn two typical variants of LDA-based topic models, such as author-topic models (ATM) and relational topic models (RTM), using BP based on the factor graph representations.

Spatial variations in zooplankton community structure along the Japanese coastline in the Japan Sea: influence of the coastal current

NASA Astrophysics Data System (ADS)

Kodama, Taketoshi; Wagawa, Taku; Iguchi, Naoki; Takada, Yoshitake; Takahashi, Takashi; Fukudome, Ken-Ichi; Morimoto, Haruyuki; Goto, Tsuneo

2018-06-01

This study evaluates spatial variations in zooplankton community structure and potential controlling factors along the Japanese coast under the influence of the coastal branch of the Tsushima Warm Current (CBTWC). Variations in the density of morphologically identified zooplankton in the surface layer in May were investigated for a 15-year period. The density of zooplankton (individuals per cubic meter) varied between sampling stations, but there was no consistent west-east trend. Instead, there were different zooplankton community structures in the west and east, with that in Toyama Bay particularly distinct: Corycaeus affinis and Calanus sinicus were dominant in the west and Oithona atlantica was dominant in Toyama Bay. Distance-based redundancy analysis (db-RDA) was used to characterize the variation in zooplankton community structure, and four axes (RD1-4) provided significant explanation. RD2-4 only explained < 4.8 % of variation in the zooplankton community and did not show significant spatial difference; however, RD1, which explained 89.9 % of variation, did vary spatially. Positive and negative species scores on RD1 represent warm- and cold-water species, respectively, and their variation was mainly explained by water column mean temperature, and it is considered to vary spatially with the CBTWC. The CBTWC intrusion to the cold Toyama Bay is weak and occasional due to the submarine canyon structure of the bay. Therefore, the varying bathymetric characteristics along the Japanese coast of the Japan Sea generate the spatial variation in zooplankton community structure, and dominance of warm-water species can be considered an indicator of the CBTWC.

A review of circulation and mixing studies of San Francisco Bay, California

USGS Publications Warehouse

Smith, Lawrence H.

1987-01-01

A description of the major characteristics and remaining unknowns of circulation and mixing in San Francisco Bay has been constructed from a review of published studies. From a broad perspective San Francisco Bay is an ocean-river mixing zone with a seaward flow equal to the sum of the river inflows less evaporation. Understanding of circulation and mixing within the bay requires quantification of freshwater inflows and ocean-bay exchanges, characterization of source-water variations, and separation of the within-bay components of circulation and mixing processes. Description of net circulation and mixing over a few days to a few months illustrates best the interactions of major components. Quantification of tidal circulation and mixing is also necessary because net circulation and mixing contain a large tide-induced component, and because tidal variations are dominant in measurements of stage, currents, and salinity. The discharge of the Sacramento-San Joaquin Delta into Suisun Bay is approximately 90 percent of the freshwater inflow to San Francisco Bay. Annual delta discharge is characterized by a winter season of high runoff and a summer season of low runoff. For the period 1956 to 1985 the mean of monthly discharges exceeded 1,000 cubic meters per second (35,000 cubic feet per second) for the months of December through April, whereas for July through October, it was less than 400 cubic meters per second (14,000 cubic feet per second). The months of November, May, and June commonly were transition months between these seasons. Large year-to-year deviations from this annual pattern have occurred frequently. Much less is known about the ocean-bay exchange process. Net exchanges depend on net seaward flow in the bay, tidal amplitude, and longshore coastal currents, but exchanges have not yet been measured successfully. Source-water variations are ignored by limiting discussion of mixing to salinity. The bay is composed of a northern reach, which is strongly influenced by delta discharge, and South Bay, a tributary estuary which responds to conditions in Central Bay. In the northern reach net circulation is characterized by the river-induced seaward, flow and a resulting gravitational circulation in the channels, and by a tide- and wind-induced net horizontal circulation. A surface layer of relatively fresh water in Central Bay generated by high delta discharges can induce gravitational circulation in South Bay. During low delta discharges South Bay has nearly the same salinity as Central Bay and is characterized by tide- and wind-induced net horizontal circulation. Several factors control the patterns of circulation and mixing in San Francisco Bay. Viewing circulation and mixing over different time-periods and at different geographic scales causes the influences of different factors to be emphasized. The exchange between the bay and coastal ocean and freshwater inflows determine the year-to-year behavior of San Francisco Bay as a freshwater-saltwater mixing zone. Within the bay, exchanges between the embayments control variations over a season. Circulation and mixing patterns within the embayments and the magnitude of river-induced seaward flow influence the between-bay exchanges. The within-bay patterns are in turn determined by tides, winds, and freshwater inflows. Because freshwater inflow is the only factor that can be managed, a major study focus is estimation of inflow-related effects. Most questions relate to the patterns of freshwater inflow necessary to protect valuable resources whose welfare is dependent on conditions in the bay. Among the important questions being addressed are: --What quantity of freshwater inflow is necessary to prevent salt intrusion into the Sacramento-San Joaquin Delta, and what salinity distributions in the bay would result from various inflow patterns? --What quantity of freshwater inflow is sufficient to flush pollutants through the bay? Knowledge of circul

Screening-level risk assessment applied to dredging of polluted sediments from Guanabara Bay, Rio de Janeiro, Brazil.

PubMed

Silveira, Ana Elisa F; Nascimento, Juliana R; Sabadini-Santos, Elisamara; Bidone, Edison D

2017-05-15

Guanabara Bay is characterized by predominant eutrophication and anoxic sediments with a mixture of pollutants. The risk prognosis associated with the dumping of its dredged sediments into the open ocean was addressed by our algorithm. Our algorithm could prioritize areas, characterize major processes related to dredging, measure the potential risk of sediments, and predict the effects of sediment mixing. The estimated risk of dredged sediment was >10-fold than that of ocean sediments. Among metals, mercury represented 50-90% of the total risk. The transfer of dredged material into the ocean or internal dumping in the bay requires a 1:10 dilution to mitigate the risk and bring the risk levels close to that in the EPA criteria, below which there is less likelihood of adverse effects to the biota, and a 1:100 dilution to maintain the original characteristics of the ocean disposal control area. Our algorithm indicator can be used in the design of both aquatic and continental disposal of dredged materials and their management. Copyright © 2017. Published by Elsevier Ltd.

[Inversion Model and Daily Variation of Total Phosphorus Concentrations in Taihu Lake Based on GOCI Data].

PubMed

Du, Cheng-gong; Li, Yun-mei; Wang, Qiao; Zhu, Li; Lü, Heng

2016-03-15

The TP concentration is an important index of water quality and an important influencing factor of eutrophication and algae blooms. Remote sensing technology has advantages of wide scope and high time limited efficacy. Monitoring the concentration of TP by satellite remote sensing is important for the study of water quality and eutrophication. In situ datasets collected during the three times of experiments in Taihu Lake between 2013 and 2014 were used to develop the TP inversion model based on GOCI data. The GOCI data in spring, summer, autumn and winter in 2014 were selected to analyze the time and space changes of TP concentration in Taihu Lake. The results showed that the TP algorithm was built up based on the variables, which was to use the eight band combination of GOCI data as variable, and build model using Multi factor linear regression method. The algorithm achieved more accurate TP estimation with R² = 0.898, MAPE = 14.296%, RMSE = 0.026 mg · L⁻¹. Meantime, a analysis on the precision of the model by using the measured sample points and the synchronous satellite images with MAPE = 33.642%, 22.551%, RMSE = 0.076 mg · L⁻¹, 0.028 mg · L⁻¹ on August 5, 2014 and October 24, 2014. Through the analysis of the 30 images on the four days of the four seasons, it showed that the absolute concentration of total phosphorus was different in different seasons. But temporal and spatial distribution of total phosphorus concentration was similar in the morning and afternoon. In spatial distribution, the TP concentration in Meiliang Bay, Zhushan Bay, Gonghu Bay, Xiaomei Port and Changdou Port in the southwest coast was at a continuously high position. The TP concentration change in different regions was influenced by wind direction, wind speed and other factors. The TP concentration highest in the morning, and then gradually decreased, this phenomenon reflected that the TP concentration was affected by temperature and light.

Modelling Wind Effects on Subtidal Salinity in Apalachicola Bay, Florida

NASA Astrophysics Data System (ADS)

Huang, W.; Jones, W. K.; Wu, T. S.

2002-07-01

Salinity is an important factor for oyster and estuarine productivity in Apalachicola Bay. Observations of salinity at oyster reefs have indicated a high correlation between subtidal salinity variations and the surface winds along the bay axis in an approximately east-west direction. In this paper, we applied a calibrated hydrodynamic model to examine the surface wind effects on the volume fluxes in the tidal inlets and the subtidal salinity variations in the bay. Model simulations show that, due to the large size of inlets located at the east and west ends of this long estuary, surface winds have significant effects on the volume fluxes in the estuary inlets for the water exchanges between the estuary and ocean. In general, eastward winds cause the inflow from the inlets at the western end and the outflow from inlets at the eastern end of the bay. Winds at 15 mph speed in the east-west direction can induce a 2000 m3 s-1 inflow of saline seawater into the bay from the inlets, a rate which is about 2·6 times that of the annual average freshwater inflow from the river. Due to the varied wind-induced volume fluxes in the inlets and the circulation in the bay, the time series of subtidal salinity at oyster reefs considerably increases during strong east-west wind conditions in comparison to salinity during windless conditions. In order to have a better understanding of the characteristics of the wind-induced subtidal circulation and salinity variations, the researchers also connected model simulations under constant east-west wind conditions. Results show that the volume fluxes are linearly proportional to the east-west wind stresses. Spatial distributions of daily average salinity and currents clearly show the significant effects of winds on the bay.

Landsat Thematic Mapper monitoring of turbid inland water quality

NASA Technical Reports Server (NTRS)

Lathrop, Richard G., Jr.

1992-01-01

This study reports on an investigation of water quality calibration algorithms under turbid inland water conditions using Landsat Thematic Mapper (TM) multispectral digital data. TM data and water quality observations (total suspended solids and Secchi disk depth) were obtained near-simultaneously and related using linear regression techniques. The relationships between reflectance and water quality for Green Bay and Lake Michigan were compared with results for Yellowstone and Jackson Lakes, Wyoming. Results show similarities in the water quality-reflectance relationships, however, the algorithms derived for Green Bay - Lake Michigan cannot be extrapolated to Yellowstone and Jackson Lake conditions.

A framework for porting the NeuroBayes machine learning algorithm to FPGAs

NASA Astrophysics Data System (ADS)

Baehr, S.; Sander, O.; Heck, M.; Feindt, M.; Becker, J.

2016-01-01

The NeuroBayes machine learning algorithm is deployed for online data reduction at the pixel detector of Belle II. In order to test, characterize and easily adapt its implementation on FPGAs, a framework was developed. Within the framework an HDL model, written in python using MyHDL, is used for fast exploration of possible configurations. Under usage of input data from physics simulations figures of merit like throughput, accuracy and resource demand of the implementation are evaluated in a fast and flexible way. Functional validation is supported by usage of unit tests and HDL simulation for chosen configurations.

Ozone in the marine boundary layer of Bay of Bengal and Arabian Sea during post winter period - continental influence

NASA Astrophysics Data System (ADS)

Nair, Prabha R.; George, Susan K.; David, Liji Mary; Parameswaran, Krishnaswamy

Ozone plays a key role in controlling the oxidation capacity of the troposphere and hence the lifetime of a variety of trace gases in the atmosphere. In pristine marine boundary layer (MBL), entire chemistry is initiated by the photolysis of ozone and the subsequent formation of OH radical from water vapour. Also in such environment, photochemical destruction is considered as a major sink in global ozone budget. Even though large number of studies on near surface ozone has been carried out over land such studies are very few over oceanic environments. This paper presents the observational results on the spatial variations of near-surface ozone over Bay of Bengal and Arabian Sea as revealed by the cruise-based measurements (cruise No. SK223) conducted as part of Integrated Campaign for Aerosol gases and Radiation Budget (ICARB) under the Geosphere Biosphere Programme of Indian Space Research Organisation (IGBP). Online measurements of ozone have been carried out by using a UV Photometric Analyser (model 49C of Thermo Electron Corporation, USA). Ozone mixing ratio was observed to be significantly high over northern Bay of Bengal (20-28 ppb) compared to southern Bay of Bengal and Arabian Sea. Minimum levels of ozone ( 5 ppb) have been measured in the central Bay of Bengal region. Over Arabian Sea latitudinal variation was not prominently observed. The over all latitudinal gradient is estimated to be 1.2 ppb/o latitude over Bay of Bengal with longitudinal gradient showing variation depending on the latitude sector. It was maximum (of 1.2ppb/o longitude) over the mid Bay of Bengal region ( 15o N). Longitudinal variation was not significant over northern and southern regions. A close examination of surface airflow patterns and the air mass back trajectories revealed increase in ozone level associated with continental outflow from the northern and central parts of the subcontinent. The diurnal pattern also showed variations depending on the proximity to inhabited land mass and also with meteorological parameters.

Stan : A Probabilistic Programming Language

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectationmore » propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can also be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.« less

Stan : A Probabilistic Programming Language

DOE PAGES

Carpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.; ...

2017-01-01

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectationmore » propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can also be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.« less

Monitoring of oceanographic properties of Glacier Bay, Alaska 2004

USGS Publications Warehouse

Madison, Erica N.; Etherington, Lisa L.

2005-01-01

Glacier Bay is a recently (300 years ago) deglaciated fjord estuarine system that has multiple sills, very deep basins, tidewater glaciers, and many streams. Glacier Bay experiences a large amount of runoff, high sedimentation, and large tidal variations. High freshwater discharge due to snow and ice melt and the presence of the tidewater glaciers makes the bay extremely cold. There are many small- and large-scale mixing and upwelling zones at sills, glacial faces, and streams. The complex topography and strong currents lead to highly variable salinity, temperature, sediment, primary productivity, light penetration, stratification levels, and current patterns within a small area. The oceanographic patterns within Glacier Bay drive a large portion of the spatial and temporal variability of the ecosystem. It has been widely recognized by scientists and resource managers in Glacier Bay that a program to monitor oceanographic patterns is essential for understanding the marine ecosystem and to differentiate between anthropogenic disturbance and natural variation. This year’s sampling marks the 12th continuous year of monitoring the oceanographic conditions at 23 stations along the primary axes within Glacier Bay, AK, making this a very unique and valuable data set in terms of its spatial and temporal coverage.

A Comparison of Full and Empirical Bayes Techniques for Inferring Sea Level Changes from Tide Gauge Records

NASA Astrophysics Data System (ADS)

Piecuch, C. G.; Huybers, P. J.; Tingley, M.

2016-12-01

Sea level observations from coastal tide gauges are some of the longest instrumental records of the ocean. However, these data can be noisy, biased, and gappy, featuring missing values, and reflecting land motion and local effects. Coping with these issues in a formal manner is a challenging task. Some studies use Bayesian approaches to estimate sea level from tide gauge records, making inference probabilistically. Such methods are typically empirically Bayesian in nature: model parameters are treated as known and assigned point values. But, in reality, parameters are not perfectly known. Empirical Bayes methods thus neglect a potentially important source of uncertainty, and so may overestimate the precision (i.e., underestimate the uncertainty) of sea level estimates. We consider whether empirical Bayes methods underestimate uncertainty in sea level from tide gauge data, comparing to a full Bayes method that treats parameters as unknowns to be solved for along with the sea level field. We develop a hierarchical algorithm that we apply to tide gauge data on the North American northeast coast over 1893-2015. The algorithm is run in full Bayes mode, solving for the sea level process and parameters, and in empirical mode, solving only for the process using fixed parameter values. Error bars on sea level from the empirical method are smaller than from the full Bayes method, and the relative discrepancies increase with time; the 95% credible interval on sea level values from the empirical Bayes method in 1910 and 2010 is 23% and 56% narrower, respectively, than from the full Bayes approach. To evaluate the representativeness of the credible intervals, empirical Bayes and full Bayes methods are applied to corrupted data of a known surrogate field. Using rank histograms to evaluate the solutions, we find that the full Bayes method produces generally reliable error bars, whereas the empirical Bayes method gives too-narrow error bars, such that the 90% credible interval only encompasses 70% of true process values. Results demonstrate that parameter uncertainty is an important source of process uncertainty, and advocate for the fully Bayesian treatment of tide gauge records in ocean circulation and climate studies.

NASA Satellite Monitoring of Water Clarity in Mobile Bay for Nutrient Criteria Development

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holekamp, Kara; Spiering, Bruce A.

2009-01-01

This project has demonstrated feasibility of deriving from MODIS daily measurements time series of water clarity parameters that provide coverage of a specific location or an area of interest for 30-50% of days. Time series derived for estuarine and coastal waters display much higher variability than time series of ecological parameters (such as vegetation indices) derived for land areas. (Temporal filtering often applied in terrestrial studies cannot be used effectively in ocean color processing). IOP-based algorithms for retrieval of diffuse light attenuation coefficient and TSS concentration perform well for the Mobile Bay environment: only a minor adjustment was needed in the TSS algorithm, despite generally recognized dependence of such algorithms on local conditions. The current IOP-based algorithm for retrieval of chlorophyll a concentration has not performed as well: a more reliable algorithm is needed that may be based on IOPs at additional wavelengths or on remote sensing reflectance from multiple spectral bands. CDOM algorithm also needs improvement to provide better separation between effects of gilvin (gelbstoff) and detritus. (Identification or development of such algorithm requires more data from in situ measurements of CDOM concentration in Gulf of Mexico coastal waters (ongoing collaboration with the EPA Gulf Ecology Division))

2017 STATE OF NARRAGANSETT BAY AND ITS WATERSHED – MAPPING DRIVERS OF CHANGE AND VARIATION

EPA Science Inventory

The Narragansett Bay Estuary Program (NBEP) developed 24 environmental indicators for its 2017 State of Narragansett Bay and Its Watershed report with the collaboration of over 50 bi-state (MA and RI) and regional partners. The report presents and tracks the 24 indicators in ord...

Automatic registration of terrestrial point clouds based on panoramic reflectance images and efficient BaySAC

NASA Astrophysics Data System (ADS)

Kang, Zhizhong

2013-10-01

This paper presents a new approach to automatic registration of terrestrial laser scanning (TLS) point clouds utilizing a novel robust estimation method by an efficient BaySAC (BAYes SAmpling Consensus). The proposed method directly generates reflectance images from 3D point clouds, and then using SIFT algorithm extracts keypoints to identify corresponding image points. The 3D corresponding points, from which transformation parameters between point clouds are computed, are acquired by mapping the 2D ones onto the point cloud. To remove false accepted correspondences, we implement a conditional sampling method to select the n data points with the highest inlier probabilities as a hypothesis set and update the inlier probabilities of each data point using simplified Bayes' rule for the purpose of improving the computation efficiency. The prior probability is estimated by the verification of the distance invariance between correspondences. The proposed approach is tested on four data sets acquired by three different scanners. The results show that, comparing with the performance of RANSAC, BaySAC leads to less iterations and cheaper computation cost when the hypothesis set is contaminated with more outliers. The registration results also indicate that, the proposed algorithm can achieve high registration accuracy on all experimental datasets.

Nitrogen Dioxide Total Column Over Terra Nova Bay Station - Antarctica - During 2001

NASA Astrophysics Data System (ADS)

Bortoli, D.; Ravegnani, F.; Giovanelli, G.; Petritoli, A.; Kostadinov, I.

GASCOD (Gas Analyzer Spectrometer Correlating Optical Differences), installed at the Italian Antarctic Station of Terra Nova Bay (TNB) - 74.69S, 164.12E - since 1995, carried out a full dataset of zenith scattered light measurements for the year 2001. The application of DOAS methodology to the collected data gave as final results, the slant column values for nitrogen dioxide. The seasonal variation shows a maxi- mum in the summer and it is in good agreement with the results obtained by other authors. The data analysis is performed by using different parameters like the po- tential vorticity (PV) at 500 K and the atmospheric temperatures at the same level. After the verification of the linear dependency between the NO2 slant column values and the temperature of NO2 cross section utilized in the DOAS algorithm, the actual stratospheric temperatures (from ECMWF) over TNB are applied to the results. The sensible changes in the nitrogen dioxide slant column values allow to highlight the good matching between the NO2 AM/PM ratio and the potential vorticity at 500 K. The NO2 slant column values follow the variations of the stratospheric temperature mainly during the spring season, when the lowest temperatures are observed and the ozone-hole phenomena mainly occur. ACKNOWLEDGMENTS: The author Daniele Bortoli was financially supported by the "Subprograma Ciência e Tecnologia do Ter- ceiro Quadro Comunitário de Apoio". The National Program for Antarctic Research (PNRA) supported this research.

Temporal and spatial patterns of phytoplankton production in Tomales Bay, California, U.S.A.

USGS Publications Warehouse

Cole, B.E.

1989-01-01

Primary productivity in the water column was measured 14 times between April 1985 and April 1986 at three sites in Tomales Bay, California, USA The conditions at these three stations encompassed the range of hydrographic conditions, phytoplankton biomass, phytoplankton community composition, and turbidity typical of this coastal embayment. Linear regression of the measured daily carbon uptake against the composite parameter B Zp Io (where B is the average phytoplankton biomass in the photic zone; Zp is the photic depth; and Io is the daily surface insolation) indicates that 90% of the variability in primary productivity is explained by variations in phytoplankton biomass and light availability. The linear function derived using Tomales Bay data is essentially the same as that which explains more than 80% of the variation in productivity in four other estuarine systems. Using the linear function and measured values for B, Zp, and Io, the daily photic-zone productivity was estimated for 10 sites at monthly intervals over the annual period. The average daily photic-zone productivity for the 10 sites ranged from 0??2 to 2??2 g C m-2. The bay-wide average annual primary productivity in the water column was 400 g C m-2, with most of the uptake occuring in spring and early summer. Spatial and temporal variations in primary productivity were similar to variations in phytoplankton biomass. Productivity was highest in the seaward and central regions of the bay and lowest in the shallow landward region. ?? 1989.

Determination of phytoplankton chlorophyll concentrations in the Chesapeake Bay with aircraft remote sensing

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.; Itsweire, Eric C.; Esaias, Wayne E.

1992-01-01

Remote sensing measurements of the distribution of phytoplankton chlorophyll concentrations in Chesapeake Bay during 1989 are described. It is shown that remote sensing from light aircraft can complement and extend measurements made from traditional platforms and provide data of improved temporal and spatial resolution, leading to a better understanding of phytoplankton dynamics in the estuary. The developments of the winter-spring diatom bloom in the polyhaline to mesohaline regions of the estuary and of the late-spring and summer dinoflagellate blooms in oligohaline and mesohaline regions are traced. The study presents the local chlorophyll algorithm developed using the NASA Ocean Data Acquisition System data and in situ chlorophyll data, interpolated maps of chlorophyll concentration generated by applying the algorithm to aircraft radiance data, ancillary in situ data on nutrients, turbidity, streamflow, and light availability, and an interpretation of phytoplankton dynamics in terms of the chlorophyll distribution in Chesapeake Bay during 1989.

Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women.

PubMed

Nassif, Houssam; Wu, Yirong; Page, David; Burnside, Elizabeth

2012-01-01

Overdiagnosis is a phenomenon in which screening identities cancer which may not go on to cause symptoms or death. Women over 65 who develop breast cancer bear the heaviest burden of overdiagnosis. This work introduces novel machine learning algorithms to improve diagnostic accuracy of breast cancer in aging populations. At the same time, we aim at minimizing unnecessary invasive procedures (thus decreasing false positives) and concomitantly addressing overdiagnosis. We develop a novel algorithm. Logical Differential Prediction Bayes Net (LDP-BN), that calculates the risk of breast disease based on mammography findings. LDP-BN uses Inductive Logic Programming (ILP) to learn relational rules, selects older-specific differentially predictive rules, and incorporates them into a Bayes Net, significantly improving its performance. In addition, LDP-BN offers valuable insight into the classification process, revealing novel older-specific rules that link mass presence to invasive, and calcification presence and lack of detectable mass to DCIS.

Mercury accumulation in Devils Lake, North Dakota effects of environmental variation in closed-basin lakes on mercury chronologies

USGS Publications Warehouse

Lent, R.M.; Alexander, C.R.

1997-01-01

Sediment cores were collected from lakes in the Devils Lake Basin in North Dakota to determine if mercury (Hg) accumulation chronologies from sediment-core data are good indicators of variations in Hg accumulation rates in saline lakes. Sediment cores from Creel Bay and Main Bay, Devils Lake were selected for detailed analysis and interpretation. The maximum Hg concentration in the Creel Bay core was 0.15 micrograms per gram at 8 to 9 centimeters. The maximum Hg concentration in the Main Bay core was 0.07 micrograms per gram at 5 to 7 centimeters. The general decreases in Hg concentrations with depth are attributed to historic variations in atmospheric Hg deposition rate. Hg stratigraphies combined with 210Pb and 137Cs dating analyses yield Hg chronologies that indicate a general increase in Hg accumulation rates in Devils Lake since the middle of the 19th century. Mean modern Hg accumulation rates in Creel Bay were 4.9 nanograms per square centimeter per year, and rates in Main Bay were 1.8 nanograms per square centimeter per year. Mean preindustrial Hg accumulation rates in Creel Bay were 1.2 nanograms per square centimeter per year, and rates in Main Bay were 1.6 nanograms per square centimeter per year. Relatively low Hg concentrations in recent sediments in the Devils Lake Basin, along with similarities in Hg accumulation rates between lakes in the Devils Lake Basin and other lakes in the northern interior of North America, indicate that local sources of Hg are not important sources of Hg. Results of the study indicate that accurate Hg chronologies are discernible in sediment cores collected from saline lakes. However, spatial and temporal variations in lake level and water chemistry common to saline lakes make interpretation of radioisotopic and geochemical chronologies difficult. Hg geochemistry in Devils Lake, and presumably in other saline lakes, is dynamic. The results of this study indicate that the absolute amount of sediment transported to Devils Lake, along with the associated Hg and total organic carbon, and the distribution of sedimentation patterns in Devils Lake may be affected by changing lake levels.

Variations of pollution sources of Cu in Jiaozhou Bay 1982-1986

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Li, Haixia; Wang, Qi; Ding, Jun; Zhang, Longlei

2017-12-01

Cu pollution in marine bays has been one of the critical environmental issues in the whole world, and understanding the variations of the pollution sources is essential to environmental protection. This paper identified the sources of Cu in Jiaozhou Bay during 1982-1986, and revealed the variations of the sources. Results showed that there were five Cu sources during study years including marine current, stream flow, island top, overland runoff and marine traffic, respectively, whose source strengths were varying from 0.39-20.60 μg L-1, 0.37-10.57 μg L-1, 0.77-4.86 μg L-1, 2.28-3.56 μg L-1, 9.48 μg L-1, respectively. These findings were helpful information in decision-making of pollution control and environmental remediation practice.

Diurnal and Tidal Variation of Temperature and Salinity in the Ponta Rasa Mangrove Swamp, Mozambique

NASA Astrophysics Data System (ADS)

Hoguane, A. M.; Hill, A. E.; Simpson, J. H.; Bowers, D. G.

1999-08-01

Measurements of hydrographic conditions in the Ponta Rasa tidal mangrove swamp, Inhaca Island, Mozambique were made in August-October 1994 during the winter dry season. The Ponta Rasa swamp/creek is tidally choked on account of the narrow channel that connects it to Maputo Bay and at neap tides, a sill prevents bay water entering the creek system altogether. Temperature variation in the swamp (15-25 °C) was predominantly diurnal with an additional signal due to the tidal advection of bay waters. There is no river discharge into Ponta Rasa and during the observation period, there was no significant rainfall. The mean salinity in the swamp ( c. 38) was controlled by evaporation and transpiration by mangroves and an overall evapotranspiration rate of 0·5 cm day -1was estimated from a steady salt balance. Salinity variation ( c. 2) was predominantly due to semi-diurnal tidal advection of lower salinity Maputo Bay water into the swamp/creek. A model which incorporates tidal dynamics coupled to heat and salt balance equations reproduces many of the observed features of the system.

Worsened physical condition due to climate change contributes to the increasing hypoxia in Chesapeake Bay.

PubMed

Du, Jiabi; Shen, Jian; Park, Kyeong; Wang, Ya Ping; Yu, Xin

2018-07-15

There are increasing concerns about the impact of worsened physical condition on hypoxia in a variety of coastal systems, especially considering the influence of changing climate. In this study, an EOF analysis of the DO data for 1985-2012, a long-term numerical simulation of vertical exchange, and statistical analysis were applied to understand the underlying mechanisms for the variation of DO condition in Chesapeake Bay. Three types of analysis consistently demonstrated that both biological and physical conditions contribute equally to seasonal and interannual variations of the hypoxic condition in Chesapeake Bay. We found the physical condition (vertical exchange+temperature) determines the spatial and seasonal pattern of the hypoxia in Chesapeake Bay. The EOF analysis showed that the first mode, which was highly related to the physical forcings and correlated with the summer hypoxia volume, can be well explained by seasonal and interannual variations of physical variables and biological activities, while the second mode is significantly correlated with the estuarine circulation and river discharge. The weakened vertical exchange and increased water temperature since the 1980s demonstrated a worsened physical condition over the past few decades. Under changing climate (e.g., warming, accelerated sea-level rise, altered precipitation and wind patterns), Chesapeake Bay is likely to experience a worsened physical condition, which will amplify the negative impact of anthropogenic inputs on eutrophication and consequently require more efforts for nutrient reduction to improve the water quality condition in Chesapeake Bay. Copyright © 2018 Elsevier B.V. All rights reserved.

Time scales of circulation and mixing processes of San Francisco Bay waters

USGS Publications Warehouse

Walters, R.A.; Cheng, R.T.; Conomos, T.J.

1985-01-01

Conceptual models for tidal period and low-frequency variations in sea level, currents, and mixing processes in the northern and southern reaches of San Francisco Bay describe the contrasting characteristics and dissimilar processes and rates in these embayments: The northern reach is a partially mixed estuary whereas the southern reach (South Bay) is a tidally oscillating lagoon with density-driven exchanges with the northern reach. The mixed semidiurnal tides are mixtures of progressive and standing waves. The relatively simple oscillations in South Bay are nearly standing waves, with energy propagating down the channels and dispersing into the broad shoal areas. The tides of the northern reach have the general properties of a progressive wave but are altered at the constriction of the embayments and gradually change in an upstream direction to a mixture of progressive and standing waves. The spring and neap variations of the tides are pronounced and cause fortnightly varying tidal currents that affect mixing and salinity stratification in the water column. Wind stress on the water surface, freshwater inflow, and tidal currents interacting with the complex bay configuration are the major local forcing mechanisms creating low-frequency variations in sea level and currents. These local forcing mechanisms drive the residual flows which, with tidal diffusion, control the water-replacement rates in the estuary. In the northern reach, the longitudinal density gradient drives an estuarine circulation in the channels, and the spatial variation in tidal amplitude creates a tidally-driven residual circulation. In contrast, South Bay exhibits a balance between wind-driven circulation and tidally-driven residual circulation for most of the year. During winter, however, there can be sufficient density variations to drive multilayer (2 to 3) flows in the channel of South Bay. Mixing models (that include both diffusive and dispersive processes) are based on time scales associated with salt variations at the boundaries and those associated with the local forcing mechanisms, while the spatial scales of variations are dependent upon the configuration of the embayments. In the northern reach, where the estuarine circulation is strong, the salt flux is carried by the mean advection of the mean salt field. Where large salinity gradients are present, the tidal correlation part of the salt flux is of the same order as the advective part. Our knowledge of mixing and exchange rates in South Bay is poor. As this embayment is nearly isohaline, the salt flux is dominated entirely by the mean advection of the mean salt field. During and after peaks in river discharge, water mixing becomes more dynamic, with a strong density-driven current creating a net exchange of both water mass and salt. These exchanges are stronger during neap tides. Residence times of the water masses vary seasonally and differ between reaches. In the northern reach, residence times are on the order of days for high winter river discharge and of months for summer periods. The residence times for South Bay are fairly long (on the order of several months) during summer, and typically shorter (less than a month) during winter when density-driven exchanges occur. ?? 1985 Dr W. Junk Publishers.

Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations

NASA Astrophysics Data System (ADS)

Le, Chengfeng; Hu, Chuanmin; English, David; Cannizzaro, Jennifer; Chen, Zhiqiang; Feng, Lian; Boler, Richard; Kovach, Charles

2013-02-01

Despite recent advances in using satellite data for continuous monitoring of estuarine water quality parameters such as turbidity and water clarity, estimating chlorophyll-a concentrations (Chla) has remained problematic due to the optical complexity of estuarine waters and imperfect atmospheric correction. This poses a significant challenge to the community as synoptic and frequent Chla “measurements” from satellites are in high demand by various government agencies and environmental groups to help make management decisions. Here, using 10 years of in situ and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from a moderately sized, turbid estuary, Tampa Bay (Florida, USA), we developed and validated a new algorithm specifically designed for retrieving Chla from MODIS data. The algorithm takes the red-to-green remote-sensing reflectance (Rrs(λ)) band ratio of [Rrs(667) + Rrs(678)]/[Rrs(531) + Rrs(547)] as the independent variable, and estimates Chla through the non-linear regression function: Ln(Chla) = 1.91Ln(x) + 3.40 (R2 = 0.87, N = 97, p < 0.01, 1.5 < Chla < 80 mg m-3) where ‘x' is the band ratio. Validation of the algorithm using two independent datasets collected by different groups and near-concurrent MODIS measurements showed robust algorithm performance for Chla within this range, with mean relative errors of 25.8% and 41.7% for the two datasets. Time-series analyses at representative stations using both in situ and MODIS Chla also showed general agreement, with instances of noticeable discrepancy attributed to different measurement frequencies. The algorithm was implemented to establish a 10-year Chla data record for Tampa Bay in order to serve as a baseline for monitoring future phytoplankton bloom events. The 10-year Chla data record showed substantial variability in both space and time, with generally higher Chla observed during the wet season and in upper bay segments, and Chla minima observed in all bay segments during May and June. These spatial and temporal distributions appear to be regulated primarily by wind and river discharge, which also explain the significant declining trend in Chla since 2005. The established 10-year MODIS-based Chla data record provides complementary information to existing field-based monitoring programs, helping to make nutrient reduction management decisions. Furthermore, preliminary tests of the algorithm for the Chesapeake Bay and for Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements suggest possible applicability of the proposed approach to other estuaries and satellite ocean color sensors.

Sentiment analysis: a comparison of deep learning neural network algorithm with SVM and naϊve Bayes for Indonesian text

NASA Astrophysics Data System (ADS)

Calvin Frans Mariel, Wahyu; Mariyah, Siti; Pramana, Setia

2018-03-01

Deep learning is a new era of machine learning techniques that essentially imitate the structure and function of the human brain. It is a development of deeper Artificial Neural Network (ANN) that uses more than one hidden layer. Deep Learning Neural Network has a great ability on recognizing patterns from various data types such as picture, audio, text, and many more. In this paper, the authors tries to measure that algorithm’s ability by applying it into the text classification. The classification task herein is done by considering the content of sentiment in a text which is also called as sentiment analysis. By using several combinations of text preprocessing and feature extraction techniques, we aim to compare the precise modelling results of Deep Learning Neural Network with the other two commonly used algorithms, the Naϊve Bayes and Support Vector Machine (SVM). This algorithm comparison uses Indonesian text data with balanced and unbalanced sentiment composition. Based on the experimental simulation, Deep Learning Neural Network clearly outperforms the Naϊve Bayes and SVM and offers a better F-1 Score while for the best feature extraction technique which improves that modelling result is Bigram.

Algorithm for computing descriptive statistics for very large data sets and the exa-scale era

NASA Astrophysics Data System (ADS)

Beekman, Izaak

2017-11-01

An algorithm for Single-point, Parallel, Online, Converging Statistics (SPOCS) is presented. It is suited for in situ analysis that traditionally would be relegated to post-processing, and can be used to monitor the statistical convergence and estimate the error/residual in the quantity-useful for uncertainty quantification too. Today, data may be generated at an overwhelming rate by numerical simulations and proliferating sensing apparatuses in experiments and engineering applications. Monitoring descriptive statistics in real time lets costly computations and experiments be gracefully aborted if an error has occurred, and monitoring the level of statistical convergence allows them to be run for the shortest amount of time required to obtain good results. This algorithm extends work by Pébay (Sandia Report SAND2008-6212). Pébay's algorithms are recast into a converging delta formulation, with provably favorable properties. The mean, variance, covariances and arbitrary higher order statistical moments are computed in one pass. The algorithm is tested using Sillero, Jiménez, & Moser's (2013, 2014) publicly available UPM high Reynolds number turbulent boundary layer data set, demonstrating numerical robustness, efficiency and other favorable properties.

From research to management: A remote sensing based water quality decision matrix (WQDM) for Tampa Bay, Florida

NASA Astrophysics Data System (ADS)

Hu, C.; Le, C.; English, D.; Cannizzaro, J.; Kovach, C.

2012-12-01

Significant advances have been made in ocean color remote sensing of water turbidity and water clarity of estuarine waters, yet accurate estimate of the water column chlorophyll-a concentrations (Chla in mg m-3) has been problematic. Here, a novel empirical Chla algorithm was developed and validated for MODIS and SeaWiFS observations between 1998 and 2011 for Tampa Bay, the largest estuary (~1000 km2) in the state of Florida, USA. The algorithm showed robust performance with two independent datasets, with relative mean uncertainties of ~30% and ~50% and RMS uncertainties of ~40% and ~65%,respectively, for Chla ranging between 1.0 and > 30.0 mg m-3. Together with other bio-optical parameters measured from this moderately turbid estuary, these data showed that although the total light absorption in the blue-green wavelengths is dominated by dissolved organic matter, the variability in light penetration (or water clarity) is mainly determined by particulate absorption rather than CDOM absorption. Thus, nutrient reduction management actions that reduce phytoplankton blooms can effectively increase the light availability on the bottom. Long-term Chla time series from SeaWiFS and MODIS observations showed both seasonal and inter-annual variations. On average, river discharge could explain ~60% of the seasonal changes and ~90% of the inter-annual changes, with the latter mainly driven by climate variability (e.g. El Niño and La Niño years) and anomaly events (e.g. tropical cyclones). Significant correlation was found between monthly mean Chla anomalies and monthly Multivariate ENSO Index (MEI) (Pearson correlation coefficient = 0.43, p<0.01, N=147), with high Chla associated with El Niño and lower Chla associated with La Niño. Further, a Water Quality Decision Matrix (WQDM) has been established from the satellite-based Chla and water clarity estimates. The WQDM provides complementary and more reliable information to the existing WQDM based on less synoptic and less frequent field measurements. These results support the decision making efforts of the management agencies that regulate nutrient discharge to the bay, and similar approaches may be established for other estuaries where field data are much more limited than for TampaBay.

The influence of negative training set size on machine learning-based virtual screening.

PubMed

Kurczab, Rafał; Smusz, Sabina; Bojarski, Andrzej J

2014-01-01

The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening.

The influence of negative training set size on machine learning-based virtual screening

PubMed Central

2014-01-01

Background The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. Results The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. Conclusions In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening. PMID:24976867

Fine-scale genetic population structure in a mobile marine mammal: inshore bottlenose dolphins in Moreton Bay, Australia.

PubMed

Ansmann, Ina C; Parra, Guido J; Lanyon, Janet M; Seddon, Jennifer M

2012-09-01

Highly mobile marine species in areas with no obvious geographic barriers are expected to show low levels of genetic differentiation. However, small-scale variation in habitat may lead to resource polymorphisms and drive local differentiation by adaptive divergence. Using nuclear microsatellite genotyping at 20 loci, and mitochondrial control region sequencing, we investigated fine-scale population structuring of inshore bottlenose dolphins (Tursiops aduncus) inhabiting a range of habitats in and around Moreton Bay, Australia. Bayesian structure analysis identified two genetic clusters within Moreton Bay, with evidence of admixture between them (F(ST) = 0.05, P = 0.001). There was only weak isolation by distance but one cluster of dolphins was more likely to be found in shallow southern areas and the other in the deeper waters of the central northern bay. In further analysis removing admixed individuals, southern dolphins appeared genetically restricted with lower levels of variation (AR = 3.252, π = 0.003) and high mean relatedness (r = 0.239) between individuals. In contrast, northern dolphins were more diverse (AR = 4.850, π = 0.009) and were mixing with a group of dolphins outside the bay (microsatellite-based STRUCTURE analysis), which appears to have historically been distinct from the bay dolphins (mtDNA Φ(ST) = 0.272, P < 0.001). This study demonstrates the ability of genetic techniques to expose fine-scale patterns of population structure and explore their origins and mechanisms. A complex variety of inter-related factors including local habitat variation, differential resource use, social behaviour and learning, and anthropogenic disturbances are likely to have played a role in driving fine-scale population structure among bottlenose dolphins in Moreton Bay. © 2012 Blackwell Publishing Ltd.

Fast Compressive Tracking.

PubMed

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

Rip currents, mega-cusps, and eroding dunes

USGS Publications Warehouse

Thornton, E.B.; MacMahan, J.; Sallenger, A.H.

2007-01-01

Dune erosion is shown to occur at the embayment of beach mega-cusps O(200 m alongshore) that are associated with rip currents. The beach is the narrowest at the embayment of the mega-cusps allowing the swash of large storm waves coincident with high tides to reach the toe of the dune, to undercut the dune and to cause dune erosion. Field measurements of dune, beach, and rip current morphology are acquired along an 18 km shoreline in southern Monterey Bay, California. This section of the bay consists of a sandy shoreline backed by extensive dunes, rising to heights exceeding 40 m. There is a large increase in wave height going from small wave heights in the shadow of a headland, to the center of the bay where convergence of waves owing to refraction over the Monterey Bay submarine canyon results in larger wave heights. The large alongshore gradient in wave height results in a concomitant alongshore gradient in morphodynamic scale. The strongly refracted waves and narrow bay aperture result in near normal wave incidence, resulting in well-developed, persistent rip currents along the entire shoreline. The alongshore variations of the cuspate shoreline are found significantly correlated with the alongshore variations in rip spacing at 95% confidence. The alongshore variations of the volume of dune erosion are found significantly correlated with alongshore variations of the cuspate shoreline at 95% confidence. Therefore, it is concluded the mega-cusps are associated with rip currents and that the location of dune erosion is associated with the embayment of the mega-cusp.

Machine Learning in the Presence of an Adversary: Attacking and Defending the SpamBayes Spam Filter

DTIC Science & Technology

2008-05-20

Machine learning techniques are often used for decision making in security critical applications such as intrusion detection and spam filtering...filter. The defenses shown in this thesis are able to work against the attacks developed against SpamBayes and are sufficiently generic to be easily extended into other statistical machine learning algorithms.

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

PubMed

Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

2018-02-01

Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to detect the dynamic muscle fatigue conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial and temporal variation in seagrass coverage in Southwest Florida: assessing the relative effects of anthropogenic nutrient load reductions and rainfall in four contiguous estuaries.

PubMed

Tomasko, D A; Corbett, C A; Greening, H S; Raulerson, G E

2005-08-01

The estuaries of Tampa Bay, Sarasota Bay, Lemon Bay, and Upper Charlotte Harbor are contiguous waterbodies located within the subtropical environment of Southwest Florida. Based on an examination of rainfall data over the period of record (1916-2001) within the watersheds of these estuaries, there is no evidence for spatial differences (at the watershed level) or monotonic trends in annual rainfall. During the 1980s, nitrogen loads into Tampa Bay and Sarasota Bay (generated primarily by domestic wastewater treatment facilities) were reduced by 57% and 46%, respectively. In response, both Tampa Bay and Sarasota Bay have lower phytoplankton concentrations, greater water clarity and more extensive seagrass coverage in 2002 than in the early 1980s. As there is no evidence of a concurrent trend in rainfall during the period of 1982-2001, it is unlikely that variation in rainfall can account for the observed increase in seagrass coverage in these two bays. In contrast, seagrass coverage has remained relatively constant since the mid 1980s in Lemon Bay and Charlotte Harbor. Domestic wastewater treatment facilities are minor sources of nitrogen to Lemon Bay, and water clarity in Charlotte Harbor varies mostly as a function of dissolved organic matter and non-chlorophyll associated turbidity, not phytoplankton levels. Even in estuaries that share boundaries and are within 100 km of each other, varied responses to anthropogenic changes and natural phenomena were observed in water quality and associated seagrass extent. Resource management strategies must take into account system-specific factors-not all strategies will result in similar results in different systems.

Applications of MODIS Fluorescence Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity in Coastal and Estuarine Waters

NASA Astrophysics Data System (ADS)

Fischer, A.; Ryan, J. P.; Moreno-Madriñán, M. J.

2012-12-01

Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS), calibration updates, improved aerosol retrievals, and new aerosol models have led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean-color. This has opened the way for studying coastal ocean phenomena and processes at finer spatial scales. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and increases in local concentrations of phytoplankton, which could result in harmful algal blooms. In two case studies we present improved and validated MODIS coastal observations of fluorescence line height (FLH) to: (1) assess trends in water quality for Tampa Bay, Florida; and (2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California, as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and imagery from Tampa Bay, we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout this large, optically complex estuarine system. A systematic analysis of sampling sites throughout the bay illustrates that the correlations between FLH and in situ chlorophyll-a are influenced by water quality parameters of total nitrogen, total phosphorous, turbidity and biological oxygen demand. Sites that correlated well with satellite imagery were in depths greater than seven meters and were located over five kilometers from shore. Satellite FLH estimates show improving water quality from 2003-2007 with a slight decline up through 2011. Dinoflagellate blooms in Monterey Bay, California have recently increased in frequency and intensity. Nine years of MODIS FLH observations are used to describe the annual and seasonal variability of bloom activity within the Bay. Three classes of MODIS algorithms were correlated against in situ chlorophyll measurements. The FLH algorithm provided the most robust estimate of bloom activity. Elevated concentrations of phytoplankton were evident during the months of August-November, a period during which increased occurrences of dinoflagellate blooms have been observed in situ. Seasonal patterns of FLH show the on- and offshore movement of areas of high phytoplankton biomass between oceanographic seasons. Higher concentrations of phytoplankton are also evident in the vicinity of the land-based nutrient sources and outflows, and cyclonic bay-wide circulation transports these nutrients to a northern Bay bloom incubation region. Both of these case studies illustrate the utility of improved MODIS FLH observations in supporting management decisions in coastal and estuarine waters.

Spatial variation of physicochemical and bacteriological parameters elucidation with GIS in Rangat Bay, Middle Andaman, India

NASA Astrophysics Data System (ADS)

Dheenan, P. S.; Jha, Dilip Kumar; Vinithkumar, N. V.; Ponmalar, A. Angelin; Venkateshwaran, P.; Kirubagaran, R.

2014-01-01

The purpose of this study was to determine the concentration, distribution of bacteria and physicochemical property of surface seawater in Rangat Bay, Middle Andaman, Andaman Islands (India). The bay experiences tidal variations. Perhaps physicochemical properties of seawater in Rangat Bay were found not to vary significantly. The concentration of faecal streptococci was high (2.2 × 103 CFU/100 mL) at creek and harbour area, whereas total coliforms were high (7.0 × 102 CFU/100 mL) at mangrove area. Similarly, total heterotrophic bacterial concentration was high (5.92 × 104 CFU/100 mL) in mangrove and harbour area. The Vibrio cholerae and Vibrio parahaemolyticus concentration was high (4.2 × 104 CFU/100 mL and 9 × 103 CFU/100 mL) at open sea. Cluster analysis showed grouping of stations in different tidal periods. The spatial maps clearly depicted the bacterial concentration pattern in the bay. The combined approach of multivariate analysis and spatial mapping techniques was proved to be useful in the current study.

Adaptive classifier for steel strip surface defects

NASA Astrophysics Data System (ADS)

Jiang, Mingming; Li, Guangyao; Xie, Li; Xiao, Mang; Yi, Li

2017-01-01

Surface defects detection system has been receiving increased attention as its precision, speed and less cost. One of the most challenges is reacting to accuracy deterioration with time as aged equipment and changed processes. These variables will make a tiny change to the real world model but a big impact on the classification result. In this paper, we propose a new adaptive classifier with a Bayes kernel (BYEC) which update the model with small sample to it adaptive for accuracy deterioration. Firstly, abundant features were introduced to cover lots of information about the defects. Secondly, we constructed a series of SVMs with the random subspace of the features. Then, a Bayes classifier was trained as an evolutionary kernel to fuse the results from base SVMs. Finally, we proposed the method to update the Bayes evolutionary kernel. The proposed algorithm is experimentally compared with different algorithms, experimental results demonstrate that the proposed method can be updated with small sample and fit the changed model well. Robustness, low requirement for samples and adaptive is presented in the experiment.

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

Yaquina Bay, Oregon, Intertidal Sediment Temperature Database, 1998 - 2006.

EPA Science Inventory

Detailed, long term sediment temperature records were obtained and compiled in a database to determine the influence of daily, monthly, seasonal and annual temperature variation on eelgrass distribution across the intertidal habitat in Yaquina Bay, Oregon. Both currently and hi...

BayMeth: improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach

PubMed Central

2014-01-01

Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package. PMID:24517713

Diurnal and Intra-Annual Variations in Greenhouse Gases at Fixed Sites in the San Francisco Bay Area

NASA Astrophysics Data System (ADS)

Newman, S.; Guha, A.; Martien, P. T.; Bower, J.; Perkins, I.; Randall, S.; Young, A.; Stevenson, E.; Hilken, H.

2017-12-01

The Bay Area Air Quality Management District, the San Francisco Bay Area's air quality regulatory agency, has set a goal to reduce the region's greenhouse gas (GHG) emissions to 80% below 1990 levels by 2050, consistent with the State of California's climate goals. Recently, the Air District's governing board adopted a 2017 Clean Air Plan which lays out the agency's vision and includes actions to put the region on a path towards achieving the 2050 goal while also reducing air pollution and related health impacts. The Plan includes GHG rule-making efforts, policy initiatives, local government partnerships, outreach, grants, and incentives, encompassing over 250 specific implementation actions across all economic sectors to effect ambitious emission reductions in the region. To track trends in atmospheric observations of GHGs and associated species and monitor changes in regional emission patterns, the Air District has established a fixed site network (CO2, CH4, CO) of one generally upwind site (Bodega Bay - on the coast north of Marin County) and three receptor sites (Bethel Island - east of the major refineries, in the Sacramento River Delta; Livermore - east of the bulk of the East Bay cities; and San Martin - south of the major city of San Jose). Having collected over a year of data for each of the fixed sites, the Air District is now investigating spatial and temporal variations in GHG emissions. Concentrating on variations in diurnal cycles, we see the commonly observed pattern of seasonal changes in diurnal amplitude at all sites, with larger variations during the winter than the summer, consistent with seasonally varying daily changes in planetary boundary layer heights. Investigations explore the weekday/weekend effect on the diurnal patterns and the effect of seasonal wind direction changes on the intra-annual variations of the local enhancements. The Air District is beginning to investigate the ways in which the fixed site network reflects the dominant upwind GHG emissions.

Flyway-scale variation in plasma triglyceride levels as an index of refueling rate in spring-migrating western sandpipers (Calidris mauri)

USGS Publications Warehouse

Williams, T.D.; Warnock, N.; Takekawa, John Y.; Bishop, M.A.

2007-01-01

We combined radiotelemetry, plasma metabolite analyses, and macro-invertebrate prey sampling to investigate variation in putative fattening rates (estimated as plasma triglyceride levels) at the flyway scale in Western Sandpipers (Calidris mauri) migrating between Punta Banda, Mexico (31°N), and Hartney Bay, Alaska (60°N), a distance of 4,240 km. Birds were caught at a wintering site (San Francisco Bay) and eight stopover sites along this Pacific Flyway. Body mass was higher in females than in males at six sites, but variation was not correlated with latitude for either sex, and the relationship of change in mass by date within sites was uninformative with regard to possible latitudinal variation in fattening rates. At San Francisco Bay, triglyceride levels were higher in the spring than in the winter. Mean plasma triglyceride varied among stopover sites, and there was a significant linear trend of increasing triglyceride levels with latitude as birds migrated north. At San Francisco Bay, length of stay was negatively related to triglyceride levels. However, plasma triglyceride levels at wintering or initial stopover sites (San Francisco and Punta Banda) did not predict individual variation in subsequent rates of travel during migration. We found no significant relationship between triglyceride levels and prey biomass at different stopover sites, which suggests that the latitudinal pattern is not explained by latitudinal changes in food availability. Rather, we suggest that differences in physiology of migratory birds at southern versus northern stopover sites or behavioral differences may allow birds to sustain higher fattening rates closer to the breeding grounds.

Qualitative and numerical analyses of the effects of river inflow variations on mixing diagrams in estuaries

USGS Publications Warehouse

Cifuentes, L.A.; Schemel, L.E.; Sharp, J.H.

1990-01-01

The effects of river inflow variations on alkalinity/salinity distributions in San Francisco Bay and nitrate/salinity distributions in Delaware Bay are described. One-dimensional, advective-dispersion equations for salinity and the dissolved constituents are solved numerically and are used to simulate mixing in the estuaries. These simulations account for time-varying river inflow, variations in estuarine cross-sectional area, and longitudinally varying dispersion coefficients. The model simulates field observations better than models that use constant hydrodynamic coefficients and uniform estuarine geometry. Furthermore, field observations and model simulations are consistent with theoretical 'predictions' that the curvature of propery-salinity distributions depends on the relation between the estuarine residence time and the period of river concentration variation. ?? 1990.

Chesapeake Bay Low Freshwater Inflow Study.

DTIC Science & Technology

1984-09-01

Flooding Study. The Chesapeake Bay The initial phase of the overall program Study Summary Report includes a de- involved the inventory and assessment... inventory of Chesapeake Bay’s water out put is expected to steadily increase, priority, and related land resources and an iden- There is authorized to be...daily, tation Studies. The final stages of the known, there is sufficient knowledge of seasonal, and yearly variations in salin- planning process

Spatiotemporal patterns of phytoplankton composition and abundance in the Maryland Coastal Bays: The influence of freshwater discharge and anthropogenic activities

NASA Astrophysics Data System (ADS)

Oseji, Ozuem F.; Chigbu, Paulinus; Oghenekaro, Efeturi; Waguespack, Yan; Chen, Nianhong

2018-07-01

The spatial and temporal variations in phytoplankton abundance and community structure in the northern and southern parts of the Maryland Coastal Bays (MCBs) that differ in anthropogenic activities and hydrological characteristics were studied in 2012 and 2013 using photosynthetic pigments as biomarkers. Phytoplankton pigment biomass and diversity were generally higher in the northern bays that receive high nutrient input from St. Martin River, than in the southern bays where nutrient levels were comparatively low. Sites close to the mouths of tributaries in northern and southern bays had higher nutrient levels, which favored the development of dinoflagellates, and nano- and picophytoplankton, than sites closer to the inlets. The microplankton dominated the phytoplankton community in spring (>90%) and decreased in relative abundance into fall (<60%) whereas nanoplankton peaked in summer or fall. Picoplankton relative abundance increased from late spring (<10%, March 2012 & 2013) to summer (40%, July 2012 and August 2013) and was correlated positively with NH4+ and negatively with salinity. The observed spatial and seasonal patterns of phytoplankton relative abundance and diversity are likely due to changes in nutrient concentrations and ratios, driven by variations in freshwater discharge, and selective grazing of phytoplankton. Water quality management in the MCBs should continue to focus on reducing nutrient inputs into the bays.

Bayesian methods for estimating GEBVs of threshold traits

PubMed Central

Wang, C-L; Ding, X-D; Wang, J-Y; Liu, J-F; Fu, W-X; Zhang, Z; Yin, Z-J; Zhang, Q

2013-01-01

Estimation of genomic breeding values is the key step in genomic selection (GS). Many methods have been proposed for continuous traits, but methods for threshold traits are still scarce. Here we introduced threshold model to the framework of GS, and specifically, we extended the three Bayesian methods BayesA, BayesB and BayesCπ on the basis of threshold model for estimating genomic breeding values of threshold traits, and the extended methods are correspondingly termed BayesTA, BayesTB and BayesTCπ. Computing procedures of the three BayesT methods using Markov Chain Monte Carlo algorithm were derived. A simulation study was performed to investigate the benefit of the presented methods in accuracy with the genomic estimated breeding values (GEBVs) for threshold traits. Factors affecting the performance of the three BayesT methods were addressed. As expected, the three BayesT methods generally performed better than the corresponding normal Bayesian methods, in particular when the number of phenotypic categories was small. In the standard scenario (number of categories=2, incidence=30%, number of quantitative trait loci=50, h2=0.3), the accuracies were improved by 30.4%, 2.4%, and 5.7% points, respectively. In most scenarios, BayesTB and BayesTCπ generated similar accuracies and both performed better than BayesTA. In conclusion, our work proved that threshold model fits well for predicting GEBVs of threshold traits, and BayesTCπ is supposed to be the method of choice for GS of threshold traits. PMID:23149458

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

PubMed Central

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

PubMed

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

Long-term simulation of vertical transport process and its impact on bottom DO in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Du, J.; Shen, J.

2016-02-01

Hypoxia in coastal waters is a widespread phenomenon that appears to have been growing globally for at least 60 years. The fact that physical transport processes and biological processes are equally important in determining the bottom DO in Chesapeake Bay is commonly agreed. However, the quantitative impact of physical transport processes is rarely documented. In this study, we use a timescale, vertical exchange time (VET), to quantify the impact of all physical processes that might have on the bottom DO. Simulation of VET from 1985 to 2012 is conducted and the monthly observed DO data along the deep channel in the Bay's main stem is collected. A conceptual bottom DO budget model is applied, using the VET to quantify the physical condition and net oxygen consumption rate to quantify biological activities. The DO budget model results show that the interannual variations of physical conditions accounts for 88.8% of the interannual variations of observed DO. The high similarity between the VET spatial pattern and the observed DO suggests that physical processes play a key role in regulating the DO condition. Model results also show that long-term VET has a slight increase in summer, but no statistically significant trend is found. Correlations among southerly wind strength, North Atlantic Oscillation index, and VET demonstrate that the physical condition in the Chesapeake Bay is highly controlled by the large-scale climate variation. The relationship is most significant during the summer, when the southerly wind dominates throughout the Chesapeake Bay.

Optical Algorithms at Satellite Wavelengths for Total Suspended Matter in Tropical Coastal Waters.

PubMed

Ouillon, Sylvain; Douillet, Pascal; Petrenko, Anne; Neveux, Jacques; Dupouy, Cécile; Froidefond, Jean-Marie; Andréfouët, Serge; Muñoz-Caravaca, Alain

2008-07-10

Is it possible to derive accurately Total Suspended Matter concentration or its proxy, turbidity, from remote sensing data in tropical coastal lagoon waters? To investigate this question, hyperspectral remote sensing reflectance, turbidity and chlorophyll pigment concentration were measured in three coral reef lagoons. The three sites enabled us to get data over very diverse environments: oligotrophic and sediment-poor waters in the southwest lagoon of New Caledonia, eutrophic waters in the Cienfuegos Bay (Cuba), and sediment-rich waters in the Laucala Bay (Fiji). In this paper, optical algorithms for turbidity are presented per site based on 113 stations in New Caledonia, 24 stations in Cuba and 56 stations in Fiji. Empirical algorithms are tested at satellite wavebands useful to coastal applications. Global algorithms are also derived for the merged data set (193 stations). The performances of global and local regression algorithms are compared. The best one-band algorithms on all the measurements are obtained at 681 nm using either a polynomial or a power model. The best two-band algorithms are obtained with R412/R620, R443/R670 and R510/R681. Two three-band algorithms based on Rrs620.Rrs681/Rrs412 and Rrs620.Rrs681/Rrs510 also give fair regression statistics. Finally, we propose a global algorithm based on one or three bands: turbidity is first calculated from Rrs681 and then, if < 1 FTU, it is recalculated using an algorithm based on Rrs620.Rrs681/Rrs412. On our data set, this algorithm is suitable for the 0.2-25 FTU turbidity range and for the three sites sampled (mean bias: 3.6 %, rms: 35%, mean quadratic error: 1.4 FTU). This shows that defining global empirical turbidity algorithms in tropical coastal waters is at reach.

Seasonal variations and sources of sedimentary organic carbon in Tokyo Bay.

PubMed

Kubo, Atsushi; Kanda, Jota

2017-01-30

Total organic carbon (TOC), total nitrogen (TN) contents, their stable C and N isotope ratio (δ 13 C and δ 15 N), and chlorophyll a ([Chl a] sed ) of surface sediments were investigated monthly to identify the seasonal variations and sources of organic matter in Tokyo Bay. The sedimentary TOC (TOC sed ) and TN (TN sed ) contents, and the sedimentary δ 13 C and δ 15 N (δ 13 C sed and δ 15 N sed ) values were higher in summer than other seasons. The seasonal variations were controlled by high primary production in the water column and hypoxic water in the bottom water during summer. The fraction of terrestrial and marine derived organic matter was estimated by Bayesian mixing model using stable isotope data and TOC/TN ratio. Surface sediments in Tokyo Bay are dominated by marine derived organic matter, which accounts for about 69±5% of TOC sed . Copyright © 2016 Elsevier Ltd. All rights reserved.

SEASONAL VARIATION IN THE BIOGEOCHEMICAL CYCLING OF SESTON IN GRAND TRAVERSE BAY, LAKE MICHIGAN. (R825151)

EPA Science Inventory

This study describes the biogeochemical cycling of seston in Grand Traverse Bay, Lake Michigan. Seston was characterized by carbon and nitrogen elemental and isotopic abundances. Fluorescence, temperature, light transmittance, and concentrations of dissolved inorganic nitrogen we...

Latitudinal variation in population structure of wintering Pacific Black Brant

USGS Publications Warehouse

Schamber, J.L.; Sedinger, J.S.; Ward, D.H.; Hagmeier, K.R.

2007-01-01

Latitudinal variation in population structure during the winter has been reported in many migratory birds, but has been documented in few species of waterfowl. Variation in environmental and social conditions at wintering sites can potentially influence the population dynamics of differential migrants. We examined latitudinal variation in sex and age classes of wintering Pacific Black Brant (Branta bernicla nigricans). Brant are distributed along a wide latitudinal gradient from Alaska to Mexico during the winter. Accordingly, migration distances for brant using different wintering locations are highly variable and winter settlement patterns are likely associated with a spatially variable food resource. We used resightings of brant banded in southwestern Alaska to examine sex and age ratios of birds wintering at Boundary Bay in British Columbia, and at San Quintin Bay, Ojo de Liebre Lagoon, and San Ignacio Lagoon in Baja California from 1998 to 2000. Sex ratios were similar among wintering locations for adults and were consistent with the mating strategy of geese. The distribution of juveniles varied among wintering areas, with greater proportions of juveniles observed at northern (San Quintin Bay and Ojo de Liebre Lagoon) than at southern (San Ignacio Lagoon) locations in Baja California. We suggest that age-related variation in the winter distribution of Pacific Black Brant is mediated by variation in productivity among individuals at different wintering locations and by social interactions among wintering family groups.

Baleen whale ecology and feeding habitat use in the Bay of Fundy, Canada

NASA Astrophysics Data System (ADS)

Davies, K. T. A.; Brown, M.; Taggart, C. T.

2016-02-01

The Bay of Fundy on the east coast of Canada contains a rich supply of zooplankton and fish that provide food for diverse baleen whales. Endangered North Atlantic right whales and other large baleen whales have been monitored in the Bay of Fundy at least weekly during every summer since the 1980s. Over the most recent years, significant declines in sightings and residency of the right whales have been observed in this habitat; hypothetically indicative of a substantial and multi-year reduction in food supply. Whether concurrent changes in other baleen whales and, by inference, their respective food supplies have also occurred is unknown. This study quantifies changes in baleen whale ecology in the Bay over three decades with a focus on comparing (1) recent declines in right whale sightings to long-term historical trends, and (2) variation in right whale sightings to other large baleen whale species who share similar zooplankton food sources (e.g., sei whales) or rely on different food sources (e.g., fin, humpback). First, survey effort is reconstructed as survey track-length and as time-on-effort, and the space-time variations in effort are quantified. Then, variation in whale density indices and residency among surveys and survey-years are examined through effort-corrected sightings of all baleen whale species, as well as effort-corrected sightings of photo-identified right whale individuals. Results are then interpreted within the context of the oceanographic and food supply variation in the habitat.

Lateral variation in crustal and mantle structure in Bay of Bengal based on surface wave data

NASA Astrophysics Data System (ADS)

Kumar, Amit; Mukhopadhyay, Sagarika; Kumar, Naresh; Baidya, P. R.

2018-01-01

Surface waves generated by earthquakes that occurred near Sumatra, Andaman-Nicobar Island chain and Sunda arc are used to estimate crustal and upper mantle S wave velocity structure of Bay of Bengal. Records of these seismic events at various stations located along the eastern coast of India and a few stations in the north eastern part of India are selected for such analysis. These stations lie within regional distance of the selected earthquakes. The selected events are shallow focused with magnitude greater than 5.5. Data of 65, 37, 36, 53 and 36 events recorded at Shillong, Bokaro, Visakhapatnam, Chennai and Trivandrum stations respectively are used for this purpose. The ray paths from the earthquake source to the recording stations cover different parts of the Bay of Bengal. Multiple Filtering Technique (MFT) is applied to compute the group velocities of surface waves from the available data. The dispersion curves thus obtained for this data set are within the period range of 15-120 s. Joint inversion of Rayleigh and Love wave group velocity is carried out to obtain the subsurface information in terms of variation of S wave velocity with depth. The estimated S wave velocity at a given depth and layer thickness can be considered to be an average value for the entire path covered by the corresponding ray paths. However, we observe variation in the value of S wave velocity and layer thickness from data recorded at different stations, indicating lateral variation in these two parameters. Thick deposition of sediments is observed along the paths followed by surface waves to Shillong and Bokaro stations. Sediment thickness keeps on decreasing as the surface wave paths move further south. Based on velocity variation the sedimentary layer is further divided in to three parts; on top lay unconsolidated sediment, underlain by consolidated sediment. Below this lies a layer which we consider as meta-sediments. The thickness and velocity of these layers decrease from north to south. The crustal material has higher velocity at the southern part compared to that at the northern part of Bay of Bengal indicating that it changes from more oceanic type in the southern part of the Bay to more continental type to its north. Both Moho and lithosphere - asthenosphere boundary (LAB) dips gently towards north. Thicknesses of both lithosphere and asthenosphere also increase in the same direction. The mantle structure shows complex variation from south to north indicating possible effect of repeated changes in type of tectonic activity in the Bay of Bengal.

Discriminative Relational Topic Models.

PubMed

Chen, Ning; Zhu, Jun; Xia, Fei; Zhang, Bo

2015-05-01

Relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents for document networks, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving prediction performance.

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

PubMed

Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi

2017-11-02

Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

Regional contamination versus regional dietary differences: Understanding geographic variation in brominated and chlorinated contaminant levels in polar bears

USGS Publications Warehouse

McKinney, M.A.; Letcher, R.J.; Aars, Jon; Born, E.W.; Branigan, M.; Dietz, R.; Evans, T.J.; Gabrielsen, G.W.; Muir, D.C.G.; Peacock, E.; Sonne, C.

2011-01-01

The relative contribution of regional contamination versus dietary differences to geographic variation in polar bear (Ursus maritimus) contaminant levels is unknown. Dietary variation between Alaska Canada, East Greenland, and Svalbard subpopulations was assessed by muscle nitrogen and carbon stable isotope (?? 15N, ?? 13C) and adipose fatty acid (FA) signatures relative to their main prey (ringed seals). Western and southern Hudson Bay signatures were characterized by depleted ?? 15N and ??13C, lower proportions of C20 and C22 monounsaturated FAs and higher proportions of C18 and longer chain polyunsaturated FAs. East Greenland and Svalbard signatures were reversed relative to Hudson Bay. Alaskan ?? 2011 American Chemical Society.

Universal Darwinism As a Process of Bayesian Inference.

PubMed

Campbell, John O

2016-01-01

Many of the mathematical frameworks describing natural selection are equivalent to Bayes' Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus, natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an "experiment" in the external world environment, and the results of that "experiment" or the "surprise" entailed by predicted and actual outcomes of the "experiment." Minimization of free energy implies that the implicit measure of "surprise" experienced serves to update the generative model in a Bayesian manner. This description closely accords with the mechanisms of generalized Darwinian process proposed both by Dawkins, in terms of replicators and vehicles, and Campbell, in terms of inferential systems. Bayesian inference is an algorithm for the accumulation of evidence-based knowledge. This algorithm is now seen to operate over a wide range of evolutionary processes, including natural selection, the evolution of mental models and cultural evolutionary processes, notably including science itself. The variational principle of free energy minimization may thus serve as a unifying mathematical framework for universal Darwinism, the study of evolutionary processes operating throughout nature.

Universal Darwinism As a Process of Bayesian Inference

PubMed Central

Campbell, John O.

2016-01-01

Many of the mathematical frameworks describing natural selection are equivalent to Bayes' Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus, natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an “experiment” in the external world environment, and the results of that “experiment” or the “surprise” entailed by predicted and actual outcomes of the “experiment.” Minimization of free energy implies that the implicit measure of “surprise” experienced serves to update the generative model in a Bayesian manner. This description closely accords with the mechanisms of generalized Darwinian process proposed both by Dawkins, in terms of replicators and vehicles, and Campbell, in terms of inferential systems. Bayesian inference is an algorithm for the accumulation of evidence-based knowledge. This algorithm is now seen to operate over a wide range of evolutionary processes, including natural selection, the evolution of mental models and cultural evolutionary processes, notably including science itself. The variational principle of free energy minimization may thus serve as a unifying mathematical framework for universal Darwinism, the study of evolutionary processes operating throughout nature. PMID:27375438

Age and growth of round gobies in Lake Huron: Implications for food web dynamics

USGS Publications Warehouse

Duan, You J.; Madenjian, Charles P.; Xie, Cong X.; Diana, James S.; O'Brien, Timothy P.; Zhao, Ying M.; He, Ji X.; Farha, Steve A.; Huo, Bin

2016-01-01

Although the round goby (Neogobius melanostomus) has become established throughout the Laurentian Great Lakes, information is scarce on spatial variation in round goby growth between and within lakes. Based on a sample of 754 specimens captured in 2014, age, growth, and mortality of round gobies at four locations in Lake Huron were assessed via otolith analysis. Total length (TL) of round gobies ranged from 44 to 111 mm for Saginaw Bay, from 45 to 115 mm for Rockport, from 50 to 123 mm for Hammond Bay, and from 51 to 118 mm for Thunder Bay. Estimated ages of round gobies ranged from 2 to 5 years for Saginaw Bay, from 2 to 6 years for Rockport, and from 2 to 7 years for Hammond Bay and Thunder Bay. Sex-specific, body–otolith relationships were used to back-calculate total lengths at age, which were then fitted to von Bertalanffy growth models. For each sex, round goby growth showed significant spatial variation among the four locations within Lake Huron. At all four locations in Lake Huron, males grew significantly faster than females and attained a larger asymptotic length than females. Annual mortality rate estimates were high (62 to 85%), based on catch-curve analysis, suggesting that round gobies may be under predatory control in Lake Huron.

Diurnal variation in rates of calcification and carbonate sediment dissolution in Florida Bay

USGS Publications Warehouse

Yates, K.K.; Halley, R.B.

2006-01-01

Water quality and circulation in Florida Bay (a shallow, subtropical estuary in south Florida) are highly dependent upon the development and evolution of carbonate mud banks distributed throughout the Bay. Predicting the effect of natural and anthropogenic perturbations on carbonate sedimentation requires an understanding of annual, seasonal, and daily variations in the biogenic and inorganic processes affecting carbonate sediment precipitation and dissolution. In this study, net calcification rates were measured over diurnal cycles on 27 d during summer and winter from 1999 to 2003 on mud banks and four representative substrate types located within basins between mud banks. Substrate types that were measured in basins include seagrass beds of sparse and intermediate density Thalassia sp., mud bottom, and hard bottom communities. Changes in total alkalinity were used as a proxy for calcification and dissolution. On 22 d (81%), diurnal variation in rates of net calcification was observed. The highest rates of net carbonate sediment production (or lowest rates of net dissolution) generally occurred during daylight hours and ranged from 2.900 to -0.410 g CaCO3 m-2 d-1. The lowest rates of carbonate sediment production (or net sediment dissolution) occurred at night and ranged from 0.210 to -1.900 g CaCO3 m -2 night-1. During typical diurnal cycles, dissolution during the night consumed an average of 29% of sediment produced during the day on banks and 68% of sediment produced during the day in basins. Net sediment dissolution also occurred during daylight, but only when there was total cloud cover, high turbidity, or hypersalinity. Diurnal variation in calcification and dissolution in surface waters and surface sediments of Florida Bay is linked to cycling of carbon dioxide through photosynthesis and respiration. Estimation of long-term sediment accumulation rates from diurnal rates of carbonate sediment production measured in this study indicates an overall average accumulation rate for Florida Bay of 8.7 cm 1000 yr-1 and suggests that sediment dissolution plays a more important role than sediment transport in loss of sediment from Florida Bay. ?? 2006 Estuarine Research Federation.

A hybrid approach to select features and classify diseases based on medical data

NASA Astrophysics Data System (ADS)

AbdelLatif, Hisham; Luo, Jiawei

2018-03-01

Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm.

PubMed

Chapman, Brian E; Lee, Sean; Kang, Hyunseok Peter; Chapman, Wendy W

2011-10-01

In this paper we describe an application called peFinder for document-level classification of CT pulmonary angiography reports. peFinder is based on a generalized version of the ConText algorithm, a simple text processing algorithm for identifying features in clinical report documents. peFinder was used to answer questions about the disease state (pulmonary emboli present or absent), the certainty state of the diagnosis (uncertainty present or absent), the temporal state of an identified pulmonary embolus (acute or chronic), and the technical quality state of the exam (diagnostic or not diagnostic). Gold standard answers for each question were determined from the consensus classifications of three human annotators. peFinder results were compared to naive Bayes' classifiers using unigrams and bigrams. The sensitivities (and positive predictive values) for peFinder were 0.98(0.83), 0.86(0.96), 0.94(0.93), and 0.60(0.90) for disease state, quality state, certainty state, and temporal state respectively, compared to 0.68(0.77), 0.67(0.87), 0.62(0.82), and 0.04(0.25) for the naive Bayes' classifier using unigrams, and 0.75(0.79), 0.52(0.69), 0.59(0.84), and 0.04(0.25) for the naive Bayes' classifier using bigrams. Copyright © 2011 Elsevier Inc. All rights reserved.

Numerical study of water residence time in the Yueqing Bay based on the eulerian approach

NASA Astrophysics Data System (ADS)

Ying, Chao; Li, Xinwen; Liu, Yong; Yao, Wenwei; Li, Ruijie

2018-05-01

The Yueqing Bay was a semi-enclosed bay located in the southeast of Zhejiang Province, China. Due to substantial anthropogenic influences since 1964, the water quality in the bay had deteriorated seriously. Thus urgent measures should be taken to protect the water body. In this study, a numerical model was calibrated for water surface elevation and tidal current from August 14 to August 26, 2011. Comparisons of observed and simulated data showed that the model reproduced the tidal range and phase and the variations of current at different periods fairly well. The calibrated model was then applied to investigate spatial flushing pattern of the bay by calculation of residence time. The results obtained from a series of model experiments demonstrated that the residence time increased from 10 day at the bay mouth to more than 70 day at the upper bay. The average residence time over the whole bay was 49.5 day. In addition, the adaptation of flushing homogeneity curve showed that the residence time in the bay varied smoothly. This study provides a numerical tool to quantify the transport timescale in Yueqing Bay and supports adaptive management of the bay by local authorities.

Generation of periodic intrusions at Suruga Bay when the Kuroshio follows a large meandering path

NASA Astrophysics Data System (ADS)

Katsumata, Takaaki

2016-07-01

We measured the vertical profiles of currents at the eastern mouth of the Suruga Bay using a moored acoustic Doppler current profiler (ADCP). Currents vertical profiles were found to be mostly barotropic in structure when intrusions occurred at the eastern mouth of the bay. Warm-water intrusions at the Suruga Bay and sea level elevations at the bay and at islands on the Izu Ridge located off the bay have the same period of 26 days. The temporal variation in the sea levels occurs in response to Kuroshio frontal waves, and the two phases are consistent. The sea level rise propagates from Hachijo Island to the Suruga Bay via Miyake Island and Kozu Island, i.e., from off the Suruga Bay to in or near the bay. The perturbation of the sea level along the Izu Ridge occurs as waves with a period of 26 days, a wavelength of 500 km, and a phase speed of 23 cm/sec. The propagated waves and those of the Kuroshio frontal waves have the same features. This means that the periodic inflows at the eastern mouth of the Suruga Bay are caused by the passage of Kuroshio frontal waves off the bay.

Decoupling the influence of biological and physical processes on the dissolved oxygen in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Du, Jiabi; Shen, Jian

2015-01-01

is instructive and essential to decouple the effects of biological and physical processes on the dissolved oxygen condition, in order to understand their contribution to the interannual variability of hypoxia in Chesapeake Bay since the 1980s. A conceptual bottom DO budget model is applied, using the vertical exchange time scale (VET) to quantify the physical condition and net oxygen consumption rate to quantify biological activities. By combining observed DO data and modeled VET values along the main stem of the Chesapeake Bay, the monthly net bottom DO consumption rate was estimated for 1985-2012. The DO budget model results show that the interannual variations of physical conditions accounts for 88.8% of the interannual variations of observed DO. The high similarity between the VET spatial pattern and the observed DO suggests that physical processes play a key role in regulating the DO condition. Model results also show that long-term VET has a slight increase in summer, but no statistically significant trend is found. Correlations among southerly wind strength, North Atlantic Oscillation index, and VET demonstrate that the physical condition in the Chesapeake Bay is highly controlled by the large-scale climate variation. The relationship is most significant during the summer, when the southerly wind dominates throughout the Chesapeake Bay. The seasonal pattern of the averaged net bottom DO consumption rate (B'20) along the main stem coincides with that of the chlorophyll-a concentration. A significant correlation between nutrient loading and B'20 suggests that the biological processes in April-May are most sensitive to the nutrient loading.

The Mid-Latitude Positive Bay and the MPB Index of Substorm Activity

NASA Astrophysics Data System (ADS)

McPherron, Robert L.; Chu, Xiangning

2017-03-01

Substorms are a major source of magnetic activity. At substorm expansion phase onset a westward current flows through the expanding aurora. This current is the ionospheric closure of the substorm current wedge produced by diversion of tail current along magnetic field lines. At low latitudes the field-aligned currents create a systematic pattern in the north (X) and east (Y) components of the surface magnetic field. The rise and decay in X is called a midlatitude positive bay whose start is a proxy for expansion onset. In this paper we describe a new index called the midlatitude positive bay index (MPB) which monitors the power in the substorm perturbations of X and Y. The index is obtained by removing the main field, storm time variations, and the solar quiet (Sq) variation from the measured field. These are estimated with spline fits and principal component analysis. The residuals of X and Y are high pass filtered to eliminate variations with period longer than 3 hours. The sum of squares of the X and Y power is determined at each of 35 midlatitude stations. The average power in night time stations is the MPB index. The index series is standardized and intervals above a fixed threshold are taken as possible bay signatures. Post processing constrains these to have reasonable values of rise time, strength, and duration. Minima in the index before and after the peak are taken as the start and end of the bay. The MPB and AL indices can be used to identify quiet intervals in the magnetic field.

Variational Bayesian Parameter Estimation Techniques for the General Linear Model

PubMed Central

Starke, Ludger; Ostwald, Dirk

2017-01-01

Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation techniques are rarely covered in introductory statistical texts. Because of the widespread practical use of VB, VML, ReML, and ML in the neuroimaging community, we reasoned that a theoretical treatment of their relationships and their application in a basic modeling scenario may be helpful for both neuroimaging novices and practitioners alike. In this technical study, we thus revisit the conceptual and formal underpinnings of VB, VML, ReML, and ML and provide a detailed account of their mathematical relationships and implementational details. We further apply VB, VML, ReML, and ML to the general linear model (GLM) with non-spherical error covariance as commonly encountered in the first-level analysis of fMRI data. To this end, we explicitly derive the corresponding free energy objective functions and ensuing iterative algorithms. Finally, in the applied part of our study, we evaluate the parameter and model recovery properties of VB, VML, ReML, and ML, first in an exemplary setting and then in the analysis of experimental fMRI data acquired from a single participant under visual stimulation. PMID:28966572

Preliminary hydrodynamic analysis of landslide-generated waves in Tidal Inlet, Glacier Bay National Park, Alaska

USGS Publications Warehouse

Geist, Eric L.; Jakob, Matthias; Wieczoreck, Gerald F.; Dartnell, Peter

2003-01-01

A landslide block perched on the northern wall of Tidal Inlet, Glacier Bay National Park (Figure 1), has the potential to generate large waves in Tidal Inlet and the western arm of Glacier Bay if it were to fail catastrophically. Landslide-generated waves are a particular concern for cruise ships transiting through Glacier Bay on a daily basis during the summer months. The objective of this study is to estimate the range of wave amplitudes and periods in the western arm of Glacier Bay from a catastrophic landslide in Tidal Inlet. This study draws upon preliminary findings of a field survey by Wieczorek et al. (2003), and evaluates the effects of variations in landslide source parameters on the wave characteristics.

Variations in the Nd isotope composition of Late Miocene to Early Pliocene glacially derived sediments in Prydz Bay, East Antarctica

NASA Astrophysics Data System (ADS)

Mabson, M.; Pierce, E. L.; Dale, C. L.; Williams, T.; Hemming, S. R.; van de Flierdt, T.; Cook, C.; Goldstein, S. L.

2010-12-01

Michelle Mabson (Howard University), Elizabeth Pierce (Lamont-Doherty Earth Observatory, Columbia University), Cathleen Doherty (Lamont-Doherty Earth Observatory, Columbia University), Trevor Williams (Lamont-Doherty Earth Observatory), Sidney Hemming (Lamont-Doherty Earth Observatory), Tina van de Flierdt (Imperial College London), Carys Cook (Imperial College London), Steve Goldstein (Lamont-Doherty Earth Observatory) Since initiation of major ice sheets on Antarctica at about 34 Ma, Antarctica has been a major player in global climate change. Understanding the response of the East Antarctic Ice Sheet to major climate changes through the Cenozoic has fundamental importance to both Earth Sciences and Society. Previous study of Nd isotope composition of sediments at Ocean Drilling Program (ODP) Site 1166 within Prydz Bay found evidence for variations of the Nd isotope composition between -15 to -30 epsilon units through this pre-glacial to glacial record (van de Flierdt et al., 2008, GRL). The Nd isotope composition of sediments provides an estimate for the average continental crust formation age of the sources. The sources around Prydz Bay have a wide range of formation ages, from Archean to Phanerozoic, so the areas which were being preferentially eroded can be inferred. This study seeks to contribute evidence for the local variations in provenance of sediments by extending the record of Nd isotope variations to ODP Site 739 in Prydz Bay. ODP Site 1165 has an unconformity that spans ~30-3 Ma. This part of the record is much more complete in ODP site 739, located about 200 km from the coast of Prydz Bay, probably more protected from ice stream erosion in the Prydz Channel. Because of its location we can conclude that the sediment deposited into this area is derived from the Lambert Glacier, and thus the variations in epsilon Nd will allow testing whether changes in the extent of this ice stream could lead to variations in the provenance of sediment carried by this ice. Recently Williams et al. (2010, EPSL) published evidence for dramatic changes in the sources of glacially derived sediments at ODP Site 1165, further offshore from Prydz Bay, at 7, 4.8 and 3.5 Ma. Their interpretation was based on the Ar-Ar ages of detrital hornblende grains, but samples taken across the 4.8 Ma event also showed an intriguing variation of the Nd isotope composition. The older part of the event includes a significant fraction of exotic Ar-Ar ages, but with epsilon Nd similar to the background values, while the younger part of the event shows a significant decrease in epsilon Nd but Ar-Ar of local origin. The specific goal of this study is to test the hypothesis that the shift to lower epsilon Nd in the 4.8 Ma ice rafting event is due to dynamical changes in the Prydz Bay sector of the East Antarctic ice sheet. Alternatively, the Lambert glacier may have retreated far enough to allow other sources in this sector to dominate the sediment composition in core 1165.

LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

NASA Astrophysics Data System (ADS)

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek; Stohl, Andreas

2016-11-01

Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. It is typically formalized as an inverse problem using a linear model that can explain observable quantities (e.g., concentrations or deposition values) as a product of the source-receptor sensitivity (SRS) matrix obtained from an atmospheric transport model multiplied by the unknown source-term vector. Since this problem is typically ill-posed, current state-of-the-art methods are based on regularization of the problem and solution of a formulated optimization problem. This procedure depends on manual settings of uncertainties that are often very poorly quantified, effectively making them tuning parameters. We formulate a probabilistic model, that has the same maximum likelihood solution as the conventional method using pre-specified uncertainties. Replacement of the maximum likelihood solution by full Bayesian estimation also allows estimation of all tuning parameters from the measurements. The estimation procedure is based on the variational Bayes approximation which is evaluated by an iterative algorithm. The resulting method is thus very similar to the conventional approach, but with the possibility to also estimate all tuning parameters from the observations. The proposed algorithm is tested and compared with the standard methods on data from the European Tracer Experiment (ETEX) where advantages of the new method are demonstrated. A MATLAB implementation of the proposed algorithm is available for download.

Baltimore Harbor and Channels Deepening Study; Chesapeake Bay Hydraulic Model Investigation.

DTIC Science & Technology

1982-02-01

neap-spring salinity vari- ability. Stations within the Patapsco River (Plates 78-90), and the Magothy River station (MA-I-1, Plate 74), immediately...to-base salinity variations are found at upper bay stations above the constriction at range CB-4. Only Magothy River sta MA-l, and sta CB-7-1 have...Across the bay at the western shore Magothy River sta MA-I-I (Plate 74) no appreciable plan-to-base salinity differences are found, although during

Linking dynamics of transport timescale and variations of hypoxia in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Hong, Bo; Shen, Jian

2013-11-01

Dissolved oxygen (DO) replenishment in the bottom waters of an estuary depends on physical processes that are significantly influenced by external forcings. The vertical exchange time (VET) is introduced in this study to quantify the physical processes that regulate the DO replenishment in the Chesapeake Bay. A 3-D numerical model was applied to simulate the circulation, VET, and DO. Results indicate that VET is a suitable parameter for evaluating the bottom DO condition over both seasonal and interannual timescales. The VET is negatively correlated with the bottom DO. Hypoxia (DO <2 mg L-1) will develop in the Bay when VET is greater than 23 days in summer if mean total DO consumption rate is about 0.3 g O2 m-3 d-1. This critical VET value may vary around 23 days when the total DO consumption rate changes. The VET volume (volume of water mass with VET >23 days) can account for 77% of variations of hypoxic volume in the main Bay. The VET cannot explain all the DO variations as it can only account for the contribution of physical processes that regulate DO replenishment. It is found that the short-term vertical exchange process is highly controlled by the wind forcing. The VET volume decreases when the high-speed wind events are frequent. The summertime VET volume is less sensitive to short-term variations (pulses) of river discharge. It is sensitive to the total amount of river discharge and the high VET volume can be expected in the wet year.

Efficient Implementation of MrBayes on Multi-GPU

PubMed Central

Zhou, Jianfu; Liu, Xiaoguang; Wang, Gang

2013-01-01

MrBayes, using Metropolis-coupled Markov chain Monte Carlo (MCMCMC or (MC)3), is a popular program for Bayesian inference. As a leading method of using DNA data to infer phylogeny, the (MC)3 Bayesian algorithm and its improved and parallel versions are now not fast enough for biologists to analyze massive real-world DNA data. Recently, graphics processor unit (GPU) has shown its power as a coprocessor (or rather, an accelerator) in many fields. This article describes an efficient implementation a(MC)3 (aMCMCMC) for MrBayes (MC)3 on compute unified device architecture. By dynamically adjusting the task granularity to adapt to input data size and hardware configuration, it makes full use of GPU cores with different data sets. An adaptive method is also developed to split and combine DNA sequences to make full use of a large number of GPU cards. Furthermore, a new “node-by-node” task scheduling strategy is developed to improve concurrency, and several optimizing methods are used to reduce extra overhead. Experimental results show that a(MC)3 achieves up to 63× speedup over serial MrBayes on a single machine with one GPU card, and up to 170× speedup with four GPU cards, and up to 478× speedup with a 32-node GPU cluster. a(MC)3 is dramatically faster than all the previous (MC)3 algorithms and scales well to large GPU clusters. PMID:23493260

Efficient implementation of MrBayes on multi-GPU.

PubMed

Bao, Jie; Xia, Hongju; Zhou, Jianfu; Liu, Xiaoguang; Wang, Gang

2013-06-01

MrBayes, using Metropolis-coupled Markov chain Monte Carlo (MCMCMC or (MC)(3)), is a popular program for Bayesian inference. As a leading method of using DNA data to infer phylogeny, the (MC)(3) Bayesian algorithm and its improved and parallel versions are now not fast enough for biologists to analyze massive real-world DNA data. Recently, graphics processor unit (GPU) has shown its power as a coprocessor (or rather, an accelerator) in many fields. This article describes an efficient implementation a(MC)(3) (aMCMCMC) for MrBayes (MC)(3) on compute unified device architecture. By dynamically adjusting the task granularity to adapt to input data size and hardware configuration, it makes full use of GPU cores with different data sets. An adaptive method is also developed to split and combine DNA sequences to make full use of a large number of GPU cards. Furthermore, a new "node-by-node" task scheduling strategy is developed to improve concurrency, and several optimizing methods are used to reduce extra overhead. Experimental results show that a(MC)(3) achieves up to 63× speedup over serial MrBayes on a single machine with one GPU card, and up to 170× speedup with four GPU cards, and up to 478× speedup with a 32-node GPU cluster. a(MC)(3) is dramatically faster than all the previous (MC)(3) algorithms and scales well to large GPU clusters.

Results and evaluation of a pilot primary monitoring network, San Francisco Bay, California, 1978

USGS Publications Warehouse

Bradford, W.L.; Iwatsubo, R.T.

1980-01-01

A primary monitoring network of 12 stations, with measurements at 1-meter depth intervals every 2 weeks during periods of high inflow from the Sacramento-San Joaquin River delta, and every 4-6 weeks during seasonal low delta inflows, appears adequate to observe major changes in ambient water quality in San Francisco Bay. A 1-year study tested the network operation and determined that analysis of the data could demonstrate the major changes in salinity, temperature, and light-attenuation distributions known to occur, based on earlier research, in response to variations of delta inflow and to other physical processes. Observations of eddies at two stations, of the influence of water from a river flooding in the extreme south bay, and of difference in salinity and temperature laterally across the entrance to the south bay are all new but are consistent with existing models. The pH, dissolved oxygen, and light-attenuation measurements, while adequate to observe small-scale vertical variations, are not sufficiently sensitive to detect the effects of phytoplankton blooms. (USGS)

Overview of existing algorithms for emotion classification. Uncertainties in evaluations of accuracies.

NASA Astrophysics Data System (ADS)

Avetisyan, H.; Bruna, O.; Holub, J.

2016-11-01

A numerous techniques and algorithms are dedicated to extract emotions from input data. In our investigation it was stated that emotion-detection approaches can be classified into 3 following types: Keyword based / lexical-based, learning based, and hybrid. The most commonly used techniques, such as keyword-spotting method, Support Vector Machines, Naïve Bayes Classifier, Hidden Markov Model and hybrid algorithms, have impressive results in this sphere and can reach more than 90% determining accuracy.

Seasonal variation of the underground cosmic muon flux observed at Daya Bay

NASA Astrophysics Data System (ADS)

An, F. P.; Balantekin, A. B.; Band, H. R.; Bishai, M.; Blyth, S.; Cao, D.; Cao, G. F.; Cao, J.; Chan, Y. L.; Chang, J. F.; Chang, Y.; Chen, H. S.; Chen, Q. Y.; Chen, S. M.; Chen, Y. X.; Chen, Y.; Cheng, J.; Cheng, Z. K.; Cherwinka, J. J.; Chu, M. C.; Chukanov, A.; Cummings, J. P.; Ding, Y. Y.; Diwan, M. V.; Dolgareva, M.; Dove, J.; Dwyer, D. A.; Edwards, W. R.; Gill, R.; Gonchar, M.; Gong, G. H.; Gong, H.; Grassi, M.; Gu, W. Q.; Guo, L.; Guo, X. H.; Guo, Y. H.; Guo, Z.; Hackenburg, R. W.; Hans, S.; He, M.; Heeger, K. M.; Heng, Y. K.; Higuera, A.; Hsiung, Y. B.; Hu, B. Z.; Hu, T.; Huang, E. C.; Huang, H. X.; Huang, X. T.; Huber, P.; Huo, W.; Hussain, G.; Jaffe, D. E.; Jen, K. L.; Jetter, S.; Ji, X. P.; Ji, X. L.; Jiao, J. B.; Johnson, R. A.; Jones, D.; Kang, L.; Kettell, S. H.; Khan, A.; Kohn, S.; Kramer, M.; Kwan, K. K.; Kwok, M. W.; Kwok, T.; Langford, T. J.; Lau, K.; Lebanowski, L.; Lee, J.; Lee, J. H. C.; Lei, R. T.; Leitner, R.; Li, C.; Li, D. J.; Li, F.; Li, G. S.; Li, Q. J.; Li, S.; Li, S. C.; Li, W. D.; Li, X. N.; Li, X. Q.; Li, Y. F.; Li, Z. B.; Liang, H.; Lin, C. J.; Lin, G. L.; Lin, S.; Lin, S. K.; Lin, Y.-C.; Ling, J. J.; Link, J. M.; Littenberg, L.; Littlejohn, B. R.; Liu, J. L.; Liu, J. C.; Loh, C. W.; Lu, C.; Lu, H. Q.; Lu, J. S.; Luk, K. B.; Ma, X. Y.; Ma, X. B.; Ma, Y. Q.; Malyshkin, Y.; Martinez Caicedo, D. A.; McDonald, K. T.; McKeown, R. D.; Mitchell, I.; Nakajima, Y.; Napolitano, J.; Naumov, D.; Naumova, E.; Ngai, H. Y.; Ochoa-Ricoux, J. P.; Olshevskiy, A.; Pan, H.-R.; Park, J.; Patton, S.; Pec, V.; Peng, J. C.; Pinsky, L.; Pun, C. S. J.; Qi, F. Z.; Qi, M.; Qian, X.; Qiu, R. M.; Raper, N.; Ren, J.; Rosero, R.; Roskovec, B.; Ruan, X. C.; Sebastiani, C.; Steiner, H.; Sun, J. L.; Tang, W.; Taychenachev, D.; Treskov, K.; Tsang, K. V.; Tull, C. E.; Viaux, N.; Viren, B.; Vorobel, V.; Wang, C. H.; Wang, M.; Wang, N. Y.; Wang, R. G.; Wang, W.; Wang, X.; Wang, Y. F.; Wang, Z.; Wang, Z.; Wang, Z. M.; Wei, H. Y.; Wen, L. J.; Whisnant, K.; White, C. G.; Whitehead, L.; Wise, T.; Wong, H. L. H.; Wong, S. C. F.; Worcester, E.; Wu, C.-H.; Wu, Q.; Wu, W. J.; Xia, D. M.; Xia, J. K.; Xing, Z. Z.; Xu, J. L.; Xu, Y.; Xue, T.; Yang, C. G.; Yang, H.; Yang, L.; Yang, M. S.; Yang, M. T.; Yang, Y. Z.; Ye, M.; Ye, Z.; Yeh, M.; Young, B. L.; Yu, Z. Y.; Zeng, S.; Zhan, L.; Zhang, C.; Zhang, C. C.; Zhang, H. H.; Zhang, J. W.; Zhang, Q. M.; Zhang, X. T.; Zhang, Y. M.; Zhang, Y. X.; Zhang, Y. M.; Zhang, Z. J.; Zhang, Z. Y.; Zhang, Z. P.; Zhao, J.; Zhou, L.; Zhuang, H. L.; Zou, J. H.

2018-01-01

The Daya Bay Experiment consists of eight identically designed detectors located in three underground experimental halls named as EH1, EH2, EH3, with 250, 265 and 860 meters of water equivalent vertical overburden, respectively. Cosmic muon events have been recorded over a two-year period. The underground muon rate is observed to be positively correlated with the effective atmospheric temperature and to follow a seasonal modulation pattern. The correlation coefficient α, describing how a variation in the muon rate relates to a variation in the effective atmospheric temperature, is found to be αEH1 = 0.362±0.031, αEH2 = 0.433±0.038 and αEH3 = 0.641±0.057 for each experimental hall.

Variations of summer phytoplankton community related to environmental factors in a macro-tidal estuarine embayment, Hangzhou Bay, China

NASA Astrophysics Data System (ADS)

Zhang, Yuexia; Yu, Jun; Jiang, Zhibing; Wang, Qin; Wang, Hui

2015-12-01

To explore the distribution and composition of phytoplankton community and their responses to environmental changes, summer net-collected phytoplankton and physicochemical parameters in the Hangzhou Bay during 2004-2010 were investigated. A total of four phyla and 84 species were identified, including 67 diatom and 12 dinoflagellate species. The dominant species constantly consisted of the diatoms, although the dominance of dinoflagellate and cyanobacteria increased recently. Due to great spatio-temporal variations in environmental factors (salinity, suspended solids, and nutrient concentration), significant heterogeneities in community compositions among different years and subregions (inner and middle sections, and bay mouth) were found based on the analyses of multidimensional scaling and similarity. Canonical correspondence analysis showed that salinity and Si/N were the main variables associated with algal assemblage. Compared with the historical data since the 1980s, eutrophication (N, P, and N/P increased with decreasing Si/N) was exacerbated drastically. Moreover, climatic forcing and human activities resulted in a series of physical alterations, including sediment retention, temperature increase, and salinity decrease as well as reduction in water exchanges. All these changes induced obvious increases in cell density and Chl- a while decreases in species diversity and diatom-dinoflagellate ratio as well as the shifting of dominant species. Therefore, the long-term phytoplankton variations were closely related to anthropogenic and climatic perturbations in the Hangzhou Bay.

Misinterpretation of lateral acoustic variations on high-resolution seismic reflection profiles as fault offsets of Holocene bay mud beneath the southern part of San Francisco Bay, California

USGS Publications Warehouse

Marlow, M. S.; Hart, P.E.; Carlson, P.R.; Childs, J. R.; Mann, D. M.; Anima, R.J.; Kayen, R.E.

1996-01-01

We collected high-resolution seismic reflection profiles in the southern part of San Francisco Bay in 1992 and 1993 to investigate possible Holocene faulting along postulated transbay bedrock fault zones. The initial analog records show apparent offsets of reflection packages along sharp vertical boundaries. These records were originally interpreted as showing a complex series of faults along closely spaced, sharp vertical boundaries in the upper 10 m (0.013 s two-way travel time) of Holocene bay mud. A subsequent survey in 1994 was run with a different seismic reflection system, which utilized a higher power source. This second system generated records with deeper penetration (max. 20 m, 0.026 s two-way travel time) and demonstrated that the reflections originally interpreted as fault offsets by faulting were actually laterally continuous reflection horizons. The pitfall in the original interpretations was caused by lateral variations in the amplitude brightness of reflection events, coupled with a long (greater than 15 ms) source signature of the low-power system. These effects combined to show apparent offsets of reflection packages along sharp vertical boundaries. These boundaries, as shown by the second system, in fact occur where the reflection amplitude diminishes abruptly on laterally continuous reflection events. This striking lateral variation in reflection amplitude is attributable to the localized presence of biogenic(?) gas.

Mobile Bay, Alabama area seen in Skylab 4 Earth Resources Experiment Package

NASA Image and Video Library

1974-02-01

SL4-92-300 (February 1974) --- A near vertical view of the Mobile Bay, Alabama area is seen in this Skylab 4 Earth Resources Experiments Package S190-B (five-inch earth terrain camera) photograph taken from the Skylab space station in Earth orbit. North of Mobile the Tombigbee and Alabama Rivers join to form the Mobile River. Detailed configuration of the individual stream channels and boundaries can be defined as the Mobile River flows into Mobile Bay, and thence into the Gulf of Mexico. The Mobile River Valley with its numerous stream channels is a distinct light shade in contrast to the dark green shade of the adjacent areas. The red coloration of Mobile Bay reflects the sediment load carried into the Bay by the rivers. Variations in red color indicate sediment load and the current paths within Mobile Bay. The waterly movement of the along shore currents at the mouth of Mobile Bay is shown by the contrasting light blue of the sediment-laden current and the blue of the Gulf predominately. Agricultural areas east and west of Mobile Bay are characterized by a rectangular pattern in green to white shades. Color variations may reflect the type and growth cycle of crops. Agricultural areas (light gray-greens) are also clearly visible in other parts of the photograph. Interstate 10 extends from near Pascagoula, Mississippi eastward through Mobile to the outskirts of Pensacola, Florida. Analysis of the EREP photographic data will be undertaken by the U.S. Corps of Engineers to determine bay dynamic processes. Federal agencies participating with NASA on the EREP project are the Departments of Agriculture, Commerce, Interior, the Environmental Protection Agency and the Corps of Engineers. All EREP photography is available to the public through the Department of Interior's Earth Resources Observations Systems Data Center, Sioux Falls, South Dakota. 57198 Photo credit: NASA

Bayesian reconstruction of gravitational wave bursts using chirplets

NASA Astrophysics Data System (ADS)

Millhouse, Margaret; Cornish, Neil; Littenberg, Tyson

2017-01-01

The BayesWave algorithm has been shown to accurately reconstruct unmodeled short duration gravitational wave bursts and to distinguish between astrophysical signals and transient noise events. BayesWave does this by using a variable number of sine-Gaussian (Morlet) wavelets to reconstruct data in multiple interferometers. While the Morlet wavelets can be summed together to produce any possible waveform, there could be other wavelet functions that improve the performance. Because we expect most astrophysical gravitational wave signals to evolve in frequency, modified Morlet wavelets with linear frequency evolution - called chirplets - may better reconstruct signals with fewer wavelets. We compare the performance of BayesWave using Morlet wavelets and chirplets on a variety of simulated signals.

Applications of MODIS Fluorescent Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity

NASA Technical Reports Server (NTRS)

Fischer, Andrew; Moreno-Mardinan, Max; Ryan, John P.

2012-01-01

Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations, processing techniques and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean-color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS) sensor calibration updates, improved aerosol retrievals and new aerosol models has led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean color in coastal waters. This has opened the way for studying ocean phenomena and processes at finer spatial scales, such as the interactions at the land-sea interface, trends in coastal water quality and algal blooms. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and have increase local concentrations of phytoplankton, which cause harmful algal blooms. In two case studies we present MODIS observations of fluorescence line height (FLH) to 1) assess trends in water quality for Tampa Bay, Florida and 2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and satellite imagery from Tampa Bay we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout a large optically complex estuarine system. A systematic analysis of sampling sites throughout the bay is undertaken to understand how the relationship between FLH and in situ chlorophyll-a responds to varying conditions and to develop a near decadal trend in water quality changes. In situ monitoring locations that correlated well with satellite imagery were in depths greater than seven meters and were located over five kilometers from shore. Water quality parameter of total nitrogen, phosphorous, turbidity and biological oxygen demand had high correlations with these sites, as well. Satellite FLH estimates show improving water quality from 2003-2007 with a slight decline up through 2011. Dinoflagellate blooms in Monterey Bay, California (USA) have recently increased in frequency and intensity. Nine years of MODIS FLH observations are used to describe the annual and seasonal variability of bloom activity within the Bay. Three classes of MODIS algorithms were correlated against in situ chlorophyll measurements. The FLH algorithm provided the most robust estimate of bloom activity. Elevated concentrations of phytoplankton were evident during the months of August-November, a period during which increased occurrences of dinoflagellate blooms have been observed in situ. Seasonal patterns of FLH show the on- and offshore movement of areas of high phytoplankton biomass between oceanographic seasons. Higher concentrations of phytoplankton are also evident in the vicinity of the land-based nutrient sources and outflows, and the cyclonic bay-wide circulation can transport these nutrients to the northern Bay bloom incubation region. Both of these case studies illustrate the utility MODIS FLH observations in supporting management decisions in coastal and estuarine waters.

Spatiotemporal variations in the abundance and composition of bulk and chromophoric dissolved organic matter in seasonally hypoxia-influenced Green Bay, Lake Michigan, USA.

PubMed

DeVilbiss, Stephen E; Zhou, Zhengzhen; Klump, J Val; Guo, Laodong

2016-09-15

Green Bay, Lake Michigan, USA, is the largest freshwater estuary in the Laurentian Great Lakes and receives disproportional terrestrial inputs as a result of a high watershed to bay surface area ratio. While seasonal hypoxia and the formation of "dead zones" in Green Bay have received increasing attention, there are no systematic studies on the dynamics of dissolved organic matter (DOM) and its linkage to the development of hypoxia. During summer 2014, bulk dissolved organic carbon (DOC) analysis, UV-vis spectroscopy, and fluorescence excitation-emission matrices (EEMs) coupled with PARAFAC analysis were used to quantify the abundance, composition and source of DOM and their spatiotemporal variations in Green Bay, Lake Michigan. Concentrations of DOC ranged from 202 to 571μM-C (average=361±73μM-C) in June and from 279 to 610μM-C (average=349±64μM-C) in August. In both months, absorption coefficient at 254nm (a254) was strongly correlated to bulk DOC and was most abundant in the Fox River, attesting a dominant terrestrial input. Non-chromophoric DOC comprised, on average, ~32% of bulk DOC in June with higher terrestrial DOM and ~47% in August with higher aquagenic DOM, indicating that autochthonous and more degraded DOM is of lower optical activity. PARAFAC modeling on EEM data resulted in four major fluorescent DOM components, including two terrestrial humic-like, one aquagenic humic-like, and one protein-like component. Variations in the abundance of DOM components further supported changes in DOM sources. Mixing behavior of DOM components also indicated that while bulk DOM behaved quasi-conservatively, significant compositional changes occurred during transport from the Fox River to the open bay. Copyright © 2016 Elsevier B.V. All rights reserved.

Annealed Importance Sampling for Neural Mass Models

PubMed Central

Penny, Will; Sengupta, Biswa

2016-01-01

Neural Mass Models provide a compact description of the dynamical activity of cell populations in neocortical regions. Moreover, models of regional activity can be connected together into networks, and inferences made about the strength of connections, using M/EEG data and Bayesian inference. To date, however, Bayesian methods have been largely restricted to the Variational Laplace (VL) algorithm which assumes that the posterior distribution is Gaussian and finds model parameters that are only locally optimal. This paper explores the use of Annealed Importance Sampling (AIS) to address these restrictions. We implement AIS using proposals derived from Langevin Monte Carlo (LMC) which uses local gradient and curvature information for efficient exploration of parameter space. In terms of the estimation of Bayes factors, VL and AIS agree about which model is best but report different degrees of belief. Additionally, AIS finds better model parameters and we find evidence of non-Gaussianity in their posterior distribution. PMID:26942606

San Francisco Bay, California as seen from STS-59

NASA Image and Video Library

1994-04-14

STS059-213-009 (9-20 April 1994) --- San Francisco Bay. Orient with the sea up. The delta of the combined Sacramento and San Joaquin Rivers occupies the foreground, San Francisco Bay the middle distance, and the Pacific Ocean the rest. Variations in water color caused both by sediment load and by wind streaking strike the eye. Man-made features dominate this scene. The Lafayette/Concord complex is left of the bay head, Vallejo is to the right, the Berkeley/Oakland complex rims the shoreline of the main bay, and San Francisco fills the peninsula beyond. Salt-evaporation ponds contain differently-colored algae depending on salinity. The low altitude (less than 120 nautical miles) and unusually-clear air combine to provide unusually-strong green colors in this Spring scene. Hasselblad camera.

San Francisco Bay, California as seen from STS-59

NASA Technical Reports Server (NTRS)

1994-01-01

San Francisco Bay as seen from STS-59. View is oriented with the sea up. The delta of the combined Sacramento and San Joaquin Rivers occupies the foreground with San Francisco Bay in the middle distance, then the Pacific Ocean. Variations in water color caused both by sediment load and by wind streaking strike the eye. Man-made features dominate this scene. The Lafayette/Concord complex is left of the bay head, Vallejo is to the right, the Berkeley/Oakland complex rims the shoreline of the main bay, and San Francisco fills the peninsula beyond. Salt-evaporation ponds contain differently-colored algae depending on salinity. The low altitude (less than 120 nautical miles) and unusually-clear air combine to provide unusually-strong green colors in this Spring scene.

Does centennial morphodynamic evolution lead to higher channel efficiency in San Pablo Bay, California?

USGS Publications Warehouse

van der Wegen, M.; Jaffe, B.E.; Barnard, P.L.; Jaffee, B.E.; Schoellhamer, D.H.

2013-01-01

Measured bathymetries on 30 year interval over the past 150 years show that San Pablo Bay experienced periods of considerable deposition followed by periods of net erosion. However, the main channel in San Pablo Bay has continuously narrowed. The underlying mechanisms and consequences of this tidal channel evolution are not well understood. The central question of this study is whether tidal channels evolve towards a geometry that leads to more efficient hydraulic conveyance and sediment throughput. We applied a hydrodynamic process-based, numerical model (Delft3D), which was run on 5 San Pablo Bay bathymetries measured between 1856 and 1983. Model results shows increasing energy dissipation levels for lower water flows leading to an approximately 15% lower efficiency in 1983 compared to 1856. During the same period the relative seaward sediment throughput through the San Pablo Bay main channel increased by 10%. A probable explanation is that San Pablo Bay is still affected by the excessive historic sediment supply. Sea level rise and Delta surface water area variations over 150 years have limited effect on the model results. With expected lower sediment concentrations in the watershed and less impact of wind waves due to erosion of the shallow flats, it is possible that energy dissipations levels will decrease again in future decades. Our study suggests that the morphodynamic adaptation time scale to excessive variations in sediment supply to estuaries may be on the order of centuries.

Assessment of various supervised learning algorithms using different performance metrics

NASA Astrophysics Data System (ADS)

Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.

2017-11-01

Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.

Optical Algorithms at Satellite Wavelengths for Total Suspended Matter in Tropical Coastal Waters

PubMed Central

Ouillon, Sylvain; Douillet, Pascal; Petrenko, Anne; Neveux, Jacques; Dupouy, Cécile; Froidefond, Jean-Marie; Andréfouët, Serge; Muñoz-Caravaca, Alain

2008-01-01

Is it possible to derive accurately Total Suspended Matter concentration or its proxy, turbidity, from remote sensing data in tropical coastal lagoon waters? To investigate this question, hyperspectral remote sensing reflectance, turbidity and chlorophyll pigment concentration were measured in three coral reef lagoons. The three sites enabled us to get data over very diverse environments: oligotrophic and sediment-poor waters in the southwest lagoon of New Caledonia, eutrophic waters in the Cienfuegos Bay (Cuba), and sediment-rich waters in the Laucala Bay (Fiji). In this paper, optical algorithms for turbidity are presented per site based on 113 stations in New Caledonia, 24 stations in Cuba and 56 stations in Fiji. Empirical algorithms are tested at satellite wavebands useful to coastal applications. Global algorithms are also derived for the merged data set (193 stations). The performances of global and local regression algorithms are compared. The best one-band algorithms on all the measurements are obtained at 681 nm using either a polynomial or a power model. The best two-band algorithms are obtained with R412/R620, R443/R670 and R510/R681. Two three-band algorithms based on Rrs620.Rrs681/Rrs412 and Rrs620.Rrs681/Rrs510 also give fair regression statistics. Finally, we propose a global algorithm based on one or three bands: turbidity is first calculated from Rrs681 and then, if < 1 FTU, it is recalculated using an algorithm based on Rrs620.Rrs681/Rrs412. On our data set, this algorithm is suitable for the 0.2-25 FTU turbidity range and for the three sites sampled (mean bias: 3.6 %, rms: 35%, mean quadratic error: 1.4 FTU). This shows that defining global empirical turbidity algorithms in tropical coastal waters is at reach. PMID:27879929

Factors affecting suspended-solids concentrations in South San Francisco Bay, California

USGS Publications Warehouse

Schoellhamer, D.H.

1996-01-01

Measurements of suspended-solids concentration (SSC) were made at two depths at three sites in South San Francisco Bay (South Bay) to determine the factors that affect SSC. Twenty-eight segments of reliable and continuous SSC time series data longer than 14 days were collected from late 1991 or 1992 through September 1993. Spectral analysis and singular spectrum analysis were used to relate these data segments to time series of several potential forcing factors, including diurnal and semidiurnal tides, the spring-neap tidal cycle, wind shear, freshwater runoff, and longitudinal density differences. SSC is greatest during summer when a landward wind shear is applied to South Bay by the afternoon sea breeze. About one half the variance of SSC is caused by the spring-neap cycle, and SSC lags the spring-neap cycle by about 2 days. Relatively short duration of slack water limits the duration of deposition of suspended solids and consolidation of newly deposited bed sediment during the tidal cycle, so suspended solids accumulate in the water column as a spring tide is approached and slowly deposit as a neap tide is approached. Perturbations in SSC caused by wind and local runoff from winter storms during the study period were usually much smaller than SSC variations caused by the spring-neap cycle. Variations of SSC at the study sites at tidal timescales are tidally forced, and nonlinear physical processes are significant. Advective transport dominates during spring tides when water with higher SSC due to wind wave resuspension is advected to the main channel from shallow water, but during neap tides, advective transport is less significant. The findings of this and other studies indicate that the tidally averaged transport of suspended solids responds to seasonal variations of wind shear in South Bay.

Investigations into the Properties, Conditions, and Effects of the Ionosphere

DTIC Science & Technology

1990-01-15

ionogram database to be used in testing trace-identification algorithms; d. Development of automatic trace-identification algorithms and autoscaling ...Scaler ( ARTIST ) and improvement of the ARTIST software; g. Maintenance and upgrade of the digital ionosondes at Argentia, Newfoundland, and Goose Bay...provided by the contractor; j. Upgrade of the ARTIST computer at the Danish Meteorological Institute/GL Qaanaaq site to provide digisonde tape-playback

Phytoplankton composition and microcystin concentrations in open and closed bays of Lake Victoria, Tanzania

PubMed Central

Mbonde, Athanasio S.; Sitoki, Lewis; Kurmayer, Rainer

2017-01-01

This study was carried out in order to investigate the spatial variation of algal toxin (microcystin) concentrations along the shoreline of Lake Victoria. A total of 16 nearshore stations differing in connectivity to the main lake basin were categorized as either closed bays (ratio of bay area to bay opening < 1) or open bays (ratio ≥ 1) and sampled during November and December 2009. Water samples were analyzed for total phosphorus (TP), chlorophyll a, phytoplankton community composition and concentrations of microcystin (MC). Open and closed bays were significantly different for phytoplankton abundance and composition: Average phytoplankton biovolume was higher for closed bays (45 mm3 L-1 ± 11 SE) than open bays (5 ± 2 mm3 L-1). Cyanobacterial biovolume (mainly Microcystis spp., Anabaena spp. and Planktolyngbya spp.) also was significantly higher in closed bays (82 ± 9% of total biovolume) than in open bays (44 ± 5%). In contrast, diatom biovolume was lower in closed bays (7 ± 1%) than in open bays (36 ± 6%). MCs were found only among sites from closed bays and concentrations ranged from 0.4 to 13 μg L-1 MC-LR equiv. and coincided with high abundance of Microcystis spp. It is concluded that the level of water exchange from individual bays to the main basin is an important factor influencing eutrophication and microcystin production in nearshore habitats of Lake Victoria. PMID:28077928

Evaluating bio-optical models to determine chlorophyll a from hyper spectral data in the turbid coastal waters of South Carolina

NASA Astrophysics Data System (ADS)

Hames, J. B.; Ali, K.

2013-12-01

Millions of people visit the beaches of South Carolina every year and the increasing utilization of the coastal waters is leading to the deterioration of water quality and the marine ecosystem. Ecological stress on these environments is reflected by the increase in the frequency and severity of Harmful Algal Blooms (HABs). This was evident during recent summer seasons particularly in the shallow nearshore waters of Long Bay, South Carolina, an open coast embayment on the South Atlantic Bight. These aspects threaten human and marine life. The early detection of HABs in the coastal waters requires more efficient and accurate monitoring tools. Remote sensing provides synoptic view of the entire Long Bay waters at high temporal coverage and allows resource managers to effectively map and monitor algal bloom development, near real time. Various remote sensing (RS) algorithms have been developed but were mostly calibrated to low resolution global data and or other specific sites. In the summer of 2013, a suite of measurements and water samples were collected from 15 locations along the nearshore waters of Long Bay using the Grice Laboratory R/V. In this study, we evaluate the efficiency of 10 bio-optical blue-green and NIR-red based RS models applied to GER 1500 hyper spectral reflectance data to predict chlorophyll a, a proxy for phytoplankton density, in the Long Bay waters of SC. Efficiency of the algorithms performance in the study site were tested through a least squares regression and residual analysis. Results show that among the selected suite of algorithms the blue green models by Darecki and Stramski (2004) produced R2 of 0.68 with RMSE=0.39μg/l, Oc4v4 model by O'Reilly et al. (2000) gave R2 of 0.62 with RMSE=0.73ug/l, and the Oc2v4 also by O'Reilly et al (2000) gave R2 of 0.69 with RMSE=0.65. Among the NIR-red models, Moses et al (2009) two-band algorithm produced R2 of 0.75 and RMSE=1.79, and the three-band version generated R2 of 0.81 and RMSE=2.25ug/l. This suggests that the global RS models have the potential to monitor water quality parameters in the region but may require calibration for higher accuracy in Long Bay, SC.

The use of decision trees and naïve Bayes algorithms and trace element patterns for controlling the authenticity of free-range-pastured hens' eggs.

PubMed

Barbosa, Rommel Melgaço; Nacano, Letícia Ramos; Freitas, Rodolfo; Batista, Bruno Lemos; Barbosa, Fernando

2014-09-01

This article aims to evaluate 2 machine learning algorithms, decision trees and naïve Bayes (NB), for egg classification (free-range eggs compared with battery eggs). The database used for the study consisted of 15 chemical elements (As, Ba, Cd, Co, Cs, Cu, Fe, Mg, Mn, Mo, Pb, Se, Sr, V, and Zn) determined in 52 eggs samples (20 free-range and 32 battery eggs) by inductively coupled plasma mass spectrometry. Our results demonstrated that decision trees and NB associated with the mineral contents of eggs provide a high level of accuracy (above 80% and 90%, respectively) for classification between free-range and battery eggs and can be used as an alternative method for adulteration evaluation. © 2014 Institute of Food Technologists®

Retrieval of total suspended particulate matter in highly turbid Hangzhou Bay waters based on geostationary ocean color imager

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Jiahang; He, Xianqiang; Chen, Tieqiao; Zhu, Feng; Wang, Yihao; Hao, Zengzhou; Chen, Peng

2017-10-01

Hangzhou Bay waters are often characterized by extremely high total suspended particulate matter (TSM) concentration due to terrestrial inputs, bottom sediment resuspension and human activities. The spatial-temporal variability of TSM directly contributes to the transport of carbon, nutrients, pollutants, and other materials. Therefore, it is essential to maintain and monitor sedimentary environment in coastal waters. Traditional field sampling methods limit observation capability for insufficient spatial-temporal resolution. Thus, it is difficult to synoptically monitor high diurnal dynamics of TSM. However, the in-orbit operation of the world's first geostationary satellite ocean color sensor, GOCI, thoroughly changes this situation with hourly observations of covered area. Taking advantage of GOCI high spatial-temporal resolution, we generated TSM maps from GOCI Level-1B data after atmospheric correction based on six TSM empirical algorithms. Validation of GOCI-retrieved normalized water-leaving radiances and TSM concentration was presented in comparison with matched-up in-situ measurements. The mean absolute percentage differences of those six TSM regional algorithms were 24.52%, 163.93%, 195.50%, 70.50%, 121.02%, 82.72%, respectively. In addition, the discrepancy reasons were presented, taking more factors such as diversified satellite data, various study area, and different research season into consideration. It is effective and indispensable to monitor and catch the diurnal dynamics of TSM in Hangzhou Bay coastal waters, with hourly GOCI observations data and appropriate inversion algorithm.

Indicators of nitrate export from forested watersheds of the Chesapeake Bay region

Treesearch

Karl W. J. Williard

1997-01-01

Soil net nitrogen mineralization and nitrification rates were studied on nine relatively undisturbed, forested watersheds in an effort to explain the large variations in nitrate export in streamflow within the Chesapeake Bay region. The primary hypothesis tested was that nitrate export from the watersheds was positively associated with rates of net soil nitrogen...

Spatial variation in reproductive effort of a southern Australian seagrass.

PubMed

Smith, Timothy M; York, Paul H; Macreadie, Peter I; Keough, Michael J; Ross, D Jeff; Sherman, Craig D H

2016-09-01

In marine environments characterised by habitat-forming plants, the relative allocation of resources into vegetative growth and flowering is an important indicator of plant condition and hence ecosystem health. In addition, the production and abundance of seeds can give clues to local resilience. Flowering density, seed bank, biomass and epiphyte levels were recorded for the temperate seagrass Zostera nigricaulis in Port Phillip Bay, south east Australia at 14 sites chosen to represent several regions with different physicochemical conditions. Strong regional differences were found within the large bay. Spathe and seed density were very low in the north of the bay (3 sites), low in the centre of the bay (2 sites) intermediate in the Outer Geelong Arm (2 sites), high in Swan Bay (2 sites) and very high in the Inner Geelong Arm (3 sites). In the south (2 sites) seed density was low and spathe density was high. These regional patterns were largely consistent for the 5 sites sampled over the three year period. Timing of flowering was consistent across sites, occurring from August until December with peak production in October, except during the third year of monitoring when overall densities were lower and peaked in November. Seagrass biomass, epiphyte load, canopy height and stem density showed few consistent spatial and temporal patterns. Variation in spathe and seed density and morphology across Port Phillip Bay reflects varying environmental conditions and suggests that northern sites may be restricted in their ability to recover from disturbance through sexual reproduction. In contrast, sites in the west and south of the bay have greater potential to recover from disturbances due to a larger seed bank and these sites could act as source populations for sites where seed production is low. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural network modelling of planform geometry of headland-bay beaches

NASA Astrophysics Data System (ADS)

Iglesias, G.; López, I.; Castro, A.; Carballo, R.

2009-02-01

The shoreline of beaches in the lee of coastal salients or man-made structures, usually known as headland-bay beaches, has a distinctive curvature; wave fronts curve as a result of wave diffraction at the headland and in turn cause the shoreline to bend. The ensuing curved planform is of great interest both as a peculiar landform and in the context of engineering projects in which it is necessary to predict how a coastal structure will affect the sandy shoreline in its lee. A number of empirical models have been put forward, each based on a specific equation. A novel approach, based on the application of artificial neural networks, is presented in this work. Unlike the conventional method, no particular equation of the planform is embedded in the model. Instead, it is the model itself that learns about the problem from a series of examples of headland-bay beaches (the training set) and thereafter applies this self-acquired knowledge to other cases (the test set) for validation. Twenty-three headland-bay beaches from around the world were selected, of which sixteen and seven make up the training and test sets, respectively. As there is no well-developed theory for deciding upon the most convenient neural network architecture to deal with a particular data set, an experimental study was conducted in which ten different architectures with one and two hidden neuron layers and five training algorithms - 50 different options combining network architecture and training algorithm - were compared. Each of these options was implemented, trained and tested in order to find the best-performing approach for modelling the planform of headland-bay beaches. Finally, the selected neural network model was compared with a state-of-the-art planform model and was shown to outperform it.

Speeding up Coarse Point Cloud Registration by Threshold-Independent Baysac Match Selection

NASA Astrophysics Data System (ADS)

Kang, Z.; Lindenbergh, R.; Pu, S.

2016-06-01

This paper presents an algorithm for the automatic registration of terrestrial point clouds by match selection using an efficiently conditional sampling method -- threshold-independent BaySAC (BAYes SAmpling Consensus) and employs the error metric of average point-to-surface residual to reduce the random measurement error and then approach the real registration error. BaySAC and other basic sampling algorithms usually need to artificially determine a threshold by which inlier points are identified, which leads to a threshold-dependent verification process. Therefore, we applied the LMedS method to construct the cost function that is used to determine the optimum model to reduce the influence of human factors and improve the robustness of the model estimate. Point-to-point and point-to-surface error metrics are most commonly used. However, point-to-point error in general consists of at least two components, random measurement error and systematic error as a result of a remaining error in the found rigid body transformation. Thus we employ the measure of the average point-to-surface residual to evaluate the registration accuracy. The proposed approaches, together with a traditional RANSAC approach, are tested on four data sets acquired by three different scanners in terms of their computational efficiency and quality of the final registration. The registration results show the st.dev of the average point-to-surface residuals is reduced from 1.4 cm (plain RANSAC) to 0.5 cm (threshold-independent BaySAC). The results also show that, compared to the performance of RANSAC, our BaySAC strategies lead to less iterations and cheaper computational cost when the hypothesis set is contaminated with more outliers.

Seasonal variations in the community structures of macrobenthic fauna and their health status in an estuarine bay, Gwangyang Bay in Korea

NASA Astrophysics Data System (ADS)

Seo, Jin-Young; An, Soon-Mo; Lim, Dhong-il; Choi, Jin-Woo

2017-09-01

Macrobenthic fauna in an estuarine Gwangyang Bay, southern Korean coast, were investigated to uncover recent variations in their community structures. In the study area, macrobenthic faunal communities were mainly composed of polychaete worms which were the most abundant faunal group with the highest values in species number and density, while mollusks accounted for the highest proportion in total biomass. There was no clear seasonal difference in species richness during the two year period of the investigation, but the mean density and biomass increased every spring and summer due to the mass recruitment of Theora fragilis. The Shannon's diversity index (H') was more than 2.0 during most sampling seasons and did not show any significant seasonal difference except for the data in August, 2011 when azoic conditions occurred. The community structures of macrobenthos in Gwangyang Bay did not show any remarkable change in the dominance of the two top dominant species, Scoletoma longifolia and Heteromastus filiformis, which abundantly occurred in all seasons, except for the abundance peaks associated with high occurrence of T. fragilis and Paraprionospio cordifolia, especially in spring and summer and in autumn, respectively. These fauna changes reflected the changes in the macrobenthic community health status in Gwangyang Bay, where stable conditions and a healthy status prevailed in winter, but a slightly disturbed status prevailed from spring to autumn.

Modeling investigation of the nutrient and phytoplankton variability in the Chesapeake Bay outflow plume

NASA Astrophysics Data System (ADS)

Jiang, Long; Xia, Meng

2018-03-01

The Chesapeake Bay outflow plume (CBOP) is the mixing zone between Chesapeake Bay and less eutrophic continental shelf waters. Variations in phytoplankton distribution in the CBOP are critical to the fish nursery habitat quality and ecosystem health; thus, an existing hydrodynamic-biogeochemical model for the bay and the adjacent coastal ocean was applied to understand the nutrient and phytoplankton variability in the plume and the dominant environmental drivers. The simulated nutrient and chlorophyll a distribution agreed well with field data and real-time satellite imagery. Based on the model calculation, the net dissolved inorganic nitrogen (DIN) and phosphorus (DIP) flux at the bay mouth was seaward and landward during 2003-2012, respectively. The CBOP was mostly nitrogen-limited because of the relatively low estuarine DIN export. The highest simulated phytoplankton biomass generally occurred in spring in the near field of the plume. Streamflow variations could regulate the estuarine residence time, and thus modulate nutrient export and phytoplankton biomass in the plume area; in comparison, changing nutrient loading with fixed streamflow had a less extensive impact, especially in the offshore and far-field regions. Correlation analyses and numerical experiments revealed that southerly winds on the shelf were effective in promoting the offshore plume expansion and phytoplankton accumulation. Climate change including precipitation and wind pattern shifts is likely to complicate the driving mechanisms of phytoplankton variability in the plume region.

Movements of brown bullheads in Presque Isle Bay, Lake Erie, Pennsylvania

USGS Publications Warehouse

Millard, M.J.; Smith, D.R.; Obert, E.; Grazio, J.; Bartron, M.L.; Wellington, C.; Grise, S.; Rafferty, S.; Wellington, R.; Julian, S.

2009-01-01

Presque Isle Bay, Lake Erie, was listed as an Area of Concern (AOC) by the International Joint Commission in part because of the high incidence of external tumor in brown bullheads. Verifying the source of the possible contaminant exposure is critical to addressing the AOC designation. We used telemetry tracking (n = 49 fish) to test the hypothesis that adult bullheads captured within the bay during spawning season do not exit the bay during the post-spawning summer and fall months. We analyzed genetic variation at 15 microsatellite loci for 112 adult fish from 5 locations, 4 inside the bay and 1 outside, in order to test for possible differences. Data from fixed-station receivers suggested fish did not leave Presque Isle Bay during the study period. Predicted locations outside Presque Isle Bay were only 0.1% of all predicted locations and were below the 0.2% error rate based on known manual relocations. However, there was evidence for movement within Presque Isle Bay. Most movement was between Misery Bay or Lagoons and the open bay area. Whereas telemetry results showed tendency for adult site fidelity, genetic results showed no differences among locations, indicating that there is a single panmictic population. Our telemetry data suggest that brown bullheads are likely a useful indicator species for environmental conditions in Presque Isle Bay, since adults likely are retained in the system.

An improved optimization algorithm and Bayes factor termination criterion for sequential projection pursuit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb-Robertson, Bobbie-Jo M.; Jarman, Kristin H.; Harvey, Scott D.

2005-05-28

A fundamental problem in analysis of highly multivariate spectral or chromatographic data is reduction of dimensionality. Principal components analysis (PCA), concerned with explaining the variance-covariance structure of the data, is a commonly used approach to dimension reduction. Recently an attractive alternative to PCA, sequential projection pursuit (SPP), has been introduced. Designed to elicit clustering tendencies in the data, SPP may be more appropriate when performing clustering or classification analysis. However, the existing genetic algorithm (GA) implementation of SPP has two shortcomings, computation time and inability to determine the number of factors necessary to explain the majority of the structure inmore » the data. We address both these shortcomings. First, we introduce a new SPP algorithm, a random scan sampling algorithm (RSSA), that significantly reduces computation time. We compare the computational burden of the RSS and GA implementation for SPP on a dataset containing Raman spectra of twelve organic compounds. Second, we propose a Bayes factor criterion, BFC, as an effective measure for selecting the number of factors needed to explain the majority of the structure in the data. We compare SPP to PCA on two datasets varying in type, size, and difficulty; in both cases SPP achieves a higher accuracy with a lower number of latent variables.« less

Shuttle payload bay thermal environments: Summary and conclusion report for STS Flights 1-5

NASA Technical Reports Server (NTRS)

Fu, J. H.; Graves, G. R.

1987-01-01

The thermal data for the payload bay of the first five shuttle flights is summarized and the engineering evaluation of that data is presented. After a general discussion on mission profiles and vehicle configurations, the thermal design and flight instrumentation systems of the payload bay are described. The thermal flight data sources and a categorization of the data are then presented. A thermal flight data summarization section provides temperature data for the five phases of a typical mission profile. These are: prelaunch, ascent, on-orbit, entry and postlanding. The thermal flight data characterization section encompasses this flight data for flight to flight variations, payload effects, temperature ranges, and other variations. Discussion of the thermal environment prediction models in use by industry and various NASA Centers, and the results predicted by these models, is followed by an evaluation of the correlation between the actual flight data and the results predicted by the models. Finally, the available thermal data are evaluated from the viewpoint of the user concerned with establishing the thermal environment in the payload bay. The data deficiencies are discussed and recommendations for their elimination are presented.

A variational Bayes spatiotemporal model for electromagnetic brain mapping.

PubMed

Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

2014-03-01

In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.

Anthropogenic activities and coastal environmental quality: a regional quantitative analysis in southeast China with management implications.

PubMed

Chen, Kai; Liu, Yan; Huang, Dongren; Ke, Hongwei; Chen, Huorong; Zhang, Songbin; Yang, Shengyun; Cai, Minggang

2018-02-01

Regional analysis of environmental issues has always been a hot topic in the field of sustainable development. Because the different levels of economic growth, urbanization, resource endowments, etc. in different regions generate apparently different ecological responses, a better description and comparison across different regions will provide more valuable implications for ecological improvement and policymaking. In this study, seven typical bays in southeast China that are a rapid developing area were selected to quantitatively analyze the relationship between socioeconomic development and coastal environmental quality. Based on the water quality data from 2007 to 2015, the multivariate statistical method was applied to analyze the potential environmental risks and to classify the seven bays based on their environmental quality status. The possible variation trends of environmental indices were predicted based on the cross-regional panel data by Environmental Kuznets Curve. The results showed that there were significant regional differences among the seven bays, especially Quanzhou, Xiamen, and Luoyuan Bays, suffered from severer artificial disturbances than other bays, despite their different development patterns. Socioeconomic development level was significantly associated with some water quality indices (pH, DIN, PO 4 -P); the association was roughly positive: the areas with higher GDP per capita have some worse water quality indices. In addition, the decreasing trend of pH values and the increasing trend of nutrient concentration in the seven bays will continue in the foreseeable future. In consideration of the variation trends, the limiting nutrient strategy should be implemented to mitigate the deterioration of the coastal environments.

The use of aircraft and satellite remote sensing of phytoplankton chlorophyll concentrations in case 2 estuarine waters of the Chesapeake Bay

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.

1989-01-01

Two projects using remote sensing of phytoplankton chlorophyll concentrations in the Chesapeake Bay estuary were proposed. The first project used aircraft remote sensing with a compact radiometer system developed at NASA's Goddard Space Flight Center (GSFC), the Ocean Data Acquisition System (ODAS). ODAS includes three radiometers at 460, 490, and 520 nm, an infrared temperature sensor (PRT-5), Loran-C for navigation, and a data acquisition system using a PC and mass storage device. This instrument package can be flown in light aircraft at relatively low expense, permitting regular and frequent flights. Sixteen flights with ODAS were completed using the Virginia Institute of Marine Science's De Havilland 'Beaver'. The goal was to increase spatial and temporal resolution in assaying phytoplankton pigment concentrations in the Chesapeake. At present, analysis is underway of flight data collected between March and July 1989. The second project focused on satellite data gathered with the Nimbus-7 Coastal Zone Color Scanner (CZSC) between late 1978 and mid 1986. The problem in using CZSC data for the Chesapeake Bay is that the optical characteristics of this (and many) coastal and estuarine waters are distinct from those of the open ocean for which algorithms for computing pigment concentrations were developed. The successful use of CZCS data for the estuary requires development of site-specific algorithms and analytical approaches. Of principal importance in developing site-specific procedures is the availability of in-situ data on pigment concentrations. A significant data set was acquired from EPA's Chesapeake Bay Program in Annapolis, Maryland, and clear satellite scenes are being analyzed for which same-day sea truth measurements of pigment were obtained. Both the University of Miami and GSFC Seapak systems are being used in this effort. The main finding to date is an expected one, i.e., the algorithms developed for oceanic waters are inadequate to compute pigment concentrations for the Case 2 waters of the Chesapeake Bay. One reason is the overestimation of aerosol radiances by assuming that water-leaving radiance in Band 4 of CZCS (670 nm) is zero, an assumption that is invalid for the Bay. This prompted any attempts to iterative procedures for estimating the proportion of the Band 4 radiance that is actually attributable to aerosol by estimating the water-leaving component using optical data. A cruise on the Chesapeake the week of 7 August 1989 was conducted to collect additional optical data necessary to this task.

Holocene sedimentation in Richardson Bay, California

USGS Publications Warehouse

Connor, Cathy L.

1983-01-01

Examination of foraminifers, diatoms, ostracodes, clay mineralogy, and sediment-size variation from 9 borehole sites along the salt-marsh margins of Richardson Bay reveals a record of gradual infilling of fine-grained estuarine sediments. Over the past 10,000 years this area was transformed from a V-shaped Pleistocene stream valley to a flat-floored arm of the San Francisco Bay estuary. A radiocarbon date obtained from a basal peat overlying nonmarine alluvial sand near the town of Mill Valley indicates that stable salt-marsh vegetation was present in the northwestern arm of Richardson Bay 4600?165 years ago and agrees within error limits with a Holocene sea-level curve developed by Atwater, Hedel, and Helley in 1977 for southern San Francisco Bay. The average sedimentation rate over the last 4600 years is estimated to be 0.2 cm/yr for the inner part of the bay. Comparison of early maps with updated versions as well as studies of marsh plant zonations in disturbed and nondisturbed areas shows that almost half of the marsh in Richardson Bay has been leveed or filled since 1899.

Mobile Bay, Alabama area seen in Skylab 4 Earth Resources Experiment Package

NASA Technical Reports Server (NTRS)

1974-01-01

A near vertical view of the Mobile Bay, Alabama area seen in this Skylab 4 Earth Resources Experiment Package S190-B (five-inch earth terrain camera) photograph taken from the Skylab space station in earth orbit. North of Mobile the Tombigbee and Alabama Rivers join to form the Mobile River. Detailed configuration of the individual stream channels and boundaries can be defined as the Mobile River flows into Mobile Bay and into the Gulf of Mexico. The Mobile River Valley with its numerous stream channels is a distinct light shade in contrast to the dark green shade of the adjacent areas. The red coloration of Mobile Bay reflects the sediment load carried into the bay by the rivers. The westerly movement of the shore currents at the mouth of Mobile Bay is shown by the contrasting light blue of the sediment-laden current the the blue of the Gulf. Agricultural areas east and west of Mobile Bay are characterized by a rectangular pattern in green to white shades. Color variations may reflect

A review on the sources and spatial-temporal distributions of Pb in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Zhang, Jie; Wang, Ming; Zhu, Sixi; Wu, Yunjie

2017-12-01

This paper provided a review on the source, spatial-distribution, temporal variations of Pb in Jiaozhou Bay based on investigation of Pb in surface and waters in different seasons during 1979-1983. The source strengths of Pb sources in Jiaozhou Bay were showing increasing trends, and the pollution level of Pb in this bay was slight or moderate in the early stage of reform and opening-up. Pb contents in the marine bay were mainly determined by the strength and frequency of Pb inputs from human activities, and Pb could be moving from high content areas to low content areas in the ocean interior. Surface waters in the ocean was polluted by human activities, and bottom waters was polluted by means of vertical water’s effect. The process of spatial distribution of Pb in waters was including three steps, i.e., 1), Pb was transferring to surface waters in the bay, 2) Pb was transferring to surface waters, and 3) Pb was transferring to and accumulating in bottom waters.

Detecting the spatial and temporal variability of chlorophylla concentration and total suspended solids in Apalachicola Bay, Florida using MODIS imagery

USGS Publications Warehouse

Wang, Hongqing; Hladik, C.M.; Huang, W.; Milla, K.; Edmiston, L.; Harwell, M.A.; Schalles, J.F.

2010-01-01

Apalachicola Bay, Florida, accounts for 90% of Florida's and 10% of the nation's eastern oyster (Crassostrea virginica) harvesting. Chlorophyll-a concentration and total suspended solids (TSS) are two important water quality variables, among other environmental factors such as salinity, for eastern oyster production in Apalachicola Bay. In this research, we developed regression models of the relationships between the reflectance of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra 250 m data and the two water quality variables based on the Bay-wide field data collected during 14-17 October 2002, a relatively dry period, and 3-5 April 2006, a relatively wet period, respectively. Then we selected the best regression models (highest coefficient of determination, R2) to derive Bay-wide maps of chlorophylla concentration and TSS for the two periods. The MODIS-derived maps revealed large spatial and temporal variations in chlorophylla concentration and TSS across the entire Apalachicola Bay. ?? 2010 Taylor & Francis.

Bayes plus Brass: Estimating Total Fertility for Many Small Areas from Sparse Census Data

PubMed Central

Schmertmann, Carl P.; Cavenaghi, Suzana M.; Assunção, Renato M.; Potter, Joseph E.

2013-01-01

Small-area fertility estimates are valuable for analysing demographic change, and important for local planning and population projection. In countries lacking complete vital registration, however, small-area estimates are possible only from sparse survey or census data that are potentially unreliable. Such estimation requires new methods for old problems: procedures must be automated if thousands of estimates are required, they must deal with extreme sampling variability in many areas, and they should also incorporate corrections for possible data errors. We present a two-step algorithm for estimating total fertility in such circumstances, and we illustrate by applying the method to 2000 Brazilian Census data for over five thousand municipalities. Our proposed algorithm first smoothes local age-specific rates using Empirical Bayes methods, and then applies a new variant of Brass’s P/F parity correction procedure that is robust under conditions of rapid fertility decline. PMID:24143946

Using Bayes factors for multi-factor, biometric authentication

NASA Astrophysics Data System (ADS)

Giffin, A.; Skufca, J. D.; Lao, P. A.

2015-01-01

Multi-factor/multi-modal authentication systems are becoming the de facto industry standard. Traditional methods typically use rates that are point estimates and lack a good measure of uncertainty. Additionally, multiple factors are typically fused together in an ad hoc manner. To be consistent, as well as to establish and make proper use of uncertainties, we use a Bayesian method that will update our estimates and uncertainties as new information presents itself. Our algorithm compares competing classes (such as genuine vs. imposter) using Bayes Factors (BF). The importance of this approach is that we not only accept or reject one model (class), but compare it to others to make a decision. We show using a Receiver Operating Characteristic (ROC) curve that using BF for determining class will always perform at least as well as the traditional combining of factors, such as a voting algorithm. As the uncertainty decreases, the BF result continues to exceed the traditional methods result.

A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors

PubMed Central

Han, Manhyung; Bang, Jae Hun; Nugent, Chris; McClean, Sally; Lee, Sungyoung

2014-01-01

Activity recognition for the purposes of recognizing a user's intentions using multimodal sensors is becoming a widely researched topic largely based on the prevalence of the smartphone. Previous studies have reported the difficulty in recognizing life-logs by only using a smartphone due to the challenges with activity modeling and real-time recognition. In addition, recognizing life-logs is difficult due to the absence of an established framework which enables the use of different sources of sensor data. In this paper, we propose a smartphone-based Hierarchical Activity Recognition Framework which extends the Naïve Bayes approach for the processing of activity modeling and real-time activity recognition. The proposed algorithm demonstrates higher accuracy than the Naïve Bayes approach and also enables the recognition of a user's activities within a mobile environment. The proposed algorithm has the ability to classify fifteen activities with an average classification accuracy of 92.96%. PMID:25184486

SEASONAL AND LONGITUDINAL HOMOGENEITY OF SUSPENDED PARTICLES IN SAN FRANCISCO BAY, CA

EPA Science Inventory

Coastal environments are particularly complex due to variations in geology and upstream watersheds, and are subject to dynamic spatial and temporal changes. Their diverse characteristics result in wide variations in response to environmental stressors such as nutrient over-enrich...

Sedimentary properties of shallow marine cores collected in June and September 2006, Hanalei Bay, Kaua‘i, Hawai‘i

USGS Publications Warehouse

Draut, Amy E.; Bothner, Michael H.; Reynolds, Richard L.; Buchan, Olivia C.; Cochran, Susan A.; Casso, Michael A.; Baldwin, Sandra M.; Goldstein, Harland L.; Xiao, Jiang; Field, Michael E.; Logan, Joshua B.

2007-01-01

Sedimentary facies, short-lived isotopes 7Be, 137Cs, and 210Pb, and magnetic properties of sediment cores in Hanalei Bay, Kaua‘i, Hawai‘i, were used to assess sediment sources and patterns of deposition associated with seasonal flooding of the Hanalei River. Sediment cores were collected from the seafloor in June and September of 2006 to supplement similar data collected during the summer of 2005. The youngest and thickest terrigenous sediment was observed on the east side of the bay: near the Hanalei River mouth and in a bathymetric depression, known locally as the Black Hole, that acts as a temporary sediment sink. Deposits from floods that occurred between February and April 2006 left flood deposits in the eastern bay that, by June of 2006, were on the order of 10 cm thick. A flood occurred on August 7, 2006, that was smaller than floods that occurred the previous winter but was a substantial discharge event for the summer season. Deposits from the winter 2006 floods continued to dominate the sedimentary record in the eastern bay through early fall, even after the addition of newer sediment during the August 7 flood; this is consistent with the much higher sediment input of the winter floods compared with the August 7 flood. Broad variations in magnetic grain size and relative magnetite-hematite abundance in several sediment cores indicate many sources of upland terrigenous sediment. As a group, recent flood deposits show much less variation in these properties compared with older deposits, implying either that the 2006 winter–spring flood sediment originated from one or more distinct upland settings, or that substantial mixing of sediment from multiple sources occurred during transport. Sediment is most readily remobilized and advected out of the bay during winter, when oceanic conditions are energetic. In summer, wave and current measurements made concurrently with this study showed weak currents and little wave energy, indicating that sediment delivered during summer floods most likely remains in the bay until winter storms can remove it. Increased turbidity and sedimentation on corals resulting from floods of the Hanalei River could affect the sustainability of coral reefs and their many associated species. This possibility is of particular concern during summer months when wave energy is low and sediment is not readily remobilized and transported out of the bay. The timing (seasonality) and magnitude of sediment input to the coastal ocean relative to seasonal variations in wave and current energy could have significant ecological consequences for coral-reef communities in the Hawaiian Islands.

Daily variation characteristics at polar geomagnetic observatories

NASA Astrophysics Data System (ADS)

Lepidi, S.; Cafarella, L.; Pietrolungo, M.; Di Mauro, D.

2011-08-01

This paper is based on the statistical analysis of the diurnal variation as observed at six polar geomagnetic observatories, three in the Northern and three in the Southern hemisphere. Data are for 2006, a year of low geomagnetic activity. We compared the Italian observatory Mario Zucchelli Station (TNB; corrected geomagnetic latitude: 80.0°S), the French-Italian observatory Dome C (DMC; 88.9°S), the French observatory Dumont D'Urville (DRV; 80.4°S) and the three Canadian observatories, Resolute Bay (RES; 83.0°N), Cambridge Bay (CBB; 77.0°N) and Alert (ALE, 87.2°N). The aim of this work was to highlight analogies and differences in daily variation as observed at the different observatories during low geomagnetic activity year, also considering Interplanetary Magnetic Field conditions and geomagnetic indices.

Optimal sensor placement for spatial lattice structure based on genetic algorithms

NASA Astrophysics Data System (ADS)

Liu, Wei; Gao, Wei-cheng; Sun, Yi; Xu, Min-jian

2008-10-01

Optimal sensor placement technique plays a key role in structural health monitoring of spatial lattice structures. This paper considers the problem of locating sensors on a spatial lattice structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterized. Based on the criterion of optimal sensor placement for modal test, an improved genetic algorithm is introduced to find the optimal placement of sensors. The modal strain energy (MSE) and the modal assurance criterion (MAC) have been taken as the fitness function, respectively, so that three placement designs were produced. The decimal two-dimension array coding method instead of binary coding method is proposed to code the solution. Forced mutation operator is introduced when the identical genes appear via the crossover procedure. A computational simulation of a 12-bay plain truss model has been implemented to demonstrate the feasibility of the three optimal algorithms above. The obtained optimal sensor placements using the improved genetic algorithm are compared with those gained by exiting genetic algorithm using the binary coding method. Further the comparison criterion based on the mean square error between the finite element method (FEM) mode shapes and the Guyan expansion mode shapes identified by data-driven stochastic subspace identification (SSI-DATA) method are employed to demonstrate the advantage of the different fitness function. The results showed that some innovations in genetic algorithm proposed in this paper can enlarge the genes storage and improve the convergence of the algorithm. More importantly, the three optimal sensor placement methods can all provide the reliable results and identify the vibration characteristics of the 12-bay plain truss model accurately.

Spatial and temporal variations in silver contamination and toxicity in San Francisco Bay

USGS Publications Warehouse

Flegal, A.R.; Brown, C.L.; Squire, S.; Ross, J.R.M.; Scelfo, G.M.; Hibdon, S.

2007-01-01

Although San Francisco Bay has a "Golden Gate", it may be argued that it is the "Silver Estuary". For at one time the Bay was reported to have the highest levels of silver in its sediments and biota, along with the only accurately measured values of silver in solution, of any estuarine system. Since then others have argued that silver contamination is higher elsewhere (e.g., New York Bight, Florida Bay, Galveston Bay) in a peculiar form of pollution machismo, while silver contamination has measurably declined in sediments, biota, and surface waters of the Bay over the past two to three decades. Documentation of those systemic temporal declines has been possible because of long-term, ongoing monitoring programs, using rigorous trace metal clean sampling and analytical techniques, of the United States Geological Survey and San Francisco Bay Regional Monitoring Program that are summarized in this report. However, recent toxicity studies with macro-invertebrates in the Bay have indicated that silver may still be adversely affecting the health of the estuarine system, and other studies have indicated that silver concentrations in the Bay may be increasing due to new industrial inputs and/or the diagenetic remobilization of silver from historically contaminated sediments being re-exposed to overlying surface waters and benthos. Consequently, the Bay may not be ready to relinquish its title as the "Silver Estuary". ?? 2007 Elsevier Inc. All rights reserved.

Mixing to Monsoons: Air-Sea Interactions in the Bay of Bengal

NASA Astrophysics Data System (ADS)

Lucas, A. J.; Shroyer, E. L.; Wijesekera, H. W.; Fernando, H. J. S.; D'Asaro, E.; Ravichandran, M.; Jinadasa, S. U. P.; MacKinnon, J. A.; Nash, J. D.; Sharma, R.; Centurioni, L.; Farrar, J. T.; Weller, R.; Pinkel, R.; Mahadevan, A.; Sengupta, D.; Tandon, A.

2014-07-01

More than 1 billion people depend on rainfall from the South Asian monsoon for their livelihoods. Summertime monsoonal precipitation is highly variable on intraseasonal time scales, with alternating "active" and "break" periods. These intraseasonal oscillations in large-scale atmospheric convection and winds are closely tied to 1°C-2°C variations of sea surface temperature in the Bay of Bengal.

Dissolved trace elements in a nitrogen-polluted river near to the Liaodong Bay in Northeast China.

PubMed

Bu, Hongmei; Song, Xianfang; Guo, Fen

2017-01-15

Dissolved trace element concentrations (Ba, Fe, Mn, Si, Sr, and Zn) were investigated in the Haicheng River near to the Liaodong Bay in Northeast China during 2010. Dissolved Ba, Fe, Mn, and Sr showed significant spatial variation, whereas dissolved Fe, Mn, and Zn displayed seasonal variations. Conditions such as water temperature, pH, and dissolved oxygen were found to have an important impact on redox reactions involving dissolved Ba, Fe, and Zn. Dissolved Fe and Mn concentrations were regulated by adsorption or desorption of Fe/Mn oxyhydroxides and the effects of organic carbon complexation on dissolved Ba and Sr were found to be significant. The sources of dissolved trace elements were found to be mainly from domestic sewage, industrial waste, agricultural surface runoff, and natural origin, with estimated seasonal and annual river fluxes established as important inputs of dissolved trace elements from the Haicheng River into the Liaodong Bay or Bohai Sea. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of two methods for using MR information in PET reconstruction

NASA Astrophysics Data System (ADS)

Caldeira, L.; Scheins, J.; Almeida, P.; Herzog, H.

2013-02-01

Using magnetic resonance (MR) information in maximum a posteriori (MAP) algorithms for positron emission tomography (PET) image reconstruction has been investigated in the last years. Recently, three methods to introduce this information have been evaluated and the Bowsher prior was considered the best. Its main advantage is that it does not require image segmentation. Another method that has been widely used for incorporating MR information is using boundaries obtained by segmentation. This method has also shown improvements in image quality. In this paper, two methods for incorporating MR information in PET reconstruction are compared. After a Bayes parameter optimization, the reconstructed images were compared using the mean squared error (MSE) and the coefficient of variation (CV). MSE values are 3% lower in Bowsher than using boundaries. CV values are 10% lower in Bowsher than using boundaries. Both methods performed better than using no prior, that is, maximum likelihood expectation maximization (MLEM) or MAP without anatomic information in terms of MSE and CV. Concluding, incorporating MR information using the Bowsher prior gives better results in terms of MSE and CV than boundaries. MAP algorithms showed again to be effective in noise reduction and convergence, specially when MR information is incorporated. The robustness of the priors in respect to noise and inhomogeneities in the MR image has however still to be performed.

Nearest Neighbor Algorithms for Pattern Classification

NASA Technical Reports Server (NTRS)

Barrios, J. O.

1972-01-01

A solution of the discrimination problem is considered by means of the minimum distance classifier, commonly referred to as the nearest neighbor (NN) rule. The NN rule is nonparametric, or distribution free, in the sense that it does not depend on any assumptions about the underlying statistics for its application. The k-NN rule is a procedure that assigns an observation vector z to a category F if most of the k nearby observations x sub i are elements of F. The condensed nearest neighbor (CNN) rule may be used to reduce the size of the training set required categorize The Bayes risk serves merely as a reference-the limit of excellence beyond which it is not possible to go. The NN rule is bounded below by the Bayes risk and above by twice the Bayes risk.

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

PubMed Central

2015-01-01

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377

L2-Boosting algorithm applied to high-dimensional problems in genomic selection.

PubMed

González-Recio, Oscar; Weigel, Kent A; Gianola, Daniel; Naya, Hugo; Rosa, Guilherme J M

2010-06-01

The L(2)-Boosting algorithm is one of the most promising machine-learning techniques that has appeared in recent decades. It may be applied to high-dimensional problems such as whole-genome studies, and it is relatively simple from a computational point of view. In this study, we used this algorithm in a genomic selection context to make predictions of yet to be observed outcomes. Two data sets were used: (1) productive lifetime predicted transmitting abilities from 4702 Holstein sires genotyped for 32 611 single nucleotide polymorphisms (SNPs) derived from the Illumina BovineSNP50 BeadChip, and (2) progeny averages of food conversion rate, pre-corrected by environmental and mate effects, in 394 broilers genotyped for 3481 SNPs. Each of these data sets was split into training and testing sets, the latter comprising dairy or broiler sires whose ancestors were in the training set. Two weak learners, ordinary least squares (OLS) and non-parametric (NP) regression were used for the L2-Boosting algorithm, to provide a stringent evaluation of the procedure. This algorithm was compared with BL [Bayesian LASSO (least absolute shrinkage and selection operator)] and BayesA regression. Learning tasks were carried out in the training set, whereas validation of the models was performed in the testing set. Pearson correlations between predicted and observed responses in the dairy cattle (broiler) data set were 0.65 (0.33), 0.53 (0.37), 0.66 (0.26) and 0.63 (0.27) for OLS-Boosting, NP-Boosting, BL and BayesA, respectively. The smallest bias and mean-squared errors (MSEs) were obtained with OLS-Boosting in both the dairy cattle (0.08 and 1.08, respectively) and broiler (-0.011 and 0.006) data sets, respectively. In the dairy cattle data set, the BL was more accurate (bias=0.10 and MSE=1.10) than BayesA (bias=1.26 and MSE=2.81), whereas no differences between these two methods were found in the broiler data set. L2-Boosting with a suitable learner was found to be a competitive alternative for genomic selection applications, providing high accuracy and low bias in genomic-assisted evaluations with a relatively short computational time.

Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Physical property data from the ICDP-USGS Eyreville cores A and B, Chesapeake Bay impact structure, Virginia, USA, acquired using a multisensor core logger

USGS Publications Warehouse

Pierce, H.A.; Murray, J.B.

2009-01-01

The International Continental Scientific Drilling Program (ICDP) and the U.S. Geological Survey (USGS) drilled three core holes to a composite depth of 1766 m within the moat of the Chesapeake Bay impact structure. Core recovery rates from the drilling were high (??90%), but problems with core hole collapse limited the geophysical downhole logging to natural-gamma and temperature logs. To supplement the downhole logs, ??5% of the Chesapeake Bay impact structure cores was processed through the USGS GeoTek multisensor core logger (MSCL) located in Menlo Park, California. The measured physical properties included core thickness (cm), density (g cm-3), P-wave velocity (m s-1), P-wave amplitude (%), magnetic susceptibility (cgs), and resistivity (ohm-m). Fractional porosity was a secondary calculated property. The MSCL data-sampling interval for all core sections was 1 cm longitudinally. Photos of each MSCL sampled core section were imbedded with the physical property data for direct comparison. These data have been used in seismic, geologic, thermal history, magnetic, and gravity models of the Chesapeake Bay impact structure. Each physical property curve has a unique signature when viewed over the full depth of the Chesapeake Bay impact structure core holes. Variations in the measured properties reflect differences in pre-impact target-rock lithologies and spatial variations in impact-related deformation during late-stage crater collapse and ocean resurge. ?? 2009 The Geological Society of America.

Clam density and scaup feeding behavior in San Pablo Bay, California

USGS Publications Warehouse

Poulton, Victoria K.; Lovvorn, James R.; Takekawa, John Y.

2002-01-01

San Pablo Bay, in northern San Francisco Bay, California, is an important wintering area for Greater (Aythya marila) and Lesser Scaup (A. affinis). We investigated variation in foraging behavior of scaup among five sites in San Pablo Bay, and whether such variation was related to densities of their main potential prey, the clams Potamocorbula amurensis and Macoma balthica. Time-activity budgets showed that scaup spent most of their time sleeping at some sites, and both sleeping and feeding at other sites, with females feeding more than males. In the first half of the observation period (12 January–5 February 2000), percent time spent feeding increased with increasing density of P. amurensis, but decreased with increasing density of M. balthica (diet studies have shown that scaup ate mostly P. amurensis and little or no M. balthica). Densities of M. balthica stayed about the same between fall and spring benthic samples, while densities of P. amurensis declined dramatically at most sites. In the second half of the observation period (7 February–3 March 2000), percent time feeding was no longer strongly related to P. amurensis densities, and dive durations increased by 14%. These changes probably reflected declines of P. amurensis, perhaps as affected by scaup predation. The large area of potential feeding habitat, and alternative prey elsewhere in the estuary, might have resulted in the low correlations between scaup behavior and prey densities in San Pablo Bay. These low correlations made it difficult to identify specific areas of prey concentrations important to scaup.

Monitoring population status of sea otters (Enhydra lutris) in Glacier Bay National Park and Preserve, Alaska: options and considerations

USGS Publications Warehouse

Esslinger, George G.; Esler, Daniel N.; Howlin, S.; Starcevich, L.A.

2015-06-25

After many decades of absence from southeast Alaska, sea otters (Enhydra lutris) are recolonizing parts of their former range, including Glacier Bay, Alaska. Sea otters are well known for structuring nearshore ecosystems and causing community-level changes such as increases in kelp abundance and changes in the size and number of other consumers. Monitoring population status of sea otters in Glacier Bay will help park researchers and managers understand and interpret sea otter-induced ecosystem changes relative to other sources of variation, including potential human-induced impacts such as ocean acidification, vessel disturbance, and oil spills. This report was prepared for the National Park Service (NPS), Southeast Alaska Inventory and Monitoring Network following a request for evaluation of options for monitoring sea otter population status in Glacier Bay National Park and Preserve. To meet this request, we provide a detailed consideration of the primary method of assessment of abundance and distribution, aerial surveys, including analyses of power to detect interannual trends and designs to reduce variation around annual abundance estimates. We also describe two alternate techniques for evaluating sea otter population status—(1) quantifying sea otter diets and energy intake rates, and (2) detecting change in ages at death. In addition, we provide a brief section on directed research to identify studies that would further our understanding of sea otter population dynamics and effects on the Glacier Bay ecosystem, and provide context for interpreting results of monitoring activities.

Postimpact deposition in the Chesapeake Bay impact structure: Variations in eustasy, compaction, sediment supply, and passive-aggressive tectonism

USGS Publications Warehouse

Kulpecz, A.A.; Miller, K.G.; Browning, J.V.; Edwards, L.E.; Powars, D.S.; McLaughlin, P.P.; Harris, A.D.; Feigenson, M.D.

2009-01-01

The Eyreville and Exmore, Virginia, core holes were drilled in the inner basin and annular trough, respectively, of the Chesapeake Bay impact structure, and they allow us to evaluate sequence deposition in an impact crater. We provide new high-resolution geochronologic (<1 Ma) and sequence-stratigraphic interpretations of the Exmore core, identify 12 definite (and four possible) postimpact depositional sequences, and present comparisons with similar results from Eyreville and other mid- Atlantic core holes. The concurrence of increases in ??18O with Chesapeake Bay impact structure sequence boundaries indicates a primary glacioeustatic control on deposition. However, regional comparisons show the differential preservation of sequences across the mid-Atlantic margin. We explain this distribution by the compaction of impactites, regional sediment-supply changes, and the differential movement of basement structures. Upper Eocene strata are thin or missing updip and around the crater, but they thicken into the inner basin (and offshore to the southeast) due to rapid crater infilling and concurrent impactite compaction. Oligocene sequences are generally thin and highly dissected throughout the mid-Atlantic region due to sediment starvation and tectonism, except in southeastern New Jersey. Regional tectonic uplift of the Norfolk Arch coupled with a southward decrease in sediment supply resulted in: (1) largely absent Lower Miocene sections around the Chesapeake Bay impact structure compared to thick sections in New Jersey and Delaware; (2) thick Middle Miocene sequences across the Delmarva Peninsula that thin south of the Chesapeake Bay impact structure; and (3) upper Middle Miocene sections that pinch out just north of the Chesapeake Bay impact structure. Conversely, the Upper Miocene-Pliocene section is thick across Virginia, but it is poorly represented in New Jersey because of regional variations in relative subsidence. ?? 2009 The Geological Society of America.

Biometric, microstructural, and high-resolution trace element studies in Crassostrea gigas of Cantabria (Bay of Biscay, Spain): Anthropogenic and seasonal influences

NASA Astrophysics Data System (ADS)

Higuera-Ruiz, R.; Elorza, J.

2009-04-01

Living Crassostrea gigas oysters of different ages and sizes were collected in three estuaries of Cantabria (Bay of Biscay, Spain): San Vicente de la Barquera Estuary, Santander Bay, and Marismas de Santoña Estuary. The main objective was to determine different shell responses to variable environmental parameters. A shell morphological study, based on three biometric indices, indicates that oysters of Santander Bay have two significant shell anomalies: abnormal thickening of the right valve and loss of vital cavity volume. These shell abnormalities are related with the presence in these waters of the chemical tributyltin. In the other two estuaries, the oysters show no detectable anomalies. Four shell microstructures have been distinguished: Regular Simple Prismatic, Regular Foliated, cone-Complex Cross Foliated, and Chalk. In Santander Bay oysters, the Chalk forms a "root-type" framework, whereas in the other two estuaries it forms a more compact microstructure. It is proposed that exposure to tributyltin has produced this modification. High-spatial-resolution geochemical transects have been carried out on the Regular Foliated microstructure in the umbo region in order to evaluate the distribution of Mg, Sr, and Na. The elements analysed exhibit clear cyclic variations in San Vicente de la Barquera Estuary and Marismas de Santoña Estuary oysters, related with seasonal periods, and characterised by broad maxima during months in which the waters are warmer and have higher salinity. These patterns are buffered in Santander Bay oysters. Our results demonstrate that biometric, microstructural, and high-resolution trace element studies in oyster shells can provide information about contaminants and seasonal variations in the estuarine environment.

Evaluation and Validation of Case 2 Algorithms in Chesapeake Bay

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.; Magnuson, Adrea

2004-01-01

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements form Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (greater than 6,500 square kilometers) make retrievals from satellites with a spatial resolution of approximately 1 kilometer (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra. Finally, past and ongoing research efforts provided an expensive data set of optical observations that support the goal of this project.

Applications of HCMM data to soil moisture snow and estuarine current studies. [soil moisture in Minnesota and water circulation in the Delaware Bay and Potomac River

NASA Technical Reports Server (NTRS)

Wiesnet, D. R. (Principal Investigator); Mcginnis, D. F.; Matson, M.

1979-01-01

The author has identified the following significant results. Additional analyses of Luverne, Minnesota ground data revealed that soil moisture variations are independent of elevation effects. Tidal fluctuations in the Potomac River and Delaware Bay were examined as a function of surface temperature. Preliminary findings suggest that temperature boundaries are sufficient to detect various stages of the tidal cycle in Delaware Bay, but are as yet uncertain for prediction in the Potomac River. At least three additional cases are needed to completely evaluate the tidal cycle. An alphanumeric printout at a scale of 1:1,000,000 compares closely with a 1:1,000,000 scale DMD image of the Chesapeake Bay region.

Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL

USGS Publications Warehouse

Hu, Chuanmin; Chen, Zhiqiang; Clayton, Tonya D.; ,; Brock, John C.; Muller-Karger, Frank E.

2004-01-01

Using Tampa Bay, FL as an example, we explored the potential for using MODIS medium-resolution bands (250- and 500-m data at 469-, 555-, and 645-nm) for estuarine monitoring. Field surveys during 21–22 October 2003 showed that Tampa Bay has Case-II waters, in that for the salinity range of 24–32 psu, (a) chlorophyll concentration (11 to 23 mg m−3), (b) colored dissolved organic matter (CDOM) absorption coefficient at 400 nm (0.9 to 2.5 m−1), and (c) total suspended sediment concentration (TSS: 2 to 11 mg L−1) often do not co-vary. CDOM is the only constituent that showed a linear, inverse relationship with surface salinity, although the slope of the relationship changed with location within the bay. The MODIS medium-resolution bands, although designed for land use, are 4–5 times more sensitive than Landsat-7/ETM+ data and are comparable to or higher than those of CZCS. Several approaches were used to derive synoptic maps of water constituents from concurrent MODIS medium-resolution data. We found that application of various atmospheric-correction algorithms yielded no significant differences, due primarily to uncertainties in the sensor radiometric calibration and other sensor artifacts. However, where each scene could be groundtruthed, simple regressions between in situ observations of constituents and at-sensor radiances provided reasonable synoptic maps. We address the need for improvements of sensor calibration/characterization, atmospheric correction, and bio-optical algorithms to make operational and quantitative use of these medium-resolution bands.

Spatial and overwinter changes in clam populations of San Pablo Bay, a semiarid estuary with highly variable freshwater inflow

USGS Publications Warehouse

Poulton, V.K.; Lovvorn, J.R.; Takekawa, John Y.

2004-01-01

In many estuaries worldwide, climate trends together with human diversion of fresh water have dramatically impacted the benthos. Such impacts have sometimes been complicated by exotic species, whose invasion and persistence can be mediated by wide variations in freshwater inflow. Monitoring such changes usually involves periodic samples at a few sites; but sampling that does not recognize variation at a range of spatial and seasonal scales may not reveal important benthic trends. San Pablo Bay, in northern San Francisco Bay, has extreme fluctuations in freshwater inflow. This bay also experienced a major benthic change with introduction of the Asian clam (Potamocorbula amurensis) in 1986. This species initially displaced the former community, but later appeared to vary in abundance depending on site and freshwater inflow. To investigate such patterns and provide guidelines for research and monitoring, we took 1746 core samples at six sites around San Pablo Bay from 19 October to 17 December 1999 and from 6 March to 19 April 2000. Most biomass consisted of the clams P. amurensis,Macoma balthica and Mya arenaria. Potamocorbula amurensis dominated the benthos at most sites in the fall and recruited a new cohort during winter, while there was weak recruitment in M. balthica and none in M. arenaria. At most but not all sites, densities of P. amurensis and M. arenaria declined dramatically over winter while M. balthica declined only slightly. The dominant clams had patch diameters >5 m at most but not all sites, and some showed inconsistent patch structure at scales of 100–1400 m. In this semiarid estuary with highly variable freshwater inflow, samples for research and monitoring should include multiple sites and seasons, and samples within sites should be ≥5 m apart to account for between-patch variation. Species abundance in winter 1999–2000 appeared to be affected by high freshwater inflows in 1997–1999, while spatial patterns were probably most affected by post-settlement dispersal and mortality.

Seasonal variations of carbonate system parameters and nutrients at the shellfish-farming bays along the south coast of Korea

NASA Astrophysics Data System (ADS)

Shim, JeongHee; Shim, Jeong-Min; Lee, Yong-Hwa

2017-04-01

About 80 90% of the annual mass production of shellfish in Korea are cultured at the inner bays including Jinhae, Tongyeong and Geoje regions, along the south coast of Korea. To understand coastal carbon and nutrients cycles and those effects/feedbacks on shellfish farming, carbonate (DIC, TA and pH) and environmental parameters were observed at Jinhae, Tongyeong and Geoje Bays 4 times (in Feb., Aug. 2014, Apr. and Oct. 2015 and are considered representative of winter, summer, spring and fall respectively). Surface temperature in the bays showed clear seasonal variation with about 6 12°C and 24 29°C in Feb. and Aug. 2014, respectively and 14 18°C and 22 26°C in Apr. and in Oct. 2015, respectively. Surface pHNBS also ranged with about 8.20 8.53 and 7.28 8.95 in Feb. and Aug. 2014, and 8.04 8.40 and 7.91 8.32 in Apr. and in Oct. 2015. High pH with low salinity in summer resulted from input of land discharge in rainy seasons, however high pH at small bays in Apr. and Oct. 2015 resulted from massive primary production by phytoplankton bloom, supported by high chlorophyll a concentrations. Seasonal variations of DIC and phosphate in the surface and bottom waters correlated largely with salinity, higher in winter and lower in summer. Specifically in shellfish (specially, oyster and mussel) growing season, aragonite saturation state (Ωarag) in bottom water ranged about 0.2 2.9 (mean 2.1) and 2.2 5.0 (mean 3.2) in Feb. 2014 and Oct. 2015, respectively, suggesting low pH environments arose seasonally in coastal area due to some mechanisms. These results suggest that seasonal ocean acidification state might seriously affect shell growth, mass production and thus shellfish industry along the south coast of Korea.

Factors affecting spatial and temporal variability in material exchange between the Southern Everglades wetlands and Florida Bay (USA)

NASA Astrophysics Data System (ADS)

Sutula, Martha A.; Perez, Brian C.; Reyes, Enrique; Childers, Daniel L.; Davis, Steve; Day, John W.; Rudnick, David; Sklar, Fred

2003-08-01

Physical and biological processes controlling spatial and temporal variations in material concentration and exchange between the Southern Everglades wetlands and Florida Bay were studied for 2.5 years in three of the five major creek systems draining the watershed. Daily total nitrogen (TN), and total phosphorus (TP) fluxes were measured for 2 years in Taylor River, and ten 10-day intensive studies were conducted in this creek to estimate the seasonal flux of dissolved inorganic nitrogen (N), phosphorus (P), total organic carbon (TOC), and suspended matter. Four 10-day studies were conducted simultaneously in Taylor, McCormick, and Trout Creeks to study the spatial variation in concentration and flux. The annual fluxes of TOC, TN, and TP from the Southern Everglades were estimated from regression equations. The Southern Everglades watershed, a 460-km 2 area that includes Taylor Slough and the area south of the C-111 canal, exported 7.1 g C m -2, 0.46 g N m -2, and 0.007 g P m -2, annually. Everglades P flux is three to four orders of magnitude lower than published flux estimates from wetlands influenced by terrigenous sedimentary inputs. These low P flux values reflect both the inherently low P content of Everglades surface water and the efficiency of Everglades carbonate sediments and biota in conserving and recycling this limiting nutrient. The seasonal variation of freshwater input to the watershed was responsible for major temporal variations in N, P, and C export to Florida Bay; approximately 99% of the export occurred during the rainy season. Wind-driven forcing was most important during the later stages of the dry season when low freshwater head coincided with southerly winds, resulting in a net import of water and materials into the wetlands. We also observed an east to west decrease in TN:TP ratio from 212:1 to 127:1. Major spatial gradients in N:P ratios and nutrient concentration and flux among the creek were consistent with the westward decrease in surface water runoff from the P-limited Everglades and increased advection of relatively P-rich Gulf of Mexico (GOM) waters into Florida Bay. Comparison of measured nutrient flux from Everglades surface water inputs from this study with published estimates of other sources of nutrients to Florida Bay (i.e. atmospheric deposition, anthropogenic inputs from the Florida Keys, advection from the GOM) show that Everglades runoff represents only 2% of N inputs and 0.5% of P input to Florida Bay.

Accuracy assessment of satellite Ocean colour products in coastal waters.

NASA Astrophysics Data System (ADS)

Tilstone, G.; Lotliker, A.; Groom, S.

2012-04-01

The use of Ocean Colour Remote Sensing to monitor phytoplankton blooms in coastal waters is hampered by the absorption and scattering from substances in the water that vary independently of phytoplankton. In this paper we compare different ocean colour algorithms available for SeaWiFS, MODIS and MERIS with in situ observations of Remote Sensing Reflectance, Chlorophyll-a (Chla), Total Suspended Material and Coloured Dissolved Organic Material in coastal waters of the Arabian Sea, Bay of Bengal, North Sea and Western English Channel, which have contrasting inherent optical properties. We demonstrate a clustering method on specific-Inherent Optical Properties (sIOP) that gives accurate water quality products from MERIS data (HYDROPT) and also test the recently developed ESA CoastColour MERIS products. We found that for coastal waters of the Bay of Bengal, OC5 gave the most accurate Chla, for the Arabian Sea GSM and OC3M Chla were more accurate and for the North Sea and Western English Channel, MERIS HYDROPT were more accurate than standard algorithms. The reasons for these differences will be discussed. A Chla time series from 2002-2011 will be presented to illustrate differences in algorithms between coastal regions and inter- and intra-annual variability in phytoplankton blooms

Modelling river discharge and precipitation from estuarine salinity in the northern Chesapeake Bay: Application to Holocene palaeoclimate

USGS Publications Warehouse

Saenger, C.; Cronin, T.; Thunell, R.; Vann, C.

2006-01-01

Long-term chronologies of precipitation can provide a baseline against which twentieth-century trends in rainfall can be evaluated in terms of natural variability and anthropogenic influence. However, there are relatively few methods to quantitatively reconstruct palaeoprecipitation and river discharge compared with proxies of other climatic factors, such as temperature. We developed autoregressive and least squares statistical models relating Chesapeake Bay salinity to river discharge and regional precipitation records. Salinity in northern and central parts of the modern Chesapeake Bay is influenced largely by seasonal, interannual and decadal variations in Susquehanna River discharge, which in turn are controlled by regional precipitation patterns. A power regressive discharge model and linear precipitation model exhibit well-defined decadal variations in peak discharge and precipitation. The utility of the models was tested by estimating Holocene palaeoprecipitation and Susquehanna River palaeodischarge, as indicated by isotopically derived palaeosalinity reconstructions from Chesapeake Bay sediment cores. Model results indicate that the early-mid Holocene (7055-5900 yr BP) was drier than the late Holocene (1500 yr BP - present), the 'Mediaeval Warm Period' (MWP) (1200-600 yr BP) was drier than the 'Little Ice Age' (LIA) (500-100 yr BP), and the twentieth century experienced extremes in precipitation possibly associated with changes in ocean-atmosphere teleconnections. ?? 2006 Edward Arnold (Publishers) Ltd.

Extremes in ecology: Avoiding the misleading effects of sampling variation in summary analyses

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1996-01-01

Surveys such as the North American Breeding Bird Survey (BBS) produce large collections of parameter estimates. One's natural inclination when confronted with lists of parameter estimates is to look for the extreme values: in the BBS, these correspond to the species that appear to have the greatest changes in population size through time. Unfortunately, extreme estimates are liable to correspond to the most poorly estimated parameters. Consequently, the most extreme parameters may not match up with the most extreme parameter estimates. The ranking of parameter values on the basis of their estimates are a difficult statistical problem. We use data from the BBS and simulations to illustrate the potential misleading effects of sampling variation in rankings of parameters. We describe empirical Bayes and constrained empirical Bayes procedures which provide partial solutions to the problem of ranking in the presence of sampling variation.

Development, implementation, and validation of a modeling system for the San Francisco Bay and Estuary

NASA Astrophysics Data System (ADS)

Chao, Yi; Farrara, John D.; Zhang, Hongchun; Zhang, Yinglong J.; Ateljevich, Eli; Chai, Fei; Davis, Curtiss O.; Dugdale, Richard; Wilkerson, Frances

2017-07-01

A three-dimensional numerical modeling system for the San Francisco Bay is presented. The system is based on an unstructured grid numerical model known as Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM). The lateral boundary condition is provided by a regional coastal ocean model. The surface forcing is provided by a regional atmospheric model. The SCHISM results from a decadal hindcast run are compared with available tide gauge data, as well as a collection of temperature and salinity profiles. An examination of the observed climatological annual mean salinities at the United States Geological Survey (USGS) stations shows the highest salinities to be in the open ocean and the lowest well north (upstream) of the Central Bay, a pattern that does not change substantially with season. The corresponding mean SCHISM salinities reproduced the observed variations with location quite well, though with a fresh bias. The lowest values within the Bay occur during spring and the highest values during autumn, mirroring the seasonal variations in river discharge. The corresponding observed mean temperatures within the Bay were 2 to 3° C cooler in the Central Bay than to either the north or south. This observed pattern of a cooler Central Bay was not particularly well reproduced in the SCHISM results, which also showed a cold bias. Examination of the seasonal means revealed that the cool Central Bay pattern is found only during summer in the SCHISM results. The persistent cold and fresh biases in the model control run were nearly eliminated in a sensitivity run with modifications to the surface heat flux and river discharge. The surface atmospheric forcing and the heat flux at the western boundary are found to be the two major terms in a SCHISM-based heat budget analysis of the mean seasonal temperature cycle for the Central Bay. In the Central Bay salt budget, freshwater discharged by rivers into upstream portions of the Bay to the north balanced by the influx of salt from the west are the primary drivers of the mean seasonal salinity cycle. Concerning the interannual variability in temperatures, the warm anomalies during the period 2014-16 were the strongest and most persistent departures from normal during the period analyzed and were realistically reproduced by SCHISM. The most prominent salinity anomalies in both the observations and SCHISM results were the salty anomalies that persisted for most of the four-year California drought of 2012-2015.

Learning Instance-Specific Predictive Models

PubMed Central

Visweswaran, Shyam; Cooper, Gregory F.

2013-01-01

This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algorithm learns Markov blanket models, carries out Bayesian model averaging over a set of models to predict a target variable of the instance at hand, and employs an instance-specific heuristic to locate a set of suitable models to average over. We call this method the instance-specific Markov blanket (ISMB) algorithm. The ISMB algorithm was evaluated on 21 UCI data sets using five different performance measures and its performance was compared to that of several commonly used predictive algorithms, including nave Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor, Lazy Bayesian Rules, and AdaBoost. Over all the data sets, the ISMB algorithm performed better on average on all performance measures against all the comparison algorithms. PMID:25045325

Analysis of change of red tide species in Yodo River estuary by the numerical ecosystem model.

PubMed

Hayashi, Mitsuru; Yanagi, Tetsuo

2008-01-01

Occurrence number of red tides in Osaka Bay in Japan is more than 20 cases every year. Diatom red tide was dominant in Osaka Bay, but the non-diatom red tide was dominant in early 1990s. Therefore, the material cycling in Yodo River estuary in Osaka Bay during August from 1991 to 2000 was analyzed by using the numerical ecosystem model and field observation data to clarify the reasons of change in red tide species. Year-to-year variation in calculated concentration ratio of diatom to non-diatom corresponds to the variation in observed ratio of red tide days of diatom to non-diatom. Limiting nutrient of primary production is phosphate over the period. Diatom dominated from 1991 to 1993, but it was difficult for non-diatom to grow due to the limitation by physical condition. Non-diatom was able to grow because of good physical and nutrient conditions from 1994 to 1996. And diatom dominated again under the good physical condition, and phosphorus supply was not enough for non-diatom to grow from 1998 to 2000. Phosphate concentration in the lower layer of Yodo River estuary was important to the variation in red tide species in the upper layer of Yodo River estuary.

Intraspecific variation in Cryptocaryon irritans.

PubMed

Diggles, B K; Adlard, R D

1997-01-01

Intraspecific variation in the ciliate Cryptocaryon irritans was examined using sequences of the first internal transcribed spacer region (ITS-1) of ribosomal DNA (rDNA) combined with developmental and morphological characters. Amplified rDNA sequences consisting of 151 bases of the flanking 18 S and 5.8 S regions, and the entire ITS-1 region (169 or 170 bases), were determined and compared for 16 isolates of C. irritans from Australia, Israel and the USA. There was one variable base between isolates in the 18 S region and 11 variable bases in the ITS-1 region. Despite their similar morphology, significant sequence variation (4.1% divergence) and developmental differences indicate that Australian C. irritans isolates from estuarine (Moreton Bay) and coral reef (Heron Island) environments are distinct. The Heron Island isolate was genetically closer to morphologically dissimilar isolates from Israel (1.8% divergence) and the USA (2.3% divergence) than it was to the Moreton Bay isolates. Three isolates maintained in our laboratory since February 1994 differed in sequence from earlier laboratory isolates (2.9% to 3.5% divergence), even though all were similar morphologically and originated from the same source. During this time the sequence of the isolates from wild fish in Moreton Bay remained unchanged. These genetic differences indicate the existence of a founder effect in laboratory populations of C. irritans. The genetic variation found here, combined with known morphological and developmental differences, is used to characterise four strains of C. irritans.

Seasonal and spatial variations of water quality and trophic status in Daya Bay, South China Sea.

PubMed

Wu, Mei-Lin; Wang, You-Shao; Wang, Yu-Tu; Sun, Fu-Lin; Sun, Cui-Ci; Cheng, Hao; Dong, Jun-De

2016-11-15

Coastal water quality and trophic status are subject to intensive environmental stress induced by human activities and climate change. Quarterly cruises were conducted to identify environmental characteristics in Daya Bay in 2013. Water quality is spatially and temporally dynamic in the bay. Cluster analysis (CA) groups 12 monitoring stations into two clusters. Cluster I consists of stations (S1, S2, S4-S7, S9, and S12) located in the central, eastern, and southern parts of the bay, representing less polluted regions. Cluster II includes stations (S3, S8, S10, and S11) located in the western and northern parts of the bay, indicating the highly polluted regions receiving a high amount of wastewater and freshwater discharge. Principal component analysis (PCA) identified that water quality experience seasonal change (summer, winter, and spring-autumn seasons) because of two monsoons in the study area. Eutrophication in the bay is graded as high by Assessment of Estuarine Trophic Status (ASSETS). Copyright © 2016 Elsevier Ltd. All rights reserved.

Processes of 30-90 days sea surface temperature variability in the northern Indian Ocean during boreal summer

NASA Astrophysics Data System (ADS)

Vialard, J.; Jayakumar, A.; Gnanaseelan, C.; Lengaigne, M.; Sengupta, D.; Goswami, B. N.

2012-05-01

During summer, the northern Indian Ocean exhibits significant atmospheric intraseasonal variability associated with active and break phases of the monsoon in the 30-90 days band. In this paper, we investigate mechanisms of the Sea Surface Temperature (SST) signature of this atmospheric variability, using a combination of observational datasets and Ocean General Circulation Model sensitivity experiments. In addition to the previously-reported intraseasonal SST signature in the Bay of Bengal, observations show clear SST signals in the Arabian Sea related to the active/break cycle of the monsoon. As the atmospheric intraseasonal oscillation moves northward, SST variations appear first at the southern tip of India (day 0), then in the Somali upwelling region (day 10), northern Bay of Bengal (day 19) and finally in the Oman upwelling region (day 23). The Bay of Bengal and Oman signals are most clearly associated with the monsoon active/break index, whereas the relationship with signals near Somali upwelling and the southern tip of India is weaker. In agreement with previous studies, we find that heat flux variations drive most of the intraseasonal SST variability in the Bay of Bengal, both in our model (regression coefficient, 0.9, against ~0.25 for wind stress) and in observations (0.8 regression coefficient); ~60% of the heat flux variation is due do shortwave radiation and ~40% due to latent heat flux. On the other hand, both observations and model results indicate a prominent role of dynamical oceanic processes in the Arabian Sea. Wind-stress variations force about 70-100% of SST intraseasonal variations in the Arabian Sea, through modulation of oceanic processes (entrainment, mixing, Ekman pumping, lateral advection). Our ~100 km resolution model suggests that internal oceanic variability (i.e. eddies) contributes substantially to intraseasonal variability at small-scale in the Somali upwelling region, but does not contribute to large-scale intraseasonal SST variability due to its small spatial scale and random phase relation to the active-break monsoon cycle. The effect of oceanic eddies; however, remains to be explored at a higher spatial resolution.

Dynamics of sediment carbon stocks across intertidal wetland habitats of Moreton Bay, Australia.

PubMed

Hayes, Matthew A; Jesse, Amber; Hawke, Bruce; Baldock, Jeff; Tabet, Basam; Lockington, David; Lovelock, Catherine E

2017-10-01

Coastal wetlands are known for high carbon storage within their sediments, but our understanding of the variation in carbon storage among intertidal habitats, particularly over geomorphological settings and along elevation gradients, is limited. Here, we collected 352 cores from 18 sites across Moreton Bay, Australia. We assessed variation in sediment organic carbon (OC) stocks among different geomorphological settings (wetlands within riverine settings along with those with reduced riverine influence located on tide-dominated sand islands), across elevation gradients, with distance from shore and among habitat and vegetation types. We used mid-infrared (MIR) spectroscopy combined with analytical data and partial least squares regression to quantify the carbon content of ~2500 sediment samples and provide fine-scale spatial coverage of sediment OC stocks to 150 cm depth. We found sites in river deltas had larger OC stocks (175-504 Mg/ha) than those in nonriverine settings (44-271 Mg/ha). Variation in OC stocks among nonriverine sites was high in comparison with riverine and mixed geomorphic settings, with sites closer to riverine outflow from the east and south of Moreton Bay having higher stocks than those located on the sand islands in the northwest of the bay. Sediment OC stocks increased with elevation within nonriverine settings, but not in riverine geomorphic settings. Sediment OC stocks did not differ between mangrove and saltmarsh habitats. OC stocks did, however, differ between dominant species across the research area and within geomorphic settings. At the landscape scale, the coastal wetlands of the South East Queensland catchments (17,792 ha) are comprised of approximately 4,100,000-5,200,000 Mg of sediment OC. Comparatively high variation in OC storage between riverine and nonriverine geomorphic settings indicates that the availability of mineral sediments and terrestrial derived OC may exert a strong influence over OC storage potential across intertidal wetland systems. © 2017 John Wiley & Sons Ltd.

Temporal variation of persistent organic pollutant (POP) residue concentrations in sediments from the bay of Chetumal, Mexico.

PubMed

Noreña-Barroso, E; Gold-Bouchot, G; Ceja-Moreno, V

2007-08-01

Bay of Chetumal is a transboundary priority area for the Mesoamerican Barrier Reef Systems project, which has been studied because it is the receiving body of pollutants from a large agricultural area and the city of Chetumal. Levels of persistent organic pollutants in sediments from the Bay were assessed a few years after a mass mortality event of Mayan catfish (Ariopsis assimilis) occurred in 1996. Recent sediments were collected in the rainy season (1999) and dry season (2000); results show concentrations in general lower than those reported after the fish kill, and a change of chemical profiles in chemical pollution.

THREE YEAR VARIATION IN SHELL GROWTH OF THEMUSSEL, ELLIPTIO WACCAMAWENSIS (LEA), IN LAKEWACCAMAW, A BAY LAKE IN NORTH CAROLINA

EPA Science Inventory

Freshwater mussels (Bivalvia: Unionidae) are one of the most endangered animal taxa in North America, and continued research on unionids will improve management decisions regarding their conservation. One unexplored aspect of unionid ecology is the magnitude of interannual variat...

Seasonal sedimentary processes of the macrotidal flat in Gomso Bay, west coast of Korea

NASA Astrophysics Data System (ADS)

Woo, H.; Kang, J.; Choi, J.

2012-12-01

The tidal flats on the west coast of Korea have broad zones with gentle slopes and a macrotidal setting with 4 to 10 meters of tidal ranges. They are directly influenced by monsoons and heavily affected by waves in winter and tidal currents in summer. As a result, most western tidal flats show the seasonal changes of sedimentary features comprising sedimentation and/or erosion of sediments. Gomso bay in the mid-west of Korea is a funnel-shaped embayment with a wide entrance to the west. Tides are semidiurnal and macrotidal, with a mean tidal range of 433.8 cm. Digital elevation model (DEM) showed that the landward inner bay had mainly high elevations and the seaward outer bay had relatively low elevations. In particular, there are considerable gradients in the outer bay from area of high-water line to area of low-water line. The sedimentary analysis and monitoring short-term sedimentation rates were investigated to understand seasonal sedimentary processes of tidal flats in Gomso bay. The surface sediments in the bay were classified into five sedimentary facies in spring 2011. Generally, sandy sediments were dominated in the outer bay, whereas sandy mud sediments were distributed on the inner bay. The middle bay mainly consisted of muddy sand sediments. The percentages of sand decreased from outer to inner bay. The short-term sedimentation rates were obtained from three lines by burying a plate at sub-bottom depth and periodically measuring the changing sediment depth from February 2011 to February 2012. In the tidal flat at inner bay (KB- Line), the annual sedimentation rates were ranged -8.87 to 74.69 mm/year with the net deposition rate of 40.90 mm/year. The deposition occurred on KB-Line in spring, autumn and winter. The erosion was dominated on the tidal flats at middle (KH-Line) and outer bay (KM-Line) during autumn and winter with an annual erosion rate of -29.86 mm/year and -9.92 mm/year, respectively. The seasonal variations of sedimentation on these tidal flats showed that the deposition occurred with an inflow of muddy sediments in summer, whereas the erosion was dominated in autumn and winter. In August 2011, the distribution patterns of rare earth elements (REEs) relative to the upper continental crust (UCC) showed the enrichment of light REEs (LREEs: La-Nd), together with an apparent depletion of Eu in the KH- and KM-Lines. This pattern was more pronounced in the middle bay sediments (KH-Line) due to influence of muddy sediment transport from Jujin Stream during the rainy period (July and August). On the other hand, the outer bay sediments in the KM-Line were reflected more inflow of second sediment source, the Geum River. The major control factors for seasonal variations of sediments on the tidal flat could be heavy rainfall and tidal currents during summer and strong waves during winter. The net sedimentation showed that the deposition occurred in the inner tidal flat and erosion occurred in the middle and outer tidal flat of the bay.

Validation of MODIS FLH and In Situ Chlorophyll a from Tampa Bay, Florida (USA)

NASA Technical Reports Server (NTRS)

Fischer, Andrew; MorenoMadrinan, Max J.

2012-01-01

Satellite observation of phytoplankton concentration or chlorophyll-a (chla) is an important characteristic, critically integral to monitoring coastal water quality. However, the optical properties of estuarine and coastal waters are highly variable and complex and pose a great challenge for accurate analysis. Constituents such as suspended solids and dissolved organic matter and the overlapping and uncorrelated absorptions in the blue region of the spectrum renders the blue-green ratio algorithms for estimating chl-a inaccurate. Measurement of suninduced chlorophyll fluorescence, on the other hand, which utilizes the near infrared portion of the electromagnetic spectrum may, provide a better estimate of phytoplankton concentrations. While modelling and laboratory studies have illustrated both the utility and limitations of satellite algorithms based on the sun induced chlorophyll fluorescence signal, few have examined the empirical validity of these algorithms or compared their accuracy against bluegreen ratio algorithms . In an unprecedented analysis using a long term (2003-2011) in situ monitoring data set from Tampa Bay, Florida (USA), we assess the validity of the FLH product from the Moderate Resolution Imaging Spectrometer against a suite of water quality parameters taken in a variety of conditions throughout this large optically complex estuarine system. . Overall, the results show a 106% increase in the validity of chla concentration estimation using FLH over the standard chla estimate from the blue-green OC3M algorithm. Additionally, a systematic analysis of sampling sites throughout the bay is undertaken to understand how the FLH product responds to varying conditions in the estuary and correlations are conducted to see how the relationships between satellite FLH and in situ chlorophyll-a change with depth, distance from shore, from structures like bridges, and nutrient concentrations and turbidity. Such analysis illustrates that the correlations between FLH and in situ chla measurements increases with increasing distance between monitoring sites and structures like bridges and shore. Due probably to confounding factors, expected improvement in the FLH- chla relationship was not clearly noted when increasing depth and distance from shore alone (not including bridges). Correlations between turbidity and nutrient concentrations are discussed further and principle component analyses are employed to address the relationships between the multivariate data sets. A thorough understanding of how satellite FLH algorithms relate to in situ water quality parameters will enhance our understanding of how MODIS s global FLH algorithm can be used empirically to monitor coastal waters worldwide.

Classification of patients by severity grades during triage in the emergency department using data mining methods.

PubMed

Zmiri, Dror; Shahar, Yuval; Taieb-Maimon, Meirav

2012-04-01

To test the feasibility of classifying emergency department patients into severity grades using data mining methods. Emergency department records of 402 patients were classified into five severity grades by two expert physicians. The Naïve Bayes and C4.5 algorithms were applied to produce classifiers from patient data into severity grades. The classifiers' results over several subsets of the data were compared with the physicians' assessments, with a random classifier, and with a classifier that selects the maximal-prevalence class. Positive predictive value, multiple-class extensions of sensitivity and specificity combinations, and entropy change. The mean accuracy of the data mining classifiers was 52.94 ± 5.89%, significantly better (P < 0.05) than the mean accuracy of a random classifier (34.60 ± 2.40%). The entropy of the input data sets was reduced through classification by a mean of 10.1%. Allowing for classification deviations of one severity grade led to mean accuracy of 85.42 ± 1.42%. The classifiers' accuracy in that case was similar to the physicians' consensus rate. Learning from consensus records led to better performance. Reducing the number of severity grades improved results in certain cases. The performance of the Naïve Bayes and C4.5 algorithms was similar; in unbalanced data sets, Naïve Bayes performed better. It is possible to produce a computerized classification model for the severity grade of triage patients, using data mining methods. Learning from patient records regarding which there is a consensus of several physicians is preferable to learning from each physician's patients. Either Naïve Bayes or C4.5 can be used; Naïve Bayes is preferable for unbalanced data sets. An ambiguity in the intermediate severity grades seems to hamper both the physicians' agreement and the classifiers' accuracy. © 2010 Blackwell Publishing Ltd.

Impact of respiratory-correlated CT sorting algorithms on the choice of margin definition for free-breathing lung radiotherapy treatments.

PubMed

Thengumpallil, Sheeba; Germond, Jean-François; Bourhis, Jean; Bochud, François; Moeckli, Raphaël

2016-06-01

To investigate the impact of Toshiba phase- and amplitude-sorting algorithms on the margin strategies for free-breathing lung radiotherapy treatments in the presence of breathing variations. 4D CT of a sphere inside a dynamic thorax phantom was acquired. The 4D CT was reconstructed according to the phase- and amplitude-sorting algorithms. The phantom was moved by reproducing amplitude, frequency, and a mix of amplitude and frequency variations. Artefact analysis was performed for Mid-Ventilation and ITV-based strategies on the images reconstructed by phase- and amplitude-sorting algorithms. The target volume deviation was assessed by comparing the target volume acquired during irregular motion to the volume acquired during regular motion. The amplitude-sorting algorithm shows reduced artefacts for only amplitude variations while the phase-sorting algorithm for only frequency variations. For amplitude and frequency variations, both algorithms perform similarly. Most of the artefacts are blurring and incomplete structures. We found larger artefacts and volume differences for the Mid-Ventilation with respect to the ITV strategy, resulting in a higher relative difference of the surface distortion value which ranges between maximum 14.6% and minimum 4.1%. The amplitude- is superior to the phase-sorting algorithm in the reduction of motion artefacts for amplitude variations while phase-sorting for frequency variations. A proper choice of 4D CT sorting algorithm is important in order to reduce motion artefacts, especially if Mid-Ventilation strategy is used. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Iterative Nonlocal Total Variation Regularization Method for Image Restoration

PubMed Central

Xu, Huanyu; Sun, Quansen; Luo, Nan; Cao, Guo; Xia, Deshen

2013-01-01

In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed. Experiment results show that the proposed algorithms outperform some other regularization methods. PMID:23776560

Strong correlation between stress drop and peak ground acceleration for recent M1–4 earthquakes in the San Francisco Bay Area

DOE PAGES

Trugman, Daniel Taylor; Shearer, Peter M.

2018-03-06

Theoretical and observational studies suggest that between-event variability in the median ground motions of larger ( M≥5 ) earthquakes is controlled primarily by the dynamic properties of the earthquake source, such as Brune-type stress drop. Analogous results remain equivocal for smaller events due to the lack of comprehensive and overlapping ground-motion and source-parameter datasets in this regime. Here in this paper, we investigate the relationship between peak ground acceleration (PGA) and dynamic stress drop for a new dataset of 5297 earthquakes that occurred in the San Francisco Bay area from 2002 through 2016. For each event, we measure PGA onmore » horizontal-component channels of stations within 100 km and estimate stress drop from P-wave spectra recorded on vertical-component channels of the same stations. We then develop a nonparametric ground-motion prediction equation (GMPE) applicable for the moderate (M 1–4) earthquakes in our study region, using a mixed-effects generalization of the Random Forest algorithm. We use the Random Forest GMPE to model the joint influence of magnitude, distance, and near-site effects on observed PGA. We observe a strong correlation between dynamic stress drop and the residual PGA of each event, with the events with higher-than-expected PGA associated with higher values of stress drop. The strength of this correlation increases as a function of magnitude but remains significant even for smaller magnitude events with corner frequencies that approach the observable bandwidth of the acceleration records. Mainshock events are characterized by systematically higher stress drop and PGA than aftershocks of equivalent magnitude. Coherent local variations in the distribution of dynamic stress drop provide observational constraints to support the future development of nonergodic GMPEs that account for variations in median stress drop at different source locations.« less

Strong correlation between stress drop and peak ground acceleration for recent M1–4 earthquakes in the San Francisco Bay Area

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trugman, Daniel Taylor; Shearer, Peter M.

Theoretical and observational studies suggest that between-event variability in the median ground motions of larger ( M≥5 ) earthquakes is controlled primarily by the dynamic properties of the earthquake source, such as Brune-type stress drop. Analogous results remain equivocal for smaller events due to the lack of comprehensive and overlapping ground-motion and source-parameter datasets in this regime. Here in this paper, we investigate the relationship between peak ground acceleration (PGA) and dynamic stress drop for a new dataset of 5297 earthquakes that occurred in the San Francisco Bay area from 2002 through 2016. For each event, we measure PGA onmore » horizontal-component channels of stations within 100 km and estimate stress drop from P-wave spectra recorded on vertical-component channels of the same stations. We then develop a nonparametric ground-motion prediction equation (GMPE) applicable for the moderate (M 1–4) earthquakes in our study region, using a mixed-effects generalization of the Random Forest algorithm. We use the Random Forest GMPE to model the joint influence of magnitude, distance, and near-site effects on observed PGA. We observe a strong correlation between dynamic stress drop and the residual PGA of each event, with the events with higher-than-expected PGA associated with higher values of stress drop. The strength of this correlation increases as a function of magnitude but remains significant even for smaller magnitude events with corner frequencies that approach the observable bandwidth of the acceleration records. Mainshock events are characterized by systematically higher stress drop and PGA than aftershocks of equivalent magnitude. Coherent local variations in the distribution of dynamic stress drop provide observational constraints to support the future development of nonergodic GMPEs that account for variations in median stress drop at different source locations.« less

The Blessing and the Curse of the Multiplicative Updates

NASA Astrophysics Data System (ADS)

Warmuth, Manfred K.

Multiplicative updates multiply the parameters by nonnegative factors. These updates are motivated by a Maximum Entropy Principle and they are prevalent in evolutionary processes where the parameters are for example concentrations of species and the factors are survival rates. The simplest such update is Bayes rule and we give an in vitro selection algorithm for RNA strands that implements this rule in the test tube where each RNA strand represents a different model. In one liter of the RNA "soup" there are approximately 1020 different strands and therefore this is a rather high-dimensional implementation of Bayes rule.

Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

NASA Astrophysics Data System (ADS)

Wang, Leilei; Cheng, Jinyong

2018-03-01

Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

Geomorphic change in Dingzi Bay, East China since the 1950s: impacts of human activity and fluvial input

NASA Astrophysics Data System (ADS)

Tian, Qing; Wang, Qing; Liu, Yalong

2017-06-01

This study examines the geomorphic evolution of Dingzi Bay, East China in response to human activity and variations in fluvial input since the 1950s. The analysis is based on data from multiple mathematical methods, along with information obtained from Remote Sensing, Geographic Information System and Global Position System technology. The results show that the annual runoff and sediment load discharged into Dingzi Bay display significant decreasing trends overall, and marked downward steps were observed in 1966 and 1980. Around 60%-80% of the decline is attributed to decreasing precipitation in the Wulong River Basin. The landform types in Dingzi Bay have changed significantly since the 1950s, especially over the period between 1981 and 1995. Large areas of tidal flats, swamp, salt fields, and paddy fields have been reclaimed, and aquaculture ponds have been constructed. Consequently, the patterns of erosion and deposition in the bay have changed substantially. Despite a reduction in sediment input of 65.68% after 1966, low rates of sediment deposition continued in the bay. However, deposition rates changed significantly after 1981 owing to large-scale development in the bay, with a net depositional area approximately 10 times larger than that during 1961-1981. This geomorphic evolution stabilized following the termination of large-scale human activity in the bay after 1995. Overall, Dingzi Bay has shown a tendency towards silting-up during 1952-2010, with the bay head migrating seaward, the number of channels in the tidal creek system decreasing, and the tidal inlet becoming narrower and shorter. In conclusion, largescale development and human activity in Dingzi Bay have controlled the geomorphic evolution of the bay since the 1950s.

Spatial variation of phytoplankton community structure in Daya Bay, China.

PubMed

Jiang, Zhao-Yu; Wang, You-Shao; Cheng, Hao; Zhang, Jian-Dong; Fei, Jiao

2015-10-01

Daya Bay is one of the largest and most important gulfs in the southern coast of China, in the northern part of the South China Sea. The phylogenetic diversity and spatial distribution of phytoplankton from the Daya Bay surface water and the relationship with the in situ water environment were investigated by the clone library of the large subunit of ribulose-1, 5-bisphosphate carboxylase (rbcL) gene. The dominant species of phytoplankton were diatoms and eustigmatophytes, which accounted for 81.9 % of all the clones of the rbcL genes. Prymnesiophytes were widely spread and wide varieties lived in Daya Bay, whereas the quantity was limited. The community structure of phytoplankton was shaped by pH and salinity and the concentration of silicate, phosphorus and nitrite. The phytoplankton biomass was significantly positively affected by phosphorus and nitrite but negatively by salinity and pH. Therefore, the phytoplankton distribution and biomass from Daya Bay were doubly affected by anthropic activities and natural factors.

Seagrass morphometrics at species level in Moreton Bay, Australia from 2012 to 2013.

PubMed

Samper-Villarreal, Jimena; Roelfsema, Chris; Kovacs, Eva M; Adi, Novi S; Lyons, Mitchell; Mumby, Peter J; Lovelock, Catherine E; Saunders, Megan I; Phinn, Stuart R

2017-05-09

Seagrass above, below and total biomass, density and leaf area, length and width were quantified at a species level for 122 sites over three sampling periods in Moreton Bay, Australia. Core samples were collected in two regions: (1) a high water quality region with varying species assemblages and canopy complexity (98 sites); and (2) along a turbidity gradient in the bay (24 sites within four locations). Core samples were collected using a 15 cm diameter×20 cm long corer. Seagrass dry biomass per component was quantified per species present in each sample. A total of 220 biomass and density data records are included, 130 from the high water quality region and 90 from the turbidity gradient. These data provide a detailed assessment of biomass, density and leaf metrics per species sampled from Moreton Bay over 2012-2013. In future, these can be used as a baseline to assess seasonal and spatial variation within the bay, within the region and among regions.

Seagrass morphometrics at species level in Moreton Bay, Australia from 2012 to 2013

PubMed Central

Samper-Villarreal, Jimena; Roelfsema, Chris; Kovacs, Eva M.; Adi, Novi S.; Lyons, Mitchell; Mumby, Peter J.; Lovelock, Catherine E.; Saunders, Megan I.; Phinn, Stuart R.

2017-01-01

Seagrass above, below and total biomass, density and leaf area, length and width were quantified at a species level for 122 sites over three sampling periods in Moreton Bay, Australia. Core samples were collected in two regions: (1) a high water quality region with varying species assemblages and canopy complexity (98 sites); and (2) along a turbidity gradient in the bay (24 sites within four locations). Core samples were collected using a 15 cm diameter×20 cm long corer. Seagrass dry biomass per component was quantified per species present in each sample. A total of 220 biomass and density data records are included, 130 from the high water quality region and 90 from the turbidity gradient. These data provide a detailed assessment of biomass, density and leaf metrics per species sampled from Moreton Bay over 2012–2013. In future, these can be used as a baseline to assess seasonal and spatial variation within the bay, within the region and among regions. PMID:28485717

Evaluation of phytoplankton community composition in the eutrophic Masan Bay by HPLC pigment analysis.

PubMed

Kim, Jeong Bae; Hong, Sokjin; Lee, Won-Chan; Lee, Yong-Woo; Kim, Hyung Chul; Cho, Yoonsik

2015-03-01

To assess the spatiotemporal changes in phytoplankton community composition in relation to the environment of Masan Bay, a semi-enclosed bay on the southern coast of Korea, photosynthetic pigments and environmental variables were analyzed in seawater, every month between March and November 2010. The level of dissolved inorganic nutrients was highest between July and September when the freshwater influx was at its peak, whereas chlorophyll a level was highest in April and August. Phosphate concentration was low in April (average: 0.22 +/- 0.17 microM), indicating the role of phosphate as a growth-limiting factor for phytoplankton. The results of pigment analysis indicate that dinoflagellate blooms occurred under favorable conditions, where competition with diatoms occurred. Fucoxanthin- and chlorophyll b-containing phytoplankton dominated the surface layer of Masan Bay from July to September. The composition of phytoplankton community in Masan Bay changed dramatically each month according to variations in the amount and composition of nutrients introduced through surface runoff.

Challenges in Ocean Data Assimilation for the US West Coast

NASA Astrophysics Data System (ADS)

Li, Z.; Chao, Y.; Farrara, J.; Wang, X.

2006-12-01

A three-dimensional variational data assimilation (3DVAR) system has been developed for the Regional Ocean Modeling System (ROMS), and it is called ROMS-DAS. This system provides a capability of predicting meso- to small-scale variations with temporal scales from hours to days in the coastal oceans. To cope with the particular difficulties that result from complex coastlines and bottom topography, unbalanced flows and sparse observations, ROMS-DAS utilizes several novel strategies. These strategies include the implementation of three-dimensional anisotropic and inhomogeneous error correlations, application of particular weak dynamic constraints, and implementation of efficient and reliable algorithms for minimizing the cost function. The ROMS-DAS system was applied in field experiments for Monterey Bay during both 2003 (Autonomous Ocean Sampling Network - AOSN) and 2006 (MB06). These two experiments included intensive data collection from a variety of observational platforms, including satellites, airplanes, High Frequency radars, Acoustic Doppler Current Profilers, ships, drifters, buoys, autonomous underwater vehicles (AUV), and particularly a fleet of undersea gliders. Using these data sets, various data assimilation experiments were performed to address several major data assimilation challenges that arise from multi-scales structures, inhomogeneous properties, dynamical imbalance of the flow, and tides. Basing on these experiments, a set of strategies were formulated to deal with those challenges.

Time scales and mechanisms of estuarine variability, a synthesis from studies of San Francisco Bay

USGS Publications Warehouse

Cloern, J.E.; Nichols, F.H.

1985-01-01

This review of the preceding papers suggests that temporal variability in San Francisco Bay can be characterized by four time scales (hours, days-weeks, months, years) and associated with at least four mechanisms (variations in freshwater inflow, tides, wind, and exchange with coastal waters). The best understood component of temporal variability is the annual cycle, which is most obviously influenced by seasonal variations in freshwater inflow. The winter season of high river discharge is characterized by: large-scale redistribution of the salinity field (e.g. the upper estuary becomes a riverine system); enhanced density stratification and gravitational circulation with shortened residence times in the bay; decreased tissue concentrations of some contaminants (e.g. copper) in resident bivalves; increased estuarine inputs of river-borne materials such as dissolved inorganic nutrients (N, P, Si), suspended sediments, and humic materials; radical redistributions of pelagic organisms such as copepods and fish; low phutoplankton biomass and primary productivity in the upper estuary; and elimination of freshwater-intolerant species of macroalgae and benthic infauna from the upper estuary. Other mechanisms modulate this river-driven annual cycle: (1) wind speed is highly seasonal (strongest in summer) and causes seasonal variations in atmosphere-water column exchange of dissolved gases, resuspension, and the texture of surficial sediments; (2) seasonal variations in the coastal ocean (e.g. the spring-summer upwelling season) influence species composition of plankton and nutrient concentrations that are advected into the bay; and (3) the annual temperature cycle influences a few selected features (e.g. production and hatching of copepod resting eggs). Much of the interannual variability in San Francisco Bay is also correlated with freshwater inflow: wet years with persistently high river discharge are characterized by persistent winter-type conditions. Mechanisms of short-term variability are not as well understood, although some responses to storm events (pulses in residual currents from wind forcing, erosion of surficial sediments by wind waves, redistribution of fish populations) and the neap-spring tidal cycle (enhanced salinity stratification, gravitational circulation, and phytoplankton biomass during neap tides) have been quantified. In addition to these somewhat predictable features of variability are (1) largely unexplained episodic events (e.g. anomalous blooms of drift macroalgae), and (2) long-term trends directly attributable to human activities (e.g. introduction of exotic species that become permanent members of the biota). ?? 1985 Dr W. Junk Publishers.

Environmental influences on potential recruitment of pink shrimp, Fatlantopenaeus duorarum, from Florida Bay nursery grounds

USGS Publications Warehouse

Browder, Joan A.; Restrepo, V.R.; Rice, J.K.; Robblee, M.B.; Zein-Eldin, Z.

1999-01-01

Two modeling approaches were used to explore the basis for variation in recruitment of pink shrimp, Farfantepenaeus duorarum, to the Tortugas fishing grounds. Emphasis was on development and juvenile densities on the nursery grounds. An exploratory simulation modeling exercise demonstrated large year-to-year variations in recruitment contributions to the Tortugas rink shrimp fishery may occur on some nursery grounds, and production may differ considerably among nursery grounds within the same year, simply on the basis of differences in temperature and salinity. We used a growth and survival model to simulate cumulative harvests from a July-centered cohort of early-settlement-stage postlarvae from two parts of Florida Bay (western Florida Bay and northcentral Florida Bay), using historic temperature and salinity data from these areas. Very large year-to-year differences in simulated cumulative harvests were found for recruits from Whipray Basin. Year-to-year differences in simulated harvests of recruits from Johnson Key Basin were much smaller. In a complementary activity, generalized linear and additive models and intermittent, historic density records were used to develop an uninterrupted multi-year time series of monthly density estimates for juvenile rink shrimp in the Johnson Key Basin. The developed data series was based on relationships of density with environmental variables. The strongest relationship was with sea-surface temperature. Three other environmental variables (rainfall, water level at Everglades National Park Well P35, and mean wind speed) also contributed significantly to explaining variation in juvenile densities. Results of the simulation model and two of the three statistical models yielded similar interannual patterns for Johnson Key Basin. While it is not possible to say that one result validates the other, the concordance of the annual patterns from the two models is supportive of both approaches.

Toward automated face detection in thermal and polarimetric thermal imagery

NASA Astrophysics Data System (ADS)

Gordon, Christopher; Acosta, Mark; Short, Nathan; Hu, Shuowen; Chan, Alex L.

2016-05-01

Visible spectrum face detection algorithms perform pretty reliably under controlled lighting conditions. However, variations in illumination and application of cosmetics can distort the features used by common face detectors, thereby degrade their detection performance. Thermal and polarimetric thermal facial imaging are relatively invariant to illumination and robust to the application of makeup, due to their measurement of emitted radiation instead of reflected light signals. The objective of this work is to evaluate a government off-the-shelf wavelet based naïve-Bayes face detection algorithm and a commercial off-the-shelf Viola-Jones cascade face detection algorithm on face imagery acquired in different spectral bands. New classifiers were trained using the Viola-Jones cascade object detection framework with preprocessed facial imagery. Preprocessing using Difference of Gaussians (DoG) filtering reduces the modality gap between facial signatures across the different spectral bands, thus enabling more correlated histogram of oriented gradients (HOG) features to be extracted from the preprocessed thermal and visible face images. Since the availability of training data is much more limited in the thermal spectrum than in the visible spectrum, it is not feasible to train a robust multi-modal face detector using thermal imagery alone. A large training dataset was constituted with DoG filtered visible and thermal imagery, which was subsequently used to generate a custom trained Viola-Jones detector. A 40% increase in face detection rate was achieved on a testing dataset, as compared to the performance of a pre-trained/baseline face detector. Insights gained in this research are valuable in the development of more robust multi-modal face detectors.

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis

NASA Astrophysics Data System (ADS)

Chaudhury, Baishali; Hall, Lawrence O.; Goldgof, Dmitry B.; Gatenby, Robert A.; Gillies, Robert; Drukteinis, Jennifer S.

2014-03-01

Magnetic Resonance Imaging (MRI) of breast cancer typically shows that tumors are heterogeneous with spatial variations in blood flow and cell density. Here, we examine the potential link between clinical tumor imaging and the underlying evolutionary dynamics behind heterogeneity in the cellular expression of estrogen receptors (ER) in breast cancer. We assume, in an evolutionary environment, that ER expression will only occur in the presence of significant concentrations of estrogen, which is delivered via the blood stream. Thus, we hypothesize, the expression of ER in breast cancer cells will correlate with blood flow on gadolinium enhanced breast MRI. To test this hypothesis, we performed quantitative analysis of blood flow on dynamic contrast enhanced MRI (DCE-MRI) and correlated it with the ER status of the tumor. Here we present our analytic methods, which utilize a novel algorithm to analyze 20 volumetric DCE-MRI breast cancer tumors. The algorithm generates post initial enhancement (PIE) maps from DCE-MRI and then performs texture features extraction from the PIE map, feature selection, and finally classification of tumors into ER positive and ER negative status. The combined gray level co-occurrence matrices, gray level run length matrices and local binary pattern histogram features allow quantification of breast tumor heterogeneity. The algorithm predicted ER expression with an accuracy of 85% using a Naive Bayes classifier in leave-one-out cross-validation. Hence, we conclude that our data supports the hypothesis that imaging characteristics can, through application of evolutionary principles, provide insights into the cellular and molecular properties of cancer cells.

Software for Data Analysis with Graphical Models

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Roy, H. Scott

1994-01-01

Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

TEMPORAL AND SPATIAL VARIATION IN PLASMA THYROXINE (T4) CONCENTRATIONS IN JUVENILE ALLIGATORS COLLECTED FROM LAKE OKEECHOBEE AND THE NORTHERN EVERGLADES, FLORIDA, USA

EPA Science Inventory

We examined variation in plasma thyroxine (T4) in juvenile American alligators (Alligator mississippiensis) collected from three sites within the Kissimmee River drainage basin (FL, USA). Based on historical sediment data, Moonshine Bay served as the low contaminant exposure site...

A MAD-Bayes Algorithm for State-Space Inference and Clustering with Application to Querying Large Collections of ChIP-Seq Data Sets.

PubMed

Zuo, Chandler; Chen, Kailei; Keleş, Sündüz

2017-06-01

Current analytic approaches for querying large collections of chromatin immunoprecipitation followed by sequencing (ChIP-seq) data from multiple cell types rely on individual analysis of each data set (i.e., peak calling) independently. This approach discards the fact that functional elements are frequently shared among related cell types and leads to overestimation of the extent of divergence between different ChIP-seq samples. Methods geared toward multisample investigations have limited applicability in settings that aim to integrate 100s to 1000s of ChIP-seq data sets for query loci (e.g., thousands of genomic loci with a specific binding site). Recently, Zuo et al. developed a hierarchical framework for state-space matrix inference and clustering, named MBASIC, to enable joint analysis of user-specified loci across multiple ChIP-seq data sets. Although this versatile framework estimates both the underlying state-space (e.g., bound vs. unbound) and also groups loci with similar patterns together, its Expectation-Maximization-based estimation structure hinders its applicability with large number of loci and samples. We address this limitation by developing MAP-based asymptotic derivations from Bayes (MAD-Bayes) framework for MBASIC. This results in a K-means-like optimization algorithm that converges rapidly and hence enables exploring multiple initialization schemes and flexibility in tuning. Comparison with MBASIC indicates that this speed comes at a relatively insignificant loss in estimation accuracy. Although MAD-Bayes MBASIC is specifically designed for the analysis of user-specified loci, it is able to capture overall patterns of histone marks from multiple ChIP-seq data sets similar to those identified by genome-wide segmentation methods such as ChromHMM and Spectacle.

Human activity recognition based on feature selection in smart home using back-propagation algorithm.

PubMed

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Seasonal and annual trends in forage fish mercury concentrations, San Francisco Bay.

PubMed

Greenfield, Ben K; Melwani, Aroon R; Allen, Rachel M; Slotton, Darell G; Ayers, Shaun M; Harrold, Katherine H; Ridolfi, Katherine; Jahn, Andrew; Grenier, J Letitia; Sandheinrich, Mark B

2013-02-01

San Francisco Bay is contaminated by mercury (Hg) due to historic and ongoing sources, and has elevated Hg concentrations throughout the aquatic food web. We monitored Hg in forage fish to indicate seasonal and interannual variations and trends. Interannual variation and long-term trends were determined by monitoring Hg bioaccumulation during September-November, for topsmelt (Atherinops affinis) and Mississippi silverside (Menidia audens) at six sites, over six years (2005 to 2010). Seasonal variation was characterized for arrow goby (Clevelandia ios) at one site, topsmelt at six sites, and Mississippi silverside at nine sites. Arrow goby exhibited a consistent seasonal pattern from 2008 to 2010, with lowest concentrations observed in late spring, and highest concentrations in late summer or early fall. In contrast, topsmelt concentrations tended to peak in late winter or early spring and silverside seasonal fluctuations varied among sites. The seasonal patterns may relate to seasonal shifts in net MeHg production in the contrasting habitats of the species. Topsmelt exhibited an increase in Alviso Slough from 2005 to 2010, possibly related to recent hypoxia in that site. Otherwise, directional trends for Hg in forage fish were not observed. For topsmelt and silverside, the variability explained by year was relatively low compared to sampling station, suggesting that interannual variation is not a strong influence on Hg concentrations. Although fish Hg has shown long-term declines in some ecosystems around the world, San Francisco Bay forage fish did not decline over the six-year monitoring period examined. Copyright © 2012 Elsevier B.V. All rights reserved.

Refining Our Understanding of Howiesons Poort Lithic Technology: The Evidence from Grey Rocky Layer in Sibudu Cave (KwaZulu-Natal, South Africa)

PubMed Central

de la Peña, Paloma

2015-01-01

The detailed technological analysis of the youngest Howiesons Poort occupation in Sibudu Cave, layer Grey Rocky, has shown the importance of blade production (with different knapping methods involved), but also of flaking methods in coarse grained rock types. Moreover, new strategies of bifacial production and microlithism were important. Grey Rocky lithic technology shows a really versatile example of reduction strategies that were highly influenced by the characteristics of the rock types. This lithic assemblage is another example of the technological variability linked to the Howiesons Poort technocomplex. The reasons for this variability are still difficult to elucidate. Discrepancies between sites might be for different reasons: diachronic variations, functional variations, organizational variations or maybe different regional variations within what has been recognized traditionally and typologically as Howiesons Poort. The technological comparison of the Grey Rocky assemblage with assemblages from other Howiesons Poort sites demonstrates that there are common technological trends during the late Pleistocene, but they still need to be properly circumscribed chronologically. On the one hand, Howiesons Poort characteristics such as the bifacial production in quartz are reminiscent of production in some Still Bay or pre-Still Bay industries and the flake production or the prismatic blade production described here could be a point in common with pre-Still Bay and post-Howiesons Poort industries. On the other hand, the detailed analysis of the Grey Rocky lithics reinforces the particular character of this Howiesons Poort technocomplex, yet it also shows clear technological links with other Middle Stone Age assemblages. PMID:26633008

Distribution of the Euryhaline Squid Lolliguncula brevis in Chesapeake Bay: Effects of Selected Abiotic Factors

DTIC Science & Technology

2002-01-31

salinity , water temperature, dissolved oxy- gen and water clarity. Since temporal variation in the Chesapeake Bay ecosystem is high, the effects of year...temperature (p ɘ.001; ψ = 2.42) had significant impacts on squid catch probability, although the effects were con- founded by a water temperature × salinity ...commonly encountered in such waters during VIMS Trawl Surveys The synergistic and independent effects of salinity , water temperature and dissolved oxygen

CHLOROPHYLL A DISTRIBUTION IN NARRAGANSETT BAY, RI: USING A SPECTRAL CURVATURE ALGORITHM

EPA Science Inventory

Chlorophyll a, a primary indicator of eutrophication in estuarine waters, varies enough in time and space to create spatial problems when monitored by satellite, and temporal problems when measured with in situ field programs. Using aircraft to sense ocean color of local waters, ...

Auto-Relevancy Baseline: A Hybrid System Without Human Feedback

DTIC Science & Technology

2010-11-01

classical Bayes algorithm upon the pseudo-hybridization of SemanticA and Latent Semantic IndexingBC systems should smooth out historically high yet...black box emulated a machine learning topic expert. Similar to some Web methods, the initial topics within the legal document were expanded upon

Seasonal Sea-Level Variations in San Francisco Bay in Response to Atmospheric Forcing, 1980

USGS Publications Warehouse

Wang, Jingyuan; Cheng, R.T.; Smith, P.C.

1997-01-01

The seasonal response of sea level in San Francisco Bay (SFB) to atmospheric forcing during 1980 is investigated. The relations between sea-level data from the Northern Reach, Central Bay and South Bay, and forcing by local wind stresses, sea level pressure (SLP), runoff and the large scale sea level pressure field are examined in detail. The analyses show that the sea-level elevations and slopes respond to the along-shore wind stress T(V) at most times of the year, and to the cross-shore wind stress T(N) during two transition periods in spring and autumn. River runoff raises the sea-level elevation during winter. It is shown that winter precipitation in the SFB area is mainly attributed to the atmospheric circulation associated with the Alcutian Low, which transports the warm, moist air into the Bay area. A multiple linear regression model is employed to estimate the independent contributions of barometric pressure and wind stress to adjusted sea level. These calculations have a simple dynamical interpretation which confirms the importance of along-shore wind to both sea level and north-south slope within the Bay.

Alternative models of climatic effects on sockeye salmon (Oncorhynchus nerka) productivity in Bristol Bay, Alaska, and the Fraser River, British Columbia

USGS Publications Warehouse

Adkison, M.; Peterman, R.; Lapointe, M.; Gillis, D.; Korman, J.

1996-01-01

We compare alternative models of sockeye salmon (Oncorhynchus nerka) productivity (returns per spawner) using more than 30 years of catch and escapement data for Bristol Bay, Alaska, and the Fraser River, British Columbia. The models examined include several alternative forms of models that incorporate climatic influences as well as models not based on climate. For most stocks, a stationary stock-recruitment relationship explains very little of the interannual variation in productivity. In Bristol Bay, productivity co-varies among stocks and appears to be strongly related to fluctuations in climate. The best model for Bristol Bay sockeye involved a change in the 1970s in the parameters of the Ricker stock-recruitment curve; the stocks generally became more productive. In contrast, none of the models of Fraser River stocks that we examined explained much of the variability in their productivity.

Textual and visual content-based anti-phishing: a Bayesian approach.

PubMed

Zhang, Haijun; Liu, Gang; Chow, Tommy W S; Liu, Wenyin

2011-10-01

A novel framework using a Bayesian approach for content-based phishing web page detection is presented. Our model takes into account textual and visual contents to measure the similarity between the protected web page and suspicious web pages. A text classifier, an image classifier, and an algorithm fusing the results from classifiers are introduced. An outstanding feature of this paper is the exploration of a Bayesian model to estimate the matching threshold. This is required in the classifier for determining the class of the web page and identifying whether the web page is phishing or not. In the text classifier, the naive Bayes rule is used to calculate the probability that a web page is phishing. In the image classifier, the earth mover's distance is employed to measure the visual similarity, and our Bayesian model is designed to determine the threshold. In the data fusion algorithm, the Bayes theory is used to synthesize the classification results from textual and visual content. The effectiveness of our proposed approach was examined in a large-scale dataset collected from real phishing cases. Experimental results demonstrated that the text classifier and the image classifier we designed deliver promising results, the fusion algorithm outperforms either of the individual classifiers, and our model can be adapted to different phishing cases. © 2011 IEEE

Bay of Fundy verification of a system for multidate Landsat measurement of suspended sediment

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.; Afoldi, T. T.; Amos, C. L.

1981-01-01

A system for automated multidate Landsat CCT MSS measurement of suspended sediment concentration (S) has been implemented and verified on nine sets (108 points) of data from the Bay of Fundy, Canada. The system employs 'chromaticity analysis' to provide automatic pixel-by-pixel adjustment of atmospheric variations, permitting reference calibration data from one or several dates to be spatially and temporally extrapolated to other regions and to other dates. For verification, each data set was used in turn as test data against the remainder as a calibration set: the average absolute error was 44 percent of S over the range 1-1000 mg/l. The system can be used to measure chlorophyll (in the absence of atmospheric variations), Secchi disk depth, and turbidity.

A Tidally Averaged Sediment-Transport Model for San Francisco Bay, California

USGS Publications Warehouse

Lionberger, Megan A.; Schoellhamer, David H.

2009-01-01

A tidally averaged sediment-transport model of San Francisco Bay was incorporated into a tidally averaged salinity box model previously developed and calibrated using salinity, a conservative tracer (Uncles and Peterson, 1995; Knowles, 1996). The Bay is represented in the model by 50 segments composed of two layers: one representing the channel (>5-meter depth) and the other the shallows (0- to 5-meter depth). Calculations are made using a daily time step and simulations can be made on the decadal time scale. The sediment-transport model includes an erosion-deposition algorithm, a bed-sediment algorithm, and sediment boundary conditions. Erosion and deposition of bed sediments are calculated explicitly, and suspended sediment is transported by implicitly solving the advection-dispersion equation. The bed-sediment model simulates the increase in bed strength with depth, owing to consolidation of fine sediments that make up San Francisco Bay mud. The model is calibrated to either net sedimentation calculated from bathymetric-change data or measured suspended-sediment concentration. Specified boundary conditions are the tributary fluxes of suspended sediment and suspended-sediment concentration in the Pacific Ocean. Results of model calibration and validation show that the model simulates the trends in suspended-sediment concentration associated with tidal fluctuations, residual velocity, and wind stress well, although the spring neap tidal suspended-sediment concentration variability was consistently underestimated. Model validation also showed poor simulation of seasonal sediment pulses from the Sacramento-San Joaquin River Delta at Point San Pablo because the pulses enter the Bay over only a few days and the fate of the pulses is determined by intra-tidal deposition and resuspension that are not included in this tidally averaged model. The model was calibrated to net-basin sedimentation to calculate budgets of sediment and sediment-associated contaminants. While simulated net sedimentation in the four basins that comprise San Francisco Bay was correct, the simulations incorrectly eroded shallows while channels deposited because model surface-layer boxes span both shallows and channels, and neglect lateral variability of suspended-sediment concentration. Validation with recent (1983-2005) net sedimentation in South San Francisco Bay was poor, perhaps owing to poorly quantified sediment supply, and to invasive species that altered erosion and deposition processes. This demonstrates that deterministically predicting future sedimentation is difficult in this or any estuary for which boundary conditions are not stationary. The model would best be used as a tool for developing past and present sediment budgets, and for creating scenarios of future sedimentation that are compared to one another rather than considered a deterministic prediction.

Oceanography of Glacier Bay, Alaska: Implications for biological patterns in a glacial fjord estuary

USGS Publications Warehouse

Etherington, L.L.; Hooge, P.N.; Hooge, Elizabeth Ross; Hill, D.F.

2007-01-01

Alaska, U.S.A, is one of the few remaining locations in the world that has fjords that contain temperate idewater glaciers. Studying such estuarine systems provides vital information on how deglaciation affects oceanographic onditions of fjords and surrounding coastal waters. The oceanographic system of Glacier Bay, Alaska, is of particular interest ue to the rapid deglaciation of the Bay and the resulting changes in the estuarine environment, the relatively high oncentrations of marine mammals, seabirds, fishes, and invertebrates, and the Bay’s status as a national park, where ommercial fisheries are being phased out. We describe the first comprehensive broad-scale analysis of physical and iological oceanographic conditions within Glacier Bay based on CTD measurements at 24 stations from 1993 to 2002. easonal patterns of near-surface salinity, temperature, stratification, turbidity, and euphotic depth suggest that freshwater nput was highest in summer, emphasizing the critical role of glacier and snowmelt to this system. Strong and persistent tratification of surface waters driven by freshwater input occurred from spring through fall. After accounting for seasonal nd spatial variation, several of the external physical factors (i.e., air temperature, precipitation, day length) explained a large mount of variation in the physical properties of the surface waters. Spatial patterns of phytoplankton biomass varied hroughout the year and were related to stratification levels, euphotic depth, and day length. We observed hydrographic atterns indicative of strong competing forces influencing water column stability within Glacier Bay: high levels of freshwater ischarge promoted stratification in the upper fjord, while strong tidal currents over the Bay’s shallow entrance sill enhanced ertical mixing. Where these two processes met in the central deep basins there were optimal conditions of intermediate tratification, higher light levels, and potential nutrient renewal. These conditions were associated with high and sustained hlorophylla levels observed from spring through fall in these zones of the Bay and provide a framework for understanding he abundance patterns of higher trophic levels within this estuarine system.

What a difference a bay makes: natural variation in dietary resources mediates growth in a recently settled herbivorous fish

NASA Astrophysics Data System (ADS)

Priest, Mark A.; Halford, Andrew R.; Clements, Kendall D.; Douglas, Emily; Abellana, Sheena L.; McIlwain, Jennifer L.

2016-12-01

Processes acting during the early stages of coral reef fish life cycles have a disproportionate influence on their adult abundance and community structure. Higher growth rates, for example, confer a major fitness advantage in larval and juvenile fishes, with larger fish undergoing significantly less mortality. The role of dietary resources in the size-structuring process has not been well validated, especially at the early post-settlement phase, where competition and predation are seen as preeminent drivers of juvenile fish assemblage structure. Here, we report on a size differential of 10-20% between recently settled Siganus spinus rabbitfish recruits from different bays around the Pacific island of Guam. This difference was maintained across multiple recruitment events within and between years. After confirming the validity of our observations through otolith increment analysis, subsequent investigation into the drivers of this variation revealed significant differences in the structure of algal assemblages between bays, congruent with the observed differences in size of the recently settled fish. Gut analyses showed a greater presence of algal types with higher levels of nitrogen and phosphorus in the stomachs of fish from Tanguisson, the bay with the largest observed recruits. To ensure this mechanism was one of causation and not correlation, we conducted a fully factorial experiment in which S. spinus recruits sampled from different bays were reared on all combinations of algal diets representative of the different bays. Recruits on the `Tanguisson' diet grew faster than recruits on other diets, regardless of their origin. We propose that the greater availability of high-quality dietary resources at this location is likely conferring benefits that impact on the population-level dynamics of this species. The spatial and temporal extent of this process clearly implicates food as a limiting resource, capable of mediating fish population dynamics at multiple spatial scales and ontogenetic phases.

Searching Algorithm Using Bayesian Updates

ERIC Educational Resources Information Center

Caudle, Kyle

2010-01-01

In late October 1967, the USS Scorpion was lost at sea, somewhere between the Azores and Norfolk Virginia. Dr. Craven of the U.S. Navy's Special Projects Division is credited with using Bayesian Search Theory to locate the submarine. Bayesian Search Theory is a straightforward and interesting application of Bayes' theorem which involves searching…

Spatial variation in effects of temperature on Phenotypic characteristics of Phytophthora ramorum isolates from eastern Sonoma county

Treesearch

Valerie Sherron; Nathan E. Rank; Michael Cohen; Brian L. Anacker; Ross K. Meentemeyer

2008-01-01

Quantifying the growth rates of plant pathogens in the laboratory can be useful for predicting rates of disease spread and impact in nature. The purpose of this study was to examine phenotypic variation among isolates of Phytophthora ramorum collected from a foliar host plant species, Umbellularia californica (California bay laurel...

The Validity Chlorophyll-a Estimation by Sun Induced Fluorescence in Estuarine Waters: An Analysis of Long-term (2003-2011) Water Quality Data from Tampa Bay, Florida (USA)

NASA Technical Reports Server (NTRS)

Moreno-Madrinan, Max Jacobo; Fischer, Andrew

2012-01-01

Satellite observation of phytoplankton concentration or chlorophyll-a is an important characteristic, critically integral to monitoring coastal water quality. However, the optical properties of estuarine and coastal waters are highly variable and complex and pose a great challenge for accurate analysis. Constituents such as suspended solids and dissolved organic matter and the overlapping and uncorrelated absorptions in the blue region of the spectrum renders the blue-green ratio algorithms for estimating chlorophyll-a inaccurate. Measurement of sun-induced chlorophyll fluorescence, on the other hand, which utilizes the near infrared portion of the electromagnetic spectrum, may provide a better estimate of phytoplankton concentrations. While modelling and laboratory studies have illustrated both the utility and limitations of satellite baseline algorithms based on the sun induced chlorophyll fluorescence signal, few have examined the empirical validity of these algorithms using a comprehensive long term in situ data set. In an unprecedented analysis of a long term (2003-2011) in situ monitoring data from Tampa Bay, Florida (USA), we assess the validity of the FLH product from the Moderate Resolution Imaging Spectrometer (MODIS) against chlorophyll ]a and a suite of water quality parameters taken in a variety of conditions throughout a large optically complex estuarine system. A systematic analysis of sampling sites throughout the bay is undertaken to understand how the relationship between FLH and in situ chlorophyll-a responds to varying conditions within the estuary including water depth, distance from shore and structures and eight water quality parameters. From the 39 station for which data was derived, 22 stations showed significant correlations when the FLH product was matched with in situ chlorophyll-alpha data. The correlations (r2) for individual stations within Tampa Bay ranged between 0.67 (n=28, pless than 0.01) and-0.457 (n=12, p=.016), indicating that for some areas within the Bay, FLH can be a good predictor of chlorophyll-alpha concentration and hence a useful tool for the analysis of water quality. Overall, the results show a 106% increase in the validity of chlorophyll -a concentration estimates using FLH over the standard the blue-green OC3M algorithm. This analysis also illustrates that the correlations between FLH and in situ chlorophyll -a measurements increases with increasing water depth and distance of the monitoring sites from both the shore and structures. However, due to confounding factors related to the complexity of the estuarine system, a linear improvement in the FLH to chlorophyll ]a relationship was not clearly noted with increasing depth and distance from shore alone. Correlations of FLH with turbidity, nutrients (total nitrogen and total phosphorous) biological oxygen demand, salinity, sea surface temperature correlated positively with FLH concentrations, while dissolved oxygen and pH showed negative correlations. Principle component analyses are employed to further describe the relationships between the multivariate water quality parameters and the FLH product. The majority of sites with higher and very significant correlations (pless than 0.01) also showed high correlation values for nutrients, turbidity and biological oxygen demand. These sites were on average in greater than seven meters of water and over five kilometers from shore. A thorough understanding of the relationship between the MODIS FLH product and in situ water quality parameters will enhance our understanding of the accuracy MODIS fs global FLH algorithm and assist in optimizing its calibration for use in monitoring the quality of estuarine and coastal waters worldwide.

Implementation and performance evaluation of acoustic denoising algorithms for UAV

NASA Astrophysics Data System (ADS)

Chowdhury, Ahmed Sony Kamal

Unmanned Aerial Vehicles (UAVs) have become popular alternative for wildlife monitoring and border surveillance applications. Elimination of the UAV's background noise and classifying the target audio signal effectively are still a major challenge. The main goal of this thesis is to remove UAV's background noise by means of acoustic denoising techniques. Existing denoising algorithms, such as Adaptive Least Mean Square (LMS), Wavelet Denoising, Time-Frequency Block Thresholding, and Wiener Filter, were implemented and their performance evaluated. The denoising algorithms were evaluated for average Signal to Noise Ratio (SNR), Segmental SNR (SSNR), Log Likelihood Ratio (LLR), and Log Spectral Distance (LSD) metrics. To evaluate the effectiveness of the denoising algorithms on classification of target audio, we implemented Support Vector Machine (SVM) and Naive Bayes classification algorithms. Simulation results demonstrate that LMS and Discrete Wavelet Transform (DWT) denoising algorithm offered superior performance than other algorithms. Finally, we implemented the LMS and DWT algorithms on a DSP board for hardware evaluation. Experimental results showed that LMS algorithm's performance is robust compared to DWT for various noise types to classify target audio signals.

Anthropogenic effects on shoreface and shoreline changes: Input from a multi-method analysis, Agadir Bay, Morocco

NASA Astrophysics Data System (ADS)

Aouiche, Ismail; Daoudi, Lahcen; Anthony, Edward J.; Sedrati, Mouncef; Ziane, Elhassane; Harti, Abderrazak; Dussouillez, Philippe

2016-02-01

In many situations, the links between shoreline fluctuations and larger-scale coastal change embracing the shoreface are not always well understood. In particular, meso-scale (years to decades) sand exchanges between the shoreface and the shoreline, considered as important on many wave-dominated coasts, are rather poorly understood and difficult to identify. Coastal systems where sediment transport is perturbed by engineering interventions on the shoreline and shoreface commonly provide fine examples liable to throw light on these links. This is especially so where shoreface bathymetric datasets, which are generally lacking, are collected over time, enabling more or less fine resolution of the meso-scale coastal sediment budget. Agadir Bay and the city of Agadir together form one of the two most important economic development poles on the Atlantic coast of Morocco. Using a combined methodological approach based on wave-current modelling, bathymetric chart-differencing, determination of shoreline fluctuations, and beach topographic surveying, we highlight the close links between variations in the bed of the inner shoreface and the bay shoreline involving both cross-shore and longshore sand transport pathways, sediment budget variations and new sediment cell patterns. We show that the significant changes that have affected the bay shoreline and shoreface since 1978 clearly reflect anthropogenic impacts, notably blocking of alongshore sand transport by Agadir harbour, completed in 1988, and the foundations of which lie well beyond the depth of wave closure. Construction of the harbour has led to the creation of a rapidly accreting beach against an original portion of rocky shoreline updrift and to a net sand loss exceeding 145,000 m3/year between 1978 and 2012 over 8.5 km2of the bay shoreface downdrift. Shoreline retreat has been further exacerbated by sand extraction from aeolian dunes and by flattening of these dunes to make space for tourist infrastructure. Digital elevation models of part of the bay beach between 2012 and 2014 confirm this on-going sand loss. These changes have involved the establishment of two divergent longshore bay sediment cells instead of the original single unidirectional cell. A prospective view of these changes suggests that perturbation of longshore drift and the on-going bay sediment budget deficit will eventual directly pose threats to the harbour access and to coastal tourism on which the economic growth of Agadir has been built.

The long-term salinity field in San Francisco Bay

USGS Publications Warehouse

Uncles, R.J.; Peterson, D.H.

1996-01-01

Data are presented on long-term salinity behaviour in San Francisco Bay, California. A two-level, width averaged model of the tidally averaged salinity and circulation has been written in order to interpret the long-term (days to decades) salinity variability. The model has been used to simulate daily averaged salinity in the upper and lower levels of a 51 segment discretization of the Bay over the 22-yr period 1967-1988. Monthly averaged surface salinity from observations and monthly-averaged simulated salinity are in reasonable agreement. Good agreement is obtained from comparison with daily averaged salinity measured in the upper reaches of North Bay. The salinity variability is driven primarily by freshwater inflow with relatively minor oceanic influence. All stations exhibit a marked seasonal cycle in accordance with the Mediterranean climate, as well as a rich spectrum of variability due to extreme inflow events and extended periods of drought. Monthly averaged salinity intrusion positions have a pronounced seasonal variability and show an approximately linear response to the logarithm of monthly averaged Delta inflow. Although few observed data are available for studies of long-term salinity stratification, modelled stratification is found to be strongly dependent on freshwater inflow; the nature of that dependence varies throughout the Bay. Near the Golden Gate, stratification tends to increase up to very high inflows. In the central reaches of North Bay, modelled stratification maximizes as a function of inflow and further inflow reduces stratification. Near the head of North Bay, lowest summer inflows are associated with the greatest modelled stratification. Observations from the central reaches of North Bay show marked spring-neap variations in stratification and gravitational circulation, both being stronger at neap tides. This spring-neap variation is simulated by the model. A feature of the modelled stratification is a hysteresis in which, for a given spring-neap tidal range and fairly steady inflows, the stratification is higher progressing from neaps to springs than from springs to neaps. The simulated responses of the Bay to perturbations in coastal sea salinity and Delta inflow have been used to further delineate the time-scales of salinity variability. Simulations have been performed about low inflow, steady-state conditions for both salinity and Delta inflow perturbations. For salinity perturbations a small, sinusoidal salinity signal with a period of 1 yr has been applied at the coastal boundary as well as a pulse of salinity with a duration of one day. For Delta inflow perturbations a small, sinusoidally varying inflow signal with a period of 1 yr has been superimposed on an otherwise constant Delta inflow, as well as a pulse of inflow with a duration of one day. Perturbations is coastal salinity dissipate as they move through the Bay. Seasonal perturbations require about 40-45 days to propagate from the coastal ocean to the Delta and to the head of South Bay. The response times of the model to perturbations in freshwater inflow are faster than this in North Bay and comparable in South Bay. In North Bay, time-scales are consistent with advection due to lower level, up-estuary transport of coastal salinity perturbations; for inflow perturbations, faster response times arise from both upper level, down-estuary advection and much faster, down-estuary migration of isohalines in response to inflow volume continuity. In South Bay, the dominant time-scales are governed by tidal dispersion.

Physical oceanographic investigation of Massachusetts and Cape Cod Bays

USGS Publications Warehouse

Geyer, W. Rockwell; Gardner, George B.; Brown, Wendell S.; Irish, James D.; Butman, Bradford; Loder, T.C.; Signell, Richard P.

1992-01-01

This physical oceanographic study of the Massachusetts Bays (fig. 1) was designed to provide for the first time a bay-wide description of the circulation and mixing processes on a seasonal basis. Most of the measurements were conducted between April 1990 and June 1991 and consisted of moored observations to study the current flow patterns (fig. 2), hydrographic surveys to document the changes in water properties (fig. 3), high-resolution surveys of velocity and water properties to provide information on the spatial variability of the flow, drifter deployments to measure the currents, and acquisition of satellite images to provide a bay-wide picture of the surface temperature and its spatial variability. A longterm objective of the Massachusetts Bays program is to develop an understanding of the transport of water, dissolved substances and particles throughout the bays. Because horizontal and vertical transport is important to biological, chemical, and geological processes in Massachusetts and Cape Cod Bays, this physical oceanographic study will have broad application and will improve the ability to manage and monitor the water and sediment quality of the Bays. Key results are:There is a marked seasonal variation in stratification in the bays, from well mixed conditions during the winter to strong stratification in the summertime. The stratification acts as a partial barrier to exchange between the surface waters and the deeper waters and causes the motion of the surface waters to be decoupled from the more sluggish flow of the deep waters. During much of the year, there is weak but persistent counterclockwise flow around the bays, made up of southwesterly flow past Cape Ann, southward flow along the western shore, and outflow north of Race Point. The data suggest that this residual flow pattern reverses in fall. Fluctuations caused by wind and density variations are typically larger than the long-term mean. With the exception of western Massachusetts Bay, flushing of the Bays is largely the result of the mean throughflow. Residence time estimates of the surface waters range from 20-45 days. The deeper water has a longer residence time, but its value is difficult to estimate. There is evidence that the deep waters in Stellwagen Basin are not renewed between the onset of stratification and the fall cooling period.Current measurements made near the new outfall site in western Massachusetts Bay suggest that water and material discharged there are not swept away in a consistent direction by a well-defined steady current but are mixed and transported by a variety of processes, including the action of tides, winds, and river inflow. One-day particle excursions are typically less than 10 km. The outfall is apparently located in a region to the west of the basin-wide residual flow pattern.Observations in western Massachusetts Bay, near the location of the future Boston sewage outfall, show that the surficial sediments are episodically resuspended from the seafloor during storms. The observations suggest onshore transport of suspended material during tranquil periods and episodic offshore and southerly alongshore transport of resuspended sediments during storms. The spatial complexity of the flow in the Massachusetts Bays is typical of nearshore areas that have irregular coastal shorelines and topography and currents that are forced locally by wind and river runoff as well as by the flow in adjacent regions. Numerical models are providing a mechanism to interpret the complex spatial flow patterns that cannot be completely resolved by field observations and to investigate key physical processes that control the physics of water and particle transport.

A Pilot Study of the Effects of Post-Hurricane Katrina Floodwater Pumping on the Chemistry and Toxicity of Violet Marsh Sediments

DTIC Science & Technology

2006-10-01

to be suitable for testing without manipulations. Survival of amphipods in the control sediment from Sequim Bay , WA was above the 90-percent level...Treatment Mean Percent Survival Coefficient of Variation (%) Negative Control ( Sequim Bay , WA) 90 ± 4 3.9 Reference (Lake Pontchartrain, LA) 95...assessed along with a perform- ance control sediment ( Sequim , WA, USA Lat. 48.0587 Long. -123.0235 and a reference sedi- ment (Lake Pontchartrain

Saco Bay, Maine: Sediment Budget for Late Twentieth Century to Present

DTIC Science & Technology

2016-02-01

determined that sediment flux was variable, depending on bathymetry and input wave conditions. Despite these variations in conditions, there is no obvious...DETAILS, SACO BAY, MAINE V3. Last update: 11 September 2014 Units are yd3/year. Source1 = bluffs, river influx, wind . Sink1 = wind -blown loss or...Beach05 (B05), Pine Point QSource1 1,600 Wind transport (from Kelley et al. 2005). DeltaV 1,600 Dune accumulation 1859–1991 (from Kelley et al. 2005

Sedimentation processes in a coral reef embayment: Hanalei Bay, Kauai

USGS Publications Warehouse

Storlazzi, C.D.; Field, M.E.; Bothner, Michael H.; Presto, M.K.; Draut, A.E.

2009-01-01

Oceanographic measurements and sediment samples were collected during the summer of 2006 as part of a multi-year study of coastal circulation and the fate of terrigenous sediment on coral reefs in Hanalei Bay, Kauai. The goal of this study was to better understand sediment dynamics in a coral reef-lined embayment where winds, ocean surface waves, and river floods are important processes. During a summer period that was marked by two wave events and one river flood, we documented significant differences in sediment trap collection rates and the composition, grain size, and magnitude of sediment transported in the bay. Sediment trap collection rates were well correlated with combined wave-current near-bed shear stresses during the non-flood periods but were not correlated during the flood. The flood's delivery of fine-grained sediment to the bay initially caused high turbidity and sediment collection rates off the river mouth but the plume dispersed relatively quickly. Over the next month, the flood deposit was reworked by mild waves and currents and the fine-grained terrestrial sediment was advected around the bay and collected in sediment traps away from the river mouth, long after the turbid surface plume was gone. The reworked flood deposits, due to their longer duration of influence and proximity to the seabed, appear to pose a greater long-term impact to benthic coral reef communities than the flood plumes themselves. The results presented here display how spatial and temporal differences in hydrodynamic processes, which result from variations in reef morphology and orientation, cause substantial variations in the deposition, residence time, resuspension, and advection of both reef-derived and fluvial sediment over relatively short spatial scales in a coral reef embayment.

Genome and Transcriptome Sequencing of the Ostreid herpesvirus 1 From Tomales Bay, California

NASA Astrophysics Data System (ADS)

Burge, C. A.; Langevin, S.; Closek, C. J.; Roberts, S. B.; Friedman, C. S.

2016-02-01

Mass mortalities of larval and seed bivalve molluscs attributed to the Ostreid herpesvirus 1 (OsHV-1) occur globally. OsHV-1 was fully sequenced and characterized as a member of the Family Malacoherpesviridae. Multiple strains of OsHV-1 exist and may vary in virulence, i.e. OsHV-1 µvar. For most global variants of OsHV-1, sequence data is limited to PCR-based sequencing of segments, including two recent genomes. In the United States, OsHV-1 is limited to detection in adjacent embayments in California, Tomales and Drakes bays. Limited DNA sequence data of OsHV-1 infecting oysters in Tomales Bay indicates the virus detected in Tomales Bay is similar but not identical to any one global variant of OsHV-1. In order to better understand both strain variation and virulence of OsHV-1 infecting oysters in Tomales Bay, we used genomic and transcriptomic sequencing. Meta-genomic sequencing (Illumina MiSeq) was conducted from infected oysters (n=4 per year) collected in 2003, 2007, and 2014, where full OsHV-1 genome sequences and low overall microbial diversity were achieved from highly infected oysters. Increased microbial diversity was detected in three of four samples sequenced from 2003, where qPCR based genome copy numbers of OsHV-1 were lower. Expression analysis (SOLiD RNA sequencing) of OsHV-1 genes expressed in oyster larvae at 24 hours post exposure revealed a nearly complete transcriptome, with several highly expressed genes, which are similar to recent transcriptomic analyses of other OsHV-1 variants. Taken together, our results indicate that genome and transcriptome sequencing may be powerful tools in understanding both strain variation and virulence of non-culturable marine viruses.

Distribution and growth dynamics of ephemeral macroalgae in shallow bays on the Swedish west coast

NASA Astrophysics Data System (ADS)

Pihl, Leif; Magnusson, Gunilla; Isaksson, Ingela; Wallentinus, Inger

1996-02-01

Distribution and growth dynamics of ephemeral macroalgae were investigated in some shallow (0-1 m) bays on the Swedish west coast during the period 1992 to 1994. Variation in cover and biomass was assessed in nine bays, and in one of them the seasonal dynamics of these algae was followed intensively over three years. Frequent measurements were taken of algal biomass, degree of cover, in situ growth, variable fluorescence and C/N-ratios. Irradiance and water nutrient concentrations were measured concurrently with the growth measurements. Ephemeral macroalgae were dominated by Cladophora and Enteromorpha species and occurred in all sampled bays, except one, covering 10 to 100% of the bottom sediment. Generally, a rapid biomass increase was recorded from mid-May, which peaked after six weeks at 400-600 g dwt·m -2. Later in the season, strong variations in biomass, cover and species composition were observed, suggesting that these opportunistic algae form a highly dynamic community. Initial growth rates estimated from biomass samples were similar to those recorded from in situ cage experiments, and also agreed with growth rates calculated from a model. For all species studied growth rate was within the range 10 to 30 g dwt·m -2·d -1, irrespective of method used. Low algal C/N-ratios (mean = 12.7) in 1993 (cold and rainy summer) indicated that growth was not limited by nutrients, but rather by light. In 1994 (warm and sunny summer), mean C/N-ratios were 20, reflecting the opposite situation. The appearance of these opportunistic algae in shallow bays which historically had been without macroalgal communities has changed the characteristics of these areas by altering habitat complexity. This could have important consequences for trophic interactions involving many species, thereby altering community structure and function.

Flow in water-intake pump bays: A guide for utility engineers. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ettema, R.

1998-09-01

This report is intended to serve as a guide for power-plant engineers facing problems with flow conditions in pump bays in water-intake structures, especially those located alongside rivers. The guide briefly introduces the typical prevailing flow field outside of a riverside water intake. That flow field often sets the inflow conditions for pump bays located within the water intake. The monograph then presents and discusses the main flow problems associated with pump bays. The problems usually revolve around the formation of troublesome vortices. A novel feature of this monograph is the use of numerical modeling to reveal diagnostically how themore » vortices form and their sensitivities to flow conditions, such as uniformity of approach flow entering the bay and water-surface elevation relative to pump-bell submergence. The modeling was carried out using a computer code developed specially for the present project. Pump-bay layouts are discussed next. The discussion begins with a summary of the main variables influencing bay flows. The numerical model is used to determine the sensitivities of the vortices to variations in the geometric parameters. The fixes include the use of flow-control vanes and suction scoops for ensuring satisfactory flow performance in severe flow conditions; notably flows with strong cross flow and shallow flows. The monograph ends with descriptions of modeling techniques. An extensive discussion is provided on the use of numerical model for illuminating bay flows. The model is used to show how fluid viscosity affects bay flow. The effect of fluid viscosity is an important consideration in hydraulic modeling of water intakes.« less

Coastal circulation and potential coral-larval dispersal in Maunalua Bay, O'ahu, Hawaii—Measurements of waves, currents, temperature, and salinity, June-September 2010

USGS Publications Warehouse

Presto, M. Katherine; Storlazzi, Curt D.; Logan, Joshua B.; Reiss, Thomas E.; Rosenberger, Kurt J.

2012-01-01

This report presents a summary of fieldwork conducted in Maunalua Bay, O'ahu, Hawaii to address coral-larval dispersal and recruitment from June through September, 2010. The objectives of this study were to understand the temporal and spatial variations in currents, waves, tides, temperature, and salinity in Maunalua Bay during the summer coral-spawning season of Montipora capitata. Short-term vessel surveys and satellite-tracked drifters were deployed to measure currents during the June 2010 spawning event and to supplement the longer-term measurements of currents and water-column properties by fixed, bottom-mounted instruments deployed in Maunalua Bay. These data show that currents at the surface and just below the surface where coral larvae are found are often oriented in opposite directions due primarily to tidal and trade-winds forcing as the primary mechanisms of circulation in the bay. These data extend our understanding of coral-larvae dispersal patterns due to tidal and wind-driven currents and may be applicable to larvae of other Hawaiian corals.

Intra- and inter-annual trends in phosphorus loads and comparison with nitrogen loads to Rehoboth Bay, Delaware (USA)

USGS Publications Warehouse

Volk, J.A.; Scudlark, J.R.; Savidge, K.B.; Andres, A.S.; Stenger, R.J.; Ullman, W.J.

2012-01-01

Monthly phosphorus loads from uplands, atmospheric deposition, and wastewater to Rehoboth Bay (Delaware) were determined from October 1998 to April 2002 to evaluate the relative importance of these three sources of P to the Bay. Loads from a representative subwatershed were determined and used in an areal extrapolation to estimate the upland load from the entire watershed. Soluble reactive phosphorus (SRP) and dissolved organic P (DOP) are the predominant forms of P in baseflow and P loads from the watershed are highest during the summer months. Particulate phosphorus (PP) becomes more significant in stormflow and during periods with more frequent or larger storms. Atmospheric deposition of P is only a minor source of P to Rehoboth Bay. During the period of 1998-2002, wastewater was the dominant external source of P to Rehoboth Bay, often exceeding all other P sources combined. Since 2002, however, due to technical improvements to the sole wastewater plant discharging directly to the Bay, the wastewater contribution of P has been significantly reduced and upland waters are now the principal source of P on an annualized basis. Based on comparison of N and P loads, primary productivity and biomass carrying capacity in Rehoboth Bay should be limited by P availability. However, due to the contrasting spatial and temporal patterns of N and P loading and perhaps internal cycling within the ecosystem, spatial and temporal variations in N and P-limitation within Rehoboth Bay are likely. ?? 2011 Elsevier Ltd.

Seasonal estimates of DOC standing stocks in Apalachicola Bay estuary: Towards a better understanding using field, ocean color and model data

NASA Astrophysics Data System (ADS)

D'Sa, E. J.; Joshi, I.; Osburn, C. L.; Bianchi, T. S.; Ko, D. S.; Oviedo-Vargas, D.; Arellano, A.; Ward, N.

2016-12-01

Apalachicola Bay, a semi-enclosed estuary located in Florida's panhandle, is well known for its water quality and oyster yields. We present the use of combined field and ocean color satellite observations and the outputs of a high-resolution hydrodynamic model to study the influence of physical processes on the distribution and the transport of terrestrially derived CDOM and DOC to shelf waters during the spring and fall of 2015. Determination of DOC stocks were based on the development of a CDOM algorithm (R2 = 0.87, N = 9) for the VIIRS ocean color sensor, and the assessment of CDOM - DOC relationships (R2 = 0.88, N = 13 in March; R2 = 0.83, N = 24 in November) for the Apalachicola Bay. Satellite-derived CDOM and DOC maps together with model-based salinity distributions revealed their spatial extent, sources and transport to the shelf water. Furthermore, strong seasonal influence on DOM distribution in the bay was associated with inputs from Apalachicola and Carrabelle Rivers and the surrounding marshes. Estimates of DOC standing stocks in the bay obtained using ocean color data and high-resolution bathymetry showed relatively higher stocks in November ( 3.71 × 106 kg C, 560 km2) than in March ( 4.07 × 106 kg C, 560 km2) despite lower river discharge in dry season. Results of DOC flux estimates from the bay to coastal waters will also be presented.

Research on Bayes matting algorithm based on Gaussian mixture model

NASA Astrophysics Data System (ADS)

Quan, Wei; Jiang, Shan; Han, Cheng; Zhang, Chao; Jiang, Zhengang

2015-12-01

The digital matting problem is a classical problem of imaging. It aims at separating non-rectangular foreground objects from a background image, and compositing with a new background image. Accurate matting determines the quality of the compositing image. A Bayesian matting Algorithm Based on Gaussian Mixture Model is proposed to solve this matting problem. Firstly, the traditional Bayesian framework is improved by introducing Gaussian mixture model. Then, a weighting factor is added in order to suppress the noises of the compositing images. Finally, the effect is further improved by regulating the user's input. This algorithm is applied to matting jobs of classical images. The results are compared to the traditional Bayesian method. It is shown that our algorithm has better performance in detail such as hair. Our algorithm eliminates the noise well. And it is very effectively in dealing with the kind of work, such as interested objects with intricate boundaries.

Gauge properties of the guiding center variational symplectic integrator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Squire, J.; Tang, W. M.; Qin, H.

Variational symplectic algorithms have recently been developed for carrying out long-time simulation of charged particles in magnetic fields [H. Qin and X. Guan, Phys. Rev. Lett. 100, 035006 (2008); H. Qin, X. Guan, and W. Tang, Phys. Plasmas (2009); J. Li, H. Qin, Z. Pu, L. Xie, and S. Fu, Phys. Plasmas 18, 052902 (2011)]. As a direct consequence of their derivation from a discrete variational principle, these algorithms have very good long-time energy conservation, as well as exactly preserving discrete momenta. We present stability results for these algorithms, focusing on understanding how explicit variational integrators can be designed formore » this type of system. It is found that for explicit algorithms, an instability arises because the discrete symplectic structure does not become the continuous structure in the t{yields}0 limit. We examine how a generalized gauge transformation can be used to put the Lagrangian in the 'antisymmetric discretization gauge,' in which the discrete symplectic structure has the correct form, thus eliminating the numerical instability. Finally, it is noted that the variational guiding center algorithms are not electromagnetically gauge invariant. By designing a model discrete Lagrangian, we show that the algorithms are approximately gauge invariant as long as A and {phi} are relatively smooth. A gauge invariant discrete Lagrangian is very important in a variational particle-in-cell algorithm where it ensures current continuity and preservation of Gauss's law [J. Squire, H. Qin, and W. Tang (to be published)].« less

Chemical variations in Yellowknife Bay formation sedimentary rocks analyzed by ChemCam on board the Curiosity rover on Mars

USGS Publications Warehouse

Mangold, Nicolas; Forni, Olivier; Dromart, G.; Stack, K.M.; Wiens, Roger C.; Gasnault, Olivier; Sumner, Dawn Y.; Nachon, Marion; Meslin, Pierre-Yves; Anderson, Ryan B.; Barraclough, Bruce; Bell, J.F.; Berger, G.; Blaney, D.L.; Bridges, J.C.; Calef, F.; Clark, Brian R.; Clegg, Samuel M.; Cousin, Agnes; Edgar, L.; Edgett, Kenneth S.; Ehlmann, B.L.; Fabre, Cecile; Fisk, M.; Grotzinger, John P.; Gupta, S.C.; Herkenhoff, Kenneth E.; Hurowitz, J.A.; Johnson, J. R.; Kah, Linda C.; Lanza, Nina L.; Lasue, Jeremie; Le Mouélic, S.; Lewin, Eric; Malin, Michael; McLennan, Scott M.; Maurice, S.; Melikechi, Noureddine; Mezzacappa, Alissa; Milliken, Ralph E.; Newsome, H.L.; Ollila, A.; Rowland, Scott K.; Sautter, Violaine; Schmidt, M.E.; Schroder, S.; D'Uston, C.; Vaniman, Dave; Williams, R.A.

2015-01-01

The Yellowknife Bay formation represents a ~5 m thick stratigraphic section of lithified fluvial and lacustrine sediments analyzed by the Curiosity rover in Gale crater, Mars. Previous works have mainly focused on the mudstones that were drilled by the rover at two locations. The present study focuses on the sedimentary rocks stratigraphically above the mudstones by studying their chemical variations in parallel with rock textures. Results show that differences in composition correlate with textures and both manifest subtle but significant variations through the stratigraphic column. Though the chemistry of the sediments does not vary much in the lower part of the stratigraphy, the variations in alkali elements indicate variations in the source material and/or physical sorting, as shown by the identification of alkali feldspars. The sandstones contain similar relative proportions of hydrogen to the mudstones below, suggesting the presence of hydrous minerals that may have contributed to their cementation. Slight variations in magnesium correlate with changes in textures suggesting that diagenesis through cementation and dissolution modified the initial rock composition and texture simultaneously. The upper part of the stratigraphy (~1 m thick) displays rocks with different compositions suggesting a strong change in the depositional system. The presence of float rocks with similar compositions found along the rover traverse suggests that some of these outcrops extend further away in the nearby hummocky plains.

Three-dimensional seismic velocity structure of the San Francisco Bay area

USGS Publications Warehouse

Hole, J.A.; Brocher, T.M.; Klemperer, S.L.; Parsons, T.; Benz, H.M.; Furlong, K.P.

2000-01-01

Seismic travel times from the northern California earthquake catalogue and from the 1991 Bay Area Seismic Imaging Experiment (BASIX) refraction survey were used to obtain a three-dimensional model of the seismic velocity structure of the San Francisco Bay area. Nonlinear tomography was used to simultaneously invert for both velocity and hypocenters. The new hypocenter inversion algorithm uses finite difference travel times and is an extension of an existing velocity tomography algorithm. Numerous inversions were performed with different parameters to test the reliability of the resulting velocity model. Most hypocenters were relocated 12 km under the Sacramento River Delta, 6 km beneath Livermore Valley, 5 km beneath the Santa Clara Valley, and 4 km beneath eastern San Pablo Bay. The Great Valley Sequence east of San Francisco Bay is 4-6 km thick. A relatively high velocity body exists in the upper 10 km beneath the Sonoma volcanic field, but no evidence for a large intrusion or magma chamber exists in the crust under The Geysers or the Clear Lake volcanic center. Lateral velocity contrasts indicate that the major strike-slip faults extend subvertically beneath their surface locations through most of the crust. Strong lateral velocity contrasts of 0.3-0.6 km/s are observed across the San Andreas Fault in the middle crust and across the Hayward, Rogers Creek, Calaveras, and Greenville Faults at shallow depth. Weaker velocity contrasts (0.1-0.3 km/s) exist across the San Andreas, Hayward, and Rogers Creek Faults at all other depths. Low spatial resolution evidence in the lower crust suggests that the top of high-velocity mafic rocks gets deeper from west to east and may be offset under the major faults. The data suggest that the major strike-slip faults extend subvertically through the middle and perhaps the lower crust and juxtapose differing lithology due to accumulated strike-slip motion. The extent and physical properties of the major geologic units as constrained by the model should be used to improve studies of seismicity, strong ground motion, and regional stress.

Assimilation of HF Radar Observations in the Chesapeake-Delaware Bay Region Using the Navy Coastal Ocean Model (NCOM) and the Four-Dimensional Variational (4DVAR) Method

DTIC Science & Technology

2015-01-01

6. Zhang WG, Wilkin JL, Arango HG. Towards an integrated observation and modeling system in the New York Bight using variational methods. Part 1...1992;7:262- 72. ---- -- - ---------------------------- References 391 17. Rosmond TE, Teixeria J, Pcng M, Hogan TF, Pauley R. Navy operational global

Regional downscaling of temporal resolution in near-surface wind from statistically downscaled Global Climate Models (GCMs) for use in San Francisco Bay coastal flood modeling

NASA Astrophysics Data System (ADS)

O'Neill, A.; Erikson, L. H.; Barnard, P.

2013-12-01

While Global Climate Models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues (MACA) provide daily near-surface winds at an appropriate spatial resolution for wave modeling within San Francisco Bay. Using 30 years (1975-2004) of climatological data from four representative stations around San Francisco Bay, a library of example daily wind conditions for four corresponding over-water sub-regions is constructed. Empirical cumulative distribution functions (ECDFs) of station conditions are compared to MACA GFDL hindcasts to create correction factors, which are then applied to 21st century MACA wind projections. For each projection day, a best match example is identified via least squares error among all stations from the library. The best match's daily variation in velocity components (u/v) is used as an analogue of representative wind variation and is applied at 3-hour increments about the corresponding sub-region's projected u/v values. High temporal resolution reconstructions using this methodology on hindcast MACA fields from 1975-2004 accurately recreate extreme wind values within the San Francisco Bay, and because these extremes in wind forcing are of key importance in wave and subsequent coastal flood modeling, this represents a valuable method of generating near-surface wind vectors for use in coastal flood modeling.

Generalized empirical Bayesian methods for discovery of differential data in high-throughput biology.

PubMed

Hardcastle, Thomas J

2016-01-15

High-throughput data are now commonplace in biological research. Rapidly changing technologies and application mean that novel methods for detecting differential behaviour that account for a 'large P, small n' setting are required at an increasing rate. The development of such methods is, in general, being done on an ad hoc basis, requiring further development cycles and a lack of standardization between analyses. We present here a generalized method for identifying differential behaviour within high-throughput biological data through empirical Bayesian methods. This approach is based on our baySeq algorithm for identification of differential expression in RNA-seq data based on a negative binomial distribution, and in paired data based on a beta-binomial distribution. Here we show how the same empirical Bayesian approach can be applied to any parametric distribution, removing the need for lengthy development of novel methods for differently distributed data. Comparisons with existing methods developed to address specific problems in high-throughput biological data show that these generic methods can achieve equivalent or better performance. A number of enhancements to the basic algorithm are also presented to increase flexibility and reduce computational costs. The methods are implemented in the R baySeq (v2) package, available on Bioconductor http://www.bioconductor.org/packages/release/bioc/html/baySeq.html. tjh48@cam.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Alkalinity-salinity relationship in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Cintrón Del Valle, S. M.; Najjar, R.; Herrmann, M.; Goldberger, S.; Stets, E.

2016-12-01

Estuaries are a significant source of atmospheric CO2, a major greenhouse gas. However, it is not known whether the Chesapeake Bay, the largest estuary in the United States, is a source or sink of CO2. Extensive pH measurements in the Bay offer the possibility of estimating the air-water CO2 flux if robust relationships between alkalinity, the acid neutralizing capacity of a water body, and salinity can be established. Here we conduct a comprehensive analysis of the alkalinity-salinity relationship in the Chesapeake Bay based on more than 18,000 alkalinity measurements made between 1985 and 2015. It was found that seven segments of the Bay could be grouped into three different linear functions, suggesting that alkalinity is conserved in the Bay and has properties that change depending on the freshwater endmember (the riverine source). The highest freshwater endmember was 1.21 mol m-3 for the Potomac River, the lowest one was 0.41 mol m-3 for the York and Rappahannock Rivers, and an intermediate freshwater endmember was 0.79 mol m-3 for the remaining four segments. For some segments, most notably the Potomac River, the scatter of the data increases with decreasing salinity, which is due, in part, to seasonal and interannual variations in the freshwater endmember.

Patchiness of phytoplankton and primary production in Liaodong Bay, China.

PubMed

Pei, Shaofeng; Laws, Edward A; Zhang, Haibo; Ye, Siyuan; Yuan, Hongming; Liu, Haiyue

2017-01-01

A comprehensive study of water quality, phytoplankton biomass, and photosynthetic rates in Liaodong Bay, China, during June and July of 2013 revealed two large patches of high biomass and production with dimensions on the order of 10 km. Nutrient concentrations were above growth-rate-saturating concentrations throughout the bay, with the possible exception of phosphate at some stations. The presence of the patches therefore appeared to reflect the distribution of water temperature and variation of light penetration restricted by water turbidity. There was no patch of high phytoplankton biomass or production in a third, linear patch of water with characteristics suitable for rapid phytoplankton growth; the absence of a bloom in that patch likely reflected the fact that the width of the patch was less than the critical size required to overcome losses of phytoplankton to turbulent diffusion. The bottom waters of virtually all of the eastern half of the bay were below the depth of the mixed layer, and the lowest bottom water oxygen concentrations, 3-5 mg L-1, were found in that part of the bay. The water column in much of the remainder of the bay was within the mixed layer, and oxygen concentrations in both surface and bottom waters exceeded 5 mg L-1.

Patchiness of phytoplankton and primary production in Liaodong Bay, China

PubMed Central

Laws, Edward A.; Zhang, Haibo; Ye, Siyuan; Yuan, Hongming; Liu, Haiyue

2017-01-01

A comprehensive study of water quality, phytoplankton biomass, and photosynthetic rates in Liaodong Bay, China, during June and July of 2013 revealed two large patches of high biomass and production with dimensions on the order of 10 km. Nutrient concentrations were above growth-rate-saturating concentrations throughout the bay, with the possible exception of phosphate at some stations. The presence of the patches therefore appeared to reflect the distribution of water temperature and variation of light penetration restricted by water turbidity. There was no patch of high phytoplankton biomass or production in a third, linear patch of water with characteristics suitable for rapid phytoplankton growth; the absence of a bloom in that patch likely reflected the fact that the width of the patch was less than the critical size required to overcome losses of phytoplankton to turbulent diffusion. The bottom waters of virtually all of the eastern half of the bay were below the depth of the mixed layer, and the lowest bottom water oxygen concentrations, 3–5 mg L–1, were found in that part of the bay. The water column in much of the remainder of the bay was within the mixed layer, and oxygen concentrations in both surface and bottom waters exceeded 5 mg L–1. PMID:28235070

Seasonal and Inter-Annual Patterns of Phytoplankton Community Structure in Monterey Bay, CA Derived from AVIRIS Data During the 2013-2015 HyspIRI Airborne Campaign

NASA Astrophysics Data System (ADS)

Palacios, S. L.; Thompson, D. R.; Kudela, R. M.; Negrey, K.; Guild, L. S.; Gao, B. C.; Green, R. O.; Torres-Perez, J. L.

2015-12-01

There is a need in the ocean color community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand ocean biodiversity, to track energy flow through ecosystems, and to identify and monitor for harmful algal blooms. Imaging spectrometer measurements enable use of sophisticated spectroscopic algorithms for applications such as differentiating among coral species, evaluating iron stress of phytoplankton, and discriminating phytoplankton taxa. These advanced algorithms rely on the fine scale, subtle spectral shape of the atmospherically corrected remote sensing reflectance (Rrs) spectrum of the ocean surface. As a consequence, these algorithms are sensitive to inaccuracies in the retrieved Rrs spectrum that may be related to the presence of nearby clouds, inadequate sensor calibration, low sensor signal-to-noise ratio, glint correction, and atmospheric correction. For the HyspIRI Airborne Campaign, flight planning considered optimal weather conditions to avoid flights with significant cloud/fog cover. Although best suited for terrestrial targets, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has enough signal for some coastal chlorophyll algorithms and meets sufficient calibration requirements for most channels. However, the coastal marine environment has special atmospheric correction needs due to error that may be introduced by aerosols and terrestrially sourced atmospheric dust and riverine sediment plumes. For this HyspIRI campaign, careful attention has been given to the correction of AVIRIS imagery of the Monterey Bay to optimize ocean Rrs retrievals for use in estimating chlorophyll (OC3 algorithm) and phytoplankton functional type (PHYDOTax algorithm) data products. This new correction method has been applied to several image collection dates during two oceanographic seasons - upwelling and the warm, stratified oceanic period for 2013 and 2014. These two periods are dominated by either diatom blooms (occasionally toxic) or red tides. Results presented include chlorophyll and phytoplankton community structure and in-water validation data for these dates during these two seasons.

Hybrid analysis for indicating patients with breast cancer using temperature time series.

PubMed

Silva, Lincoln F; Santos, Alair Augusto S M D; Bravo, Renato S; Silva, Aristófanes C; Muchaluat-Saade, Débora C; Conci, Aura

2016-07-01

Breast cancer is the most common cancer among women worldwide. Diagnosis and treatment in early stages increase cure chances. The temperature of cancerous tissue is generally higher than that of healthy surrounding tissues, making thermography an option to be considered in screening strategies of this cancer type. This paper proposes a hybrid methodology for analyzing dynamic infrared thermography in order to indicate patients with risk of breast cancer, using unsupervised and supervised machine learning techniques, which characterizes the methodology as hybrid. The dynamic infrared thermography monitors or quantitatively measures temperature changes on the examined surface, after a thermal stress. In the dynamic infrared thermography execution, a sequence of breast thermograms is generated. In the proposed methodology, this sequence is processed and analyzed by several techniques. First, the region of the breasts is segmented and the thermograms of the sequence are registered. Then, temperature time series are built and the k-means algorithm is applied on these series using various values of k. Clustering formed by k-means algorithm, for each k value, is evaluated using clustering validation indices, generating values treated as features in the classification model construction step. A data mining tool was used to solve the combined algorithm selection and hyperparameter optimization (CASH) problem in classification tasks. Besides the classification algorithm recommended by the data mining tool, classifiers based on Bayesian networks, neural networks, decision rules and decision tree were executed on the data set used for evaluation. Test results support that the proposed analysis methodology is able to indicate patients with breast cancer. Among 39 tested classification algorithms, K-Star and Bayes Net presented 100% classification accuracy. Furthermore, among the Bayes Net, multi-layer perceptron, decision table and random forest classification algorithms, an average accuracy of 95.38% was obtained. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

One year observations of atmospheric reactive gases (O3, CO, NOx, SO2) at Jang Bogo base in Terra Nova Bay, Antarctica

NASA Astrophysics Data System (ADS)

Siek Rhee, Tae; Seo, Sora

2016-04-01

Antarctica is a remote area surrounded by the Southern Ocean and far from the influence of human activities, giving us unique opportunity to investigate the background variation of trace gases which are sensitive to the human activities. Korean Antarctic base, Jang Bogo, was established as a unique permanent overwintering base in Terra Nova Bay in February, 2014. One year later, we installed a package of instruments to monitor atmospheric trace gases at the base, which includes long-lived greenhouse gases, CO2, CH4, and N2O, and reactive gases, O3, CO, NOx, and SO2. The atmospheric chemistry observatory, where these scientific instruments were installed, is located ca. 1 km far from the main building and power plant, minimizing the influence of pollution that may come from the operation of the base. Here we focus on the reactive gases measured in-situ at the base; O3 displays a typical seasonal variation with high in winter and low in summer with seasonal amplitude of ~18 ppb, CO was high in September at ~56 ppb, probably implying the invasion of lower latitude air mass with biomass burning, and low in late summer due to photochemical oxidation. NO did not show clear seasonal variation, but SO2 reveals larger values in summer than in winter. We will discuss potential atmospheric processes behind these first observations of reactive gases in Terra Nova Bay, Antarctica.

Improving the quantification of contrast enhanced ultrasound using a Bayesian approach

NASA Astrophysics Data System (ADS)

Rizzo, Gaia; Tonietto, Matteo; Castellaro, Marco; Raffeiner, Bernd; Coran, Alessandro; Fiocco, Ugo; Stramare, Roberto; Grisan, Enrico

2017-03-01

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity, that can be useful in the quantification of different perfusion patterns. This can be particularly important in the early detection and staging of arthritis. In a recent study we have shown that a Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. Moreover, we have shown that through a pixel-by-pixel analysis the quantitative information gathered characterizes more effectively the perfusion. However, the SNR ratio of the data and the nonlinearity of the model makes the parameter estimation difficult. Using classical non-linear-leastsquares (NLLS) approach the number of unreliable estimates (those with an asymptotic coefficient of variation greater than a user-defined threshold) is significant, thus affecting the overall description of the perfusion kinetics and of its heterogeneity. In this work we propose to solve the parameter estimation at the pixel level within a Bayesian framework using Variational Bayes (VB), and an automatic and data-driven prior initialization. When evaluating the pixels for which both VB and NLLS provided reliable estimates, we demonstrated that the parameter values provided by the two methods are well correlated (Pearson's correlation between 0.85 and 0.99). Moreover, the mean number of unreliable pixels drastically reduces from 54% (NLLS) to 26% (VB), without increasing the computational time (0.05 s/pixel for NLLS and 0.07 s/pixel for VB). When considering the efficiency of the algorithms as computational time per reliable estimate, VB outperforms NLLS (0.11 versus 0.25 seconds per reliable estimate respectively).

The application of remote sensing image sea ice monitoring method in Bohai Bay based on C4.5 decision tree algorithm

NASA Astrophysics Data System (ADS)

Ye, Wei; Song, Wei

2018-02-01

In The Paper, the remote sensing monitoring of sea ice problem was turned into a classification problem in data mining. Based on the statistic of the related band data of HJ1B remote sensing images, the main bands of HJ1B images related with the reflectance of seawater and sea ice were found. On the basis, the decision tree rules for sea ice monitoring were constructed by the related bands found above, and then the rules were applied to Liaodong Bay area seriously covered by sea ice for sea ice monitoring. The result proved that the method is effective.

Naïve Bayes Approach for Expert System Design of Children Skin Identification Based on Android

NASA Astrophysics Data System (ADS)

Hartatik; Purnomo, A.; Hartono, R.; Munawaroh, H.

2018-03-01

The development of technology gives some benefits to each person that we can use it properly and correctly. Technology has helped humans in every way. Such as the excess task of an expert in providing information or answers to a problem. Thus problem that often occurs is skin disease that affecting on child. That because the skin of children still vulnerable to the environment. The application was developed using the naïve Bayes algorithm. Through this application, users can consult with a system like an expert to know the symptoms that occur to the child and find the correct treatment to solve the problems.

Multisensor Observation and Simulation of Snowfall During the 2003 Wakasa Bay Field Experiment

NASA Technical Reports Server (NTRS)

Johnson, Benjamin T.; Petty, Grant W.; Skofronick-Jackson, Gail; Wang, James W.

2005-01-01

This research seeks to assess and improve the accuracy of microphysical assumptions used in satellite passive microwave radiative transfer models and retrieval algorithms by exploiting complementary observations from satellite radiometers, such as TRMM/AMSR-E/GPM, and coincident aircraft instruments, such as the next generation precipitation radar (PR-2). We focus in particular on aircraft data obtained during the Wakasa Bay field experiment, Japan 2003, pertaining to surface snowfall events. The observations of vertical profiles of reflectivity and Doppler-derived fall speeds are used in conjunction with the radiometric measurements to identify 1-D profiles of precipitation particle types, sizes, and concentrations that are consistent with the observations.

A Theoretical Analysis of Why Hybrid Ensembles Work.

PubMed

Hsu, Kuo-Wei

2017-01-01

Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

Responses of water environment to tidal flat reduction in Xiangshan Bay: Part I hydrodynamics

NASA Astrophysics Data System (ADS)

Li, Li; Guan, Weibing; Hu, Jianyu; Cheng, Peng; Wang, Xiao Hua

2018-06-01

Xiangshan Bay consists of a deep tidal channel and three shallow inlets. A large-scale tidal flat has been utilized through coastal construction. To ascertain the accumulate influences of these engineering projects upon the tidal dynamics of the channel-inlets system, this study uses FVCOM to investigate the tides and flow asymmetries of the bay, and numerically simulate the long-term variations of tidal dynamics caused by the loss of tidal flats. It was found that the reduction of tidal flat areas from 1963 to 2010 slightly dampened M2 tidal amplitudes (0.1 m, ∼6%) and advanced its phases by reducing shoaling effects, while amplified M4 tidal amplitudes (0.09 m, ∼27%) and advanced its phases by reducing bottom friction, in the inner bay. Consequently, the ebb dominance was dampened indicated by reduced absolute value of elevation skewness (∼20%) in the bay. The tides and tidal asymmetry were impacted by the locations, areas and slopes of the tidal flats through changing tidal prism, shoaling effect and bottom friction, and consequently impacted tidal duration asymmetry in the bay. Tides and tidal asymmetry were more sensitive to the tidal flat at the head of the bay than the side bank. Reduced/increased tidal flat slopes around the Tie inlet dampened the ebb dominance. Tidal flat had a role in dissipating the M4 tide rather than generating it, while the advection only play a secondary role in generating the M4 tide. The full-length tidal flats reclamation would trigger the reverse of ebb to flood dominance in the bay. This study would be applicable for similar narrow bays worldwide.

Intense Convective Activity Over Northern Bay of Bengal during Late Southwest Monsoon

NASA Astrophysics Data System (ADS)

Mathew, S.; Venkatesan, R.; Natesan, U.; G, L.

2016-02-01

Warming of the northern Bay of Bengal during late southwest monsoon was very much influenced by the intensity of freshening by river discharges. The inter-annual variability of freshening and associated warming was analyzed for 2011 to 2015, with the help of in-situ data obtained from the moored buoys deployed at specific locations in northern Bay of Bengal. The shoaling of mixed layer depth associated with the advection of freshwaters has favored intense warming and supported convective activity thereby. The year 2011 recorded highest freshening with salinity touched as low as 21.3 p.s.u.; with the heavy river discharges, resulted from intense rainfall over catchment areas of rivers that discharged into the bay, due to positive Indian Ocean Dipole and La-Nina affect. It has resulted in intense warming of the surface temperature by 2°C, which persisted for nearly three weeks. The year 2014 was least fresh, with no signature of freshening and associated warming. The latent heat flux term computed from the moored buoy using the COARE 3.5 algorithm showed increased loss of latent heat flux during the late monsoon associated with the warming. It directly supported increased convective activity and delayed the withdrawal of monsoon activity from Indian sub-continent. Two depressions with intense convective activity formed over bay during September of 2011 which delayed the withdrawal of monsoon by three weeks.

Reconstructing the history of eastern and central Florida Bay using mollusk-shell isotope records

USGS Publications Warehouse

Halley, R.B.; Roulier, L.M.

1999-01-01

Stable isotopic ratios of carbon and oxygen (??13C and ??18O) from mollusk shells reflect the water quality characteristics of Florida Bay and can be used to characterize the great temporal variability of the bay. Values of ?? 18O are directly influenced by temperature and evaporation and may be related to salinity. ??13C values of ??13C are sensitive to organic and inorganic sources of carbon and are influenced by productivity. Analyses of eight mollusk species from five short-core localities across Florida Bay show large ranges in the values of ??13C and ??18O, and reflect the variation of the bay over decades. Samples from southwestern Florida Bay have distinct ??13C values relative to samples collected in northeastern Florida Bay, and intermediate localities have intermediate values. 13C values of ??13C grade from marine in the southwest bay to more estuarine in the northeast. Long cores (> 1 m) with excellent chronologies were analyzed from central and eastern Florida Bay. Preliminary analyses of Brachiodontes exustus and Transenella spp. from the cores showed that both ??13C and ??18O changed during the first part of the twentieth century. After a century of relative stability during the 1800s, ??13C decreased between about 1910 and 1940, then stabilized at these new values for the next five decades. The magnitude of the reduction in ??13C values increased toward the northeast. Using a carbon budget model, reduced ??13C values are interpreted as resulting from decreased circulation in the bay, probably associated with decreased freshwater flow into the Bay. Mollusk shell ??18O values display several negative excursions during the 1800s, suggesting that the bay was less evaporitic than during the twentieth century. The isotope records indicate a fundamental change took place in Florida Bay circulation early in the twentieth century. The timing of the change links it to railroad building and early drainage efforts in South Florida rather than to flood control and water management measures initiated after World War II.

Total variation-based neutron computed tomography

NASA Astrophysics Data System (ADS)

Barnard, Richard C.; Bilheux, Hassina; Toops, Todd; Nafziger, Eric; Finney, Charles; Splitter, Derek; Archibald, Rick

2018-05-01

We perform the neutron computed tomography reconstruction problem via an inverse problem formulation with a total variation penalty. In the case of highly under-resolved angular measurements, the total variation penalty suppresses high-frequency artifacts which appear in filtered back projections. In order to efficiently compute solutions for this problem, we implement a variation of the split Bregman algorithm; due to the error-forgetting nature of the algorithm, the computational cost of updating can be significantly reduced via very inexact approximate linear solvers. We present the effectiveness of the algorithm in the significantly low-angular sampling case using synthetic test problems as well as data obtained from a high flux neutron source. The algorithm removes artifacts and can even roughly capture small features when an extremely low number of angles are used.

Regional distribution of the high-altitude clouds over the Indian subcontinent and surrounding oceanic regions based on seven years of satellite observations

NASA Astrophysics Data System (ADS)

Meenu, S.; Rajeev, K.; Parameswaran, K.; Suresh Raju, C.

2006-12-01

Quantitative estimates of the spatio-temporal variations in deep convective events over the Indian subcontinent, Arabian Sea, Bay of Bengal, and tropical Indian Ocean are carried out using the data obtained from Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-14 and NOAA-16 during the period 1996-2003. Pixels having thermal IR brightness temperature (BT) less than 245K are considered as high altitude clouds and those having BT<220 K are considered as very high altitude clouds. Very deep convective clouds are observed over north Bay of Bengal during the Asian summer monsoon season when the mean cloud top temperature reaches as low as 190K. Over the Head Bay of Bengal (HBoB) from June to September, more than 50% of the observed clouds are deep convective type and more than half of these deep convective clouds are very deep convective clouds. Histogram analysis of the cloud top temperatures during this period shows that over HBoB the most prominent cloud top temperature of the deep convective clouds is ~205K over the HBoB while that over southeast Arabian Sea (SEAS) is ~220K. This indicates that most probably the cloud top altitude over HBoB is ~2 km larger than that over SEAS during the Asian summer monsoon period. Another remarkable feature observed during the Asian summer monsoon period is the significantly low values of deep convective clouds observed over the south Bay of Bengal close to Srilanka, which appears as a large pool of reduced cloud amount surrounded by regions of large-scale deep convection. Over both SEAS and HBoB, the total, deep convective and very deep convective cloud amounts as well as their corresponding cloud top temperatures (or the altitude of the cloud top) undergo large seasonal variations, while such variations are less prominent over the eastern equatorial Indian Ocean.

Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay

DOE PAGES

An, F. P.; Balantekin, A. B.; Band, H. R.; ...

2017-06-19

Here, the Daya Bay experiment has observed correlations between reactor core fuel evolution and changes in the reactor antineutrino flux and energy spectrum. Four antineutrino detectors in two experimental halls were used to identify 2.2 million inverse beta decays (IBDs) over 1230 days spanning multiple fuel cycles for each of six 2.9 GW th reactor cores at the Daya Bay and Ling Ao nuclear power plants. Using detector data spanning effective 239Pu fission fractions F 239 from 0.25 to 0.35, Daya Bay measures an average IBD yield ¯σf of (5.90±0.13)×10 –43 cm 2/fission and a fuel-dependent variation in the IBDmore » yield, dσ f/dF 239, of (–1.86±0.18)×10 –43 cm 2/fission. This observation rejects the hypothesis of a constant antineutrino flux as a function of the 239Pu fission fraction at 10 standard deviations. The variation in IBD yield is found to be energy dependent, rejecting the hypothesis of a constant antineutrino energy spectrum at 5.1 standard deviations. While measurements of the evolution in the IBD spectrum show general agreement with predictions from recent reactor models, the measured evolution in total IBD yield disagrees with recent predictions at 3.1σ. This discrepancy indicates that an overall deficit in the measured flux with respect to predictions does not result from equal fractional deficits from the primary fission isotopes 235U, 239Pu, 238U, and 241Pu. Based on measured IBD yield variations, yields of (6.17±0.17) and (4.27±0.26)×10 –43 cm 2/fission have been determined for the two dominant fission parent isotopes 235U and 239Pu. A 7.8% discrepancy between the observed and predicted 235U yields suggests that this isotope may be the primary contributor to the reactor antineutrino anomaly.« less

Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay.

PubMed

An, F P; Balantekin, A B; Band, H R; Bishai, M; Blyth, S; Cao, D; Cao, G F; Cao, J; Chan, Y L; Chang, J F; Chang, Y; Chen, H S; Chen, Q Y; Chen, S M; Chen, Y X; Chen, Y; Cheng, J; Cheng, Z K; Cherwinka, J J; Chu, M C; Chukanov, A; Cummings, J P; Ding, Y Y; Diwan, M V; Dolgareva, M; Dove, J; Dwyer, D A; Edwards, W R; Gill, R; Gonchar, M; Gong, G H; Gong, H; Grassi, M; Gu, W Q; Guo, L; Guo, X H; Guo, Y H; Guo, Z; Hackenburg, R W; Hans, S; He, M; Heeger, K M; Heng, Y K; Higuera, A; Hsiung, Y B; Hu, B Z; Hu, T; Huang, E C; Huang, H X; Huang, X T; Huang, Y B; Huber, P; Huo, W; Hussain, G; Jaffe, D E; Jen, K L; Ji, X P; Ji, X L; Jiao, J B; Johnson, R A; Jones, D; Kang, L; Kettell, S H; Khan, A; Kohn, S; Kramer, M; Kwan, K K; Kwok, M W; Langford, T J; Lau, K; Lebanowski, L; Lee, J; Lee, J H C; Lei, R T; Leitner, R; Leung, J K C; Li, C; Li, D J; Li, F; Li, G S; Li, Q J; Li, S; Li, S C; Li, W D; Li, X N; Li, X Q; Li, Y F; Li, Z B; Liang, H; Lin, C J; Lin, G L; Lin, S; Lin, S K; Lin, Y-C; Ling, J J; Link, J M; Littenberg, L; Littlejohn, B R; Liu, J L; Liu, J C; Loh, C W; Lu, C; Lu, H Q; Lu, J S; Luk, K B; Ma, X Y; Ma, X B; Ma, Y Q; Malyshkin, Y; Martinez Caicedo, D A; McDonald, K T; McKeown, R D; Mitchell, I; Nakajima, Y; Napolitano, J; Naumov, D; Naumova, E; Ngai, H Y; Ochoa-Ricoux, J P; Olshevskiy, A; Pan, H-R; Park, J; Patton, S; Pec, V; Peng, J C; Pinsky, L; Pun, C S J; Qi, F Z; Qi, M; Qian, X; Qiu, R M; Raper, N; Ren, J; Rosero, R; Roskovec, B; Ruan, X C; Steiner, H; Stoler, P; Sun, J L; Tang, W; Taychenachev, D; Treskov, K; Tsang, K V; Tull, C E; Viaux, N; Viren, B; Vorobel, V; Wang, C H; Wang, M; Wang, N Y; Wang, R G; Wang, W; Wang, X; Wang, Y F; Wang, Z; Wang, Z; Wang, Z M; Wei, H Y; Wen, L J; Whisnant, K; White, C G; Whitehead, L; Wise, T; Wong, H L H; Wong, S C F; Worcester, E; Wu, C-H; Wu, Q; Wu, W J; Xia, D M; Xia, J K; Xing, Z Z; Xu, J L; Xu, Y; Xue, T; Yang, C G; Yang, H; Yang, L; Yang, M S; Yang, M T; Yang, Y Z; Ye, M; Ye, Z; Yeh, M; Young, B L; Yu, Z Y; Zeng, S; Zhan, L; Zhang, C; Zhang, C C; Zhang, H H; Zhang, J W; Zhang, Q M; Zhang, R; Zhang, X T; Zhang, Y M; Zhang, Y X; Zhang, Y M; Zhang, Z J; Zhang, Z Y; Zhang, Z P; Zhao, J; Zhou, L; Zhuang, H L; Zou, J H

2017-06-23

The Daya Bay experiment has observed correlations between reactor core fuel evolution and changes in the reactor antineutrino flux and energy spectrum. Four antineutrino detectors in two experimental halls were used to identify 2.2 million inverse beta decays (IBDs) over 1230 days spanning multiple fuel cycles for each of six 2.9 GW_{th} reactor cores at the Daya Bay and Ling Ao nuclear power plants. Using detector data spanning effective ^{239}Pu fission fractions F_{239} from 0.25 to 0.35, Daya Bay measures an average IBD yield σ[over ¯]_{f} of (5.90±0.13)×10^{-43}  cm^{2}/fission and a fuel-dependent variation in the IBD yield, dσ_{f}/dF_{239}, of (-1.86±0.18)×10^{-43}  cm^{2}/fission. This observation rejects the hypothesis of a constant antineutrino flux as a function of the ^{239}Pu fission fraction at 10 standard deviations. The variation in IBD yield is found to be energy dependent, rejecting the hypothesis of a constant antineutrino energy spectrum at 5.1 standard deviations. While measurements of the evolution in the IBD spectrum show general agreement with predictions from recent reactor models, the measured evolution in total IBD yield disagrees with recent predictions at 3.1σ. This discrepancy indicates that an overall deficit in the measured flux with respect to predictions does not result from equal fractional deficits from the primary fission isotopes ^{235}U, ^{239}Pu, ^{238}U, and ^{241}Pu. Based on measured IBD yield variations, yields of (6.17±0.17) and (4.27±0.26)×10^{-43}  cm^{2}/fission have been determined for the two dominant fission parent isotopes ^{235}U and ^{239}Pu. A 7.8% discrepancy between the observed and predicted ^{235}U yields suggests that this isotope may be the primary contributor to the reactor antineutrino anomaly.

Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay

NASA Astrophysics Data System (ADS)

An, F. P.; Balantekin, A. B.; Band, H. R.; Bishai, M.; Blyth, S.; Cao, D.; Cao, G. F.; Cao, J.; Chan, Y. L.; Chang, J. F.; Chang, Y.; Chen, H. S.; Chen, Q. Y.; Chen, S. M.; Chen, Y. X.; Chen, Y.; Cheng, J.; Cheng, Z. K.; Cherwinka, J. J.; Chu, M. C.; Chukanov, A.; Cummings, J. P.; Ding, Y. Y.; Diwan, M. V.; Dolgareva, M.; Dove, J.; Dwyer, D. A.; Edwards, W. R.; Gill, R.; Gonchar, M.; Gong, G. H.; Gong, H.; Grassi, M.; Gu, W. Q.; Guo, L.; Guo, X. H.; Guo, Y. H.; Guo, Z.; Hackenburg, R. W.; Hans, S.; He, M.; Heeger, K. M.; Heng, Y. K.; Higuera, A.; Hsiung, Y. B.; Hu, B. Z.; Hu, T.; Huang, E. C.; Huang, H. X.; Huang, X. T.; Huang, Y. B.; Huber, P.; Huo, W.; Hussain, G.; Jaffe, D. E.; Jen, K. L.; Ji, X. P.; Ji, X. L.; Jiao, J. B.; Johnson, R. A.; Jones, D.; Kang, L.; Kettell, S. H.; Khan, A.; Kohn, S.; Kramer, M.; Kwan, K. K.; Kwok, M. W.; Langford, T. J.; Lau, K.; Lebanowski, L.; Lee, J.; Lee, J. H. C.; Lei, R. T.; Leitner, R.; Leung, J. K. C.; Li, C.; Li, D. J.; Li, F.; Li, G. S.; Li, Q. J.; Li, S.; Li, S. C.; Li, W. D.; Li, X. N.; Li, X. Q.; Li, Y. F.; Li, Z. B.; Liang, H.; Lin, C. J.; Lin, G. L.; Lin, S.; Lin, S. K.; Lin, Y.-C.; Ling, J. J.; Link, J. M.; Littenberg, L.; Littlejohn, B. R.; Liu, J. L.; Liu, J. C.; Loh, C. W.; Lu, C.; Lu, H. Q.; Lu, J. S.; Luk, K. B.; Ma, X. Y.; Ma, X. B.; Ma, Y. Q.; Malyshkin, Y.; Martinez Caicedo, D. A.; McDonald, K. T.; McKeown, R. D.; Mitchell, I.; Nakajima, Y.; Napolitano, J.; Naumov, D.; Naumova, E.; Ngai, H. Y.; Ochoa-Ricoux, J. P.; Olshevskiy, A.; Pan, H.-R.; Park, J.; Patton, S.; Pec, V.; Peng, J. C.; Pinsky, L.; Pun, C. S. J.; Qi, F. Z.; Qi, M.; Qian, X.; Qiu, R. M.; Raper, N.; Ren, J.; Rosero, R.; Roskovec, B.; Ruan, X. C.; Steiner, H.; Stoler, P.; Sun, J. L.; Tang, W.; Taychenachev, D.; Treskov, K.; Tsang, K. V.; Tull, C. E.; Viaux, N.; Viren, B.; Vorobel, V.; Wang, C. H.; Wang, M.; Wang, N. Y.; Wang, R. G.; Wang, W.; Wang, X.; Wang, Y. F.; Wang, Z.; Wang, Z.; Wang, Z. M.; Wei, H. Y.; Wen, L. J.; Whisnant, K.; White, C. G.; Whitehead, L.; Wise, T.; Wong, H. L. H.; Wong, S. C. F.; Worcester, E.; Wu, C.-H.; Wu, Q.; Wu, W. J.; Xia, D. M.; Xia, J. K.; Xing, Z. Z.; Xu, J. L.; Xu, Y.; Xue, T.; Yang, C. G.; Yang, H.; Yang, L.; Yang, M. S.; Yang, M. T.; Yang, Y. Z.; Ye, M.; Ye, Z.; Yeh, M.; Young, B. L.; Yu, Z. Y.; Zeng, S.; Zhan, L.; Zhang, C.; Zhang, C. C.; Zhang, H. H.; Zhang, J. W.; Zhang, Q. M.; Zhang, R.; Zhang, X. T.; Zhang, Y. M.; Zhang, Y. X.; Zhang, Y. M.; Zhang, Z. J.; Zhang, Z. Y.; Zhang, Z. P.; Zhao, J.; Zhou, L.; Zhuang, H. L.; Zou, J. H.; Daya Bay Collaboration

2017-06-01

The Daya Bay experiment has observed correlations between reactor core fuel evolution and changes in the reactor antineutrino flux and energy spectrum. Four antineutrino detectors in two experimental halls were used to identify 2.2 million inverse beta decays (IBDs) over 1230 days spanning multiple fuel cycles for each of six 2.9 G Wth reactor cores at the Daya Bay and Ling Ao nuclear power plants. Using detector data spanning effective 239Pu fission fractions F239 from 0.25 to 0.35, Daya Bay measures an average IBD yield σ¯f of (5.90 ±0.13 )×10-43 cm2/fission and a fuel-dependent variation in the IBD yield, d σf/d F239, of (-1.86 ±0.18 )×10-43 cm2/fission . This observation rejects the hypothesis of a constant antineutrino flux as a function of the 239Pu fission fraction at 10 standard deviations. The variation in IBD yield is found to be energy dependent, rejecting the hypothesis of a constant antineutrino energy spectrum at 5.1 standard deviations. While measurements of the evolution in the IBD spectrum show general agreement with predictions from recent reactor models, the measured evolution in total IBD yield disagrees with recent predictions at 3.1 σ . This discrepancy indicates that an overall deficit in the measured flux with respect to predictions does not result from equal fractional deficits from the primary fission isotopes 235U, 239Pu, 238U, and 241Pu. Based on measured IBD yield variations, yields of (6.17 ±0.17 ) and (4.27 ±0.26 )×10-43 cm2 /fission have been determined for the two dominant fission parent isotopes 235U and 239Pu. A 7.8% discrepancy between the observed and predicted 235U yields suggests that this isotope may be the primary contributor to the reactor antineutrino anomaly.

Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay

DOE Office of Scientific and Technical Information (OSTI.GOV)

An, F. P.; Balantekin, A. B.; Band, H. R.

Here, the Daya Bay experiment has observed correlations between reactor core fuel evolution and changes in the reactor antineutrino flux and energy spectrum. Four antineutrino detectors in two experimental halls were used to identify 2.2 million inverse beta decays (IBDs) over 1230 days spanning multiple fuel cycles for each of six 2.9 GW th reactor cores at the Daya Bay and Ling Ao nuclear power plants. Using detector data spanning effective 239Pu fission fractions F 239 from 0.25 to 0.35, Daya Bay measures an average IBD yield ¯σf of (5.90±0.13)×10 –43 cm 2/fission and a fuel-dependent variation in the IBDmore » yield, dσ f/dF 239, of (–1.86±0.18)×10 –43 cm 2/fission. This observation rejects the hypothesis of a constant antineutrino flux as a function of the 239Pu fission fraction at 10 standard deviations. The variation in IBD yield is found to be energy dependent, rejecting the hypothesis of a constant antineutrino energy spectrum at 5.1 standard deviations. While measurements of the evolution in the IBD spectrum show general agreement with predictions from recent reactor models, the measured evolution in total IBD yield disagrees with recent predictions at 3.1σ. This discrepancy indicates that an overall deficit in the measured flux with respect to predictions does not result from equal fractional deficits from the primary fission isotopes 235U, 239Pu, 238U, and 241Pu. Based on measured IBD yield variations, yields of (6.17±0.17) and (4.27±0.26)×10 –43 cm 2/fission have been determined for the two dominant fission parent isotopes 235U and 239Pu. A 7.8% discrepancy between the observed and predicted 235U yields suggests that this isotope may be the primary contributor to the reactor antineutrino anomaly.« less

The changing seascape of Galway Bay, Western Ireland

NASA Astrophysics Data System (ADS)

Mc Cullagh, D.; Benetti, S.; Plets, R. M. K.; Edwards, R.

2016-12-01

During the late Quaternary significant environmental and relative sea-level variations have contributed to shaping present day coastlines. This is particularly evident along formerly glaciated continental margins. Strong evidence of these changes are recorded in Galway Bay, Western Ireland. This research uses a multidisciplinary approach. Seismic and multibeam data, sedimentological, micropaleontological, geochemical analysis and 15 radiocarbon dates of sediment cores from the bay provide post last glacial maximum (LGM) sea level and environmental reconstructions for the region. The acoustic stratigraphy of the bay includes 3 seismic units: the deepest unit represents the acoustic basement, composed of limestone and granite bedrock; the middle unit is composed of the oldest preserved sediments, deposited during and after the LGM, and interpreted to be glacial till. The uppermost unit represents deposition and reworking after glacial retreat. The erosive action of the ice sheet that extended off the Irish coast is thought to be responsible for the removal and reworking of all sediments older that the LGM. In the sediment cores, three main lithofacies were identified: 1) a sandy silt and clay facies, 2) a distinct shell hash interlayer and, 3) a fine silty sand facies. These 3 facies are found within the uppermost seismic unit, and initial radiocarbon dating of shells in 4 cores, constrain these sediments and the uppermost seismic unit to the Holocene. Preliminary qualitative analysis on foraminifera from several cores shows a general trend of progression from estuarine to open marine conditions, inferred from indicator species. This trend is supported by X-ray fluorescence (XRF) analysis which shows increased ratios of Cl/Fe in younger deposits. Constraining dates on sea level variations in the region will be added to the sea level database for Ireland and possibly used to adjust the existing relative sea level models. These are important for understating past sea level variations and modelling future trends.

Assessment of remotely sensed chlorophyll-a concentration in Guanabara Bay, Brazil

NASA Astrophysics Data System (ADS)

Oliveira, Eduardo N.; Fernandes, Alexandre M.; Kampel, Milton; Cordeiro, Renato C.; Brandini, Nilva; Vinzon, Susana B.; Grassi, Renata M.; Pinto, Fernando N.; Fillipo, Alessandro M.; Paranhos, Rodolfo

2016-04-01

The Guanabara Bay (GB) is an estuarine system in the metropolitan region of Rio de Janeiro (Brazil), with a surface area of ˜346 km2 threatened by anthropogenic pressure. Remote sensing can provide frequent data for studies and monitoring of water quality parameters, such as chlorophyll-a concentration (Chl-a). Different combination of Medium Resolution Imaging Spectrometer (MERIS) remote sensing reflectance band ratios were used to estimate Chl-a. Standard algorithms such as Ocean Color 3-band, Ocean Color-4 band, fluorescence line height, and maximum chlorophyll index were also tested. The MERIS Chl-a estimates were statistically compared with a dataset of in situ Chl-a (2002 to 2012). Good correlations were obtained with the use of green, red, and near-infrared bands. The best performing algorithm was based on the red (665 nm) and green (560 nm) band ratio, named "RG3" algorithm (r2=0.71, chl-a=62,565*x1.6118). The RG3 was applied to a time series of MERIS images (2003- to 2012). The GB has a high temporal and spatial variability of Chl-a, with highest values found in the wet season (October to March) and in some of the most internal regions of the estuary. Lowest concentrations are found in the central circulation channel due to the flushing of ocean water masses promoted by pumping tide.

Vertical Structure of Aerosols and Mineral Dust Over the Bay of Bengal From Multisatellite Observations

NASA Astrophysics Data System (ADS)

Lakshmi, N. B.; Nair, Vijayakumar S.; Suresh Babu, S.

2017-12-01

The vertical distribution of aerosol and dust extinction coefficient over the Bay of Bengal is examined using the satellite observations (Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and Moderate Resolution Imaging Spectroradiometer (MODIS)) for the period from 2006 to 2017. Distinct seasonal pattern is observed in the vertical structure of both aerosol and dust over the Bay of Bengal with an enhancement of 24% in the aerosol extinction above 1 km from winter (December, January and February) to premonsoon (March, April, and May). Significant contribution of dust is observed over the northern Bay of Bengal during premonsoon season where 22% of the total aerosol extinction is contributed by dust aerosols transported from the nearby continental regions. During winter, dust transport is found to be less significant with fractional contribution of 10%-13% to the total aerosol optical depth over the Bay of Bengal. MODIS-derived dust fraction (fine mode based) shows an overestimation up to twofold compared to CALIOP dust fraction (depolarization based), whereas the Goddard Chemistry Aerosol Radiation and Transport-simulated dust fraction underestimates the satellite-derived dust fractions over the Bay of Bengal. Though the long-term variation in dust aerosol showed a decreasing trend over the Bay of Bengal, the confidence level is insufficient in establishing the robustness of the observed trend. However, significant dust-induced heating is observed above the boundary layer during premonsoon season. This dust-induced elevated heating can affect the convection over the Bay of Bengal which will have implication on the monsoon dynamics over the Indian region.

Stormwater impact in Guanabara Bay (Rio de Janeiro): Evidences of seasonal variability in the dynamic of the sediment heavy metals

NASA Astrophysics Data System (ADS)

Fonseca, E. M.; Baptista Neto, J. A.; Silva, C. G.; McAlister, J. J.; Smith, B. J.; Fernandez, M. A.

2013-09-01

Guanabara Bay is one of the most prominent coastal bays in Brazil. This environment is an estuary of 91 rivers and channels, surrounded by the metropolis of Rio de Janeiro. The bay receives considerable amounts of contaminants introduced from sewage effluents, industrial discharge, urban and agricultural runoff, atmospheric fallout, and the combined inputs from the rivers, making Guanabara Bay one of the most polluted coastal environments on the Brazilian coastline. The aim of this work is to study the concentration and fractionation of the heavy metals within the sediments of the bay. In order to understand the possible seasonal influence on the heavy metal fractionation, two campaigns were carried out in two different seasons of the year (rainy and dry). Twelve stations, in four different areas, with different oceanographic characteristics, where chosen. To assess the bioavailability of the metals a selective extraction procedure was used to study the geochemical fractionation and bioavailability of Zn, Cu, Cr, Ni and Pb. The rainy season was very important with respect to variation in the total concentrations of Cr, Ni and Pb and their fractionation within different "operational" phases present in Guanabara Bay sediments. The water-soluble phase showed little importance, with respect to metal adsorption and this would suggest very low mobility of metals in the water column. Nevertheless, the potentially available metals within these sediments showed a high probability for their release and therefore cause contamination of the water column, since different parts of the bay are constantly subjected to dredging projects promoted by the harbor authorities.

Spatial distribution of dinoflagellates from the tropical coastal waters of the South Andaman, India: Implications for coastal pollution monitoring.

PubMed

Narale, Dhiraj Dhondiram; Anil, Arga Chandrashekar

2017-02-15

Dinoflagellate community structure from two semi-enclosed areas along the South Andaman region, India, was investigated to assess the anthropogenic impact on coastal water quality. At the densely inhabited Port Blair Bay, the dominance of mixotrophs in water and Protoperidinoids in sediments was attributed to anthropogenic nutrient enrichment and prey availability. A significant decrease in dinoflagellate abundance from inner to outer bay emphasize the variation in nutrient availability. The dominance of autotrophs and Gonyaulacoid cysts at the North Bay highlight low nutrient conditions with less anthropogenic pressure. The occurrence of oceanic Ornithocercus steinii and Diplopsalis sp. could evince the oceanic water intrusion into the North Bay. Nine potentially harmful and red-tide-forming species including Alexandrium tamarense complex, A. minutum were identified in this study. Although there are no harmful algal bloom (HABs) incidences in this region so far, increasing coastal pollution could support their candidature towards the future HABs initiation and development. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting the vertical structure of tidal current and salinity in San Francisco Bay, California

USGS Publications Warehouse

Ford, Michael; Wang, Jia; Cheng, Ralph T.

1990-01-01

A two-dimensional laterally averaged numerical estuarine model is developed to study the vertical variations of tidal hydrodynamic properties in the central/north part of San Francisco Bay, California. Tidal stage data, current meter measurements, and conductivity, temperature, and depth profiling data in San Francisco Bay are used for comparison with model predictions. An extensive review of the literature is conducted to assess the success and failure of previous similar investigations and to establish a strategy for development of the present model. A σ plane transformation is used in the vertical dimension to alleviate problems associated with fixed grid model applications in the bay, where the tidal range can be as much as 20–25% of the total water depth. Model predictions of tidal stage and velocity compare favorably with the available field data, and prototype salinity stratification is qualitatively reproduced. Conclusions from this study as well as future model applications and research needs are discussed.

Spatial distribution of heavy metals in surficial sediments from Guanabara Bay: Rio de Janeiro, Brazil

NASA Astrophysics Data System (ADS)

Neto, José Antônio Baptista; Gingele, Franz Xaver; Leipe, Thomas; Brehme, Isa

2006-04-01

Ninety-two surface sediment samples were collected in Guanabara Bay, one of the most prominent urban bays in SE Brazil, to investigate the spatial distribution of anthropogenic pollutants. The concentrations of heavy metals, organic carbon and particle size were examined in all samples. Large spatial variations of heavy metals and particle size were observed. The highest concentrations of heavy metals were found in the muddy sediments from the north western region of the bay near the main outlets of the most polluted rivers, municipal waste drainage systems and one of the major oil refineries. Another anomalous concentration of metals was found adjacent to Rio de Janeiro Harbour. The heavy metal concentrations decrease to the northeast, due to intact rivers and the mangrove systems in this area, and to the south where the sand fraction and open-marine processes dominate. The geochemical normalization of metal data to Li or Al has also demonstrated that the anthropogenic input of heavy metals have altered the natural sediment heavy metal distribution.

Variational optimization algorithms for uniform matrix product states

NASA Astrophysics Data System (ADS)

Zauner-Stauber, V.; Vanderstraeten, L.; Fishman, M. T.; Verstraete, F.; Haegeman, J.

2018-01-01

We combine the density matrix renormalization group (DMRG) with matrix product state tangent space concepts to construct a variational algorithm for finding ground states of one-dimensional quantum lattices in the thermodynamic limit. A careful comparison of this variational uniform matrix product state algorithm (VUMPS) with infinite density matrix renormalization group (IDMRG) and with infinite time evolving block decimation (ITEBD) reveals substantial gains in convergence speed and precision. We also demonstrate that VUMPS works very efficiently for Hamiltonians with long-range interactions and also for the simulation of two-dimensional models on infinite cylinders. The new algorithm can be conveniently implemented as an extension of an already existing DMRG implementation.

Using Hyperspectral Remote Sensing Models to Determine Phytoplankton Density in the Coastal Waters of Long Bay, South Carolina

NASA Astrophysics Data System (ADS)

Harrington, J. E.; Ali, K.

2013-12-01

The southeast coastal region is one of the fastest growing regions in the United States and the increasing utilization of open water bodies has led to the deterioration of water quality and aquatic ecology, placing the future of these resources at risk. In coastal zones, a key index that can be used to assess the stress on the environment is the water quality. The shallow nearshore waters of Long Bay, South Carolina (SC) are heavily influenced by multiple biogeochemical constituents or color producing agents (CPAs) such as, phytoplankton, suspend matter, and dissolved organic carbon. The interaction of the various chemical, biological and physical components gives rise to the optical complexity observed in the coastal waters producing turbid waters. Ecological stress on these environments is reflected by the increase in the frequency and severity of Harmful Algal Blooms (HABs), a prime agent of water quality deterioration, including foul odors and tastes, deoxygenation of bottom waters (hypoxia), toxicity, fish kills, and food web alterations. These are of great concern for human health and are detrimental to the marine life. Therefore, efficient monitoring tools are required for early detection and forecasting purposes as well as to understand the state of the conditions and better protect, manage and address the question of how various natural and anthropogenic factors affect the health of these environments. This study assesses the efficiency remote sensing as a potential tool for accurate and timely detection of HABs, as well as for providing high spatial and temporal resolution information regarding the biogeodynamics in coastal water bodies. Existing blue-green and NIR-red based remote sensing algorithms are applied to the reflectance data obtained using ASD spectroradiometer to predict the amount of chlorophyll, an independent of other associated CPAs in the Long Bay waters. The pigment is the primary light harvesting pigment in all phytoplankton and is used as an index for the estimation of phytoplankton density. Efficiency of the algorithms were evaluated through a least squares regression and residual analysis. Results show that for prediction models of chlorophyll a concentrations, the Oc4v4 by Reilly et al (2000), two -band blue-green empirical algorithm yielded coefficients of determination as high as 0.64 with RMSE=0.29μg/l for an aggregated dataset (n=62, P<0.05). The NIR-red -based two-band algorithm by Dekker et al. (1993) and Gitelson et al. (2000) gave the best chlorophyll a prediction model, with R2 =0.79, RMSE=0.19μg/l. The results illustrate the potential of remote sensing in accounting for the chlorophyll a variability in the turbid waters of Long Bay, SC.

Correlation of chlorophyll, suspended matter, and related parameters of waters in the lower Chesapeake Bay area to LANDSAT-1 imagery

NASA Technical Reports Server (NTRS)

Fleischer, P. (Principal Investigator); Bowker, D. E.; Witte, W. G.; Gosink, T. A.; Hanna, W. J.; Ludwick, J. C.

1976-01-01

The author has identified the following significant results. An effort to relate water parameters of the lower Chesapeake Bay area to multispectral scanner images of LANDSAT 1 has shown that some spectral bands can be correlated to water parameters, and has demonstrated the feasibility of synoptic mapping of estuaries by satellite. Bands 5 and 6 were shown to be useful for monitoring total particles. Band 5 showed high correlation with suspended sediment concentration. Attenuation coefficients monitored continuously by ship along three baselines were cross correlated with radiance values on three days. Improved correlations resulted when tidal conditions were taken into consideration. A contouring program was developed to display sediment variation in the lower Chesapeake Bay from the MSS bands.

The holocene biochronostratigraphy and paleoenvironment in Dvina Bay from benthic foraminiferal studies of the White Sea

NASA Astrophysics Data System (ADS)

Saidova, Kh. M.

2010-08-01

The compositional changes and frequency variations in the foraminiferal communities through the sediment section across Dvina Bay allow us to identify 14 ecological-stratigraphic zones. Based on the 14C dates for the foraminiferal tests, the distinguished ecozones correspond to the appropriate Holocene stages and substages. Because most of the foraminiferal species identified in the Holocene sediments are abundant and diverse in the modern oceans, they provide a powerful tool for the reconstruction of the paleoenvironmental changes during the Holocene.

Phytoplankton assemblages within the Chesapeake Bay plume and adjacent waters of the continental shelf

NASA Technical Reports Server (NTRS)

Marshall, H. G.

1981-01-01

The Chesapeake Bay plume was identified and plotted in relation to the presence and high concentrations of phytoplankton assemblages. Seasonal differences occurred within the plume during the collection period, with Skeletonema costatum and an ultraplankton component the dominant forms. Patchiness was found along the transects, with variations in composition and concentrations common on consecutive day sampling within the plume in its movement along the shelf. The presence of 236 species is noted, with their presence indicated for plume and shelf stations during the March, June, and October 1980 collections.

A class of parallel algorithms for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

Parallel and parallel/pipeline algorithms for computation of the manipulator inertia matrix are presented. An algorithm based on composite rigid-body spatial inertia method, which provides better features for parallelization, is used for the computation of the inertia matrix. Two parallel algorithms are developed which achieve the time lower bound in computation. Also described is the mapping of these algorithms with topological variation on a two-dimensional processor array, with nearest-neighbor connection, and with cardinality variation on a linear processor array. An efficient parallel/pipeline algorithm for the linear array was also developed, but at significantly higher efficiency.

Local wind forcing of the Monterey Bay area inner shelf

USGS Publications Warehouse

Drake, P.T.; McManus, M.A.; Storlazzi, C.D.

2005-01-01

Wind forcing and the seasonal cycles of temperature and currents were investigated on the inner shelf of the Monterey Bay area of the California coast for 460 days, from June 2001 to September 2002. Temperature measurements spanned an approximate 100 km stretch of coastline from a bluff just north of Monterey Bay south to Point Sur. Inner shelf currents were measured at two sites near the bay's northern shore. Seasonal temperature variations were consistent with previous observations from the central California shelf. During the spring, summer and fall, a seasonal mean alongshore current was observed flowing northwestward in the northern bay, in direct opposition to a southeastward wind stress. A barotropic alongshore pressure gradient, potentially driving the northwestward flow, was needed to balance the alongshore momentum equation. With the exception of the winter season, vertical profiles of mean cross-shore currents were consistent with two-dimensional upwelling and existing observations from upwelling regions with poleward subsurface flow. At periods of 15-60 days, temperature fluctuations were coherent both throughout the domain and with the regional wind field. Remote wind forcing was minimal. During the spring upwelling season, alongshore currents and temperatures in the northern bay were most coherent with winds measured at a nearby land meteorological station. This wind site showed relatively low correlations to offshore buoy wind stations, indicating localized wind effects are important to the circulation along this stretch of Monterey Bay's inner shelf. ?? 2004 Elsevier Ltd. All rights reserved.

ElarmS Earthquake Early Warning System 2016 Performance and New Research

NASA Astrophysics Data System (ADS)

Chung, A. I.; Allen, R. M.; Hellweg, M.; Henson, I. H.; Neuhauser, D. S.

2016-12-01

The ElarmS earthquake early warning system has been detecting earthquakes throughout California since 2007. It is one of the algorithms that contributes to the West Coast ShakeAlert, a prototype earthquake early warning system being developed for the US West Coast. ElarmS is also running in the Pacific Northwest, and in Israel, Chile, Turkey, and Peru in test mode. We summarize the performance of the ElarmS system over the past year and review some of the more problematic events that the system has encountered. During the first half of 2016 (2016-01-01 through 2016-07-21), ElarmS successfully alerted on all events with ANSS catalog magnitudes M>3 in the Los Angeles area. The mean alert time for these 9 events was just 4.84 seconds. In the San Francisco Bay Area, ElarmS detected 26 events with ANSS catalog magnitudes M>3. The alert times for these events is 9.12 seconds. The alert times are longer in the Bay Area than in the Los Angeles area due to the sparser network of stations in the Bay Area. 7 Bay Area events were not detected by ElarmS. These events occurred in areas where there is less dense station coverage. In addition, ElarmS sent alerts for 13 of the 16 moderately-sized (ANSS catalog magnitudes M>4) events that occurred throughout the state of California. One of those missed events was a M4.5 that occurred far offshore in the northernmost part of the state. The other two missed events occurred inland in regions with sparse station coverage. Over the past year, we have worked towards the implementation of a new filterbank teleseismic filter algorithm, which we will discuss. Other than teleseismic events, a significant cause of false alerts and severely mislocated events is spurious triggers being associated with triggers from a real earthquake. Here, we address new approaches to filtering out problematic triggers.

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

PubMed

Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

2017-01-01

Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as we have done here, utilizing readily-available off-the-shelf machine learning techniques and resulting in only a fraction of narratives that require manual review. Human-machine ensemble methods are likely to improve performance over total manual coding. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evaluating the performance of distributed approaches for modal identification

NASA Astrophysics Data System (ADS)

Krishnan, Sriram S.; Sun, Zhuoxiong; Irfanoglu, Ayhan; Dyke, Shirley J.; Yan, Guirong

2011-04-01

In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

NASA Astrophysics Data System (ADS)

Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

2017-01-01

In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

Assessing Habitat Suitability at Multiple Scales: A Landscape-Level Approach

Treesearch

Kurt H. Riitters; R.V. O' Neill; K.B. Jones

1997-01-01

The distribution and abundance of many plants and animals are influenced by the spatial arrangement of suitable habitats across landscapes. We derived habitat maps from a digital land cover map of the ~178,000 km2 Chesapeake Bay Watershed by using a spatial filtering algorithm. The regional amounts and patterns of habitats were different for...

Detection Optimization of the Progressive Multi-Channel Correlation Algorithm Used in Infrasound Nuclear Treaty Monitoring

DTIC Science & Technology

2013-03-01

82 4.3.2 Bayes Decision Criteria and Risk Minimization ............................................ 86...on the globe. In its mission to achieve information superiority, AFTAC has historically combined data garnered from seismic and infrasound networks...to improve location estimates for nuclear events. For instance, underground explosions produce seismic waves that can couple into the atmosphere

Temperature variability caused by internal tides in the coral reef ecosystem of Hanauma bay, Hawai'i

NASA Astrophysics Data System (ADS)

Smith, Katharine A.; Rocheleau, Greg; Merrifield, Mark A.; Jaramillo, Sergio; Pawlak, Geno

2016-03-01

Hanauma Bay Nature Preserve is a shallow bay (<30 m depth) on the island of O'ahu, Hawai'i, offshore of which tidal flow over deep ridge topography (500-1000 m depth) is known to generate semidiurnal frequency internal tides. A field experiment was conducted during March to June 2009 to determine whether the deep internal tides propagate shoreward to influence variability in temperature and currents in the bay environment. Temperature observations in the bay exhibit a diurnal cycle that is strongest near the surface (upper 10 m) and is associated with solar heating. In early summer (May-June), as the upper mixed layer warms and a shallow seasonal thermocline develops, temperature fluctuations in deeper bay waters (>15 m depth) become dominated by large semidiurnal variations (up to 2.7 °C) that are attributed to the internal tide. These temperature drops caused by the internal tide occur consistently twice a day under summer stratification at depths as shallow as 15 m, while smaller temperature drops (up to 1.8 °C) occur occasionally at 5 m. Although semidiurnal band temperatures vary seasonally, semidiurnal band currents exhibit similar magnitudes in spring and summer. This suggests that the weak temperature fluctuations in spring are due to the bay residing entirely in the upper mixed layer at this time of year, while internal tide energy continues to influence currents. Observations made along a cross-shore/vertical transect at the center of the bay with an autonomous underwater vehicle highlight the structure of cold intrusions that fill a large portion of the bay as well as the relationship between temperature, salinity, chlorophyll, and backscatter. Near-bottom, advective heat flux estimates at the mouth of the bay indicate that the internal tide tends to advect cold water into the bay primarily on the northeast side of the bay entrance, with cold water outflow on the opposite side. The observations highlight the role of the internal tide along with seasonal changes in stratification in temperature variability in shallow ecosystems, particularly those close to generation sites.

Spatial and temporal variability of thermohaline properties in the Bay of Koper (northern Adriatic Sea)

NASA Astrophysics Data System (ADS)

Soczka Mandac, Rok; Žagar, Dušan; Faganeli, Jadran

2013-04-01

In this study influence of fresh water discharge on the spatial and temporal variability of thermohaline (TH) conditions is explored for the Bay of Koper (Bay). The Bay is subject to different driving agents: wind stress (bora, sirocco), tidal and seiches effect, buoyancy fluxes, general circulation of the Adriatic Sea and discharge of the Rizana and Badaševica rivers. These rivers have torrential characteristics that are hard to forecast in relation to meteorological events (precipitation). Therefore, during episodic events the spatial and temporal variability of TH properties in the Bay is difficult to determine [1]. Measurements of temperature, salinity and turbidity were conducted monthly on 35 sampling points in the period: June 2011 - December 2012. The data were processed and spatial interpolated with an objective analysis method. Furthermore, empirical orthogonal function analysis (EOF) [2] was applied to investigate spatial and temporal TH variations. Strong horizontal and vertical stratification was observed in the beginning of June 2011 due to high fresh water discharge of the Rizana (31 m3/s) and Badaševica (2 m3/s) rivers. The horizontal gradient (ΔT = 6°C) was noticed near the mouth of the Rizana river. Similar pattern was identified for salinity field on the boundary of the front where the gradient was ΔS = 20 PSU. Vertical temperature gradient was ΔT = 4°C while salinity gradient was ΔS = 18 PSU in the subsurface layer at depth of 3 m. Spatial analysis of the first principal component (86% of the total variance) shows uniform temperature distribution in the surface layer (1m) during the studied period. Furthermore, temporal variability of temperature shows seasonal variation with a minimum in February and maximum in August. This confirms that episodic events have a negligible effect on spatial and temporal variation of temperature in the subsurface layer. Further analysis will include application of EOF on the salinity, density and total suspended matter. Additionally, we will investigate the cross correlations between the above mentioned parameters with singular value decomposition method. Reference: 1. Faganeli, J., Planinc, R., Pezdic, J., Smodis, B., Stegnar, P., and Ogorelec, B. 1991. Marine geology of Gulf of Trieste (northern Adriatic): Geochemical aspects. Marine Geology, 99: 93-108. 2. Glover, M., Jenkins, J., and Doney, S. C. 2011. Modeling methods for marine science. Cambridge University Press, 571 p.

The stable oxygen and carbon isotopic record from a coral growing in Florida Bay: a 160 year record of climatic and anthropogenic influence

USGS Publications Warehouse

Swart, Peter K.; Healy, Genevieve F.; Dodge, Richard E.; Kramer, Philip; Hudson, J. Harold; Halley, Robert B.; Robblee, Michael B.

1996-01-01

A 160 year record of skeletal δ13C and δ18O was examined in a specimen of the coral Solenastrea bournonigrowing in Florida Bay. Variations in the δ18O of the skeleton can be correlated to changes in salinity while changes in the δ13C reflect cycling of organic material within the Bay. Based on the correlation between salinity and skeletal δ18O, we have concluded that there has been no long term increase in salinity in this area of Florida Bay over the past 160 years. Using salinity correlations between the various basins obtained from instrumental data, we have been able to extend our interpretations to other parts of Florida Bay reaching similar conclusions. In contrast to current ideas which have focused on changes in Florida Bay water quality over the past 20-yr history of the Bay as causative in its decline, we have determined that changes in water quality in this basin were already set in motion between 1905 and 1912 by the construction of the Florida East Coast Railway from Miami to Key West. The construction of the railway resulted in the restriction of the exchange of water between the Florida reef tract and the Gulf of Mexico causing Florida Bay to become more eutrophic. Evidence of this process is observed in the sudden shift to relatively lower δ13C values coincident with railway construction. Natural events also appear to have influenced the water in the Bay. Between 1912 and 1948 frequent hurricanes had the effect of increasing exchange of water between the Bay and reef tract and removing large quantities of organic rich sediments. However, since 1948 the number of hurricanes affecting the area has decreased and the products of the oxidation of organic material have been increasingly retained within the basin promoting the initiation of eutrophic conditions.

Towards Better Calibration of Modern Palynological Data against Climate: A Case Study in Osaka Bay, Japan

NASA Astrophysics Data System (ADS)

Kitaba, I.; Nakagawa, T.; McClymont, E.; Dettman, D. L.; Yamada, K.; Takemura, K.; Hyodo, M.

2014-12-01

Many of the difficulties in the pollen fossil-based paleoclimate reconstruction in coastal regions derive from the complex sedimentary processes of the near-shore environment. In order to examine this problem, we carried out pollen analysis of surface sediments collected from 35 sites in Osaka Bay, Japan. Using the biomisation method, the surrounding vegetation was accurately reconstructed at all sites. Applying the modern analogue technique to the same data, however, led to reconstructed temperatures that were lower by ca. 5 deg. C and precipitation amounts higher by ca. 5000 mm than the current sea level climate of the region. The range of reconstructed values was larger than the reconstruction error associated with the method. The principal component analysis shows that the surface pollen variation in Osaka Bay reflects sedimentary processes. This significant error associated with the quantitative climatic reconstruction using pollen data is attributed to the fact that the pollen assemblage is not determined solely by climate but reflects non-climatic influences. The accuracy and precision of climatic reconstruction can be improved significantly by expanding counts of minor taxa. Given this result, we re-examined the reconstructed climate using Osaka Bay palynological record reported in Kitaba et al. (2013). This new method did not significantly alter the overall variation in the reconstructed climate, and thus we conclude that the reconstruction was generally reliable. However, some intervals were strongly affected by depositional environmental change. In these, a climate signal can be extracted by excluding the patterns that arise from coastal sedimentation.

Insights into Seasonal Variations in Phosphorus Concentrations and Cycling in Monterey Bay

NASA Astrophysics Data System (ADS)

Kong, M.; Defforey, D.; Paytan, A.; Roberts, K.

2014-12-01

Phosphorus (P) is an essential nutrient for life as it is a structural constituent in many cell components and a key player in cellular energy metabolism. Therefore, P availability can impact primary productivity. Here we quantify dissolved and particulate P compounds and trace P sources and cycling in Monterey Bay over the course of a year. This time series gives insights into monthly and seasonal variations in the surface water chemistry of this region. Preliminary characterization of seawater samples involves measuring total P and soluble reactive P (SRP) concentrations. 31P nuclear magnetic resonance spectroscopy (31P NMR) is used to determine the chemical structure of organic phosphorus compounds present in surface seawater. The isotopic signature of phosphatic oxygen (δ18Op) is used as a proxy for studying P cycling and sources. Oxygen isotope ratios in phosphate are determined by continuous-flow isotope mass ratio spectrometry (CF-IRMS) following purification of dissolved P from seawater samples and precipitation as silver phosphate. We expect to observe seasonal changes in P concentrations, as well as differences in organic P composition and P sources. The chemical structure of organic P compounds will affect their bioavailability and thus the extent to which they can fuel primary productivity in Monterey Bay. δ18Op will reflect source signatures and provide information on turnover rates of P in surface waters. Results from this work will provide valuable insights into seasonal changes in P cycling in surface waters and have important implications for understanding primary productivity in the Monterey Bay ecosystem.

A Theoretical Analysis of Why Hybrid Ensembles Work

PubMed Central

2017-01-01

Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles. PMID:28255296

Integrated scheduling of a container handling system with simultaneous loading and discharging operations

NASA Astrophysics Data System (ADS)

Li, Chen; Lu, Zhiqiang; Han, Xiaole; Zhang, Yuejun; Wang, Li

2016-03-01

The integrated scheduling of container handling systems aims to optimize the coordination and overall utilization of all handling equipment, so as to minimize the makespan of a given set of container tasks. A modified disjunctive graph is proposed and a mixed 0-1 programming model is formulated. A heuristic algorithm is presented, in which the original problem is divided into two subproblems. In the first subproblem, contiguous bay crane operations are applied to obtain a good quay crane schedule. In the second subproblem, proper internal truck and yard crane schedules are generated to match the given quay crane schedule. Furthermore, a genetic algorithm based on the heuristic algorithm is developed to search for better solutions. The computational results show that the proposed algorithm can efficiently find high-quality solutions. They also indicate the effectiveness of simultaneous loading and discharging operations compared with separate ones.

Identification of observer/Kalman filter Markov parameters: Theory and experiments

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh; Horta, Lucas G.; Longman, Richard W.

1991-01-01

An algorithm to compute Markov parameters of an observer or Kalman filter from experimental input and output data is discussed. The Markov parameters can then be used for identification of a state space representation, with associated Kalman gain or observer gain, for the purpose of controller design. The algorithm is a non-recursive matrix version of two recursive algorithms developed in previous works for different purposes. The relationship between these other algorithms is developed. The new matrix formulation here gives insight into the existence and uniqueness of solutions of certain equations and gives bounds on the proper choice of observer order. It is shown that if one uses data containing noise, and seeks the fastest possible deterministic observer, the deadbeat observer, one instead obtains the Kalman filter, which is the fastest possible observer in the stochastic environment. Results are demonstrated in numerical studies and in experiments on an ten-bay truss structure.

Variations in sediment texture on the northern Monterey Bay National Marine Sanctuary continental shelf

USGS Publications Warehouse

Edwards, B.D.

2002-01-01

The storm-protected continental shelf of Monterey Bay, part of the Monterey Bay National Marine Sanctuary, north-central California, is subject to abundant, episodic sediment input from fluvial sources. North of Monterey Bay, conditions of reduced sediment supply combined with the exposed nature of the shelf provide an effective laboratory for studying the contrasting effects of storm- versus fluvial-dominated conditions on modern sedimentation. Textural analyses performed on surface sediment samples collected from more than 380 box cores and MultiCores??? document the existence of a clearly defined mud belt occupying the mid-shelf throughout the region. Inshore sands combined with these mid-shelf muds represent deposits from modern sedimentation processes. In Monterey Bay, where episodic fluvial input from winter storms dominates sedimentation, the mid-shelf mud belt extends across the shelf to the shelf break. North of Monterey Bay, where sediment loads are reduced and both oceanographic and storm processes dominate, the mid-shelf mud belt is bordered by relict sediments occupying the outer shelf. In the study area, mass accumulation rates established by radiochemical studies support the contention that storm-induced along-shelf processes result in northward transport of sediment within the mud belt. The continuity of transport, however, is interrupted by topographic highs which are barriers or inhibitors to sediment transport created by wrench-style tectonics associated with the San Andreas fault system.

Gaseous exchange of polycyclic aromatic hydrocarbons across the air-water interface of lower Chesapeake Bay

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gustafson, K.E.; Dickhut, R.M.

1995-12-31

The gaseous exchange fluxes of polycyclic aromatic hydrocarbons (PAHs) across the air-water interface of lower Chesapeake Bay were determined using a modified two-film exchange model. Sampling covered the period January 1994 to June 1995 for five sites on lower Chesapeake Bay ranging from rural to urban and highly industrialized. Simultaneous air and water samples were collected and the atmospheric gas phase and water column dissolved phase analyzed via GC/MS for 17 PAHs. The direction and magnitude of flux for each PAH was calculated using Henry`s law constants, hydrological and meteorological parameters, Temperature was observed to be an important environmental factormore » in determining both the direction and magnitude of PAH gas exchange. Nonetheless, wind speed significantly impacts mass transfer coefficients, and therefore was found to control the magnitude of flux. Spatial and temporal variation of PAH gaseous exchange fluxes were examined. Fluxes were determined to be both into and out of Chesapeake Bay. The range of gas exchange fluxes ({minus}560 to 600{micro}g/M{sup 2}*Mo) is of the same order to 10X greater than atmospheric wet and dry depositional fluxes to lower Chesapeake Bay. The results of this study support the hypothesis that gas exchange is a major transport process affecting the net loadings of PAHs in lower Chesapeake Bay.« less

Nutrient and chlorophyll a anomaly in red-tide periods of 2003-2008 in Sishili Bay, China

NASA Astrophysics Data System (ADS)

Hao, Yanju; Tang, Danling; Yu, Long; Xing, Qianguo

2011-05-01

Sishili Bay is the most important aquiculture and tourism area for the city of Yantai, China; however, red tides occurred frequently and have caused huge economic losses in this bay in recent years. To gain a better understanding of the local ecological environments in the bay, we conducted this research between 2003 and 2008 to analyze variations in nutrients and chlorophyll (chl- a) during high frequency red tide period (May to September). The results show that the chl- a concentration increased from 2.70 in 2003 to 7.26 mg/m3 in 2008, while the concentration of total inorganic nitrogen (TIN) and silicate (SiO3-Si) increased lineally from 5.18 and 1.45 μmol/L in 2003 to 18.57 and 9.52 μmol/L in 2008, respectively, and the annual phosphate (PO4-P) varied between 0.15 and 0.46 μmol/L. Special attention was given to a red tide in August 2007 occurred when water temperature was high and nutrient concentrations increased sharply because of a heavy rainfall. Overall, the results show the P limitation in Sishili Bay, and reveal that red tides were caused by eutrophication from terrestrial inputs and local warm weather, particularly during rainy periods. Therefore, to control red tide, greater efforts should be made to reduce sewage discharges into Sishili Bay, particularly during rainfall seasons.

Comparative study of classification algorithms for damage classification in smart composite laminates

NASA Astrophysics Data System (ADS)

Khan, Asif; Ryoo, Chang-Kyung; Kim, Heung Soo

2017-04-01

This paper presents a comparative study of different classification algorithms for the classification of various types of inter-ply delaminations in smart composite laminates. Improved layerwise theory is used to model delamination at different interfaces along the thickness and longitudinal directions of the smart composite laminate. The input-output data obtained through surface bonded piezoelectric sensor and actuator is analyzed by the system identification algorithm to get the system parameters. The identified parameters for the healthy and delaminated structure are supplied as input data to the classification algorithms. The classification algorithms considered in this study are ZeroR, Classification via regression, Naïve Bayes, Multilayer Perceptron, Sequential Minimal Optimization, Multiclass-Classifier, and Decision tree (J48). The open source software of Waikato Environment for Knowledge Analysis (WEKA) is used to evaluate the classification performance of the classifiers mentioned above via 75-25 holdout and leave-one-sample-out cross-validation regarding classification accuracy, precision, recall, kappa statistic and ROC Area.

Simulation Model of Mobile Detection Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edmunds, T; Faissol, D; Yao, Y

2009-01-27

In this paper, we consider a mobile source that we attempt to detect with man-portable, vehicle-mounted or boat-mounted radiation detectors. The source is assumed to transit an area populated with these mobile detectors, and the objective is to detect the source before it reaches a perimeter. We describe a simulation model developed to estimate the probability that one of the mobile detectors will come in to close proximity of the moving source and detect it. We illustrate with a maritime simulation example. Our simulation takes place in a 10 km by 5 km rectangular bay patrolled by boats equipped withmore » 2-inch x 4-inch x 16-inch NaI detectors. Boats to be inspected enter the bay and randomly proceed to one of seven harbors on the shore. A source-bearing boat enters the mouth of the bay and proceeds to a pier on the opposite side. We wish to determine the probability that the source is detected and its range from target when detected. Patrol boats select the nearest in-bound boat for inspection and initiate an intercept course. Once within an operational range for the detection system, a detection algorithm is started. If the patrol boat confirms the source is not present, it selects the next nearest boat for inspection. Each run of the simulation ends either when a patrol successfully detects a source or when the source reaches its target. Several statistical detection algorithms have been implemented in the simulation model. First, a simple k-sigma algorithm, which alarms with the counts in a time window exceeds the mean background plus k times the standard deviation of background, is available to the user. The time window used is optimized with respect to the signal-to-background ratio for that range and relative speed. Second, a sequential probability ratio test [Wald 1947] is available, and configured in this simulation with a target false positive probability of 0.001 and false negative probability of 0.1. This test is utilized when the mobile detector maintains a constant range to the vessel being inspected. Finally, a variation of the sequential probability ratio test that is more appropriate when source and detector are not at constant range is available [Nelson 2005]. Each patrol boat in the fleet can be assigned a particular zone of the bay, or all boats can be assigned to monitor the entire bay. Boats assigned to a zone will only intercept and inspect other boats when they enter their zone. In our example simulation, each of two patrol boats operate in a 5 km by 5 km zone. Other parameters for this example include: (1) Detection range - 15 m range maintained between patrol boat and inspected boat; (2) Inbound boat arrival rate - Poisson process with mean arrival rate of 30 boats per hour; (3) Speed of boats to be inspected - Random between 4.5 and 9 knots; (4) Patrol boat speed - 10 knots; (5) Number of detectors per patrol boat - 4-2-inch x 4-inch x 16-inch NaI detectors; (6) Background radiation - 40 counts/sec per detector; and (7) Detector response due to radiation source at 1 meter - 1,589 counts/sec per detector. Simulation results indicate that two patrol boats are able to detect the source 81% of the time without zones and 90% of the time with zones. The average distances between the source and target at the end of the simulation is 5,866 km and 5,712 km for non-zoned and zoned patrols, respectively. Of those that did not reach the target, the average distance to the target is 7,305 km and 6,441 km respectively. Note that a design trade-off exists. While zoned patrols provide a higher probability of detection, the nonzoned patrols tend to detect the source farther from its target. Figure 1 displays the location of the source at the end of 1,000 simulations for the 5 x 10 km bay simulation. The simulation model and analysis described here can be used to determine the number of mobile detectors one would need to deploy in order to have a have reasonable chance of detecting a source in transit. By fixing the source speed to zero, the same model could be used to estimate how long it would take to detect a stationary source. For example, the model could predict how long it would take plant staff performing assigned duties carrying dosimeters to discover a contaminated spot in the facility.« less

Effects of Submarine Groundwater Discharge (SGD) on the Growth of the Lobe Coral Porites lobata in Maunalua Bay, Hawaii.

NASA Astrophysics Data System (ADS)

Lubarsky, K.

2016-02-01

Submarine groundwater discharge (SGD) constitutes a large percentage of the freshwater inputs onto coastal coral reefs on high islands such as the Hawaiian Islands, although the impact of SGD on coral reef health is currently understudied. In Maunalua Bay, on Oahu, Hawaii, SGD is discharged onto shallow reef flats from discrete seeps, creating natural gradients of water chemistry across the reef flat. We used this system to investigate rates of growth of the lobe coral Porites lobata across a gradient of SGD influence at two study sites within the bay, and to characterize the variation in water chemistry gradient over space and time due to SGD. SGD input at these sites is tidally modulated, and the groundwater itself is brackish and extremely nutrient-rich (mean=190 μM NO3- at the Black Point study site, mean=40 μM NO3- at Wailupe Beach Park), with distinct carbonate signatures at both study sites. Coral nubbins were placed across the gradient for 6 months, and growth was measured using three metrics: surface area (photo analysis), buoyant weight, and linear extension. Various chemical parameters, including pH, salinity, total alkalinity, nutrients, and chlorphyll were sampled at the same locations across the gradient over 24 hour periods in the spring and fall in order to capture spatial and temporal variation in water chemistry due to the SGD plume. Spatial patterns and temporal variation in water chemistry were correlated with the observed spatial patterns in coral growth across the SGD gradient.

Modelling green macroalgal blooms on the coasts of Brittany, France to enhance water quality management

NASA Astrophysics Data System (ADS)

Perrot, Thierry; Rossi, Nadège; Ménesguen, Alain; Dumas, Franck

2014-04-01

First recorded in the 1970s, massive green macroalgal blooms have since become an annual recurrence in Brittany, France. Eutrophication (in particular to anthropogenic nitrogen input) has been identified as the main factor controlling Ulva ‘green tide' events. In this study, we modelled Ulva proliferation using a two-dimensional model by coupling hydrodynamic and biological models (coined ‘MARS-Ulves') for five sites along the Brittany coastline (La Fresnaye Bay, Saint-Brieuc Bay, Lannion Bay, Guissény Bay and Douarnenez Bay). Calibration of the biological model was mainly based on the seasonal variation of the maximum nitrogen uptake rate (VmaxN) and the half-saturation constant for nitrogen (KN) to reproduce the internal nutrient quotas measured in situ for each site. In each bay, model predictions were in agreement with observed algal coverage converted into biomass. A numerical tracking method was implemented to identify the contribution of the rivers that empty into the study bays, and scenarios of decreases in nitrate concentration in rivers were simulated. Results from numerical nitrogen tracking highlighted the main nitrogen sources of green tides and also showed that each river contributes locally to green tides. In addition, dynamic modelling showed that the nitrate concentrations in rivers must be limited to between 5 and 15 mg l- 1, depending on the bay, to reduce Ulva biomass by half on the coasts. The three-step methodology developed in this study (analysing total dissolved inorganic nitrogen flux from rivers, tracking nitrogen sources in Ulva and developing scenarios for reducing nitrogen) provides qualitative and quantitative guidelines for stakeholders to define specific nitrogen reduction targets for better environmental management of water quality.

Synoptic volumetric variations and flushing of the Tampa Bay estuary

NASA Astrophysics Data System (ADS)

Wilson, M.; Meyers, S. D.; Luther, M. E.

2014-03-01

Two types of analyses are used to investigate the synoptic wind-driven flushing of Tampa Bay in response to the El Niño-Southern Oscillation (ENSO) cycle from 1950 to 2007. Hourly sea level elevations from the St. Petersburg tide gauge, and wind speed and direction from three different sites around Tampa Bay are used for the study. The zonal (u) and meridional (v) wind components are rotated clockwise by 40° to obtain axial and co-axial components according to the layout of the bay. First, we use the subtidal observed water level as a proxy for mean tidal height to estimate the rate of volumetric bay outflow. Second, we use wavelet analysis to bandpass sea level and wind data in the time-frequency domain to isolate the synoptic sea level and surface wind variance. For both analyses the long-term monthly climatology is removed and we focus on the volumetric and wavelet variance anomalies. The overall correlation between the Oceanic Niño Index and volumetric analysis is small due to the seasonal dependence of the ENSO response. The mean monthly climatology between the synoptic wavelet variance of elevation and axial winds are in close agreement. During the winter, El Niño (La Niña) increases (decreases) the synoptic variability, but decreases (increases) it during the summer. The difference in winter El Niño/La Niña wavelet variances is about 20 % of the climatological value, meaning that ENSO can swing the synoptic flushing of the bay by 0.22 bay volumes per month. These changes in circulation associated with synoptic variability have the potential to impact mixing and transport within the bay.

Treatment effect heterogeneity for univariate subgroups in clinical trials: Shrinkage, standardization, or else

PubMed Central

Varadhan, Ravi; Wang, Sue-Jane

2016-01-01

Treatment effect heterogeneity is a well-recognized phenomenon in randomized controlled clinical trials. In this paper, we discuss subgroup analyses with prespecified subgroups of clinical or biological importance. We explore various alternatives to the naive (the traditional univariate) subgroup analyses to address the issues of multiplicity and confounding. Specifically, we consider a model-based Bayesian shrinkage (Bayes-DS) and a nonparametric, empirical Bayes shrinkage approach (Emp-Bayes) to temper the optimism of traditional univariate subgroup analyses; a standardization approach (standardization) that accounts for correlation between baseline covariates; and a model-based maximum likelihood estimation (MLE) approach. The Bayes-DS and Emp-Bayes methods model the variation in subgroup-specific treatment effect rather than testing the null hypothesis of no difference between subgroups. The standardization approach addresses the issue of confounding in subgroup analyses. The MLE approach is considered only for comparison in simulation studies as the “truth” since the data were generated from the same model. Using the characteristics of a hypothetical large outcome trial, we perform simulation studies and articulate the utilities and potential limitations of these estimators. Simulation results indicate that Bayes-DS and Emp-Bayes can protect against optimism present in the naïve approach. Due to its simplicity, the naïve approach should be the reference for reporting univariate subgroup-specific treatment effect estimates from exploratory subgroup analyses. Standardization, although it tends to have a larger variance, is suggested when it is important to address the confounding of univariate subgroup effects due to correlation between baseline covariates. The Bayes-DS approach is available as an R package (DSBayes). PMID:26485117

Reproductive traits of the small Patagonian octopus Octopus tehuelchus

NASA Astrophysics Data System (ADS)

Storero, Lorena P.; Narvarte, Maite A.; González, Raúl A.

2012-12-01

This study evaluated the reproductive features of Octopus tehuelchus in three coastal environments of San Matías Gulf (Patagonia). Monthly samples of O. tehuelchus were used to estimate size at maturity, compare seasonal changes in oocyte size frequency distributions between sites as well as oocyte number and size between female maturity stage and sites. Females in Islote Lobos had a smaller size at maturity than females in San Antonio Bay and El Fuerte, probably as a consequence of a generally smaller body size. Males in San Antonio Bay were smaller at maturity than females. O. tehuelchus is a simultaneous terminal spawner. Fecundity (expressed as number of vitellogenic oocytes in ovary) was lower in Islote Lobos, and an increase in oocyte number in relation to female total weight was found. Females in San Antonio Bay had the largest oocytes, which may indicate higher energy reserves for the embryo and therefore higher juvenile survival. There was a close relationship between reproduction, growth and condition, represented as size at maturity, number and size of vitellogenic oocytes and period of maturity and spawning. Given the local variation in some reproductive features of O. tehuelchus, studies should focus on the environmental factors, which bring about this variation, and on how it affects the dynamics of local populations.

Seasonal variation of absorption by particles and colored dissolved organic matter (CDOM) in Funka Bay, southwestern Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Sasaki, Hiroaki; Miyamura, Tsuyoshi; Saitoh, Sei-ichi; Ishizaka, Joji

2005-08-01

Between November 2000 and October 2001, the seasonal variation in absorption by particles (phytoplankton and detritus) and colored dissolved organic matter (CDOM) was measured in Funka Bay (a subarctic coastal region of Japan). In autumn-winter, chlorophyll a concentration (Chl a) near the euphotic zone remained very low (<1.0 mg m -3) but markedly increased in spring (16.8 mg m -3). Chlorophyll-specific absorption coefficient for phytoplankton ( a∗ph( λ)) was high during summer and low during the spring bloom. This is because the package effect was greater during the spring bloom due to the presence of large diatoms, while small phytoplankton dominated during summer. Absorption at 440 nm by CDOM was higher than that of phytoplankton and detritus, except during the spring bloom, and the relative contribution of CDOM absorption to the total absorption coefficient was >50%. CDOM and detritus absorption did not increase with increasing Chl a, but it showed a time lag between the spring bloom. It is suggested that phytoplankton degradation started after the spring bloom; detritus absorption increased and, then, CDOM absorption increased. River runoff was not a significant influence in Funka Bay, therefore, CDOM production may be mainly related to microbial activity.

Energy density of anchovy Engraulis encrasicolus in the Bay of Biscay.

PubMed

Dubreuil, J; Petitgas, P

2009-02-01

The energy density (E(D)) of anchovy Engraulis encrasicolus in the Bay of Biscay was determined by direct calorimetry and its evolution with size, age and season was investigated. The water content and energy density varied seasonally following opposite trends. The E(D) g(-1) of wet mass (M(W)) was highest at the end of the feeding season (autumn: c. 8 kJ g(-1)M(W)) and lowest in late winter (c. 6 kJ g(-1)M(W)). In winter, the fish lost mass, which was partially replaced by water, and the energy density decreased. These variations in water content and organic matter content may have implications on the buoyancy of the fish. The water content was the major driver of the energy density variations for a M(W) basis. A significant linear relationship was established between E(D) g(-1) (y) and the per cent dry mass (M(D); x): y =-4.937 + 0.411x. In the light of the current literature, this relationship seemed to be not only species specific but also ecosystem specific. Calibration and validation of fish bioenergetics models require energy content measurements on fish samples collected at sea. The present study provides a first reference for the energetics of E. encrasicolus in the Bay of Biscay.

Diet of a piscivorous seabird reveals spatiotemporal variation in abundance of forage fishes in the Monterey Bay region

NASA Astrophysics Data System (ADS)

Webb, Lisa A.; Harvey, James T.

2015-06-01

Brandt's Cormorant (Phalacrocorax penicillatus) diet was investigated using regurgitated pellets (n = 285) collected on 19 sampling days at three locations during the 2006-07 and 2007-08 nonbreeding seasons in the Monterey Bay region. The efficacy of using nested sieves and the all-structure technique to facilitate prey detection in the pellets was evaluated, but this method did not increase prey enumeration and greatly decreased efficiency. Although 29 prey species were consumed, northern anchovy (Engraulis mordax) dominated and speckled sanddab (Citharichthys stigmaeus) also was important in the diet. Few rockfishes (Sebastes spp.) and market squid (Doryteuthis opalescens) were consumed compared with great prevalence in previous studies during the 1970s. El Niño and La Niña during the study provided a unique opportunity to examine predator response to variation in prey availability. Patterns of prey number and diversity were not consistent among locations. Greatest number and diversity of prey occurred at locations within Monterey Bay during La Niña, results not evident at the outer coast location. Short-term specialization occurred but mean prey diversity indicated a generalist feeding mode. This study demonstrated the importance of periodic sampling at multiple locations within a region to detect spatiotemporal variability in the diet of opportunistic generalists.

Holocene climates and connections between the San Francisco Bay Estuary and its watershed: A review

USGS Publications Warehouse

Malamud-Roam, F.; Dettinger, M.; Ingram, B. Lynn; Hughes, Malcolm K.; Florsheim, Joan

2007-01-01

This review of paleoclimate records reveals a gradual warming and drying in California from about 10,000 years to about 4,000 years before present. During this period, the current Bay and Delta were inundated by rising sea level so that by 4,000 years ago the Bay and Delta had taken on much of their present shape and extent. Between about 4,000 and 2,000 years ago, cooler and wetter conditions prevailed in the watershed, lowering salinity in the Estuary and altering local ecosystems. Those wetter conditions gave way to increasing aridity during the past 2,000 years, a general trend punctuated by occasional prolonged and severe droughts and occasional unusually wet, cool periods. California’s climate since A.D. 1850 has been unusually stable and benign, compared to climate variations during the previous 2,000 or more years. Thus, climate variations in California’s future may be even more (perhaps much more) challenging than those of the past 100 years. To improve our understanding of these past examples of climate variability in California, and of the linkages between watershed climate and estuarine responses, greater emphases on paleoclimate records in and around the Estuary, improved temporal resolutions in several record types, and linked watershed-estuary paleo-modeling capabilities are needed. 

Classification of earth terrain using polarimetric synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Lim, H. H.; Swartz, A. A.; Yueh, H. A.; Kong, J. A.; Shin, R. T.; Van Zyl, J. J.

1989-01-01

Supervised and unsupervised classification techniques are developed and used to classify the earth terrain components from SAR polarimetric images of San Francisco Bay and Traverse City, Michigan. The supervised techniques include the Bayes classifiers, normalized polarimetric classification, and simple feature classification using discriminates such as the absolute and normalized magnitude response of individual receiver channel returns and the phase difference between receiver channels. An algorithm is developed as an unsupervised technique which classifies terrain elements based on the relationship between the orientation angle and the handedness of the transmitting and receiving polariation states. It is found that supervised classification produces the best results when accurate classifier training data are used, while unsupervised classification may be applied when training data are not available.

Living on the edge: latitudinal variations in the reproductive biology of two coastal species of sharks.

PubMed

Taylor, S M; Harry, A V; Bennett, M B

2016-11-01

Differences in the reproductive biology of both the Australian weasel shark Hemigaleus australiensis and the Australian sharpnose shark Rhizoprionodon taylori were apparent between individuals from the southern-most extent of their range in eastern Australia (Moreton Bay) and those from northern Australia. For H. australiensis from Moreton Bay the total length (L T ) at which 50% of individuals were mature (L T50 ) was 759 mm for females and 756 mm for males, values that were respectively 17-26% larger than reported for the species in northern Australia. The relatively low percentage (63%) of pregnant mature females and presence of small, similar-sized, embryos in utero in both May and November suggested a semi-synchronous, annual reproductive cycle in Moreton Bay, whereas a synchronous, biannual reproductive cycle occurred in northern Australia. It is likely that H. australiensis has a resting phase between gestation cycles at the southern-most extent of its range. For R. taylori from Moreton Bay the L T50 s were 588 and 579 mm for females and males, respectively, values 2-3% larger than for individuals from the mid-Queensland coast and 31-35% larger than for individuals from northern Australia. The length at which 50% of the females were maternal (611 mm L T ) in Moreton Bay was greater than the L T50 , indicating that not all sharks mate immediately after maturing. Rhizoprionodon taylori in the south had an annual reproductive cycle incorporating a 7-8 month embryonic diapause, with pups probably born in February. A mean fecundity of 7·5 was almost double that reported from northern Australia. Regional variations in the reproductive characteristics of H. australiensis and R. taylori may influence their resilience to fishing and other anthropogenic pressures. The substantial differences reported here highlight the importance of region-specific life-history parameters to successful management and conservation. © 2016 The Fisheries Society of the British Isles.

INTEGRATED ASSESSMENTS OF ANTHROPOGENIC AND NATURAL CHANGES IN CHESAPEAKE BAY WATERSHEDS

EPA Science Inventory

Both natural and anthropogenic factors affect spatial and temporal patterns in ecosystem conditions. To manage environmental change and risks, distinguishing between natural variations in ecosystem conditions and anthropogenic changes becomes important. This concept is illustrate...

Baleen whales and their prey in a coastal environment

USGS Publications Warehouse

Piatt, John F.; Methven, David A.; Burger, Alan E.; McLagan, Ruth L.; Mercer, Vicki; Creelman, Elizabeth

1989-01-01

Patterns of abundance of humpback (Megaptera novaeangliae), fin (Balaenoptera physalus), and minke (Balaenoptera acutorostrata) whales are described in relation to the abundance of their primary prey, capelin (Mallotus villosus), during 1982–1985 at Witless Bay, Newfoundland. The abundance ratio of the three whale species was 10:1:3.5, respectively. Abundance of all whale species was strongly correlated with abundance of capelin through each season and between years. Capelin abundance accounted for 63% of the variation in whale numbers in 1983 and 1984, while environmental parameters (e.g., water temperatures) accounted for little variance. The amount of capelin consumed by whales was small (< 2%) compared with the amount available. All three species overlapped temporally at Witless Bay, but spatial overlap was reduced as fins occurred primarily offshore, minkes primarily inshore, and humpbacks in bay habitats of intermediate depth.

Long-term, High Frequency, High Precision pH Measurements on the MBARI deep-water FOCE Experiment at the MARS Cabled Observatory in Monterey Bay, CA

NASA Astrophysics Data System (ADS)

Peltzer, E. T.; Maughan, T.; Barry, J. P.; Brewer, P. G.; Headley, K. L.; Herlien, R.; Kirkwood, W. J.; Matsumoto, G. I.; O'Reilly, T. C.; Salamy, K. A.; Scholfield, J.; Shane, F. F.; Walz, P. M.

2012-12-01

The MBARI deep-water FOCE experiment was deployed on the MARS cabled observatory in Monterey Bay on May 4th, 2011. It has been in continuous operation (excluding a few minor shore based power outages) ever since. During the fifteen months of deployment, we have been able to observe both the daily variation in pH in response to water mass movements associated with the semi-diurnal tides, internal waves and longer-term trends as a function of the seasonal variations in the water masses within the Monterey Bay Canyon. Our experimental site is located at 890 meters, just below the oxygen minimum for Monterey Bay, and we clearly see the anticipated inverse correlation between seawater temperature and pH. Daily variation in pH is on the order of 0.020-0.030 pH units with longer term trends adding an additional variation of similar magnitude. Instrumentation on this experiment included two CTDs with oxygen sensors (Sea-Bird 52). One CTD is mounted on the external FOCE framework to measure the background conditions, and one CTD is installed within the FOCE pH control area to monitor the experimentally manipulated conditions. In addition, 6 MBARI modified Sea-Bird 18 pH sensors were mounted on the FOCE apparatus. Four of these pH sensors monitored pH inside the experimental chamber and two monitored the external background seawater conditions. Although we originally intended to conduct several in situ CO2 enrichment experiments to study the impact of ocean acidification on the benthic biology and then recover the apparatus after one year, unanticipated changes in the ship schedule have left the FOCE experiment in place for nearly fifteen months at the time of this writing. Throughout this time period, all sensor data has been logged by the MBARI Shore-Side Data System (SSDS) resulting in the longest continuous record of high precision pH measurements in the intermediate water column. We present an analysis of the data obtained from this unique data set, and discuss our in-situ calibration techniques used to compensate for long term sensor drift associated with the reference electrode.

Monitoring terrestrial dissolved organic carbon export at land-water interfaces using remote sensing

NASA Astrophysics Data System (ADS)

Yu, Q.; Li, J.; Tian, Y. Q.

2017-12-01

Carbon flux from land to oceans and lakes is a crucial component of carbon cycling. However, this lateral carbon flow at land-water interface is often neglected in the terrestrial carbon cycle budget, mainly because observations of the carbon dynamics are very limited. Monitoring CDOM/DOC dynamics using remote sensing and assessing DOC export from land to water remains a challenge. Current CDOM retrieval algorithms in the field of ocean color are not simply applicable to inland aquatic ecosystems since they were developed for coarse resolution ocean-viewing imagery and less complex water types in open-sea. We developed a new semi-analytical algorithm, called SBOP (Shallow water Bio-Optical Properties algorithm) to adapt to shallow inland waters. SBOP was first developed and calibrated based on in situ hyperspectral radiometer data. Then we applied it to the Landsat-8 OLI images and evaluated the effectiveness of the multispectral images on inversion of CDOM absorption based on our field sampling at the Saginaw Bay in the Lake Huron. The algorithm performances (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay; R2 = 0.80 in the northeastern US lakes) is promising and we conclude the CDOM absorption can be derived from Landsat-8 OLI image in both optically deep and optically shallow waters with high accuracy. Our method addressed challenges on employing appropriate atmospheric correction, determining bottom reflectance influence for shallow waters, and improving for bio-optical properties retrieval, as well as adapting to both hyperspectral and the multispectral remote sensing imagery. Over 100 Landsat-8 images in Lake Huron, northeastern US lakes, and the Arctic major rivers were processed to understand the CDOM spatio-temporal dynamics and its associated driving factors.

Seasonal and Inter-Annual Patterns of Chlorophyll and Phytoplankton Community Structure in Monterey Bay, CA Derived from AVIRIS Data During the 2013-2015 HyspIRI Airborne Campaign

NASA Astrophysics Data System (ADS)

Palacios, S. L.; Thompson, D. R.; Kudela, R. M.; Negrey, K.; Guild, L. S.; Gao, B. C.; Green, R. O.; Torres-Perez, J. L.

2016-02-01

There is a need in the ocean color community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand ocean biodiversity, track energy flow through ecosystems, and identify and monitor for harmful algal blooms. Imaging spectrometer measurements enable the use of sophisticated spectroscopic algorithms for applications such as differentiating among coral species and discriminating phytoplankton taxa. These advanced algorithms rely on the fine scale, subtle spectral shape of the atmospherically corrected remote sensing reflectance (Rrs) spectrum of the ocean surface. Consequently, these algorithms are sensitive to inaccuracies in the retrieved Rrs spectrum that may be related to the presence of nearby clouds, inadequate sensor calibration, low sensor signal-to-noise ratio, glint correction, and atmospheric correction. For the HyspIRI Airborne Campaign, flight planning considered optimal weather conditions to avoid flights with significant cloud/fog cover. Although best suited for terrestrial targets, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has enough signal for some coastal chlorophyll algorithms and meets sufficient calibration requirements for most channels. The coastal marine environment has special atmospheric correction needs due to error introduced by aerosols and terrestrially sourced atmospheric dust and riverine sediment plumes. For this HyspIRI campaign, careful attention has been given to the correction of AVIRIS imagery of the Monterey Bay to optimize ocean Rrs retrievals to estimate chlorophyll (OC3) and phytoplankton functional type (PHYDOTax) data products. This new correction method has been applied to several image collection dates during two oceanographic seasons in 2013 and 2014. These two periods are dominated by either diatom blooms or red tides. Results to be presented include chlorophyll and phytoplankton community structure and in-water validation data for these dates during the two seasons.

Robust resolution enhancement optimization methods to process variations based on vector imaging model

NASA Astrophysics Data System (ADS)

Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong

2012-03-01

Optical proximity correction (OPC) and phase shifting mask (PSM) are the most widely used resolution enhancement techniques (RET) in the semiconductor industry. Recently, a set of OPC and PSM optimization algorithms have been developed to solve for the inverse lithography problem, which are only designed for the nominal imaging parameters without giving sufficient attention to the process variations due to the aberrations, defocus and dose variation. However, the effects of process variations existing in the practical optical lithography systems become more pronounced as the critical dimension (CD) continuously shrinks. On the other hand, the lithography systems with larger NA (NA>0.6) are now extensively used, rendering the scalar imaging models inadequate to describe the vector nature of the electromagnetic field in the current optical lithography systems. In order to tackle the above problems, this paper focuses on developing robust gradient-based OPC and PSM optimization algorithms to the process variations under a vector imaging model. To achieve this goal, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. The steepest descent algorithm is used to optimize the mask iteratively. In order to improve the efficiency of the proposed algorithms, a set of algorithm acceleration techniques (AAT) are exploited during the optimization procedure.

A generalized Condat's algorithm of 1D total variation regularization

NASA Astrophysics Data System (ADS)

Makovetskii, Artyom; Voronin, Sergei; Kober, Vitaly

2017-09-01

A common way for solving the denosing problem is to utilize the total variation (TV) regularization. Many efficient numerical algorithms have been developed for solving the TV regularization problem. Condat described a fast direct algorithm to compute the processed 1D signal. Also there exists a direct algorithm with a linear time for 1D TV denoising referred to as the taut string algorithm. The Condat's algorithm is based on a dual problem to the 1D TV regularization. In this paper, we propose a variant of the Condat's algorithm based on the direct 1D TV regularization problem. The usage of the Condat's algorithm with the taut string approach leads to a clear geometric description of the extremal function. Computer simulation results are provided to illustrate the performance of the proposed algorithm for restoration of degraded signals.

Sources of mercury to San Francisco Bay surface sediment as revealed by mercury stable isotopes

USGS Publications Warehouse

Gehrke, Gretchen E.; Blum, Joel D.; Marvin-DePasquale, Mark

2011-01-01

Mercury (Hg) concentrations and isotopic compositions were examined in shallow-water surface sediment (0–2 cm) from San Francisco (SF) Bay to determine the extent to which historic Hg mining contributes to current Hg contamination in SF Bay, and to assess the use of Hg isotopes to trace sources of contamination in estuaries. Inter-tidal and wetland sediment had total Hg (HgT) concentrations ranging from 161 to 1529 ng/g with no simple gradients of spatial variation. In contrast, inter-tidal and wetland sediment displayed a geographic gradient of δ202Hg values, ranging from -0.30% in the southern-most part of SF Bay (draining the New Almaden Hg District) to -0.99% in the northern-most part of SF Bay near the Sacramento–San Joaquin River Delta. Similar to SF Bay inter-tidal sediment, surface sediment from the Alviso Slough channel draining into South SF Bay had a δ202Hg value of -0.29%, while surface sediment from the Cosumnes River and Sacramento–San Joaquin River Delta draining into north SF Bay had lower average δ202Hg values of -0.90% and -0.75%, respectively. This isotopic trend suggests that Hg-contaminated sediment from the New Almaden Hg District mixes with Hg-contaminated sediment from a low δ202Hg source north of SF Bay. Tailings and thermally decomposed ore (calcine) from the New Idria Hg mine in the California Coast Range had average δ202Hg values of -0.37 and +0.03%, respectively, showing that Hg calcination fractionates Hg isotopes resulting in Hg contamination from Hg(II) mine waste products with higher δ202Hg values than metallic Hg(0) produced from Hg mines. Thus, there is evidence for at least two distinct isotopic signals for Hg contamination in SF Bay: Hg associated with calcine waste materials at Hg mines in the Coast Range, such as New Almaden and New Idria; and Hg(0) produced from these mines and used in placer gold mines and/or in other industrial processes in the Sierra Nevada region and SF Bay area.

A Coastal Bay Summer Breeze Study, Part 2: High-resolution Numerical Simulation of Sea-breeze Local Influences

NASA Astrophysics Data System (ADS)

Calmet, Isabelle; Mestayer, Patrice G.; van Eijk, Alexander M. J.; Herlédant, Olivier

2018-04-01

We complete the analysis of the data obtained during the experimental campaign around the semi circular bay of Quiberon, France, during two weeks in June 2006 (see Part 1). A reanalysis of numerical simulations performed with the Advanced Regional Prediction System model is presented. Three nested computational domains with increasing horizontal resolution down to 100 m, and a vertical resolution of 10 m at the lowest level, are used to reproduce the local-scale variations of the breeze close to the water surface of the bay. The Weather Research and Forecasting mesoscale model is used to assimilate the meteorological data. Comparisons of the simulations with the experimental data obtained at three sites reveal a good agreement of the flow over the bay and around the Quiberon peninsula during the daytime periods of sea-breeze development and weakening. In conditions of offshore synoptic flow, the simulations demonstrate that the semi-circular shape of the bay induces a corresponding circular shape in the offshore zones of stagnant flow preceding the sea-breeze onset, which move further offshore thereafter. The higher-resolution simulations are successful in reproducing the small-scale impacts of the peninsula and local coasts (breeze deviations, wakes, flow divergences), and in demonstrating the complexity of the breeze fields close to the surface over the bay. Our reanalysis also provides guidance for numerical simulation strategies for analyzing the structure and evolution of the near-surface breeze over a semi-circular bay, and for forecasting important flow details for use in upcoming sailing competitions.

Wind-Driven Waves in Tampa Bay, Florida

NASA Astrophysics Data System (ADS)

Gilbert, S. A.; Meyers, S. D.; Luther, M. E.

2002-12-01

Turbidity and nutrient flux due to sediment resuspension by waves and currents are important factors controlling water quality in Tampa Bay. During December 2001 and January 2002, four Sea Bird Electronics SeaGauge wave and tide recorders were deployed in Tampa Bay in each major bay segment. Since May 2002, a SeaGauge has been continuously deployed at a site in middle Tampa Bay as a component of the Bay Regional Atmospheric Chemistry Experiment (BRACE). Initial results for the summer 2002 data indicate that significant wave height is linearly dependent on wind speed and direction over a range of 1 to 12 m/s. The data were divided into four groups according to wind direction. Wave height dependence on wind speed was examined for each group. Both northeasterly and southwesterly winds force significant wave heights that are about 30% larger than those for northwesterly and southeasterly winds. This difference is explained by variations in fetch due to basin shape. Comparisons are made between these observations and the results of a SWAN-based model of Tampa Bay. The SWAN wave model is coupled to a three-dimensional circulation model and computes wave spectra at each model grid cell under observed wind conditions and modeled water velocity. When SWAN is run without dissipation, the model results are generally similar in wave period but about 25%-50% higher in significant wave height than the observations. The impact of various dissipation mechanisms such as bottom drag and whitecapping on the wave state is being investigated. Preliminary analyses on winter data give similar results.

Transmission of hemic neoplasia in the bay mussel, Mytilus edulis, using whole cells and cell homogenate.

PubMed

Elston, R A; Kent, M L; Drum, A S

1988-01-01

Experimental studies with hemic neoplasia in the bay mussel indicated that the condition can be transmitted allogeneically with intact whole cells and cell-free homogenate. A differential pathogenesis of the disease in mussels receiving the two different inocula supports the argument that actual cell transplantation occurred. In addition to the first demonstration of the infectious nature of the disease with cell-free homogenates, it was also shown that the disease is transmitted by cohabitation. Remission of the disease occurred in some mussels indicating individual variation in recognition mechanisms.

Space-variant restoration of images degraded by camera motion blur.

PubMed

Sorel, Michal; Flusser, Jan

2008-02-01

We examine the problem of restoration from multiple images degraded by camera motion blur. We consider scenes with significant depth variations resulting in space-variant blur. The proposed algorithm can be applied if the camera moves along an arbitrary curve parallel to the image plane, without any rotations. The knowledge of camera trajectory and camera parameters is not necessary. At the input, the user selects a region where depth variations are negligible. The algorithm belongs to the group of variational methods that estimate simultaneously a sharp image and a depth map, based on the minimization of a cost functional. To initialize the minimization, it uses an auxiliary window-based depth estimation algorithm. Feasibility of the algorithm is demonstrated by three experiments with real images.

Algorithmic-Reducibility = Renormalization-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') Replacing CRUTCHES!!!: Gauss Modular/Clock-Arithmetic Congruences = Signal X Noise PRODUCTS..

NASA Astrophysics Data System (ADS)

Siegel, J.; Siegel, Edward Carl-Ludwig

2011-03-01

Cook-Levin computational-"complexity"(C-C) algorithmic-equivalence reduction-theorem reducibility equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited with Gauss modular/clock-arithmetic/model congruences = signal X noise PRODUCT reinterpretation. Siegel-Baez FUZZYICS=CATEGORYICS(SON of ``TRIZ''): Category-Semantics(C-S) tabular list-format truth-table matrix analytics predicts and implements "noise"-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics(1987)]-Sipser[Intro. Theory Computation(1997) algorithmic C-C: "NIT-picking" to optimize optimization-problems optimally(OOPO). Versus iso-"noise" power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, this "NIT-picking" is "noise" power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-"science" algorithmic C-C models: Turing-machine, finite-state-models/automata, are identified as early-days once-workable but NOW ONLY LIMITING CRUTCHES IMPEDING latter-days new-insights!!!

The theory of variational hybrid quantum-classical algorithms

NASA Astrophysics Data System (ADS)

McClean, Jarrod R.; Romero, Jonathan; Babbush, Ryan; Aspuru-Guzik, Alán

2016-02-01

Many quantum algorithms have daunting resource requirements when compared to what is available today. To address this discrepancy, a quantum-classical hybrid optimization scheme known as ‘the quantum variational eigensolver’ was developed (Peruzzo et al 2014 Nat. Commun. 5 4213) with the philosophy that even minimal quantum resources could be made useful when used in conjunction with classical routines. In this work we extend the general theory of this algorithm and suggest algorithmic improvements for practical implementations. Specifically, we develop a variational adiabatic ansatz and explore unitary coupled cluster where we establish a connection from second order unitary coupled cluster to universal gate sets through a relaxation of exponential operator splitting. We introduce the concept of quantum variational error suppression that allows some errors to be suppressed naturally in this algorithm on a pre-threshold quantum device. Additionally, we analyze truncation and correlated sampling in Hamiltonian averaging as ways to reduce the cost of this procedure. Finally, we show how the use of modern derivative free optimization techniques can offer dramatic computational savings of up to three orders of magnitude over previously used optimization techniques.

Cook-Levin Theorem Algorithmic-Reducibility/Completeness = Wilson Renormalization-(Semi)-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') REPLACING CRUTCHES!!!: Models: Turing-machine, finite-state-models, finite-automata

NASA Astrophysics Data System (ADS)

Young, Frederic; Siegel, Edward

Cook-Levin theorem theorem algorithmic computational-complexity(C-C) algorithmic-equivalence reducibility/completeness equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited via Siegel FUZZYICS =CATEGORYICS = ANALOGYICS =PRAGMATYICS/CATEGORY-SEMANTICS ONTOLOGY COGNITION ANALYTICS-Aristotle ``square-of-opposition'' tabular list-format truth-table matrix analytics predicts and implements ''noise''-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics (1987)]-Sipser[Intro.Thy. Computation(`97)] algorithmic C-C: ''NIT-picking''(!!!), to optimize optimization-problems optimally(OOPO). Versus iso-''noise'' power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, ''NIT-picking'' is ''noise'' power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-''science''/SEANCE algorithmic C-C models: Turing-machine, finite-state-models, finite-automata,..., discrete-maths graph-theory equivalence to physics Feynman-diagrams are identified as early-days once-workable valid but limiting IMPEDING CRUTCHES(!!!), ONLY IMPEDE latter-days new-insights!!!

Computer methods for sampling from the gamma distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, M.E.; Tadikamalla, P.R.

1978-01-01

Considerable attention has recently been directed at developing ever faster algorithms for generating gamma random variates on digital computers. This paper surveys the current state of the art including the leading algorithms of Ahrens and Dieter, Atkinson, Cheng, Fishman, Marsaglia, Tadikamalla, and Wallace. General random variate generation techniques are explained with reference to these gamma algorithms. Computer simulation experiments on IBM and CDC computers are reported.

VIIRS validation and algorithm development efforts in coastal and inland Waters

NASA Astrophysics Data System (ADS)

Stengel, E.; Ondrusek, M.

2016-02-01

Accurate satellite ocean color measurements in coastal and inland waters are more challenging than open-ocean measurements. Complex water and atmospheric conditions can limit the utilization of remote sensing data in coastal waters where it is most needed. The Coastal Optical Characterization Experiment (COCE) is an ongoing project at NOAA/NESDIS/STAR Satellite Oceanography and Climatology Division. The primary goals of COCE are satellite ocean color validation and application development. Currently, this effort concentrates on the initialization and validation of the Joint Polar Satellite System (JPSS) VIIRS sensor using a Satlantic HyperPro II radiometer as a validation tool. A report on VIIRS performance in coastal waters will be given by presenting comparisons between in situ ground truth measurements and VIIRS retrievals made in the Chesapeake Bay, and inland waters of the Gulf of Mexico and Puerto Rico. The COCE application development effort focuses on developing new ocean color satellite remote sensing tools for monitoring relevant coastal ocean parameters. A new VIIRS total suspended matter algorithm will be presented for the Chesapeake Bay. These activities improve the utility of ocean color satellite data in monitoring and analyzing coastal and oceanic processes. Progress on these activities will be reported.

Autonomous Navigation for Autonomous Underwater Vehicles Based on Information Filters and Active Sensing

PubMed Central

He, Bo; Zhang, Hongjin; Li, Chao; Zhang, Shujing; Liang, Yan; Yan, Tianhong

2011-01-01

This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV) C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM), and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China). Weak links in the information matrix in an extended information filter (EIF) can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM). All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM. PMID:22346682

Autonomous navigation for autonomous underwater vehicles based on information filters and active sensing.

PubMed

He, Bo; Zhang, Hongjin; Li, Chao; Zhang, Shujing; Liang, Yan; Yan, Tianhong

2011-01-01

This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV) C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM), and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China). Weak links in the information matrix in an extended information filter (EIF) can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM). All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM.

Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data

PubMed Central

Zhang, Nannan; Wu, Lifeng; Yang, Jing; Guan, Yong

2018-01-01

The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis. PMID:29401730

Statistical Methods Applied to Gamma-ray Spectroscopy Algorithms in Nuclear Security Missions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fagan, Deborah K.; Robinson, Sean M.; Runkle, Robert C.

2012-10-01

In a wide range of nuclear security missions, gamma-ray spectroscopy is a critical research and development priority. One particularly relevant challenge is the interdiction of special nuclear material for which gamma-ray spectroscopy supports the goals of detecting and identifying gamma-ray sources. This manuscript examines the existing set of spectroscopy methods, attempts to categorize them by the statistical methods on which they rely, and identifies methods that have yet to be considered. Our examination shows that current methods effectively estimate the effect of counting uncertainty but in many cases do not address larger sources of decision uncertainty—ones that are significantly moremore » complex. We thus explore the premise that significantly improving algorithm performance requires greater coupling between the problem physics that drives data acquisition and statistical methods that analyze such data. Untapped statistical methods, such as Bayes Modeling Averaging and hierarchical and empirical Bayes methods have the potential to reduce decision uncertainty by more rigorously and comprehensively incorporating all sources of uncertainty. We expect that application of such methods will demonstrate progress in meeting the needs of nuclear security missions by improving on the existing numerical infrastructure for which these analyses have not been conducted.« less

Recognition of pornographic web pages by classifying texts and images.

PubMed

Hu, Weiming; Wu, Ou; Chen, Zhouyao; Fu, Zhouyu; Maybank, Steve

2007-06-01

With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image classifier, the object's contour-based features are extracted to recognize pornographic images. In the text and image fusion algorithm, the Bayes theory is used to combine the recognition results from images and texts. Experimental results demonstrate that the continuous text classifier outperforms the traditional keyword-statistics-based classifier, the contour-based image classifier outperforms the traditional skin-region-based image classifier, the results obtained by our fusion algorithm outperform those by either of the individual classifiers, and our framework can be adapted to different categories of Web pages.

Empirical Bayes scan statistics for detecting clusters of disease risk variants in genetic studies.

PubMed

McCallum, Kenneth J; Ionita-Laza, Iuliana

2015-12-01

Recent developments of high-throughput genomic technologies offer an unprecedented detailed view of the genetic variation in various human populations, and promise to lead to significant progress in understanding the genetic basis of complex diseases. Despite this tremendous advance in data generation, it remains very challenging to analyze and interpret these data due to their sparse and high-dimensional nature. Here, we propose novel applications and new developments of empirical Bayes scan statistics to identify genomic regions significantly enriched with disease risk variants. We show that the proposed empirical Bayes methodology can be substantially more powerful than existing scan statistics methods especially so in the presence of many non-disease risk variants, and in situations when there is a mixture of risk and protective variants. Furthermore, the empirical Bayes approach has greater flexibility to accommodate covariates such as functional prediction scores and additional biomarkers. As proof-of-concept we apply the proposed methods to a whole-exome sequencing study for autism spectrum disorders and identify several promising candidate genes. © 2015, The International Biometric Society.

Influence of marine current on vertical migration of Pb in marine bay

NASA Astrophysics Data System (ADS)

Yu, Chen; Hong, Ai; Danfeng, Yang; Huijuan, Zhao; Dongfang, Yang

2018-02-01

This paper analyzed that vertical migration of Pb contents waters in Jiaozhou Bay, and revealed the influence of marine current on vertical migration process. Results showed that Pb contents in bottom waters of Jiaozhou Bay in April and July 1988 were 1.49-18.53 μg L-1 and 12.68/-27.64 μg L-1, respectively. The pollution level of Pb in bottom waters was moderate to heavy, and were showing temporal variations and spatial heterogeneity. The vertical migration process of Pb in April 1988 included a drifting process from the southwest to the north by means of the marine current was rapid in this region. The vertical migration process of Pb in July 1988 in the open waters included no drifting process since the flow rate of marine current was relative low in this region. The vertical migration process of Pb was jointly determined by vertical water’s effect, source input and water exchange, and the influence of marine current on the vertical migration of Pb in marine bay was significant.

An historical perspective on eutrophication in the Pensacola ...

EPA Pesticide Factsheets

In this chapter, we provide a brief description of the Pensacola Bay estuary, examining the available historical data for evidence of trends in eutrophication within the estuary. Common to many industrialized estuaries, Pensacola Bay has been subjected to unregulated point sources of nutrients and other contaminants, peaking during the 1950s and 1960s. Also, over the past 60 years, the region has experienced a 5-fold increase in population in the watershed and a doubling of river nitrate concentrations. Today, the estuary exhibits classical symptoms of eutrophication, including extensive summer hypoxia, significant loss of seagrass habitat, and phytoplankton dynamics that respond strongly to seasonal and interannual variation in freshwater flow. Surprisingly, Pensacola Bay appears to have low nutrient concentrations, moderate productivity, and high water transparency; characteristics that appear to have persisted during a period of rapid human population growth. We find the lack of demonstrable changes in the distribution of phytoplankton biomass or distribution and severity of hypoxia during a period of increasing human population pressures enigmatic. This brief manuscript summarizes historical water quality data from Pensacola Bay Florida

Factors Influencing Spatial and Annual Variability in Eelgrass (Zostera marina L.) Meadows in Willapa Bay, Washington, and Coos Bay, Oregon, Estuaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thom, Ronald M.; Borde, Amy B.; Rumrill, Steven

2003-08-01

Environmental factors that influence annual variability and spatial differences in eelgrass meadows (Zostera marina L.) were examined within Willapa Bay, WA, and Coos Bay, OR, over a period of 4 years (1998-2001). A suite of eelgrass metrics were recorded annually at field sites that spanned the estuarine gradient from the marine-dominated to mesohaline regions. Growth of eelgrass plants was also monitored on a monthly basis within Sequim Bay, WA. Both the spatial cover and density of Z. marina were positively correlated with estuarine salinity and inversely correlated with temperature of the tideflat sediment. Experimental evidence verified that optimal eelgrass growthmore » occurred at highest salinities and relatively low temperatures. Eelgrass density, biomass, and the incident of flowering plants all increased substantially in Willapa Bay, and less so in Coos Bay, over the duration of the study. Warmer winters and cooler summers associated with the transition from El Ni?o to La Ni?a ocean conditions during the study period were correlated with the increase in eelgrass abundance and flowering. Anthropogenic factors (e.g., disturbance and erosion by vessel wakes and recreational shellfishing activities) may have contributed to spatial variability. Our findings indicate that large-scale changes in climate and nearshore ocean conditions can exert a strong regional influence on eelgrass abundance, which can vary annually by as much as 700% in Willapa Bay. Lower levels of variability observed in Coos Bay may be due to the stronger and more direct influence of the nearshore Pacific Ocean. We conclude that climate variation may have profound effects on the abundance and distribution of eelgrass meadows throughout the Pacific Northwest, and we anticipate that ocean conditions will emerge as a primary driving force for living estuarine resources and ecological processes that are associated with Z. marina beds within the landscape of these estuarine tidal basins.« less

Bayesian Quantification of Contrast-Enhanced Ultrasound Images With Adaptive Inclusion of an Irreversible Component.

PubMed

Rizzo, Gaia; Tonietto, Matteo; Castellaro, Marco; Raffeiner, Bernd; Coran, Alessandro; Fiocco, Ugo; Stramare, Roberto; Grisan, Enrico

2017-04-01

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity and it can be particularly useful in early detection and grading of arthritis. In a recent study we have shown that a Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. However, in some cases the heterogeneity of the kinetics can be such that even the Gamma model does not properly describe the curve, with a high number of outliers. In this work we apply to CEUS data the single compartment recirculation model (SCR) which takes explicitly into account the trapping of the microbubbles contrast agent by adding to the single Gamma-variate model its integral. The SCR model, originally proposed for dynamic-susceptibility magnetic resonance imaging, is solved here at pixel level within a Bayesian framework using Variational Bayes (VB). We also include the automatic relevant determination (ARD) algorithm to automatically infer the model complexity (SCR vs. Gamma model) from the data. We demonstrate that the inclusion of trapping best describes the CEUS patterns in 50% of the pixels, with the other 50% best fitted by a single Gamma. Such results highlight the necessity of the use ARD, to automatically exclude the irreversible component where not supported by the data. VB with ARD returns precise estimates in the majority of the kinetics (88% of total percentage of pixels) in a limited computational time (on average, 3.6 min per subject). Moreover, the impact of the additional trapping component has been evaluated for the differentiation of rheumatoid and non-rheumatoid patients, by means of a support vector machine classifier with backward feature selection. The results show that the trapping parameter is always present in the selected feature set, and improves the classification.

Acoustic detection of ice crystals in Antarctic waters

NASA Astrophysics Data System (ADS)

Penrose, John D.; Conde, M.; Pauly, T. J.

1994-06-01

During the voyage of the RSV Aurora Australis to the region of Prydz Bay, Antarctica in January-March 1991, ice crystals were encountered at depths from the surface to 125-m in the western area of the bay. On two occasions, crystals were retrieved by netting, and echo sounder records have been used to infer additional regions of occurrence. Acoustic target strength estimates made on the ice crystal assemblies encountered show significant spatial variation, which may relate to crystal size and/or aggregation. Data from a suite of conductivity-temperature-depth casts have been used to map regions of the study area where in situ water temperatures fell below the computed freezing point. Such regions correlate well with those selected on the basis of echogram type and imply that ice crystals occurred at depth over large areas of the bay during the cruise period. The ice crystal distribution described is consistent with that expected from a plume of supercooled water emerging from under the Amery Ice Shelf and forming part of the general circulation of the bay. The magnitude of the supercooled water plume is greater than those reported previously in the Prydz Bay region. If misinterpreted as biota on echo sounder records, ice crystals could significantly bias biomass estimates based on echo integration in this and potentially other areas.

Drivers of Variability of Diel-Cycling and Episodic Hypoxia In ...

EPA Pesticide Factsheets

Eutrophication of coastal ecosystems is a longstanding environmental concern, exacerbated by population growth and associated nutrient pollution, and ultimately resulting in increased incidence of hypoxia. Shallow and highly productive estuaries and embayments are particularly susceptible to diel-cycling hypoxia, associated with day-night cycles of production and respiration, which can cause extreme excursions in dissolved oxygen (DO) concentrations from anoxia to super-saturation within a single day. Diel oxygen dynamics in these systems are complex, and may be influenced by wind forcing, vertical and horizontal mixing, variation in freshwater inflow, cloud cover, and temperature. To better understand the environmental drivers of periodic hypoxia, this study examined four northern Gulf of Mexico Estuaries (Weeks Bay, AL; Wolf Bay, AL; Fowl River, AL; and St. Louis Bay, MS). Dissolved oxygen varied strongly on a diel basis in all four systems, with periods of sustained low oxygen (>24 h) observed in both Weeks Bay and Wolf Bay. The duration and persistence of hypoxia further varied in response to changing salinity regimes and regional weather. These results underscore the dynamic nature of hypoxia in shallow estuarine systems, and highlight the importance of combining fixed site continuous monitoring data with spatial hydrographic surveys to accurately resolve DO dynamics. This abstract is submitted for presentation at the CERF conference held Nov 8-12 in Oregon

Origins of cryptic variation in the Ediacaran-Fortunian rhyolitic ignimbrites of the Saldanha Bay Volcanic Complex, Western Cape, South Africa

NASA Astrophysics Data System (ADS)

Clemens, J. D.; Stevens, G.; Frei, D.; Joseph, C. S. A.

2017-12-01

The Saldanha eruption centre, on the West Coast of South Africa, consists of 542 Ma, intracaldera, S-type, rhyolite ignimbrites divided into the basal Saldanha Ignimbrite and the partly overlying Jacob's Bay Ignimbrite. Depleted-mantle Nd model ages suggest magma sources younger than the Early Mesoproterozoic, and located within the Neoproterozoic Malmesbury Group and Swartland complex metasedimentary and metavolcanic rocks that form the regional basement. The Sr isotope systematics suggest that the dominant source rocks were metavolcaniclastic rocks and metagreywackes, and that the magmas formed from separate batches extracted from the same heterogeneous source. No apparent magma mixing trends relate the Saldanha to the Jacob's Bay Ignimbrites, or either of these to the magmas that formed the Plankiesbaai or Tsaarsbank Ignimbrites in the neighbouring Postberg eruption centre. The magmas were extracted from their source rocks carrying small but significant proportions of peritectic and restitic accessory minerals. Variations in the content of this entrained crystal cargo were responsible for most of the chemical variations in the magmas. Although we cannot construct a cogent crystal fractionation model to relate these groups of magmas, at least some crystal fractionation occurred, as an overlay on the primary signal due to peritectic assemblage entrainment (PAE). Thus, the causes of the cryptic chemical variation among the ignimbrite magmas of the Saldanha centre are variable, but dominated by the compositions of the parent melts and PAE. The preservation of clear, source-inherited chemical signatures, in individual samples, calls into question the common interpretation of silicic calderas as having been formed in large magma reservoirs, with magma compositions shaped by magma mingling, mixing, and fractional crystallization. The Saldanha rocks suggest a more intimate connection between source and erupted magma, and perhaps indicate that silicic magmas are too viscous to be significantly modified by magma-chamber processes.

Use of empirical and full Bayes before-after approaches to estimate the safety effects of roadside barriers with different crash conditions.

PubMed

Park, Juneyoung; Abdel-Aty, Mohamed; Lee, Jaeyoung

2016-09-01

Although many researchers have estimated the crash modification factors (CMFs) for specific treatments (or countermeasures), there is a lack of prior studies that have explored the variation of CMFs. Thus, the main objectives of this study are: (a) to estimate CMFs for the installation of different types of roadside barriers, and (b) to determine the changes of safety effects for different crash types, severities, and conditions. Two observational before-after analyses (i.e. empirical Bayes (EB) and full Bayes (FB) approaches) were utilized in this study to estimate CMFs. To consider the variation of safety effects based on different vehicle, driver, weather, and time of day information, the crashes were categorized based on vehicle size (passenger and heavy), driver age (young, middle, and old), weather condition (normal and rain), and time difference (day time and night time). The results show that the addition of roadside barriers is safety effective in reducing severe crashes for all types and run-off roadway (ROR) crashes. On the other hand, it was found that roadside barriers tend to increase all types of crashes for all severities. The results indicate that the treatment might increase the total number of crashes but it might be helpful in reducing injury and severe crashes. In this study, the variation of CMFs was determined for ROR crashes based on the different vehicle, driver, weather, and time information. Based on the findings from this study, the variation of CMFs can enhance the reliability of CMFs for different roadway conditions in decision making process. Also, it can be recommended to identify the safety effects of specific treatments for different crash types and severity levels with consideration of the different vehicle, driver, weather, and time of day information. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

A NEW METHOD OF PEAK DETECTION FOR ANALYSIS OF COMPREHENSIVE TWO-DIMENSIONAL GAS CHROMATOGRAPHY MASS SPECTROMETRY DATA.

PubMed

Kim, Seongho; Ouyang, Ming; Jeong, Jaesik; Shen, Changyu; Zhang, Xiang

2014-06-01

We develop a novel peak detection algorithm for the analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) data using normal-exponential-Bernoulli (NEB) and mixture probability models. The algorithm first performs baseline correction and denoising simultaneously using the NEB model, which also defines peak regions. Peaks are then picked using a mixture of probability distribution to deal with the co-eluting peaks. Peak merging is further carried out based on the mass spectral similarities among the peaks within the same peak group. The algorithm is evaluated using experimental data to study the effect of different cut-offs of the conditional Bayes factors and the effect of different mixture models including Poisson, truncated Gaussian, Gaussian, Gamma, and exponentially modified Gaussian (EMG) distributions, and the optimal version is introduced using a trial-and-error approach. We then compare the new algorithm with two existing algorithms in terms of compound identification. Data analysis shows that the developed algorithm can detect the peaks with lower false discovery rates than the existing algorithms, and a less complicated peak picking model is a promising alternative to the more complicated and widely used EMG mixture models.

Research on compressive sensing reconstruction algorithm based on total variation model

NASA Astrophysics Data System (ADS)

Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

2017-12-01

Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

Seasonal variations of phytoplankton assemblages and its relation to environmental variables in a scallop culture sea area of Bohai Bay, China.

PubMed

Chen, Yang-Hang; Gao, Ya-Hui; Chen, Chang-Ping; Liang, Jun-Rong; Sun, Lin; Zhen, Yu; Qiao, Ling

2016-12-15

Seasonal variations of phytoplankton assemblages were examined in a scallop culture sea area of Bohai Bay (China) with regard to some major physical and chemical variables. Samples were collected at three stations from July 2011 to September 2013. A total of 134 species belong to 4 phyla were identified, of which 104 were diatoms, 27 were dinoflagellates, 1 was euglenophyte and 2 were chrysophytes. The cells abundance in autumn (55.44×10 3 cells/L) was higher than that in summer (6.99×10 3 cells/L), spring (3.46×10 3 cells/L) and winter (2.69×10 3 cells/L). The Shannon-Wiener diversity index was higher in summer (3.06), followed by spring (3.02) and winter (2.91), and low in autumn (1.40). Results of canonical correspondence analysis showed that phosphate, salinity, temperature, silicate and DIN/SiO 2 ratio were the most important environmental factors influencing the variation of phytoplankton community structure. It is suggested that eutrophication resulted from scallop culture would cause a potential red tide risk. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of marine pollution in Izmir Bay: nutrient, heavy metal and total hydrocarbon concentrations.

PubMed

Kucuksezgin, F; Kontas, A; Altay, O; Uluturhan, E; Darilmaz, E

2006-01-01

Izmir Bay (western Turkey) is one of the great natural bays of the Mediterranean. Izmir is an important industrial and commercial centre and a cultural focal point. The main industries in the region include food processing, oil, soap and paint production, chemical industries, paper and pulp factories, textile industries and metal processing. The mean concentrations showed ranges of 0.01-0.19 and 0.01-10 microM for phosphate, 0.10-1.8 and 0.12-27 microM for nitrate+nitrite, and 0.30-5.8 and 0.43-39 microM for silicate in the outer and middle-inner bays, respectively. The TNO(x)/PO(4) ratio is significantly lower than the Redfield's ratio and nitrogen is the limiting element in the middle-inner bays. Diatoms and dinoflagellates were observed all year around in the bay and are normally nitrogen limited. Metal concentrations ranged between Hg: 0.05-1.3, Cd: 0.005-0.82, Pb: 14-113 and Cr: 29-316 microg g(-1) in the sediments. The results showed significant enrichments during sampling periods from Inner Bay. Outer and middle bays show low levels of heavy metal enrichments except estuary of Gediz River. The concentrations of Hg, Cd and Pb in the outer bay were generally similar to the background levels from the Mediterranean. The levels gradually decreased over the sampling period. Total hydrocarbons concentrations range from 427 to 7800 ng g(-1) of sediments. The highest total hydrocarbon levels were found in the inner bay due to the anthropogenic activities, mainly combustion processes of traffic and industrial activities. The concentrations of heavy metals found in fish varied for Hg: 4.5-520, Cd: 0.10-10 and Pb: 0.10-491 microg kg(-1) in Izmir Bay. There was no significant seasonal variation in metal concentrations. An increase in Hg concentration with increasing length was noted for Mullus barbatus. A person can consume more than 2, 133 and 20 meals per week of fish in human diet would represent the tolerable weekly intake of mercury, cadmium and lead, respectively, in Izmir Bay. Heavy metal levels were lower than the results in fish tissues reported from polluted areas of the Mediterranean Sea.

Measuring the Carolina Bays Using Archetype Template Overlays on the Google Earth Virtual Globe; Planform Metrics for 25,000 Bays Extracted from LiDAR and Satellite Imagery

NASA Astrophysics Data System (ADS)

Davias, M. E.; Gilbride, J. L.

2011-12-01

Aerial photographs of Carolina bays taken in the 1930's sparked the initial research into their geomorphology. Satellite Imagery available today through the Google Earth Virtual Globe facility expands the regions available for interrogation, but reveal only part of their unique planforms. Digital Elevation Maps (DEMs), using Light Detection And Ranging (LiDAR) remote sensing data, accentuate the visual presentation of these aligned ovoid shallow basins by emphasizing their robust circumpheral rims. To support a geospatial survey of Carolina bay landforms in the continental USA, 400,000 km2 of hsv-shaded DEMs were created as KML-JPEG tile sets. A majority of these DEMs were generated with LiDAR-derived data. We demonstrate the tile generation process and their integration into Google Earth, where the DEMs augment available photographic imagery for the visualization of bay planforms. While the generic Carolina bay planform is considered oval, we document subtle regional variations. Using a small set of empirically derived planform shapes, we created corresponding Google Earth overlay templates. We demonstrate the analysis of an individual Carolina bay by placing an appropriate overlay onto the virtually globe, then orientating, sizing and rotating it by edit handles such that it satisfactorily represents the bay's rim. The resulting overlay data element is extracted from Google Earth's object directory and programmatically processed to generate metrics such as geographic location, elevation, major and minor axis and inferred orientation. Utilizing a virtual globe facility for data capture may result in higher quality data compared to methods that reference flat maps, where geospatial shape and orientation of the bays could be skewed and distorted in the orthographic projection process. Using the methodology described, we have measured over 25k distinct Carolina bays. We discuss the Google Fusion geospatial data repository facility, through which these data have been assembled and made web-accessible to other researchers. Preliminary findings from the survey are discussed, such as how bay surface area, eccentricity and orientation vary across ~800 1/4° × 1/4° grid elements. Future work includes measuring 25k additional bays, as well as interrogation of the orientation data to identify any possible systematic geospatial relationships.

Variations in water clarity and bottom albedo in Florida Bay from 1985 to 1997

USGS Publications Warehouse

Stumpf, R.P.; Frayer, M.L.; Durako, M.J.; Brock, J.C.

1999-01-01

Following extensive seagrass die-offs of the late 1980s and early 1990s, Florida Bay reportedly had significant declines in water clarity due to turbidity and algal blooms. Scant information exists on the extent of the decline, as this bay was not investigated for water quality concerns before the die-offs and limited areas were sampled after the primary die-off. We use imagery from the Advanced Very High Resolution Radiometer (AVHRR) to examine water clarity in Florida Bay for the period 1985 to 1997. The AVHRR provides data on nominal water reflectance and estimated fight attenuation, which are used here to describe turbidity conditions in the bay on a seasonal basis. In situ observations on changes in seagrass abundance within the bay, combined with the satellite data, provide additional insights into losses of seagrass. The imagery shows an extensive region to the west of Florida Bay having increased reflectance and fight attenuation in both winter and summer beginning in winter of 1988. These increases are consistent with a change from dense seagrass to sparse or negligible cover. Approximately 200 km2 of these offshore seagrasses may have been lost during the primary die-off (1988 through 1991), significantly more than in the bay. The imagery shows the distribution and timing of increased turbidity that followed the die-offs in the northwestern regions of the bay, exemplified in Rankin Lake and Johnson Key Basin, and indicates that about 200 km2 of dense seagrass may have been lost or severely degraded within the bay from the start of the die-off. The decline in water clarity has continued in the northwestern bay since 1991. The area west of the Everglades National Park boundaries has shown decreases in both winter turbidity and summer reflectances, suggestive of partial seagrass recovery. Areas of low reflectance associated with a major Syringodium filiforme seagrass meadow north of Marathon (Vaca Key, in the Florida Keys) appear to have expanded westward toward Big Pine Key, indicating changes in the bottom cover from before the die-off. The southern and eastern sections of the Bay have not shown significant changes in water clarity or bottom albedo throughout the entire time period.

Spatial variation in sediment-water exchange of phosphorus in Florida Bay: AMP as a model organic compound.

PubMed

Huang, Xiao-Lan; Zhang, Jia-Zhong

2010-10-15

Dissolved organic phosphorus (DOP) has been recognized as dominant components in total dissolved phosphorus (TDP) pools in many coastal waters, and its exchange between sediment and water is an important process in biogeochemical cycle of phosphorus. Adenosine monophosphate (AMP) was employed as a model DOP compound to simulate phosphorus exchange across sediment-water interface in Florida Bay. The sorption data from 40 stations were fitted to a modified Freundlich equation and provided a detailed spatial distribution both of the sediment's zero equilibrium phosphorus concentration (EPC(0-T)) and of the distribution coefficient (K(d-T)) with respect to TDP. The K(d-T) was found to be a function of the index of phosphorus saturation (IPS), a molar ratio of the surface reactive phosphorus to the surface reactive iron oxide content in the sediment, across the entire bay. However, the EPC(0-T) was found to correlate to the contents of phosphorus in the eastern bay only. Sediment in the western bay might act as a source of the phosphorus in the exchange process due to their high EPC(0-T) and low K(d-T), whereas sediments in the eastern bay might act as a sink because of their low EPC(0-T) and high K(d-T). These results strongly support the hypothesis that both phosphorus and iron species in calcareous marine sediments play a critical role in governing the sediment-water exchange of both phosphate and DOP in the coastal and estuarine ecosystems.

Phosphate oxygen isotope ratios as a tracer for sources and cycling of phosphate in North San Francisco Bay, California

USGS Publications Warehouse

McLaughlin, K.; Kendall, C.; Silva, S.R.; Young, M.; Paytan, A.

2006-01-01

A seasonal analysis assesing variations in the oxygen isotopic composition of dissolved inorganic phosphate (DIP) was conducted in the San Francisco Bay estuarine system, California. Isotopic fractionation of oxygen in DIP (exchange of oxygen between phosphate and environmental water) at surface water temperatures occurs only as a result of enzyme-mediated, biological reactions. Accordingly, if phospate demand is low relative to input and phosphate is not heavily cycled in the ecosystem, the oxygen isotopic composition of DIP (?? 18Op) will reflect the isotopic composition of the source of phosphate to the system. Such is the case for the North San Francisco Bay, an anthropogenically impacted estuary with high surface water phosphate concentrations. Variability in the ?? 18Op in the bay is primarily controlled by mixing of water masses with different ??18Op signatures. The ??18Op values range from 11.4??? at the Sacramento River to 20.1??? at the Golden Gate. Deviations from the two-component mixing model for the North Bay reflect additional, local sources of phosphate to the estuary that vary seasonally. Most notably, deviations from the mixing model occur at the confluence of a major river into the bay during periods of high river discharge and near wastewater treatment outlets. These data suggest that ??18Op can be an effective tool for identifying P point sources and understanding phosphate dynamics in estuarine systems. Copyright 2006 by the American Geophysical Union.

PHENOTYPIC PLASTICITY INDUCED IN TRANSPLANT EXPERIMENTS IN A MUTUALISTIC ASSOCIATION BETWEEN THE RED ALGA JANIA ADHAERENS (RHODOPHYTA, CORALLINALES) AND THE SPONGE HALICLONA CAERULEA (PORIFERA: HAPLOSCLERIDA): MORPHOLOGICAL RESPONSES OF THE ALGA(1).

PubMed

Enríquez, Susana; Ávila, Enrique; Carballo, José Luis

2009-02-01

The association between the red macroalga Jania adhaerens J. V. Lamour. and the sponge Haliclona caerulea is the most successful life-form between 2 and 4 m depth in Mazatlán Bay (Mexican Pacific). J. adhaerens colonizes the rocky intertidal area and penetrates into deeper areas only when it lives in association with H. caerulea. The aposymbiotic form of the sponge has not been reported in the bay. To understand the ecological success of this association, we examined the capacity of J. adhaerens to acclimate in Mazatlán Bay using transplant experiments. The transplanted aposymbiotic J. adhaerens did not survive the first 2 weeks; however, J. adhaerens when living in association with H. caerulea, acclimated easily to depth, showing no sign of mortality during the 103 d of the experiment. We conclude that the ability of J. adhaerens to colonize in deeper areas in this hydrodynamic environment may in part rely on the protection provided by the sponge to the algal canopy. Both species contribute to the shape of the associated form. Nevertheless, the morphological variation in the association appears to be dominated by the variation in J. adhaerens canopy to regulate pigment self-shading under light-limited conditions and/or tissue resistance under high hydrodynamics. Consequently, our results are consistent with light as the abiotic controlling factor, which regulates the lower depth distribution of the association in Mazatlán Bay, through limiting the growth rate of J. adhaerens. Hydrodynamics may determine the upper limit of the association by imposing high mass losses. © 2009 Phycological Society of America.

Crustal structure of the North Iberian continental margin from seismic refraction/wide-angle reflection profiles

NASA Astrophysics Data System (ADS)

Ruiz, M.; Díaz, J.; Pedreira, D.; Gallart, J.; Pulgar, J. A.

2017-10-01

The structure and geodynamics of the southern margin of the Bay of Biscay have been investigated from a set of 11 multichannel seismic reflection profiles, recorded also at wide angle offsets in an onshore-offshore network of 24 OBS/OBH and 46 land sites. This contribution focuses on the analysis of the wide-angle reflection/refraction data along representative profiles. The results document strong lateral variations of the crustal structure along the margin and provide an extensive test of the crustal models previously proposed for the northern part of the Iberian Peninsula. Offshore, the crust has a typical continental structure in the eastern tip of the bay, which disappears smoothly towards the NW to reach crustal thickness close to 10 km at the edge of the studied area ( 45°N, 6°W). The analysis of the velocity-depth profiles, altogether with additional information provided by the multichannel seismic data and magnetic surveys, led to the conclusion that the crust in this part of the bay should be interpreted as transitional from continental to oceanic. Typical oceanic crust has not been imaged in the investigated area. Onshore, the new results are in good agreement with previous results and document the indentation of the Bay of Biscay crust into the Iberian crust, forcing its subduction to the North. The interpreted profiles show that the extent of the southward indentation is not uniform, with an Alpine root less developed in the central and western sector of the Basque-Cantabrian Basin. N-S to NE-SW transfer structures seem to control those variations in the indentation degree.

The role of thermal stratification in tidal exchange at the mouth of San Diego Bay

USGS Publications Warehouse

Chadwick, D. B.; Largier, J. L.; Cheng, R.T.; Aubrey, D.G.; Friedrichs, C.T.; Aubrey, D.G.; Friedrichs, C.T.

1996-01-01

We have examined, from an observational viewpoint, the role of thermal stratification in the tidal exchange process at the mouth of San Diego Bay. In this region, we found that both horizontal and vertical exchange processes appear to be active. The vertical exchange in this case was apparently due to the temperature difference between the'bay water and ocean water. We found that the structure of the outflow and the nature of the tidal exchange process both appear to be influenced by thermal stratification. The tidal outflow was found to lift-off tan the bottom during the initial and later stages of the ebb flow when barotropic forcing was weak. During the peak ebb flow, the mouth section was flooded, and the outflow extended to the bottom. As the ebb flow weakened, a period of two-way exchange occurred, with the surface layer flowing seaward, and the deep layer flowing into the bay. The structure of the tidal-residual flow and the residual transport of a measured tracer were strongly influenced by this vertical exchange. Exchange appeared to occur laterally as well, in a manner consistent with the tidal-pumping mechanism described by Stommel and Farmer [1952]. Tidal cycle variations in shear and stratification were characterized by strong vertical shear and breakdown of stratification during the ebb, and weak vertical shear and build-up of stratification on the flood. Evaluation of multiple tidal-cycles from time-series records of flow and temperature indicated that the vertical variations of the flow and stratification observed during the cross-sectional measurements are a general phenomenon during the summer. Together, these observations suggest that thermal stratification can play an important role in regulating the tidal exchange of low-inflow estuaries.

Distributions and seasonal variations of dissolved carbohydrates in the Jiaozhou Bay, China

NASA Astrophysics Data System (ADS)

Yang, Gui-Peng; Zhang, Yan-Ping; Lu, Xiao-Lan; Ding, Hai-Bing

2010-06-01

Surface seawater samples were collected in the Jiaozhou Bay, a typical semi-closed basin located at the western part of the Shandong Peninsula, China, during four cruises. Concentrations of monosaccharides (MCHO), polysaccharides (PCHO) and total dissolved carbohydrates (TCHO) were measured with the 2,4,6-tripyridyl- s-triazine spectroscopic method. Concentrations of TCHO varied from 10.8 to 276.1 μM C for all samples and the ratios of TCHO to dissolved organic carbon (DOC) ranged from 1.1 to 67.9% with an average of 10.1%. This result indicated that dissolved carbohydrates were an important constituent of DOC in the surface seawater of the Jiaozhou Bay. In all samples, the concentrations of MCHO ranged from 2.9 to 65.9 μM C, comprising 46.1 ± 16.6% of TCHO on average, while PCHO ranged from 0.3 to 210.2 μM C, comprising 53.9 ± 16.6% of TCHO on average. As a major part of dissolved carbohydrates, the concentrations of PCHO were higher than those of MCHO. MCHO and PCHO accumulated in January and July, with minimum average concentration in April. The seasonal variation in the ratios of TCHO to DOC was related to water temperature, with high values in January and low values in July and October. The concentrations of dissolved carbohydrates displayed a decreasing trend from the coastal to the central areas. Negative correlations between concentrations of TCHO and salinity in July suggested that riverine input around the Jiaozhou Bay had an important effect on the concentrations of dissolved carbohydrates in surface seawater. The pattern of distributions of MCHO and PCHO reported in this study added to the global picture of dissolved carbohydrates distribution.

Long-term variations of the riverine input of potentially toxic dissolved elements and the impacts on their distribution in Jiaozhou Bay, China.

PubMed

Wang, Changyou; Guo, Jinqiang; Liang, Shengkang; Wang, Yunfei; Yang, Yanqun; Wang, Xiulin

2018-03-01

The concentrations of the potentially toxic dissolved elements (PTEs) As, Hg, Cr, Pb, Cd, and Cu in the main rivers into Jiaozhou Bay (JZB) during 1981-2006 were measured, and the impact of the fluvial PTE fluxes on their distributions in the bay was investigated. The overall average concentration in the rivers into JZB ranged from 8.8 to 39.6 μg L -1 for As, 10.1 to 632.6 ng L -1 for Hg, 4.1 to 3003.6 μg L -1 for Cr, 8.5 to 141.9 μg L -1 for Pb, 1.1 to 34.2 μg L -1 for Cd, and 13.2 to 1042.8 μg L -1 for Cu. The interannual average concentration variations of the PTEs in these rivers were enormous, with maximum differences of 41-21,680 times, while their relative seasonal changes were far smaller with maximum differences of 3-12 times. The total annual fluvial fluxes for As, Hg, and Cr into JZB exhibited the inverse "U" pattern, while those for Pb and Cd showed the "N" pattern. As a whole, the total annual Cu flux presented a growing tendency from 1998 to 2006. In general, the changing trends of the PTE concentrations in JZB were similar to those of their annual fluxes from the rivers, indicating a great impact of their fluvial fluxes on their distributions in JZB. The annual concentration of Cd in the bay almost remained constant and differed from the fluvial flux of Cd. The diversified pattern of the environmental Kuznets curve (EKC) represented China's approach to industrialization as "improving while developing."

Seasonal and inter-annual variation in occurrence and biomass of rooted macrophytes and drift algae in shallow bays

NASA Astrophysics Data System (ADS)

Berglund, J.; Mattila, J.; Rönnberg, O.; Heikkilä, J.; Bonsdorff, E.

2003-04-01

Submerged rooted macrophytes and drift algae were studied in shallow (0-1 m) brackish soft-bottom bays in the Åland Islands, N Baltic Sea, in 1997-2000. The study was performed by aerial photography and ground-truth sampling and the compatibility of the methods was evaluated. The study provided quantitative results on seasonal and inter-annual variation in growth, distribution and biomass of submerged macrophytes and drift algae. On an average, 18 submerged macrophyte species occurred in the studied bays. The most common species, by weight and occurrence, were Chara aspera, Cladophora glomerata, Pilayella littoralis and Potamogeton pectinatus. Filamentous green algae constituted 45-70% of the biomass, charophytes 25-40% and vascular plants 3-18%. A seasonal pattern with a peak in biomass in July-August was found and the mean biomass was negatively correlated with exposure. There were statistically significant differences in coverage among years, and among levels of exposure. The coverage was highest when exposure was low. Both sheltered and exposed bays were influenced by drift algae (30 and 60% occurrence in July-August) and there was a positive correlation between exposure and occurrence of algal accumulations. At exposed sites, most of the algae had drifted in from other areas, while at sheltered ones they were mainly of local origin. Data obtained by aerial photography and ground-truth sampling showed a high concordance, but aerial photography gave a 9% higher estimate than the ground-truth samples. The results can be applied in planning of monitoring and management strategies for shallow soft-bottom areas under potential threat of drift algae.

High Frequency Radar Observations of Tidal Current Variability in the Lower Chesapeake Bay

NASA Astrophysics Data System (ADS)

Updyke, T. G.; Dusek, G.; Atkinson, L. P.

2016-02-01

Analysis of eight years of high frequency radar surface current observations in the lower Chesapeake Bay is presented with a focus on the variability of the tidal component of the surface circulation which accounts for a majority of the variance of the surface flow (typically 70-80% for the middle of the radar footprint). Variations in amplitude and phase of the major tidal constituents are examined in the context of water level, wind and river discharge data. Comparisons are made with harmonic analysis results from long-term records of current data measured by three current profilers operated by NOAA as part of the Chesapeake Bay Physical Oceanographic Real-Time System (PORTS). Preliminary results indicate that there is significant spatial variability in the M2 amplitude over the HF radar grid as well as temporal variability when harmonic analysis is performed using bi-monthly time segments over the course of the record.

Modeling and predicting intertidal variations of the salinity field in the Bay/Delta

USGS Publications Warehouse

Knowles, Noah; Uncles, Reginald J.

1995-01-01

One approach to simulating daily to monthly variability in the bay is the development of intertidal model using tidally-averaged equations and a time step on the order of the day.  An intertidal numerical model of the bay's physics, capable of portraying seasonal and inter-annual variability, would have several uses.  Observations are limited in time and space, so simulation could help fill the gaps.  Also, the ability to simulate multi-year episodes (eg, an extended drought) could provide insight into the response of the ecosystem to such events.  Finally, such a model could be used in a forecast mode wherein predicted delta flow is used as model input, and predicted salinity distribution is output with estimates days and months in advance.  This note briefly introduces such a tidally-averaged model (Uncles and Peterson, in press) and a corresponding predictive scheme for baywide forecasting.

Mechanisms of sediment flux between shallows and marshes

USGS Publications Warehouse

Lacy, Jessica R.; Schile, L.M.; Callaway, J.C.; Ferner, M.C.

2015-01-01

We conducted a field study to investigate temporal variation and forcing mechanisms of sediment flux between a salt marsh and adjacent shallows in northern San Francisco Bay. Suspended-sediment concentration (SSC), tidal currents, and wave properties were measured over the marsh, in marsh creeks, and in bay shallows. Cumulative sediment flux in the marsh creeks was bayward during the study, and was dominated by large bayward flux during the largest tides of the year. This result was unexpected because extreme high tides with long inundation periods are commonly assumed to supply sediment to marshes, and long-term accretion estimates show that the marsh in the study site is depositional. A water mass-balance shows that some landward transport bypassed the creeks, most likely across the marsh-bay interface. An estimate of transport by this pathway based on observed SSC and inferred volume indicates that it was likely much less than the observed export.

Variation in the carbon cycle of the Sevastopol Bay (Black Sea)

NASA Astrophysics Data System (ADS)

Orekhova, N. A.; Konovalov, S. K.

2018-01-01

Continuous increase in CO2 inventory in the ocean results in dramatic changes in marine biogeochemistry, e.g. acidification. That is why temporal and spatial variabilities in atmospheric pCO2 and dissolved inorganic carbon, including CO2, pH and alkalinity in water, as well as organic and inorganic carbon in bottom sediments have to be studied together making possible to resolve the key features of the carbon cycle transformation. A 30% increase of pCO2 in the Sevastopol Bay for 2008 - 2016 evidences changes in the DIC components ratios and a significant decrease in the ability to absorb atmospheric CO2 by surface waters. High organic carbon content in the bottom sediments and predominance of organic carbon production in the biological pump at inner parts of the bay reveal ongoing transformation of the carbon cycle. This has negative consequences for recreation, social and economic potentials of the Sevastopol region.

[Fish larvae association in a Mexican Caribbean bay].

PubMed

Quintal-Lizama, C; Vásquez-Yeomans, L

2001-06-01

Interannual ichthyoplankton variation, was analyzed in Bahía de la Ascensión, Mexico, during December of four consecutive years (1994-1997). A total of 32 families, 35 genera and 21 species of fish larvae were identified. The most abundant fish larvae were the Gobiidae followed by the Callionymidae, Clupeidae and Tetraodontidae. Larval diversity was low when compared with other periods ("dry" and "rainy"). Three spatial associations (internal, medium and external) were found in December 1994 and 1995. In 1996-1997, stations of the inner and outer parts of the bay were mixed. The dominant families characterized most of the faunal associations. Egg density was highest in the external zone of the bay, whereas larvae were most abundant in the inner area. Major factors affecting the fish larval assemblages during December (1994-1997) in Bahía de la Ascensión seem to be related to the nursery areas location and to the tropical fishes reproductive period.

Selenium and stable isotopes of carbon and nitrogen in the benthic clam Corbula amurensis from Northern San Francisco Bay, California: May 1995-February 2010

USGS Publications Warehouse

Kleckner, Amy E.; Stewart, A. Robin; Luoma, Samuel N.

2010-01-01

The clam-based food webs of San Francisco Bay, California efficiently bioaccumlate selenium and thus provide pathways for exposure to predators important to the estuary. This study documents changes in monthly selenium concentrations for the clam Corbula amurensis, a keystone species of the estuary, at five locations in northern San Francisco Bay from 1995 through 2010. Samples were collected from designated U.S. Geological Survey stations and prepared and analyzed by U.S. Geological Survey methods. Stable isotopes of carbon and nitrogen in soft tissues of clams also were measured as an indicator of sources of selenium for the clams. These monitoring data indicate that clam selenium concentrations ranged from a low of 2 to a high of 22 micrograms per gram dry weight with strong spatial and seasonal variation over the period of study.

Core Perylene Diimide Designs via Direct Bay- and ortho-(Poly)trifluoromethylation: Synthesis, Isolation, X-Ray Structures, Optical and Electronic Properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clikeman, Tyler T.; Bukovsky, Eric V.; Wang, Xue-Bin

2015-09-22

We developed an efficient solvent- and catalyst-free direct polytrifluoromethylation of solid perylene-3,4,9,10-tetracarboxylic dianhydride that produced a new family of (poly)perfluoroalkyl bay- and ortho-substituted PDIs with two different imide substituents. Direct hydrogen substitution with CN group led to the synthesis of a cyanated perfluoroalkyl PDI derivative for the first time. Absorption, steady-state and time-resolved emission, X-ray diffraction, electrochemical, and gas-phase electron affinity data allowed for systematic studies of substitution effects at bay, ortho, and imide positions in the new PDIs. Solid-state packing showed remarkable variations in the intermolecular interactions that are important for charge transport and photophysical properties. Moreover, analysis ofmore » the electrochemical data for 143 electron poor PDIs, including newly reported compounds, revealed some general trends and peculiar effects from substituting electron-withdrawing groups at all three positions.« less

Core Perylene Diimide Designs via Direct Bay and Ortho (Poly)trifluoromethylation: Synthesis, Isolation, X-ray Structures, Optical and Electronic Properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clikeman, Tyler T.; Bukovsky, Eric V.; Wang, Xue B.

2015-09-22

We developed an efficient solvent- and catalyst-free direct polytrifluoromethylation of solid perylene-3,4,9,10-tetracarboxylic dianhydride that produced a new family of (poly)perfluoroalkyl bay and ortho substituted PDIs with two different imide substituents. Direct hydrogen substitution with CN group led to the synthesis of a cyanated perfluoroalkyl PDI derivative for the first time. Absorption, steady-state and time-resolved emission, X-ray diffraction, electrochemical, and gas-phase electron affinity data allowed for systematic studies of substitution effects at bay, ortho, and imide positions in the new PDIs. Solid-state packing showed remarkable variations in the intermolecular interactions that are important for charge transport and photophysical properties. Analysis ofmore » the electrochemical data for 143 electron poor PDIs, including newly reported compounds, revealed some general trends and peculiar effects of electron withdrawing group substitution at all three positions.« less

Hydrography and bottom boundary layer dynamics: Influence on inner shelf sediment mobility, Long Bay, North Carolina

USGS Publications Warehouse

Davis, L.A.; Leonard, L.A.; Snedden, G.A.

2008-01-01

This study examined the hydrography and bottom boundary-layer dynamics of two typical storm events affecting coastal North Carolina (NC); a hurricane and the passages of two small consecutive extratropical storms during November 2005. Two upward-looking 1200-kHz Acoustic Doppler Current Profilers (ADCP) were deployed on the inner shelf in northern Long Bay, NC at water depths of less than 15 m. Both instruments profiled the overlying water column in 0.35 in bins beginning at a height of 1.35 in above the bottom (mab). Simultaneous measurements of wind speed and direction, wave and current parameters, and acoustic backscatter were coupled with output from a bottom boundary layer (bbl) model to describe the hydrography and boundary layer conditions during each event. The bbl model also was used to quantify sediment transport in the boundary layer during each storm. Both study sites exhibited similar temporal variations in wave and current magnitude, however, wave heights during the November event were higher than waves associated with the hurricane. Near-bottom mean and subtidal currents, however, were of greater magnitude during the hurricane. Peak depth-integrated suspended sediment transport during the November event exceeded transport associated with the hurricane by 25-70%. Substantial spatial variations in sediment transport existed throughout both events. During both events, along-shelf sediment transport exceeded across-shelf transport and was related to the magnitude and direction of subtidal currents. Given the variations in sediment type across the bay, complex shoreline configuration, and local bathymetry, the sediment transport rates reported here are very site specific. However, the general hydrography associated with the two storms is representative of conditions across northern Long Bay. Since the beaches in the study area undergo frequent renourishment to counter the effects of beach erosion, the results of this study also are relevant to coastal management decision-making. Specifically, these issues include 1) identification of municipalities that should share the cost for renourishment given the likelihood for significant along-shelf sand movement and 2) appropriate timing of sand placement with respect to local climatology and sea-turtle nesting restrictions.

Underwater Optics in Sub-Antarctic and Antarctic Coastal Ecosystems

PubMed Central

Huovinen, Pirjo; Ramírez, Jaime; Gómez, Iván

2016-01-01

Understanding underwater optics in natural waters is essential in evaluating aquatic primary production and risk of UV exposure in aquatic habitats. Changing environmental conditions related with global climate change, which imply potential contrasting changes in underwater light climate further emphasize the need to gain insights into patterns related with underwater optics for more accurate future predictions. The present study evaluated penetration of solar radiation in six sub-Antarctic estuaries and fjords in Chilean North Patagonian region (39–44°S) and in an Antarctic bay (62°S). Based on vertical diffuse attenuation coefficients (Kd), derived from measurements with a submersible multichannel radiometer, average summer UV penetration depth (z1%) in these water bodies ranged 2–11 m for UV-B (313 nm), 4–27 m for UV-A (395 nm), and 7–30 m for PAR (euphotic zone). UV attenuation was strongest in the shallow Quempillén estuary, while Fildes Bay (Antarctica) exhibited the highest transparency. Optically non-homogeneous water layers and seasonal variation in transparency (lower in winter) characterized Comau Fjord and Puyuhuapi Channel. In general, multivariate analysis based on Kd values of UV and PAR wavelengths discriminated strongly Quempillén estuary and Puyuhuapi Channel from other study sites. Spatial (horizontal) variation within the estuary of Valdivia river reflected stronger attenuation in zones receiving river impact, while within Fildes Bay a lower spatial variation in water transparency could in general be related to closeness of glaciers, likely due to increased turbidity through ice-driven processes. Higher transparency and deeper UV-B penetration in proportion to UV-A/visible wavelengths observed in Fildes Bay suggests a higher risk for Antarctic ecosystems reflected by e.g. altered UV-B damage vs. photorepair under UV-A/PAR. Considering that damage repair processes often slow down under cool temperatures, adverse UV impact could be further exacerbated by cold temperatures in this location, together with episodes of ozone depletion. Overall, the results emphasize the marked spatial (horizontal and vertical) and temporal heterogeneity of optical characteristics, and challenges that these imply for estimations of underwater optics. PMID:27144454

Probabilistic Multi-Person Tracking Using Dynamic Bayes Networks

NASA Astrophysics Data System (ADS)

Klinger, T.; Rottensteiner, F.; Heipke, C.

2015-08-01

Tracking-by-detection is a widely used practice in recent tracking systems. These usually rely on independent single frame detections that are handled as observations in a recursive estimation framework. If these observations are imprecise the generated trajectory is prone to be updated towards a wrong position. In contrary to existing methods our novel approach uses a Dynamic Bayes Network in which the state vector of a recursive Bayes filter, as well as the location of the tracked object in the image are modelled as unknowns. These unknowns are estimated in a probabilistic framework taking into account a dynamic model, and a state-of-the-art pedestrian detector and classifier. The classifier is based on the Random Forest-algorithm and is capable of being trained incrementally so that new training samples can be incorporated at runtime. This allows the classifier to adapt to the changing appearance of a target and to unlearn outdated features. The approach is evaluated on a publicly available benchmark. The results confirm that our approach is well suited for tracking pedestrians over long distances while at the same time achieving comparatively good geometric accuracy.

The Analysis Performance Method Naive Bayes Andssvm Determine Pattern Groups of Disease

NASA Astrophysics Data System (ADS)

Sitanggang, Rianto; Tulus; Situmorang, Zakarias

2017-12-01

Information is a very important element and into the daily needs of the moment, to get a precise and accurate information is not easy, this research can help decision makers and make a comparison. Researchers perform data mining techniques to analyze the performance of methods and algorithms naïve Bayes methods Smooth Support Vector Machine (ssvm) in the grouping of the disease.The pattern of disease that is often suffered by people in the group can be in the detection area of the collection of information contained in the medical record. Medical records have infromasi disease by patients in coded according to standard WHO. Processing of medical record data to find patterns of this group of diseases that often occur in this community take the attribute address, sex, type of disease, and age. Determining the next analysis is grouping of four ersebut attribute. From the results of research conducted on the dataset fever diabete mellitus, naïve Bayes method produces an average value of 99% and an accuracy and SSVM method produces an average value of 93% accuracy

Fast magnetic resonance imaging based on high degree total variation

NASA Astrophysics Data System (ADS)

Wang, Sujie; Lu, Liangliang; Zheng, Junbao; Jiang, Mingfeng

2018-04-01

In order to eliminating the artifacts and "staircase effect" of total variation in Compressive Sensing MRI, high degree total variation model is proposed for dynamic MRI reconstruction. the high degree total variation regularization term is used as a constraint to reconstruct the magnetic resonance image, and the iterative weighted MM algorithm is proposed to solve the convex optimization problem of the reconstructed MR image model, In addtion, one set of cardiac magnetic resonance data is used to verify the proposed algorithm for MRI. The results show that the high degree total variation method has a better reconstruction effect than the total variation and the total generalized variation, which can obtain higher reconstruction SNR and better structural similarity.

Multiscale 3D Shape Analysis using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2013-01-01

Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data. PMID:16685992

Multiscale 3D shape analysis using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen R

2005-01-01

Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data.

The Flash ADC system and PMT waveform reconstruction for the Daya Bay experiment

NASA Astrophysics Data System (ADS)

Huang, Yongbo; Chang, Jinfan; Cheng, Yaping; Chen, Zhang; Hu, Jun; Ji, Xiaolu; Li, Fei; Li, Jin; Li, Qiuju; Qian, Xin; Jetter, Soeren; Wang, Wei; Wang, Zheng; Xu, Yu; Yu, Zeyuan

2018-07-01

To better understand the energy response of the Antineutrino Detector (AD), the Daya Bay Reactor Neutrino Experiment installed a full Flash ADC readout system on one AD that allowed for simultaneous data taking with the current readout system. This paper presents the design, data acquisition, and simulation of the Flash ADC system, and focuses on the PMT waveform reconstruction algorithms. For liquid scintillator calorimetry, the most critical requirement to waveform reconstruction is linearity. Several common reconstruction methods were tested but the linearity performance was not satisfactory. A new method based on the deconvolution technique was developed with 1% residual non-linearity, which fulfills the requirement. The performance was validated with both data and Monte Carlo (MC) simulations, and 1% consistency between them has been achieved.

Predicting flight delay based on multiple linear regression

NASA Astrophysics Data System (ADS)

Ding, Yi

2017-08-01

Delay of flight has been regarded as one of the toughest difficulties in aviation control. How to establish an effective model to handle the delay prediction problem is a significant work. To solve the problem that the flight delay is difficult to predict, this study proposes a method to model the arriving flights and a multiple linear regression algorithm to predict delay, comparing with Naive-Bayes and C4.5 approach. Experiments based on a realistic dataset of domestic airports show that the accuracy of the proposed model approximates 80%, which is further improved than the Naive-Bayes and C4.5 approach approaches. The result testing shows that this method is convenient for calculation, and also can predict the flight delays effectively. It can provide decision basis for airport authorities.

A new approach to measure visual field progression in glaucoma patients using variational bayes linear regression.

PubMed

Murata, Hiroshi; Araie, Makoto; Asaoka, Ryo

2014-11-20

We generated a variational Bayes model to predict visual field (VF) progression in glaucoma patients. This retrospective study included VF series from 911 eyes of 547 glaucoma patients as test data, and VF series from 5049 eyes of 2858 glaucoma patients as training data. Using training data, variational Bayes linear regression (VBLR) was created to predict VF progression. The performance of VBLR was compared against ordinary least-squares linear regression (OLSLR) by predicting VFs in the test dataset. The total deviation (TD) values of test patients' 11th VFs were predicted using TD values from their second to 10th VFs (VF2-10), the root mean squared error (RMSE) associated with each approach then was calculated. Similarly, mean TD (mTD) of test patients' 11th VFs was predicted using VBLR and OLSLR, and the absolute prediction errors compared. The RMSE resulting from VBLR averaged 3.9 ± 2.1 (SD) and 4.9 ± 2.6 dB for prediction based on the second to 10th VFs (VF2-10) and the second to fourth VFs (VF2-4), respectively. The RMSE resulting from OLSLR was 4.1 ± 2.0 (VF2-10) and 19.9 ± 12.0 (VF2-4) dB. The absolute prediction error (SD) for mTD using VBLR was 1.2 ± 1.3 (VF2-10) and 1.9 ± 2.0 (VF2-4) dB, while the prediction error resulting from OLSLR was 1.2 ± 1.3 (VF2-10) and 6.2 ± 6.6 (VF2-4) dB. The VBLR more accurately predicts future VF progression in glaucoma patients compared to conventional OLSLR, especially in short VF series. © ARVO.

Predicting seasonal variations in coastal seabird habitats in the English Channel and the Bay of Biscay

NASA Astrophysics Data System (ADS)

Virgili, A.; Lambert, C.; Pettex, E.; Dorémus, G.; Van Canneyt, O.; Ridoux, V.

2017-07-01

Seabirds, like all animals, have to live in suitable habitats to fulfil their energetic needs for both somatic and reproductive growth and maintenance. Apart from migration trips, all coastal seabirds are linked to the coast, because they need to return daily to land for resting or breeding. Their use of marine habitats strongly depends on their biology, but also on environmental conditions, and can be described using habitat models. This study aimed to: (1) identify the processes that mostly influence seabird distributions along the coasts of the English Channel and the Bay of Biscay; (2) determine seasonal variations of these processes, (3) provide prediction maps that describe the species distributions. We collected data of coastal seabird sightings from aerial surveys carried out in the English Channel and the eastern North Atlantic in the winter 2011-2012 and summer 2012. We classified seabirds into morphological groups and described their habitats using physiographic and oceanographic variables in Generalised Additive Models (GAMs). Finally, we produced maps of predicted distributions by season for each group. The distributions of coastal seabirds were essentially determined by the distance to the nearest coast, with a weaker influence of oceanographic variables. The nature of the substrate, sand or rock, combined with the timing of reproduction, also contributed to determine seasonal at-sea distributions for some species. The highest densities were predicted near the coast, particularly in bays and estuaries for strictly coastal species with possible variations depending on the season. From this study, we were able to predict the seasonal distribution of the studied species according to varying environmental parameters that changed over time, allowing us to understand better their behaviour and ecology.

Air-water CO2 Fluxes In Seasonal Hypoxia-influenced Green Bay, Lake Michigan

NASA Astrophysics Data System (ADS)

Lin, P.; Klump, J. V.; Guo, L.

2016-02-01

Increasing anthropogenic nutrient enrichment has led to seasonal hypoxia in Green Bay, the largest freshwater estuary in the Laurentian Great Lakes, but change in carbon dynamics associated with the development of hypoxia remains poorly understood. Variations in alkalinity, abundance of carbon species, and air-water CO2 fluxes were quantified under contrasting hypoxic conditions during summer 2014. Green Bay was characterized with high pH (average 8.62 ± 0.16 in August), high DIC concentrations (2113 - 3213 µmol/kg) and high pCO2 in the water column. pCO2 was mostly >700 µatm in June, resulting in a net CO2 source to the air, while pCO2 was mostly <650 µatm in August when hypoxic conditions occurred in Green Bay. In central Green Bay, pCO2 was the highest during both sampling months, accompanying by low dissolved oxygen (DO) and lower pH in the water column. In August, pCO2 was inversely correlated with DOC concentration and increased with DOC/DOP ratio, suggesting a control by organic matter on air-water CO2 dynamics and consumption of DO in Green Bay. Positive CO2 fluxes to the atmosphere during August were only observed in northern bay but a CO2 sink was found in southern Green Bay ( 40% of study area) with high biological production and terrestrial DOM. Daily CO2 flux ranged from 10.9 to 48.5 mmol-C m-2 d-1 in June with an average of 18.29 ± 7.44 mmol-C m-2 d-1, whereas it varied from 1.82 ± 1.18 mmol m-2 d-1 in the north to -2.05 ± 1.89 mmol m-2 d-1 in the south of Green Bay in August. Even though strong biological production reduced the CO2 emission, daily CO2 fluxes from Green Bay to the air were as high as 7.4 × 107 mole-C in June and 4.6 × 106 mole-C in August, suggesting a significant role of high-DIC lakes in global CO2 budget and cycling.

Monitoring of hourly variations in coastal water turbidity using the geostationary ocean color imager (GOCI)

NASA Astrophysics Data System (ADS)

Choi, J.; Ryu, J.

2011-12-01

Temporal variations of suspended sediment concentration (SSC) in coastal water are the key to understanding the pattern of sediment movement within coastal area, in particular, such as in the west coast of the Korean Peninsula which is influenced by semi-diurnal tides. Remote sensing techniques can effectively monitor the distribution and dynamic changes in seawater properties across wide areas. Thus, SSC on the sea surface has been investigated using various types of satellite-based sensors. An advantage of Geostationary Ocean Color Imager (GOCI), the world's first geostationary ocean color observation satellite, over other ocean color satellite images is that it can obtain data every hour during the day and makes it possible to monitor the ocean in real time. In this study, hourly variations in turbidity on the coastal waters were estimated quantitatively using GOCI. Thirty three water samples were obtained on the coastal water surface in southern Gyeonggi Bay, located on the west coast of Korea. Water samples were filtered using 25-mm glass fiber filters (GF/F) for the estimation of SSC. The radiometric characteristics of the surface water, such as the total water-leaving radiance (LwT, W/m2/nm/sr), the sky radiance (Lsky, W/m2/nm/sr) and the downwelling irradiance, were also measured at each sampling location. In situ optical properties of the surface water were converted into remote sensing reflectance (Rrs) and then were used to develop an algorithm to generate SSC images in the study area. GOCI images acquired on the same day as the samples acquisition were used to generate the map of turbidity and to estimate the difference in SSC displayed in each image. The estimation of the time-series variation in SSC in a coastal, shallow-water area affected by tides was successfully achieved using GOCI data that had been acquired at hourly intervals during the daytime.

Radiocarbon dating, chronologic framework, and changes in accumulation rates of holocene estuarine sediments from Chesapeake Bay

USGS Publications Warehouse

Colman, Steven M.; Baucom, P.C.; Bratton, J.F.; Cronin, T. M.; McGeehin, J.P.; Willard, D.; Zimmerman, A.R.; Vogt, P.R.

2002-01-01

Rapidly accumulating Holocene sediments in estuaries commonly are difficult to sample and date. In Chesapeake Bay, we obtained sediment cores as much as 20 m in length and used numerous radiocarbon ages measured by accelarator mass spectrometry methods to provide the first detailed chronologies of Holocene sediment accumulation in the bay. Carbon in these sediments is a complex mixture of materials from a variety of sources. Analyses of different components of the sediments show that total organic carbon ages are largely unreliable, because much of the carbon (including coal) has been transported to the bay from upstream sources and is older than sediments in which it was deposited. Mollusk shells (clams, oysters) and foraminifera appear to give reliable results, although reworking and burrowing are potential problems. Analyses of museum specimens collected alive before atmospheric nuclear testing suggest that the standard reservoir correction for marine samples is appropriate for middle to lower Chesapeake Bay. The biogenic carbonate radiocarbon ages are compatible with 210 Pb and 137 Cs data and pollen stratigraphy from the same sites. Post-settlement changes in sediment transport and accumulation is an important environmental issue in many estuaries, including the Chesapeake. Our data show that large variations in sediment mass accumulation rates occur among sites. At shallow water sites, local factors seem to control changes in accumulation rates with time. Our two relatively deep-water sites in the axial channel of the bay have different long-term average accumulation rates, but the history of sediment accumulation at these sites appears to reflect overall conditions in the bay. Mass accumulation rates at the two deep-water sites rapidly increased by about fourfold coincident with widespread land clearance for agriculture in the Chesapeake watershed.

δ15N as a Potential Paleoenvironmental Proxy for Nitrogen Loading in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Black, H. D.; Andrus, C. F.; Rick, T.; Hines, A.

2013-12-01

Stable isotope analysis of Eastern Oyster (Crassostrea virginica) and other mollusk shells from archaeological sites is a useful means of acquiring paleoenvironmental data. Recently, nitrogen isotopes have been identified as a potential new proxy in these shells. δ15N content in mollusk shells is affected by numerous anthropogenic and natural influences and may be used as an environmental proxy for nitrogen loading conditions. Chesapeake Bay is well known for both historic and modern pollution problems from numerous anthropogenic sources, such as fertilizer runoff, sewage discharge, and densely populated land use and serves as an ideal study location for long-term nitrogen loading processes. Longer records of these processes may be recorded in abundant archaeological remains around the bay, however, little is known about the stability of δ15N and %N in shell material over recent geologic time. In this study, 90 archaeological C. virginica shells were collected by the Smithsonian Institution from the Rhode River Estuary within Chesapeake Bay and range in age from ~150 to 3200 years old. Twenty-two modern C. virginica shells were also collected from nearby beds in the bay. All shell samples were subsampled from the resilifer region of the calcitic shell using a hand-held micro drill and were analyzed using EA-IRMS analysis to determine the potential temporal variability of δ15N and %N as well as creating a baseline for ancient nitrogen conditions in the bay area. Modern POM water samples and C. virginica soft tissues were also analyzed in this study to determine the degree of seasonal variation of δ15N and %N in Chesapeake Bay.

Effects of nutrients and zooplankton on the phytoplankton community structure in Marudu Bay

NASA Astrophysics Data System (ADS)

Tan, Kar Soon; Ransangan, Julian

2017-07-01

Current study was carried out to provide a better understanding on spatial and temporal variations in the phytoplankton community structure in Marudu Bay, an important nursery ground for fishery resources within the Tun Mustapha Marine Park and Coral Triangle Initiative, and their relationship with environmental variables. Samplings were conducted monthly from April 2014 to April 2015 in Marudu Bay, Malaysia. Water samples were collected for nutrients analysis, zooplankton and phytoplankton counting. Moreover, the in situ environmental parameters were also examined. The field study showed a total of forty seven phytoplankton genera, representative of 33 families were identified. The nutrient concentrations in Marudu Bay was low (mesotrophic) throughout the year, where the phytoplankton community was often dominated by Chaetoceros spp. and Bacteriastrum spp. In general, increase in nitrate concentration triggered the bloom of centric diatom, Chaetoceros spp. and Bacteriastrum spp. in Marudu Bay. However, the bloom of these phytoplankton taxa did not occur in the presence of high ammonia concentration. In addition, high abundance of zooplankton also a limiting factor of the phytoplankton blooms particularly at end of southwest monsoon. High silica concentration promoted the growth of pennate diatoms, Proboscia spp. and Thallassionema spp., but the depletion of silica quickly terminated the bloom. Interestingly, our study showed that Chaetoceros spp., tolerated silica depletion condition, but the average cell size of this taxon reduced significantly. In summary, the phytoplankton community structure in mesotrophic environment is more sensitive to the changes in zooplankton abundance, nutrient concentration and its ratio than that in nutrient rich environments. This study also recommends that bivalve farming at industrial scale is not recommended in Marudu Bay because it potentially depletes the primary productivity hence jeopardizing the availability of live food for larvae of many natural fishery resources in the bay.

Spatial and temporal variation in distribution of larval lake whitefish in eastern Lake Ontario: signs of recovery?

USGS Publications Warehouse

McKenna, J.E.; Johnson, J. H.

2009-01-01

The lake whitefish (Coregonus clupeaformis) is one of the native Lake Ontario fishes that declined severely over the past century. Recent evidence of larval lake whitefish production in a historic spawning area (Chaumont Bay) might signal a recovery of this species in New York waters. We surveyed coastal and open water areas to evaluate densities and estimate total abundance of larval lake whitefish in Chaumont Bay. Other historic spawning areas and embayments with appropriate spawning and nursery habitat were also surveyed, but only a few larvae were found outside of Chaumont Bay. Lake whitefish larvae were found in every embayment sampled within Chaumont Bay, with larval densities of nearly 600/1000 m2 in some samples. Greatest abundances occurred in the northern sectors and near the mouth of the bay. Open water densities were generally less than half that of nearshore sites. The total bay-wide estimate for 2005 was approximately 644,000 lake whitefish larvae, but dropped to 230,000–400,000 in 2006 and 2007, respectively. Mean larval growth rates (0.36 mm/day) did not differ by year, but were consistently higher in early May than in late April. Lake whitefish production in Chaumont Bay is encouraging for this species, but the cause and persistence of the decline after 2005 can be determined only by continued monitoring. Other possible bottlenecks of survival may exist at juvenile and adult stages and could significantly affect recruitment dynamics. This species is sensitive to normal climatic fluctuations and increased variability associated with global climatic change could make winter nursery conditions unfavorable for this species.

A computer model of long-term salinity in San Francisco Bay: Sensitivity to mixing and inflows

USGS Publications Warehouse

Uncles, R.J.; Peterson, D.H.

1995-01-01

A two-level model of the residual circulation and tidally-averaged salinity in San Francisco Bay has been developed in order to interpret long-term (days to decades) salinity variability in the Bay. Applications of the model to biogeochemical studies are also envisaged. The model has been used to simulate daily-averaged salinity in the upper and lower levels of a 51-segment discretization of the Bay over the 22-y period 1967–1988. Observed, monthly-averaged surface salinity data and monthly averages of the daily-simulated salinity are in reasonable agreement, both near the Golden Gate and in the upper reaches, close to the delta. Agreement is less satisfactory in the central reaches of North Bay, in the vicinity of Carquinez Strait. Comparison of daily-averaged data at Station 5 (Pittsburg, in the upper North Bay) with modeled data indicates close agreement with a correlation coefficient of 0.97 for the 4110 daily values. The model successfully simulates the marked seasonal variability in salinity as well as the effects of rapidly changing freshwater inflows. Salinity variability is driven primarily by freshwater inflow. The sensitivity of the modeled salinity to variations in the longitudinal mixing coefficients is investigated. The modeled salinity is relatively insensitive to the calibration factor for vertical mixing and relatively sensitive to the calibration factor for longitudinal mixing. The optimum value of the longitudinal calibration factor is 1.1, compared with the physically-based value of 1.0. Linear time-series analysis indicates that the observed and dynamically-modeled salinity-inflow responses are in good agreement in the lower reaches of the Bay.

Compressed sensing with gradient total variation for low-dose CBCT reconstruction

NASA Astrophysics Data System (ADS)

Seo, Chang-Woo; Cha, Bo Kyung; Jeon, Seongchae; Huh, Young; Park, Justin C.; Lee, Byeonghun; Baek, Junghee; Kim, Eunyoung

2015-06-01

This paper describes the improvement of convergence speed with gradient total variation (GTV) in compressed sensing (CS) for low-dose cone-beam computed tomography (CBCT) reconstruction. We derive a fast algorithm for the constrained total variation (TV)-based a minimum number of noisy projections. To achieve this task we combine the GTV with a TV-norm regularization term to promote an accelerated sparsity in the X-ray attenuation characteristics of the human body. The GTV is derived from a TV and enforces more efficient computationally and faster in convergence until a desired solution is achieved. The numerical algorithm is simple and derives relatively fast convergence. We apply a gradient projection algorithm that seeks a solution iteratively in the direction of the projected gradient while enforcing a non-negatively of the found solution. In comparison with the Feldkamp, Davis, and Kress (FDK) and conventional TV algorithms, the proposed GTV algorithm showed convergence in ≤18 iterations, whereas the original TV algorithm needs at least 34 iterations in reducing 50% of the projections compared with the FDK algorithm in order to reconstruct the chest phantom images. Future investigation includes improving imaging quality, particularly regarding X-ray cone-beam scatter, and motion artifacts of CBCT reconstruction.

Mining and Querying Multimedia Data

DTIC Science & Technology

2011-09-29

able to capture more subtle spatial variations such as repetitiveness. Local feature descriptors such as SIFT [74] and SURF [12] have also been widely...empirically set to s = 90%, r = 50%, K = 20, where small variations lead to little perturbation of the output. The pseudo-code of the algorithm is...by constructing a three-layer graph based on clustering outputs, and executing a slight variation of random walk with restart algorithm. It provided

Feeding ecology of lake whitefish larvae in eastern Lake Ontario

USGS Publications Warehouse

Johnson, James H.; McKenna, James E.; Chalupnicki, Marc A.; Wallbridge, Tim; Chiavelli, Rich

2009-01-01

We examined the feeding ecology of larval lake whitefish (Coregonus clupeaformis) in Chaumont Bay, Lake Ontario, during April and May 2004-2006. Larvae were collected with towed ichthyoplankton nets offshore and with larval seines along the shoreline. Larval feeding periodicity was examined from collections made at 4-h intervals over one 24-h period in 2005. Inter-annual variation in diet composition (% dry weight) was low, as was spatial variation among collection sites within the bay. Copepods (81.4%), primarily cyclopoids (59.1%), were the primary prey of larvae over the 3-year period. Cladocerans (8.1%; mainly daphnids, 6.7%) and chironomids (7.3%) were the other major prey consumed. Larvae did not exhibit a preference for any specific prey taxa. Food consumption of lake whitefish larvae was significantly lower at night (i.e., 2400 and 0400 h). Substantial variation in diet composition occurred over the 24-h diel study. For the 24-h period, copepods were the major prey consumed (50.4%) and their contribution in the diet ranged from 29.3% (0400 h) to 85.9% (1200 h). Chironomids made up 33.4% of the diel diet, ranging from 8.0% (0800 h) to 69.9% (0400 h). Diel variation in the diet composition of lake whitefish larvae may require samples taken at several intervals over a 24-h period to gain adequate representation of their feeding ecology.

Hyperspectral Biofilm Classification Analysis for Carrying Capacity of Migratory Birds in the South Bay Salt Ponds

NASA Technical Reports Server (NTRS)

Hsu, Wei-Chen; Kuss, Amber Jean; Ketron, Tyler; Nguyen, Andrew; Remar, Alex Covello; Newcomer, Michelle; Fleming, Erich; Debout, Leslie; Debout, Brad; Detweiler, Angela;

A two-dimensional hydrodynamic model of a tidal estuary

USGS Publications Warehouse

Walters, Roy A.; Cheng, Ralph T.

1979-01-01

A finite element model is described which is used in the computation of tidal currents in an estuary. This numerical model is patterned after an existing algorithm and has been carefully tested in rectangular and curve-sided channels with constant and variable depth. One of the common uncertainties in this class of two-dimensional hydrodynamic models is the treatment of the lateral boundary conditions. Special attention is paid specifically to addressing this problem. To maintain continuity within the domain of interest, ‘smooth’ curve-sided elements must be used at all shoreline boundaries. The present model uses triangular, isoparametric elements with quadratic basis functions for the two velocity components and a linear basis function for water surface elevation. An implicit time integration is used and the model is unconditionally stable. The resultant governing equations are nonlinear owing to the advective and the bottom friction terms and are solved iteratively at each time step by the Newton-Raphson method. Model test runs have been made in the southern portion of San Francisco Bay, California (South Bay) as well as in the Bay west of Carquinez Strait. Owing to the complex bathymetry, the hydrodynamic characteristics of the Bay system are dictated by the generally shallow basins which contain deep, relict river channels. Great care must be exercised to ensure that the conservation equations remain locally as well as globally accurate. Simulations have been made over several representative tidal cycles using this finite element model, and the results compare favourably with existing data. In particular, the standing wave in South Bay and the progressive wave in the northern reach are well represented.

Remote sensing of particle backscattering in Chesapeake Bay: a 6-year SeaWiFS retrospective view

USGS Publications Warehouse

Zawada, D.G.; Hu, C.; Clayton, T.; Chen, Z.; Brock, J.C.; Muller-Karger, F. E.

2007-01-01

Traditional field techniques to monitor water quality in large estuaries, such as boat-based surveys and autonomous moored sensors, generally provide limited spatial coverage. Satellite imagery potentially can be used to address both of these limitations. Here, we show that satellite-based observations are useful for inferring total-suspended-solids (TSS) concentrations in estuarine areas. A spectra-matching optimization algorithm was used to estimate the particle backscattering coefficient at 400 nm, bbp(400), in Chesapeake Bay from Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) satellite imagery. These estimated values of bbp(400) were compared to in situ measurements of TSS for the study period of September 1997–December 2003. Contemporaneous SeaWiFS bbp(400) values and TSS concentrations were positively correlated (N = 340, r2 = 0.4, P bp(400) values served as a reasonable first-order approximation for synoptically mapping TSS. Overall, large-scale patterns of SeaWiFS bbp(400) appeared to be consistent with expectations based on field observations and historical reports of TSS. Monthly averages indicated that SeaWiFS bbp(400) was typically largest in winter (>0.049 m−1, November–February) and smallest in summer (−1, June–August), regardless of the amount of riverine discharge to the bay. The study period also included Hurricanes Floyd and Isabel, which caused large-scale turbidity events and changes in the water quality of the bay. These results demonstrate that this technique can provide frequent synoptic assessments of suspended solids concentrations in Chesapeake Bay and other coastal regions.

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

The coupling of bay hydrodynamics with sediment supply and micro-tidal wetland stability under high rates of relative sea level rise

NASA Astrophysics Data System (ADS)

Wang, J.; Xu, K.; Restreppo, G. A.; Bentley, S. J.; Meng, X.; Zhang, X.

2017-12-01

Due to global sea level rise, local subsidence and sediment deficit, the Mississippi River (MR) deltaic plain has lost a total of 25% of coastal Louisiana's wetlands during the last century, leading to huge losses of ecological services, economic and social crises. Ecosystem-based restoration strategies which rely on coastal system processes and feedbacks are urgently needed. Understanding linkages between estuarine and coastal systems and the adjacent marshlands will help the designing strategies. To investigate bay hydrodynamics and its impacts on the adjacent micro-tidal wetland stability, hourly measurements of wave, tidal current, and benthic sediment concentration in summer, winter, and spring of 2015-2016 were conducted in Fourleague Bay, Louisiana, USA. The bay-marsh system has been stable for almost 80 years under high relative sea level rising rate, which is 11 km southeast of the Atchafalaya River mouth, with a water depth of 1-3 m. High-temporal resolution data indicate that benthic sediment resuspension is mainly caused by wind-driven waves with a dominant periodicity of 4.8 d. The sediment flux reaches 28 g·m-1·s-1 per unit depth in cm during the events. Net sediment transport is northwestward in summer, and southeastward in winter and spring. Sediment flux available for surrounding marsh varies from 0-500 g·m-1·s-1. An optimal inundation depth of 50 cm is estimated by the equilibrium wetland elevation change model under high relative sea level rising rate of 1.57 cm·yr-1. Seasonal variations of river discharge and wind direction (particularly speeds >3 m·s-1) greatly impact potential sediment contribution from bay to the surrounding wetlands. Three sediment transport regimes are concluded based on the seasonal variations of river discharge and wind direction: the `bypassing' season, the resuspension-accumulation season, and the combined `bypassing' and resuspension-accumulation season. The bay hydrodynamic processes and their impacts on the stability of surrounding wetlands fill in our knowledge gaps on how the micro tidal estuarine-marsh system responds to the fast relative sea level rise, and provide valuable information for future ecological restoration plans in the micro tidal deltas like the MR delta.

Variation of Strom Surge Propagation in a Shallow Estuary with Sea Level Rise

NASA Astrophysics Data System (ADS)

Herrington, T. O., Jr.; Blumberg, A. F.

2014-12-01

Hurricane Sandy made landfall along the New Jersey coast at 8pm EDT on October 29th, 2012. At landfall wind gusts of between 129 and 145 km/hr were recorded in New York and New Jersey. The large wind field associated with the storm generated an extreme storm surge north of the eye at landfall resulting in high-velocity overland storm surge along the northern barrier Islands of the Barnegat Bay followed 7 hours later by a rapid rise in water level along the bayside of the barrier islands. A high-resolution, hydrodynamic model for the Barnegat Bay estuary; including its vast intertidal areas, has been developed and validated to simulate the observed Sandy storm surge. The Barnegat Bay Inundation Model (BBIMS) has a constant 100m resolution and is nested within the three dimensional Stevens NYHOPS ocean circulation model at its offshore open boundary. Wetting and drying of land features in the model's external time step is as low as 0.1 sec in its 2D barotropic mode. This mode provides for the dynamic prediction of depth integrated flood elevations and velocities across land features during inundation events. The BBIMS was calibrated using the NYHOPS hindcast of Hurricane Sandy. The hindcast utilized Sandy over ocean wind field and atmospheric pressure data, offshore wave and tidal boundary forcing, atmospheric heat fluxes, interior stream flow data and was validated against observed water levels and measured high water marks. A comparison against 6 water level time series measured by USGS tide gauges located in the Barnegat Bay verified that the model is able to capture the spatial and temporal variation of water levels in the Bay observed during Hurricane Sandy. A comparison against the verified high water marks found that the model is capable of hincasting overland water elevation to within 0.63ft (one standard deviation) at 71% of the total water marks measured. The modeling results show that strong northerly winds along the axis of the estuary prior to landfall suppressed the storm surge in the northern portion of the Bay. A rapid shift in wind direction to southerly winds after landfall allowed the surge to propagate north up the estuary as a shallow water wave (Figure 1). The effect of future sea levels on surge propagation in the estuary is investigated through increases in model mean sea level.

An Empirical Bayes Estimate of Multinomial Probabilities.

DTIC Science & Technology

1982-02-01

multinomial probabilities has been considered from a decision theoretic point of view by Steinhaus (1957), Trybula (1958) and Rutkowska (1977). In a recent...variate Rypergeometric and Multinomial Distributions," Zastosowania Matematyki, 16, 9-21. Steinhaus , H. (1957), "The Problem of Estimation." Annals of

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

NASA Technical Reports Server (NTRS)

Palacios, Sherry L.; Schafer, Chris; Broughton, Jennifer; Guild, Liane S.; Kudela, Raphael M.

2013-01-01

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in-land water bodies. Results presented are from the 10 April 2013 overflight of the Monterey Bay region and focus primarily on the first objective - sensitivity to atmospheric correction. On-going and future work will continue to evaluate if PHYDOTax can be applied to historical (SeaWiFS and MERIS), existing (MODIS, VIIRS, and HICO), and future (PACE, GEO-CAPE, and HyspIRI) satellite sensors. Demonstration of cross-platform continuity may aid in calibration and validation efforts of these sensors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Torrey, M S

The report is a synoptic review of data collected over the past twenty years on the chemistry of Lake Michigan. Changes in water quality and sediment chemistry, attributable to cultural and natural influences, are considered in relation to interacting processes and factors controlling the distribution and concentration of chemical substances within the Lake. Temperature, light, and mixing processes are among the important natural influences that affect nutrient cycling, dispersal of pollutants, and fate of materials entering the Lake. Characterization of inshore-offshore and longitudinal differences in chemical concentrations and sediment chemistry for the main body of the Lake is supplemented bymore » discussion of specific areas such as Green Bay and Grand Traverse Bay. Residues, specific conductance, dissolved oxygen, major and trace nutrients, and contaminants are described in the following context: biological essentiality and/or toxicity, sources to the Lake, concentrations in the water column and sediments, chemical forms, seasonal variations and variation with depth. A summary of existing water quality standards, statutes, and criteria applicable to Lake Michigan is appended.« less

Composition and temporal stability of turf sediments on inner-shelf coral reefs.

PubMed

Gordon, Sophie E; Goatley, Christopher H R; Bellwood, David R

2016-10-15

Elevated sediment loads within the epilithic algal matrix (EAM) of coral reefs can increase coral mortality and inhibit herbivory. Yet the composition, distribution and temporal variability of EAM sediment loads are poorly known, especially on inshore reefs. This study quantified EAM sediment loads (including organic particulates) and algal length across the reef profile of two bays at Orpheus Island (inner-shelf Great Barrier Reef) over a six month period. We examined the total sediment mass, organic load, carbonate and silicate content, and the particle sizes of EAM sediments. Throughout the study period, all EAM sediment variables exhibited marked variation among reef zones. However, EAM sediment loads and algal length were consistent between bays and over time, despite major seasonal variation in climate including a severe tropical cyclone. This study provides a comprehensive description of EAM sediments on inshore reefs and highlights the exceptional temporal stability of EAM sediments on coral reefs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identifying selectively important amino acid positions associated with alternative habitat environments in fish mitochondrial genomes.

PubMed

Xia, Jun Hong; Li, Hong Lian; Zhang, Yong; Meng, Zi Ning; Lin, Hao Ran

2018-05-01

Fish species inhabitating seawater (SW) or freshwater (FW) habitats have to develop genetic adaptations to alternative environment factors, especially salinity. Functional consequences of the protein variations associated with habitat environments in fish mitochondrial genomes have not yet received much attention. We analyzed 829 complete fish mitochondrial genomes and compared the amino acid differences of 13 mitochondrial protein families between FW and SW fish groups. We identified 47 specificity determining sites (SDS) that associated with FW or SW environments from 12 mitochondrial protein families. Thirty-two (68%) of the SDS sites are hydrophobic, 13 (28%) are neutral, and the remaining sites are acidic or basic. Seven of those SDS from ND1, ND2 and ND5 were scored as probably damaging to the protein structures. Furthermore, phylogenetic tree based Bayes Empirical Bayes analysis also detected 63 positive sites associated with alternative habitat environments across ten mtDNA proteins. These signatures could be important for studying mitochondrial genetic variation relevant to fish physiology and ecology.

Efficient Mean Field Variational Algorithm for Data Assimilation (Invited)

NASA Astrophysics Data System (ADS)

Vrettas, M. D.; Cornford, D.; Opper, M.

2013-12-01

Data assimilation algorithms combine available observations of physical systems with the assumed model dynamics in a systematic manner, to produce better estimates of initial conditions for prediction. Broadly they can be categorized in three main approaches: (a) sequential algorithms, (b) sampling methods and (c) variational algorithms which transform the density estimation problem to an optimization problem. However, given finite computational resources, only a handful of ensemble Kalman filters and 4DVar algorithms have been applied operationally to very high dimensional geophysical applications, such as weather forecasting. In this paper we present a recent extension to our variational Bayesian algorithm which seeks the ';optimal' posterior distribution over the continuous time states, within a family of non-stationary Gaussian processes. Our initial work on variational Bayesian approaches to data assimilation, unlike the well-known 4DVar method which seeks only the most probable solution, computes the best time varying Gaussian process approximation to the posterior smoothing distribution for dynamical systems that can be represented by stochastic differential equations. This approach was based on minimising the Kullback-Leibler divergence, over paths, between the true posterior and our Gaussian process approximation. Whilst the observations were informative enough to keep the posterior smoothing density close to Gaussian the algorithm proved very effective on low dimensional systems (e.g. O(10)D). However for higher dimensional systems, the high computational demands make the algorithm prohibitively expensive. To overcome the difficulties presented in the original framework and make our approach more efficient in higher dimensional systems we have been developing a new mean field version of the algorithm which treats the state variables at any given time as being independent in the posterior approximation, while still accounting for their relationships in the mean solution arising from the original system dynamics. Here we present this new mean field approach, illustrating its performance on a range of benchmark data assimilation problems whose dimensionality varies from O(10) to O(10^3)D. We emphasise that the variational Bayesian approach we adopt, unlike other variational approaches, provides a natural bound on the marginal likelihood of the observations given the model parameters which also allows for inference of (hyper-) parameters such as observational errors, parameters in the dynamical model and model error representation. We also stress that since our approach is intrinsically parallel it can be implemented very efficiently to address very long data assimilation time windows. Moreover, like most traditional variational approaches our Bayesian variational method has the benefit of being posed as an optimisation problem therefore its complexity can be tuned to the available computational resources. We finish with a sketch of possible future directions.

Evaluating acoustic speaker normalization algorithms: evidence from longitudinal child data.

PubMed

Kohn, Mary Elizabeth; Farrington, Charlie

2012-03-01

Speaker vowel formant normalization, a technique that controls for variation introduced by physical differences between speakers, is necessary in variationist studies to compare speakers of different ages, genders, and physiological makeup in order to understand non-physiological variation patterns within populations. Many algorithms have been established to reduce variation introduced into vocalic data from physiological sources. The lack of real-time studies tracking the effectiveness of these normalization algorithms from childhood through adolescence inhibits exploration of child participation in vowel shifts. This analysis compares normalization techniques applied to data collected from ten African American children across five time points. Linear regressions compare the reduction in variation attributable to age and gender for each speaker for the vowels BEET, BAT, BOT, BUT, and BOAR. A normalization technique is successful if it maintains variation attributable to a reference sociolinguistic variable, while reducing variation attributable to age. Results indicate that normalization techniques which rely on both a measure of central tendency and range of the vowel space perform best at reducing variation attributable to age, although some variation attributable to age persists after normalization for some sections of the vowel space. © 2012 Acoustical Society of America

A new Mumford-Shah total variation minimization based model for sparse-view x-ray computed tomography image reconstruction.

PubMed

Chen, Bo; Bian, Zhaoying; Zhou, Xiaohui; Chen, Wensheng; Ma, Jianhua; Liang, Zhengrong

2018-04-12

Total variation (TV) minimization for the sparse-view x-ray computer tomography (CT) reconstruction has been widely explored to reduce radiation dose. However, due to the piecewise constant assumption for the TV model, the reconstructed images often suffer from over-smoothness on the image edges. To mitigate this drawback of TV minimization, we present a Mumford-Shah total variation (MSTV) minimization algorithm in this paper. The presented MSTV model is derived by integrating TV minimization and Mumford-Shah segmentation. Subsequently, a penalized weighted least-squares (PWLS) scheme with MSTV is developed for the sparse-view CT reconstruction. For simplicity, the proposed algorithm is named as 'PWLS-MSTV.' To evaluate the performance of the present PWLS-MSTV algorithm, both qualitative and quantitative studies were conducted by using a digital XCAT phantom and a physical phantom. Experimental results show that the present PWLS-MSTV algorithm has noticeable gains over the existing algorithms in terms of noise reduction, contrast-to-ratio measure and edge-preservation.

Bayesian module identification from multiple noisy networks.

PubMed

Zamani Dadaneh, Siamak; Qian, Xiaoning

2016-12-01

Module identification has been studied extensively in order to gain deeper understanding of complex systems, such as social networks as well as biological networks. Modules are often defined as groups of vertices in these networks that are topologically cohesive with similar interaction patterns with the rest of the vertices. Most of the existing module identification algorithms assume that the given networks are faithfully measured without errors. However, in many real-world applications, for example, when analyzing protein-protein interaction networks from high-throughput profiling techniques, there is significant noise with both false positive and missing links between vertices. In this paper, we propose a new model for more robust module identification by taking advantage of multiple observed networks with significant noise so that signals in multiple networks can be strengthened and help improve the solution quality by combining information from various sources. We adopt a hierarchical Bayesian model to integrate multiple noisy snapshots that capture the underlying modular structure of the networks under study. By introducing a latent root assignment matrix and its relations to instantaneous module assignments in all the observed networks to capture the underlying modular structure and combine information across multiple networks, an efficient variational Bayes algorithm can be derived to accurately and robustly identify the underlying modules from multiple noisy networks. Experiments on synthetic and protein-protein interaction data sets show that our proposed model enhances both the accuracy and resolution in detecting cohesive modules, and it is less vulnerable to noise in the observed data. In addition, it shows higher power in predicting missing edges compared to individual-network methods.

A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York

USGS Publications Warehouse

Bennett, Vanessa C. C.; Mulligan, Ryan P.; Hapke, Cheryl J.

2018-01-01

Hurricane Sandy was a large and intense storm with high winds that caused total water levels from combined tides and storm surge to reach 4.0 m in the Atlantic Ocean and 2.5 m in Great South Bay (GSB), a back-barrier bay between Fire Island and Long Island, New York. In this study the impact of the hurricane winds and waves are examined in order to understand the flow of ocean water into the back-barrier bay and water level variations within the bay. To accomplish this goal, a high resolution hurricane wind field is used to drive the coupled Delft3D-SWAN hydrodynamic and wave models over a series of grids with the finest resolution in GSB. The processes that control water levels in the back-barrier bay are investigated by comparing the results of four cases that include: (i) tides only; (ii) tides, winds and waves with no overwash over Fire Island allowed; (iii) tides, winds, waves and limited overwash at the east end of the island; (iv) tides, winds, waves and extensive overwash along the island. The results indicate that strong local wind-driven storm surge along the bay axis had the largest influence on the total water level fluctuations during the hurricane. However, the simulations allowing for overwash have higher correlation with water level observations in GSB and suggest that island overwash provided a significant contribution of ocean water to eastern GSB during the storm. The computations indicate that overwash of 7500–10,000 m3s−1 was approximately the same as the inflow from the ocean through the major existing inlet. Overall, the model results indicate the complex variability in total water levels driven by tides, ocean storm surge, surge from local winds, and overwash that had a significant impact on the circulation in Great South Bay during Hurricane Sandy.

A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York

NASA Astrophysics Data System (ADS)

Bennett, Vanessa C. C.; Mulligan, Ryan P.; Hapke, Cheryl J.

2018-06-01

Hurricane Sandy was a large and intense storm with high winds that caused total water levels from combined tides and storm surge to reach 4.0 m in the Atlantic Ocean and 2.5 m in Great South Bay (GSB), a back-barrier bay between Fire Island and Long Island, New York. In this study the impact of the hurricane winds and waves are examined in order to understand the flow of ocean water into the back-barrier bay and water level variations within the bay. To accomplish this goal, a high resolution hurricane wind field is used to drive the coupled Delft3D-SWAN hydrodynamic and wave models over a series of grids with the finest resolution in GSB. The processes that control water levels in the back-barrier bay are investigated by comparing the results of four cases that include: (i) tides only; (ii) tides, winds and waves with no overwash over Fire Island allowed; (iii) tides, winds, waves and limited overwash at the east end of the island; (iv) tides, winds, waves and extensive overwash along the island. The results indicate that strong local wind-driven storm surge along the bay axis had the largest influence on the total water level fluctuations during the hurricane. However, the simulations allowing for overwash have higher correlation with water level observations in GSB and suggest that island overwash provided a significant contribution of ocean water to eastern GSB during the storm. The computations indicate that overwash of 7500-10,000 m3s-1 was approximately the same as the inflow from the ocean through the major existing inlet. Overall, the model results indicate the complex variability in total water levels driven by tides, ocean storm surge, surge from local winds, and overwash that had a significant impact on the circulation in Great South Bay during Hurricane Sandy.

Bathymetry, substrate and circulation in Westcott Bay, San Juan Islands, Washington

USGS Publications Warehouse

Grossman, Eric E.; Stevens, Andrew W.; Curran, Chris; Smith, Collin; Schwartz, Andrew

2007-01-01

Nearshore bathymetry, substrate type, and circulation patterns in Westcott Bay, San Juan Islands, Washington, were mapped using two acoustic sonar systems, video and direct sampling of seafloor sediments. The goal of the project was to characterize nearshore habitat and conditions influencing eelgrass (Z. marina) where extensive loss has occurred since 1995. A principal hypothesis for the loss of eelgrass is a recent decrease in light availability for eelgrass growth due to increase in turbidity associated with either an increase in fine sedimentation or biological productivity within the bay. To explore sources for this fine sediment and turbidity, a dual-frequency Biosonics sonar operating at 200 and 430 kHz was used to map seafloor depth, morphology and vegetation along 69 linear kilometers of the bay. The higher frequency 430 kHz system also provided information on particulate concentrations in the water column. A boat-mounted 600 kHz RDI Acoustic Doppler Current Profiler (ADCP) was used to map current velocity and direction and water column backscatter intensity along another 29 km, with select measurements made to characterize variations in circulation with tides. An underwater video camera was deployed to ground-truth acoustic data. Seventy one sediment samples were collected to quantify sediment grain size distributions across Westcott Bay. Sediment samples were analyzed for grain size at the Western Coastal and Marine Geology Team sediment laboratory in Menlo Park, Calif. These data reveal that the seafloor near the entrance to Westcott Bay is rocky with a complex morphology and covered with dense and diverse benthic vegetation. Current velocities were also measured to be highest at the entrance and along a deep channel extending 1 km into the bay. The substrate is increasingly comprised of finer sediments with distance into Westcott Bay where current velocities are lower. This report describes the data collected and preliminary findings of USGS Cruise B-6-07-PS conducted between May 31, 2007 and June 5, 2007.

First Step Towards a Coastal Modelling System for South Africa: a St. Helena Bay Case Study

NASA Astrophysics Data System (ADS)

Collins, C.; Lamont, T.; Loveday, B. R.; Hermes, J. C.; Veitch, J.; Backeberg, B.

2016-02-01

St. Helena Bay, forming part of the southern Benguela ecosystem, is the largest bay on the west coast of South Africa and is a biologically important region for pelagic fish, hake, and rock lobster. To date, only a few infrequent studies have focussed on variations in the bay scale circulation. A monthly ship-based monitoring line, the St. Helena Bay Monitoring Line (SHBML), was initiated in 2000 to determine the seasonal changes in cross-shelf hydrography and biology. Even though there has been an increase in ocean modelling in and around South Africa in recent years, coastal modelling is still in its infancy. The 12-year observational data set in the St. Helena Bay region, the only long-term, cross-shelf, full water column data-set for South Africa, makes this area the perfect natural laboratory for the development of a coastal modelling system. In this study, the climatological mean temperature and salinity from three different ROMS simulations and a HYCOM simulation are evaluated against the in situ observations from the SHBML with the aim of determining the influence of different forcing products, horizontal and vertical resolution as well as vertical coordinate schemes on the vertical structure of the ocean. The model simulations tend to overestimate the temperature and salinity across the shelf, and particularly within St. Helena Bay. Furthermore, the models misrepresent the vertical salinity and temperature structures. Interestingly, below 800m, there is a better agreement between temperature in the models and the in-situ observations. This is the first detailed comparison of modelled and in-situ data for the greater St. Helena Bay area at this scale and the next phase will examine whether the model that is most congruent with the observations resolves the same interannual signals as observed in the in-situ data.

The role of surface and subsurface processes in keeping pace with sea level rise in intertidal wetlands of Moreton Bay, Queensland, Australia

USGS Publications Warehouse

Lovelock, Catherine E.; Bennion, Vicki; Grinham, Alistair; Cahoon, Donald R.

2011-01-01

Increases in the elevation of the soil surfaces of mangroves and salt marshes are key to the maintenance of these habitats with accelerating sea level rise. Understanding the processes that give rise to increases in soil surface elevation provides science for management of landscapes for sustainable coastal wetlands. Here, we tested whether the soil surface elevation of mangroves and salt marshes in Moreton Bay is keeping up with local rates of sea level rise (2.358 mm y-1) and whether accretion on the soil surface was the most important process for keeping up with sea level rise. We found variability in surface elevation gains, with sandy areas in the eastern bay having the highest surface elevation gains in both mangrove and salt marsh (5.9 and 1.9 mm y-1) whereas in the muddier western bay rates of surface elevation gain were lower (1.4 and -0.3 mm y-1 in mangrove and salt marsh, respectively). Both sides of the bay had similar rates of surface accretion (~7–9 mm y-1 in the mangrove and 1–3 mm y-1 in the salt marsh), but mangrove soils in the western bay were subsiding at a rate of approximately 8 mm y-1, possibly due to compaction of organic sediments. Over the study surface elevation increments were sensitive to position in the intertidal zone (higher when lower in the intertidal) and also to variation in mean sea level (higher at high sea level). Although surface accretion was the most important process for keeping up with sea level rise in the eastern bay, subsidence largely negated gains made through surface accretion in the western bay indicating a high vulnerability to sea level rise in these forests.

Make the most of your samples: Bayes factor estimators for high-dimensional models of sequence evolution.

PubMed

Baele, Guy; Lemey, Philippe; Vansteelandt, Stijn

2013-03-06

Accurate model comparison requires extensive computation times, especially for parameter-rich models of sequence evolution. In the Bayesian framework, model selection is typically performed through the evaluation of a Bayes factor, the ratio of two marginal likelihoods (one for each model). Recently introduced techniques to estimate (log) marginal likelihoods, such as path sampling and stepping-stone sampling, offer increased accuracy over the traditional harmonic mean estimator at an increased computational cost. Most often, each model's marginal likelihood will be estimated individually, which leads the resulting Bayes factor to suffer from errors associated with each of these independent estimation processes. We here assess the original 'model-switch' path sampling approach for direct Bayes factor estimation in phylogenetics, as well as an extension that uses more samples, to construct a direct path between two competing models, thereby eliminating the need to calculate each model's marginal likelihood independently. Further, we provide a competing Bayes factor estimator using an adaptation of the recently introduced stepping-stone sampling algorithm and set out to determine appropriate settings for accurately calculating such Bayes factors, with context-dependent evolutionary models as an example. While we show that modest efforts are required to roughly identify the increase in model fit, only drastically increased computation times ensure the accuracy needed to detect more subtle details of the evolutionary process. We show that our adaptation of stepping-stone sampling for direct Bayes factor calculation outperforms the original path sampling approach as well as an extension that exploits more samples. Our proposed approach for Bayes factor estimation also has preferable statistical properties over the use of individual marginal likelihood estimates for both models under comparison. Assuming a sigmoid function to determine the path between two competing models, we provide evidence that a single well-chosen sigmoid shape value requires less computational efforts in order to approximate the true value of the (log) Bayes factor compared to the original approach. We show that the (log) Bayes factors calculated using path sampling and stepping-stone sampling differ drastically from those estimated using either of the harmonic mean estimators, supporting earlier claims that the latter systematically overestimate the performance of high-dimensional models, which we show can lead to erroneous conclusions. Based on our results, we argue that highly accurate estimation of differences in model fit for high-dimensional models requires much more computational effort than suggested in recent studies on marginal likelihood estimation.

Make the most of your samples: Bayes factor estimators for high-dimensional models of sequence evolution

PubMed Central

2013-01-01

Background Accurate model comparison requires extensive computation times, especially for parameter-rich models of sequence evolution. In the Bayesian framework, model selection is typically performed through the evaluation of a Bayes factor, the ratio of two marginal likelihoods (one for each model). Recently introduced techniques to estimate (log) marginal likelihoods, such as path sampling and stepping-stone sampling, offer increased accuracy over the traditional harmonic mean estimator at an increased computational cost. Most often, each model’s marginal likelihood will be estimated individually, which leads the resulting Bayes factor to suffer from errors associated with each of these independent estimation processes. Results We here assess the original ‘model-switch’ path sampling approach for direct Bayes factor estimation in phylogenetics, as well as an extension that uses more samples, to construct a direct path between two competing models, thereby eliminating the need to calculate each model’s marginal likelihood independently. Further, we provide a competing Bayes factor estimator using an adaptation of the recently introduced stepping-stone sampling algorithm and set out to determine appropriate settings for accurately calculating such Bayes factors, with context-dependent evolutionary models as an example. While we show that modest efforts are required to roughly identify the increase in model fit, only drastically increased computation times ensure the accuracy needed to detect more subtle details of the evolutionary process. Conclusions We show that our adaptation of stepping-stone sampling for direct Bayes factor calculation outperforms the original path sampling approach as well as an extension that exploits more samples. Our proposed approach for Bayes factor estimation also has preferable statistical properties over the use of individual marginal likelihood estimates for both models under comparison. Assuming a sigmoid function to determine the path between two competing models, we provide evidence that a single well-chosen sigmoid shape value requires less computational efforts in order to approximate the true value of the (log) Bayes factor compared to the original approach. We show that the (log) Bayes factors calculated using path sampling and stepping-stone sampling differ drastically from those estimated using either of the harmonic mean estimators, supporting earlier claims that the latter systematically overestimate the performance of high-dimensional models, which we show can lead to erroneous conclusions. Based on our results, we argue that highly accurate estimation of differences in model fit for high-dimensional models requires much more computational effort than suggested in recent studies on marginal likelihood estimation. PMID:23497171

Categorizing Variations of Student-Implemented Sorting Algorithms

ERIC Educational Resources Information Center

Taherkhani, Ahmad; Korhonen, Ari; Malmi, Lauri

2012-01-01

In this study, we examined freshmen students' sorting algorithm implementations in data structures and algorithms' course in two phases: at the beginning of the course before the students received any instruction on sorting algorithms, and after taking a lecture on sorting algorithms. The analysis revealed that many students have insufficient…

A simple new filter for nonlinear high-dimensional data assimilation

NASA Astrophysics Data System (ADS)

Tödter, Julian; Kirchgessner, Paul; Ahrens, Bodo

2015-04-01

The ensemble Kalman filter (EnKF) and its deterministic variants, mostly square root filters such as the ensemble transform Kalman filter (ETKF), represent a popular alternative to variational data assimilation schemes and are applied in a wide range of operational and research activities. Their forecast step employs an ensemble integration that fully respects the nonlinear nature of the analyzed system. In the analysis step, they implicitly assume the prior state and observation errors to be Gaussian. Consequently, in nonlinear systems, the analysis mean and covariance are biased, and these filters remain suboptimal. In contrast, the fully nonlinear, non-Gaussian particle filter (PF) only relies on Bayes' theorem, which guarantees an exact asymptotic behavior, but because of the so-called curse of dimensionality it is exposed to weight collapse. This work shows how to obtain a new analysis ensemble whose mean and covariance exactly match the Bayesian estimates. This is achieved by a deterministic matrix square root transformation of the forecast ensemble, and subsequently a suitable random rotation that significantly contributes to filter stability while preserving the required second-order statistics. The forecast step remains as in the ETKF. The proposed algorithm, which is fairly easy to implement and computationally efficient, is referred to as the nonlinear ensemble transform filter (NETF). The properties and performance of the proposed algorithm are investigated via a set of Lorenz experiments. They indicate that such a filter formulation can increase the analysis quality, even for relatively small ensemble sizes, compared to other ensemble filters in nonlinear, non-Gaussian scenarios. Furthermore, localization enhances the potential applicability of this PF-inspired scheme in larger-dimensional systems. Finally, the novel algorithm is coupled to a large-scale ocean general circulation model. The NETF is stable, behaves reasonably and shows a good performance with a realistic ensemble size. The results confirm that, in principle, it can be applied successfully and as simple as the ETKF in high-dimensional problems without further modifications of the algorithm, even though it is only based on the particle weights. This proves that the suggested method constitutes a useful filter for nonlinear, high-dimensional data assimilation, and is able to overcome the curse of dimensionality even in deterministic systems.

Variational Bayes method for estimating transit route OD flows using APC data.

DOT National Transportation Integrated Search

2017-01-31

The focus of this study is on the use of large quantities of APC data to estimate OD flows : for transit bus routes. Since most OD flow estimation methodologies based on boarding and : alighting counts were developed before the prevalence of APC tech...

Pathogenicity variation in two west coast forest Phytophthoras, Phytophthora nemorosa and P. pseudosyringae, to bay laurel

Treesearch

R.E. Linzer; M. Garbelotto

2008-01-01

Two recently described pathogenic oomycetes, Phytophthora nemorosa and P. pseudosyringae, have overlapping host and geographic ranges in California and Oregon forests with P. ramorum, causal agent of ?sudden oak death? disease. Preliminary genetic evidence indicates P. nemorosa and P....

Seasonal variation in apparent conductivity and soil salinity at two Narragansett Bay salt marshes

EPA Science Inventory

Measurement of the apparent conductivity of salt marsh sediments using electromagnetic induction (EMI) is a rapid alternative to traditional methods of salinity determination that can be used to map soil salinity across a marsh surface. Soil salinity measures can provide informat...

ESTUARINE PHYTOPLANKTON PRIMARY PRODUCTION AND SIZE AS DETERMINED REMOTELY FROM AIRCRAFT AND COASTAL OBSERVATION

EPA Science Inventory

We used remotely sensed estimates of chlorophyll a and sea surface temperature, incorporated into the Chesapeake Bay Productivity Model (Harding et al., 2002), to estimate the spatial and temporal variation of phytoplankton net primary production and species size in the Narragans...

Relative contributions of external forcing factors to circulation and hydrographic properties in a micro-tidal bay

NASA Astrophysics Data System (ADS)

Yoon, Seokjin; Kasai, Akihide

2017-11-01

The dominant external forcing factors influencing estuarine circulation differ among coastal environments. A three-dimensional regional circulation model was developed to estimate external influence indices and relative contributions of external forcing factors such as external oceanic forcing, surface heat flux, wind stress, and river discharge to circulation and hydrographic properties in Tango Bay, Japan. Model results show that in Tango Bay, where the Tsushima Warm Current passes offshore of the bay, under conditions of strong seasonal winds and river discharge, the water temperature and salinity are strongly influenced by surface heat flux and river discharge in the surface layer, respectively, while in the middle and bottom layers both are mainly controlled by open boundary conditions. The estuarine circulation is comparably influenced by all external forcing factors, the strong current, surface heat flux, wind stress, and river discharge. However, the influence degree of each forcing factor varies with temporal variations in external forcing factors as: the influence of open boundary conditions is higher in spring and early summer when the stronger current passes offshore of the bay, that of surface heat flux reflects the absolute value of surface heat flux, that of wind stress is higher in late fall and winter due to strong seasonal winds, and that of river discharge is higher in early spring due to snow-melting and summer and early fall due to flood events.

Effect of temperature and salinity on phosphate sorption on marine sediments.

PubMed

Zhang, Jia-Zhong; Huang, Xiao-Lan

2011-08-15

Our previous studies on the phosphate sorption on sediments in Florida Bay at 25 °C in salinity 36 seawater revealed that the sorption capacity varies considerably within the bay but can be attributed to the content of sedimentary P and Fe. It is known that both temperature and salinity influence the sorption process and their natural variations are the greatest in estuaries. To provide useful sorption parameters for modeling phosphate cycle in Florida Bay, a systematic study was carried out to quantify the effects of salinity and temperature on phosphate sorption on sediments. For a given sample, the zero equilibrium phosphate concentration and the distribution coefficient were measured over a range of salinity (2-72) and temperature (15-35 °C) conditions. Such a suite of experiments with combinations of different temperature and salinity were performed for 14 selected stations that cover a range of sediment characteristics and geographic locations of the bay. Phosphate sorption was found to increase with increasing temperature or decreasing salinity and their effects depended upon sediment's exchangeable P content. This study provided the first estimate of the phosphate sorption parameters as a function of salinity and temperature in marine sediments. Incorporation of these parameters in water quality models will enable them to predict the effect of increasing freshwater input, as proposed by the Comprehensive Everglades Restoration Plan, on the seasonal cycle of phosphate in Florida Bay.

Distribution and spawning dynamics of capelin (Mallotus villosus) in Glacier Bay, Alaska: A cold water refugium

USGS Publications Warehouse

Arimitsu, Mayumi L.; Piatt, John F.; Litzow, Michael A.; Abookire, Alisa A.; Romano, Marc D.; Robards, Martin D.

2008-01-01

Pacific capelin (Mallotus villosus) populations declined dramatically in the Northeastern Pacific following ocean warming after the regime shift of 1977, but little is known about the cause of the decline or the functional relationships between capelin and their environment. We assessed the distribution and abundance of spawning, non-spawning adult and larval capelin in Glacier Bay, an estuarine fjord system in southeastern Alaska. We used principal components analysis to analyze midwater trawl and beach seine data collected between 1999 and 2004 with respect to oceanographic data and other measures of physical habitat including proximity to tidewater glaciers and potential spawning habitat. Both spawning and non-spawning adult Pacific capelin were more likely to occur in areas closest to tidewater glaciers, and those areas were distinguished by lower temperature, higher turbidity, higher dissolved oxygen and lower chlorophyll a levels when compared with other areas of the bay. The distribution of larval Pacific capelin was not sensitive to glacial influence. Pre-spawning females collected farther from tidewater glaciers were at a lower maturity state than those sampled closer to tidewater glaciers, and the geographic variation in the onset of spawning is likely the result of differences in the marine habitat among sub-areas of Glacier Bay. Proximity to cold water in Glacier Bay may have provided a refuge for capelin during the recent warm years in the Gulf of Alaska.

Hyperspectral remote sensing of coral reefs: Deriving bathymetry, aquatic optical properties and a benthic spectral unmixing classification using AVIRIS data in the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Goodman, James Ansell

My research focuses on the development and application of hyperspectral remote sensing as a valuable component in the assessment and management of coral ecosystems. Remote sensing provides an important quantitative ability to investigate the spatial dynamics of coral health and evaluate the impacts of local, regional and global change on this important natural resource. Furthermore, advances in detector capabilities and analysis methods, particularly with respect to hyperspectral remote sensing, are also increasing the accuracy and level of effectiveness of the resulting data products. Using imagery of Kaneohe Bay and French Frigate Shoals in the Hawaiian Islands, acquired in 2000 by NASA's Airborne Visible InfraRed Imaging Spectrometer (AVIRIS), I developed, applied and evaluated algorithms for analyzing coral reefs using hyperspectral remote sensing data. Research included developing methods for acquiring in situ underwater reflectance, collecting spectral measurements of the dominant bottom components in Kaneohe Bay, applying atmospheric correction and sunglint removal algorithms, employing a semianalytical optimization model to derive bathymetry and aquatic optical properties, and developing a linear unmixing approach for deriving bottom composition. Additionally, algorithm development focused on using fundamental scientific principles to facilitate the portability of methods to diverse geographic locations and across variable environmental conditions. Assessments of this methodology compared favorably with available field measurements and habitat information, and the overall analysis demonstrated the capacity to derive information on water properties, bathymetry and habitat composition. Thus, results illustrated a successful approach for extracting environmental information and habitat composition from a coral reef environment using hyperspectral remote sensing.

Prediction of Endocrine System Affectation in Fisher 344 Rats by Food Intake Exposed with Malathion, Applying Naïve Bayes Classifier and Genetic Algorithms

PubMed Central

Mora, Juan David Sandino; Hurtado, Darío Amaya; Sandoval, Olga Lucía Ramos

2016-01-01

Background: Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. Methods: It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. Results: There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. Conclusions: The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands. PMID:27833725

Prediction of Endocrine System Affectation in Fisher 344 Rats by Food Intake Exposed with Malathion, Applying Naïve Bayes Classifier and Genetic Algorithms.

PubMed

Mora, Juan David Sandino; Hurtado, Darío Amaya; Sandoval, Olga Lucía Ramos

2016-01-01

Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands.

How does ocean seasonality drive habitat preferences of highly mobile top predators? Part II: The eastern North-Atlantic

NASA Astrophysics Data System (ADS)

Lambert, C.; Pettex, E.; Dorémus, G.; Laran, S.; Stéphan, E.; Canneyt, O. Van; Ridoux, V.

2017-07-01

Marine ecosystems are characterised by strong heterogeneity and variability, both spatially and temporally. In particular, seasonal variations may lead to severe constraints for predators which have to cope with these variations, for example through migration to avoid unfavourable seasons, or adaptation to local modification of the ecosystem. In the Bay of Biscay and English Channel, ecosystem seasonality is well marked, especially over the shelf. Cetacean and seabird communities within the Bay of Biscay, Celtic Sea and English Channel were studied during aerial surveys conducted in winter 2011-2012 and summer 2012, following a strip-transect methodology deployed from the coast to oceanic waters. We explored seasonal variations of habitat preferences of four cetacean and six seabird groups through Generalised Additive Models, using physiographic variables and weekly- and monthly-averaged oceanographic predictors for both seasons. Our results provided the first overview at such a large scale of the variation of habitat preferences in response to the seasonality of the ocean by seabirds in that region, at such a large scale. Habitat models resulted in explained deviances from 13 to 55%. Predators answered the seasonality of their environment in different ways. Long-finned pilot whales and Risso's dolphins were the only studied group exhibiting no habitat variations between seasons, targeting the shelf break throughout the year. The other groups modulated their habitat preferences between seasons to optimise the compromise between the ocean seasonal variations and their own constraints: common and striped dolphins, bottlenose dolphins and harbour porpoises for cetaceans; northern gannets, auks, northern fulmars and kittiwakes for seabirds. For shearwaters, the seasonality had an extreme impact, inducing a complete absence from the region during the unfavourable season.

Virioplankton dynamics are related to eutrophication levels in a tropical urbanized bay

PubMed Central

Cabral, Anderson S.; Lessa, Mariana M.; Junger, Pedro C.; Thompson, Fabiano L.; Paranhos, Rodolfo

2017-01-01

Virioplankton are an important and abundant biological component of marine and freshwater ecosystems. Often overlooked, aquatic viruses play an important role in biogeochemical cycles on a global scale, infecting both autotrophic and heterotrophic microbes. Viral diversity, abundance, and viral interactions at different trophic levels in aqueous environments are not well understood. Tropical ecosystems are less frequently studied than temperate ecosystems, but could provide new insights into how physical and chemical variability can shape or force microbial community changes. In this study, we found high viral abundance values in Guanabara Bay relative to other estuaries around the world. Viral abundance was positively correlated with bacterioplankton abundance and chlorophyll a concentrations. Moreover, prokaryotic and viral abundance were positively correlated with eutrophication, especially in surface waters. These results provide novel baseline data on the quantitative distribution of aquatic viruses in tropical estuaries. They also provide new information on a complex and dynamic relationship in which environmental factors influence the abundance of bacterial hosts and consequently their viruses. Guanabara Bay is characterized by spatial and seasonal variations, and the eutrophication process is the most important factor explaining the structuring of virioplankton abundance and distribution in this tropical urbanized bay. PMID:28362842

Greenland coastal air temperatures linked to Baffin Bay and Greenland Sea ice conditions during autumn through regional blocking patterns

NASA Astrophysics Data System (ADS)

Ballinger, Thomas J.; Hanna, Edward; Hall, Richard J.; Miller, Jeffrey; Ribergaard, Mads H.; Høyer, Jacob L.

2018-01-01

Variations in sea ice freeze onset and regional sea surface temperatures (SSTs) in Baffin Bay and Greenland Sea are linked to autumn surface air temperatures (SATs) around coastal Greenland through 500 hPa blocking patterns, 1979-2014. We find strong, statistically significant correlations between Baffin Bay freeze onset and SSTs and SATs across the western and southernmost coastal areas, while weaker and fewer significant correlations are found between eastern SATs, SSTs, and freeze periods observed in the neighboring Greenland Sea. Autumn Greenland Blocking Index values and the incidence of meridional circulation patterns have increased over the modern sea ice monitoring era. Increased anticyclonic blocking patterns promote poleward transport of warm air from lower latitudes and local warm air advection onshore from ocean-atmosphere sensible heat exchange through ice-free or thin ice-covered seas bordering the coastal stations. Temperature composites by years of extreme late freeze conditions, occurring since 2006 in Baffin Bay, reveal positive monthly SAT departures that often exceed 1 standard deviation from the 1981-2010 climate normal over coastal areas that exhibit a similar spatial pattern as the peak correlations.

Occurance and survival of Vibrio alginolyticus in Tamouda Bay (Morocco).

PubMed

Sabir, M; Cohen, N; Boukhanjer, A; Ennaji, M M

2011-10-15

The objectives of this study were to investigate the spatial and seasonal fluctuations of Vibrio alginolyticus in marine environment of the Tamouda Bay on the Mediterranean coast of Morocco and to determine the dominant factors of the environment that govern these fluctuations. The samples (sea water, plankton, shellfish and sediment) were collected fortnightly for two years from three study sites on the coast Tamouda Bay in northern Morocco. The charge of Vibrio alginolyticus is determined by MPN method. The physicochemical parameters including temperature of sea water, pH, salinity, turbidity and chlorophyll a concentration were determined. Analysis of variance of specific variables and several principal component analyses showed that the temperature of seawater is the major determinant of seasonal distribution of Vibrio alginolyticus. The results showed a positive linear correlation between Vibrio alginolyticus and the water temperature, pH, turbidity and chlorophyll a. Similarly, there are seasonal variations and spatial of Vibrio alginolyticus in marine environment of the Tamouda bay and the highest concentrations were recorded in both years of study during the warm season whereas it was minimal during the cold season. Linear positive correlation was recorded between Vibrio alginolyticus populations in all ecological types of samples studied.

Paleomagnetic investigation of late Quaternary sediments of south San Francisco Bay, California

USGS Publications Warehouse

Hillhouse, John W.

1977-01-01

Paleomagnetic inclinations of the Late Quaternary sediments of South San Francisco Bay were determined from bore hole samples collected near Dumbarton Bridge. The sediments consist of estuarine muds and nonmarine sand deposits, floored by bedrock of the Mesozoic Franciscan Formation. - Beneath Dumbarton Bridge the entire sedimentary fill is normally polarized; therefore, the fill postdates the Brunhes-Matayama polarity reversal (700,000 y. B.P.). Magnetic time lines such as the Mono Lake excursion (24,000 y. B.P.) and the reversed Blake event (110,000 y B.P.) were not found in this bore hole. In addition to Holocene and modern deposits of San Francisco Bay, an older estuarine unit occurs in the stratigraphic section. The older unit was deposited during a period of high sea level, tentatively correlated with the Sangamon interglacial period. Because evidence of the Blake event is not present in the older estuarine unit, the proposed age of this unit could not be confirmed. Although the Holocene estuarine deposits of South San Francisco Bay carry stable remanent magnetization, a reliable record of geomagnetic secular variation could not be recovered because the water-saturated sdiment was deformed by drilling.

Human and riverine impacts on the dynamics of seawater nutrient and carbon parameters in Kwangyang Bay, South Korea

NASA Astrophysics Data System (ADS)

Kim, Tae-Wook; Kim, Dongseon; Baek, Seung Ho; Kim, Young Ok

2015-04-01

We investigated seawater nutrient and carbon parameters in Kwangyang Bay, South Korea, which has been exposed to significant human influences, in each core month of four seasons for between 2010 and 2012. The survey data were analyzed using multivariate statistics analysis (cluster and factor analysis). As a result, we found that the Seomjin River (the fifth largest river in South Korea) and biological activity, including phytoplankton photosynthesis and bacterial decomposition, were the main factors determining the overall water quality of the bay. However, the impacts of these factors varied both spatially and seasonally, because the factors were linked with the geographical environments and seasonal variations in freshwater discharge. In particular, the Seomjin River was primarily responsible for nitrate, silicate, total alkalinity, and dissolved inorganic carbon, and exhibited a significant impact in the summer. During the past 10 years, nutrient loads from the river and industrial complexes to the bay have decreased. The impacts of this decrease are visible in the phosphate concentration, which has fallen to a third of its initial value. We also examined the potential role of atmospheric nitrogen deposition in nitrogen cycling in the study area.

Diagnostic modeling of trace metal partitioning in south San Francisco Bay

USGS Publications Warehouse

Wood, T. W.; Baptista, A. M.; Kuwabara, J.S.; Flegal, A.R.

1995-01-01

The numerical results indicate that aqueous speciation will control basin-scale spatial variations in the apparent distribution coefficient, Kda, if the system is close to equilibrium. However, basin-scale spatial variations in Kda are determined by the location of the sources of metal and the suspended solids concentration of the receiving water if the system is far from equilibrium. The overall spatial variability in Kda also increases as the system moves away from equilibrium.

Assessing the suitability of benthic foraminiferal morpho-groups to reconstruct paleomonsoon from Bay of Bengal

NASA Astrophysics Data System (ADS)

Manasa, M.; Saraswat, Rajeev; Nigam, Rajiv

2016-04-01

Temporal changes in benthic foraminiferal morpho-groups were suggested as an effective proxy to reconstruct past monsoon intensity from the Arabian Sea. Here, in order to test the applicability of temporal variation in morpho-groups to reconstruct past monsoon intensity from the Bay of Bengal, we have documented recent benthic foraminiferal distribution from the continental shelf region of the northwestern Bay of Bengal. Based on the external morphology, benthic foraminifera were categorized into rounded symmetrical (RSBF) and angular asymmetrical benthic foraminifera (AABF). Additionally, a few other dominant groups were also identified based on test composition (agglutinated, calcareous) and abundance (Asterorotalids and Nonions). The relative abundance of each group was compared with the ambient physico-chemical conditions, including dissolved oxygen, organic matter, salinity and temperature. We report that the RSBF are abundant in comparatively warm and well oxygenated waters of low salinity, suggesting a preference for high energy environment, whereas AABF dominate relatively cold, hypersaline deeper waters with low dissolved oxygen, indicating a low energy environment. The agglutinated foraminifera, Asterorotalids and Nonions dominate shallow water, low salinity regions, whereas the calcareous benthic foraminiferal abundance increases away from the riverine influx regions. Food availability, as estimated from organic carbon abundance in sediments, has comparatively less influence on faunal distribution in the northwestern Bay of Bengal, as compared to dissolved oxygen, temperature and salinity. We conclude that the factors associated with freshwater influx affect the distribution of benthic foraminiferal morpho-groups in the northwestern Bay of Bengal and thus it can be used to reconstruct past monsoon intensity from the Bay of Bengal.

A NEW METHOD OF PEAK DETECTION FOR ANALYSIS OF COMPREHENSIVE TWO-DIMENSIONAL GAS CHROMATOGRAPHY MASS SPECTROMETRY DATA*

PubMed Central

Kim, Seongho; Ouyang, Ming; Jeong, Jaesik; Shen, Changyu; Zhang, Xiang

2014-01-01

We develop a novel peak detection algorithm for the analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) data using normal-exponential-Bernoulli (NEB) and mixture probability models. The algorithm first performs baseline correction and denoising simultaneously using the NEB model, which also defines peak regions. Peaks are then picked using a mixture of probability distribution to deal with the co-eluting peaks. Peak merging is further carried out based on the mass spectral similarities among the peaks within the same peak group. The algorithm is evaluated using experimental data to study the effect of different cut-offs of the conditional Bayes factors and the effect of different mixture models including Poisson, truncated Gaussian, Gaussian, Gamma, and exponentially modified Gaussian (EMG) distributions, and the optimal version is introduced using a trial-and-error approach. We then compare the new algorithm with two existing algorithms in terms of compound identification. Data analysis shows that the developed algorithm can detect the peaks with lower false discovery rates than the existing algorithms, and a less complicated peak picking model is a promising alternative to the more complicated and widely used EMG mixture models. PMID:25264474

Multivariate spline methods in surface fitting

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator); Schumaker, L. L.

1984-01-01

The use of spline functions in the development of classification algorithms is examined. In particular, a method is formulated for producing spline approximations to bivariate density functions where the density function is decribed by a histogram of measurements. The resulting approximations are then incorporated into a Bayesiaan classification procedure for which the Bayes decision regions and the probability of misclassification is readily computed. Some preliminary numerical results are presented to illustrate the method.

Adaptive Bayes classifiers for remotely sensed data

NASA Technical Reports Server (NTRS)

Raulston, H. S.; Pace, M. O.; Gonzalez, R. C.

1975-01-01

An algorithm is developed for a learning, adaptive, statistical pattern classifier for remotely sensed data. The estimation procedure consists of two steps: (1) an optimal stochastic approximation of the parameters of interest, and (2) a projection of the parameters in time and space. The results reported are for Gaussian data in which the mean vector of each class may vary with time or position after the classifier is trained.

On Algorithms for Generating Computationally Simple Piecewise Linear Classifiers

DTIC Science & Technology

1989-05-01

suffers. - Waveform classification, e.g. speech recognition, seismic analysis (i.e. discrimination between earthquakes and nuclear explosions), target...assuming Gaussian distributions (B-G) d) Bayes classifier with probability densities estimated with the k-N-N method (B- kNN ) e) The -arest neighbour...range of classifiers are chosen including a fast, easy computable and often used classifier (B-G), reliable and complex classifiers (B- kNN and NNR

Validation of potential fishing zone forecast using experimental fishing method in Tolo Bay, Central Sulawesi Province

NASA Astrophysics Data System (ADS)

Rintaka, W. E.; Susilo, E.

2018-04-01

The national scale of Indonesian Potential Fishing Zone (PFZ) forecast system has been established since 2000. Recent times this system use Single Image Edge Detection algorithm to automatically identify thermal front from remote sensing images. Its generate two fishing ground/FG criteria: FG (high probability) and potential fishing ground/PFG (medium/low probability). To quantify the accuracy of this algorithm, an experimental fishing/EF was carried out in Tolo Bay, Central Sulawesi Province at September 2016 the late southeast monsoon period by using a pole and line fishing vessel. Four fishing activities (P1, P2, P3, and P4) were conducted during this study at a different location nearby the PFZ forecast position, two of them had good results. Based on distance measurement, these locations P1 and P4 were associated with PFZ forecast position. They were associated with PFG and FG criteria. The distance between EF to P1 and P4 were 9.7 and 6.69 nautical miles. The amount of catch for each location was 850 and 900 kg, respectively. The other locations P2 and P3 were also associated with PFG criteria, but there was no catch. We conclude that the number of the catch is influenced by the distance from PFZ forecast position and criteria.

Exploring variation-aware contig graphs for (comparative) metagenomics using MaryGold

PubMed Central

Nijkamp, Jurgen F.; Pop, Mihai; Reinders, Marcel J. T.; de Ridder, Dick

2013-01-01

Motivation: Although many tools are available to study variation and its impact in single genomes, there is a lack of algorithms for finding such variation in metagenomes. This hampers the interpretation of metagenomics sequencing datasets, which are increasingly acquired in research on the (human) microbiome, in environmental studies and in the study of processes in the production of foods and beverages. Existing algorithms often depend on the use of reference genomes, which pose a problem when a metagenome of a priori unknown strain composition is studied. In this article, we develop a method to perform reference-free detection and visual exploration of genomic variation, both within a single metagenome and between metagenomes. Results: We present the MaryGold algorithm and its implementation, which efficiently detects bubble structures in contig graphs using graph decomposition. These bubbles represent variable genomic regions in closely related strains in metagenomic samples. The variation found is presented in a condensed Circos-based visualization, which allows for easy exploration and interpretation of the found variation. We validated the algorithm on two simulated datasets containing three respectively seven Escherichia coli genomes and showed that finding allelic variation in these genomes improves assemblies. Additionally, we applied MaryGold to publicly available real metagenomic datasets, enabling us to find within-sample genomic variation in the metagenomes of a kimchi fermentation process, the microbiome of a premature infant and in microbial communities living on acid mine drainage. Moreover, we used MaryGold for between-sample variation detection and exploration by comparing sequencing data sampled at different time points for both of these datasets. Availability: MaryGold has been written in C++ and Python and can be downloaded from http://bioinformatics.tudelft.nl/software Contact: d.deridder@tudelft.nl PMID:24058058

Current temporal asymmetry and the role of tides: Nan-Wan Bay vs. the Gulf of Elat

NASA Astrophysics Data System (ADS)

Ashkenazy, Yosef; Fredj, Erick; Gildor, Hezi; Gong, Gwo-Ching; Lee, Hung-Jen

2016-05-01

Nan-Wan Bay in Taiwan and the Gulf of Elat in Israel are two different coastal environments, and as such, their currents are expected to have different statistical properties. While Nan-Wan Bay is shallow, has three open boundaries, and is directly connected to the open ocean, the Gulf of Elat is deep, semi-enclosed, and connected to the Red Sea via the Straits of Tiran. Surface currents have been continuously measured with fine temporal (less than or equal to 1 h) and spatial resolution (less than or equal to 1 km) for more than a year in both environments using coastal radars (CODARs) that cover a domain of roughly 10 × 10 km. These measurements show that the currents in Nan-Wan Bay are much stronger than those in the Gulf of Elat and that the mean current field in Nan-Wan Bay exhibits cyclonic circulation, which is stronger in the summer; in the Gulf of Elat, the mean current field is directed southward and is also stronger during the summer. We have compared the statistical properties of the current speeds in both environments and found that both exhibit large spatial and seasonal variations in the shape parameter of the Weibull distribution. However, we have found fundamental and significant differences when comparing the temporal asymmetry of the current speed (i.e., the ratio between the time during which the current speed increases and the total time). While the Nan-Wan Bay currents are significantly asymmetric, those of the Gulf of Elat are not. We then extracted the tidal component of the Nan-Wan Bay currents and found that it is strongly asymmetric, while the asymmetry of tidally filtered currents is much weaker. We thus conclude that the temporal asymmetry of the Nan-Wan Bay currents reported here is due to the strong tides in the region. We show that the asymmetry ratio in Nan-Wan Bay varies spatially and seasonally: (i) the currents increase rapidly and decay slowly in the northern part of the domain and vice versa in the southern part, and (ii) the asymmetry is stronger during summer.

Current temporal asymmetry and the role of tides: Nan-Wan Bay vs. the Gulf of Elat

NASA Astrophysics Data System (ADS)

Ashkenazy, Y.; Fredj, E.; Gildor, H.; Gong, G. C.; Lee, H. J.; Wu, C. R.

2016-02-01

Nan-Wan Bay in Taiwan and the Gulf of Elat in Israel are two different coastal environments and as such are expected to have different statistical properties of their currents. While the Nan-Wan Bay is shallow, has three open boundaries, and directly connected to the open ocean, the Gulf of Elat is deep, semi-enclosed, and connected to the Red Sea via the Straits of Tiran. High temporal (less or equal one hour) and spatial (less or equal one km) surface currents have been measured continuously for more than a year in both environments using Coastal Radars (CODARs) that cover a domain of roughly 10×10 kms. These measurements show that the currents in Nan-Wan Bay are much stronger than those in the Gulf of Elat and that the mean current field in Nan-Wan Bay exhibits cyclonic circulation, which is stronger in the summer; in the Gulf of Elat the mean current field is directed to south and is stronger during the summer. We have compared the statistical properties of the CODAR current speeds in both environments and found that both exhibit large spatial and seasonal variations in the shape parameter of the Weibull distribution. However, we have found fundamental and significant differences when comparing the temporal asymmetry of the current speed (i.e., the ratio between the time during which the current speed is increasing to the total time). While the Nan-Wan Bay currents are significantly asymmetric, those of the Gulf of Elat are not significantly asymmetric. We then extracted the tidal component of the Nan-Wan Bay currents and found that it is strongly asymmetric while the asymmetry of tidally-filtered currents is much weaker. We thus conclude that the temporal asymmetry of the Nan-Wan Bay currents reported here is due to the strong tides in the region. We show that the asymmetry ratio in the Nan-Wan Bay is varied spatially and seasonally: (i) currents increase rapidly and decay slowly in the northern part of the domain and vice versa in the southern part, and that (ii) the asymmetry is stronger during summer.

Seasonal/Yearly Salinity Variations in San Francisco Bay

USGS Publications Warehouse

Peterson, David H.; Cayan, Daniel R.; Dettinger, Michael D.; DiLeo, Jeanne Sandra; Hager, Stephen E.; Knowles, Noah; Nichols, Frederic H.; Schemel, Laurence E.; Smith, Richard E.; Uncles, Reginald J.

1995-01-01

The ability of resource agencies to manage fish, wildlife and freshwater supplies of San Francisco Bay estuary requires an integrated knowledge of the relations between the biota and their physical environment. A key factor in these relations is the role of salinity in determining both the physical and the biological character of the estuary. The saltiness of the water, and particularly its seasonal and interannual patterns of variability, affects which aquatic species live where within the estuary. Salinity also determines where water can and cannot be diverted for human consumption and irrigated agriculture, and plays a role in determining the capacity of the estuary to cleanse itself of wastes. In short, salinity is a fundamental property of estuarine physics and chemistry that, in turn, determines the biological characteristics of each estuary. Freshwater is a major control on estuarine salinity. Most freshwater supplied to the Bay is from river flow through the Delta, which is primarily runoff from the Sierra Nevada. Most contaminants in San Francisco Bay are from the Sacramento/San Joaquin Valley and the local watershed around the Bay rather than the sea or atmosphere. Land is the primary source of freshwater and freshwater serves as a tracer of land-derived substances such as the trace metals (copper, lead and selenium), pesticides and plant nutrients (nitrate and phosphate). The U.S. Geological Survey is collaborating with other agencies and institutions in studying San Francisco Bay salinity using field observations and numerical simulations to define the physical processes that control salinity. The issues that arise from salinity fluctuations, however, differ in the northern and southern parts of the bay. In North Bay we need to know how salinity responds to freshwater flow through the Sacramento/San Joaquin Delta; this knowledge will benefit water managers who determine how much delta flow is needed a) to protect freshwater supplies for municipal water use and b) modulate salinity for a healthy estuary. In South Bay we need to know where the freshwater comes from (the distant Delta or local streams) to sort out the sources of a) contamination or b) dilution.

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. II: Multivariate spike and slab priors for marker effects and derivation of approximate Bayes and fractional Bayes factors for the complete family of models.

PubMed

Martínez, Carlos Alberto; Khare, Kshitij; Banerjee, Arunava; Elzo, Mauricio A

2017-03-21

This study corresponds to the second part of a companion paper devoted to the development of Bayesian multiple regression models accounting for randomness of genotypes in across population genome-wide prediction. This family of models considers heterogeneous and correlated marker effects and allelic frequencies across populations, and has the ability of considering records from non-genotyped individuals and individuals with missing genotypes in any subset of loci without the need for previous imputation, taking into account uncertainty about imputed genotypes. This paper extends this family of models by considering multivariate spike and slab conditional priors for marker allele substitution effects and contains derivations of approximate Bayes factors and fractional Bayes factors to compare models from part I and those developed here with their null versions. These null versions correspond to simpler models ignoring heterogeneity of populations, but still accounting for randomness of genotypes. For each marker loci, the spike component of priors corresponded to point mass at 0 in R S , where S is the number of populations, and the slab component was a S-variate Gaussian distribution, independent conditional priors were assumed. For the Gaussian components, covariance matrices were assumed to be either the same for all markers or different for each marker. For null models, the priors were simply univariate versions of these finite mixture distributions. Approximate algebraic expressions for Bayes factors and fractional Bayes factors were found using the Laplace approximation. Using the simulated datasets described in part I, these models were implemented and compared with models derived in part I using measures of predictive performance based on squared Pearson correlations, Deviance Information Criterion, Bayes factors, and fractional Bayes factors. The extensions presented here enlarge our family of genome-wide prediction models making it more flexible in the sense that it now offers more modeling options. Copyright © 2017 Elsevier Ltd. All rights reserved.

SU-F-I-09: Improvement of Image Registration Using Total-Variation Based Noise Reduction Algorithms for Low-Dose CBCT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukherjee, S; Farr, J; Merchant, T

Purpose: To study the effect of total-variation based noise reduction algorithms to improve the image registration of low-dose CBCT for patient positioning in radiation therapy. Methods: In low-dose CBCT, the reconstructed image is degraded by excessive quantum noise. In this study, we developed a total-variation based noise reduction algorithm and studied the effect of the algorithm on noise reduction and image registration accuracy. To study the effect of noise reduction, we have calculated the peak signal-to-noise ratio (PSNR). To study the improvement of image registration, we performed image registration between volumetric CT and MV- CBCT images of different head-and-neck patientsmore » and calculated the mutual information (MI) and Pearson correlation coefficient (PCC) as a similarity metric. The PSNR, MI and PCC were calculated for both the noisy and noise-reduced CBCT images. Results: The algorithms were shown to be effective in reducing the noise level and improving the MI and PCC for the low-dose CBCT images tested. For the different head-and-neck patients, a maximum improvement of PSNR of 10 dB with respect to the noisy image was calculated. The improvement of MI and PCC was 9% and 2% respectively. Conclusion: Total-variation based noise reduction algorithm was studied to improve the image registration between CT and low-dose CBCT. The algorithm had shown promising results in reducing the noise from low-dose CBCT images and improving the similarity metric in terms of MI and PCC.« less

Total variation regularization of the 3-D gravity inverse problem using a randomized generalized singular value decomposition

NASA Astrophysics Data System (ADS)

Vatankhah, Saeed; Renaut, Rosemary A.; Ardestani, Vahid E.

2018-04-01

We present a fast algorithm for the total variation regularization of the 3-D gravity inverse problem. Through imposition of the total variation regularization, subsurface structures presenting with sharp discontinuities are preserved better than when using a conventional minimum-structure inversion. The associated problem formulation for the regularization is nonlinear but can be solved using an iteratively reweighted least-squares algorithm. For small-scale problems the regularized least-squares problem at each iteration can be solved using the generalized singular value decomposition. This is not feasible for large-scale, or even moderate-scale, problems. Instead we introduce the use of a randomized generalized singular value decomposition in order to reduce the dimensions of the problem and provide an effective and efficient solution technique. For further efficiency an alternating direction algorithm is used to implement the total variation weighting operator within the iteratively reweighted least-squares algorithm. Presented results for synthetic examples demonstrate that the novel randomized decomposition provides good accuracy for reduced computational and memory demands as compared to use of classical approaches.

An Analysis of Periodic Components in BL Lac Object S5 0716 +714 with MUSIC Method

NASA Astrophysics Data System (ADS)

Tang, J.

2012-01-01

Multiple signal classification (MUSIC) algorithms are introduced to the estimation of the period of variation of BL Lac objects.The principle of MUSIC spectral analysis method and theoretical analysis of the resolution of frequency spectrum using analog signals are included. From a lot of literatures, we have collected a lot of effective observation data of BL Lac object S5 0716 + 714 in V, R, I bands from 1994 to 2008. The light variation periods of S5 0716 +714 are obtained by means of the MUSIC spectral analysis method and periodogram spectral analysis method. There exist two major periods: (3.33±0.08) years and (1.24±0.01) years for all bands. The estimation of the period of variation of the algorithm based on the MUSIC spectral analysis method is compared with that of the algorithm based on the periodogram spectral analysis method. It is a super-resolution algorithm with small data length, and could be used to detect the period of variation of weak signals.

Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data

PubMed Central

Kang, D.-K.; Silvescu, A.; Honavar, V.

2009-01-01

In many application domains, there is a need for learning algorithms that can effectively exploit attribute value taxonomies (AVT)—hierarchical groupings of attribute values—to learn compact, comprehensible and accurate classifiers from data—including data that are partially specified. This paper describes AVT-NBL, a natural generalization of the naïve Bayes learner (NBL), for learning classifiers from AVT and data. Our experimental results show that AVT-NBL is able to generate classifiers that are substantially more compact and more accurate than those produced by NBL on a broad range of data sets with different percentages of partially specified values. We also show that AVT-NBL is more efficient in its use of training data: AVT-NBL produces classifiers that outperform those produced by NBL using substantially fewer training examples. PMID:20351793

Unconventional Hamilton-type variational principle in phase space and symplectic algorithm

NASA Astrophysics Data System (ADS)

Luo, En; Huang, Weijiang; Zhang, Hexin

2003-06-01

By a novel approach proposed by Luo, the unconventional Hamilton-type variational principle in phase space for elastodynamics of multidegree-of-freedom system is established in this paper. It not only can fully characterize the initial-value problem of this dynamic, but also has a natural symplectic structure. Based on this variational principle, a symplectic algorithm which is called a symplectic time-subdomain method is proposed. A non-difference scheme is constructed by applying Lagrange interpolation polynomial to the time subdomain. Furthermore, it is also proved that the presented symplectic algorithm is an unconditionally stable one. From the results of the two numerical examples of different types, it can be seen that the accuracy and the computational efficiency of the new method excel obviously those of widely used Wilson-θ and Newmark-β methods. Therefore, this new algorithm is a highly efficient one with better computational performance.

A comparative analysis of DBSCAN, K-means, and quadratic variation algorithms for automatic identification of swallows from swallowing accelerometry signals.

PubMed

Dudik, Joshua M; Kurosu, Atsuko; Coyle, James L; Sejdić, Ervin

2015-04-01

Cervical auscultation with high resolution sensors is currently under consideration as a method of automatically screening for specific swallowing abnormalities. To be clinically useful without human involvement, any devices based on cervical auscultation should be able to detect specified swallowing events in an automatic manner. In this paper, we comparatively analyze the density-based spatial clustering of applications with noise algorithm (DBSCAN), a k-means based algorithm, and an algorithm based on quadratic variation as methods of differentiating periods of swallowing activity from periods of time without swallows. These algorithms utilized swallowing vibration data exclusively and compared the results to a gold standard measure of swallowing duration. Data was collected from 23 subjects that were actively suffering from swallowing difficulties. Comparing the performance of the DBSCAN algorithm with a proven segmentation algorithm that utilizes k-means clustering demonstrated that the DBSCAN algorithm had a higher sensitivity and correctly segmented more swallows. Comparing its performance with a threshold-based algorithm that utilized the quadratic variation of the signal showed that the DBSCAN algorithm offered no direct increase in performance. However, it offered several other benefits including a faster run time and more consistent performance between patients. All algorithms showed noticeable differentiation from the endpoints provided by a videofluoroscopy examination as well as reduced sensitivity. In summary, we showed that the DBSCAN algorithm is a viable method for detecting the occurrence of a swallowing event using cervical auscultation signals, but significant work must be done to improve its performance before it can be implemented in an unsupervised manner. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Comparative Analysis of DBSCAN, K-Means, and Quadratic Variation Algorithms for Automatic Identification of Swallows from Swallowing Accelerometry Signals

PubMed Central

Dudik, Joshua M.; Kurosu, Atsuko; Coyle, James L

2015-01-01

Background Cervical auscultation with high resolution sensors is currently under consideration as a method of automatically screening for specific swallowing abnormalities. To be clinically useful without human involvement, any devices based on cervical auscultation should be able to detect specified swallowing events in an automatic manner. Methods In this paper, we comparatively analyze the density-based spatial clustering of applications with noise algorithm (DBSCAN), a k-means based algorithm, and an algorithm based on quadratic variation as methods of differentiating periods of swallowing activity from periods of time without swallows. These algorithms utilized swallowing vibration data exclusively and compared the results to a gold standard measure of swallowing duration. Data was collected from 23 subjects that were actively suffering from swallowing difficulties. Results Comparing the performance of the DBSCAN algorithm with a proven segmentation algorithm that utilizes k-means clustering demonstrated that the DBSCAN algorithm had a higher sensitivity and correctly segmented more swallows. Comparing its performance with a threshold-based algorithm that utilized the quadratic variation of the signal showed that the DBSCAN algorithm offered no direct increase in performance. However, it offered several other benefits including a faster run time and more consistent performance between patients. All algorithms showed noticeable differen-tiation from the endpoints provided by a videofluoroscopy examination as well as reduced sensitivity. Conclusions In summary, we showed that the DBSCAN algorithm is a viable method for detecting the occurrence of a swallowing event using cervical auscultation signals, but significant work must be done to improve its performance before it can be implemented in an unsupervised manner. PMID:25658505

A nudging-based data assimilation method: the Back and Forth Nudging (BFN) algorithm

NASA Astrophysics Data System (ADS)

Auroux, D.; Blum, J.

2008-03-01

This paper deals with a new data assimilation algorithm, called Back and Forth Nudging. The standard nudging technique consists in adding to the equations of the model a relaxation term that is supposed to force the observations to the model. The BFN algorithm consists in repeatedly performing forward and backward integrations of the model with relaxation (or nudging) terms, using opposite signs in the direct and inverse integrations, so as to make the backward evolution numerically stable. This algorithm has first been tested on the standard Lorenz model with discrete observations (perfect or noisy) and compared with the variational assimilation method. The same type of study has then been performed on the viscous Burgers equation, comparing again with the variational method and focusing on the time evolution of the reconstruction error, i.e. the difference between the reference trajectory and the identified one over a time period composed of an assimilation period followed by a prediction period. The possible use of the BFN algorithm as an initialization for the variational method has also been investigated. Finally the algorithm has been tested on a layered quasi-geostrophic model with sea-surface height observations. The behaviours of the two algorithms have been compared in the presence of perfect or noisy observations, and also for imperfect models. This has allowed us to reach a conclusion concerning the relative performances of the two algorithms.

Variation in tidal wetland plant diversity and composition within and among coastal estuaries: assessing the relative importance of environmental gradients

EPA Science Inventory

Question: Does wetland plant composition vary more by estuarine type (differentiated by the degree of riverine versus oceanic influence) or habitat type within estuaries (defined by US National Wetlands Inventory [NWI] marsh classes)? Location: Oregon estuaries: Netarts Bay, ...

INDICATORS OF CHANGE IN MID-ATLANTIC WATERSHEDS, AND CONSEQUENCES IN UPPER CHESAPEAKE BAY

EPA Science Inventory

The rate of change of atmospheric temperature in the Northern Hemisphere in the past century relative to the preceding millennium strongly suggests that we are in a period of rapid global climate change. The mid-Atlantic region is quite sensitive to larger-scale climate variation...

A hybrid-domain approach for modeling climate data time series

NASA Astrophysics Data System (ADS)

Wen, Qiuzi H.; Wang, Xiaolan L.; Wong, Augustine

2011-09-01

In order to model climate data time series that often contain periodic variations, trends, and sudden changes in mean (mean shifts, mostly artificial), this study proposes a hybrid-domain (HD) algorithm, which incorporates a time domain test and a newly developed frequency domain test through an iterative procedure that is analogue to the well known backfitting algorithm. A two-phase competition procedure is developed to address the confounding issue between modeling periodic variations and mean shifts. A variety of distinctive features of climate data time series, including trends, periodic variations, mean shifts, and a dependent noise structure, can be modeled in tandem using the HD algorithm. This is particularly important for homogenization of climate data from a low density observing network in which reference series are not available to help preserve climatic trends and long-term periodic variations, preventing them from being mistaken as artificial shifts. The HD algorithm is also powerful in estimating trend and periodicity in a homogeneous data time series (i.e., in the absence of any mean shift). The performance of the HD algorithm (in terms of false alarm rate and hit rate in detecting shifts/cycles, and estimation accuracy) is assessed via a simulation study. Its power is further illustrated through its application to a few climate data time series.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

Adaptive optics image restoration algorithm based on wavefront reconstruction and adaptive total variation method

NASA Astrophysics Data System (ADS)

Li, Dongming; Zhang, Lijuan; Wang, Ting; Liu, Huan; Yang, Jinhua; Chen, Guifen

2016-11-01

To improve the adaptive optics (AO) image's quality, we study the AO image restoration algorithm based on wavefront reconstruction technology and adaptive total variation (TV) method in this paper. Firstly, the wavefront reconstruction using Zernike polynomial is used for initial estimated for the point spread function (PSF). Then, we develop our proposed iterative solutions for AO images restoration, addressing the joint deconvolution issue. The image restoration experiments are performed to verify the image restoration effect of our proposed algorithm. The experimental results show that, compared with the RL-IBD algorithm and Wiener-IBD algorithm, we can see that GMG measures (for real AO image) from our algorithm are increased by 36.92%, and 27.44% respectively, and the computation time are decreased by 7.2%, and 3.4% respectively, and its estimation accuracy is significantly improved.

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm

PubMed Central

Xu, Yaofang; Wu, Jiayi; Yin, Chang-Cheng; Mao, Youdong

2016-01-01

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis. PMID:27959895

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm.

PubMed

Xu, Yaofang; Wu, Jiayi; Yin, Chang-Cheng; Mao, Youdong

2016-01-01

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.

Experimental and analytical study of secondary path variations in active engine mounts

NASA Astrophysics Data System (ADS)

Hausberg, Fabian; Scheiblegger, Christian; Pfeffer, Peter; Plöchl, Manfred; Hecker, Simon; Rupp, Markus

2015-03-01

Active engine mounts (AEMs) provide an effective solution to further improve the acoustic and vibrational comfort of passenger cars. Typically, adaptive feedforward control algorithms, e.g., the filtered-x-least-mean-squares (FxLMS) algorithm, are applied to cancel disturbing engine vibrations. These algorithms require an accurate estimate of the AEM active dynamic characteristics, also known as the secondary path, in order to guarantee control performance and stability. This paper focuses on the experimental and theoretical study of secondary path variations in AEMs. The impact of three major influences, namely nonlinearity, change of preload and component temperature, on the AEM active dynamic characteristics is experimentally analyzed. The obtained test results are theoretically investigated with a linear AEM model which incorporates an appropriate description for elastomeric components. A special experimental set-up extends the model validation of the active dynamic characteristics to higher frequencies up to 400 Hz. The theoretical and experimental results show that significant secondary path variations are merely observed in the frequency range of the AEM actuator's resonance frequency. These variations mainly result from the change of the component temperature. As the stability of the algorithm is primarily affected by the actuator's resonance frequency, the findings of this paper facilitate the design of AEMs with simpler adaptive feedforward algorithms. From a practical point of view it may further be concluded that algorithmic countermeasures against instability are only necessary in the frequency range of the AEM actuator's resonance frequency.

Effects of local geology on ground motion in the San Francisco Bay region, California—A continued study

USGS Publications Warehouse

Gibbs, James F.; Borcherdt, Roger D.

1974-01-01

Measurements of ground motion generated by nuclear explosions in Nevada have been completed for 99 locations in the San Francisco Bay region, California. The seismograms, Fourier amplitude spectra, spectral amplification curves for the signal, and the Fourier amplitude spectra of the seismic noise are presented for 60 locations. Analog amplifications, based on the maximum signal amplitude, are computed for an additional 39 locations. The recordings of the nuclear explosions show marked amplitude variations which are consistently related to the local geologic conditions of the recording site. The average spectral amplifications observed for vertical and horizontal ground motions are, respectively: (1, 1) for granite, (1.5, 1.6) for the Franciscan Formation, (2.3, 2.3), for other pre-Tertiary and Tertiary rocks, (3.0, 2.7) for the Santa Clara Formation, (3.3, 4.4) for older bay sediments, and (3.7, 11.3) for younger bay mud. Spectral amplification curves define predominant ground frequencies for younger bay mud sites and for some older bay sediment sites. The predominant frequencies for most sites were not clearly defined by the amplitude spectra computed from the seismic background noise. The intensities ascribed to various sites in the San Francisco Bay region for the California earthquake of April 18, 1906, are strongly dependent on distance from the zone of surface faulting and the geological character of the ground. Considering only those sites (approximately one square city block in size) for which there is good evidence for the degree of ascribed intensity, the intensities for 917 sites on Franciscan rocks generally decrease with the logarithm of distance as Intensity = 2.69 - 1.90 log (Distance Km). For sites on other geologic units, intensity increments, derived from this empirical rela.tion, correlate strongly with the Average Horizontal Spectral Amplifications (MISA) according to the empirical relation Intensity Increment= 0.27 + 2.70 log(AHSA). Average intensity increments predicted for various geologic units are -0.3 for granite, 0.2 for Franciscan Formation, 0.6 for other pre-Tertiary, Tertiary bedrock, 0.8 for Santa Clara Formation, 1 .3 for older bay sediments, 2.4 for younger bay mud. These empirical relations, together with detailed geologic maps, delineate areas in the San Francisco Bay region of potentially high intensity from future earthquakes on either the San Andreas fault or the Hayward fault.

Development of Multistep and Degenerate Variational Integrators for Applications in Plasma Physics

NASA Astrophysics Data System (ADS)

Ellison, Charles Leland

Geometric integrators yield high-fidelity numerical results by retaining conservation laws in the time advance. A particularly powerful class of geometric integrators is symplectic integrators, which are widely used in orbital mechanics and accelerator physics. An important application presently lacking symplectic integrators is the guiding center motion of magnetized particles represented by non-canonical coordinates. Because guiding center trajectories are foundational to many simulations of magnetically confined plasmas, geometric guiding center algorithms have high potential for impact. The motivation is compounded by the need to simulate long-pulse fusion devices, including ITER, and opportunities in high performance computing, including the use of petascale resources and beyond. This dissertation uses a systematic procedure for constructing geometric integrators --- known as variational integration --- to deliver new algorithms for guiding center trajectories and other plasma-relevant dynamical systems. These variational integrators are non-trivial because the Lagrangians of interest are degenerate - the Euler-Lagrange equations are first-order differential equations and the Legendre transform is not invertible. The first contribution of this dissertation is that variational integrators for degenerate Lagrangian systems are typically multistep methods. Multistep methods admit parasitic mode instabilities that can ruin the numerical results. These instabilities motivate the second major contribution: degenerate variational integrators. By replicating the degeneracy of the continuous system, degenerate variational integrators avoid parasitic mode instabilities. The new methods are therefore robust geometric integrators for degenerate Lagrangian systems. These developments in variational integration theory culminate in one-step degenerate variational integrators for non-canonical magnetic field line flow and guiding center dynamics. The guiding center integrator assumes coordinates such that one component of the magnetic field is zero; it is shown how to construct such coordinates for nested magnetic surface configurations. Additionally, collisional drag effects are incorporated in the variational guiding center algorithm for the first time, allowing simulation of energetic particle thermalization. Advantages relative to existing canonical-symplectic and non-geometric algorithms are numerically demonstrated. All algorithms have been implemented as part of a modern, parallel, ODE-solving library, suitable for use in high-performance simulations.

Determining individual variation in growth and its implication for life-history and population processes using the empirical Bayes method.

PubMed

Vincenzi, Simone; Mangel, Marc; Crivelli, Alain J; Munch, Stephan; Skaug, Hans J

2014-09-01

The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and L∞ (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish.

Local and regional scale exchanges of dissolved organic carbon (DOC) between tidal wetlands and their adjacent coastal waters

NASA Astrophysics Data System (ADS)

Osburn, C. L.; Joshi, I.; Lebrasse, M. C.; Oviedo-Vargas, D.; Bianchi, T. S.; Bohnenstiehl, D. R.; D'Sa, E. J.; He, R.; Ko, D.; Arellano, A.; Ward, N. D.

2017-12-01

The contribution of blue carbon from tidal wetlands to the coastal ocean in the form of dissolved organic carbon (DOC) represents a terrestrial-aquatic linkage of increasing importance. DOC flux results will be presented from local (tidal creek) and regional (bays) scale studies in which various combinations of field observations, ocean-color satellite observations, and the outputs of high-resolution hydrodynamic models were used to estimate DOC export. The first project was located in Bald Head Creek, a tributary to the Cape Fear River estuary in eastern North Carolina (NC). DOC fluxes were computed using a bathymetric data collected via unmanned surface vehicle (USV) and a numerical hydrodynamic model (SCHISM) based on the relationships between colored dissolved organic matter (CDOM) absorption, DOC concentration, and salinity taken from field observations. Model predictions estimated an annual net export of DOC at 54 g C m-2 yr-1 from the tidal creek to the adjacent estuary. Carbon stable isotope (δ13C) values were used to estimate the contribution of wetland carbon to this export. In the second project, DOC fluxes from the Apalachicola Bay, FL, Barataria Bay, LA, were based on the development of algorithms between DOC and CDOM absorption derived from the VIIRS ocean color sensor. The Navy Coastal Ocean Model (NCOM) was used to compute salt flux estimates from each bay to the Louisiana-Texas shelf. The relationship between salinity and CDOM was used to estimate net annual DOC exports of 8.35 x 106 g C m-2 y-1 (Apalachicola Bay) and 7.14 x 106 g C m-2 yr-1 (Barataria Bay). These values approximate 13% and 9% of the annual loads of DOC from the Mississippi River to the Gulf of Mexico, respectively. CDOM and lignin were used in a mixing model to estimate wetland-derived DOC were 2% for Apalachicola Bay and 13% for Barataria Bay, the latter having one of the highest rates of relative sea level rise in North America. Results from our project demonstrated the utility of CDOM, amenable to high resolution observations from multiple platforms, as a basis for constraining the heterogeneity of DOC exports from tidal wetlands to estuaries and coastal waters using numerical models at local and regional scales.

Natural and anthropogenic nitrogen uptake by bloom-forming macroalgae.

PubMed

Thornber, Carol S; DiMilla, Peter; Nixon, Scott W; McKinney, Richard A

2008-02-01

The frequency and duration of macroalgal blooms have increased in many coastal waters over the past several decades. We used field surveys and laboratory culturing experiments to examine the nitrogen content and delta(15)N values of Ulva and Gracilaria, two bloom-forming algal genera in Narragansett Bay, RI (USA). The northern end of this bay is densely populated with large sewage treatment plant nitrogen inputs; the southern end is more lightly populated and opens to the Atlantic Ocean. Field-collected Ulva varied in delta(15)N among sites, but with two exceptions had delta(15)N above 10 per thousand, reflecting a significant component of heavy anthropogenic N. This variation was not correlated with a north-south gradient. Both Ulva and Gracilaria cultured in water from across Narragansett Bay also had high signals (delta(15)N= approximately 14-17 per thousand and 8-12 per thousand, respectively). These results indicate that inputs of anthropogenic N can have far-reaching impacts throughout estuaries.

Effects of hypoxia caused by mussel farming on benthic foraminifera in semi-closed Gamak Bay, South Korea.

PubMed

Lee, Yeon Gyu; Jeong, Da Un; Lee, Jung Sick; Choi, Yang Ho; Lee, Moon Ok

2016-08-15

Seawater monitoring and geochemical and benthic foraminiferal analysis of sediments were conducted to identify the effects of hypoxia created by a mussel farm on benthic foraminifera in a semi-closed bay. Extremely polluted reductive conditions with a high content of organic matter (OM) at >12.0% and oxygen minimum zones (OMZs) with dissolved oxygen (DO) <0.4mg∙L(-1) were formed below the mussel farm in the northwest area of Gamak Bay, and gradually diffused toward the south. Highly similar patterns of variation were observed in species diversity, abundance frequency, and benthic foraminiferal assemblage distributed from Elphidium subarcticum-Ammonia beccarii in the northwest area through E. subarcticum-A. beccarii-Trochammina hadai, E. subarcticum-A. beccarii-Elphidiumclavatum, and E. clavatum-Ammonia ketienziensis in the southern area. These phenomena were caused by hydrodynamics in the current water mass. It was thought that E. subarcticum is a bioindicator of organic pollution caused by the mussel farm. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Accidental Tide Gauge: A GPS Reflection Case Study from Kachemak Bay, Alaska

NASA Technical Reports Server (NTRS)

Larson, Kristine M.; Ray, Richard D.; Nievinski, Felipe G..; Freymueller, Jeffrey T.

2013-01-01

For the last decade, it has been known that reflected GPS signals observed with specialized instruments could be used to measure sea level. In this letter, data from an existing geodeticquality GPS site near Kachemak Bay, Alaska, are analyzed for a one-year time period. Daily sea-level variations are more than 7 m. Tidal coefficients have been estimated and compared with coefficients estimated from records from a traditional tide gauge at Seldovia Harbor, approximately 30 km away. The GPS and Seldovia estimates of M(sub 2) and S(sub 2) coefficients agree to better than 2%; much of this residual can be attributed to true differences in the tide over 30 km as it propagates up Kachemak Bay. For daily mean sea levels the agreement is 2.3 cm. Because a standard geodetic GPS receiver/antenna is used, this GPS instrument can measure long-term sea-level changes in a stable terrestrial reference frame.

Spatio-temporal variations in bloom of the red-tide dinoflagellate Karenia mikimotoi in Imari Bay, Japan, in 2014: Factors controlling horizontal and vertical distribution.

PubMed

Aoki, Kazuhiro; Kameda, Takahiko; Yamatogi, Toshifumi; Ishida, Naoya; Hirae, Sou; Kawaguchi, Mayumi; Syutou, Toshio

2017-11-15

A massive bloom of the dinoflagellate Karenia mikimotoi appeared in 2014 in Imari Bay, Japan. Bloom dynamics and hydrographical conditions were examined by field survey. The bloom initially developed in the eastern area of Imari Bay, subsequently after rainfall during the neap tides, cell density exceeded over 10,000cellsml. Vertical distribution of K. mikimotoi was primarily controlled by the light intensity and secondarily by the water quality during the daytime. Almost all cell-density maxima occurred in depths with weak daytime light intensities of <300μmolm -2 s -1 . In some cases of weak light intensity, cell-density maxima occurred in depths with favorable hydrodynamic conditions for the growth. Spatially classified areas were identified by cluster analysis using the growth rate calculated from seawater temperature and salinity. This study quantitatively evaluated the environmental factors of the eastern area, where the bloom initially occurred, during the development of the bloom. Copyright © 2017 Elsevier Ltd. All rights reserved.

Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention.

PubMed

Nguyen, Trang Quynh; Webb-Vargas, Yenny; Koning, Ina M; Stuart, Elizabeth A

We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation of risk-difference- and risk-ratio-based effects (RDs, RRs) using the ML, WLSMV and Bayes estimators in Mplus. Across most variations in path-coefficient and mediator-residual-correlation signs and strengths, and confounding situations investigated, the method performs well with all estimators, but favors ML/WLSMV for RDs with continuous mediators, and Bayes for RRs with ordinal mediators. Bayes outperforms WLSMV/ML regardless of mediator type when estimating RRs with small potential outcome probabilities and in two other special cases. An adolescent alcohol prevention study is used for illustration.

Muon reconstruction in the Daya Bay water pools

DOE PAGES

Hackenburg, R. W.

2017-08-12

Muon reconstruction in the Daya Bay water pools would serve to verify the simulated muon fluxes and offer the possibility of studying cosmic muons in general. This reconstruction is, however, complicated by many optical obstacles and the small coverage of photomultiplier tubes (PMTs) as compared to other large water Cherenkov detectors. The PMTs’ timing information is useful only in the case of direct, unreflected Cherenkov light. This requires PMTs to be added and removed as an hypothesized muon trajectory is iteratively improved, to account for the changing effects of obstacles and direction of light. Therefore, muon reconstruction in the Dayamore » Bay water pools does not lend itself to a general fitting procedure employing smoothly varying functions with continuous derivatives. Here, we describe an algorithm which overcomes these complications. It employs the method of Least Mean Squares to determine an hypothesized trajectory from the PMTs’ charge-weighted positions. This initially hypothesized trajectory is then iteratively refined using the PMTs’ timing information. Reconstructions with simulated data reproduce the simulated trajectory to within about 5° in direction and about 45 cm in position at the pool surface, with a bias that tends to pull tracks away from the vertical by about 3°.« less

Muon reconstruction in the Daya Bay water pools

NASA Astrophysics Data System (ADS)

Hackenburg, R. W.

2017-11-01

Muon reconstruction in the Daya Bay water pools would serve to verify the simulated muon fluxes and offer the possibility of studying cosmic muons in general. This reconstruction is, however, complicated by many optical obstacles and the small coverage of photomultiplier tubes (PMTs) as compared to other large water Cherenkov detectors. The PMTs' timing information is useful only in the case of direct, unreflected Cherenkov light. This requires PMTs to be added and removed as an hypothesized muon trajectory is iteratively improved, to account for the changing effects of obstacles and direction of light. Therefore, muon reconstruction in the Daya Bay water pools does not lend itself to a general fitting procedure employing smoothly varying functions with continuous derivatives. Here, an algorithm is described which overcomes these complications. It employs the method of Least Mean Squares to determine an hypothesized trajectory from the PMTs' charge-weighted positions. This initially hypothesized trajectory is then iteratively refined using the PMTs' timing information. Reconstructions with simulated data reproduce the simulated trajectory to within about 5°in direction and about 45 cm in position at the pool surface, with a bias that tends to pull tracks away from the vertical by about 3°.

Bio-Optical and Remote Sensing Observations in Chesapeake Bay. Chapter 7

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.; Magnuson, Andrea

2003-01-01

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements from Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (> 6,500 km2) make retrievals from satellites with a spatial resolution of approx. 1 km (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra.

The Space Operations Simulation Center (SOSC) and Closed-loop Hardware Testing for Orion Rendezvous System Design

NASA Technical Reports Server (NTRS)

D'Souza, Christopher; Milenkovich, Zoran; Wilson, Zachary; Huich, David; Bendle, John; Kibler, Angela

2011-01-01

The Space Operations Simulation Center (SOSC) at the Lockheed Martin (LM) Waterton Campus in Littleton, Colorado is a dynamic test environment focused on Autonomous Rendezvous and Docking (AR&D) development testing and risk reduction activities. The SOSC supports multiple program pursuits and accommodates testing Guidance, Navigation, and Control (GN&C) algorithms for relative navigation, hardware testing and characterization, as well as software and test process development. The SOSC consists of a high bay (60 meters long by 15.2 meters wide by 15.2 meters tall) with dual six degree-of-freedom (6DOF) motion simulators and a single fixed base 6DOF robot. The large testing area (maximum sensor-to-target effective range of 60 meters) allows for large-scale, flight-like simulations of proximity maneuvers and docking events. The facility also has two apertures for access to external extended-range outdoor target test operations. In addition, the facility contains four Mission Operations Centers (MOCs) with connectivity to dual high bay control rooms and a data/video interface room. The high bay is rated at Class 300,000 (. 0.5 m maximum particles/m3) cleanliness and includes orbital lighting simulation capabilities.

An historical survey of computational methods in optimal control.

NASA Technical Reports Server (NTRS)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

Colour based fire detection method with temporal intensity variation filtration

NASA Astrophysics Data System (ADS)

Trambitckii, K.; Anding, K.; Musalimov, V.; Linß, G.

2015-02-01

Development of video, computing technologies and computer vision gives a possibility of automatic fire detection on video information. Under that project different algorithms was implemented to find more efficient way of fire detection. In that article colour based fire detection algorithm is described. But it is not enough to use only colour information to detect fire properly. The main reason of this is that in the shooting conditions may be a lot of things having colour similar to fire. A temporary intensity variation of pixels is used to separate them from the fire. These variations are averaged over the series of several frames. This algorithm shows robust work and was realised as a computer program by using of the OpenCV library.

Exploitation of intertidal feeding resources by the red knot Calidris canutus under megatidal conditions (Bay of Saint-Brieuc, France)

NASA Astrophysics Data System (ADS)

Sturbois, Anthony; Ponsero, Alain; Desroy, Nicolas; Le Mao, Patrick; Fournier, Jérôme

2015-02-01

The feeding ecology of the red knot has been widely studied across its wintering range. Red knots mainly select bivalves and gastropods, with differences between sites due to variation in prey availability. The shorebird's diet is also influenced or controlled by the tidal regime. The aim of this paper is to demonstrate the adaptation of foraging red knots to the megatidal environment. The variation in their diet during tidal cycles was studied in the bay of Saint-Brieuc, a functional unit for this species. The method used combined macrofauna, distribution of foraging birds and diet data. Comparative spatial analyses of macrofauna and distribution of foraging red knots have shown that the bay's four benthic assemblages are exploited by birds. By analysing droppings, we highlighted that bivalve molluscs are the main component of their diet, as shown in most overwintering sites. Fifteen types of prey were identified and Donax vittatus was discovered to be a significant prey item. The relative proportion of each main prey item differs significantly depending on the benthic assemblage used to forage. All available benthic assemblages and all potential feeding resources can be used during a single tidal cycle, reflecting an adaptation to megatidal conditions. This approach develops accurate knowledge about the feeding ecology of birds which managers need in order to identify optimal areas for the conservation of waders based on the areas and resources actually used by the birds.

Modeling Salinity Exchanges Between the Equatorial Indian Ocean and the Bay of Bengal

DTIC Science & Technology

2016-06-01

Technology, has produced a model salinity climatology using daily atmosphere and surface flux climatology as forcing. Here, we present the results...surface, the model was forced by the daily climatology of atmo- spheric variables obtained from vari- ous sources. We used daily QuikSCAT and...2012). Precipitation data were obtained from the Global Precipitation Climatology Project (GPCP). Using the bulk flux algorithm by Fairall et al

Expert system constant false alarm rate processor

NASA Astrophysics Data System (ADS)

Baldygo, William J., Jr.; Wicks, Michael C.

1993-10-01

The requirements for high detection probability and low false alarm probability in modern wide area surveillance radars are rarely met due to spatial variations in clutter characteristics. Many filtering and CFAR detection algorithms have been developed to effectively deal with these variations; however, any single algorithm is likely to exhibit excessive false alarms and intolerably low detection probabilities in a dynamically changing environment. A great deal of research has led to advances in the state of the art in Artificial Intelligence (AI) and numerous areas have been identified for application to radar signal processing. The approach suggested here, discussed in a patent application submitted by the authors, is to intelligently select the filtering and CFAR detection algorithms being executed at any given time, based upon the observed characteristics of the interference environment. This approach requires sensing the environment, employing the most suitable algorithms, and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.