Resistance Against Basil Downy Mildew in Ocimum Species.

PubMed

Ben-Naim, Yariv; Falach, Lidan; Cohen, Yigal

2015-06-01

Downy mildew, caused by the oomycete Peronospora belbahrii, is a devastating disease of sweet basil. In this study, 113 accessions of Ocimum species (83 Plant Introduction entries and 30 commercial entries) were tested for resistance against downy mildew at the seedling stage in growth chambers, and during three seasons, in the field. Most entries belonging to O. basilicum were highly susceptible whereas most entries belonging to O. americanum, O. kilimanadascharicum, O. gratissimum, O. campechianum, or O. tenuiflorum were highly resistant at both the seedling stage and the field. Twenty-seven highly resistant individual plants were each crossed with the susceptible sweet basil 'Peri', and the F1 progeny plants were examined for disease resistance. The F1 plants of two crosses were highly resistant, F1 plants of 24 crosses were moderately resistant, and F1 plants of one cross were susceptible, suggesting full, partial, or no dominance of the resistance gene(s), respectively. These data confirm the feasibility of producing downy mildew-resistant cultivars of sweet basil by crossing with wild Ocimum species.

Basil Downy Mildew (Peronospora belbahrii): Discoveries and Challenges Relative to Its Control.

PubMed

Wyenandt, Christian A; Simon, James E; Pyne, Robert M; Homa, Kathryn; McGrath, Margaret T; Zhang, Shouan; Raid, Richard N; Ma, Li-Jun; Wick, Robert; Guo, Li; Madeiras, Angela

2015-07-01

Basil (Ocimum spp.) is one of the most economically important and widely grown herbs in the world. Basil downy mildew, caused by Peronospora belbahrii, has become an important disease in sweet basil (O. basilicum) production worldwide in the past decade. Global sweet basil production is at significant risk to basil downy mildew because of the lack of genetic resistance and the ability of the pathogen to be distributed on infested seed. Controlling the disease is challenging and consequently many crops have been lost. In the past few years, plant breeding efforts have been made to identify germplasm that can be used to introduce downy mildew resistance genes into commercial sweet basils while ensuring that resistant plants have the correct phenotype, aroma, and tastes needed for market acceptability. Fungicide efficacy studies have been conducted to evaluate current and newly developed conventional and organic fungicides for its management with limited success. This review explores the current efforts and progress being made in understanding basil downy mildew and its control.

Distributional changes and range predictions of downy brome (Bromus tectorum) in Rocky Mountain National Park

USGS Publications Warehouse

Bromberg, J.E.; Kumar, S.; Brown, C.S.; Stohlgren, T.J.

2011-01-01

Downy brome (Bromus tectorum L.), an invasive winter annual grass, may be increasing in extent and abundance at high elevations in the western United States. This would pose a great threat to high-elevation plant communities and resources. However, data to track this species in high-elevation environments are limited. To address changes in the distribution and abundance of downy brome and the factors most associated with its occurrence, we used field sampling and statistical methods, and niche modeling. In 2007, we resampled plots from two vegetation surveys in Rocky Mountain National Park for presence and cover of downy brome. One survey was established in 1993 and had been resampled in 1999. The other survey was established in 1996 and had not been resampled until our study. Although not all comparisons between years demonstrated significant changes in downy brome abundance, its mean cover increased nearly fivefold from 1993 (0.7%) to 2007 (3.6%) in one of the two vegetation surveys (P = 0.06). Although the average cover of downy brome within the second survey appeared to be increasing from 1996 to 2007, this slight change from 0.5% to 1.2% was not statistically significant (P = 0.24). Downy brome was present in 50% more plots in 1999 than in 1993 (P = 0.02) in the first survey. In the second survey, downy brome was present in 30% more plots in 2007 than in 1996 (P = 0.08). Maxent, a species-environmental matching model, was generally able to predict occurrences of downy brome, as new locations were in the ranges predicted by earlier generated models. The model found that distance to roads, elevation, and vegetation community influenced the predictions most. The strong response of downy brome to interannual environmental variability makes detecting change challenging, especially with small sample sizes. However, our results suggest that the area in which downy brome occurs is likely increasing in Rocky Mountain National Park through increased frequency and cover

Season-long dynamics of spinach downy mildew determined by spore trapping and disease

USDA-ARS?s Scientific Manuscript database

Peronospora effusa is an obligate oomycete pathogen, and the cause of downy mildew of spinach. Downy mildew threatens sustainable production of fresh market organic spinach in California, and routine fungicide sprays are often necessary for conventional production. In this study, airborne P. effus...

Measurements of morphology and refractive indexes on human downy hairs using three-dimensional quantitative phase imaging.

PubMed

Lee, SangYun; Kim, Kyoohyun; Lee, Yuhyun; Park, Sungjin; Shin, Heejae; Yang, Jongwon; Ko, Kwanhong; Park, HyunJoo; Park, YongKeun

2015-01-01

We present optical measurements of morphology and refractive indexes (RIs) of human downy arm hairs using three-dimensional (3-D) quantitative phase imaging techniques. 3-D RI tomograms and high-resolution two-dimensional synthetic aperture images of individual downy arm hairs were measured using a Mach–Zehnder laser interferometric microscopy equipped with a two-axis galvanometer mirror. From the measured quantitative images, the RIs and morphological parameters of downy hairs were noninvasively quantified including the mean RI, volume, cylinder, and effective radius of individual hairs. In addition, the effects of hydrogen peroxide on individual downy hairs were investigated.

Downy Brome: evidence for soil engineering

USDA-ARS?s Scientific Manuscript database

Bromus tectorum L. (downy brome, cheatgrass) is an invasive Eurasian grass largely responsible for landscape level conversion of sagebrush/bunchgrass communities to annual grass dominance. We tested the hypothesis that B. tectorum alters or “engineers” the soil to favor its growth. The hypothesis wa...

Identification of QTLs conferring resistance to downy mildew in legacy cultivars of lettuce

USDA-ARS?s Scientific Manuscript database

Many cultivars of lettuce (Lactuca sativa L.), the most popular leafy vegetable, are susceptible to downy mildew disease caused by Bremia lactucae. Cultivars Iceberg and Grand Rapids that were released in 18th and 19th century, respectively, have high levels of quantitative resistance to downy milde...

Genome analyses of the sunflower pathogen Plasmopara halstedii provide insights into effector evolution in downy mildews and Phytophthora.

PubMed

Sharma, Rahul; Xia, Xiaojuan; Cano, Liliana M; Evangelisti, Edouard; Kemen, Eric; Judelson, Howard; Oome, Stan; Sambles, Christine; van den Hoogen, D Johan; Kitner, Miloslav; Klein, Joël; Meijer, Harold J G; Spring, Otmar; Win, Joe; Zipper, Reinhard; Bode, Helge B; Govers, Francine; Kamoun, Sophien; Schornack, Sebastian; Studholme, David J; Van den Ackerveken, Guido; Thines, Marco

2015-10-05

Downy mildews are the most speciose group of oomycetes and affect crops of great economic importance. So far, there is only a single deeply-sequenced downy mildew genome available, from Hyaloperonospora arabidopsidis. Further genomic resources for downy mildews are required to study their evolution, including pathogenicity effector proteins, such as RxLR effectors. Plasmopara halstedii is a devastating pathogen of sunflower and a potential pathosystem model to study downy mildews, as several Avr-genes and R-genes have been predicted and unlike Arabidopsis downy mildew, large quantities of almost contamination-free material can be obtained easily. Here a high-quality draft genome of Plasmopara halstedii is reported and analysed with respect to various aspects, including genome organisation, secondary metabolism, effector proteins and comparative genomics with other sequenced oomycetes. Interestingly, the present analyses revealed further variation of the RxLR motif, suggesting an important role of the conservation of the dEER-motif. Orthology analyses revealed the conservation of 28 RxLR-like core effectors among Phytophthora species. Only six putative RxLR-like effectors were shared by the two sequenced downy mildews, highlighting the fast and largely independent evolution of two of the three major downy mildew lineages. This is seemingly supported by phylogenomic results, in which downy mildews did not appear to be monophyletic. The genome resource will be useful for developing markers for monitoring the pathogen population and might provide the basis for new approaches to fight Phytophthora and downy mildew pathogens by targeting core pathogenicity effectors.

Effects of soil amendments on germination and emergence of downy brome (Bromus tectorum) and Hilaria jamesii

USGS Publications Warehouse

Belnap, J.; Sherrod, S.K.; Miller, M.E.

2003-01-01

Downy brome is an introduced Mediterranean annual grass that now dominates millions of hectares of western U.S. rangelands. The presence of this grass has eliminated many native species and accelerated wildfire cycles. The objective of this study was to identify soil additives that allowed germination but inhibited emergence of downy brome, while not affecting germination or emergence of the native perennial grass Hilaria jamesii. On the basis of data from previous studies, we focused on additives that altered the availability of soil nitrogen (N), phosphorus (P), and potassium (K). Most water-soluble treatments inhibited downy brome germination and emergence. We attribute the inhibitory effects of these treatments to excessive salinity and ion-specific effects of the additives themselves. An exception to this was oxalic acid, which showed no effect. Most water-insoluble treatments had no effect in soils with high P but did have an effect in soils with low P. Zeolite was effective regardless of P level, probably due to the high amounts of Na+ it added to the soil solution. Most treatments at higher concentrations resulted in lower downy brome emergence rates in soils currently dominated by downy brome than in uninvaded (but theoretically invadable) Hilaria soils. This difference is possibly attributable to inherent differences in labile soil P. In Stipa soils, where Stipa spp. grow, but which are generally considered to be uninvadable by downy brome, additions of high amounts of N resulted in lower emergence. This may have been an effect of NH4 + interference with uptake of K or other cations or toxicity of high N. We also saw a positive relationship between downy brome emergence and pH in Stipa soils. Hilaria development parameters were not as susceptible to the treatments, regardless of concentration, as downy brome. Our results suggest that there are additions that may be effective management tools for inhibiting downy brome in calcareous soils, including (1

allantools: Allan deviation calculation

NASA Astrophysics Data System (ADS)

Wallin, Anders E. E.; Price, Danny C.; Carson, Cantwell G.; Meynadier, Frédéric

2018-04-01

allantools calculates Allan deviation and related time & frequency statistics. The library is written in Python and has a GPL v3+ license. It takes input data that is either evenly spaced observations of either fractional frequency, or phase in seconds. Deviations are calculated for given tau values in seconds. Several noise generators for creating synthetic datasets are also included.

Rehabilitating downy brome (Bromus tectorum)-invaded scrublands using imazapic and seeding with native shrubs

Treesearch

Suzanne M. Owen; Carolyn Hull Sieg; Catherine A. Gehring

2011-01-01

Rehabilitation of downy brome-infested shrublands is challenging once this invasive grass dominates native communities. The effectiveness of imazapic herbicide in reducing downy brome cover has been variable, and there is uncertainty about the impacts of imazapic on native species. We used a before-after-control-impact (BACI) field experiment and greenhouse studies to...

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

Genetics of resistance against lettuce downy mildew

USDA-ARS?s Scientific Manuscript database

Lettuce (Lactuca sativa) is one of the most valuable vegetable crops in the U.S. Downy mildew (DM), caused by Bremia lactucae, is the most important foliar disease of lettuce worldwide, which decreases the quality of the marketable portion of the crop. The use of resistant varieties carrying dominan...

Real-time PCR and spore trap-based detection of the downy mildew pathogen, Peronospora effusa

USDA-ARS?s Scientific Manuscript database

Peronospora effusa is an obligate pathogen and the causal agent of downy mildew on spinach. The pathogen can be dispersed by splashing rain and wind, and may overwinter as oospores. Outbreaks of downy mildew on spinach are common in the cool climate of central coastal California, including the Sal...

Chemical control of downy mildew on lettuce and basil under greenhouse.

PubMed

Gullino, M L; Gilardi, G; Garibaldi, A

2009-01-01

Eight experimental trials were carried out during 2007 and 2008 to evaluate the efficacy of different fungicides against downy mildew of lettuce (Bremia lactucae) and basil (Peronospora belbahrii) under greenhouse conditions, at temperatures ranging from 19 to 24 degrees C. The mixture fluopicolide (fungicide belonging to the + propamocarb hydrochloride (fungicide belonging to the new chemical class of acyl-picolides) was compared with metalaxyl m + copper, zoxamide + mancozeb, iprovalicarb + Cu, fenamidone + fosetyl-Al and azoxystrobin. Two treatments were carried out at 8-12 day interval on lettuce and basil. The artificial inoculation of B. lactucae on lettuce (cv Cobham Green) and P. belbahrii. on basil (cv Genovese gigante) was carried out by using 1 x 10(5) CFU/ml 24 h after the first treatment. In the presence of a medium-high disease severity, all fungicides tested in these trials were effective against downy mildew on lettuce and basil as the other fungicides already available. The importance of the availability of a number of different chemicals to control downy mildews is discussed.

Single and multiple phenotype QTL analyses of downy mildew resistance in interspecific grapevines.

PubMed

Divilov, Konstantin; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

2018-05-01

Downy mildew resistance across days post-inoculation, experiments, and years in two interspecific grapevine F 1 families was investigated using linear mixed models and Bayesian networks, and five new QTL were identified. Breeding grapevines for downy mildew disease resistance has traditionally relied on qualitative gene resistance, which can be overcome by pathogen evolution. Analyzing two interspecific F 1 families, both having ancestry derived from Vitis vinifera and wild North American Vitis species, across 2 years and multiple experiments, we found multiple loci associated with downy mildew sporulation and hypersensitive response in both families using a single phenotype model. The loci explained between 7 and 17% of the variance for either phenotype, suggesting a complex genetic architecture for these traits in the two families studied. For two loci, we used RNA-Seq to detect differentially transcribed genes and found that the candidate genes at these loci were likely not NBS-LRR genes. Additionally, using a multiple phenotype Bayesian network analysis, we found effects between the leaf trichome density, hypersensitive response, and sporulation phenotypes. Moderate-high heritabilities were found for all three phenotypes, suggesting that selection for downy mildew resistance is an achievable goal by breeding for either physical- or non-physical-based resistance mechanisms, with the combination of the two possibly providing durable resistance.

Allan Bloom, America, and Education.

ERIC Educational Resources Information Center

West, Thomas

2000-01-01

Refutes the claims of Allan Bloom that the source of the problem with today's universities is modern philosophy, that the writings and ideas of Hobbes and Locke planted the seeds of relativism in American culture, and that the cure is Great Books education. Suggests instead that America's founding principles are the only solution to the failure of…

The inclusion of downy mildews in a multi-locus-dataset and its reanalysis reveals a high degree of paraphyly in Phytophthora.

PubMed

Runge, Fabian; Telle, Sabine; Ploch, Sebastian; Savory, Elizabeth; Day, Brad; Sharma, Rahul; Thines, Marco

2011-12-01

Pathogens belonging to the Oomycota, a group of heterokont, fungal-like organisms, are amongst the most notorious pathogens in agriculture. In particular, the obligate biotrophic downy mildews and the hemibiotrophic members of the genus Phytophthora are responsible for a huge variety of destructive diseases, including sudden oak death caused by P. ramorum, potato late blight caused by P. infestans, cucurbit downy mildew caused by Pseudoperonospora cubensis, and grape downy mildew caused by Plasmopara viticola. About 800 species of downy mildews and roughly 100 species of Phytophthora are currently accepted, and recent studies have revealed that these groups are closely related. However, the degree to which Phytophthora is paraphyletic and where exactly the downy mildews insert into this genus in relation to other clades could not be inferred with certainty to date. Here we present a molecular phylogeny encompassing all clades of Phytophthora as represented in a multi-locus dataset and two representatives of the monophyletic downy mildews from divergent genera. Our results demonstrate that Phytophthora is at least six times paraphyletic with respect to the downy mildews. The downy mildew representatives are consistently nested within clade 4 (contains Phytophthora palmivora), which is placed sister to clade 1 (contains Phytophthora infestans). This finding would either necessitate placing all downy mildews and Phytopthora species in a single genus, either under the oldest generic name Peronospora or by conservation the later name Phytophthora, or the description of at least six new genera within Phytophthora. The complications of both options are discussed, and it is concluded that the latter is preferable, as it warrants fewer name changes and is more practical.

Genetic architecture of downy mildew resistance in cucumber

USDA-ARS?s Scientific Manuscript database

Downy mildew (DM) caused by the obligate oomycete Pseudoperonospora cubensis is the most devastating fungal disease to cucumber production. The molecular mechanism of DM resistance in cucumber is not well understood. We conducted QTL mapping for DM resistances in four cucumber lines including WI7120...

Edgar Allan Poe and neurology.

PubMed

Teive, Hélio Afonso Ghizoni; Paola, Luciano de; Munhoz, Renato Puppi

2014-06-01

Edgar Allan Poe was one of the most celebrated writers of all time. He published several masterpieces, some of which include references to neurological diseases. Poe suffered from recurrent depression, suggesting a bipolar disorder, as well as alcohol and drug abuse, which in fact led to his death from complications related to alcoholism. Various hypotheses were put forward, including Wernicke's encephalopathy.

Daytime Solar Heating Controls Downy Mildew Peronospora belbahrii in Sweet Basil

PubMed Central

Cohen, Yigal; Rubin, Avia E.

2015-01-01

The biotrophic oomycete Peronospora belbahrii causes a devastating downy mildew disease in sweet basil. Due to the lack of resistant cultivars current control measures rely heavily on fungicides. However, resistance to fungicides and strict regulation on their deployment greatly restrict their use. Here we report on a ‘green’ method to control this disease. Growth chamber studies showed that P. belbahrii could hardly withstand exposure to high temperatures; exposure of spores, infected leaves, or infected plants to 35-45°C for 6-9 hours suppressed its survival. Therefore, daytime solar heating was employed in the field to control the downy mildew disease it causes in basil. Covering growth houses of sweet basil already infected with downy mildew with transparent infra-red-impermeable, transparent polyethylene sheets raised the daily maximal temperature during sunny hours by 11-22°C reaching 40-58°C (greenhouse effect). Such coverage, applied for a few hours during 1-3 consecutive days, had a detrimental effect on the survival of P. belbahrii: killing the pathogen and/or suppressing disease progress while enhancing growth of the host basil plants. PMID:25992649

Allan Deviation Plot as a Tool for Quartz-Enhanced Photoacoustic Sensors Noise Analysis.

PubMed

Giglio, Marilena; Patimisco, Pietro; Sampaolo, Angelo; Scamarcio, Gaetano; Tittel, Frank K; Spagnolo, Vincenzo

2016-04-01

We report here on the use of the Allan deviation plot to analyze the long-term stability of a quartz-enhanced photoacoustic (QEPAS) gas sensor. The Allan plot provides information about the optimum averaging time for the QEPAS signal and allows the prediction of its ultimate detection limit. The Allan deviation can also be used to determine the main sources of noise coming from the individual components of the sensor. Quartz tuning fork thermal noise dominates for integration times up to 275 s, whereas at longer averaging times, the main contribution to the sensor noise originates from laser power instabilities.

Pragmatics: The State of the Art: An Online Interview with Keith Allan

ERIC Educational Resources Information Center

Allan, Keith; Salmani Nodoushan, Mohammad Ali

2015-01-01

This interview was conducted with Professor Keith Allan with the aim of providing a brief but informative summary of the state of the art of pragmatics. In providing answers to the interview questions, Professor Allan begins with a definition of pragmatics as it is practiced today, i.e., the study of the meanings of utterances with attention to…

Association of RGA-SSCP markers with resistance to downy mildew and anthracnose in grapevines.

PubMed

Tantasawat, P A; Poolsawat, O; Prajongjai, T; Chaowiset, W; Tharapreuksapong, A

2012-07-02

Downy mildew (Plasmopara viticola) and anthracnose (Sphaceloma ampelinum) are two major diseases that severely affect most grapevine (Vitis vinifera) cultivars grown commercially in Thailand. Progress of conventional breeding programs of grapevine for improved resistance to these diseases can be speeded up by selection of molecular markers associated with resistance traits. We evaluated the association between 13 resistance gene analog (RGA)-single-strand conformation polymorphism (SSCP) markers with resistance to downy mildew and anthracnose in 71 segregating progenies of seven cross combinations between susceptible cultivars and resistant lines. F(1) hybrids from each cross were assessed for resistance to downy mildew and anthracnose (isolates Nk4-1 and Rc2-1) under laboratory conditions. Association of resistance traits with RGA-SSCP markers was evaluated using simple linear regression analysis. Three RGA-SSCP markers were found to be significantly correlated with anthracnose resistance, whereas significant correlation with downy mildew resistance was observed for only one RGA-SSCP marker. These results demonstrate the usefulness of RGA-SSCP markers. Four candidate markers with significant associations to resistance to these two major diseases of grapevine were identified. However, these putative associations between markers and resistance need to be verified with larger segregating populations before they can be used for marker-assisted selection.

The Downy Mildews: so many genomes, so little time

USDA-ARS?s Scientific Manuscript database

Downy mildews (DMs) are obligate biotrophic oomycete pathogens that cause diseases on a wide range of plant species. Individual species exhibit a high degree of host specialization. We have utilized next generation sequencing to efficiently generate de novo genome assemblies of multiple geographica...

Allan deviation computations of a linear frequency synthesizer system using frequency domain techniques

NASA Technical Reports Server (NTRS)

Wu, Andy

1995-01-01

Allan Deviation computations of linear frequency synthesizer systems have been reported previously using real-time simulations. Even though it takes less time compared with the actual measurement, it is still very time consuming to compute the Allan Deviation for long sample times with the desired confidence level. Also noises, such as flicker phase noise and flicker frequency noise, can not be simulated precisely. The use of frequency domain techniques can overcome these drawbacks. In this paper the system error model of a fictitious linear frequency synthesizer is developed and its performance using a Cesium (Cs) atomic frequency standard (AFS) as a reference is evaluated using frequency domain techniques. For a linear timing system, the power spectral density at the system output can be computed with known system transfer functions and known power spectral densities from the input noise sources. The resulting power spectral density can then be used to compute the Allan Variance at the system output. Sensitivities of the Allan Variance at the system output to each of its independent input noises are obtained, and they are valuable for design trade-off and trouble-shooting.

Spatial analysis of lettuce downy mildew using geostatistics and geographic information systems.

PubMed

Wu, B M; van Bruggen, A H; Subbarao, K V; Pennings, G G

2001-02-01

ABSTRACT The epidemiology of lettuce downy mildew has been investigated extensively in coastal California. However, the spatial patterns of the disease and the distance that Bremia lactucae spores can be transported have not been determined. During 1995 to 1998, we conducted several field- and valley-scale surveys to determine spatial patterns of this disease in the Salinas valley. Geostatistical analyses of the survey data at both scales showed that the influence range of downy mildew incidence at one location on incidence at other locations was between 80 and 3,000 m. A linear relationship was detected between semivariance and lag distance at the field scale, although no single statistical model could fit the semi-variograms at the valley scale. Spatial interpolation by the inverse distance weighting method with a power of 2 resulted in plausible estimates of incidence throughout the valley. Cluster analysis in geographic information systems on the interpolated disease incidence from different dates demonstrated that the Salinas valley could be divided into two areas, north and south of Salinas City, with high and low disease pressure, respectively. Seasonal and spatial trends along the valley suggested that the distinction between the downy mildew conducive and nonconducive areas might be determined by environmental factors.

How do obligate parasites evolve? A multi-gene phylogenetic analysis of downy mildews.

PubMed

Göker, Markus; Voglmayr, Hermann; Riethmüller, Alexandra; Oberwinkler, Franz

2007-02-01

Plant parasitism has independently evolved as a nutrition strategy in both true fungi and Oomycetes (stramenopiles). A large number of species within phytopathogenic Oomycetes, the so-called downy mildews, are defined as obligate biotrophs since they have not, to date, been cultured on any artificial medium. Other genera like Phytophthora and Pythium can in general be cultured on standard or non-standard agar media. Within all three groups there are many important plant pathogens responsible for severe economic losses as well as damage to natural ecosystems. Although they are important model systems to elucidate the evolution of obligate parasites, the phylogenetic relationships between these genera have not been clearly resolved. Based on the most comprehensive sampling of downy mildew genera to date and a representative sample of Phytophthora subgroups, we inferred the phylogenetic relationships from a multi-gene dataset containing both coding and non-coding nuclear and mitochondrial loci. Phylogenetic analyses were conducted under several optimality criteria and the results were largely consistent between all the methods applied. Strong support is achieved for monophyly of a clade comprising both the genus Phytophthora and the obligate biotrophic species. The facultatively parasitic genus Phytophthora is shown to be at least partly paraphyletic. Monophyly of a cluster nested within Phytophthora containing all obligate parasites is strongly supported. Within the obligate biotrophic downy mildews, four morphologically or ecologically well-defined subgroups receive statistical support: (1) A cluster containing all species with brownish-violet conidiosporangia, i.e., the genera Peronospora and Pseudoperonospora; (2) a clade comprising the genera with vesicular to pyriform haustoria (Basidiophora, Benua, Bremia, Paraperonospora, Plasmopara, Plasmoverna, Protobremia); (3) a group containing species included in Hyaloperonospora and Perofascia which almost exclusively

Epidemiology and population biology of Pseudoperonospora cubensis: a model system for management of downy mildews.

PubMed

Ojiambo, Peter S; Gent, David H; Quesada-Ocampo, Lina M; Hausbeck, Mary K; Holmes, Gerald J

2015-01-01

The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of outbreaks of cucurbit downy mildew. The dispersal potential of Pseudoperonospora cubensis appears to be limited primarily by sporangia production in source fields and availability of susceptible hosts and less by sporangia survival during transport. Uncertainty remains regarding the role of locally produced inoculum in disease outbreaks, but evidence suggests multiple sources of primary inoculum could be important. Understanding pathogen diversity and population differentiation is a critical aspect of disease management and an active research area. Underpinning advances in our understanding of pathogen biology and disease management has been the research capacity and coordination of stakeholders, scientists, and extension personnel. Concepts and approaches developed in this pathosystem can guide future efforts when responding to incursions of new or reemerging downy mildew pathogens.

Spatiotemporal patterns in the airborne dispersal of spinach downy mildew

USDA-ARS?s Scientific Manuscript database

Downy mildew, caused by the biotrophic oomycete pathogen, Peronospora effusa, is the most devastating disease of spinach that threatens sustainable production. The disease results in yellow lesions that render leaves unmarketable as the high value fresh produce. In this study, the levels of D...

Genetic variation of the pathogen causing impatiens downy mildew pre-dating and including 21st century epidemics on Impatiens walleriana

USDA-ARS?s Scientific Manuscript database

Impatiens downy mildew (IDM) disease on cultivated Impatiens walleriana has had a significant economic impact on the ornamental horticulture industry in the U.S. and globally. Although recent IDM outbreaks started in 2004, downy mildews on non-cultivated Impatiens species have been documented since ...

The effects of downy brome invasion on mule deer habitat

USDA-ARS?s Scientific Manuscript database

Downy brome (Bromus tectorum), also widely known as cheatgrass, is a highly invasive exotic weed that has spread over millions of hectares of rangelands throughout the Intermountain West. Native to Eurasia, this early maturing annual provides a fine textured fuel that increases the chance, rate, sea...

Measurements of Ultra-Stable Oscillator (USO) Allan Deviations in Space

NASA Technical Reports Server (NTRS)

Enzer, Daphna G.; Klipstein, William M.; Wang, Rabi T.; Dunn, Charles E.

2013-01-01

Researchers have used data from the GRAIL mission to the Moon to make the first in-flight verification of ultra-stable oscillators (USOs) with Allan deviation below 10 13 for 1-to-100-second averaging times. USOs are flown in space to provide stable timing and/or navigation signals for a variety of different science and programmatic missions. The Gravity Recovery and Interior Laboratory (GRAIL) mission is flying twin spacecraft, each with its own USO and with a Ka-band crosslink used to measure range fluctuations. Data from this crosslink can be combined in such a way as to give the relative time offsets of the two spacecrafts USOs and to calculate the Allan deviation to describe the USOs combined performance while orbiting the Moon. Researchers find the first direct in-space Allan deviations below 10(exp -13) for 1-to-100-second averaging times comparable to pre-launch data, and better than measurements from ground tracking of an X-band carrier coherent with the USO. Fluctuations in Earth s atmosphere limit measurement performance in direct-to-Earth links. Inflight USO performance verification was also performed for GRAIL s parent mission, the Gravity Recovery and Climate Experiment (GRACE), using both Kband and Ka-band crosslinks.

The Cosmology of Edgar Allan Poe

NASA Astrophysics Data System (ADS)

Cappi, Alberto

2011-06-01

Eureka is a ``prose poem'' published in 1848, where Edgar Allan Poe presents his original cosmology. While starting from metaphysical assumptions, Poe develops an evolving Newtonian model of the Universe which has many and non casual analogies with modern cosmology. Poe was well informed about astronomical and physical discoveries, and he was influenced by both contemporary science and ancient ideas. For these reasons, Eureka is a unique synthesis of metaphysics, art and science.

Overexpression of a thaumatin-like protein gene from Vitis amurensis improves downy mildew resistance in Vitis vinifera grapevine.

PubMed

He, Rongrong; Wu, Jiao; Zhang, Yali; Agüero, Cecilia B; Li, Xinlong; Liu, Shaoli; Wang, Chaoxia; Walker, M Andrew; Lu, Jiang

2017-07-01

Downy mildew is a highly destructive disease in grapevine production. A gene encoding pathogenesis-related (PR) thaumatin-like protein was isolated from the downy mildew-resistant grapevine "Zuoshan-1," a clonal selection from wild Vitis amurensis Rupr. The predicted thaumatin-like protein (VaTLP) has 225 amino acids and it is acidic, with a calculated isoelectric point of 4.8. The full length of the VaTLP gene was transformed into somatic embryogenic calli of V. vinifera 'Thompson Seedless' via Agrobacterium tumefaciens. Real-time RT-PCR confirmed that the VaTLP gene was expressed at a high level in the transgenic grapevines. Improved resistance of the transgenic lines against downy mildew was evaluated using leaf disks and whole plants inoculated with Plasmopara viticola, the pathogen causing grapevine downy mildew disease. Bioassay of the pathogen showed that both hyphae growth and asexual reproduction were inhibited significantly among the transgenic plants. Histological analysis also confirmed this disease resistance by demonstrating the inhibition and malformation of hyphae development in leaf tissue of the transgenic plants. These results indicated that the accumulation of VaTLP could enhance resistance to P. viticola in transgenic 'Thompson Seedless' grapevines.

Evaluation of fungicides for hop downy mildew, Hubbard, Oregon, 2016

USDA-ARS?s Scientific Manuscript database

This research was conducted to quantify the degree of control of the disease with a phosphorous acid-based fungicide, the present industry-standard for management of downy mildew on hop in the Pacific Northwestern U.S. No suppression of the disease was observed with the industry standard fungicide,...

Allan Variance Computed in Space Domain: Definition and Application to InSAR Data to Characterize Noise and Geophysical Signal.

PubMed

Cavalié, Olivier; Vernotte, François

2016-04-01

The Allan variance was introduced 50 years ago for analyzing the stability of frequency standards. In addition to its metrological interest, it may be also considered as an estimator of the large trends of the power spectral density (PSD) of frequency deviation. For instance, the Allan variance is able to discriminate different types of noise characterized by different power laws in the PSD. The Allan variance was also used in other fields than time and frequency metrology: for more than 20 years, it has been used in accelerometry, geophysics, geodesy, astrophysics, and even finances. However, it seems that up to now, it has been exclusively applied for time series analysis. We propose here to use the Allan variance on spatial data. Interferometric synthetic aperture radar (InSAR) is used in geophysics to image ground displacements in space [over the synthetic aperture radar (SAR) image spatial coverage] and in time thanks to the regular SAR image acquisitions by dedicated satellites. The main limitation of the technique is the atmospheric disturbances that affect the radar signal while traveling from the sensor to the ground and back. In this paper, we propose to use the Allan variance for analyzing spatial data from InSAR measurements. The Allan variance was computed in XY mode as well as in radial mode for detecting different types of behavior for different space-scales, in the same way as the different types of noise versus the integration time in the classical time and frequency application. We found that radial Allan variance is the more appropriate way to have an estimator insensitive to the spatial axis and we applied it on SAR data acquired over eastern Turkey for the period 2003-2011. Spatial Allan variance allowed us to well characterize noise features, classically found in InSAR such as phase decorrelation producing white noise or atmospheric delays, behaving like a random walk signal. We finally applied the spatial Allan variance to an InSAR time

32. SCIENTISTS ALLAN COX (SEATED), RICHARD DOELL, AND BRENT DALRYMPLE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

32. SCIENTISTS ALLAN COX (SEATED), RICHARD DOELL, AND BRENT DALRYMPLE AT CONTROL PANEL, ABOUT 1965. - U.S. Geological Survey, Rock Magnetics Laboratory, 345 Middlefield Road, Menlo Park, San Mateo County, CA

Downy mildew: a serious disease threat to rose health worldwide

USDA-ARS?s Scientific Manuscript database

Peronospora sparsa is a downy mildew-causing oomycete that can infect roses, blackberries and other members of the rose family. During the last 20 years, this disease has become a serious problem for rose growers in the U.S. and worldwide. While much is known about the disease and its treatment, inc...

Simple sequence repeat markers useful for sorghum downy mildew (Peronosclerospora sorghi) and related species

PubMed Central

Perumal, Ramasamy; Nimmakayala, Padmavathi; Erattaimuthu, Saradha R; No, Eun-Gyu; Reddy, Umesh K; Prom, Louis K; Odvody, Gary N; Luster, Douglas G; Magill, Clint W

2008-01-01

Background A recent outbreak of sorghum downy mildew in Texas has led to the discovery of both metalaxyl resistance and a new pathotype in the causal organism, Peronosclerospora sorghi. These observations and the difficulty in resolving among phylogenetically related downy mildew pathogens dramatically point out the need for simply scored markers in order to differentiate among isolates and species, and to study the population structure within these obligate oomycetes. Here we present the initial results from the use of a biotin capture method to discover, clone and develop PCR primers that permit the use of simple sequence repeats (microsatellites) to detect differences at the DNA level. Results Among the 55 primers pairs designed from clones from pathotype 3 of P. sorghi, 36 flanked microsatellite loci containing simple repeats, including 28 (55%) with dinucleotide repeats and 6 (11%) with trinucleotide repeats. A total of 22 microsatellites with CA/AC or GT/TG repeats were the most abundant (40%) and GA/AG or CT/TC types contribute 15% in our collection. When used to amplify DNA from 19 isolates from P. sorghi, as well as from 5 related species that cause downy mildew on other hosts, the number of different bands detected for each SSR primer pair using a LI-COR- DNA Analyzer ranged from two to eight. Successful cross-amplification for 12 primer pairs studied in detail using DNA from downy mildews that attack maize (P. maydis & P. philippinensis), sugar cane (P. sacchari), pearl millet (Sclerospora graminicola) and rose (Peronospora sparsa) indicate that the flanking regions are conserved in all these species. A total of 15 SSR amplicons unique to P. philippinensis (one of the potential threats to US maize production) were detected, and these have potential for development of diagnostic tests. A total of 260 alleles were obtained using 54 microsatellites primer combinations, with an average of 4.8 polymorphic markers per SSR across 34 Peronosclerospora

Allan R. Sanford (1927–2016)

DOE PAGES

Hartse, Hans Edward

2016-12-07

Allan (Al) R. Sanford, professor of geophysics, emeritus, at New Mexico Tech (NMT) passed away quietly at his home in Woodinville, WA on August 9, 2016. He was 89. Al was a pioneer in the recording and interpretation of microearthquake seismograms. For decades he was the leading authority concerning seismicity across New Mexico and within the Rio Grande Rift (RGR). He published numerous papers with graduate students and colleagues on the unique, high-amplitude reflected phases seen on Socorro-area microearthquake records.

Species delimitation in downy mildews: the case of Hyaloperonospora in the light of nuclear ribosomal ITS and LSU sequences.

PubMed

Göker, Markus; Voglmayr, Hermann; Blázquez, Gema García; Oberwinkler, Franz

2009-03-01

Species definitions for plant pathogens have considerable practical impact for measures such as plant protection or biological control, and are also important for comparative studies involving model organisms. However, in many groups, the delimitation of species is a notoriously difficult taxonomic problem. This is particularly evident in the obligate biotrophic downy mildew genera (Peronosporaceae, Peronosporales, Oomycetes), which display a considerable diversity with respect to genetic distances and host plants, but are, for the most part, morphologically rather uniform. The recently established genus Hyaloperonospora is of particular biological interest because it shows an impressive radiation on virtually a single host family, Brassicaceae, and it contains the downy mildew parasite, Arabidopsis thaliana, of importance as a model organism. Based on the most comprehensive molecular sampling of specimens from a downy mildew genus to date, including various collections from different host species and geographic locations, we investigate the phylogenetic relationships of Hyaloperonospora by molecular analysis of the nuclear ribosomal ITS and LSU sequences. Phylogenetic trees were inferred with ML and MP from the combined dataset; partitioned Bremer support (PBrS) was used to assess potential conflict between data partitions. As in other downy mildew groups, the molecular data clearly corroborate earlier results that supported the use of narrow species delimitations and host ranges as taxonomic markers. With few exceptions, suggested species boundaries are supported without conflict between different data partitions. The results indicate that a combination of molecular and host features is a reliable means to discriminate downy mildew species for which morphological differences are unknown.

Nocturnal Fanning Suppresses Downy Mildew Epidemics in Sweet Basil

PubMed Central

Cohen, Yigal; Ben-Naim, Yariv

2016-01-01

Downy mildew is currently the most serious disease of sweet basil around the world. The oomycete causal agent Peronospora belbahrii requires ≥ 4h free leaf moisture for infection and ≥7.5h of water-saturated atmosphere (relative humidity RH≥95%) at night for sporulation. We show here that continued nocturnal fanning (wind speed of 0.4–1.5 m/s) from 8pm to 8am dramatically suppressed downy mildew development. In three experiments conducted during 2015, percent infected leaves in regular (non-fanned) net-houses reached a mean of 89.9, 94.3 and 96.0% compared to1.2, 1.7 and 0.5% in adjacent fanned net-houses, respectively. Nocturnal fanning reduced the number of hours per night with RH≥95% thus shortened the dew periods below the threshold required for infection or sporulation. In experiments A, B and C, the number of nights with ≥4h of RH≥95% was 28, 10 and 17 in the non-fanned net-houses compared to 5, 0 and 5 in the fanned net-houses, respectively. In the third experiment leaf wetness sensors were installed. Dew formation was strongly suppressed in the fanned net-house as compared to the non-fanned net-house. Healthy potted plants became infected and sporulated a week later if placed one night in the non-fanned house whereas healthy plants placed during that night in the fanned house remained healthy. Infected potted basil plants sporulated heavily after one night of incubation in the non-fanned house whereas almost no sporulation occurred in similar plants incubated that night in the fanned house. The data suggest that nocturnal fanning is highly effective in suppressing downy mildew epidemics in sweet basil. Fanning prevented the within-canopy RH from reaching saturation, reduced dew deposition on the leaves, and hence prevented both infection and sporulation of P. belbahrii. PMID:27171554

Application of Allan Deviation to Assessing Uncertainties of Continuous-measurement Instruments, and Optimizing Calibration Schemes

NASA Astrophysics Data System (ADS)

Jacobson, Gloria; Rella, Chris; Farinas, Alejandro

2014-05-01

Technological advancement of instrumentation in atmospheric and other geoscience disciplines over the past decade has lead to a shift from discrete sample analysis to continuous, in-situ monitoring. Standard error analysis used for discrete measurements is not sufficient to assess and compare the error contribution of noise and drift from continuous-measurement instruments, and a different statistical analysis approach should be applied. The Allan standard deviation analysis technique developed for atomic clock stability assessment by David W. Allan [1] can be effectively and gainfully applied to continuous measurement instruments. As an example, P. Werle et al has applied these techniques to look at signal averaging for atmospheric monitoring by Tunable Diode-Laser Absorption Spectroscopy (TDLAS) [2]. This presentation will build on, and translate prior foundational publications to provide contextual definitions and guidelines for the practical application of this analysis technique to continuous scientific measurements. The specific example of a Picarro G2401 Cavity Ringdown Spectroscopy (CRDS) analyzer used for continuous, atmospheric monitoring of CO2, CH4 and CO will be used to define the basics features the Allan deviation, assess factors affecting the analysis, and explore the time-series to Allan deviation plot translation for different types of instrument noise (white noise, linear drift, and interpolated data). In addition, the useful application of using an Allan deviation to optimize and predict the performance of different calibration schemes will be presented. Even though this presentation will use the specific example of the Picarro G2401 CRDS Analyzer for atmospheric monitoring, the objective is to present the information such that it can be successfully applied to other instrument sets and disciplines. [1] D.W. Allan, "Statistics of Atomic Frequency Standards," Proc, IEEE, vol. 54, pp 221-230, Feb 1966 [2] P. Werle, R. Miicke, F. Slemr, "The Limits

Mary Ann Franden | NREL

Science.gov Websites

Ann Franden Photo of Mary Ann Franden Mary Franden Researcher IV-Molecular Biology Mary.Ann.Franden @nrel.gov | 303-384-7767 Research Interests Mary Ann Franden is a senior scientist in the Applied Biology University Professional Experience Senior Scientist, NREL, NBC, Applied Biology Group Professional Research

Process-based management approaches for salt desert shrublands dominated by downy brome

USDA-ARS?s Scientific Manuscript database

Downy brome grass (Bromus tectorum L.) invasion has severely altered key ecological processes such as disturbance regimes, soil nutrient cycling, community assembly, and successional pathways in semi-arid Great Basin salt desert shrublands. Restoring the structure and function of these severly alte...

Seeds of a Soldier: The True Story of Edgar Allan Poe - The Sergeant Major

DTIC Science & Technology

2003-01-01

2003 2. REPORT TYPE 3. DATES COVERED 00-00-2003 to 00-00-2003 4. TITLE AND SUBTITLE Seeds of a Soldier. The true story of Edgar Allan Poe - the...Std Z39-18 Army Space Journal Fall 200360 By Michael L. Howard Seeds of a Soldier The true story of Edgar Allan Poe — the Sergeant Major...provided additional motivation for Poe to ultimately suc- ceed. Poe’s biological father disappeared when Edgar was E (See Seeds , page 56) Author’s Note

Genetics and mapping of a novel downy mildew resistance gene, Pl18, introgressed from wild Helianthus argophyllus into cultivated sunflower (Helianthus annuus L.)

USDA-ARS?s Scientific Manuscript database

Sunflower downy mildew is considered to be the most destructive foliar disease that has spread to every major sunflower-growing country of the world, except Australia. A new dominant downy mildew resistance gene (Pl18) transferred from wild Helianthus argophyllus (PI 494573) into cultivated sunflowe...

The Openness That Closes: Allan Bloom and the Contemporary University.

ERIC Educational Resources Information Center

Orwin, Clifford; Forbes, H. D.

1991-01-01

Discusses the contemporary university in Canada, focusing on Allan Bloom's "The Closing of the American Mind" which analyzes problems in today's education. The paper calls Bloom's book an unrivaled diagnosis of the impasse of the university, and it examines Bloom's relativistic principles. (SM)

Soil engineering facilitates Downy brome (Bromus tectorum L.) growth - A case study

USDA-ARS?s Scientific Manuscript database

Some exotic plants are able to engineer new host soils and engender characteristics that potentially increase their growth. We hypothesized that this positive feedback may be a facet in the competitiveness of the exotic annual grass downy brome. Using rhizotrons in the greenhouse, we compared the gr...

Breeding for resistance to downy mildews and stalk rots in maize.

PubMed

Lal, S; Singh, I S

1984-12-01

The present review includes information on distribution, symptoms, inoculation techniques, disease rating, sources of resistance, genetics of resistance, breeding approaches for resistance, and the present status of resistance breeding with respect to Sclerophthora and Peronosclerospora downy mildews and Erwinia, Cephalosporium and Fusarium stalk rots. Some suggestions highlighting research gaps pertinent to future breeding strategies are mentioned.

[The medical history of Edgar Allan Poe].

PubMed

Miranda C, Marcelo

2007-09-01

Edgar Allan Poe, one of the best American storytellers and poets, suffered an episodic behaviour disorder partially triggered by alcohol and opiate use. Much confusion still exists about the last days of his turbulent life and the cause of his death at an early age. Different etiologies have been proposed to explain his main medical problem, however, complex partial seizures triggered by alcohol, poorly recognized at the time when Poe lived, seems to be one of the most acceptable hypothesis, among others discussed.

Precision QTL mapping of downy mildew resistance in Hop (Humulus lupulus L.)

USDA-ARS?s Scientific Manuscript database

Hop Downy mildew (DM) is an obligate parasite causing severe losses in hop if not controlled. Resistance to this pathogen is a primary goal for hop breeding programs. The objective of this study was to identify QTLs linked to DM resistance. Next-generation-sequencing was performed on a mapping po...

Is Pyrenophora semeniperda the cause of downy brome (Bromus tectorum) die-offs?

Treesearch

Owen W. Baughman; Susan E. Meyer

2013-01-01

Downy brome (cheatgrass) is a highly successful, exotic, winter annual invader in semi-arid western North America, forming near-monocultures across many landscapes. A frequent but poorly understood phenomenon in these heavily invaded areas is periodic 'die-off' or complete stand failure. The fungal pathogen Pyrenophora semeniperda is abundant in cheatgrass...

The ghost of outcrossing past in downy brome, an inbreeding annual grass

Treesearch

Susan E. Meyer; Sudeep Ghimire; Samuel Decker; Keith R. Merrill; Craig E. Coleman

2013-01-01

We investigated the frequency of outcrossing in downy brome (Bromus tectorum L.), a cleistogamous weedy annual grass, in both common garden and wild populations, using microsatellite and single nucleotide polymorphic (SNP) markers. In the common garden study, 25 lines with strongly contrasting genotypes were planted in close proximity. We fingerprinted 10 seed progeny...

On the Design of Attitude-Heading Reference Systems Using the Allan Variance.

PubMed

Hidalgo-Carrió, Javier; Arnold, Sascha; Poulakis, Pantelis

2016-04-01

The Allan variance is a method to characterize stochastic random processes. The technique was originally developed to characterize the stability of atomic clocks and has also been successfully applied to the characterization of inertial sensors. Inertial navigation systems (INS) can provide accurate results in a short time, which tend to rapidly degrade in longer time intervals. During the last decade, the performance of inertial sensors has significantly improved, particularly in terms of signal stability, mechanical robustness, and power consumption. The mass and volume of inertial sensors have also been significantly reduced, offering system-level design and accommodation advantages. This paper presents a complete methodology for the characterization and modeling of inertial sensors using the Allan variance, with direct application to navigation systems. Although the concept of sensor fusion is relatively straightforward, accurate characterization and sensor-information filtering is not a trivial task, yet they are essential for good performance. A complete and reproducible methodology utilizing the Allan variance, including all the intermediate steps, is described. An end-to-end (E2E) process for sensor-error characterization and modeling up to the final integration in the sensor-fusion scheme is explained in detail. The strength of this approach is demonstrated with representative tests on novel, high-grade inertial sensors. Experimental navigation results are presented from two distinct robotic applications: a planetary exploration rover prototype and an autonomous underwater vehicle (AUV).

Allan Urho Paivio (1925-2016).

PubMed

Katz, Albert

2017-01-01

Presents an obituary for Allan Urho Paivio, who passed away on June 19, 2016. One of his many accomplishments was the development of a dual-coding theory. Dual-coding theory, while very influential, has, unfortunately, been discussed all too often as a theory of mental imagery, and not within its larger context wherein mental imagery and verbal processes are separable but interconnected representational systems, an academic battle in clarification that Paivio waged much of his life. He published prodigiously, even in the decades after retirement. Among his many honors, he served as president of the Canadian Psychological Association (1975) and was appointed a fellow of the Royal Society of Canada (1978). (PsycINFO Database Record (c) 2017 APA, all rights reserved).

QTL mapping of downy mildew resistance in PI 197088 and PI 330628 cucumbers

USDA-ARS?s Scientific Manuscript database

Downy mildew (DM, Pseudoperonospora cubensis) is a devastating fungal disease of cucumber worldwide. Several plant introduction lines have been identified with high resistance to the post-2004 new DM strain found in the U.S. However, the inheritance of DM resistance is still not well defined. Molecu...

Identification of QTLs conferring resistance to downy mildew in legacy cultivars of lettuce

PubMed Central

Simko, Ivan; Atallah, Amy J.; Ochoa, Oswaldo E.; Antonise, Rudie; Galeano, Carlos H.; Truco, Maria Jose; Michelmore, Richard W.

2013-01-01

Many cultivars of lettuce (Lactuca sativa L.), the most popular leafy vegetable, are susceptible to downy mildew disease caused by Bremia lactucae. Cultivars Iceberg and Grand Rapids that were released in the 18th and 19th centuries, respectively, have high levels of quantitative resistance to downy mildew. We developed a population of recombinant inbred lines (RILs) originating from a cross between these two legacy cultivars, constructed a linkage map, and identified two QTLs for resistance on linkage groups 2 (qDM2.1) and 5 (qDM5.1) that determined resistance under field conditions in California and the Netherlands. The same QTLs determined delayed sporulation at the seedling stage in laboratory experiments. Alleles conferring elevated resistance at both QTLs originate from cultivar Iceberg. An additional QTL on linkage group 9 (qDM9.1) was detected through simultaneous analysis of all experiments with mixed-model approach. Alleles for elevated resistance at this locus originate from cultivar Grand Rapids. PMID:24096732

Occurrence of downy mildews on ornamental plants and their control by chemical compounds.

PubMed

Skrzypczak, C

2007-01-01

The downy mildew on Coreopsis grandiflora caused by Plasmopara halstedii was observed during summer, mainly in July and August. Symptoms of the disease were first seen on external leaves and progressively spread to inner parts of plant rosette. On Alyssum saxatile downy mildew symptoms induced by Peronospora parasitica were observed during whole vegetation period with the strongest expression in early spring and late summer. Amistar 250 SC (25% azoxystrobine), Mildex 711,9 WG (66.7% phosethyl aluminium + 4.4% fenamidone), Previcur Energy 840 SL (530 g/l propamocarb + 310 g/l phosetyl aluminium) and Tanos 50 WG (25% cymoxanil + 25% famoxate) were used for pathogens control. In the protection of Coreopsis grandiflora against P. halstedii all tested compounds, applied curatively, decreased sporulation of the pathogen. On treaded plants at least 4-time less leaves were diseased. In the control of P. parasitica on Alyssum saxatile, the smallest number of swallowed structures on leaves was noticed on plants treated with azoxystrobine at conc. 250 microg/cm3.

Advances in diagnostics of downy mildews: Lessons learned from other oomycetes and future challenges

USDA-ARS?s Scientific Manuscript database

Early detection of downy mildews in the environment is critical to establish pathogen presence and identity, determine fungicide resistance, and understand how pathogen populations disperse. Knowing when and where pathogens emerge is also important for identifying critical control points to restrict...

Downy mildew resistance induced by Trichoderma harzianum T39 in susceptible grapevines partially mimics transcriptional changes of resistant genotypes

PubMed Central

2012-01-01

Background Downy mildew, caused by Plasmopara viticola, is one of the most severe diseases of grapevine and is commonly controlled by fungicide treatments. The beneficial microorganism Trichoderma harzianum T39 (T39) can induce resistance to downy mildew, although the molecular events associated with this process have not yet been elucidated in grapevine. A next generation RNA sequencing (RNA-Seq) approach was used to study global transcriptional changes associated with resistance induced by T39 in Vitis vinifera Pinot Noir leaves. The long-term aim was to develop strategies to optimize the use of this agent for downy mildew control. Results More than 14.8 million paired-end reads were obtained for each biological replicate of T39-treated and control leaf samples collected before and 24 h after P. viticola inoculation. RNA-Seq analysis resulted in the identification of 7,024 differentially expressed genes, highlighting the complex transcriptional reprogramming of grapevine leaves during resistance induction and in response to pathogen inoculation. Our data show that T39 has a dual effect: it directly modulates genes related to the microbial recognition machinery, and it enhances the expression of defence-related processes after pathogen inoculation. Whereas several genes were commonly affected by P. viticola in control and T39-treated plants, opposing modulation of genes related to responses to stress and protein metabolism was found. T39-induced resistance partially inhibited some disease-related processes and specifically activated defence responses after P. viticola inoculation, causing a significant reduction of downy mildew symptoms. Conclusions The global transcriptional analysis revealed that defence processes known to be implicated in the reaction of resistant genotypes to downy mildew were partially activated by T39-induced resistance in susceptible grapevines. Genes identified in this work are an important source of markers for selecting novel

Multi-Dimensional Analysis of Large, Complex Slope Instability: Case study of Downie Slide, British Columbia, Canada. (Invited)

NASA Astrophysics Data System (ADS)

Kalenchuk, K. S.; Hutchinson, D.; Diederichs, M. S.

2013-12-01

Downie Slide, one of the world's largest landslides, is a massive, active, composite, extremely slow rockslide located on the west bank of the Revelstoke Reservoir in British Columbia. It is a 1.5 billion m3 rockslide measuring 2400 m along the river valley, 3300m from toe to headscarp and up to 245 m thick. Significant contributions to the field of landslide geomechanics have been made by analyses of spatially and temporally discriminated slope deformations, and how these are controlled by complex geological and geotechnical factors. Downie Slide research demonstrates the importance of delineating massive landslides into morphological regions in order to characterize global slope behaviour and identify localized events, which may or may not influence the overall slope deformation patterns. Massive slope instabilities do not behave as monolithic masses, rather, different landslide zones can display specific landslide processes occurring at variable rates of deformation. The global deformation of Downie Slide is extremely slow moving; however localized regions of the slope incur moderate to high rates of movement. Complex deformation processes and composite failure mechanism are contributed to by topography, non-uniform shear surfaces, heterogeneous rockmass and shear zone strength and stiffness characteristics. Further, from the analysis of temporal changes in landslide behaviour it has been clearly recognized that different regions of the slope respond differently to changing hydrogeological boundary conditions. State-of-the-art methodologies have been developed for numerical simulation of large landslides; these provide important tools for investigating dynamic landslide systems which account for complex three-dimensional geometries, heterogenous shear zone strength parameters, internal shear zones, the interaction of discrete landslide zones and piezometric fluctuations. Numerical models of Downie Slide have been calibrated to reproduce observed slope behaviour

Effect of detergent on the quantification of grapevine downy mildew Sporangia from leaf discs

USDA-ARS?s Scientific Manuscript database

Grapevine downy mildew (DM), caused by the oomycete Plasmopara viticola (Berk. & Curt.) Berlese & de Toni, is a major disease, especially in humid viticultural areas. Development of resistant cultivars is an important objective for grapevine breeding. In order to establish a reliable and inexpensive...

Downy mildew on coleus (Plectranthus scutellarioides) caused by Peronospora belbahrii sensu lato in Tennessee

USDA-ARS?s Scientific Manuscript database

Coleus (Plectranthus scutellarioides [syn. = Solenostemon scutellarioides]) is a popular ornamental plant in the mint family (Lamiaceae), prized for its colorful and showy foliage. In August 2015, disease symptoms typical of downy mildew were observed at two sites in Nashville, Tennessee: (i) at the...

Impact of clonal variability in Vitis vinifera Cabernet franc on grape composition, wine quality, leaf blade stilbene content, and downy mildew resistance.

PubMed

van Leeuwen, Cornelis; Roby, Jean-Philippe; Alonso-Villaverde, Virginia; Gindro, Katia

2013-01-09

In this study, 10 clones of Vitis vinifera Cabernet franc (not yet commercial) have been phenotyped on precocity, grape composition, and assessment of wine quality made by microvinification in 2008-2010. Additionally, two original criteria have been considered: concentration of 3-isobutyl-2-methoxypyrazine (IBMP) in grapes and wines (the green bell pepper flavor) and resistance of grapevines to downy mildew ( Plasmopara viticola ) by stilbene quantification upon infection. Precocity of veraison varied up to four days at veraison. Berry size and yield were highly variable among clones. However, these variables were not correlated. Tanins and anthocyanins varied among clones in grapes and wines. Variations in grape and wine IBMP were not significant. Some clones showed lower susceptibility for downy mildew on leaves. Lower susceptibility was linked to a higher production of stilbenic phytoalexins involved in downy mildew resistance mechanisms.

Assessing the vulnerability of sorghum converted lines to anthracnose and downy mildew infection

USDA-ARS?s Scientific Manuscript database

A total of 59 converted sorghum lines and six checks were evaluated for resistance to two foliar fungal diseases, anthracnose and downy mildew (SDM) in 2008 and 2009 growing seasons at the Texas A&M AgriLife Research Farm, College Station, Texas. In 2008, 23 lines exhibited resistance (35%), 29 sus...

Quantifying the Precision of Single-Molecule Torque and Twist Measurements Using Allan Variance.

PubMed

van Oene, Maarten M; Ha, Seungkyu; Jager, Tessa; Lee, Mina; Pedaci, Francesco; Lipfert, Jan; Dekker, Nynke H

2018-04-24

Single-molecule manipulation techniques have provided unprecedented insights into the structure, function, interactions, and mechanical properties of biological macromolecules. Recently, the single-molecule toolbox has been expanded by techniques that enable measurements of rotation and torque, such as the optical torque wrench (OTW) and several different implementations of magnetic (torque) tweezers. Although systematic analyses of the position and force precision of single-molecule techniques have attracted considerable attention, their angle and torque precision have been treated in much less detail. Here, we propose Allan deviation as a tool to systematically quantitate angle and torque precision in single-molecule measurements. We apply the Allan variance method to experimental data from our implementations of (electro)magnetic torque tweezers and an OTW and find that both approaches can achieve a torque precision better than 1 pN · nm. The OTW, capable of measuring torque on (sub)millisecond timescales, provides the best torque precision for measurement times ≲10 s, after which drift becomes a limiting factor. For longer measurement times, magnetic torque tweezers with their superior stability provide the best torque precision. Use of the Allan deviation enables critical assessments of the torque precision as a function of measurement time across different measurement modalities and provides a tool to optimize measurement protocols for a given instrument and application. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Horror from the Soul--Gothic Style in Allan Poe's Horror Fictions

ERIC Educational Resources Information Center

Sun, Chunyan

2015-01-01

Edgar Allan Poe made tremendous contribution to horror fiction. Poe's inheritance of gothic fiction and American literature tradition combined with his living experience forms the background of his horror fictions. He inherited the tradition of the gothic fictions and made innovations on it, so as to penetrate to subconsciousness. Poe's horror…

Phylogenetic relationships of graminicolous downy mildews based on cox2 sequence data.

PubMed

Thines, Marco; Göker, Markus; Telle, Sabine; Ryley, Malcolm; Mathur, Kusum; Narayana, Yaladabagi D; Spring, Otmar; Thakur, Ram P

2008-03-01

Graminicolous downy mildews (GDM) are an understudied, yet economically important, group of plant pathogens, which are one of the major constraints to poaceous crops in the tropics and subtropics. Here we present a first molecular phylogeny based on cox2 sequences comprising all genera of the GDM currently accepted, with both lasting (Graminivora, Poakatesthia, and Viennotia) and evanescent (Peronosclerospora, Sclerophthora, and Sclerospora) sporangiophores. In addition, all other downy mildew genera currently accepted, as well as a representative sample of other oomycete taxa, have been included. It was shown that all genera of the GDM have had a long, independent evolutionary history, and that the delineation between Peronosclerospora and Sclerospora is correct. Sclerophthora was found to be a particularly divergent taxon nested within a paraphyletic Phytophthora, but without support. The results confirm that the placement of Peronosclerospora and Sclerospora in the Saprolegniomycetidae is incorrect. Sclerophthora is not closely related to Pachymetra of the family Verrucalvaceae, and also does not belong to the Saprolegniomycetidae, but shows close affinities to the Peronosporaceae. In addition, all GDM are interspersed throughout the Peronosporaceae s lat., suggesting that a separate family for the Sclerosporaceae might not be justified.

Two species of Gelechioidea (Lepidoptera) from Southeast Asia associated with downy rose myrtle, Rhodomyrtus tomentosa (Myrtaceae)

USDA-ARS?s Scientific Manuscript database

Two species of Gelechioidea (Lepidoptera), Metharmostis multilineata Adamski, n. sp. (Cosmopterigidae), and Idiophantis soreuta Meyrick, 1906 (Gelechiidae), were collected in southeastern Asia for evaluation as potential biocontrol agents against downy rose myrtle, Rhodomyrtus tomentosa (Aiton) Hass...

Epidemiology and population biology of pseudoperonospora cubensis: a model system for management of downy mildews

USDA-ARS?s Scientific Manuscript database

The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of disease outbreaks. Dispersal potential of th...

Development and dissection of diagnostic SNP markers for the downy mildew resistance genes PlArg and Pl8 and maker-assisted gene pyramiding in sunflower (Helianthus annuus L.)

USDA-ARS?s Scientific Manuscript database

Downy mildew, which is caused by fungus Plasmopara halstedii (Farl.) Berlese & de Toni, is one of the most important diseases that affect sunflower production globally. Two downy mildew resistance genes, PlArg and Pl8, were discovered in the late 1980s. Over two decades, PlArg is still effective aga...

Maniac Talk - Dr. Anne Thompson

NASA Image and Video Library

2014-04-30

Anne Thompson Maniac Lecture, 30 April 2014 NASA climate scientist Dr. Anne Thompson presented a Maniac Talk entitled "A Career in Many Ozone Layers." Anne shared some of her long scientific career both as a researcher at Goddard and Meteorology professor at Penn State. She also described some of the problems she has worked on and tried to convey an enthusiasm for Earth Observations

Maniac Talk - Dr. Anne Douglass

NASA Image and Video Library

2013-03-27

Anne Douglass Maniac Lecture, 27 March, 2013 NASA climate scientist Dr. Anne Douglass presented a Maniac Talk entitled "Satellite Observations - the Touchstone of Atmospheric Modeling." Anne shared some of her scientific career that is filled with unexpected twists and turns and even a few blind alleys, but most important her passion in satellite measurements of ozone and other trace gases, which have been her touchstone.

Control of downy mildew (Pseudoperonospora cubensis) of greenhouse grown cucumbers with alternative biological agents.

PubMed

Scherf, A; Schuster, C; Marx, P; Gärber, U; Konstantinidou-Doltsinis, S; Schmitt, A

2010-01-01

In organic cucumber production infection with downy mildew (Pseudoperonospora cubensis) is a major problem. Plant extracts from Glycyrrhiza glabra L. (licorice), a plant belonging to the family Fabaceae, and Salvia officinalis (sage) as well as cultures of the bacterium Aneurinibacillus migulanus were investigated for efficacy of disease control under commercial growing conditions. Contrary to bioassays, where sage extract and the microorganism showed highest activity, in the trials of 2008 G. glabra extract was more effective than sage extract or A. migulanus against P. cubensis. Parameters such as concentrations of the preparations or application intervals could have been the reason for this. In the following year's trial (2009) the concentration of these agents was therefore increased somewhat and plants were either treated in seven day application intervals or in ten day application intervals. In the semi-commercial trials of 2009 all alternative biological agents showed good efficacies up to around 80% against infection with downy mildew. The application interval seemed to have a marginal effect only. Again, the licorice extract tended to be the best agent.

Genetic characterization of quantitative resistance to Bremia lactucae, the causal organism of lettuce downy mildew

USDA-ARS?s Scientific Manuscript database

Lettuce (Lactuca sativa) is one of the most valuable vegetable crops in the United States. Downy mildew (DM), caused by Bremia lactucae, is the most important foliar disease of lettuce worldwide, which decreases the quality of the marketable portion of the crop. The use of resistant varieties carryi...

Using next-generation sequencing to develop molecular diagnostics for Pseudoperonospora cubensis, the cucurbit downy mildew pathogen

USDA-ARS?s Scientific Manuscript database

Advances in Next Generation Sequencing (NGS) allow for rapid development of genomics resources needed to generate molecular diagnostics assays for infectious agents. NGS approaches are particularly helpful for organisms that cannot be cultured, such as the downy mildew pathogens, a group of biotrop...

Allan M. Freedman, LLB: a lawyer’s gift to Canadian chiropractors

PubMed Central

Brown, Douglas M.

2007-01-01

This paper reviews the leadership role, contributions, accolades, and impact of Professor Allan Freedman through a 30 year history of service to CMCC and the chiropractic profession in Canada. Professor Freedman has served as an educator, philanthropist and also as legal counsel. His influence on chiropractic organizations and chiropractors during this significant period in the profession is discussed. PMID:18060008

Quantifying noise in optical tweezers by allan variance.

PubMed

Czerwinski, Fabian; Richardson, Andrew C; Oddershede, Lene B

2009-07-20

Much effort is put into minimizing noise in optical tweezers experiments because noise and drift can mask fundamental behaviours of, e.g., single molecule assays. Various initiatives have been taken to reduce or eliminate noise but it has been difficult to quantify their effect. We propose to use Allan variance as a simple and efficient method to quantify noise in optical tweezers setups.We apply the method to determine the optimal measurement time, frequency, and detection scheme, and quantify the effect of acoustic noise in the lab. The method can also be used on-the-fly for determining optimal parameters of running experiments.

First report of downy mildew caused by Hyaloperonospora sp. on Iberis sempervirens in the United States

USDA-ARS?s Scientific Manuscript database

Iberis sempervirens (candytuft) is a herbaceous perennial in the Brassicaceae. It has evergreen foliage and fragrant, pure white flowers, and is a popular groundcover. During March 2016, downy mildew-like symptoms were observed on potted plants in a commercial greenhouse located in Baltimore Co. Mar...

Multi-locus tree and species tree approaches toward resolving a complex clade of downy mildews (Straminipila, Oomycota), including pathogens of beet and spinach

PubMed Central

Choi, Young-Joon; Klosterman, Steven J.; Kummer, Volker; Voglmayr, Hermann; Shin, Hyeon-Dong; Thines, Marco

2017-01-01

Accurate species determination of plant pathogens is a prerequisite for their control and quarantine, and further for assessing their potential threat to crops. The family Peronosporaceae (Straminipila; Oomycota) consists of obligate biotrophic pathogens that cause downy mildew disease on angiosperms, including a large number of cultivated plants. In the largest downy mildew genus Peronospora, a phylogenetically complex clade includes the economically important downy mildew pathogens of spinach and beet, as well as the type species of the genus Peronospora. To resolve this complex clade at the species level and to infer evolutionary relationships among them, we used multi-locus phylogenetic analysis and species tree estimation. Both approaches discriminated all nine currently accepted species and revealed four previously unrecognized lineages, which are specific to a host genus or species. This is in line with a narrow species concept, i.e. that a downy mildew species is associated with only a particular host plant genus or species. Instead of applying the dubious name Peronospora farinosa, which has been proposed for formal rejection, our results provide strong evidence that Peronospora schachtii is an independent species from lineages on Atriplex and apparently occurs exclusively on Beta vulgaris. The members of the clade investigated, the Peronospora rumicis clade, associate with three different host plant families, Amaranthaceae, Caryophyllaceae, and Polygonaceae, suggesting that they may have speciated following at least two recent inter-family host shifts, rather than contemporary cospeciation with the host plants. PMID:25772799

Multi-locus tree and species tree approaches toward resolving a complex clade of downy mildews (Straminipila, Oomycota), including pathogens of beet and spinach.

PubMed

Choi, Young-Joon; Klosterman, Steven J; Kummer, Volker; Voglmayr, Hermann; Shin, Hyeon-Dong; Thines, Marco

2015-05-01

Accurate species determination of plant pathogens is a prerequisite for their control and quarantine, and further for assessing their potential threat to crops. The family Peronosporaceae (Straminipila; Oomycota) consists of obligate biotrophic pathogens that cause downy mildew disease on angiosperms, including a large number of cultivated plants. In the largest downy mildew genus Peronospora, a phylogenetically complex clade includes the economically important downy mildew pathogens of spinach and beet, as well as the type species of the genus Peronospora. To resolve this complex clade at the species level and to infer evolutionary relationships among them, we used multi-locus phylogenetic analysis and species tree estimation. Both approaches discriminated all nine currently accepted species and revealed four previously unrecognized lineages, which are specific to a host genus or species. This is in line with a narrow species concept, i.e. that a downy mildew species is associated with only a particular host plant genus or species. Instead of applying the dubious name Peronospora farinosa, which has been proposed for formal rejection, our results provide strong evidence that Peronospora schachtii is an independent species from lineages on Atriplex and apparently occurs exclusively on Beta vulgaris. The members of the clade investigated, the Peronospora rumicis clade, associate with three different host plant families, Amaranthaceae, Caryophyllaceae, and Polygonaceae, suggesting that they may have speciated following at least two recent inter-family host shifts, rather than contemporary cospeciation with the host plants. Copyright © 2015 Elsevier Inc. All rights reserved.

Polymorphic SSR markers for Plasmopara obducens (Peronosporaceae), the newly emergent downy mildew pathogen of Impatiens (Balsaminaceae)

USDA-ARS?s Scientific Manuscript database

Premise of the study: Microsatellite markers were developed for Plasmopara obducens, the causal agent of the newly emergent downy mildew disease of Impatiens walleriana. Methods and Results: A 151.2 Mb draft genome assembly was generated from P. obducens using Illumina technology and mined to identi...

Population structure, genetic diversity and downy mildew resistance among Ocimum species germplasm.

PubMed

Pyne, Robert M; Honig, Josh A; Vaiciunas, Jennifer; Wyenandt, Christian A; Simon, James E

2018-04-23

The basil (Ocimum spp.) genus maintains a rich diversity of phenotypes and aromatic volatiles through natural and artificial outcrossing. Characterization of population structure and genetic diversity among a representative sample of this genus is severely lacking. Absence of such information has slowed breeding efforts and the development of sweet basil (Ocimum basilicum L.) with resistance to the worldwide downy mildew epidemic, caused by the obligate oomycete Peronospora belbahrii. In an effort to improve classification of relationships 20 EST-SSR markers with species-level transferability were developed and used to resolve relationships among a diverse panel of 180 Ocimum spp. accessions with varying response to downy mildew. Results obtained from nested Bayesian model-based clustering, analysis of molecular variance and unweighted pair group method using arithmetic average (UPGMA) analyses were synergized to provide an updated phylogeny of the Ocimum genus. Three (major) and seven (sub) population (cluster) models were identified and well-supported (P < 0.001) by PhiPT (Φ PT ) values of 0.433 and 0.344, respectively. Allelic frequency among clusters supported previously developed hypotheses of allopolyploid genome structure. Evidence of cryptic population structure was demonstrated for the k1 O. basilicum cluster suggesting prevalence of gene flow. UPGMA analysis provided best resolution for the 36-accession, DM resistant k3 cluster with consistently strong bootstrap support. Although the k3 cluster is a rich source of DM resistance introgression of resistance into the commercially important k1 accessions is impeded by reproductive barriers as demonstrated by multiple sterile F1 hybrids. The k2 cluster located between k1 and k3, represents a source of transferrable tolerance evidenced by fertile backcross progeny. The 90-accession k1 cluster was largely susceptible to downy mildew with accession 'MRI' representing the only source of DM resistance. High

Polymorphic SSR Markers for Plasmopara obducens (Peronosporaceae), the Newly Emergent Downy Mildew Pathogen of Impatiens (Balsaminaceae)

DOE PAGES

Salgado-Salazar, Catalina; Rivera, Yazmín; Veltri, Daniel; ...

2015-11-10

Premise of the study: Simple sequence repeat (SSR) markers were developed for Plasmopara obducens, the causal agent of the newly emergent downy mildew disease of Impatiens walleriana. Methods and Results: A 202-Mb draft genome assembly was generated from P. obducens using Illumina technology and mined to identify 13,483 SSR motifs. Primers were synthesized for 62 marker candidates, of which 37 generated reliable PCR products. Testing of the 37 markers using 96 P. obducens samples showed 96% of the markers were polymorphic, with 2-6 alleles observed. Observed and expected heterozygosity ranged from 0.000-0.892 and 0.023-0.746, respectively. Just 17 markers were sufficientmore » to identify all multilocus genotypes. Conclusions: These are the first SSR markers available for this pathogen, and one of the first molecular resources. These markers will be useful in assessing variation in pathogen populations and determining the factors contributing to the emergence of destructive impatiens downy mildew disease.« less

Looking at the "Next" 20 Years of Multiliteracies: A Discussion with Allan Luke

ERIC Educational Resources Information Center

Garcia, Antero; Luke, Allan; Seglem, Robyn

2018-01-01

In this discussion with literacies researcher Allan Luke, the New London Group Member reflects on the role of multiliteracies in shaping literacies research and the continuing changes to technology, capitalism, and learning. Focused on looking toward future advances in literacies research, Luke reflects on the role of multiliteracies in…

Uranium series dating of Allan Hills ice

NASA Technical Reports Server (NTRS)

Fireman, E. L.

1986-01-01

Uranium-238 decay series nuclides dissolved in Antarctic ice samples were measured in areas of both high and low concentrations of volcanic glass shards. Ice from the Allan Hills site (high shard content) had high Ra-226, Th-230 and U-234 activities but similarly low U-238 activities in comparison with Antarctic ice samples without shards. The Ra-226, Th-230 and U-234 excesses were found to be proportional to the shard content, while the U-238 decay series results were consistent with the assumption that alpha decay products recoiled into the ice from the shards. Through this method of uranium series dating, it was learned that the Allen Hills Cul de Sac ice is approximately 325,000 years old.

Computer Vision for High-Throughput Quantitative Phenotyping: A Case Study of Grapevine Downy Mildew Sporulation and Leaf Trichomes.

PubMed

Divilov, Konstantin; Wiesner-Hanks, Tyr; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

2017-12-01

Quantitative phenotyping of downy mildew sporulation is frequently used in plant breeding and genetic studies, as well as in studies focused on pathogen biology such as chemical efficacy trials. In these scenarios, phenotyping a large number of genotypes or treatments can be advantageous but is often limited by time and cost. We present a novel computational pipeline dedicated to estimating the percent area of downy mildew sporulation from images of inoculated grapevine leaf discs in a manner that is time and cost efficient. The pipeline was tested on images from leaf disc assay experiments involving two F 1 grapevine families, one that had glabrous leaves (Vitis rupestris B38 × 'Horizon' [RH]) and another that had leaf trichomes (Horizon × V. cinerea B9 [HC]). Correlations between computer vision and manual visual ratings reached 0.89 in the RH family and 0.43 in the HC family. Additionally, we were able to use the computer vision system prior to sporulation to measure the percent leaf trichome area. We estimate that an experienced rater scoring sporulation would spend at least 90% less time using the computer vision system compared with the manual visual method. This will allow more treatments to be phenotyped in order to better understand the genetic architecture of downy mildew resistance and of leaf trichome density. We anticipate that this computer vision system will find applications in other pathosystems or traits where responses can be imaged with sufficient contrast from the background.

Genome analysis of the foxtail millet pathogen Sclerospora graminicola reveals the complex effector repertoire of graminicolous downy mildews.

PubMed

Kobayashi, Michie; Hiraka, Yukie; Abe, Akira; Yaegashi, Hiroki; Natsume, Satoshi; Kikuchi, Hideko; Takagi, Hiroki; Saitoh, Hiromasa; Win, Joe; Kamoun, Sophien; Terauchi, Ryohei

2017-11-22

Downy mildew, caused by the oomycete pathogen Sclerospora graminicola, is an economically important disease of Gramineae crops including foxtail millet (Setaria italica). Plants infected with S. graminicola are generally stunted and often undergo a transformation of flower organs into leaves (phyllody or witches' broom), resulting in serious yield loss. To establish the molecular basis of downy mildew disease in foxtail millet, we carried out whole-genome sequencing and an RNA-seq analysis of S. graminicola. Sequence reads were generated from S. graminicola using an Illumina sequencing platform and assembled de novo into a draft genome sequence comprising approximately 360 Mbp. Of this sequence, 73% comprised repetitive elements, and a total of 16,736 genes were predicted from the RNA-seq data. The predicted genes included those encoding effector-like proteins with high sequence similarity to those previously identified in other oomycete pathogens. Genes encoding jacalin-like lectin-domain-containing secreted proteins were enriched in S. graminicola compared to other oomycetes. Of a total of 1220 genes encoding putative secreted proteins, 91 significantly changed their expression levels during the infection of plant tissues compared to the sporangia and zoospore stages of the S. graminicola lifecycle. We established the draft genome sequence of a downy mildew pathogen that infects Gramineae plants. Based on this sequence and our transcriptome analysis, we generated a catalog of in planta-induced candidate effector genes, providing a solid foundation from which to identify the effectors causing phyllody.

Where Were the Whistleblowers? The Case of Allan McDonald and Roger Boisjoly.

ERIC Educational Resources Information Center

Stewart, Lea P.

Employees who "blow the whistle" on their company because they believe it is engaged in practices that are illegal, immoral, or harmful to the public, often face grave consequences for their actions, including demotion, harassment, forced resignation, or termination. The case of Allan McDonald and Roger Boisjoly, engineers who blew the…

Proteomic analysis of grapevine resistance induced by Trichoderma harzianum T39 reveals specific defence pathways activated against downy mildew

PubMed Central

Perazzolli, Michele

2012-01-01

Downy mildew is caused by the oomycete Plasmopara viticola and is one of the most serious diseases of grapevine. The beneficial microorganism Trichoderma harzianum T39 (T39) has previously been shown to induce plant-mediated resistance and to reduce the severity of downy mildew in susceptible grapevines. In order to better understand the cellular processes associated with T39-induced resistance, the proteomic and histochemical changes activated by T39 in grapevine were investigated before and 1 day after P. viticola inoculation. A comprehensive proteomic analysis of T39-induced resistance in grapevine was performed using an eight-plex iTRAQ protocol, resulting in the identification and quantification of a total of 800 proteins. Most of the proteins directly affected by T39 were found to be involved in signal transduction, indicating activation of a complete microbial recognition machinery. Moreover, T39-induced resistance was associated with rapid accumulation of reactive oxygen species and callose at infection sites, as well as changes in abundance of proteins involved in response to stress and redox balance, indicating an active defence response to downy mildew. On the other hand, proteins affected by P. viticola in control plants mainly decreased in abundance, possibly reflecting the establishment of a compatible interaction. Finally, the high-throughput iTRAQ protocol allowed de novo peptide sequencing, which will be used to improve annotation of the Vitis vinifera cv. Pinot Noir proteome. PMID:23105132

Overexpression of VpPR10.1 by an efficient transformation method enhances downy mildew resistance in V. vinifera.

PubMed

Su, Hang; Jiao, Yun-Tong; Wang, Fang-Fang; Liu, Yue-E; Niu, Wei-Li; Liu, Guo-Tian; Xu, Yan

2018-05-01

Putrescine and spermidine increase the transformation efficiency of Vitis vinifera L. cv. Thompson seedless. Accumulation of VpPR10.1 in transgenic V. vinifera Thompson seedless, likely increases its resistance to downy mildew. A more efficient method is described for facilitating Agrobacterium-mediated transformation of Vitis vinifera L. cv. Thompson Seedless somatic embryogenesis using polyamines (PAs). The efficacies of putrescine, spermidine and spermine are identified at a range of concentrations (10 µM, 100 µM and 1 mM) added to the culture medium during somatic embryo growth. Putrescine (PUT) and spermidine (SPD) promote the recovery of proembryonic masses (PEM) and the development of somatic embryos (SE) after co-cultivation. Judging from the importance of the time-frame in genetic transformation, PAs added at the co-cultivation stage have a stronger effect than delayed selection treatments, which are superior to antibiotic treatments in the selection stage. Best embryogenic responses are with 1 mM PUT and 100 µM SPD added to the co-culture medium. Using the above method, a pathogenesis-related gene (VpPR10.1) from Chinese wild Vitis pseudoreticulata was transferred into Thompson Seedless for functional evaluation. The transgenic line, confirmed by western blot analysis, was inoculated with Plasmopara viticola to test for downy mildew resistance. Based on observed restrictions of hyphal growth and increases in H 2 O 2 accumulation in the transgenic plants, the accumulation of VpPR10.1 likely enhanced the transgenic plants resistance to downy mildew.

Genotyping-by-sequencing targeting of a novel downy mildew resistance gene Pl 20 from wild Helianthus argophyllus for sunflower (Helianthus annuus L.).

PubMed

Ma, G J; Markell, S G; Song, Q J; Qi, L L

2017-07-01

Genotyping-by-sequencing revealed a new downy mildew resistance gene, Pl 20 , from wild Helianthus argophyllus located on linkage group 8 of the sunflower genome and closely linked to SNP markers that facilitate the marker-assisted selection of resistance genes. Downy mildew (DM), caused by Plasmopara halstedii, is one of the most devastating and yield-limiting diseases of sunflower. Downy mildew resistance identified in wild Helianthus argophyllus accession PI 494578 was determined to be effective against the predominant and virulent races of P. halstedii occurring in the United States. The evaluation of 114 BC 1 F 2:3 families derived from the cross between HA 89 and PI 494578 against P. halstedii race 734 revealed that single dominant gene controls downy mildew resistance in the population. Genotyping-by-sequencing analysis conducted in the BC 1 F 2 population indicated that the DM resistance gene derived from wild H. argophyllus PI 494578 is located on the upper end of the linkage group (LG) 8 of the sunflower genome, as was determined single nucleotide polymorphism (SNP) markers associated with DM resistance. Analysis of 11 additional SNP markers previously mapped to this region revealed that the resistance gene, named Pl 20 , co-segregated with four markers, SFW02745, SFW09076, S8_11272025, and S8_11272046, and is flanked by SFW04358 and S8_100385559 at an interval of 1.8 cM. The newly discovered P. halstedii resistance gene has been introgressed from wild species into cultivated sunflower to provide a novel gene with DM resistance. The homozygous resistant individuals were selected from BC 2 F 2 progenies with the use of markers linked to the Pl 20 gene, and these lines should benefit the sunflower community for Helianthus improvement.

Observation, Inference, and Imagination: Elements of Edgar Allan Poe's Philosophy of Science

ERIC Educational Resources Information Center

Gelfert, Axel

2014-01-01

Edgar Allan Poe's standing as a literary figure, who drew on (and sometimes dabbled in) the scientific debates of his time, makes him an intriguing character for any exploration of the historical interrelationship between science, literature and philosophy. His sprawling "prose-poem" "Eureka" (1848), in particular, has…

European Studies as Answer to Allan Bloom's "The Closing of the American Mind."

ERIC Educational Resources Information Center

Macdonald, Michael H.

European studies can provide a solution to several of the issues raised in Allan Bloom's "The Closing of the American Mind." European studies pursue the academic quest for what is truth, what is goodness, and what is beauty. In seeking to answer these questions, the Greeks were among the first to explore many of humanity's problems and…

Playing on the Right Side of the Brain: An Interview with Allan N. Schore

ERIC Educational Resources Information Center

American Journal of Play, 2017

2017-01-01

Allan N. Schore has served on the clinical faculty of the Department of Psychiatry and Biobehavioral Sciences at UCLA's David Geffen School of Medicine since 1996 and has maintained a private clinical practice for more than four decades. He has contributed significant research to the disciplines of interpersonal neurobiology, affective…

Total OH reactivity in a mediterranean forest of downy oaks

NASA Astrophysics Data System (ADS)

Zannoni, Nora; Gros, Valerie; Sarda, Roland; Lanza, Matteo; Bonsang, Bernard; Kalogridis, Cerise; Preunkert, Suzanne; Legrand, Michel; Jambert, Corinne; Boissard, Christophe; Lathiere, Juliette

2015-04-01

Forests emit large quantities of reactive molecules which can affect the concentration of the most important oxidizing agent in the atmosphere, the hydroxyl radical OH. There are still many unknowns on how biogenic compounds interact with the atmosphere. Among those, we still lack to fully understand the species that can potentially influence the atmospheric oxidative capacity and thus the OH cleansing effect over several forested areas. We conducted total OH reactivity measurements during spring 2014 inside and above the canopy height of a forest dominated at 80% by downy oaks in the Mediterranean basin (Observatoire Haute Provence site, France). Downy oak trees are capable to emit almost exclusively isoprene (~99%), the most abundant volatile organic compound and among the most reactive towards the OH radical. We measured the total OH reactivity with the Comparative Reactivity Method together with atmospheric concentrations of the primary compounds emitted by the forest, main secondary species generated from the oxidation of isoprene, and main atmospheric constituents. We then compared the OH reactivity inferred by measured compounds and their oxidation rate coefficients with the measured total OH reactivity. This approach permits to identify the presence of any primary emitted biogenic compound, unknown before and relevant for OH oxidation; or any secondary generated compound whose associated chemical mechanism is not well established. Our results show higher OH reactivity inside the canopy, with peaks up to 78 s-1, when isoprene concentration reached ~20 ppb due to temperature and PAR increase. Such high level of OH reactivity has only been observed in the tropics so far. Furthermore, our measured total OH reactivity closes the total amount of reactive species present in this specific forest, suggesting that we quantified precisely both the primary emitted species as well as the secondary generated products.

Resistance to downy mildew in lettuce ‘La Brillante’ is conferred by dm50 gene and multiple QTL

USDA-ARS?s Scientific Manuscript database

Many cultivars of lettuce (Lactuca sativa L.) are susceptible to downy mildew, a nearly globally ubiquitous disease caused by Bremia lactucae. We previously determined that Batavia type cultivar La Brillante has a high level of field resistance to the disease in California. Testing of a mapping popu...

Field evaluation of an expertise-based formal decision system for fungicide management of grapevine downy and powdery mildews.

PubMed

Delière, Laurent; Cartolaro, Philippe; Léger, Bertrand; Naud, Olivier

2015-09-01

In France, viticulture accounts for 20% of the phytochemicals sprayed in agriculture, and 80% of grapevine pesticides target powdery and downy mildews. European policies promote pesticide use reduction, and new methods for low-input disease management are needed for viticulture. Here, we present the assessment, in France, of Mildium, a new decision support system for the management of grapevine mildews. A 4 year assessment trial of Mildium has been conducted in a network of 83 plots distributed across the French vineyards. In most vineyards, Mildium has proved to be successful at protecting the crop while reducing by 30-50% the number of treatments required when compared with grower practices. The design of Mildium results from the formalisation of a common management of both powdery and downy mildews and eventually leads to a significant fungicide reduction at the plot scale. It could encourage stakeholders to design customised farm-scale and low-chemical-input decision support methods. © 2014 Society of Chemical Industry.

Identification and characterization of potential NBS-encoding resistance genes and induction kinetics of a putative candidate gene associated with downy mildew resistance in Cucumis

PubMed Central

2010-01-01

Background Due to the variation and mutation of the races of Pseudoperonospora cubensis, downy mildew has in recent years become the most devastating leaf disease of cucumber worldwide. Novel resistance to downy mildew has been identified in the wild Cucumis species, C. hystrix Chakr. After the successful hybridization between C. hystrix and cultivated cucumber (C. sativus L.), an introgression line (IL5211S) was identified as highly resistant to downy mildew. Nucleotide-binding site and leucine-rich repeat (NBS-LRR) genes are the largest class of disease resistance genes cloned from plant with highly conserved domains, which can be used to facilitate the isolation of candidate genes associated with downy mildew resistance in IL5211S. Results Degenerate primers that were designed based on the conserved motifs in the NBS domain of resistance (R) proteins were used to isolate NBS-type sequences from IL5211S. A total of 28 sequences were identified and named as cucumber (C. sativus = CS) resistance gene analogs as CSRGAs. Polygenetic analyses separated these sequences into four different classes. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis showed that these CSRGAs expressed at different levels in leaves, roots, and stems. In addition, introgression from C. hystrix induced expression of the partial CSRGAs in cultivated cucumber, especially CSRGA23, increased four-fold when compared to the backcross parent CC3. Furthermore, the expression of CSRGA23 under P. cubensis infection and abiotic stresses was also analyzed at different time points. Results showed that the P. cubensis treatment and four tested abiotic stimuli, MeJA, SA, ABA, and H2O2, triggered a significant induction of CSRGA23 within 72 h of inoculation. The results indicate that CSRGA23 may play a critical role in protecting cucumber against P. cubensis through a signaling the pathway triggered by these molecules. Conclusions Four classes of NBS-type RGAs were successfully isolated

Genotyping-by-sequencing of a bi-parental mapping population segregating for downy mildew resistance in hop (Humulus lupulus L.)

USDA-ARS?s Scientific Manuscript database

Breeding for resistance to downy mildew in hop has proved difficult presumably because of the highly quantitative nature of genetic control over expression with environment playing a large role in determining phenotype. We hypothesize that eliminating environmental influences over the expression of...

Discovery and introgression of the wild sunflower-derived novel downy mildew resistance gene Pl 19 in confection sunflower (Helianthus annuus L.).

PubMed

Zhang, Z W; Ma, G J; Zhao, J; Markell, S G; Qi, L L

2017-01-01

A new downy mildew resistance gene, Pl 19 , was identified from wild Helianthus annuus accession PI 435414, introduced to confection sunflower, and genetically mapped to linkage group 4 of the sunflower genome. Wild Helianthus annuus accession PI 435414 exhibited resistance to downy mildew, which is one of the most destructive diseases to sunflower production globally. Evaluation of the 140 BC 1 F 2:3 families derived from the cross of CMS CONFSCLB1 and PI 435414 against Plasmopara halstedii race 734 revealed that a single dominant gene controls downy mildew resistance in the population. Bulked segregant analysis conducted in the BC 1 F 2 population with 860 simple sequence repeat (SSR) markers indicated that the resistance derived from wild H. annuus was associated with SSR markers located on linkage group (LG) 4 of the sunflower genome. To map and tag this resistance locus, designated Pl 19 , 140 BC 1 F 2 individuals were used to construct a linkage map of the gene region. Two SSR markers, ORS963 and HT298, were linked to Pl 19 within a distance of 4.7 cM. After screening 27 additional single nucleotide polymorphism (SNP) markers previously mapped to this region, two flanking SNP markers, NSA_003564 and NSA_006089, were identified as surrounding the Pl 19 gene at a distance of 0.6 cM from each side. Genetic analysis indicated that Pl 19 is different from Pl 17 , which had previously been mapped to LG4, but is closely linked to Pl 17 . This new gene is highly effective against the most predominant and virulent races of P. halstedii currently identified in North America and is the first downy mildew resistance gene that has been transferred to confection sunflower. The selected resistant germplasm derived from homozygous BC 2 F 3 progeny provides a novel gene for use in confection sunflower breeding programs.

MALDI-based intact spore mass spectrometry of downy and powdery mildews.

PubMed

Chalupová, Jana; Sedlářová, Michaela; Helmel, Michaela; Rehulka, Pavel; Marchetti-Deschmann, Martina; Allmaier, Günter; Sebela, Marek

2012-08-01

Fast and easy identification of fungal phytopathogens is of great importance in agriculture. In this context, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has emerged as a powerful tool for analyzing microorganisms. This study deals with a methodology for MALDI-TOF MS-based identification of downy and powdery mildews representing obligate biotrophic parasites of crop plants. Experimental approaches for the MS analyses were optimized using Bremia lactucae, cause of lettuce downy mildew, and Oidium neolycopersici, cause of tomato powdery mildew. This involved determining a suitable concentration of spores in the sample, selection of a proper MALDI matrix, looking for the optimal solvent composition, and evaluation of different sample preparation methods. Furthermore, using different MALDI target materials and surfaces (stainless steel vs polymer-based) and applying various conditions for sample exposure to the acidic MALDI matrix system were investigated. The dried droplet method involving solvent evaporation at room temperature was found to be the most suitable for the deposition of spores and MALDI matrix on the target and the subsequent crystallization. The concentration of spore suspension was optimal between 2 and 5 × 10(9) spores per ml. The best peptide/protein profiles (in terms of signal-to-noise ratio and number of peaks) were obtained by combining ferulic and sinapinic acids as a mixed MALDI matrix. A pretreatment of the spore cell wall with hydrolases was successfully introduced prior to MS measurements to obtain more pronounced signals. Finally, a novel procedure was developed for direct mass spectra acquisition from infected plant leaves. Copyright © 2012 John Wiley & Sons, Ltd.

A first linkage map and downy mildew resistance QTL discovery for sweet basil (Ocimum basilicum) facilitated by double digestion restriction site associated DNA sequencing (ddRADseq).

PubMed

Pyne, Robert; Honig, Josh; Vaiciunas, Jennifer; Koroch, Adolfina; Wyenandt, Christian; Bonos, Stacy; Simon, James

2017-01-01

Limited understanding of sweet basil (Ocimum basilicum L.) genetics and genome structure has reduced efficiency of breeding strategies. This is evidenced by the rapid, worldwide dissemination of basil downy mildew (Peronospora belbahrii) in the absence of resistant cultivars. In an effort to improve available genetic resources, expressed sequence tag simple sequence repeat (EST-SSR) and single nucleotide polymorphism (SNP) markers were developed and used to genotype the MRI x SB22 F2 mapping population, which segregates for response to downy mildew. SNP markers were generated from genomic sequences derived from double digestion restriction site associated DNA sequencing (ddRADseq). Disomic segregation was observed in both SNP and EST-SSR markers providing evidence of an O. basilicum allotetraploid genome structure and allowing for subsequent analysis of the mapping population as a diploid intercross. A dense linkage map was constructed using 42 EST-SSR and 1,847 SNP markers spanning 3,030.9 cM. Multiple quantitative trait loci (QTL) model (MQM) analysis identified three QTL that explained 37-55% of phenotypic variance associated with downy mildew response across three environments. A single major QTL, dm11.1 explained 21-28% of phenotypic variance and demonstrated dominant gene action. Two minor QTL dm9.1 and dm14.1 explained 5-16% and 4-18% of phenotypic variance, respectively. Evidence is provided for an additive effect between the two minor QTL and the major QTL dm11.1 increasing downy mildew susceptibility. Results indicate that ddRADseq-facilitated SNP and SSR marker genotyping is an effective approach for mapping the sweet basil genome.

[Exome sequencing revealed Allan-Herndon-Dudley syndrome underlying multiple disabilities].

PubMed

Arvio, Maria; Philips, Anju K; Ahvenainen, Minna; Somer, Mirja; Kalscheuer, Vera; Järvelä, Irma

2014-01-01

Normal function of the thyroid gland is the cornerstone of a child's mental development and physical growth. We describe a Finnish family, in which the diagnosis of three brothers became clear after investigations that lasted for more than 30 years. Two of the sons have already died. DNA analysis of the third one, a 16-year-old boy, revealed in exome sequencing of the complete X chromosome a mutation in the SLC16A2 gene, i.e. MCT8, coding for a thyroid hormone transport protein. Allan-Herndon-Dudley syndrome was thus shown to be the cause of multiple disabilities.

QTL mapping of downy and powdery mildew resistances in PI 197088 cucumber with genotyping-by-sequencing in RIL population

USDA-ARS?s Scientific Manuscript database

The downy mildew (DM) and powdery mildew (PM) are the two most important foliar diseases of cucurbit crops worldwide. The cucumber accession PI 197088 exhibits high level resistances to both pathogens. We conducted QTL mapping to identified genes underlying host resistance for DM and PM in PI 197088...

Phosphorus component in AnnAGNPS

USGS Publications Warehouse

Yuan, Y.; Bingner, R.L.; Theurer, F.D.; Rebich, R.A.; Moore, P.A.

2005-01-01

The USDA Annualized Agricultural Non-Point Source Pollution model (AnnAGNPS) has been developed to aid in evaluation of watershed response to agricultural management practices. Previous studies have demonstrated the capability of the model to simulate runoff and sediment, but not phosphorus (P). The main purpose of this article is to evaluate the performance of AnnAGNPS on P simulation using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. A sensitivity analysis was performed to identify input parameters whose impact is the greatest on P yields. Sensitivity analysis results indicate that the most sensitive variables of those selected are initial soil P contents, P application rate, and plant P uptake. AnnAGNPS simulations of dissolved P yield do not agree well with observed dissolved P yield (Nash-Sutcliffe coefficient of efficiency of 0.34, R2 of 0.51, and slope of 0.24); however, AnnAGNPS simulations of total P yield agree well with observed total P yield (Nash-Sutcliffe coefficient of efficiency of 0.85, R2 of 0.88, and slope of 0.83). The difference in dissolved P yield may be attributed to limitations in model simulation of P processes. Uncertainties in input parameter selections also affect the model's performance.

First report of downy mildew caused by Plasmopara halstedii on black-eyed susan (Rudbeckia fulgida cv. ‘Goldsturm’) in Maryland

USDA-ARS?s Scientific Manuscript database

The North American perennial black-eyed Susan (Rudbeckia fulgida cv. ‘Goldsturm’) is an important nursery crop, prized by gardeners and landscapers for its persistent bloom and ease of cultivation. In September 2013 disease symptoms characteristic of downy mildew were observed from multiple plants a...

A first linkage map and downy mildew resistance QTL discovery for sweet basil (Ocimum basilicum) facilitated by double digestion restriction site associated DNA sequencing (ddRADseq)

PubMed Central

Honig, Josh; Vaiciunas, Jennifer; Koroch, Adolfina; Wyenandt, Christian; Bonos, Stacy; Simon, James

2017-01-01

Limited understanding of sweet basil (Ocimum basilicum L.) genetics and genome structure has reduced efficiency of breeding strategies. This is evidenced by the rapid, worldwide dissemination of basil downy mildew (Peronospora belbahrii) in the absence of resistant cultivars. In an effort to improve available genetic resources, expressed sequence tag simple sequence repeat (EST-SSR) and single nucleotide polymorphism (SNP) markers were developed and used to genotype the MRI x SB22 F2 mapping population, which segregates for response to downy mildew. SNP markers were generated from genomic sequences derived from double digestion restriction site associated DNA sequencing (ddRADseq). Disomic segregation was observed in both SNP and EST-SSR markers providing evidence of an O. basilicum allotetraploid genome structure and allowing for subsequent analysis of the mapping population as a diploid intercross. A dense linkage map was constructed using 42 EST-SSR and 1,847 SNP markers spanning 3,030.9 cM. Multiple quantitative trait loci (QTL) model (MQM) analysis identified three QTL that explained 37–55% of phenotypic variance associated with downy mildew response across three environments. A single major QTL, dm11.1 explained 21–28% of phenotypic variance and demonstrated dominant gene action. Two minor QTL dm9.1 and dm14.1 explained 5–16% and 4–18% of phenotypic variance, respectively. Evidence is provided for an additive effect between the two minor QTL and the major QTL dm11.1 increasing downy mildew susceptibility. Results indicate that ddRADseq-facilitated SNP and SSR marker genotyping is an effective approach for mapping the sweet basil genome. PMID:28922359

Genetics and mapping of a novel downy mildew resistance gene, Pl(18), introgressed from wild Helianthus argophyllus into cultivated sunflower (Helianthus annuus L.).

PubMed

Qi, L L; Foley, M E; Cai, X W; Gulya, T J

2016-04-01

A novel downy mildew resistance gene, Pl(18), was introgressed from wild Helianthus argophyllus into cultivated sunflower and genetically mapped to linkage group 2 of the sunflower genome. The new germplasm, HA-DM1, carrying Pl(18) has been released to the public. Sunflower downy mildew (DM) is considered to be the most destructive foliar disease that has spread to every major sunflower-growing country of the world, except Australia. A new dominant downy mildew resistance gene (Pl 18) transferred from wild Helianthus argophyllus (PI 494573) into cultivated sunflower was mapped to linkage group (LG) 2 of the sunflower genome using bulked segregant analysis with 869 simple sequence repeat (SSR) markers. Phenotyping 142 BC1F2:3 families derived from the cross of HA 89 and H. argophyllus confirmed the single gene inheritance of resistance. Since no other Pl gene has been mapped to LG2, this gene was novel and designated as Pl (18). SSR markers CRT214 and ORS203 flanked Pl(18) at a genetic distance of 1.1 and 0.4 cM, respectively. Forty-six single nucleotide polymorphism (SNP) markers that cover the Pl(18) region were surveyed for saturation mapping of the region. Six co-segregating SNP markers were 1.2 cM distal to Pl(18), and another four co-segregating SNP markers were 0.9 cM proximal to Pl(18). The new BC2F4-derived germplasm, HA-DM1, carrying Pl(18) has been released to the public. This new line is highly resistant to all Plasmopara halstedii races identified in the USA providing breeders with an effective new source of resistance against downy mildew in sunflower. The molecular markers that were developed will be especially useful in marker-assisted selection and pyramiding of Pl resistance genes because of their close proximity to the gene and the availability of high-throughput SNP detection assays.

Obituary: Anne Barbara Underhill, 1920-2003

NASA Astrophysics Data System (ADS)

Roman, Nancy Grace

2003-12-01

Anne was born in Vancouver, British Columbia on 12 June 1920. Her parents were Frederic Clare Underhill, a civil engineer and Irene Anna (née Creery) Underhill. She had a twin brother and three younger brothers. As a young girl she was active in Girl Guides and graduated from high school winning the Lieutenant Governor's medal as one of the top students in the Province. She also excelled in high school sports. Her mother died when Anne was 18 and, while undertaking her university studies, Anne assisted in raising her younger brothers. Her twin brother was killed in Italy during World War II (1944), a loss that Anne felt deeply. Possibly because of fighting to get ahead in astronomy, a field overwhelming male when she started, she frequently appeared combative. At the University of British Columbia, Anne obtained a BA (honors) in Chemistry (1942), followed by a MA in 1944. After working for the NRC in Montreal for a year, she studied at the University of Toronto prior to entering the University of Chicago in 1946 to obtain her PhD. Her thesis was the first model computed for a multi-layered stellar atmosphere (1948). During this time she worked with Otto Struve, developing a lifetime interest in hot stars and the analysis of their high dispersion spectra. She received two fellowships from the University Women of Canada. She received a U.S. National Research Fellowship to work at the Copenhagen Observatory, and upon its completion, she returned to British Columbia to work at the Dominion Astrophysical Observatory as a research scientist from 1949--1962. During this period she spent a year at Harvard University as a visiting professor and at Princeton where she used their advanced computer to write the first code for modeling stellar atmospheres. Anne was invited to the University of Utrecht (Netherlands) as a full professor in 1962. She was an excellent teacher, well liked by the students in her classes, and by the many individuals that she guided throughout her

Obituary: Allan R. Sandage (1926-2010)

NASA Astrophysics Data System (ADS)

Devorkin, David

2011-12-01

Allan Rex Sandage died of pancreatic cancer at his home in San Gabriel, California, in the shadow of Mount Wilson, on November 13, 2010. Born in Iowa City, Iowa, on June 18, 1926, he was 84 years old at his death, leaving his wife, former astronomer Mary Connelly Sandage, and two sons, David and John. He also left a legacy to the world of astronomical knowledge that has long been universally admired and appreciated, making his name synonymous with late 20th-Century observational cosmology. The only child of Charles Harold Sandage, a professor of advertising who helped establish that academic specialty after obtaining a PhD in business administration, and Dorothy Briggs Sandage, whose father was president of Graceland College in Iowa, Allan Sandage grew up in a thoroughly intellectual, university oriented atmosphere but also a peripatetic one taking him to Philadelphia and later to Illinois as his father rose in his career. During his 2 years in Philadelphia, at about age eleven, Allan developed a curiosity about astronomy stimulated by a friend's interest. His father bought him a telescope and he used it to systematically record sunspots, and later attempted to make a larger 6-inch reflector, a project left uncompleted. As a teenager Allan read widely, especially astronomy books of all kinds, recalling in particular The Glass Giant of Palomar as well as popular works by Eddington and Hubble (The Realm of the Nebulae) in the early 1940s. Although his family was Mormon, of the Reorganized Church, he was not practicing, though he later sporadically attended a Methodist church in Oxford, Iowa during his college years. Sandage knew by his high school years that he would engage in some form of intellectual life related to astronomy. He particularly recalls an influential science teacher at Miami University in Oxford, Ohio named Ray Edwards, who inspired him to think critically and "not settle for any hand-waving of any kind." [Interview of Allan Rex Sandage by Spencer

Which morphological characteristics are most influenced by the host matrix in downy mildews? A case study in Pseudoperonospora cubensis.

PubMed

Runge, Fabian; Ndambi, Beninweck; Thines, Marco

2012-01-01

Before the advent of molecular phylogenetics, species concepts in the downy mildews, an economically important group of obligate biotrophic oomycete pathogens, have mostly been based upon host range and morphology. While molecular phylogenetic studies have confirmed a narrow host range for many downy mildew species, others, like Pseudoperonospora cubensis affect even different genera. Although often morphological differences were found for new, phylogenetically distinct species, uncertainty prevails regarding their host ranges, especially regarding related plants that have been reported as downy mildew hosts, but were not included in the phylogenetic studies. In these cases, the basis for deciding if the divergence in some morphological characters can be deemed sufficient for designation as separate species is uncertain, as observed morphological divergence could be due to different host matrices colonised. The broad host range of P. cubensis (ca. 60 host species) renders this pathogen an ideal model organism for the investigation of morphological variations in relation to the host matrix and to evaluate which characteristics are best indicators for conspecificity or distinctiveness. On the basis of twelve morphological characterisitcs and a set of twelve cucurbits from five different Cucurbitaceae tribes, including the two species, Cyclanthera pedata and Thladiantha dubia, hitherto not reported as hosts of P. cubensis, a significant influence of the host matrix on pathogen morphology was found. Given the high intraspecific variation of some characteristics, also their plasticity has to be taken into account. The implications for morphological species determination and the confidence limits of morphological characteristics are discussed. For species delimitations in Pseudoperonospora it is shown that the ratio of the height of the first ramification to the sporangiophore length, ratio of the longer to the shorter ultimate branchlet, and especially the length and

Which Morphological Characteristics Are Most Influenced by the Host Matrix in Downy Mildews? A Case Study in Pseudoperonospora cubensis

PubMed Central

Runge, Fabian; Ndambi, Beninweck; Thines, Marco

2012-01-01

Before the advent of molecular phylogenetics, species concepts in the downy mildews, an economically important group of obligate biotrophic oomycete pathogens, have mostly been based upon host range and morphology. While molecular phylogenetic studies have confirmed a narrow host range for many downy mildew species, others, like Pseudoperonospora cubensis affect even different genera. Although often morphological differences were found for new, phylogenetically distinct species, uncertainty prevails regarding their host ranges, especially regarding related plants that have been reported as downy mildew hosts, but were not included in the phylogenetic studies. In these cases, the basis for deciding if the divergence in some morphological characters can be deemed sufficient for designation as separate species is uncertain, as observed morphological divergence could be due to different host matrices colonised. The broad host range of P. cubensis (ca. 60 host species) renders this pathogen an ideal model organism for the investigation of morphological variations in relation to the host matrix and to evaluate which characteristics are best indicators for conspecificity or distinctiveness. On the basis of twelve morphological characterisitcs and a set of twelve cucurbits from five different Cucurbitaceae tribes, including the two species, Cyclanthera pedata and Thladiantha dubia, hitherto not reported as hosts of P. cubensis, a significant influence of the host matrix on pathogen morphology was found. Given the high intraspecific variation of some characteristics, also their plasticity has to be taken into account. The implications for morphological species determination and the confidence limits of morphological characteristics are discussed. For species delimitations in Pseudoperonospora it is shown that the ratio of the height of the first ramification to the sporangiophore length, ratio of the longer to the shorter ultimate branchlet, and especially the length and

An Interview with Allan Wigfield: A Giant on Research on Expectancy Value, Motivation, and Reading Achievement

ERIC Educational Resources Information Center

Bembenutty, Hefer

2012-01-01

This article presents an interview with Allan Wigfield, professor and chair of the Department of Human Development and distinguished scholar-teacher at the University of Maryland. He has authored more than 100 peer-reviewed journal articles and book chapters on children's motivation and other topics. He is a fellow of Division 15 (Educational…

Discrimination of isotrigon textures using the Rényi entropy of Allan variances.

PubMed

Gabarda, Salvador; Cristóbal, Gabriel

2008-09-01

We present a computational algorithm for isotrigon texture discrimination. The aim of this method consists in discriminating isotrigon textures against a binary random background. The extension of the method to the problem of multitexture discrimination is considered as well. The method relies on the fact that the information content of time or space-frequency representations of signals, including images, can be readily analyzed by means of generalized entropy measures. In such a scenario, the Rényi entropy appears as an effective tool, given that Rényi measures can be used to provide information about a local neighborhood within an image. Localization is essential for comparing images on a pixel-by-pixel basis. Discrimination is performed through a local Rényi entropy measurement applied on a spatially oriented 1-D pseudo-Wigner distribution (PWD) of the test image. The PWD is normalized so that it may be interpreted as a probability distribution. Prior to the calculation of the texture's PWD, a preprocessing filtering step replaces the original texture with its localized spatially oriented Allan variances. The anisotropic structure of the textures, as revealed by the Allan variances, turns out to be crucial later to attain a high discrimination by the extraction of Rényi entropy measures. The method has been empirically evaluated with a family of isotrigon textures embedded in a binary random background. The extension to the case of multiple isotrigon mosaics has also been considered. Discrimination results are compared with other existing methods.

The History of Allan Hills 84001 Revised: Multiple Shock Events

NASA Technical Reports Server (NTRS)

Treiman, Allan H.

1998-01-01

The geologic history of Martian meteorite Allan Hills (ALH) 84001 is more complex than previously recognized, with evidence for four or five crater-forming impacts onto Mars. This history of repeated deformation and shock metamorphism appears to weaken some arguments that have been offered for and against the hypothesis of ancient Martian life in ALH 84001. Allan Hills 84001 formed originally from basaltic magma. Its first impact event (I1) is inferred from the deformation (D1) that produced the granular-textured bands ("crush zones") that transect the original igneous fabric. Deformation D1 is characterized by intense shear and may represent excavation or rebound flow of rock beneath a large impact crater. An intense thermal metamorphism followed D1 and may be related to it. The next impact (I2) produced fractures, (Fr2) in which carbonate "pancakes" were deposited and produced feldspathic glass from some of the igneous feldspars and silica. After I2, carbonate pancakes and globules were deposited in Fr2 fractures and replaced feldspathic glass and possibly crystalline silicates. Next, feldspars, feldspathic glass, and possibly some carbonates were mobilized and melted in the third impact (I3). Microfaulting, intense fracturing, and shear are also associated with 13. In the fourth impact (I4), the rock was fractured and deformed without significant heating, which permitted remnant magnetization directions to vary across fracture surfaces. Finally, ALH 84001 was ejected from Mars in event I5, which could be identical to I4. This history of multiple impacts is consistent with the photogeology of the Martian highlands and may help resolve some apparent contradictions among recent results on ALH 84001. For example, the submicron rounded magnetite grains in the carbonate globules could be contemporaneous with carbonate deposition, whereas the elongate magnetite grains, epitaxial on carbonates, could be ascribed to vapor-phase deposition during I3.

Genetic modification of European winegrapes with genes from an American wild relative confers resistance to the major diseases powdery and downy mildew

USDA-ARS?s Scientific Manuscript database

The two most economically important diseases of grapevine cultivation worldwide are caused by the fungal pathogen powdery mildew (Erysiphe necator syn. Uncinula necator) and the oomycete, downy mildew (Plasmopara viticola). These pathogens, endemic to North America, were introduced into Europe in t...

Effect of Pseudomonas spp on infection of Peronosporaparasitica (Pers. Fr), the pathogen of downy mildew on Chinese cabbage

NASA Astrophysics Data System (ADS)

Damiri, N.; Mulawarman; Umayah, A.; Agustin, S. E.; Rahmiyah, M.

2018-01-01

This research was conducted to study the effect of the application of Pseudomonasspp on infection of Peronosporaparasitica (Pers. Fr), the pathogen of Downy mildew on Chinese cabbage. The research was conducted in the laboratory and greenhouse Department of Plant Pests and Diseases Faculty of Agriculture Sriwijaya University, Inderalaya, OganIlir South Sumatra Indonesia. The research was conducted in the laboratory and greenhouse Department of Plant Pests and Diseases Faculty of Agriculture Sriwijaya University, Inderalaya, Ogan Ilir South Sumatra Indonesia. The research was conducted using Completely Randomized Design with ten treatments including control. ie: isolate A, Isolate B, isolate C, isolate D, isolate E, isolate F, isolate G, isolate H, isolate I and control. Each treatment consists of four replications. Results of the study showed that the application of Pseudomonas spp. can suppress the infection of P. parasitica on Chinese cabbage. The lowest disease intensity was shown by treatment C (isolate Pseudomonas sp.) which was significantly different from control. The best treatment in suppressing disease severity of downy mildew on chinese cabbage was isolate H which had disease severity of 37.07 percent, which was significantly different from control and other treatment.

Pl17 is a novel gene independent of known downy mildew resistance genes in the cultivated sunflower (Helianthus annuus L.)

USDA-ARS?s Scientific Manuscript database

Downy mildew (DM), caused by Plasmopara halstedii (Farl.) Berl. et de Toni, is one of the serious sunflower diseases in the world due to its high virulence and the variability of the pathogen. DM resistance in the USDA inbred line, HA 458, has been shown to be effective against all virulent races of...

Evaluating the Duration and Continuity of Potential Climate Records From the Allan Hills Blue Ice Area, East Antarctica

NASA Astrophysics Data System (ADS)

Kehrl, Laura; Conway, Howard; Holschuh, Nicholas; Campbell, Seth; Kurbatov, Andrei V.; Spaulding, Nicole E.

2018-05-01

The current ice core record extends back 800,000 years. Geologic and glaciological evidence suggests that the Allan Hills Blue Ice Area, East Antarctica, may preserve a continuous record that extends further back in time. In this study, we use ice-penetrating radar and existing age constraints to map the internal stratigraphy and age structure of the Allan Hills Main Ice Field. The dated isochrones provide constraints for an ice flow model to estimate the age of ice near the bed. Previous drilling in the region recovered stratigraphically disturbed sections of ice up to 2.7 million years old. Our study identifies a site 5 km upstream, which likely preserves a continuous record through Marine Isotope Stage 11 with the possibility that the record extends back 1 million years. Such records would provide new insight into the past climate and glacial history of the Ross Sea Sector.

Detection of the downy mildew pathogens of spinach (Peronospora effusa) and beet (P. schachtii) using spore traps and quantitative PCR assays

USDA-ARS?s Scientific Manuscript database

Downy mildew of spinach, caused by Peronospora effusa, is a disease constraint on spinach production worldwide. The aim of this study was to develop a real-time quantitative PCR assay for detection of airborne inoculum of P. effusa in California. This type of assay may, in combination with disease-...

Allan deviation analysis of financial return series

NASA Astrophysics Data System (ADS)

Hernández-Pérez, R.

2012-05-01

We perform a scaling analysis for the return series of different financial assets applying the Allan deviation (ADEV), which is used in the time and frequency metrology to characterize quantitatively the stability of frequency standards since it has demonstrated to be a robust quantity to analyze fluctuations of non-stationary time series for different observation intervals. The data used are opening price daily series for assets from different markets during a time span of around ten years. We found that the ADEV results for the return series at short scales resemble those expected for an uncorrelated series, consistent with the efficient market hypothesis. On the other hand, the ADEV results for absolute return series for short scales (first one or two decades) decrease following approximately a scaling relation up to a point that is different for almost each asset, after which the ADEV deviates from scaling, which suggests that the presence of clustering, long-range dependence and non-stationarity signatures in the series drive the results for large observation intervals.

Genotyping-by-sequencing targeting of a novel downy mildew resistance gene Pl20 from wild Helianthus argophyllus for sunflower (Helianthus annuus L.)

USDA-ARS?s Scientific Manuscript database

Downy mildew (DM) caused by Plasmopara halstedii is one of the most destructive diseases in the world that severely impacts sunflower production. Management tools for DM include the destruction of volunteer sunflower plants, fungicides applied as seed treatments, and planting DM-resistant hybrids; t...

Applications of artificial neural networks (ANNs) in food science.

PubMed

Huang, Yiqun; Kangas, Lars J; Rasco, Barbara A

2007-01-01

Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs hold a great deal of promise for modeling complex tasks in process control and simulation and in applications of machine perception including machine vision and electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in the field.

Multi-locus tree and species tree approaches toward resolving a complex clade of downy mildews (Straminipila, Oomycota), including pathogens of beet and spinach

USDA-ARS?s Scientific Manuscript database

Accurate species determination of plant pathogens is a prerequisite for their control and quarantine, and further for assessing their potential threat to crops. The family Peronosporaceae (Straminipila; Oomycota) consists of obligate biotrophic pathogens that cause downy mildew disease on angiosperm...

Pl(17) is a novel gene independent of known downy mildew resistance genes in the cultivated sunflower (Helianthus annuus L.).

PubMed

Qi, L L; Long, Y M; Jan, C C; Ma, G J; Gulya, T J

2015-04-01

Pl 17, a novel downy mildew resistance gene independent of known downy mildew resistance genes in sunflowers, was genetically mapped to linkage group 4 of the sunflower genome. Downy mildew (DM), caused by Plasmopara halstedii (Farl.). Berl. et de Toni, is one of the serious sunflower diseases in the world due to its high virulence and the variability of the pathogen. DM resistance in the USDA inbred line, HA 458, has been shown to be effective against all virulent races of P. halstedii currently identified in the USA. To determine the chromosomal location of this resistance, 186 F 2:3 families derived from a cross of HA 458 with HA 234 were phenotyped for their resistance to race 734 of P. halstedii. The segregation ratio of the population supported that the resistance was controlled by a single dominant gene, Pl 17. Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) primers were used to identify molecular markers linked to Pl 17. Bulked segregant analysis using 849 SSR markers located Pl 17 to linkage group (LG) 4, which is the first DM gene discovered in this linkage group. An F2 population of 186 individuals was screened with polymorphic SSR and SNP primers from LG4. Two flanking markers, SNP SFW04052 and SSR ORS963, delineated Pl 17 in an interval of 3.0 cM. The markers linked to Pl 17 were validated in a BC3 population. A search for the physical location of flanking markers in sunflower genome sequences revealed that the Pl 17 region had a recombination frequency of 0.59 Mb/cM, which was a fourfold higher recombination rate relative to the genomic average. This region can be considered amenable to molecular manipulation for further map-based cloning of Pl 17.

Exogenous Trehalose Treatment Enhances the Activities of Defense-Related Enzymes and Triggers Resistance against Downy Mildew Disease of Pearl Millet.

PubMed

Govind, Sharathchandra R; Jogaiah, Sudisha; Abdelrahman, Mostafa; Shetty, Hunthrike S; Tran, Lam Son P

2016-01-01

In recent years, diverse physiological functions of various sugars are the subject of investigations. Their roles in signal transduction in plant responses to adverse biotic and abiotic stress conditions have become apparent, and growing scientific evidence has indicated that disaccharides like sucrose and trehalose mediate plant defense responses in similar way as those induced by elicitors against the pathogens. Trehalose is a well-known metabolic osmoregulator, stress-protectant and non-reducing disaccharide existing in a variety of organisms, including fungi, bacteria, and plants. Commercially procured trehalose was applied to seeds of susceptible pearl millet ( Pennisetum glaucum ) cultivar "HB3," and tested for its ability to reduce downy mildew disease incidence by induction of resistance. Seed treatment with trehalose at 200 mM for 9 h recorded 70.25% downy mildew disease protection, followed by those with 100 and 50 mM trehalose which offered 64.35 and 52.55% defense, respectively, under greenhouse conditions. Furthermore, under field conditions treatment with 200 mM trehalose for 9 h recorded 67.25% downy mildew disease protection, and reduced the disease severity to 32.75% when compared with untreated control which displayed 90% of disease severity. Trehalose did not affect either sporangial formation or zoospore release from sporangia, indicating that the reduction in disease incidence was not due to direct inhibition but rather through induction of resistance responses in the host. Additionally, trehalose was shown to enhance the levels of polyphenol oxidase, phenylalanine ammonia lyase, and peroxidase, which are known as markers of both biotic and abiotic stress responses. Our study shows that osmoregulators like trehalose could be used to protect plants against pathogen attacks by seed treatment, thus offering dual benefits of biotic and abiotic stress tolerance.

Exogenous Trehalose Treatment Enhances the Activities of Defense-Related Enzymes and Triggers Resistance against Downy Mildew Disease of Pearl Millet

PubMed Central

Govind, Sharathchandra R.; Jogaiah, Sudisha; Abdelrahman, Mostafa; Shetty, Hunthrike S.; Tran, Lam-Son P.

2016-01-01

In recent years, diverse physiological functions of various sugars are the subject of investigations. Their roles in signal transduction in plant responses to adverse biotic and abiotic stress conditions have become apparent, and growing scientific evidence has indicated that disaccharides like sucrose and trehalose mediate plant defense responses in similar way as those induced by elicitors against the pathogens. Trehalose is a well-known metabolic osmoregulator, stress-protectant and non-reducing disaccharide existing in a variety of organisms, including fungi, bacteria, and plants. Commercially procured trehalose was applied to seeds of susceptible pearl millet (Pennisetum glaucum) cultivar “HB3,” and tested for its ability to reduce downy mildew disease incidence by induction of resistance. Seed treatment with trehalose at 200 mM for 9 h recorded 70.25% downy mildew disease protection, followed by those with 100 and 50 mM trehalose which offered 64.35 and 52.55% defense, respectively, under greenhouse conditions. Furthermore, under field conditions treatment with 200 mM trehalose for 9 h recorded 67.25% downy mildew disease protection, and reduced the disease severity to 32.75% when compared with untreated control which displayed 90% of disease severity. Trehalose did not affect either sporangial formation or zoospore release from sporangia, indicating that the reduction in disease incidence was not due to direct inhibition but rather through induction of resistance responses in the host. Additionally, trehalose was shown to enhance the levels of polyphenol oxidase, phenylalanine ammonia lyase, and peroxidase, which are known as markers of both biotic and abiotic stress responses. Our study shows that osmoregulators like trehalose could be used to protect plants against pathogen attacks by seed treatment, thus offering dual benefits of biotic and abiotic stress tolerance. PMID:27895647

Enhancement of downy mildew disease resistance in pearl millet by the G_app7 bioactive compound produced by Ganoderma applanatum.

PubMed

Jogaiah, Sudisha; Shetty, Hunthrike Shekar; Ito, Shin-Ichi; Tran, Lam-Son Phan

2016-08-01

Pearl millet (Pennisetum glaucum) stands sixth among the most important cereal crops grown in the semi-arid and arid regions of the world. The downy mildew disease caused by Sclerospora graminicola, an oomycete pathogen, has been recognized as a major biotic constraint in pearl millet production. On the other hand, basidiomycetes are known to produce a large number of antimicrobial metabolites, providing a good source of anti-oomycete agrochemicals. Here, we report the discovery and efficacy of a compound, named G_app7, purified from Ganoderma applanatum on inhibition of growth and development of S. graminicola, as well as the effects of seed treatment with G_app7 on protection of pearl millet from downy mildew. G_app7 consistently demonstrated remarkable effects against S. graminicola by recording significant inhibition of sporangium formation (41.4%), zoospore release (77.5%) and zoospore motility (91%). Analyses of G_app7 compound using two-dimensional nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry revealed its close resemblance to metominostrobin, a derivative of strobilurin group of fungicides. Furthermore, the G_app7 was shown to stably maintain the inhibitory effects at different temperatures between 25 and 80 °C. In addition, the anti-oomycete activity of G_app7 was fairly stable for a period of at least 12 months at 4 °C and was only completely lost after being autoclaved. Seed treatment with G_app7 resulted in a significant increase in disease protection (63%) under greenhouse conditions compared with water control. The identification and isolation of this novel and functional anti-oomycete compound from G. applanatum provide a considerable agrochemical importance for plant protection against downy mildew in an environmentally safe and economical manner. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Incorporation of temperature and solar radiation thresholds to modify a lettuce downy mildew warning system.

PubMed

Wu, B M; van Bruggen, A H C; Subbarao, K V; Scherm, H

2002-06-01

ABSTRACT The effect of temperature on infection of lettuce by Bremia lactucae was investigated in controlled environment studies and in the field. In controlled conditions, lettuce seedlings inoculated with B. lactucae were incubated at 15, 20, 25, or 30 degrees C during a 4-h wet period immediately after inoculation or at the same temperatures during an 8-h dry period after the 4-h postinoculation wet period at 15 degrees C. High temperatures during wet and dry periods reduced subsequent disease incidence. Historical data from field studies in 1991 and 1992, in which days with or without infection had been identified, were analyzed by comparing average air temperatures during 0600 to 1000 and 1000 to 1400 Pacific standard time (PST) between the two groups of days. Days without infection had significantly higher temperatures (mean 21.4 degrees C) than days with infection (20.3 degrees C) during 1000 to 1400 PST (P < 0.01) but not during 0600 to 1000 PST. Therefore, temperature thresholds of 20 and 22 degrees C for the 3-h wet period after sunrise and the subsequent 4-h postpenetration period, respectively, were added to a previously developed disease warning system that predicts infection when morning leaf wetness lasts >/=4 h from 0600 PST. No infection was assumed to occur if average temperature during these periods exceeded the thresholds. Based on nonlinear regression and receiver operating characteristic curve analysis, the leaf wetness threshold of the previous warning system was also modified to >/=3-h leaf wetness (>/=0900 PST). Furthermore, by comparing solar radiation on days with infection and without infection, we determined that high solar radiation during 0500 to 0600 PST in conjunction with leaf wetness ending between 0900 and 1000 PST was associated with downy mildew infection. Therefore, instead of starting at 0600 PST, the calculation of the 3-h morning leaf wetness period was modified to start after sunrise, defined as the hour when measured

Grapevine Downy Mildew Plasmopara viticola Infection Elicits the Expression of Allergenic Pathogenesis-Related Proteins.

PubMed

Rossin, Giacomo; Villalta, Danilo; Martelli, Paola; Cecconi, Daniela; Polverari, Annalisa; Zoccatelli, Gianni

2015-01-01

Downy mildews are a group of microorganisms belonging to the Chromista kingdom that can infect specific plants. When growing on plant tissues these microbes can elicit the expression of pathogenesis-related proteins (PRs), a group of stress-induced proteins frequently described as allergens in many plant species. Our aim was to verify by a proteomic approach whether the allergic reactions experienced by a farmer working in a vineyard infected by Plasmopara viticola (Pv), the etiological agent of downy mildew, are elicited by PRs expressed by the grapevine upon infection or by allergens present in Pv. A skin prick test and prick-to-prick test with infected field grapevine leaves and control leaves were carried out. Field leaves and ad hoc Pv-inoculated leaves were compared by SDS-PAGE and IgE-immunoblotting with extracts from control leaves and Pv sporangia. IgE-binding proteins were further separated by two-dimensional electrophoresis and the positive spots analyzed by nanoHPLC-Chip and tandem mass spectrometry (MS/MS) for identification. Only infected leaves showed IgE-binding protein bands at 42 and 36 kDa. This agreed with the positive skin prick test experienced by the patient only with the infected leaves extract. Two-dimensional electrophoresis followed by MS/MS analysis led to the identification of PR-2 (β-1,3-glucanase) and harpin-binding protein 1 as putative allergens, the latter having never been reported before. The results indicate that Pv infection might represent a new source of plant allergens. © 2015 S. Karger AG, Basel.

Discovery and introgression of the wild sunflower-derived novel downy mildew resistance gene Pl19 in confection sunflower (Helianthus annuus L.)

USDA-ARS?s Scientific Manuscript database

Wild Helianthus annuus accession PI 435414 exhibited resistance to downy mildew, which is one of the most destructive diseases to sunflower production globally. Evaluation of the 140 BC1F2:3 families derived from the cross of CMS CONFSCLB1 and PI 435414 against Plasmopara halstedii race 734 revealed...

Allan Franklin, Shifting Standards: Experiments in Particle Physics in the Twentieth Century. Book Review

DOE PAGES

Pronskikh, Vitaly

2015-10-01

The book Shifting Standards is a valuable contribution to the literature on the history and philosophy of science and specifically to the philosophy of scientific experimentation, the discipline of which Allan Franklin is one of the outstanding scholars and founders. Here, the central focus of the book is the contemporary shift in the norms of representation of experimental results in particle physics as well as the increasing role and drawbacks of statistical standards of acceptance for those results.

Coupling spore traps and quantitative PCR assays for detection of the downy mildew pathogens of spinach (Peronospora effusa) and beet (Peronospora schachtii)

USDA-ARS?s Scientific Manuscript database

Downy mildew of spinach (Spinacia oleracea L.), caused by Peronospora effusa, is a disease constraint on production worldwide, including in California where the majority of United States spinach is grown. The aim of this study was to develop a real-time quantitative PCR (qPCR) assay for detection o...

An Overview of ANN Application in the Power Industry

NASA Technical Reports Server (NTRS)

Niebur, D.

1995-01-01

The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.

QTL mapping of downy and powdery mildew resistances in PI 197088 cucumber with genotyping-by-sequencing in RIL population.

PubMed

Wang, Yuhui; VandenLangenberg, Kyle; Wen, Changlong; Wehner, Todd C; Weng, Yiqun

2018-03-01

Host resistances in PI 197088 cucumber to downy and powdery mildew pathogens are conferred by 11 (3 with major effect) and 4 (1 major effect) QTL, respectively, and three of which are co-localized. The downy mildew (DM) and powdery mildew (PM) are the two most important foliar diseases of cucurbit crops worldwide. The cucumber accession PI 197088 exhibits high-level resistances to both pathogens. Here, we reported QTL mapping results for DM and PM resistances with 148 recombinant inbred lines from a cross between PI 197088 and the susceptible line 'Coolgreen'. Phenotypic data on responses to natural DM and PM infection were collected in multi-year and multi-location replicated field trials. A high-density genetic map with 2780 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing and 55 microsatellite markers was developed, which revealed genomic regions with segregation distortion and mis-assemblies in the '9930' cucumber draft genome. QTL analysis identified 11 and 4 QTL for DM and PM resistances accounting for more than 73.5 and 63.0% total phenotypic variance, respectively. Among the 11 DM resistance QTL, dm5.1, dm5.2, and dm5.3 were major-effect contributing QTL, whereas dm1.1, dm2.1, and dm6.2 conferred susceptibility. Of the 4 QTL for PM resistance, pm5.1 was the major-effect QTL explaining 32.4% phenotypic variance and the minor-effect QTL pm6.1 contributed to disease susceptibility. Three PM QTL, pm2.1, pm5.1, and pm6.1, were co-localized with DM QTL dm2.1, dm5.2, and dm6.1, respectively, which was consistent with the observed linkage of PM and DM resistances in PI 197088. The genetic architecture of DM resistance in PI 197088 and another resistant line WI7120 (PI 330628) was compared, and the potential of using PI 197088 in cucumber breeding for downy and powdery mildew resistances is discussed.

Final Technical Report, Wind Generator Project (Ann Arbor)

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

Geisler, Nathan

A Final Technical Report (57 pages) describing educational exhibits and devices focused on wind energy, and related outreach activities and programs. Project partnership includes the City of Ann Arbor, MI and the Ann Arbor Hands-on Museum, along with additional sub-recipients, and U.S. Department of Energy/Office of Energy Efficiency and Renewable Energy (EERE). Report relays key milestones and sub-tasks as well as numerous graphics and images of five (5) transportable wind energy demonstration devices and five (5) wind energy exhibits designed and constructed between 2014 and 2016 for transport and use by the Ann Arbor Hands-on Museum.

The Professor as Teacher: Allan Bloom, Wayne Booth, and the Tradition of Teaching at the University of Chicago.

ERIC Educational Resources Information Center

Wrightson, Katherine M.

1998-01-01

The University of Chicago (Illinois) has long emphasized teaching as a valued skill, fostering an image focused on the intellectual search for truth and transmission of intellectual values, a stand in opposition to popular relativist theories. Through the writings of Allan Bloom, Wayne Booth, and historical university documents, this model of…

iAnn: an event sharing platform for the life sciences.

PubMed

Jimenez, Rafael C; Albar, Juan P; Bhak, Jong; Blatter, Marie-Claude; Blicher, Thomas; Brazas, Michelle D; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; van Driel, Marc A; Dunn, Michael J; Fernandes, Pedro L; van Gelder, Celia W G; Hermjakob, Henning; Ioannidis, Vassilios; Judge, David P; Kahlem, Pascal; Korpelainen, Eija; Kraus, Hans-Joachim; Loveland, Jane; Mayer, Christine; McDowall, Jennifer; Moran, Federico; Mulder, Nicola; Nyronen, Tommi; Rother, Kristian; Salazar, Gustavo A; Schneider, Reinhard; Via, Allegra; Villaveces, Jose M; Yu, Ping; Schneider, Maria V; Attwood, Teresa K; Corpas, Manuel

2013-08-01

We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available. http://iann.pro/iannviewer manuel.corpas@tgac.ac.uk.

Radial forcing and Edgar Allan Poe's lengthening pendulum

NASA Astrophysics Data System (ADS)

McMillan, Matthew; Blasing, David; Whitney, Heather M.

2013-09-01

Inspired by Edgar Allan Poe's The Pit and the Pendulum, we investigate a radially driven, lengthening pendulum. We first show that increasing the length of an undriven pendulum at a uniform rate does not amplify the oscillations in a manner consistent with the behavior of the scythe in Poe's story. We discuss parametric amplification and the transfer of energy (through the parameter of the pendulum's length) to the oscillating part of the system. In this manner, radial driving can easily and intuitively be understood, and the fundamental concept applied in many other areas. We propose and show by a numerical model that appropriately timed radial forcing can increase the oscillation amplitude in a manner consistent with Poe's story. Our analysis contributes a computational exploration of the complex harmonic motion that can result from radially driving a pendulum and sheds light on a mechanism by which oscillations can be amplified parametrically. These insights should prove especially valuable in the undergraduate physics classroom, where investigations into pendulums and oscillations are commonplace.

Improving Signal Detection using Allan and Theo Variances

NASA Astrophysics Data System (ADS)

Hardy, Andrew; Broering, Mark; Korsch, Wolfgang

2017-09-01

Precision measurements often deal with small signals buried within electronic noise. Extracting these signals can be enhanced through digital signal processing. Improving these techniques provide signal to noise ratios. Studies presently performed at the University of Kentucky are utilizing the electro-optic Kerr effect to understand cell charging effects within ultra-cold neutron storage cells. This work is relevant for the neutron electric dipole moment (nEDM) experiment at Oak Ridge National Laboratory. These investigations, and future investigations in general, will benefit from the illustrated improved analysis techniques. This project will showcase various methods for determining the optimum duration that data should be gathered for. Typically, extending the measuring time of an experimental run reduces the averaged noise. However, experiments also encounter drift due to fluctuations which mitigate the benefits of extended data gathering. Through comparing FFT averaging techniques, along with Allan and Theo variance measurements, quantifiable differences in signal detection will be presented. This research is supported by DOE Grants: DE-FG02-99ER411001, DE-AC05-00OR22725.

An ANN That Applies Pragmatic Decision on Texts.

ERIC Educational Resources Information Center

Aretoulaki, Maria; Tsujii, Jun-ichi

A computer-based artificial neural network (ANN) that learns to classify sentences in a text as important or unimportant is described. The program is designed to select the sentences that are important enough to be included in composition of an abstract of the text. The ANN is embedded in a conventional symbolic environment consisting of…

Physical Mapping in a Triplicated Genome: Mapping the Downy Mildew Resistance Locus Pp523 in Brassica oleracea L.

PubMed Central

Carlier, Jorge D.; Alabaça, Claudia S.; Sousa, Nelson H.; Coelho, Paula S.; Monteiro, António A.; Paterson, Andrew H.; Leitão, José M.

2011-01-01

We describe the construction of a BAC contig and identification of a minimal tiling path that encompass the dominant and monogenically inherited downy mildew resistance locus Pp523 of Brassica oleracea L. The selection of BAC clones for construction of the physical map was carried out by screening gridded BAC libraries with DNA overgo probes derived from both genetically mapped DNA markers flanking the locus of interest and BAC-end sequences that align to Arabidopsis thaliana sequences within the previously identified syntenic region. The selected BAC clones consistently mapped to three different genomic regions of B. oleracea. Although 83 BAC clones were accurately mapped within a ∼4.6 cM region surrounding the downy mildew resistance locus Pp523, a subset of 33 BAC clones mapped to another region on chromosome C8 that was ∼60 cM away from the resistance gene, and a subset of 63 BAC clones mapped to chromosome C5. These results reflect the triplication of the Brassica genomes since their divergence from a common ancestor shared with A. thaliana, and they are consonant with recent analyses of the C genome of Brassica napus. The assembly of a minimal tiling path constituted by 13 (BoT01) BAC clones that span the Pp523 locus sets the stage for map-based cloning of this resistance gene. PMID:22384370

Selective sweep at the Rpv3 locus during grapevine breeding for downy mildew resistance.

PubMed

Di Gaspero, Gabriele; Copetti, Dario; Coleman, Courtney; Castellarin, Simone Diego; Eibach, Rudolf; Kozma, Pál; Lacombe, Thierry; Gambetta, Gregory; Zvyagin, Andrey; Cindrić, Petar; Kovács, László; Morgante, Michele; Testolin, Raffaele

2012-02-01

The Rpv3 locus is a major determinant of downy mildew resistance in grapevine (Vitis spp.). A selective sweep at this locus was revealed by the DNA genotyping of 580 grapevines, which include a highly diverse set of 265 European varieties that predated the spread of North American mildews, 82 accessions of wild species, and 233 registered breeding lines with North American ancestry produced in the past 150 years. Artificial hybridisation and subsequent phenotypic selection favoured a few Rpv3 haplotypes that were introgressed from wild vines and retained in released varieties. Seven conserved haplotypes in five descent groups of resistant varieties were traced back to their founders: (1) 'Munson', a cross between two of Hermann Jaeger's selections of V. rupestris and V. lincecumii made in the early 1880s in Missouri, (2) V. rupestris 'Ganzin', first utilised for breeding in 1879 by Victor Ganzin in France, (3) 'Noah', selected in 1869 from intermingled accessions of V. riparia and V. labrusca by Otto Wasserzieher in Illinois, (4) 'Bayard', a V. rupestris × V. labrusca offspring generated in 1882 by George Couderc in France, and (5) a wild form closely related to V. rupestris accessions in the Midwestern United States and introgressed into 'Seibel 4614' in the 1880s by Albert Seibel in France. Persistence of these Rpv3 haplotypes across many of the varieties generated by human intervention indicates that a handful of vines with prominent resistance have laid the foundation for modern grape breeding. A rampant hot spot of NB-LRR genes at the Rpv3 locus has provided a distinctive advantage for the adaptation of native North American grapevines to withstand downy mildew. The coexistence of multiple resistance alleles or paralogues in the same chromosomal region but in different haplotypes counteracts efforts to pyramidise them in a diploid individual via conventional breeding.

77 FR 75629 - Pramaggiore, Anne R.; Notice of Filing

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-21

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. ID-6059-001] Pramaggiore, Anne R.; Notice of Filing Take notice that on December 14, 2012, Anne R. Pramaggiore submitted for filing, an application for authority to hold interlocking positions, pursuant to section 305(b) of the...

Allan Hills Pleistocene Ice Project (PIP)

NASA Astrophysics Data System (ADS)

Kurbatov, A.; Brook, E.; Campbell, S. W.; Conway, H.; Dunbar, N. W.; Higgins, J. A.; Iverson, N. A.; Kehrl, L. M.; McIntosh, W. C.; Spaulding, N. E.; Yan, Y.; Mayewski, P. A.

2016-12-01

A major international effort to identify at least 1.5 Ma old ice for paleoclimate reconstructions has successfully resulted in the selection of several potential drill sites in East Antarctica. At this point it is indisputable that the Antarctic ice sheet captures a continuous envinronmental record of the Earth that spans the Mid Pleistocene Transition (MPT). In addition to traditional ice coring approaches, the oldest ice can also be recovered in Antarctic Blue Ice Areas (BIA). We have already successfully demonstrated that the Allan Hills (AH) BIA captures a regional climate signal and robust record of 1Ma atmosphere that can be studied with a relatively uncomplicated logistical imprint and essentially unlimited sampling volume. The attractiveness of unlimited sampling of known age ice is the basis for the "ice park" concept proposed earlier by our research team. The idea is that, once the age of ice exposed along the flow line at the surface of BIA is mapped, it could be sampled for numerous research projects as needed. Here we propose an intermediate ( 1,150 m deep) ice core drill site, located only 240 km away from McMurdo base that will help to develop a, continuous, high quality regional paleoclimate record that is at least 1Ma old. We will introduce and discuss the glaciological settings, paleoclimate signals and possible limitations and advantages of the 1 Ma AH BIA regional paleoclimate record. The research was funded by NSF Division of Polar Programs.

Genome-wide association study in Asia-adapted tropical maize reveals novel and explored genomic regions for sorghum downy mildew resistance.

PubMed

Rashid, Zerka; Singh, Pradeep Kumar; Vemuri, Hindu; Zaidi, Pervez Haider; Prasanna, Boddupalli Maruthi; Nair, Sudha Krishnan

2018-01-10

Globally, downy mildews are among the important foliar diseases of maize that cause significant yield losses. We conducted a genome-wide association study for sorghum downy mildew (SDM; Peronosclerospora sorghi) resistance in a panel of 368 inbred lines adapted to the Asian tropics. High density SNPs from Genotyping-by-sequencing were used in GWAS after controlling for population structure and kinship in the panel using a single locus mixed model. The study identified a set of 26 SNPs that were significantly associated with SDM resistance, with Bonferroni corrected P values ≤ 0.05. Among all the identified SNPs, the minor alleles were found to be favorable to SDM resistance in the mapping panel. Trend regression analysis with 16 independent genetic variants including 12 SNPs and four haplotype blocks identified SNP S2_6154311 on chromosome 2 with P value 2.61E-24 and contributing 26.7% of the phenotypic variation. Six of the SNPs/haplotypes were within the same chromosomal bins as the QTLs for SDM resistance mapped in previous studies. Apart from this, eight novel genomic regions for SDM resistance were identified in this study; they need further validation before being applied in the breeding pipeline. Ten SNPs identified in this study were co-located in reported mildew resistance genes.

Non-selective feeding and oviposition behavior of Cryptocephalus trifasciata (Coleoptera: Cerambycidae: Cryptocephalinae), precludes its use as a biological control agent for downy rose myrtle (Rhodomyrtus tomentosa)

USDA-ARS?s Scientific Manuscript database

Downy rose myrtle (Rhodomyrtus tomentosa), a southeast Asian native shrub, invades natural areas in Florida and Hawaii where it forms dense, impenetrable thickets. We tested the host affinity and survivorship of a case bearing beetle, Cryptocephalus trifasciata on R. tomentosa and related species. C...

Clues on Past Climatic Environments and Subsurface Flow in Mars from Aqueous Alteration Minerals Found in Nakhla and Allan Hills 84001 Meteorites

NASA Astrophysics Data System (ADS)

Trigo-Rodriguez, J. M.; Moyano-Cambero, C. E.; Donoso, J. A.; Benito-Moreno, M. I.; Alonso-Azcárate, J.

2018-04-01

The study of aqueous alteration minerals like Fe-Mg-Ca carbonates in Allan Hills 84001 or iddingsite and magnetite in Nakhla meteorite allow us to constrain their formation conditions and water availability at 4 and 1.3 Ga ago, respectively.

Ice dynamics of the Allan Hills meteorite concentration sites revealed by satellite aperture radar interferometry

NASA Astrophysics Data System (ADS)

Coren, F.; Delisle, G.; Sterzai, P.

2003-09-01

The ice flow conditions of a 100 x 100 km area of Victoria Land, Antarctica were analyzed with the synthetic aperture radar (SAR) technique. The area includes a number of meteorite concentration sites, in particular the Allan Hills ice fields. Regional ice flow velocities around the Mid- western and Near-western ice fields and the Allan Hills main ice field are shown to be 2.5 m yr-1. These sites are located on a horseshoe-shaped area that bounds an area characterized by higher ice flow velocities of up to 5 m yr-1. Meteorite find locations on the Elephant Moraine are located in this "high ice flow" area. The SAR derived digital elevation model (DEM) shows atypical low surface slopes for Antarctic conditions, which are the cause for the slow ice movements. Numerous ice rises in the area are interpreted to cap sub-ice obstacles, which were formed by tectonic processes in the past. The ice rises are considered to represent temporary features, which develop only during warm stages when the regional ice stand is lowered. Ice depressions, which develop in warm stages on the lee side of ice rises, may act as the sites of temporary build-up of meteorite concentrations, which turn inoperative during cold stages when the regional ice level rises and the ice rises disappear. Based on a simplified ice flow model, we argue that the regional ice flow in cold stages is reduced by a factor of at least 3.

Investigation of Allan variance for determining noise spectral forms with application to microwave radiometry

NASA Technical Reports Server (NTRS)

Stanley, William D.

1994-01-01

An investigation of the Allan variance method as a possible means for characterizing fluctuations in radiometric noise diodes has been performed. The goal is to separate fluctuation components into white noise, flicker noise, and random-walk noise. The primary means is by discrete-time processing, and the study focused primarily on the digital processes involved. Noise satisfying the requirements was generated by direct convolution, fast Fourier transformation (FFT) processing in the time domain, and FFT processing in the frequency domain. Some of the numerous results obtained are presented along with the programs used in the study.

Effects of stacked quantitative resistances to downy mildew in lettuce do not simply add up.

PubMed

den Boer, Erik; Pelgrom, Koen T B; Zhang, Ningwen W; Visser, Richard G F; Niks, Rients E; Jeuken, Marieke J W

2014-08-01

In a stacking study of eight resistance QTLs in lettuce against downy mildew, only three out of ten double combinations showed an increased resistance effect under field conditions. Complete race nonspecific resistance to lettuce downy mildew, as observed for the nonhost wild lettuce species Lactuca saligna, is desired in lettuce cultivation. Genetic dissection of L. saligna's complete resistance has revealed several quantitative loci (QTL) for resistance with field infection reductions of 30-50 %. To test the effect of stacking these QTL, we analyzed interactions between homozygous L. saligna CGN05271 chromosome segments introgressed into the genetic background of L. sativa cv. Olof. Eight different backcross inbred lines (BILs) with single introgressions of 30-70 cM and selected predominately for quantitative resistance in field situations were intercrossed. Ten developed homozygous lines with stacked introgression segments (double combinations) were evaluated for resistance in the field. Seven double combinations showed a similar infection as the individual most resistant parental BIL, revealing epistatic interactions with 'less-than-additive' effects. Three double combinations showed an increased resistance level compared to their parental BILs and their interactions were additive, 'less-than-additive' epistatic and 'more-than-additive' epistatic, respectively. The additive interaction reduced field infection by 73 %. The double combination with a 'more-than-additive' epistatic effect, derived from a combination between a susceptible and a resistant BIL with 0 and 30 % infection reduction, respectively, showed an average field infection reduction of 52 %. For the latter line, an attempt to genetically dissect its underlying epistatic loci by substitution mapping did not result in smaller mapping intervals as none of the 22 substitution lines reached a similar high resistance level. Implications for breeding and the inheritance of L. saligna's complete

Seasonal and spatial variability of rainfall redistribution under Scots pine and Downy oak forests in Mediterranean conditions

NASA Astrophysics Data System (ADS)

Garcia-Estringana, Pablo; Latron, Jérôme; Molina, Antonio J.; Llorens, Pilar

2013-04-01

The large degree of temporal and spatial variability of throughfall input patterns may lead to significant changes in the volume of water that reach the soil in each location, and beyond in the hydrological response of forested hillslopes. To explore the role of vegetation in the temporal and spatial redistribution of rainfall in Mediterranean climatic conditions two contrasted stands were monitored. One is a Downy oak forest (Quercus pubescens) and the other is a Scots pine forest (Pinus sylvestris), both are located in the Vallcebre research catchments (NE Spain, 42° 12'N, 1° 49'E). These plots are representative of Mediterranean mountain areas with spontaneous afforestation by Scots pine as a consequence of the abandonment of agricultural terraces, formerly covered by Downy oaks. The monitoring design of each plot consists of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. 100 hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover are also automatically recorded. Canopy cover as well as biometric characteristics of the plots are also regularly measured. This work presents the first results describing the variability of throughfall beneath each forest stand and compares the persistence of temporal patterns among stands, and for the oaks stand among the leafed and the leafless period. Furthermore, canopy structure, rainfall characteristics and meteorological conditions of rainfall events are evaluated as main drivers of throughfall redistribution.

Noble gases in twenty Yamato H-chondrites: Comparison with Allan Hills chondrites and modern falls

NASA Technical Reports Server (NTRS)

Loeken, TH.; Scherer, P.; Schultz, L.

1993-01-01

Concentration and isotopic composition of noble gases have been measured in 20 H-chrondrites found on the Yamato Mountains ice fields in Antarctica. The distribution of exposure ages as well as of radiogenic He-4 contents is similar to that of H-chrondrites collected at the Allan Hills site. Furthermore, a comparison of the noble gas record of Antarctic H-chrondrites and finds or falls from non-Antarctic areas gives no support to the suggestion that Antarctic H-chrondrites and modern falls derive from differing interplanetary meteorite populations.

A revision of Plasmopara penniseti, with implications for the host range of the downy mildews with pyriform haustoria.

PubMed

Thines, Marco; Göker, Markus; Oberwinkler, Franz; Spring, Otmar

2007-12-01

Plasmopara penniseti is the sole member of the genus Plasmopara parasitic to Poaceae, after the genus Viennotia had been described to accommodate Plasmopara oplismeni. Morphological, ultrastructural, and molecular phylogenetic data indicate that Plasmopara penniseti is not closely related to the generic type, and it is, therefore, transferred to the newly described genus Poakatesthia. The view that the genera of downy mildews with pyriform to vesicular haustoria (Basidiophora, Benua, Bremia, Paraperonospora, Plasmopara, Plasmoverna, and Protobremia) include species parasitic to Poaceae has to be discarded. All of these genera are apparently restricted to dicotyledonous hosts.

On an Allan variance approach to classify VLBI radio-sources on the basis of their astrometric stability

NASA Astrophysics Data System (ADS)

Gattano, C.; Lambert, S.; Bizouard, C.

2017-12-01

In the context of selecting sources defining the celestial reference frame, we compute astrometric time series of all VLBI radio-sources from observations in the International VLBI Service database. The time series are then analyzed with Allan variance in order to estimate the astrometric stability. From results, we establish a new classification that takes into account the whole multi-time scales information. The algorithm is flexible on the definition of ``stable source" through an adjustable threshold.

Modeling and prediction of copper removal from aqueous solutions by nZVI/rGO magnetic nanocomposites using ANN-GA and ANN-PSO.

PubMed

Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Xiong, Kangning; Wei, Xionghui

2017-12-21

Reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) magnetic nanocomposites were prepared and then applied in the Cu(II) removal from aqueous solutions. Scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy and superconduction quantum interference device magnetometer were performed to characterize the nZVI/rGO nanocomposites. In order to reduce the number of experiments and the economic cost, response surface methodology (RSM) combined with artificial intelligence (AI) techniques, such as artificial neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), has been utilized as a major tool that can model and optimize the removal processes, because a tremendous advance has recently been made on AI that may result in extensive applications. Based on RSM, ANN-GA and ANN-PSO were employed to model the Cu(II) removal process and optimize the operating parameters, e.g., operating temperature, initial pH, initial concentration and contact time. The ANN-PSO model was proven to be an effective tool for modeling and optimizing the Cu(II) removal with a low absolute error and a high removal efficiency. Furthermore, the isotherm, kinetic, thermodynamic studies and the XPS analysis were performed to explore the mechanisms of Cu(II) removal process.

ANN modeling of DNA sequences: new strategies using DNA shape code.

PubMed

Parbhane, R V; Tambe, S S; Kulkarni, B D

2000-09-01

Two new encoding strategies, namely, wedge and twist codes, which are based on the DNA helical parameters, are introduced to represent DNA sequences in artificial neural network (ANN)-based modeling of biological systems. The performance of the new coding strategies has been evaluated by conducting three case studies involving mapping (modeling) and classification applications of ANNs. The proposed coding schemes have been compared rigorously and shown to outperform the existing coding strategies especially in situations wherein limited data are available for building the ANN models.

Investigations into an unknown organism on the martian meteorite Allan Hills 84001

NASA Technical Reports Server (NTRS)

Steele, A.; Goddard, D. T.; Stapleton, D.; Toporski, J. K.; Peters, V.; Bassinger, V.; Sharples, G.; Wynn-Williams, D. D.; McKay, D. S.

2000-01-01

Examination of fracture surfaces near the fusion crust of the martian meteorite Allan Hills (ALH) 84001 have been conducted using scanning electron microscopy (SEM) and atomic force microscopy (AFM) and has revealed structures strongly resembling mycelium. These structures were compared with similar structures found in Antarctic cryptoendolithic communities. On morphology alone, we conclude that these features are not only terrestrial in origin but probably belong to a member of the Actinomycetales, which we consider was introduced during the Antarctic residency of this meteorite. If true, this is the first documented account of terrestrial microbial activity within a meteorite from the Antarctic blue ice fields. These structures, however, do not bear any resemblance to those postulated to be martian biota, although they are a probable source of the organic contaminants previously reported in this meteorite.

Using artificial neural networks (ANN) for open-loop tomography

NASA Astrophysics Data System (ADS)

Osborn, James; De Cos Juez, Francisco Javier; Guzman, Dani; Butterley, Timothy; Myers, Richard; Guesalaga, Andres; Laine, Jesus

2011-09-01

The next generation of adaptive optics (AO) systems require tomographic techniques in order to correct for atmospheric turbulence along lines of sight separated from the guide stars. Multi-object adaptive optics (MOAO) is one such technique. Here, we present a method which uses an artificial neural network (ANN) to reconstruct the target phase given off-axis references sources. This method does not require any input of the turbulence profile and is therefore less susceptible to changing conditions than some existing methods. We compare our ANN method with a standard least squares type matrix multiplication method (MVM) in simulation and find that the tomographic error is similar to the MVM method. In changing conditions the tomographic error increases for MVM but remains constant with the ANN model and no large matrix inversions are required.

Evidence for asexual genetic recombination in sunflower downy mildew, Plasmopara halstedii.

PubMed

Spring, Otmar; Zipper, Reinhard

2006-06-01

Field isolates and single sporangium lines of the biotrophic Oomycete Plasmopara halstedii, differing in host preference and fungicide sensitivity, were used simultaneously for infection of sunflower. Dual infections led to asexually formed zoosporangia which gave rise to a new phenotype combining the characteristics of the parental strains. The new phenotype showed the metalaxyl-tolerance of one parent and virulence behaviour characteristic of the other, thus being able to infect a specific and fungicide treated sunflower line that neither of the parental strains could infect alone. These characteristics were inherited over many generations and did not occur spontaneously when parental strains were propagated separately. DNA fingerprints with minisatellite and simple sequence repeat primers showed characteristic differences between the patterns of the parental strains and the new phenotype. PCR experiments with mixed parental DNA resulted in additive patterns, but did not show the amplification product specific for the new phenotype. Since sexual reproduction was excluded under the experimental conditions used, the results provide evidence for genetic recombination through parasexual events in dual infections of sunflower downy mildew.

Ann Eliza Young: A Nineteenth Century Champion of Women's Rights.

ERIC Educational Resources Information Center

Cullen, Jack B.

Concentrating on the efforts of such nineteenth century women's rights advocates as Susan B. Anthony and Elizabeth Cady Stanton, communication researchers have largely overlooked the contributions made to the cause by Ann Eliza Young. The nineteenth wife of Mormon leader Brigham Young, Ann Eliza Young left her husband and took to the speaker's…

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 1 2013-10-01 2013-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 1 2012-10-01 2012-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 1 2014-10-01 2014-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

A novel modular ANN architecture for efficient monitoring of gases/odours in real-time

NASA Astrophysics Data System (ADS)

Mishra, A.; Rajput, N. S.

2018-04-01

Data pre-processing is tremendously used for enhanced classification of gases. However, it suppresses the concentration variances of different gas samples. A classical solution of using single artificial neural network (ANN) architecture is also inefficient and renders degraded quantification. In this paper, a novel modular ANN design has been proposed to provide an efficient and scalable solution in real–time. Here, two separate ANN blocks viz. classifier block and quantifier block have been used to provide efficient and scalable gas monitoring in real—time. The classifier ANN consists of two stages. In the first stage, the Net 1-NDSRT has been trained to transform raw sensor responses into corresponding virtual multi-sensor responses using normalized difference sensor response transformation (NDSRT). These responses have been fed to the second stage (i.e., Net 2-classifier ). The Net 2-classifier has been trained to classify various gas samples to their respective class. Further, the quantifier block has parallel ANN modules, multiplexed to quantify each gas. Therefore, the classifier ANN decides class and quantifier ANN decides the exact quantity of the gas/odor present in the respective sample of that class.

[An early warning method of cucumber downy mildew in solar greenhouse based on canopy temperature and humidity modeling].

PubMed

Wang, Hui; Li, Mei-lan; Xu, Jian-ping; Chen, Mei-xiang; Li, Wen-yong; Li, Ming

2015-10-01

The greenhouse environmental parameters can be used to establish greenhouse nirco-climate model, which can combine with disease model for early warning, with aim of ecological controlling diseases to reduce pesticide usage, and protecting greenhouse ecological environment to ensure the agricultural product quality safety. Greenhouse canopy leaf temperature and air relative humidity, models were established using energy balance and moisture balance principle inside the greenhouse. The leaf temperature model considered radiation heat transfer between the greenhouse crops, wall, soil and cover, plus the heat exchange caused by indoor net radiation and crop transpiration. Furthermore, the water dynamic balance in the greenhouse including leaf transpiration, soil evaporation, cover and leaf water vapor condensation, was considered to develop a relative humidity model. The primary infection and latent period warning models for cucumber downy mildew (Pseudoperonospora cubensis) were validated using the results of the leaf temperature and relative humidity model, and then the estimated disease occurrence date of cucumber downy mildew was compared with actual disease occurrence date of field observation. Finally, the results were verified by the measured temperature and humidity data of September and October, 2014. The results showed that the root mean square deviations (RMSDs) of the measured and estimated leaf temperature were 0.016 and 0.024 °C, and the RMSDs of the measured and estimated air relative humidity were 0.15% and 0.13%, respectively. Combining the result of estimated temperature and humidity models, a cucumber disease early warning system was established to forecast the date of disease occurrence, which met with the real date. Thus, this work could provide the micro-environment data for the early warning system of cucumber diseases in solar greenhouses.

Biotic and abiotic factors affecting stemflow variability in downy oak and Scots pine stands in Mediterranean conditions

NASA Astrophysics Data System (ADS)

Cayuela, Carles; Garcia-Estringana, Pablo; Latron, Jérôme; Llorens, Pilar

2015-04-01

Although stemflow is only a small portion of rainfall, it may represent an important local input of water and nutrients at the plant stem. Previous studies have shown that stemflow has a significant influence on hydrological and biogeochemical processes. Stemflow volume is affected by many biotic factors as species, age, branch or bark characteristics. Moreover, the seasonality of the rainfall regime in Mediterranean areas, which includes both frontal rainfall events and short convective storms, can add complexity to the rainfall-stemflow relationship. This work investigates stemflow dynamics and the influence of biotic and abiotic factors on stemflow rates in two Mediterranean stands during the leafed period - from May to October. The monitored stands are a Downy oak forest (Quercus pubescens) and a Scots pine forest (Pinus sylvestris), both located in the Vallcebre research catchments (NE Spain, 42° 12'N, 1° 49'E). The monitoring design of each plot consists of 7 stemflow rings connected to tipping-buckets, bulk rainfall measured in a nearby clearing and meteorological conditions above the canopies. All data were recorded at 5 min interval. Biometric characteristics of the measured trees were also measured. The analysis of 39 rainfall events (65% smaller than 10 mm) shows that stemflow accounted for less than 1% of the bulk rainfall in both stands. Results also show that, on average, the rainfall amount required for the start of the stemflow and the time delay between the beginning of the precipitation and the start of stemflow are higher in the Downy oak forest. As suggested by stemflow funneling ratios, these differences might be linked to the canopy structure and bark water storage capacity of the trees, indicating that during low magnitude events, oaks have more difficulty to reach storage capacity. The role of other biotic and abiotic parameters on stemflow variability in both stands is still under investigation.

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

Identification of drought in Dhalai river watershed using MCDM and ANN models

NASA Astrophysics Data System (ADS)

Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

2017-03-01

An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

Application of Fast Dynamic Allan Variance for the Characterization of FOGs-Based Measurement While Drilling.

PubMed

Wang, Lu; Zhang, Chunxi; Gao, Shuang; Wang, Tao; Lin, Tie; Li, Xianmu

2016-12-07

The stability of a fiber optic gyroscope (FOG) in measurement while drilling (MWD) could vary with time because of changing temperature, high vibration, and sudden power failure. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool that could represent the non-stationary behavior of the gyroscope signal. Since the normal DAVAR takes too long to deal with long time series, a fast DAVAR algorithm has been developed to accelerate the computation speed. However, both the normal DAVAR algorithm and the fast algorithm become invalid for discontinuous time series. What is worse, the FOG-based MWD underground often keeps working for several days; the gyro data collected aboveground is not only very time-consuming, but also sometimes discontinuous in the timeline. In this article, on the basis of the fast algorithm for DAVAR, we make a further advance in the fast algorithm (improved fast DAVAR) to extend the fast DAVAR to discontinuous time series. The improved fast DAVAR and the normal DAVAR are used to responsively characterize two sets of simulation data. The simulation results show that when the length of the time series is short, the improved fast DAVAR saves 78.93% of calculation time. When the length of the time series is long ( 6 × 10 5 samples), the improved fast DAVAR reduces calculation time by 97.09%. Another set of simulation data with missing data is characterized by the improved fast DAVAR. Its simulation results prove that the improved fast DAVAR could successfully deal with discontinuous data. In the end, a vibration experiment with FOGs-based MWD has been implemented to validate the good performance of the improved fast DAVAR. The results of the experience testify that the improved fast DAVAR not only shortens computation time, but could also analyze discontinuous time series.

Application of Fast Dynamic Allan Variance for the Characterization of FOGs-Based Measurement While Drilling

PubMed Central

Wang, Lu; Zhang, Chunxi; Gao, Shuang; Wang, Tao; Lin, Tie; Li, Xianmu

2016-01-01

The stability of a fiber optic gyroscope (FOG) in measurement while drilling (MWD) could vary with time because of changing temperature, high vibration, and sudden power failure. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool that could represent the non-stationary behavior of the gyroscope signal. Since the normal DAVAR takes too long to deal with long time series, a fast DAVAR algorithm has been developed to accelerate the computation speed. However, both the normal DAVAR algorithm and the fast algorithm become invalid for discontinuous time series. What is worse, the FOG-based MWD underground often keeps working for several days; the gyro data collected aboveground is not only very time-consuming, but also sometimes discontinuous in the timeline. In this article, on the basis of the fast algorithm for DAVAR, we make a further advance in the fast algorithm (improved fast DAVAR) to extend the fast DAVAR to discontinuous time series. The improved fast DAVAR and the normal DAVAR are used to responsively characterize two sets of simulation data. The simulation results show that when the length of the time series is short, the improved fast DAVAR saves 78.93% of calculation time. When the length of the time series is long (6×105 samples), the improved fast DAVAR reduces calculation time by 97.09%. Another set of simulation data with missing data is characterized by the improved fast DAVAR. Its simulation results prove that the improved fast DAVAR could successfully deal with discontinuous data. In the end, a vibration experiment with FOGs-based MWD has been implemented to validate the good performance of the improved fast DAVAR. The results of the experience testify that the improved fast DAVAR not only shortens computation time, but could also analyze discontinuous time series. PMID:27941600

A Hybrid FEM-ANN Approach for Slope Instability Prediction

NASA Astrophysics Data System (ADS)

Verma, A. K.; Singh, T. N.; Chauhan, Nikhil Kumar; Sarkar, K.

2016-09-01

Assessment of slope stability is one of the most critical aspects for the life of a slope. In any slope vulnerability appraisal, Factor Of Safety (FOS) is the widely accepted index to understand, how close or far a slope from the failure. In this work, an attempt has been made to simulate a road cut slope in a landslide prone area in Rudrapryag, Uttarakhand, India which lies near Himalayan geodynamic mountain belt. A combination of Finite Element Method (FEM) and Artificial Neural Network (ANN) has been adopted to predict FOS of the slope. In ANN, a three layer, feed- forward back-propagation neural network with one input layer and one hidden layer with three neurons and one output layer has been considered and trained using datasets generated from numerical analysis of the slope and validated with new set of field slope data. Mean absolute percentage error estimated as 1.04 with coefficient of correlation between the FOS of FEM and ANN as 0.973, which indicates that the system is very vigorous and fast to predict FOS for any slope.

Comparison of Conventional and ANN Models for River Flow Forecasting

NASA Astrophysics Data System (ADS)

Jain, A.; Ganti, R.

2011-12-01

Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. River flow is generally estimated using time series or rainfall-runoff models. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been extensively adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conventional models. In this paper, a comparative study has been carried out for river flow forecasting using the conventional and ANN models. Among the conventional models, multiple linear, and non linear regression, and time series models of auto regressive (AR) type have been developed. Feed forward neural network model structure trained using the back propagation algorithm, a gradient search method, was adopted. The daily river flow data derived from Godavari Basin @ Polavaram, Andhra Pradesh, India have been employed to develop all the models included here. Two inputs, flows at two past time steps, (Q(t-1) and Q(t-2)) were selected using partial auto correlation analysis for forecasting flow at time t, Q(t). A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. It has been found that the regression and AR models performed comparably, and the ANN model performed the best amongst all the models investigated in this study. It is concluded that ANN model should be adopted in real catchments for hydrological modeling and forecasting.

75 FR 418 - Certificate of Alternative Compliance for the Offshore Supply Vessel KELLY ANN CANDIES

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-05

... Compliance for the Offshore Supply Vessel KELLY ANN CANDIES AGENCY: Coast Guard, DHS. ACTION: Notice. SUMMARY... supply vessel KELLY ANN CANDIES as required by 33 U.S.C. 1605(c) and 33 CFR 81.18. DATES: The Certificate... Purpose The offshore supply vessel KELLY ANN CANDIES will be used for offshore supply operations. Full...

Observation, Inference, and Imagination: Elements of Edgar Allan Poe's Philosophy of Science

NASA Astrophysics Data System (ADS)

Gelfert, Axel

2014-03-01

Edgar Allan Poe's standing as a literary figure, who drew on (and sometimes dabbled in) the scientific debates of his time, makes him an intriguing character for any exploration of the historical interrelationship between science, literature and philosophy. His sprawling `prose-poem' Eureka (1848), in particular, has sometimes been scrutinized for anticipations of later scientific developments. By contrast, the present paper argues that it should be understood as a contribution to the raging debates about scientific methodology at the time. This methodological interest, which is echoed in Poe's `tales of ratiocination', gives rise to a proposed new mode of—broadly abductive—inference, which Poe attributes to the hybrid figure of the `poet-mathematician'. Without creative imagination and intuition, Science would necessarily remain incomplete, even by its own standards. This concern with imaginative (abductive) inference ties in nicely with his coherentism, which grants pride of place to the twin virtues of Simplicity and Consistency, which must constrain imagination lest it degenerate into mere fancy.

Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

ERIC Educational Resources Information Center

Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

2011-01-01

Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

Coupling Spore Traps and Quantitative PCR Assays for Detection of the Downy Mildew Pathogens of Spinach (Peronospora effusa) and Beet (P. schachtii)

PubMed Central

Klosterman, Steven J.; Anchieta, Amy; McRoberts, Neil; Koike, Steven T.; Subbarao, Krishna V.; Voglmayr, Hermann; Choi, Young-Joon; Thines, Marco; Martin, Frank N.

2016-01-01

Downy mildew of spinach (Spinacia oleracea), caused by Peronospora effusa, is a production constraint on production worldwide, including in California, where the majority of U.S. spinach is grown. The aim of this study was to develop a real-time quantitative polymerase chain reaction (qPCR) assay for detection of airborne inoculum of P. effusa in California. Among oomycete ribosomal DNA (rDNA) sequences examined for assay development, the highest nucleotide sequence identity was observed between rDNA sequences of P. effusa and P. schachtii, the cause of downy mildew on sugar beet and Swiss chard in the leaf beet group (Beta vulgaris subsp. vulgaris). Single-nucleotide polymorphisms were detected between P. effusa and P. schachtii in the 18S rDNA regions for design of P. effusa- and P. schachtii-specific TaqMan probes and reverse primers. An allele-specific probe and primer amplification method was applied to determine the frequency of both P. effusa and P. schachtii rDNA target sequences in pooled DNA samples, enabling quantification of rDNA of P. effusa from impaction spore trap samples collected from spinach production fields. The rDNA copy numbers of P. effusa were, on average, ≈3,300-fold higher from trap samples collected near an infected field compared with those levels recorded at a site without a nearby spinach field. In combination with disease-conducive weather forecasting, application of the assays may be helpful to time fungicide applications for disease management. PMID:24964150

Saint Anne: A Multicultural Education Dilemma.

ERIC Educational Resources Information Center

Bruce, Bill; And Others

This 5-hour simulation is designed to give secondary- and college-level students and community persons the opportunity to deal with multicultural issues in a typical organizational and community setting. St. Anne is a fictitious town of 75,000 residents with two major ethnic neighborhoods--one German and the other Swedish. The local paper industry…

Allan Hills 76005 Polymict Eucrite Pairing Group: Curatorial and Scientific Update on a Jointly Curated Meteorite

NASA Technical Reports Server (NTRS)

Righter, K.

2011-01-01

Allan Hills 76005 (or 765) was collected by the joint US-Japan field search for meteorites in 1976-77. It was described in detail as "pale gray in color and consists of finely divided macrocrystalline pyroxene-rich matrix that contains abundant clastic fragments: (1) Clasts of white, plagioclase-rich rocks. (2) Medium-gray, partly devitrified, cryptocrystalline. (3) Monomineralic fragments and grains of pyroxene, plagioclases, oxide minerals, sulfides, and metal. In overall appearance it is very similar to some lunar breccias." Subsequent studies found a great diversity of basaltic clast textures and compositions, and therefore it is best classified as a polymict eucrite. Samples from the 1976-77, 77-78, and 78-79 field seasons (76, 77, and 78 prefixes) were split between US and Japan (NIPR). The US specimens are currently at NASA-JSC, Smithsonian Institution, or the Field Museum in Chicago. After this initial finding of ALH 76005, the next year s team recovered one additional mass ALH 77302, and then four additional masses were found during the third season ALH 78040 and ALH 78132, 78158 and 78165. The joint US-Japan collection effort ended after three years and the US began collecting in the Trans-Antarctic Mountains with the 1979-80 and subsequent field seasons. ALH 79017 and ALH 80102 were recovered in these first two years, and then in 1981-82 field season, 6 additional masses were recovered from the Allan Hills. Of course it took some time to establish pairing of all of these specimens, but altogether the samples comprise 4292.4 g of material. Here will be summarized the scientific findings as well as some curatorial details of how specimens have been subdivided and allocated for study. A detailed summary is also presented on the NASA-JSC curation webpage for the HED meteorite compendium.

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

NASA Astrophysics Data System (ADS)

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

2011-01-01

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actual experimental observations.

Predicting the risk of cucurbit downy mildew in the eastern United States using an integrated aerobiological model

NASA Astrophysics Data System (ADS)

Neufeld, K. N.; Keinath, A. P.; Gugino, B. K.; McGrath, M. T.; Sikora, E. J.; Miller, S. A.; Ivey, M. L.; Langston, D. B.; Dutta, B.; Keever, T.; Sims, A.; Ojiambo, P. S.

2017-11-01

Cucurbit downy mildew caused by the obligate oomycete, Pseudoperonospora cubensis, is considered one of the most economically important diseases of cucurbits worldwide. In the continental United States, the pathogen overwinters in southern Florida and along the coast of the Gulf of Mexico. Outbreaks of the disease in northern states occur annually via long-distance aerial transport of sporangia from infected source fields. An integrated aerobiological modeling system has been developed to predict the risk of disease occurrence and to facilitate timely use of fungicides for disease management. The forecasting system, which combines information on known inoculum sources, long-distance atmospheric spore transport and spore deposition modules, was tested to determine its accuracy in predicting risk of disease outbreak. Rainwater samples at disease monitoring sites in Alabama, Georgia, Louisiana, New York, North Carolina, Ohio, Pennsylvania and South Carolina were collected weekly from planting to the first appearance of symptoms at the field sites during the 2013, 2014, and 2015 growing seasons. A conventional PCR assay with primers specific to P. cubensis was used to detect the presence of sporangia in rain water samples. Disease forecasts were monitored and recorded for each site after each rain event until initial disease symptoms appeared. The pathogen was detected in 38 of the 187 rainwater samples collected during the study period. The forecasting system correctly predicted the risk of disease outbreak based on the presence of sporangia or appearance of initial disease symptoms with an overall accuracy rate of 66 and 75%, respectively. In addition, the probability that the forecasting system correctly classified the presence or absence of disease was ≥ 73%. The true skill statistic calculated based on the appearance of disease symptoms in cucurbit field plantings ranged from 0.42 to 0.58, indicating that the disease forecasting system had an acceptable to good

Predicting the risk of cucurbit downy mildew in the eastern United States using an integrated aerobiological model.

PubMed

Neufeld, K N; Keinath, A P; Gugino, B K; McGrath, M T; Sikora, E J; Miller, S A; Ivey, M L; Langston, D B; Dutta, B; Keever, T; Sims, A; Ojiambo, P S

2018-04-01

Cucurbit downy mildew caused by the obligate oomycete, Pseudoperonospora cubensis, is considered one of the most economically important diseases of cucurbits worldwide. In the continental United States, the pathogen overwinters in southern Florida and along the coast of the Gulf of Mexico. Outbreaks of the disease in northern states occur annually via long-distance aerial transport of sporangia from infected source fields. An integrated aerobiological modeling system has been developed to predict the risk of disease occurrence and to facilitate timely use of fungicides for disease management. The forecasting system, which combines information on known inoculum sources, long-distance atmospheric spore transport and spore deposition modules, was tested to determine its accuracy in predicting risk of disease outbreak. Rainwater samples at disease monitoring sites in Alabama, Georgia, Louisiana, New York, North Carolina, Ohio, Pennsylvania and South Carolina were collected weekly from planting to the first appearance of symptoms at the field sites during the 2013, 2014, and 2015 growing seasons. A conventional PCR assay with primers specific to P. cubensis was used to detect the presence of sporangia in rain water samples. Disease forecasts were monitored and recorded for each site after each rain event until initial disease symptoms appeared. The pathogen was detected in 38 of the 187 rainwater samples collected during the study period. The forecasting system correctly predicted the risk of disease outbreak based on the presence of sporangia or appearance of initial disease symptoms with an overall accuracy rate of 66 and 75%, respectively. In addition, the probability that the forecasting system correctly classified the presence or absence of disease was ≥ 73%. The true skill statistic calculated based on the appearance of disease symptoms in cucurbit field plantings ranged from 0.42 to 0.58, indicating that the disease forecasting system had an acceptable to

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

NASA Astrophysics Data System (ADS)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration

Prediction of Film Cooling Effectiveness on a Gas Turbine Blade Leading Edge Using ANN and CFD

NASA Astrophysics Data System (ADS)

Dávalos, J. O.; García, J. C.; Urquiza, G.; Huicochea, A.; De Santiago, O.

2018-05-01

In this work, the area-averaged film cooling effectiveness (AAFCE) on a gas turbine blade leading edge was predicted by employing an artificial neural network (ANN) using as input variables: hole diameter, injection angle, blowing ratio, hole and columns pitch. The database used to train the network was built using computational fluid dynamics (CFD) based on a two level full factorial design of experiments. The CFD numerical model was validated with an experimental rig, where a first stage blade of a gas turbine was represented by a cylindrical specimen. The ANN architecture was composed of three layers with four neurons in hidden layer and Levenberg-Marquardt was selected as ANN optimization algorithm. The AAFCE was successfully predicted by the ANN with a regression coefficient R2<0.99 and a root mean square error RMSE=0.0038. The ANN weight coefficients were used to estimate the relative importance of the input parameters. Blowing ratio was the most influential parameter with relative importance of 40.36 % followed by hole diameter. Additionally, by using the ANN model, the relationship between input parameters was analyzed.

Modeling and forecasting of KLCI weekly return using WT-ANN integrated model

NASA Astrophysics Data System (ADS)

Liew, Wei-Thong; Liong, Choong-Yeun; Hussain, Saiful Izzuan; Isa, Zaidi

2013-04-01

The forecasting of weekly return is one of the most challenging tasks in investment since the time series are volatile and non-stationary. In this study, an integrated model of wavelet transform and artificial neural network, WT-ANN is studied for modeling and forecasting of KLCI weekly return. First, the WT is applied to decompose the weekly return time series in order to eliminate noise. Then, a mathematical model of the time series is constructed using the ANN. The performance of the suggested model will be evaluated by root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE). The result shows that the WT-ANN model can be considered as a feasible and powerful model for time series modeling and prediction.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Thomas Tate, a third grade student at Anne Beers Elementary school, asks a question following a presentation by the crew of STS-127, Thursday, Sept. 24, 2009, in Washington. Photo Credit: (NASA/Paul E. Alers)

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

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

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actualmore » experimental observations.« less

Epidemiology of Basil Downy Mildew.

PubMed

Cohen, Yigal; Ben Naim, Yariv; Falach, Lidan; Rubin, Avia E

2017-10-01

Basil downy mildew (BDM) caused by the oomycete Peronospora belbahrii is a destructive disease of sweet basil (Ocimum basilicum) worldwide. It originated in Uganda in the 1930s and recently spread to Europe, the Middle East, Americas, and the Far East. Seed transmission may be responsible for its quick global spread. The pathogen attacks leaf blades, producing chlorotic lesions with ample dark asexual spores on the lower leaf surface. Oospores may form in the mesophyll of infected leaves. The asexual spores germinate on a wet leaf surface within 2 h and penetrate into the epidermis within 4 h. Spore germination and infection occur at a wide range of temperatures from 5 to 28.5°C. Infection intensity depends on the length of dew period, leaf temperature, and inoculum dose. The duration of latent period (from infection to sporulation) extends from 5 to 10 days, depending on temperature and light regime. The shortest is 5 days at 25°C under continuous light. Sporulation requires high humidity but not free leaf wetness. Sporulation occurs at 10 to 26°C. At the optimum temperature of 18°C, the process of sporulation requires 7.5 h at relative humidity ≥ 85%, with 3 h for sporophores emergence from stomata and 4.5 h for spore formation. Sporophores can emerge under light or darkness, but spore formation occurs in the dark only. Limited data are available on spore dispersal. Spores dispersed from sporulating plants contaminate healthy plants within 2 h of exposure. Settled spores may survive on leaf surface of healthy plants for prolonged periods, depending on temperature. Seed transmission of the disease occurs in Europe, but not in Israel or the United States. P. belbahrii in Israel also attacks species belonging to Rosemarinus, Nepeta, Agastache, Micromeria, and Salvia but not Plectranthus (coleus). A Peronospora species that infects coleus does not infect sweet basil. Control of BDM includes chemical, physical, and genetic means. The fungicide mefenoxam was

Comparison of ANN and RKS approaches to model SCC strength

NASA Astrophysics Data System (ADS)

Prakash, Aravind J.; Sathyan, Dhanya; Anand, K. B.; Aravind, N. R.

2018-02-01

Self compacting concrete (SCC) is a high performance concrete that has high flowability and can be used in heavily reinforced concrete members with minimal compaction segregation and bleeding. The mix proportioning of SCC is highly complex and large number of trials are required to get the mix with the desired properties resulting in the wastage of materials and time. The research on SCC has been highly empirical and no theoretical relationships have been developed between the mixture proportioning and engineering properties of SCC. In this work effectiveness of artificial neural network (ANN) and random kitchen sink algorithm(RKS) with regularized least square algorithm(RLS) in predicting the split tensile strength of the SCC is analysed. Random kitchen sink algorithm is used for mapping data to higher dimension and classification of this data is done using Regularized least square algorithm. The training and testing data for the algorithm was obtained experimentally using standard test procedures and materials available. Total of 40 trials were done which were used as the training and testing data. Trials were performed by varying the amount of fine aggregate, coarse aggregate, dosage and type of super plasticizer and water. Prediction accuracy of the ANN and RKS model is checked by comparing the RMSE value of both ANN and RKS. Analysis shows that eventhough the RKS model is good for large data set, its prediction accuracy is as good as conventional prediction method like ANN so the split tensile strength model developed by RKS can be used in industries for the proportioning of SCC with tailor made property.

THE DEAD-LIVING-MOTHER: MARIE BONAPARTE'S INTERPRETATION OF EDGAR ALLAN POE'S SHORT STORIES.

PubMed

Obaid, Francisco Pizarro

2016-06-01

Princess Marie Bonaparte is an important figure in the history of psychoanalysis, remembered for her crucial role in arranging Freud's escape to safety in London from Nazi Vienna, in 1938. This paper connects us to Bonaparte's work on Poe's short stories. Founded on concepts of Freudian theory and an exhaustive review of the biographical facts, Marie Bonaparte concluded that the works of Edgar Allan Poe drew their most powerful inspirational force from the psychological consequences of the early death of the poet's mother. In Bonaparte's approach, which was powerfully influenced by her recognition of the impact of the death of her own mother when she was born-an understanding she gained in her analysis with Freud-the thesis of the dead-living-mother achieved the status of a paradigmatic key to analyze and understand Poe's literary legacy. This paper explores the background and support of this hypothesis and reviews Bonaparte's interpretation of Poe's most notable short stories, in which extraordinary female figures feature in the narrative.

An Interview with Dr. Anne LaBastille.

ERIC Educational Resources Information Center

Griffin, Elizabeth

1982-01-01

Anne LaBastille, a role model for women interested in exploring the wilderness, gives hints on lessening the effects of acid rain, tells outdoor educators to encourage women to explore the wilderness and to take children outdoors to experience nature, and predicts a future economic slump for outdoor education. (LC)

Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment

NASA Astrophysics Data System (ADS)

Kothari, Mahesh; Gharde, K. D.

2015-07-01

The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.

Day and Night Dust Retrievals from MODIS IR Band Measurements using Artificial Neural Network (ANN) model

NASA Astrophysics Data System (ADS)

Lee, S.; Sohn, B.

2008-12-01

Artificial Neural Network (ANN) on the East Asia domain (20°N-55°N, 90°E-145°E) during the springs of 2006 and 2007 was investigated for retrieving aerosol optical thickness (AOT) of dust aerosol at both daytime and nighttime. The input data for ANN include brightness temperature, BTD (11 μm - 12 μm), spectral emissivity, surface temperature (Land: Price [1984] Equation, Ocean: The IMAPP MODIS Algorithm), relative airmass of satellite, and topography (SRTM30). The D*-parameter is adopted as dust detection algorithm which was developed by Hansell et al [2007]. The target data of the ANN is corresponding AOT at 550nm obtained from MODIS aerosol product (MYD04). After optimization and training, ANN AOT is retrieved. Among the many dust episodes during the spring of 2006, only the 8 April 2006 case was selected for the detailed analysis. Because it is one of the strongest episodes and shows a well-developed root penetrating the Korean peninsula and reaching the Japanese area. It is shown that ANN AOT coincide well with MODIS AOT having correlation coefficient of 0.8502 when the training and applying periods are the same (spring of 2006). Even a different period with training ANN AOT has a good relationship with MODIS AOT with the correlation coefficient of 0.7766 (spring 2007). This yearly difference is resulted from vegetation change and fixed IGBP land cover map. Also notable is that ANN AOT is underestimated in most IGBP types having low slope and negative mean bias. This study showed that ANN model has a good potential to retrieve AOT. More examinations and trials are needed, however, to improve this ANN algorithm using IR bands. Also this model should be extended to specify the dust aerosol property from other aerosols and clouds to assure that it has a capability during both daytime and nighttime.

New consensus multivariate models based on PLS and ANN studies of sigma-1 receptor antagonists.

PubMed

Oliveira, Aline A; Lipinski, Célio F; Pereira, Estevão B; Honorio, Kathia M; Oliveira, Patrícia R; Weber, Karen C; Romero, Roseli A F; de Sousa, Alexsandro G; da Silva, Albérico B F

2017-10-02

The treatment of neuropathic pain is very complex and there are few drugs approved for this purpose. Among the studied compounds in the literature, sigma-1 receptor antagonists have shown to be promising. In order to develop QSAR studies applied to the compounds of 1-arylpyrazole derivatives, multivariate analyses have been performed in this work using partial least square (PLS) and artificial neural network (ANN) methods. A PLS model has been obtained and validated with 45 compounds in the training set and 13 compounds in the test set (r 2 training = 0.761, q 2 = 0.656, r 2 test = 0.746, MSE test = 0.132 and MAE test = 0.258). Additionally, multi-layer perceptron ANNs (MLP-ANNs) were employed in order to propose non-linear models trained by gradient descent with momentum backpropagation function. Based on MSE test values, the best MLP-ANN models were combined in a MLP-ANN consensus model (MLP-ANN-CM; r 2 test = 0.824, MSE test = 0.088 and MAE test = 0.197). In the end, a general consensus model (GCM) has been obtained using PLS and MLP-ANN-CM models (r 2 test = 0.811, MSE test = 0.100 and MAE test = 0.218). Besides, the selected descriptors (GGI6, Mor23m, SRW06, H7m, MLOGP, and μ) revealed important features that should be considered when one is planning new compounds of the 1-arylpyrazole class. The multivariate models proposed in this work are definitely a powerful tool for the rational drug design of new compounds for neuropathic pain treatment. Graphical abstract Main scaffold of the 1-arylpyrazole derivatives and the selected descriptors.

Influence of canopy traits on spatio-temporal variability of throughfall in Mediterranean Downy oak and Scots pine stands

NASA Astrophysics Data System (ADS)

Llorens, Pilar; Garcia-Estringana, Pablo; Latron, Jérôme; Molina, Antonio J.; Gallart, Francesc

2014-05-01

The spatio-temporal variability of throughfall is the result of the interaction of biotic factors, related to the canopy traits, and abiotic factors, linked to the meteorological conditions. This variability may lead to significant differences in the volume of water and solutes that reach the ground in each location, and beyond in the hydrological and biogeochemical dynamics of forest soils. Two forest stands in Mediterranean climatic conditions were studied to analyse the role of biotic and abiotic factors in the temporal and spatial redistribution of throughfall. The monitored stands are a Downy oak forest (Quercus pubescens) and a Scots pine forest (Pinus sylvestris), both located in the Vallcebre research catchments (NE Spain, 42º 12'N, 1º 49'E). The study plots are representative of Mediterranean mountain areas with spontaneous afforestation by Scots pine as a consequence of the abandonment of agricultural terraces, formerly covered by Downy oaks. The monitoring design of each plot consisted of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. 100 hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover were also automatically recorded. Canopy cover as well as biometric characteristics of the plots were also regularly measured. The results indicate a temporal persistence of throughfall in both stands, as observed elsewhere. However, for the oak plot the seasonal evolution of canopy traits added additional variability, with higher variability in summer and different locations of wet and dry spots depending on the season. Furthermore, this work investigates the influence of canopy structure on the spatial variability of throughfall by analysing a large set of forest parameters, from main canopy traits to detailed leaves and wood characteristics

Process Control Strategies for Dual-Phase Steel Manufacturing Using ANN and ANFIS

NASA Astrophysics Data System (ADS)

Vafaeenezhad, H.; Ghanei, S.; Seyedein, S. H.; Beygi, H.; Mazinani, M.

2014-11-01

In this research, a comprehensive soft computational approach is presented for the analysis of the influencing parameters on manufacturing of dual-phase steels. A set of experimental data have been gathered to obtain the initial database used for the training and testing of both artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). The parameters used in the strategy were intercritical annealing temperature, carbon content, and holding time which gives off martensite percentage as an output. A fraction of the data set was chosen to train both ANN and ANFIS, and the rest was put into practice to authenticate the act of the trained networks while seeing unseen data. To compare the obtained results, coefficient of determination and root mean squared error indexes were chosen. Using artificial intelligence methods, it is not necessary to consider and establish a preliminary mathematical model and formulate its affecting parameters on its definition. In conclusion, the martensite percentages corresponding to the manufacturing parameters can be determined prior to a production using these controlling algorithms. Although the results acquired from both ANN and ANFIS are very encouraging, the proposed ANFIS has enhanced performance over the ANN and takes better effect on cost-reduction profit.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Students, including Marcus Pratt, left, and Ajani Young, second from left, pay close attention as the crew from STS-127 makes their presentation during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Photo Credit: (NASA/Paul E. Alers)

Novel Formulation of Adaptive MPC as EKF Using ANN Model: Multiproduct Semibatch Polymerization Reactor Case Study.

PubMed

Kamesh, Reddi; Rani, Kalipatnapu Yamuna

2017-12-01

In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation over control horizon based on minimizing the deviation of model output predictions from set points along the prediction horizon. An industrial case study for temperature control of a multiproduct semibatch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANN-EKFMPC strategy at supervisory level as a cascade control configuration along with proportional integral controller [ANN-EKFMPC with PI (ANN-EKFMPC-PI)]. The proposed approach is formulated incorporating all aspects of MPC including move suppression factor for control effort minimization and constraint-handling capability including terminal constraints. The nominal stability analysis and offset-free tracking capabilities of the proposed controller are proved. Its performance is evaluated by comparison with a standard MPC-based cascade control approach using the same adaptive ANN model. The ANN-EKFMPC-PI control configuration has shown better controller performance in terms of temperature tracking, smoother input profiles, as well as constraint-handling ability compared with the ANN-MPC with PI approach for two products in summer and winter. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.

Influence of throughfall spatial and temporal patterns on soil moisture variability under Downy oak and Scots pine stands in Mediterranean conditions

NASA Astrophysics Data System (ADS)

Llorens, Pilar; Garcia-Estringana, Pablo; Cayuela, Carles; Latron, Jérôme; Molina, Antonio; Gallart, Francesc

2015-04-01

Temporal and spatial variability of throughfall and stemflow patterns, due to differences in forest structure and seasonality of Mediterranean climate, may lead to significant changes in the volume of water that locally reaches the soil, with a potential effect on groundwater recharge and on hydrological response of forested hillslopes. Two forest stands in Mediterranean climatic conditions were studied to explore the role of vegetation on the temporal and spatial redistribution of rainfall. One is a Downy oak forest (Quercus pubescens) and the other is a Scots pine forest (Pinus sylvestris), both located in the Vallcebre research catchments (NE Spain, 42° 12'N, 1° 49'E). These plots are representative of Mediterranean mountain areas with spontaneous afforestation by Scots pine as a consequence of the abandonment of agricultural terraces, formerly covered by Downy oaks. The monitoring design of each plot consists of 20 automatic rain recorders to measuring throughfall, 7 stemflow rings connected to tipping-buckets and 40 automatic soil moisture probes. All data were recorded each 5 min. Bulk rainfall and meteorological conditions above both forest covers were also recorded, and canopy cover and biometric characteristics of the plots were measured. Results indicate a marked temporal stability of throughfall in both stands, and a lower persistence of spatial patterns in the leafless period than in the leafed one in the oaks stand. Moreover, in the oaks plot the ranks of gauges in the leafed and leafless periods were not significantly correlated, indicating different wet and dry hotspots in each season. The spatial distribution of throughfall varied significantly depending on rainfall volume, with small events having larger variability, whereas large events tended to homogenize the relative differences in point throughfall. Soil water content spatial variability increased with increasing soil water content, but direct dependence of soil water content variability on

QTL mapping for downy mildew resistance in cucumber via bulked segregant analysis using next-generation sequencing and conventional methods.

PubMed

Win, Khin Thanda; Vegas, Juan; Zhang, Chunying; Song, Kihwan; Lee, Sanghyeob

2017-01-01

QTL mapping using NGS-assisted BSA was successfully applied to an F 2 population for downy mildew resistance in cucumber. QTLs detected by NGS-assisted BSA were confirmed by conventional QTL analysis. Downy mildew (DM), caused by Pseudoperonospora cubensis, is one of the most destructive foliar diseases in cucumber. QTL mapping is a fundamental approach for understanding the genetic inheritance of DM resistance in cucumber. Recently, many studies have reported that a combination of bulked segregant analysis (BSA) and next-generation sequencing (NGS) can be a rapid and cost-effective way of mapping QTLs. In this study, we applied NGS-assisted BSA to QTL mapping of DM resistance in cucumber and confirmed the results by conventional QTL analysis. By sequencing two DNA pools each consisting of ten individuals showing high resistance and susceptibility to DM from a F 2 population, we identified single nucleotide polymorphisms (SNPs) between the two pools. We employed a statistical method for QTL mapping based on these SNPs. Five QTLs, dm2.2, dm4.1, dm5.1, dm5.2, and dm6.1, were detected and dm2.2 showed the largest effect on DM resistance. Conventional QTL analysis using the F 2 confirmed dm2.2 (R 2  = 10.8-24 %) and dm5.2 (R 2  = 14-27.2 %) as major QTLs and dm4.1 (R 2  = 8 %) as two minor QTLs, but could not detect dm5.1 and dm6.1. A new QTL on chromosome 2, dm2.1 (R 2  = 28.2 %) was detected by the conventional QTL method using an F 3 population. This study demonstrated the effectiveness of NGS-assisted BSA for mapping QTLs conferring DM resistance in cucumber and revealed the unique genetic inheritance of DM resistance in this population through two distinct major QTLs on chromosome 2 that mainly harbor DM resistance.

The pearl millet mitogen-activated protein kinase PgMPK4 is involved in responses to downy mildew infection and in jasmonic- and salicylic acid-mediated defense.

PubMed

Melvin, Prasad; Prabhu, S Ashok; Veena, Mariswamy; Shailasree, Sekhar; Petersen, Morten; Mundy, John; Shetty, Shekar H; Kini, K Ramachandra

2015-02-01

Plant mitogen-activated protein kinases (MPKs) transduce signals required for the induction of immunity triggered by host recognition of pathogen-associated molecular patterns. We isolated a full-length cDNA of a group B MPK (PgMPK4) from pearl millet. Autophosphorylation assay of recombinant PgMPK4 produced in Escherichia coli confirmed it as a kinase. Differential accumulation of PgMPK4 mRNA and kinase activity was observed between pearl millet cultivars 852B and IP18292 in response to inoculation with the downy mildew oomycete pathogen Sclerospora graminicola. This increased accumulation of PgMPK4 mRNA, kinase activity as well as nuclear-localization of PgMPK protein(s) was only detected in the S. graminicola resistant cultivar IP18292 with a ~tenfold peak at 9 h post inoculation. In the susceptible cultivar 852B, PgMPK4 mRNA and immuno-detectable nuclear PgMPK could be induced by application of the chemical elicitor β-amino butyric acid, the non-pathogenic bacteria Pseudomonas fluorescens, or by the phytohormones jasmonic acid (JA) or salicylic acid (SA). Furthermore, kinase inhibitor treatments indicated that PgMPK4 is involved in the JA- and SA-mediated expression of three defense genes, lipoxygenase, catalase 3 and polygalacturonase-inhibitor protein. These findings indicate that PgMPK/s contribute to pearl millet defense against the downy mildew pathogen by activating the expression of defense proteins.

ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

NASA Astrophysics Data System (ADS)

Chandrasekaran, Muthumari; Tamang, Santosh

2017-08-01

Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

Molecular cloning of a CC-NBS-LRR gene from Vitis quinquangularis and its expression pattern in response to downy mildew pathogen infection.

PubMed

Zhang, Shuwei; Ding, Feng; Peng, Hongxiang; Huang, Yu; Lu, Jiang

2018-02-01

Downy mildew, caused by Plasmopara viticola, can result in a substantial decrease in grapevine productivity. Vitis vinifera is a widely cultivated grapevine species, which is susceptible to this disease. Repeated pesticide applications are harmful for both the environment and human health. Thus, it is essential to develop varieties/cultivars that are resistant to downy mildew and other diseases. In our previous studies, we investigated the natural resistance of the Chinese wild grapevine V. quinquangularis accession 'PS' against P. viticola and obtained several candidate resistance (R) genes that may play important roles in plant disease resistance. In the present study, we isolated a CC-NBS-LRR-type R gene from 'PS' and designated it VqCN. Its open reading frame is 2676 bp which encodes a protein of 891 amino acids with a predicted molecular mass of 102.12 kDa and predicted isoelectric point of 6.53. Multiple alignments with other disease resistant (R) proteins revealed a conserved phosphate-binding loop (P-loop), resistance nucleotide binding site, a hydrophobic domain (GLPL) and methionine-histidine-aspartate (MHD) motifs, which are typical components of nucleotide-binding site leucine-rich repeat proteins, as well as a coiled-coil region in the N-terminus. Quantitative real-time polymerase chain reaction analysis showed that the transcript of VqCN was rapidly and highly induced after infection with P. viticola in 'PS'. Moreover, the leaves of susceptible 'Cabernet Sauvignon' transiently expressing VqCN manifested increased resistance to P. viticola. The results indicated that VqCN might play a positive role in protecting grapevine against infection with P. viticola. Cloning and functional analysis of a putative resistance gene provide a basis for disease-resistance breeding.

[Nondestructive discrimination of strawberry varieties by NIR and BP-ANN].

PubMed

Niu, Xiao-ying; Shao, Li-min; Zhao, Zhi-lei; Zhang, Xiao-yu

2012-08-01

Strawberry variety is a main factor that can influence strawberry fruit quality. The use of near-infrared reflectance spectroscopy was explored discriminate among samples of strawberry of different varieties. And the significance of difference among different varieties was analyzed by comparison of the chemical composition of the different varieties samples. The performance of models established using back propagation-artificial neural networks (BP-ANN), least squares-support vector machine and discriminant analysis were evaluated on spectra range of 4545-9090 cm(-1). The optimal model was obtained by BP-ANN with a topology of 12-18-3, which correctly classified 96.68% of calibration set and 97.14% of prediction set. And the 94.95%, 97% and 98.29% classifications were given respectively for "Tianbao" (n=99), "Fengxiang" (n=100) and "Mingxing" (n=117). One-way analysis of variance was made for comparison of the mean values for soluble solids content (SSC), titratable acid (TA), pH value and SSC-TA ratio, and the statistically significant differences were found. Principal component analysis was performed on the four chemical compositions, and obvious clustering tendencies for different varieties were found. These results showed that NIR combined with BP-ANN can discriminate strawberry of different varieties effectively, and the difference in chemical compositions of different varieties strawberry might be a chemical validation for NIR results.

Intelligent MRTD testing for thermal imaging system using ANN

NASA Astrophysics Data System (ADS)

Sun, Junyue; Ma, Dongmei

2006-01-01

The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task, for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type, the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP, but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly, we use frame grabber to capture the 4-bar target image data. Then according to image gray scale, we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets, along with known target visibility, are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm, demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.

Overexpression of Arabidopsis AnnAt8 Alleviates Abiotic Stress in Transgenic Arabidopsis and Tobacco

PubMed Central

Yadav, Deepanker; Ahmed, Israr; Shukla, Pawan; Boyidi, Prasanna; Kirti, Pulugurtha Bharadwaja

2016-01-01

Abiotic stress results in massive loss of crop productivity throughout the world. Because of our limited knowledge of the plant defense mechanisms, it is very difficult to exploit the plant genetic resources for manipulation of traits that could benefit multiple stress tolerance in plants. To achieve this, we need a deeper understanding of the plant gene regulatory mechanisms involved in stress responses. Understanding the roles of different members of plant gene families involved in different stress responses, would be a step in this direction. Arabidopsis, which served as a model system for the plant research, is also the most suitable system for the functional characterization of plant gene families. Annexin family in Arabidopsis also is one gene family which has not been fully explored. Eight annexin genes have been reported in the genome of Arabidopsis thaliana. Expression studies of different Arabidopsis annexins revealed their differential regulation under various abiotic stress conditions. AnnAt8 (At5g12380), a member of this family has been shown to exhibit ~433 and ~175 fold increase in transcript levels under NaCl and dehydration stress respectively. To characterize Annexin8 (AnnAt8) further, we have generated transgenic Arabidopsis and tobacco plants constitutively expressing AnnAt8, which were evaluated under different abiotic stress conditions. AnnAt8 overexpressing transgenic plants exhibited higher seed germination rates, better plant growth, and higher chlorophyll retention when compared to wild type plants under abiotic stress treatments. Under stress conditions transgenic plants showed comparatively higher levels of proline and lower levels of malondialdehyde compared to the wild-type plants. Real-Time PCR analyses revealed that the expression of several stress-regulated genes was altered in AnnAt8 over-expressing transgenic tobacco plants, and the enhanced tolerance exhibited by the transgenic plants can be correlated with altered expressions of

How can we deal with ANN in flood forecasting? As a simulation model or updating kernel!

NASA Astrophysics Data System (ADS)

Hassan Saddagh, Mohammad; Javad Abedini, Mohammad

2010-05-01

Flood forecasting and early warning, as a non-structural measure for flood control, is often considered to be the most effective and suitable alternative to mitigate the damage and human loss caused by flood. Forecast results which are output of hydrologic, hydraulic and/or black box models should secure accuracy of flood values and timing, especially for long lead time. The application of the artificial neural network (ANN) in flood forecasting has received extensive attentions in recent years due to its capability to capture the dynamics inherent in complex processes including flood. However, results obtained from executing plain ANN as simulation model demonstrate dramatic reduction in performance indices as lead time increases. This paper is intended to monitor the performance indices as it relates to flood forecasting and early warning using two different methodologies. While the first method employs a multilayer neural network trained using back-propagation scheme to forecast output hydrograph of a hypothetical river for various forecast lead time up to 6.0 hr, the second method uses 1D hydrodynamic MIKE11 model as forecasting model and multilayer neural network as updating kernel to monitor and assess the performance indices compared to ANN alone in light of increase in lead time. Results presented in both graphical and tabular format indicate superiority of MIKE11 coupled with ANN as updating kernel compared to ANN as simulation model alone. While plain ANN produces more accurate results for short lead time, the errors increase expeditiously for longer lead time. The second methodology provides more accurate and reliable results for longer forecast lead time.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Students and teachers look on as STS-127 Commander Mark Polansky, seated left on stage talks about the mission to the International Space Station as other crew members Chris Cassidy, Doug Hurley, David Wolf, Tom Marshburn looks on during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Photo Credit: (NASA/Paul E. Alers)

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Canadian Space Agency astronaut Julie Payette, right, a mission specialist on STS-127, talks with two unidentified students during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Payette, along with the rest of the crew from STS-127, visited with students at the school Thursday. Photo Credit: (NASA/Paul E. Alers)

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Ajani Young, a fourth grade student at Anne Beers Elementary school, at podium, introduces the crew of STS-127 during their visit, Thursday, Sept. 24, 2009, in Washington. Seated from left are crew members, Chris Cassidy, Doug Hurley, Commander Mark Polansky, David Wolf, Tom Marshburn and Canadian Space Agency astronaut Julie Payette. Photo Credit: (NASA/Paul E. Alers)

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

NASA Astrophysics Data System (ADS)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

The final days of Edgar Allan Poe: clues to an old mystery using 21st century medical science.

PubMed

Francis, Roger A

This study examines all documented information regarding the final days and death of Edgar Allan Poe (1809-1849), in an attempt to determine the most likely cause of death of the American poet, short story writer, and literary critic. Information was gathered from letters, newspaper accounts, and magazine articles written during the period after Poe's death, and also from biographies and medical journal articles written up until the present. A chronology of Poe's final days was constructed, and this was used to form a differential diagnosis of possible causes of death. Death theories over the last 160 years were analyzed using this information. This analysis, along with a review of Poe's past medical history, would seem to support an alcohol-related cause of death.

Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review.

PubMed

Malkin, Zinovy

2016-04-01

The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing the frequency standards deviations. For the past decades, AVAR has increasingly been used in geodesy and astrometry to assess the noise characteristics in geodetic and astrometric time series. A specific feature of astrometric and geodetic measurements, as compared with clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. In addition, some physically connected scalar time series naturally form series of multidimensional vectors. For example, three station coordinates time series X, Y, and Z can be combined to analyze 3-D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multidimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multidimensional AVAR (MAVAR), and weighted multidimensional AVAR (WMAVAR), were introduced to overcome these deficiencies. In this paper, a brief review is given of the experience of using AVAR and its modifications in processing astrogeodetic time series.

Mapping brain circuits of reward and motivation: in the footsteps of Ann Kelley.

PubMed

Richard, Jocelyn M; Castro, Daniel C; Difeliceantonio, Alexandra G; Robinson, Mike J F; Berridge, Kent C

2013-11-01

Ann Kelley was a scientific pioneer in reward neuroscience. Her many notable discoveries included demonstrations of accumbens/striatal circuitry roles in eating behavior and in food reward, explorations of limbic interactions with hypothalamic regulatory circuits, and additional interactions of motivation circuits with learning functions. Ann Kelley's accomplishments inspired other researchers to follow in her footsteps, including our own laboratory group. Here we describe results from several lines of our research that sprang in part from earlier findings by Kelley and colleagues. We describe hedonic hotspots for generating intense pleasure 'liking', separate identities of 'wanting' versus 'liking' systems, a novel role for dorsal neostriatum in generating motivation to eat, a limbic keyboard mechanism in nucleus accumbens for generating intense desire versus intense dread, and dynamic limbic transformations of learned memories into motivation. We describe how origins for each of these themes can be traced to fundamental contributions by Ann Kelley. Copyright © 2013 Elsevier Ltd. All rights reserved.

Twenty-Five Years of Applications of the Modified Allan Variance in Telecommunications.

PubMed

Bregni, Stefano

2016-04-01

The Modified Allan Variance (MAVAR) was originally defined in 1981 for measuring frequency stability in precision oscillators. Due to its outstanding accuracy in discriminating power-law noise, it attracted significant interest among telecommunications engineers since the early 1990s, when it was approved as a standard measure in international standards, redressed as Time Variance (TVAR), for specifying the time stability of network synchronization signals and of equipment clocks. A dozen years later, the usage of MAVAR was also introduced for Internet traffic analysis to estimate self-similarity and long-range dependence. Further, in this field, it demonstrated superior accuracy and sensitivity, better than most popular tools already in use. This paper surveys the last 25 years of progress in extending the field of application of the MAVAR in telecommunications. First, the rationale and principles of the MAVAR are briefly summarized. Its adaptation as TVAR for specification of timing stability is presented. The usage of MAVAR/TVAR in telecommunications standards is reviewed. Examples of measurements on real telecommunications equipment clocks are presented, providing an overview on their actual performance in terms of MAVAR. Moreover, applications of MAVAR to network traffic analysis are surveyed. The superior accuracy of MAVAR in estimating long-range dependence is emphasized by highlighting some remarkable practical examples of real network traffic analysis.

Professor Ann De Vaney and a Good Conversation.

ERIC Educational Resources Information Center

Nichols, Randall G.

The author begins this paper by explaining that in examining 10 works by Ann De Vaney his goal is to see what her writing generally reveals about her playing close attention to people-to research subjects, to subjects otherwise addressed in the works, to readers of her works. The author attempts to address each by asking basic questions: (1) What…

The Anne Frank Haven in an Israeli Kibbutz.

PubMed

Dror, Y

1995-01-01

The Anne Frank Haven, founded in 1956, in the Israeli Kibbutz Sasa provides a unique educational program for coping with muticultural and integration problems. It is a holistic, regional junior and senior high school system within the holistic community of three kibbutzim. The Haven has been the subject of much research into "Moral Development," carried out by Wolins (1969, 1971), and mainly by Kohlberg (1971), his doctoral students Reimer and Snarey and other colleagues. In the seventies and eighties they used the Kibbutz example as a model for the "Just Community" approach. In the early nineties, an Israeli group evaluated the success of the program and its rationale, taking into consideration all the "educational factors" of the community, in the Haven, and in the kibbutzim around it. This article offers a comprehensive picture of the Kohlbergian moral-developmental research at the Anne Frank Haven, including all the relevant references and evaluations of the Haven as a part of the "Just Community" approach. It concludes with a suggestion for another approach--"Community Education" research in the same Haven--as an example of present and future studies in the area of "Moral" and "Values" education.

Late-Night Shared-Ride Taxi Transit in Ann Arbor, MI

DOT National Transportation Integrated Search

1984-10-01

The Ann Arbor Transportation Authority introduced Night Ride, a late-night shared-ride taxi transit service, in mid-March 1982. The service was provided through a contract with a local taxicab company and funded through a demonstration grant from the...

Further Insights into the Allan-Herndon-Dudley Syndrome: Clinical and Functional Characterization of a Novel MCT8 Mutation.

PubMed

Armour, Christine M; Kersseboom, Simone; Yoon, Grace; Visser, Theo J

2015-01-01

Mutations in the thyroid hormone (TH) transporter MCT8 have been identified as the cause for Allan-Herndon-Dudley Syndrome (AHDS), characterized by severe psychomotor retardation and altered TH serum levels. Here we report a novel MCT8 mutation identified in 4 generations of one family, and its functional characterization. Proband and family members were screened for 60 genes involved in X-linked cognitive impairment and the MCT8 mutation was confirmed. Functional consequences of MCT8 mutations were studied by analysis of [125I]TH transport in fibroblasts and transiently transfected JEG3 and COS1 cells, and by subcellular localization of the transporter. The proband and a male cousin demonstrated clinical findings characteristic of AHDS. Serum analysis showed high T3, low rT3, and normal T4 and TSH levels in the proband. A MCT8 mutation (c.869C>T; p.S290F) was identified in the proband, his cousin, and several female carriers. Functional analysis of the S290F mutant showed decreased TH transport, metabolism and protein expression in the three cell types, whereas the S290A mutation had no effect. Interestingly, both uptake and efflux of T3 and T4 was impaired in fibroblasts of the proband, compared to his healthy brother. However, no effect of the S290F mutation was observed on TH efflux from COS1 and JEG3 cells. Immunocytochemistry showed plasma membrane localization of wild-type MCT8 and the S290A and S290F mutants in JEG3 cells. We describe a novel MCT8 mutation (S290F) in 4 generations of a family with Allan-Herndon-Dudley Syndrome. Functional analysis demonstrates loss-of-function of the MCT8 transporter. Furthermore, our results indicate that the function of the S290F mutant is dependent on cell context. Comparison of the S290F and S290A mutants indicates that it is not the loss of Ser but its substitution with Phe, which leads to S290F dysfunction.

Comparative effects of glyphosate and atrazine in chloroplast ultrastructure of wheat and downy brome. [Triticum aestivum; Bromus tectorum

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

Auge, R.M.; Gealy, D.R.; Ogg, A.G.

1987-04-01

Developing and mature leaves of winter wheat (Triticum aestivum L. var. Daws) and the weed species downy brome (Bromus tectorum L.) were subjected to 10 mM (foliar application) and 1 mM (root application) herbicide solutions. Glyphosate (N-(phosphonomethyl) glycine) and atrazine (2-chloro-4-(ethyl-amino)-6-(isopropylamino)-s-triazine) were prepared in a carrier composed of 5% soybean oil concentrate, 35% acetone and 60% water. Penetration experiments with /sup 3/H-labelled herbicides assessed what percentage of herbicide entered leaves, and microautoradiography was used to determine qualitatively how much herbicide was present in the sections viewed with TEM. Tissue was excised at 4, 18, 62 and 200 hours, and thenmore » either freeze-substituted or fixed chemically. Ultrastructural effects of each herbicide on chloroplasts from leaves of newly-germinated seedlings and of well-tillered plants are depicted and discussed. Temporal differences in response of chloroplasts to each herbicide are noted.« less

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

NASA Astrophysics Data System (ADS)

Mandal, Sukomal; Rao, Subba; N., Harish; Lokesha

2012-06-01

The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

STS-127 Commander Mark Polansky, center, speaks to students during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Polansky, along with the rest of the crew from STS-127, visited with students at the school Thursday. Seated from left are Canadian Space Agency astronaut Julie Payette, Chris Cassidy, Doug Hurley, David Wolf and Tom Marshburn. Photo Credit: (NASA/Paul E. Alers)

Development and Application of ANN Model for Worker Assignment into Virtual Cells of Large Sized Configurations

NASA Astrophysics Data System (ADS)

Murali, R. V.; Puri, A. B.; Fathi, Khalid

2010-10-01

This paper presents an extended version of study already undertaken on development of an artificial neural networks (ANNs) model for assigning workforce into virtual cells under virtual cellular manufacturing systems (VCMS) environments. Previously, the same authors have introduced this concept and applied it to virtual cells of two-cell configuration and the results demonstrated that ANNs could be a worth applying tool for carrying out workforce assignments. In this attempt, three-cell configurations problems are considered for worker assignment task. Virtual cells are formed under dual resource constraint (DRC) context in which the number of available workers is less than the total number of machines available. Since worker assignment tasks are quite non-linear and highly dynamic in nature under varying inputs & conditions and, in parallel, ANNs have the ability to model complex relationships between inputs and outputs and find similar patterns effectively, an attempt was earlier made to employ ANNs into the above task. In this paper, the multilayered perceptron with feed forward (MLP-FF) neural network model has been reused for worker assignment tasks of three-cell configurations under DRC context and its performance at different time periods has been analyzed. The previously proposed worker assignment model has been reconfigured and cell formation solutions available for three-cell configuration in the literature are used in combination to generate datasets for training ANNs framework. Finally, results of the study have been presented and discussed.

Decolonizing the Choctaws: Teaching LeAnne Howe's "Shell Shaker"

ERIC Educational Resources Information Center

Hollrah, Patrice

2004-01-01

"Shell Shaker" (2001) by LeAnne Howe (Choctaw) is a novel that gives students an opportunity to learn that the history and culture of the Choctaw Nation of Oklahoma are alive today. Winner of the Before Columbus Foundation American Book Award in 2002, the novel deals with two parallel stories that converge in the present, one about the eighteenth…

An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment

PubMed Central

de Cos Juez, Francisco J.; Lasheras, Fernando Sánchez; Roqueñí, Nieves; Osborn, James

2012-01-01

In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A). PMID:23012524

1. JoAnn SieburgBaker, Photographer, September 1977. OVERALL VIEW OF ROUNDHOUSE. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. JoAnn Sieburg-Baker, Photographer, September 1977. OVERALL VIEW OF ROUNDHOUSE. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

PubMed

Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

2016-11-01

This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R 2 ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016. © 2016 American Institute of Chemical Engineers.

10. JoAnn SieburgBaker, Photographer, September 1977. INTERIOR VIEW OF BACK ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

10. JoAnn Sieburg-Baker, Photographer, September 1977. INTERIOR VIEW OF BACK SHOP. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Analysis of nonlinear relationships in dual epidemics, and its application to the management of grapevine downy and powdery mildews.

PubMed

Savary, Serge; Delbac, Lionel; Rochas, Amélie; Taisant, Guillaume; Willocquet, Laetitia

2009-08-01

Dual epidemics are defined as epidemics developing on two or several plant organs in the course of a cropping season. Agricultural pathosystems where such epidemics develop are often very important, because the harvestable part is one of the organs affected. These epidemics also are often difficult to manage, because the linkage between epidemiological components occurring on different organs is poorly understood, and because prediction of the risk toward the harvestable organs is difficult. In the case of downy mildew (DM) and powdery mildew (PM) of grapevine, nonlinear modeling and logistic regression indicated nonlinearity in the foliage-cluster relationships. Nonlinear modeling enabled the parameterization of a transmission coefficient that numerically links the two components, leaves and clusters, in DM and PM epidemics. Logistic regression analysis yielded a series of probabilistic models that enabled predicting preset levels of cluster infection risks based on DM and PM severities on the foliage at successive crop stages. The usefulness of this framework for tactical decision-making for disease control is discussed.

Estimating SPT-N Value Based on Soil Resistivity using Hybrid ANN-PSO Algorithm

NASA Astrophysics Data System (ADS)

Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

2018-04-01

Standard Penetration Resistance (N value) is used in many empirical geotechnical engineering formulas. Meanwhile, soil resistivity is a measure of soil’s resistance to electrical flow. For a particular site, usually, only a limited N value data are available. In contrast, resistivity data can be obtained extensively. Moreover, previous studies showed evidence of a correlation between N value and resistivity value. Yet, no existing method is able to interpret resistivity data for estimation of N value. Thus, the aim is to develop a method for estimating N-value using resistivity data. This study proposes a hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) method to estimate N value using resistivity data. Five different ANN-PSO models based on five boreholes were developed and analyzed. The performance metrics used were the coefficient of determination, R2 and mean absolute error, MAE. Analysis of result found that this method can estimate N value (R2 best=0.85 and MAEbest=0.54) given that the constraint, Δ {\\bar{l}}ref, is satisfied. The results suggest that ANN-PSO method can be used to estimate N value with good accuracy.

Anne S. Young: Professor and Variable Star Observer Extraordinaire

NASA Astrophysics Data System (ADS)

Bracher, Katherine

2011-05-01

Anne Sewell Young (1871-1961) was one of the eight original members of the AAVSO, to which she contributed more than 6500 observations over 33 years. She also taught astronomy for 37 years at Mount Holyoke College; among her students was Helen Sawyer Hogg. This paper will look at her life and career both at Mount Holyoke and with the AAVSO.

Jo Ann Rinaudo, PhD | Division of Cancer Prevention

Cancer.gov

Dr. Jo Ann Rinaudo is a Program Director in the Cancer Biomarkers Research Group in the Division of Cancer Prevention at the National Cancer Institute. She received a doctoral degree from the University of Toronto, where she studied chemical carcinogenesis in the liver. She was in the pathology department and has a broad background in human disease. Post-graduate training

3. JoAnn SieburgBaker, Photographer, September 1977. VIEW OF BACK SHOP ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. JoAnn Sieburg-Baker, Photographer, September 1977. VIEW OF BACK SHOP FROM SOUTHEAST. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

7. JoAnn SieburgBaker, Photographer, September 1977. VIEW OF OFFICES IN ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

7. JoAnn Sieburg-Baker, Photographer, September 1977. VIEW OF OFFICES IN BACK SHOP. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

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

Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu

Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT,more » status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.« less

Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

PubMed

Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

2017-05-01

This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

Abiotic stresses affect Trichoderma harzianum T39-induced resistance to downy mildew in grapevine.

PubMed

Roatti, Benedetta; Perazzolli, Michele; Gessler, Cesare; Pertot, Ilaria

2013-12-01

Enhancement of plant defense through the application of resistance inducers seems a promising alternative to chemical fungicides for controlling crop diseases but the efficacy can be affected by abiotic factors in the field. Plants respond to abiotic stresses with hormonal signals that may interfere with the mechanisms of induced systemic resistance (ISR) to pathogens. In this study, we exposed grapevines to heat, drought, or both to investigate the effects of abiotic stresses on grapevine resistance induced by Trichoderma harzianum T39 (T39) to downy mildew. Whereas the efficacy of T39-induced resistance was not affected by exposure to heat or drought, it was significantly reduced by combined abiotic stresses. Decrease of leaf water potential and upregulation of heat-stress markers confirmed that plants reacted to abiotic stresses. Basal expression of defense-related genes and their upregulation during T39-induced resistance were attenuated by abiotic stresses, in agreement with the reduced efficacy of T39. The evidence reported here suggests that exposure of crops to abiotic stress should be carefully considered to optimize the use of resistance inducers, especially in view of future global climate changes. Expression analysis of ISR marker genes could be helpful to identify when plants are responding to abiotic stresses, in order to optimize treatments with resistance inducers in field.

5. JoAnn SieburgBaker, Photographer, September 1977. VIEW OF ICE HOUSE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. JoAnn Sieburg-Baker, Photographer, September 1977. VIEW OF ICE HOUSE AND SURROUNDING BUILDINGS. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Lucy Maude Montgomery and Anne of Green Gables: An Early Description of Attention-Deficit/Hyperactivity Disorder.

PubMed

Edison, Jessica Katz; Clardy, Christopher

2017-07-01

Attention-deficit/hyperactivity disorder (ADHD) was added to the Diagnostic and Statistical Manual of Mental Disorders, third edition, revised in 1987. Similar disorders had appeared earlier, and many consider the first description of ADHD to be a lecture in 1902 about children with an "abnormal defect in moral control" but normal intelligence. This definition of ADHD is more alarming than the current one. Anne Shirley, the protagonist of the novel Anne of Green Gables (written by Lucy Maude Montgomery and published in 1908), shares the hyperactive and inattentive qualities that fit the current definition of ADHD. She also lacks the menacing characteristics of the 1902 description. This indicates that ADHD, by its modern definition, was probably present in the early 1900s. Furthermore, the character of Anne Shirley shares many biographical similarities with her author, suggesting that Montgomery herself may have had ADHD. Thus, looking at literature from the past not only provides insight into the timeline of ADHD, but also into the thought process of an individual with ADHD. By viewing literary classics through a medical lens, we may gain insight into other diseases as well. [Pediatr Ann. 2017; 46(7):e270-e272.]. Copyright 2017, SLACK Incorporated.

4. JoAnn SieburgBaker, Photographer, September 1977. OVERALL VIEW OF BACK ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. JoAnn Sieburg-Baker, Photographer, September 1977. OVERALL VIEW OF BACK SHOP FROM ROOF OF ROUNDHOUSE. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Evaluation of the advanced operating system of the Ann Arbor Transit Authority

DOT National Transportation Integrated Search

1999-10-01

These reports constitute an evaluation of the intelligent transportation system deployment efforts of the Ann Arbor Transportation Authority. These efforts, collectively termed "Advanced Operating System" (AOS), represent a vision of an integrated ad...

Identification of downy mildew resistance gene candidates by positional cloning in maize (Zea mays subsp. mays; Poaceae)1

PubMed Central

Kim, Jae Yoon; Moon, Jun-Cheol; Kim, Hyo Chul; Shin, Seungho; Song, Kitae; Kim, Kyung-Hee; Lee, Byung-Moo

2017-01-01

Premise of the study: Positional cloning in combination with phenotyping is a general approach to identify disease-resistance gene candidates in plants; however, it requires several time-consuming steps including population or fine mapping. Therefore, in the present study, we suggest a new combined strategy to improve the identification of disease-resistance gene candidates. Methods and Results: Downy mildew (DM)–resistant maize was selected from five cultivars using a spreader row technique. Positional cloning and bioinformatics tools were used to identify the DM-resistance quantitative trait locus marker (bnlg1702) and 47 protein-coding gene annotations. Eventually, five DM-resistance gene candidates, including bZIP34, Bak1, and Ppr, were identified by quantitative reverse-transcription PCR (RT-PCR) without fine mapping of the bnlg1702 locus. Conclusions: The combined protocol with the spreader row technique, quantitative trait locus positional cloning, and quantitative RT-PCR was effective for identifying DM-resistance candidate genes. This cloning approach may be applied to other whole-genome-sequenced crops or resistance to other diseases. PMID:28224059

Further Insights into the Allan-Herndon-Dudley Syndrome: Clinical and Functional Characterization of a Novel MCT8 Mutation

PubMed Central

Yoon, Grace; Visser, Theo J.

2015-01-01

Background Mutations in the thyroid hormone (TH) transporter MCT8 have been identified as the cause for Allan-Herndon-Dudley Syndrome (AHDS), characterized by severe psychomotor retardation and altered TH serum levels. Here we report a novel MCT8 mutation identified in 4 generations of one family, and its functional characterization. Methods Proband and family members were screened for 60 genes involved in X-linked cognitive impairment and the MCT8 mutation was confirmed. Functional consequences of MCT8 mutations were studied by analysis of [125I]TH transport in fibroblasts and transiently transfected JEG3 and COS1 cells, and by subcellular localization of the transporter. Results The proband and a male cousin demonstrated clinical findings characteristic of AHDS. Serum analysis showed high T3, low rT3, and normal T4 and TSH levels in the proband. A MCT8 mutation (c.869C>T; p.S290F) was identified in the proband, his cousin, and several female carriers. Functional analysis of the S290F mutant showed decreased TH transport, metabolism and protein expression in the three cell types, whereas the S290A mutation had no effect. Interestingly, both uptake and efflux of T3 and T4 was impaired in fibroblasts of the proband, compared to his healthy brother. However, no effect of the S290F mutation was observed on TH efflux from COS1 and JEG3 cells. Immunocytochemistry showed plasma membrane localization of wild-type MCT8 and the S290A and S290F mutants in JEG3 cells. Conclusions We describe a novel MCT8 mutation (S290F) in 4 generations of a family with Allan-Herndon-Dudley Syndrome. Functional analysis demonstrates loss-of-function of the MCT8 transporter. Furthermore, our results indicate that the function of the S290F mutant is dependent on cell context. Comparison of the S290F and S290A mutants indicates that it is not the loss of Ser but its substitution with Phe, which leads to S290F dysfunction. PMID:26426690

ANN based Performance Evaluation of BDI for Condition Monitoring of Induction Motor Bearings

NASA Astrophysics Data System (ADS)

Patel, Raj Kumar; Giri, V. K.

2017-06-01

One of the critical parts in rotating machines is bearings and most of the failure arises from the defective bearings. Bearing failure leads to failure of a machine and the unpredicted productivity loss in the performance. Therefore, bearing fault detection and prognosis is an integral part of the preventive maintenance procedures. In this paper vibration signal for four conditions of a deep groove ball bearing; normal (N), inner race defect (IRD), ball defect (BD) and outer race defect (ORD) were acquired from a customized bearing test rig, under four different conditions and three different fault sizes. Two approaches have been opted for statistical feature extraction from the vibration signal. In the first approach, raw signal is used for statistical feature extraction and in the second approach statistical features extracted are based on bearing damage index (BDI). The proposed BDI technique uses wavelet packet node energy coefficients analysis method. Both the features are used as inputs to an ANN classifier to evaluate its performance. A comparison of ANN performance is made based on raw vibration data and data chosen by using BDI. The ANN performance has been found to be fairly higher when BDI based signals were used as inputs to the classifier.

Host Jumps and Radiation, Not Co-Divergence Drives Diversification of Obligate Pathogens. A Case Study in Downy Mildews and Asteraceae.

PubMed

Choi, Young-Joon; Thines, Marco

2015-01-01

Even though the microevolution of plant hosts and pathogens has been intensely studied, knowledge regarding macro-evolutionary patterns is limited. Having the highest species diversity and host-specificity among Oomycetes, downy mildews are a useful a model for investigating long-term host-pathogen coevolution. We show that phylogenies of Bremia and Asteraceae are significantly congruent. The accepted hypothesis is that pathogens have diverged contemporarily with their hosts. But maximum clade age estimation and sequence divergence comparison reveal that congruence is not due to long-term coevolution but rather due to host-shift driven speciation (pseudo-cospeciation). This pattern results from parasite radiation in related hosts, long after radiation and speciation of the hosts. As large host shifts free pathogens from hosts with effector triggered immunity subsequent radiation and diversification in related hosts with similar innate immunity may follow, resulting in a pattern mimicking true co-divergence, which is probably limited to the terminal nodes in many pathogen groups.

Host Jumps and Radiation, Not Co‐Divergence Drives Diversification of Obligate Pathogens. A Case Study in Downy Mildews and Asteraceae

PubMed Central

Choi, Young-Joon; Thines, Marco

2015-01-01

Even though the microevolution of plant hosts and pathogens has been intensely studied, knowledge regarding macro-evolutionary patterns is limited. Having the highest species diversity and host-specificity among Oomycetes, downy mildews are a useful a model for investigating long-term host-pathogen coevolution. We show that phylogenies of Bremia and Asteraceae are significantly congruent. The accepted hypothesis is that pathogens have diverged contemporarily with their hosts. But maximum clade age estimation and sequence divergence comparison reveal that congruence is not due to long-term coevolution but rather due to host-shift driven speciation (pseudo-cospeciation). This pattern results from parasite radiation in related hosts, long after radiation and speciation of the hosts. As large host shifts free pathogens from hosts with effector triggered immunity subsequent radiation and diversification in related hosts with similar innate immunity may follow, resulting in a pattern mimicking true co-divergence, which is probably limited to the terminal nodes in many pathogen groups. PMID:26230508

Archaeological Data Recovery at the Mary Ann Cole Site

DTIC Science & Technology

1981-06-01

documents the methods and results of archaeological excavations conducted at the Mary Ann Cole Site (12Crl) near Leavenworth, Indiana. The purpose of the...the area now range from 363 feet to 953 feet above sea level (Wingard 1975). The pre-Pleistocene drainage systems differed substantially from the...defined for this report, the Wyandotte chert zone consists of different types of "chert which are often stratigraphically distinct, but also Intergrade

WEPP and ANN models for simulating soil loss and runoff in a semi-arid Mediterranean region.

PubMed

Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam

2011-09-01

This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.

Modelling soil erosion in a Mediterranean watershed: Comparison between SWAT and AnnAGNPS models.

PubMed

Abdelwahab, O M M; Ricci, G F; De Girolamo, A M; Gentile, F

2018-06-20

In this study, the simulations generated by two of the most widely used hydrological basin-scale models, the Annualized Agricultural Non-Point Source (AnnAGNPS) and the Soil and Water Assessment Tool (SWAT), were compared in a Mediterranean watershed, the Carapelle (Apulia, Southern Italy). Input data requirements, time and efforts needed for input preparation, strength and weakness points of each model, ease of use and limitations were evaluated in order to give information to users. Models were calibrated and validated at monthly time scale for hydrology and sediment load using a four year period of observations (streamflow and suspended sediment concentrations). In the driest year, the specific sediment load measured at the outlet was 0.89 t ha -1 yr -1 , while the simulated values were 0.83 t ha -1 yr -1 and 1.99 t ha -1 yr -1 for SWAT and AnnAGNPS, respectively. In the wettest year, the specific measured sediment load was 7.45 t ha -1 yr -1 , and the simulated values were 8.27 t ha -1 yr -1 and 6.23 t ha -1 yr -1 for SWAT and AnnAGNPS, respectively. Both models showed from fair to a very good correlation between observed and simulated streamflow and satisfactory for sediment load. Results showed that most of the basin is under moderate (1.4-10 t ha -1 yr -1 ) and high-risk erosion (> 10 t ha -1 yr -1 ). The sediment yield predicted by the SWAT and AnnAGNPS models were compared with estimates of soil erosion simulated by models for Europe (PESERA and RUSLE2015). The average gross erosion estimated by the RUSLE2015 model (12.5 t ha -1 yr -1 ) resulted comparable with the average specific sediment yield estimated by SWAT (8.8 t ha -1 yr -1 ) and AnnAGNPS (5.6 t ha -1 yr -1 ), while it was found that the average soil erosion estimated by PESERA is lower than the other estimates (1.2 t ha -1 yr -1 ). Copyright © 2018 Elsevier Inc. All rights reserved.

Long-term solar UV radiation reconstructed by Artificial Neural Networks (ANN)

NASA Astrophysics Data System (ADS)

Feister, U.; Junk, J.; Woldt, M.

2008-01-01

Artificial Neural Networks (ANN) are efficient tools to derive solar UV radiation from measured meteorological parameters such as global radiation, aerosol optical depths and atmospheric column ozone. The ANN model has been tested with different combinations of data from the two sites Potsdam and Lindenberg, and used to reconstruct solar UV radiation at eight European sites by more than 100 years into the past. Annual totals of UV radiation derived from reconstructed daily UV values reflect interannual variations and long-term patterns that are compatible with variabilities and changes of measured input data, in particular global dimming by about 1980-1990, subsequent global brightening, volcanic eruption effects such as that of Mt. Pinatubo, and the long-term ozone decline since the 1970s. Patterns of annual erythemal UV radiation are very similar at sites located at latitudes close to each other, but different patterns occur between UV radiation at sites in different latitude regions.

Development and dissection of diagnostic SNP markers for the downy mildew resistance genes Pl Arg and Pl 8 and maker-assisted gene pyramiding in sunflower (Helianthus annuus L.).

PubMed

Qi, L L; Talukder, Z I; Hulke, B S; Foley, M E

2017-06-01

Diagnostic DNA markers are an invaluable resource in breeding programs for successful introgression and pyramiding of disease resistance genes. Resistance to downy mildew (DM) disease in sunflower is mediated by Pl genes which are known to be effective against the causal fungus, Plasmopara halstedii. Two DM resistance genes, Pl Arg and Pl 8 , are highly effective against P. halstedii races in the USA, and have been previously mapped to the sunflower linkage groups (LGs) 1 and 13, respectively, using simple sequence repeat (SSR) markers. In this study, we developed high-density single nucleotide polymorphism (SNP) maps encompassing the Pl arg and Pl 8 genes and identified diagnostic SNP markers closely linked to these genes. The specificity of the diagnostic markers was validated in a highly diverse panel of 548 sunflower lines. Dissection of a large marker cluster co-segregated with Pl Arg revealed that the closest SNP markers NSA_007595 and NSA_001835 delimited Pl Arg to an interval of 2.83 Mb on the LG1 physical map. The SNP markers SFW01497 and SFW06597 delimited Pl 8 to an interval of 2.85 Mb on the LG13 physical map. We also developed sunflower lines with homozygous, three gene pyramids carrying Pl Arg , Pl 8 , and the sunflower rust resistance gene R 12 using the linked SNP markers from a segregating F 2 population of RHA 340 (carrying Pl 8 )/RHA 464 (carrying Pl Arg and R 12 ). The high-throughput diagnostic SNP markers developed in this study will facilitate marker-assisted selection breeding, and the pyramided sunflower lines will provide durable resistance to downy mildew and rust diseases.

2. JoAnn SieburgBaker, Photographer, September 1977. SECTION SHOWING BACK OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. JoAnn Sieburg-Baker, Photographer, September 1977. SECTION SHOWING BACK OF ROUNDHOUSE AND END OF BACK SHOP WHERE CRANE WAS LOCATED. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

A Curve Fitting Approach Using ANN for Converting CT Number to Linear Attenuation Coefficient for CT-based PET Attenuation Correction

NASA Astrophysics Data System (ADS)

Lai, Chia-Lin; Lee, Jhih-Shian; Chen, Jyh-Cheng

2015-02-01

Energy-mapping, the conversion of linear attenuation coefficients (μ) calculated at the effective computed tomography (CT) energy to those corresponding to 511 keV, is an important step in CT-based attenuation correction (CTAC) for positron emission tomography (PET) quantification. The aim of this study was to implement energy-mapping step by using curve fitting ability of artificial neural network (ANN). Eleven digital phantoms simulated by Geant4 application for tomographic emission (GATE) and 12 physical phantoms composed of various volume concentrations of iodine contrast were used in this study to generate energy-mapping curves by acquiring average CT values and linear attenuation coefficients at 511 keV of these phantoms. The curves were built with ANN toolbox in MATLAB. To evaluate the effectiveness of the proposed method, another two digital phantoms (liver and spine-bone) and three physical phantoms (volume concentrations of 3%, 10% and 20%) were used to compare the energy-mapping curves built by ANN and bilinear transformation, and a semi-quantitative analysis was proceeded by injecting 0.5 mCi FDG into a SD rat for micro-PET scanning. The results showed that the percentage relative difference (PRD) values of digital liver and spine-bone phantom are 5.46% and 1.28% based on ANN, and 19.21% and 1.87% based on bilinear transformation. For 3%, 10% and 20% physical phantoms, the PRD values of ANN curve are 0.91%, 0.70% and 3.70%, and the PRD values of bilinear transformation are 3.80%, 1.44% and 4.30%, respectively. Both digital and physical phantoms indicated that the ANN curve can achieve better performance than bilinear transformation. The semi-quantitative analysis of rat PET images showed that the ANN curve can reduce the inaccuracy caused by attenuation effect from 13.75% to 4.43% in brain tissue, and 23.26% to 9.41% in heart tissue. On the other hand, the inaccuracy remained 6.47% and 11.51% in brain and heart tissue when the bilinear transformation

Symbolism--The Main Artistic Style of Katherine Anne Porter's Short Stories

ERIC Educational Resources Information Center

Wang, Ru

2010-01-01

The paper takes Katherine Anne Porter's two short stories: "Flowering Judas", "The Grave" as objects of study. It will try to analyze Porter's writing style through her imaginary conception, vivid psychological description and multiple symbolisms so that we can understand her studies and her attitudes to female psychological…

Application of back-propagation artificial neural network (ANN) to predict crystallite size and band gap energy of ZnO quantum dots

NASA Astrophysics Data System (ADS)

Pelicano, Christian Mark; Rapadas, Nick; Cagatan, Gerard; Magdaluyo, Eduardo

2017-12-01

Herein, the crystallite size and band gap energy of zinc oxide (ZnO) quantum dots were predicted using artificial neural network (ANN). Three input factors including reagent ratio, growth time, and growth temperature were examined with respect to crystallite size and band gap energy as response factors. The generated results from neural network model were then compared with the experimental results. Experimental crystallite size and band gap energy of ZnO quantum dots were measured from TEM images and absorbance spectra, respectively. The Levenberg-Marquardt (LM) algorithm was used as the learning algorithm for the ANN model. The performance of the ANN model was then assessed through mean square error (MSE) and regression values. Based on the results, the ANN modelling results are in good agreement with the experimental data.

Exploring QSARs of the interaction of flavonoids with GABA (A) receptor using MLR, ANN and SVM techniques.

PubMed

Deeb, Omar; Shaik, Basheerulla; Agrawal, Vijay K

2014-10-01

Quantitative Structure-Activity Relationship (QSAR) models for binding affinity constants (log Ki) of 78 flavonoid ligands towards the benzodiazepine site of GABA (A) receptor complex were calculated using the machine learning methods: artificial neural network (ANN) and support vector machine (SVM) techniques. The models obtained were compared with those obtained using multiple linear regression (MLR) analysis. The descriptor selection and model building were performed with 10-fold cross-validation using the training data set. The SVM and MLR coefficient of determination values are 0.944 and 0.879, respectively, for the training set and are higher than those of ANN models. Though the SVM model shows improvement of training set fitting, the ANN model was superior to SVM and MLR in predicting the test set. Randomization test is employed to check the suitability of the models.

On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

NASA Astrophysics Data System (ADS)

Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

2017-10-01

Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

ANN expert system screening for illicit amphetamines using molecular descriptors

NASA Astrophysics Data System (ADS)

Gosav, S.; Praisler, M.; Dorohoi, D. O.

2007-05-01

The goal of this study was to develop and an artificial neural network (ANN) based on computed descriptors, which would be able to classify the molecular structures of potential illicit amphetamines and to derive their biological activity according to the similarity of their molecular structure with amphetamines of known toxicity. The system is necessary for testing new molecular structures for epidemiological, clinical, and forensic purposes. It was built using a database formed by 146 compounds representing drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors, or derivatized counterparts. Their molecular structures were characterized by computing three types of descriptors: 38 constitutional descriptors (CDs), 69 topological descriptors (TDs) and 160 3D-MoRSE descriptors (3DDs). An ANN system was built for each category of variables. All three networks (CD-NN, TD-NN and 3DD-NN) were trained to distinguish between stimulant amphetamines, hallucinogenic amphetamines, and nonamphetamines. A selection of variables was performed when necessary. The efficiency with which each network identifies the class identity of an unknown sample was evaluated by calculating several figures of merit. The results of the comparative analysis are presented.

The Sally-Anne Test: An Interactional Analysis of a Dyadic Assessment

ERIC Educational Resources Information Center

Korkiakangas, Terhi; Dindar, Katja; Laitila, Aarno; Kärnä, Eija

2016-01-01

Background: The Sally-Anne test has been extensively used to examine children's theory of mind understanding. Many task-related factors have been suggested to impact children's performance on this test. Yet little is known about the interactional aspects of such dyadic assessment situations that might contribute to the ways in which children…

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

Analysis of Closely Related Antioxidant Nutraceuticals Using the Green Analytical Methodology of ANN and Smart Spectrophotometric Methods.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2017-01-01

Two new, simple, and specific green analytical methods are proposed: zero-crossing first-derivative and chemometric-based spectrophotometric artificial neural network (ANN). The proposed methods were used for the simultaneous estimation of two closely related antioxidant nutraceuticals, coenzyme Q10 (Q10) and vitamin E, in their mixtures and pharmaceutical preparations. The first method is based on the handling of spectrophotometric data with the first-derivative technique, in which both nutraceuticals were determined in ethanol, each at the zero crossing of the other. The amplitudes of the first-derivative spectra for Q10 and vitamin E were recorded at 285 and 235 nm respectively, and correlated with their concentrations. The linearity ranges of Q10 and vitamin E were 10-60 and 5.6-70 μg⋅mL-1, respectively. The second method, ANN, is a multivariate calibration method and it was developed and applied for the simultaneous determination of both analytes. A training set of 90 different synthetic mixtures containing Q10 and vitamin E in the ranges of 0-100 and 0-556 μg⋅mL-1, respectively, was prepared in ethanol. The absorption spectra of the training set were recorded in the spectral region of 230-300 nm. By relating the concentration sets (x-block) with their corresponding absorption data (y-block), gradient-descent back-propagation ANN calibration could be computed. To validate the proposed network, a set of 45 synthetic mixtures of the two drugs was used. Both proposed methods were successfully applied for the assay of Q10 and vitamin E in their laboratory-prepared mixtures and in their pharmaceutical tablets with excellent recovery. These methods offer advantages over other methods because of low-cost equipment, time-saving measures, and environmentally friendly materials. In addition, no chemical separation prior to analysis was needed. The ANN method was superior to the derivative technique because ANN can determine both drugs under nonlinear experimental

Prediction of frequency for simulation of asphalt mix fatigue tests using MARS and ANN.

PubMed

Ghanizadeh, Ali Reza; Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation.

Predicting PM10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN).

PubMed

Park, Sechan; Kim, Minjeong; Kim, Minhae; Namgung, Hyeong-Gyu; Kim, Ki-Tae; Cho, Kyung Hwa; Kwon, Soon-Bark

2018-01-05

The indoor air quality of subway systems can significantly affect the health of passengers since these systems are widely used for short-distance transit in metropolitan urban areas in many countries. The particles generated by abrasion during subway operations and the vehicle-emitted pollutants flowing in from the street in particular affect the air quality in underground subway stations. Thus the continuous monitoring of particulate matter (PM) in underground station is important to evaluate the exposure level of PM to passengers. However, it is difficult to obtain indoor PM data because the measurement systems are expensive and difficult to install and operate for significant periods of time in spaces crowded with people. In this study, we predicted the indoor PM concentration using the information of outdoor PM, the number of subway trains running, and information on ventilation operation by the artificial neural network (ANN) model. As well, we investigated the relationship between ANN's performance and the depth of underground subway station. ANN model showed a high correlation between the predicted and actual measured values and it was able to predict 67∼80% of PM at 6 subway station. In addition, we found that platform shape and depth influenced the model performance. Copyright © 2017 Elsevier B.V. All rights reserved.

78 FR 65380 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... the University of Michigan, Ann Arbor, MI. The human remains were removed from Alpena, Isabella, Grand... removed from the Devil River Mound site (20AL1) in Alpena County, MI. A resident of Ossineke, MI...

Prediction of temperature and HAZ in thermal-based processes with Gaussian heat source by a hybrid GA-ANN model

NASA Astrophysics Data System (ADS)

Fazli Shahri, Hamid Reza; Mahdavinejad, Ramezanali

2018-02-01

Thermal-based processes with Gaussian heat source often produce excessive temperature which can impose thermally-affected layers in specimens. Therefore, the temperature distribution and Heat Affected Zone (HAZ) of materials are two critical factors which are influenced by different process parameters. Measurement of the HAZ thickness and temperature distribution within the processes are not only difficult but also expensive. This research aims at finding a valuable knowledge on these factors by prediction of the process through a novel combinatory model. In this study, an integrated Artificial Neural Network (ANN) and genetic algorithm (GA) was used to predict the HAZ and temperature distribution of the specimens. To end this, a series of full factorial design of experiments were conducted by applying a Gaussian heat flux on Ti-6Al-4 V at first, then the temperature of the specimen was measured by Infrared thermography. The HAZ width of each sample was investigated through measuring the microhardness. Secondly, the experimental data was used to create a GA-ANN model. The efficiency of GA in design and optimization of the architecture of ANN was investigated. The GA was used to determine the optimal number of neurons in hidden layer, learning rate and momentum coefficient of both output and hidden layers of ANN. Finally, the reliability of models was assessed according to the experimental results and statistical indicators. The results demonstrated that the combinatory model predicted the HAZ and temperature more effective than a trial-and-error ANN model.

Balancing between sensitization and repression: the role of opium in the life and art of Edgar Allan Poe and Samuel Taylor Coleridge.

PubMed

Iszáj, Fruzsina; Demetrovics, Zsolt

2011-01-01

The creative process contains both conscious and unconscious work. Therefore, artists have to face their unconscious processes and work with emotional material that is difficult to keep under control in the course of artistic creation. Bringing these contents of consciousness to the surface needs special sensitivity and special control functions while working with them. Considering these mechanisms, psychoactive substance can serve a double function in the case of artists. On the one hand, chemical substances may enhance the artists' sensitivity. On the other hand, they can help moderate the hypersensitivity and repress extreme emotions and burdensome contents of consciousness. The authors posit how the use of opiates could have influenced the life and creative work of Edgar Allan Poe and Samuel Taylor Coleridge.

Bethany Ann Teachman: Award for Distinguished Scientific Early Career Contributions to Psychology

ERIC Educational Resources Information Center

American Psychologist, 2012

2012-01-01

Presents a short biography of one of the winners of the American Psychological Association's Award for Distinguished Scientific Early Career Contributions to Psychology. The 2012 winner is Bethany Ann Teachman for transformative, translational research integrating social cognition, life-span, and perceptual approaches to investigating clinical…

Modelling and optimization of Mn/activate carbon nanocatalysts for NO reduction: comparison of RSM and ANN techniques.

PubMed

Mousavi, Seyed Mahdi; Niaei, Aligholi; Salari, Dariush; Panahi, Parvaneh Nakhostin; Samandari, Masoud

2013-01-01

A response surface methodology (RSM) involving a central composite design was applied to the modelling and optimization of a preparation of Mn/active carbon nanocatalysts in NH3-SCR of NO at 250 degrees C and the results were compared with the artificial neural network (ANN) predicted values. The catalyst preparation parameters, including metal loading (wt%), calcination temperature and pre-oxidization degree (v/v% HNO3) were selected as influence factors on catalyst efficiency. In the RSM model, the predicted values of NO conversion were found to be in good agreement with the experimental values. Pareto graphic analysis showed that all the chosen parameters and some of the interactions were effective on response. The optimization results showed that maximum NO conversion was achieved at the optimum conditions: 10.2 v/v% HNO3, 6.1 wt% Mn loading and calcination at 480 degrees C. The ANN model was developed by a feed-forward back propagation network with the topology 3, 8 and 1 and a Levenberg-Marquardt training algorithm. The mean square error for the ANN and RSM models were 0.339 and 1.176, respectively, and the R2 values were 0.991 and 0.972, respectively, indicating the superiority of ANN in capturing the nonlinear behaviour of the system and being accurate in estimating the values of the NO conversion.

Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

NASA Astrophysics Data System (ADS)

Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

2018-02-01

This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

PubMed

Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

2018-04-25

Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

PubMed Central

Erdakov, Ivan Nikolaevich; Taha, Mohamed~Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-01-01

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth–Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness (Ra) prediction of one component in computer numerical control (CNC) turning over minimal machining time (Tm) and at prime machining costs (C). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra, Tm, and C, in relation to cutting speed, vc, depth of cut, ap, and feed per revolution, fr. For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values vc, ap, and fr. The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, Tm = 0.358 min/cm3, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed vc = 250 m/min, cutting depth ap = 1.0 mm, and feed per revolution fr = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness. PMID:29772670

Audits of Meaning: A Festschrift in Honor of Ann E. Berthoff.

ERIC Educational Resources Information Center

Smith, Louise Z., Ed.

A tribute to the work of Ann Berthoff, this book--a collection of 6 poems and 21 essays--explores issues in the philosophy and teaching of composition. Each of the five sections is introduced with a poem by Marie Ponsot. Essays and their authors consist of (1) "Genre Theory, Academic Discourse, and Writing within Disciplines" (James F.…

Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

NASA Astrophysics Data System (ADS)

Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

2018-02-01

As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm

NASA Astrophysics Data System (ADS)

Prasad, Ramendra; Deo, Ravinesh C.; Li, Yan; Maraseni, Tek

2017-11-01

Forecasting streamflow is vital for strategically planning, utilizing and redistributing water resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated with iterative input selection (IIS) algorithm (IIS-W-ANN) is evaluated for its statistical preciseness in forecasting monthly streamflow, and it is then benchmarked against M5 Tree model. To develop hybrid IIS-W-ANN model, a global predictor matrix is constructed for three local hydrological sites (Richmond, Gwydir, and Darling River) in Australia's agricultural (Murray-Darling) Basin. Model inputs comprised of statistically significant lagged combination of streamflow water level, are supplemented by meteorological data (i.e., precipitation, maximum and minimum temperature, mean solar radiation, vapor pressure and evaporation) as the potential model inputs. To establish robust forecasting models, iterative input selection (IIS) algorithm is applied to screen the best data from the predictor matrix and is integrated with the non-decimated maximum overlap discrete wavelet transform (MODWT) applied on the IIS-selected variables. This resolved the frequencies contained in predictor data while constructing a wavelet-hybrid (i.e., IIS-W-ANN and IIS-W-M5 Tree) model. Forecasting ability of IIS-W-ANN is evaluated via correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe Efficiency (ENS), root-mean-square-error (RMSE), and mean absolute error (MAE), including the percentage RMSE and MAE. While ANN models are seen to outperform M5 Tree executed for all hydrological sites, the IIS variable selector was efficient in determining the appropriate predictors, as stipulated by the better performance of the IIS coupled (ANN and M5 Tree) models relative to the models without IIS. When IIS-coupled models are integrated with MODWT, the wavelet-hybrid IIS-W-ANN and IIS-W-M5 Tree are seen to attain significantly accurate performance relative to their standalone counterparts. Importantly

BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

PubMed Central

Pi, Erxu; Mantri, Nitin; Ngai, Sai Ming; Lu, Hongfei; Du, Liqun

2013-01-01

Temperature is one of the most significant environmental factors that affects germination of grass seeds. Reliable prediction of the optimal temperature for seed germination is crucial for determining the suitable regions and favorable sowing timing for turf grass cultivation. In this study, a back-propagation-artificial-neural-network-aided dual quintic equation (BP-ANN-QE) model was developed to improve the prediction of the optimal temperature for seed germination. This BP-ANN-QE model was used to determine optimal sowing times and suitable regions for three Cynodon dactylon cultivars (C. dactylon, ‘Savannah’ and ‘Princess VII’). Prediction of the optimal temperature for these seeds was based on comprehensive germination tests using 36 day/night (high/low) temperature regimes (both ranging from 5/5 to 40/40°C with 5°C increments). Seed germination data from these temperature regimes were used to construct temperature-germination correlation models for estimating germination percentage with confidence intervals. Our tests revealed that the optimal high/low temperature regimes required for all the three bermudagrass cultivars are 30/5, 30/10, 35/5, 35/10, 35/15, 35/20, 40/15 and 40/20°C; constant temperatures ranging from 5 to 40°C inhibited the germination of all three cultivars. While comparing different simulating methods, including DQEM, Bisquare ANN-QE, and BP-ANN-QE in establishing temperature based germination percentage rules, we found that the R2 values of germination prediction function could be significantly improved from about 0.6940–0.8177 (DQEM approach) to 0.9439–0.9813 (BP-ANN-QE). These results indicated that our BP-ANN-QE model has better performance than the rests of the compared models. Furthermore, data of the national temperature grids generated from monthly-average temperature for 25 years were fit into these functions and we were able to map the germination percentage of these C. dactylon cultivars in the national scale of

Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN

PubMed Central

Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation. PMID:24688400

Ann O'Mara, PhD, RN, MPH | Division of Cancer Prevention

Cancer.gov

Dr. Ann O'Mara is Head of Palliative Research in the NCI Division of Cancer Prevention. She manages a portfolio of symptom management and palliative and end-of-life care research projects. The majority of these projects focus on the more common morbidities associated with cancer and its treatment, e.g., pain, chemotherapy induced neuropathy, fatigue, sleep disturbances, and

Optimization of thermal conductivity lightweight brick type AAC (Autoclaved Aerated Concrete) effect of Si & Ca composition by using Artificial Neural Network (ANN)

NASA Astrophysics Data System (ADS)

Zulkifli; Wiryawan, G. P.

2018-03-01

Lightweight brick is the most important component of building construction, therefore it is necessary to have lightweight thermal, mechanical and aqustic thermal properties that meet the standard, in this paper which is discussed is the domain of light brick thermal conductivity properties. The advantage of lightweight brick has a low density (500-650 kg/m3), more economical, can reduce the load 30-40% compared to conventional brick (clay brick). In this research, Artificial Neural Network (ANN) is used to predict the thermal conductivity of lightweight brick type Autoclaved Aerated Concrete (AAC). Based on the training and evaluation that have been done on 10 model of ANN with number of hidden node 1 to 10, obtained that ANN with 3 hidden node have the best performance. It is known from the mean value of MSE (Mean Square Error) validation for three training times of 0.003269. This ANN was further used to predict the thermal conductivity of four light brick samples. The predicted results for each of the AAC1, AAC2, AAC3 and AAC4 light brick samples were 0.243 W/m.K, respectively; 0.29 W/m.K; 0.32 W/m.K; and 0.32 W/m.K. Furthermore, ANN is used to determine the effect of silicon composition (Si), Calcium (Ca), to light brick thermal conductivity. ANN simulation results show that the thermal conductivity increases with increasing Si composition. Si content is allowed maximum of 26.57%, while the Ca content in the range 20.32% - 30.35%.

Processing RoxAnn sonar data to improve its categorization of lake bed surficial sediments

USGS Publications Warehouse

Cholwek, Gary; Bonde, John; Li, Xing; Richards, Carl; Yin, Karen

2000-01-01

To categorize spawning and nursery habitat for lake trout in Minnesota's near shore waters of Lake Superior, data was collected with a single beam echo sounder coupled with a RoxAnn bottom classification sensor. Test areas representative of different bottom surficial substrates were sampled. The collected data consisted of acoustic signals which showed both depth and substrate type. The location of the signals was tagged in real-time with a DGPS. All data was imported into a GIS database. To better interpret the output signal from the RoxAnn, several pattern classifiers were developed by multivariate statistical method. From the data a detailed and accurate map of lake bed bathymetry and surficial substrate types was produced. This map will be of great value to fishery and other natural resource managers.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs.

PubMed

Abbas, Adel Taha; Pimenov, Danil Yurievich; Erdakov, Ivan Nikolaevich; Taha, Mohamed Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-05-16

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth⁻Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness ( Ra ) prediction of one component in computer numerical control (CNC) turning over minimal machining time ( T m ) and at prime machining costs ( C ). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra , T m , and C , in relation to cutting speed, v c , depth of cut, a p , and feed per revolution, f r . For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values v c , a p , and f r . The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, T m = 0.358 min/cm³, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed v c = 250 m/min, cutting depth a p = 1.0 mm, and feed per revolution f r = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

ANN-based calibration model of FTIR used in transformer online monitoring

NASA Astrophysics Data System (ADS)

Li, Honglei; Liu, Xian-yong; Zhou, Fangjie; Tan, Kexiong

2005-02-01

Recently, chromatography column and gas sensor have been used in online monitoring device of dissolved gases in transformer oil. But some disadvantages still exist in these devices: consumption of carrier gas, requirement of calibration, etc. Since FTIR has high accuracy, consume no carrier gas and require no calibration, the researcher studied the application of FTIR in such monitoring device. Experiments of "Flow gas method" were designed, and spectrum of mixture composed of different gases was collected with A BOMEM MB104 FTIR Spectrometer. A key question in the application of FTIR is that: the absorbance spectrum of 3 fault key gases, including C2H4, CH4 and C2H6, are overlapped seriously at 2700~3400cm-1. Because Absorbance Law is no longer appropriate, a nonlinear calibration model based on BP ANN was setup to in the quantitative analysis. The height absorbance of C2H4, CH4 and C2H6 were adopted as quantitative feature, and all the data were normalized before training the ANN. Computing results show that the calibration model can effectively eliminate the cross disturbance to measurement.

Evaluation of effectiveness of wavelet based denoising schemes using ANN and SVM for bearing condition classification.

PubMed

Vijay, G S; Kumar, H S; Srinivasa Pai, P; Sriram, N S; Rao, Raj B K N

2012-01-01

The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR) and reducing the root-mean-square error (RMSE). In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN) and the Support Vector Machine (SVM), for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB) test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher's Criterion (FC). Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

Development of LC-MS determination method and back-propagation ANN pharmacokinetic model of corynoxeine in rat.

PubMed

Ma, Jianshe; Cai, Jinzhang; Lin, Guanyang; Chen, Huilin; Wang, Xianqin; Wang, Xianchuan; Hu, Lufeng

2014-05-15

Corynoxeine(CX), isolated from the extract of Uncaria rhynchophylla, is a useful and prospective compound in the prevention and treatment for vascular diseases. A simple and selective liquid chromatography mass spectrometry (LC-MS) method was developed to determine the concentration of CX in rat plasma. The chromatographic separation was achieved on a Zorbax SB-C18 (2.1 mm × 150 mm, 5 μm) column with acetonitrile-0.1% formic acid in water as mobile phase. Selective ion monitoring (SIM) mode was used for quantification using target ions m/z 383 for CX and m/z 237 for the carbamazepine (IS). After the LC-MS method was validated, it was applied to a back-propagation artificial neural network (BP-ANN) pharmacokinetic model study of CX in rats. The results showed that after intravenous administration of CX, it was mainly distributed in blood and eliminated quickly, t1/2 was less than 1h. The predicted concentrations generated by BP-ANN model had a high correlation coefficient (R>0.99) with experimental values. The developed BP-ANN pharmacokinetic model can be used to predict the concentration of CX in rats. Copyright © 2014 Elsevier B.V. All rights reserved.

Long-term solar UV radiation reconstructed by ANN modelling with emphasis on spatial characteristics of input data

NASA Astrophysics Data System (ADS)

Feister, U.; Junk, J.; Woldt, M.; Bais, A.; Helbig, A.; Janouch, M.; Josefsson, W.; Kazantzidis, A.; Lindfors, A.; den Outer, P. N.; Slaper, H.

2008-06-01

Artificial Neural Networks (ANN) are efficient tools to derive solar UV radiation from measured meteorological parameters such as global radiation, aerosol optical depths and atmospheric column ozone. The ANN model has been tested with different combinations of data from the two sites Potsdam and Lindenberg, and used to reconstruct solar UV radiation at eight European sites by more than 100 years into the past. Special emphasis will be given to the discussion of small-scale characteristics of input data to the ANN model. Annual totals of UV radiation derived from reconstructed daily UV values reflect interannual variations and long-term patterns that are compatible with variabilities and changes of measured input data, in particular global dimming by about 1980/1990, subsequent global brightening, volcanic eruption effects such as that of Mt. Pinatubo, and the long-term ozone decline since the 1970s. Patterns of annual erythemal UV radiation are very similar at sites located at latitudes close to each other, but different patterns occur between UV radiation at sites in different latitude regions.

Simulation of CO2 Solubility in Polystyrene-b-Polybutadieneb-Polystyrene (SEBS) by artificial intelligence network (ANN) method

NASA Astrophysics Data System (ADS)

Sharudin, R. W.; AbdulBari Ali, S.; Zulkarnain, M.; Shukri, M. A.

2018-05-01

This study reports on the integration of Artificial Neural Network (ANNs) with experimental data in predicting the solubility of carbon dioxide (CO2) blowing agent in SEBS by generating highest possible value for Regression coefficient (R2). Basically, foaming of thermoplastic elastomer with CO2 is highly affected by the CO2 solubility. The ability of ANN in predicting interpolated data of CO2 solubility was investigated by comparing training results via different method of network training. Regards to the final prediction result for CO2 solubility by ANN, the prediction trend (output generate) was corroborated with the experimental results. The obtained result of different method of training showed the trend of output generated by Gradient Descent with Momentum & Adaptive LR (traingdx) required longer training time and required more accurate input to produce better output with final Regression Value of 0.88. However, it goes vice versa with Levenberg-Marquardt (trainlm) technique as it produced better output in quick detention time with final Regression Value of 0.91.

[The embroidery work of the lady at Saint-Anne Hospital].

PubMed

Thillaud, Pierre L; Postel, Jacques

2014-01-01

In July 1974, a 72 old woman had been a patient for forty years in Sainte-Anne Hospital, Ward C. As she had again a violent brawl with her neighbour patient, she revealed being a tremendous artist. She had been confined on account of dementia paralytica in the Mecca of malariotherapy, and passionately devoted herself to embroidery. Her fancy work was rather a matter for Jean Dubuffet's art through its perfect expression and deserved being known.

Childhood and Modernity: Dark Themes in Carol Ann Duffy's Poetry for Children

ERIC Educational Resources Information Center

Whitley, David

2007-01-01

Carol Ann Duffy's three volumes of children's poetry are important and interesting because they emerge from the work of a writer whose adult poetry has persistently associated childhood with dark and difficult areas of experience. This article explores what happens to such challenging material when a poet of major significance changes the focus of…

Development of experimental design approach and ANN-based models for determination of Cr(VI) ions uptake rate from aqueous solution onto the solid biodiesel waste residue.

PubMed

Shanmugaprakash, M; Sivakumar, V

2013-11-01

In the present work, the evaluation capacities of two optimization methodologies such as RSM and ANN were employed and compared for predication of Cr(VI) uptake rate using defatted pongamia oil cake (DPOC) in both batch and column mode. The influence of operating parameters was investigated through a central composite design (CCD) of RSM using Design Expert 8.0.7.1 software. The same data was fed as input in ANN to obtain a trained the multilayer feed-forward networks back-propagation algorithm using MATLAB. The performance of the developed ANN models were compared with RSM mathematical models for Cr(VI) uptake rate in terms of the coefficient of determination (R(2)), root mean square error (RMSE) and absolute average deviation (AAD). The estimated values confirm that ANN predominates RSM representing the superiority of a trained ANN models over RSM models in order to capture the non-linear behavior of the given system. Copyright © 2013 Elsevier Ltd. All rights reserved.

Occurrence and genetic diversity of the Plasmopara halstedii virus in sunflower downy mildew populations of the world.

PubMed

Grasse, Wolfgang; Spring, Otmar

2015-03-01

Plasmopara halstedii virus (PhV) is a ss(+)RNA virus that exclusively occurs in the sunflower downy mildew pathogen Plasmopara halstedii, a biotrophic oomycete of severe economic impact. The virus origin and its genomic variability are unknown. A PCR-based screening of 128 samples of P. halstedii from five continents and up to 40 y old was conducted. PhV RNA was found in over 90 % of the isolates with no correlation to geographic origin or pathotype of its host. Sequence analyses of the two open reading frames (ORFs) revealed only 18 single nucleotide polymorphisms (SNPs) in 3873 nucleotides. The SNPs had no recognizable effect on the two encoded virus proteins. In 398 nucleotides of the untranslated regions (UTRs) of the RNA 2 strand eight additional SNPs and one short deletion was found. Modelling experiments revealed no effects of these variations on the secondary structure of the RNA. The results showed the presence of PhV in P. halstedii isolates of global origin and the existence of the virus since more than 40 y. The virus genome revealed a surprisingly low variation in both coding and noncoding parts. No sequence differences were correlated with host pathotype or geographic populations of the oomycete. Copyright © 2014 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Statistical optimization of the phytoremediation of arsenic by Ludwigia octovalvis- in a pilot reed bed using response surface methodology (RSM) versus an artificial neural network (ANN).

PubMed

Titah, Harmin Sulistiyaning; Halmi, Mohd Izuan Effendi Bin; Abdullah, Siti Rozaimah Sheikh; Hasan, Hassimi Abu; Idris, Mushrifah; Anuar, Nurina

2018-06-07

In this study, the removal of arsenic (As) by plant, Ludwigia octovalvis, in a pilot reed bed was optimized. A Box-Behnken design was employed including a comparative analysis of both Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) for the prediction of maximum arsenic removal. The predicted optimum condition using the desirability function of both models was 39 mg kg -1 for the arsenic concentration in soil, an elapsed time of 42 days (the sampling day) and an aeration rate of 0.22 L/min, with the predicted values of arsenic removal by RSM and ANN being 72.6% and 71.4%, respectively. The validation of the predicted optimum point showed an actual arsenic removal of 70.6%. This was achieved with the deviation between the validation value and the predicted values being within 3.49% (RSM) and 1.87% (ANN). The performance evaluation of the RSM and ANN models showed that ANN performs better than RSM with a higher R 2 (0.97) close to 1.0 and very small Average Absolute Deviation (AAD) (0.02) and Root Mean Square Error (RMSE) (0.004) values close to zero. Both models were appropriate for the optimization of arsenic removal with ANN demonstrating significantly higher predictive and fitting ability than RSM.

Friendly Letters on the Correspondence of Helen Keller, Anne Sullivan, and Alexander Graham Bell.

ERIC Educational Resources Information Center

Blatt, Burton

1985-01-01

Excerpts from the letters between Alexander Graham Bell and Anne Sullivan and Helen Keller are given to illustrate the educational and personal growth of Helen Keller as well as the educational philosophy of Bell regarding the education of the deaf blind. (DB)

Prophecy, patriarchy, and violence in the early modern household: the revelations of Anne Wentworth.

PubMed

Johnston, Warren

2009-10-01

In 1676 the apostate Baptist prophet Anne Wentworth (1629/30-1693?) published "A True Account of Anne Wentworths Being Cruelly, Unjustly, and Unchristianly Dealt with by Some of Those People called Anabaptists," the first in a series of pamphlets that would continue to the end of the decade. Orignially a member of a London Baptist church, Wentworth left the congregation and eventually her own home after her husband used physical force to stop her writing and prophesying. Yet Wentworth persisted in her "revelations." These prophecies increasingly focused on her response to those who were trying to stop her efforts, especially within her own household. This article examines Wentworth's writings as an effort by an early modern woman, using arguments of spiritual agency, to assert ideas about proper gender roles and household responsibilities to denounce her husband and rebut those who criticized and attempted to suppress her.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : AATA Web Survey

DOT National Transportation Integrated Search

1999-01-01

During 1997, visitors to the Ann Arbor (Michigan) Transportation Authority's worldwide web site were invited to complete an electronic questionnaire about their experience with the site. Eighty surveys were collected, representing a non-scientific se...

Carbon Cycle 2.0: Mary Ann Piette: Impact of efficient buildings

ScienceCinema

Mary Ann Piette

2017-12-09

Mary Ann Piette speaks at the Carbon Cycle 2.0 kick-off symposium Feb. 2, 2010. We emit more carbon into the atmosphere than natural processes are able to remove - an imbalance with negative consequences. Carbon Cycle 2.0 is a Berkeley Lab initiative to provide the science needed to restore this balance by integrating the Labs diverse research activities and delivering creative solutions toward a carbon-neutral energy future. http://carboncycle2.lbl.gov/

Carbon Cycle 2.0: Mary Ann Piette: Impact of efficient buildings

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

Mary Ann Piette

Mary Ann Piette speaks at the Carbon Cycle 2.0 kick-off symposium Feb. 2, 2010. We emit more carbon into the atmosphere than natural processes are able to remove - an imbalance with negative consequences. Carbon Cycle 2.0 is a Berkeley Lab initiative to provide the science needed to restore this balance by integrating the Labs diverse research activities and delivering creative solutions toward a carbon-neutral energy future. http://carboncycle2.lbl.gov/

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Archives And Records

DOT National Transportation Integrated Search

1999-01-01

This study examines data regularly maintained by the AATA (Ann Arbor Transportation Authority) for evidence of AOS (Advanced Operating System) impact. These data include on-time performance, bus trips broken because of maintenance or other incidents,...

Using AnnAGNPS to Predict the Effects of Tile Drainage Control on Nutrient and Sediment Loads for a River Basin.

PubMed

Que, Z; Seidou, O; Droste, R L; Wilkes, G; Sunohara, M; Topp, E; Lapen, D R

2015-03-01

Controlled tile drainage (CTD) can reduce pollutant loading. The Annualized Agricultural Nonpoint Source model (AnnAGNPS version 5.2) was used to examine changes in growing season discharge, sediment, nitrogen, and phosphorus loads due to CTD for a ∼3900-km agriculturally dominated river basin in Ontario, Canada. Two tile drain depth scenarios were examined in detail to mimic tile drainage control for flat cropland: 600 mm depth (CTD) and 200 mm (CTD) depth below surface. Summed for five growing seasons (CTD), direct runoff, total N, and dissolved N were reduced by 6.6, 3.5, and 13.7%, respectively. However, five seasons of summed total P, dissolved P, and total suspended solid loads increased as a result of CTD by 0.96, 1.6, and 0.23%. The AnnAGNPS results were compared with mass fluxes observed from paired experimental watersheds (250, 470 ha) in the river basin. The "test" experimental watershed was dominated by CTD and the "reference" watershed by free drainage. Notwithstanding environmental/land use differences between the watersheds and basin, comparisons of seasonal observed and predicted discharge reductions were comparable in 100% of respective cases. Nutrient load comparisons were more consistent for dissolved, relative to particulate water quality endpoints. For one season under corn crop production, AnnAGNPS predicted a 55% decrease (CTD) in dissolved N from the basin. AnnAGNPS v. 5.2 treats P transport from a surface pool perspective, which is appropriate for many systems. However, for assessment of tile drainage management practices for relatively flat tile-dominated systems, AnnAGNPS may benefit from consideration of P and particulate transport in the subsurface. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Elemental Study on Auscultaiting Diagnosis Support System of Hemodialysis Shunt Stenosis by ANN

NASA Astrophysics Data System (ADS)

Suzuki, Yutaka; Fukasawa, Mizuya; Mori, Takahiro; Sakata, Osamu; Hattori, Asobu; Kato, Takaya

It is desired to detect stenosis at an early stage to use hemodailysis shunt for longer time. Stethoscope auscultation of vascular murmurs is useful noninvasive diagnostic approach, but an experienced expert operator is necessary. Some experts often say that the high-pitch murmurs exist if the shunt becomes stenosed, and some studies report that there are some features detected at high frequency by time-frequency analysis. However, some of the murmurs are difficult to detect, and the final judgment is difficult. This study proposes a new diagnosis support system to screen stenosis by using vascular murmurs. The system is performed using artificial neural networks (ANN) with the analyzed frequency data by maximum entropy method (MEM). The author recorded vascular murmurs both before percutaneous transluminal angioplasty (PTA) and after. Examining the MEM spectral characteristics of the high-pitch stenosis murmurs, three features could be classified, which covered 85 percent of stenosis vascular murmurs. The features were learnt by the ANN, and judged. As a result, a percentage of judging the classified stenosis murmurs was 100%, and that of normal was 86%.

Computer Based Language Training: A Conversation with Duane M. Rumbaugh and Mary Ann Romski.

ERIC Educational Resources Information Center

Thomas, M. Angele

1981-01-01

An interview with Duane Rumbaugh and Mary Ann Romski, researchers on the use of alternative communication systems for severely and profoundly retarded persons, focuses on applications from their primate research and the use of a computerized keyboard system to investigate language acquisition in severely retarded persons. (CL)

Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain.

PubMed

Hussain, Amjad; Syed, Muhammad Ali; Abbas, Nasir; Hanif, Sana; Arshad, Muhammad Sohail; Bukhari, Nadeem Irfan; Hussain, Khalid; Akhlaq, Muhammad; Ahmad, Zeeshan

2016-06-01

A novel mucoadhesive buccal tablet containing flurbiprofen (FLB) and lidocaine HCl (LID) was prepared to relieve dental pain. Tablet formulations (F1-F9) were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC) and sodium alginate (SA). The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN) approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release), which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach.

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN

PubMed Central

AlSharabi, Khalil; Ibrahim, Sutrisno; Alsuwailem, Abdullah

2017-01-01

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new computer aided diagnosis (CAD) of autism ‎based on electroencephalography (EEG) signal analysis is investigated. The proposed method is based on discrete wavelet transform (DWT), entropy (En), and artificial neural network (ANN). DWT is used to decompose EEG signals into approximation and details coefficients to obtain EEG subbands. The feature vector is constructed by computing Shannon entropy values from each EEG subband. ANN classifies the corresponding EEG signal into normal or autistic based on the extracted features. The experimental results show the effectiveness of the proposed method for assisting autism diagnosis. A receiver operating characteristic (ROC) curve metric is used to quantify the performance of the proposed method. The proposed method obtained promising results tested using real dataset provided by King Abdulaziz Hospital, Jeddah, Saudi Arabia. PMID:28484720

A Practically Validated Intelligent Calibration Circuit Using Optimized ANN for Flow Measurement by Venturi

NASA Astrophysics Data System (ADS)

Venkata, Santhosh Krishnan; Roy, Binoy Krishna

2016-03-01

Design of an intelligent flow measurement technique using venturi flow meter is reported in this paper. The objectives of the present work are: (1) to extend the linearity range of measurement to 100 % of full scale input range, (2) to make the measurement technique adaptive to variations in discharge coefficient, diameter ratio of venturi nozzle and pipe (β), liquid density, and liquid temperature, and (3) to achieve the objectives (1) and (2) using an optimized neural network. The output of venturi flow meter is differential pressure. It is converted to voltage by using a suitable data conversion unit. A suitable optimized artificial neural network (ANN) is added, in place of conventional calibration circuit. ANN is trained, tested with simulated data considering variations in discharge coefficient, diameter ratio between venturi nozzle and pipe, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the objectives.

Comparison of geology of Jurassic Norphlet Mary Ann field, Mobile Bay, Alabama, to onshore regional Norphlet trends

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

Marzono, M.; Pense, G.; Andronaco, P.

The geology of the Mary Ann field is better understood in light of regional studies, which help to establish a depositional model in terms of both facies and thickness variations. These studies also illustrate major differences between onshore and offshore Norphlet deposits concerning topics such as diagenesis, hydrocarbon trapping, and migration. The Jurassic Norphlet sandstone was deposited in an arid basin extending from east Texas to Florida by a fluvial-eolian depositional system, prior to the transgression of the Smackover Formation. Until discovery of the Mary Ann field in 1979, Norphlet production was restricted to onshore areas, mostly along the Pickens-Pollardmore » fault system in Mississippi, Alabama, and Florida. The Mary Ann field is a Norphlet dry-gas accumulation, and was the first offshore field in the Gulf of Mexico to establish economic reserves in the Jurassic. The field is located in Mobile Bay, approximately 25 mi (40 km) south of Mobile, Alabama. Formed by a deep-seated (more than 20,000 ft or 6096 m) faulted salt pillow, Mary Ann field produces from a series of stacked eolian dune sands situated near the Norphlet paleocoastline. Five lithofacies have been recognized in cores from the Mobil 76 No. 2 well. Each lithofacies has a distinct reservoir quality. Optimum reservoir faces are the dune and sheet sands. Nonreservoir facies are interdune (wet and dry), marine reworked, and evaporitic sands. Following deposition, these sediments have undergone varying amounts of diagenesis. Early cementation of well-sorted sands supported the pore system during compaction. However, late cementation by chlorite, silica, and alteration of liquid hydrocarbons to an asphaltic residue have completely occluded the pore system in parts of the reservoir.« less

Effect of DEM mesh size on AnnAGNPS simulation and slope correction.

PubMed

Wang, Xiaoyan; Lin, Q

2011-08-01

The objective of this paper is to study the impact of the mesh size of the digital elevation model (DEM) on terrain attributes within an Annualized AGricultural NonPoint Source pollution (AnnAGNPS) Model simulation at watershed scale and provide a correction of slope gradient for low resolution DEMs. The effect of different grid sizes of DEMs on terrain attributes was examined by comparing eight DEMs (30, 40, 50, 60, 70, 80, 90, and 100 m). The accuracy of the AnnAGNPS stimulation on runoff, sediments, and nutrient loads is evaluated. The results are as follows: (1) Rnoff does not vary much with decrease of DEM resolution whereas soil erosion and total nitrogen (TN) load change prominently. There is little effect on runoff simulation of AnnAGNPS modeling by the amended slope using an adjusted 50 m DEM. (2) A decrease of sediment yield and TN load is observed with an increase of DEM mesh size from 30 to 60 m; a slight decrease of sediment and TN load with the DEM mesh size bigger than 60 m. There is similar trend for total phosphorus (TP) variation, but with less range of variation, the simulation of sediment, TN, and TP increase, in which sediment increase up to 1.75 times compared to the model using unadjusted 50 m DEM. In all, the amended simulation still has a large difference relative to the results using 30 m DEM. AnnAGNPS is less reliable for sediment loading prediction in a small hilly watershed. (3) Resolution of DEM has significant impact on slope gradient. The average, minimum, maximum of slope from the various DEMs reduced obviously with the decrease of DEM precision. For the grade of 0∼15°, the slopes at lower resolution DEM are generally bigger than those at higher resolution DEM. But for the grade bigger than 15°, the slopes at lower resolution DEM are generally smaller than those at higher resolution DEM. So it is necessary to adjust the slope with a fitting equation. A cubic model is used for correction of slope gradient from lower resolution to

Master Builder of Bridges between Research and Practice: An Interview with Ann Robinson

ERIC Educational Resources Information Center

Henshon, Suzanna E.

2010-01-01

This article presents an interview with Ann Robinson, a professor of educational psychology and founding director of the Center for Gifted Education at the University of Arkansas at Little Rock. She is the president of the National Association for Gifted Children (NAGC), a former editor of the Gifted Child Quarterly (GCQ), and was the first Editor…

Development Opportunities: The Effect of UMES on the Town of Princess Anne, Maryland.

ERIC Educational Resources Information Center

Sann, David; Tervala, Victor K.

A study was done of the potential economic effect of the University of Maryland Eastern Shore (UMES) campus on the nearby town of Princess Anne, a small rural community. The study used estimates made by a UMES faculty member which projected that UMES students in 1990 spent over $7 million on goods and services unrelated to educational expenses.…

Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study.

PubMed

Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

2007-06-21

Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus. The results of this study

History of psychosurgery at Sainte-Anne Hospital, Paris, France, through translational interactions between psychiatrists and neurosurgeons.

PubMed

Zanello, Marc; Pallud, Johan; Baup, Nicolas; Peeters, Sophie; Turak, Baris; Krebs, Marie Odile; Oppenheim, Catherine; Gaillard, Raphael; Devaux, Bertrand

2017-09-01

Sainte-Anne Hospital is the largest psychiatric hospital in Paris. Its long and fascinating history began in the 18th century. In 1952, it was at Sainte-Anne Hospital that Jean Delay and Pierre Deniker used the first neuroleptic, chlorpromazine, to cure psychiatric patients, putting an end to the expansion of psychosurgery. The Department of Neuro-psychosurgery was created in 1941. The works of successive heads of the Neurosurgery Department at Sainte-Anne Hospital summarized the history of psychosurgery in France. Pierre Puech defined psychosurgery as the necessary cooperation between neurosurgeons and psychiatrists to treat the conditions causing psychiatric symptoms, from brain tumors to mental health disorders. He reported the results of his series of 369 cases and underlined the necessity for proper follow-up and postoperative re-education, illustrating the relative caution of French neurosurgeons concerning psychosurgery. Marcel David and his assistants tried to follow their patients closely postoperatively; this resulted in numerous publications with significant follow-up and conclusions. As early as 1955, David reported intellectual degradation 2 years after prefrontal leucotomies. Jean Talairach, a psychiatrist who eventually trained as a neurosurgeon, was the first to describe anterior capsulotomy in 1949. He operated in several hospitals outside of Paris, including the Sarthe Psychiatric Hospital and the Public Institution of Mental Health in the Lille region. He developed stereotactic surgery, notably stereo-electroencephalography, for epilepsy surgery but also to treat psychiatric patients using stereotactic lesioning with radiofrequency ablation or radioactive seeds of yttrium-90. The evolution of functional neurosurgery has been marked by the development of deep brain stimulation, in particular for obsessive-compulsive disorder, replacing the former lesional stereotactic procedures. The history of Sainte-Anne Hospital's Neurosurgery Department sheds

A study of using smartphone to detect and identify construction workers' near-miss falls based on ANN

NASA Astrophysics Data System (ADS)

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2018-03-01

As an effective fall accident preventive method, insight into near-miss falls provides an efficient solution to find out the causes of fall accidents, classify the type of near-miss falls and control the potential hazards. In this context, the paper proposes a method to detect and identify near-miss falls that occur when a worker walks in a workplace based on artificial neural network (ANN). The energy variation generated by workers who meet with near-miss falls is measured by sensors embedded in smart phone. Two experiments were designed to train the algorithm to identify various types of near-miss falls and test the recognition accuracy, respectively. At last, a test was conducted by workers wearing smart phones as they walked around a simulated construction workplace. The motion data was collected, processed and inputted to the trained ANN to detect and identify near-miss falls. Thresholds were obtained to measure the relationship between near-miss falls and fall accidents in a quantitate way. This approach, which integrates smart phone and ANN, will help detect near-miss fall events, identify hazardous elements and vulnerable workers, providing opportunities to eliminate dangerous conditions in a construction site or to alert possible victims that need to change their behavior before the occurrence of a fall accident.

Seafloor monitoring west of Helgoland (German Bight, North Sea) using the acoustic ground discrimination system RoxAnn

NASA Astrophysics Data System (ADS)

Hass, H. Christian; Mielck, Finn; Fiorentino, Dario; Papenmeier, Svenja; Holler, Peter; Bartholomä, Alexander

2017-04-01

Marine habitats of shelf seas are in constant dynamic change and therefore need regular assessment particularly in areas of special interest. In this study, the single-beam acoustic ground discrimination system RoxAnn served to assess seafloor hardness and roughness, and combine these parameters into one variable expressed as RGB (red green blue) color code followed by k-means fuzzy cluster analysis (FCA). The data were collected at a monitoring site west of the island of Helgoland (German Bight, SE North Sea) in the course of four surveys between September 2011 and November 2014. The study area has complex characteristics varying from outcropping bedrock to sandy and muddy sectors with mostly gradual transitions. RoxAnn data enabled to discriminate all seafloor types that were suggested by ground-truth information (seafloor samples, video). The area appears to be quite stable overall; sediment import (including fluid mud) was detected only from the NW. Although hard substrates (boulders, bedrock) are clearly identified, the signal can be modified by inclination and biocover. Manually, six RoxAnn zones were identified; for the FCA, only three classes are suggested. The latter classification based on `hard' boundaries would suffice for stakeholder issues, but the former classification based on `soft' boundaries is preferred to meet state-of-the-art scientific objectives.

Analysis of the effects of geological and geomorphological factors on earthquake triggered landslides using artificial neural networks (ANN)

NASA Astrophysics Data System (ADS)

Kawabata, D.; Bandibas, J.

2007-12-01

The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic and geologic features, rock types and vegetative cover are important base factors of landslide occurrence. However, determining the relationship between these factors and landslide occurrence is very difficult using conventional mathematical analysis. The use of an advanced computing technique for this kind of analysis is very important. Artificial neural network (ANN) has recently been included in the list of analytical tools for a wide range of applications in the natural sciences research fields. One of the advantages of using ANN for pattern recognition is that it can handle data at any measurement scale ranging from nominal, ordinal to linear and ratio, and any form of data distribution (Wang et al., 1995). In addition, it can easily handle qualitative variables making it widely used in integrated analysis of spatial data from multiple sources for predicting and classification. This study focuses on the definition of the relationship between geological factors and landslide occurrence using artificial neural networks. The study also focuses on the effect of the DTMs (e.g. ASTER DTM, ALSM, digitized from paper map and digital photogrammetric measurement data). The main aim of the study is to generate landslide susceptibility index map using the defined relationship using ANN. Landslide data in the Chuetsu region were used in this research. The 2004 earthquake triggered many landslides in the region. The initial results of the study showed that ANN is more accurate in defining the relationship between geological and geomorphological factors and landslide occurrence. It also determined the best combination of geological and geomorphological factors that is directly related to landslide occurrence.

Estimation of Release History of Pollutant Source and Dispersion Coefficient of Aquifer Using Trained ANN Model

NASA Astrophysics Data System (ADS)

Srivastava, R.; Ayaz, M.; Jain, A.

2013-12-01

Knowledge of the release history of a groundwater pollutant source is critical in the prediction of the future trend of the pollutant movement and in choosing an effective remediation strategy. Moreover, for source sites which have undergone an ownership change, the estimated release history can be utilized for appropriate allocation of the costs of remediation among different parties who may be responsible for the contamination. Estimation of the release history with the help of concentration data is an inverse problem that becomes ill-posed because of the irreversible nature of the dispersion process. Breakthrough curves represent the temporal variation of pollutant concentration at a particular location, and contain significant information about the source and the release history. Several methodologies have been developed to solve the inverse problem of estimating the source and/or porous medium properties using the breakthrough curves as a known input. A common problem in the use of the breakthrough curves for this purpose is that, in most field situations, we have little or no information about the time of measurement of the breakthrough curve with respect to the time when the pollutant source becomes active. We develop an Artificial Neural Network (ANN) model to estimate the release history of a groundwater pollutant source through the use of breakthrough curves. It is assumed that the source location is known but the time dependent contaminant source strength is unknown. This temporal variation of the strength of the pollutant source is the output of the ANN model that is trained using the Levenberg-Marquardt algorithm utilizing synthetically generated breakthrough curves as inputs. A single hidden layer was used in the neural network and, to utilize just sufficient information and reduce the required sampling duration, only the upper half of the curve is used as the input pattern. The second objective of this work was to identify the aquifer parameters. An

The Nation behind the Diary: Anne Frank and the Holocaust of the Dutch Jews

ERIC Educational Resources Information Center

Foray, Jennifer L.

2011-01-01

Since its first appearance in 1947, "The Diary of Anne Frank" has been translated into sixty-five different languages, including Welsh, Esperanto, and Faroese. Millions and perhaps even billions of readers, scattered throughout the globe and now spanning multiple generations, are familiar with the life and work of this young Jewish…

Quantification of phenylpropanoids in commercial Echinacea products using TLC with video densitometry as detection technique and ANN for data modelling.

PubMed

Agatonovic-Kustrin, S; Loescher, Christine M; Singh, Ragini

2013-01-01

Echinacea preparations are among the most popular herbal remedies worldwide. Although it is generally assigned immune enhancement activities, the effectiveness of Echinacea is highly dependent on the Echinacea species, part of the plant used, the age of the plant, its location and the method of extraction. The aim of this study was to investigate the capacity of an artificial neural network (ANN) to analyse thin-layer chromatography (TLC) chromatograms as fingerprint patterns for quantitative estimation of three phenylpropanoid markers (chicoric acid, chlorogenic acid and echinacoside) in commercial Echinacea products. By applying samples with different weight ratios of marker compounds to the system, a database of chromatograms was constructed. One hundred and one signal intensities in each of the TLC chromatograms were correlated to the amounts of applied echinacoside, chlorogenic acid and chicoric acid using an ANN. The developed ANN correlation was used to quantify the amounts of three marker compounds in Echinacea commercial formulations. The minimum quantifiable level of 63, 154 and 98 ng and the limit of detection of 19, 46 and 29 ng were established for echinacoside, chlorogenic acid and chicoric acid respectively. A novel method for quality control of herbal products, based on TLC separation, high-resolution digital plate imaging and ANN data analysis has been developed. The method proposed can be adopted for routine evaluation of the phytochemical variability in Echinacea formulations available in the market. Copyright © 2012 John Wiley & Sons, Ltd.

Effects of rainfall partitioning in the seasonal and spatial variability of soil water content in a Mediterranean downy oak forest

NASA Astrophysics Data System (ADS)

Garcia-Estringana, P.; Latron, J.; Molina, A. J.; Llorens, P.

2012-04-01

Rainfall partitioning fluxes (throughfall and stemflow) have a large degree of temporal and spatial variability and may consequently lead to significant changes in the volume and composition of water that reach the understory and the soil. The objective of this work is to study the effect of rainfall partitioning on the seasonal and spatial variability of the soil water content in a Mediterranean downy oak forest (Quercus pubescens), located in the Vallcebre research catchments (42° 12'N, 1° 49'E). The monitoring design, started on July 2011, consists of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. One hundred hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover are also automatically recorded. Canopy cover, in leaf and leafless periods, as well as biometric characteristics of the plot, are also regularly measured. This work presents the first results describing throughfall and soil moisture spatial variability during both the leaf and leafless periods. The main drivers of throughfall variability, as canopy structure and meteorological conditions are also analysed.

Fine-Grained Rims in the Allan Hills 81002 and Lewis Cliff 90500 CM2 Meteorites: Their Origin and Modification

NASA Technical Reports Server (NTRS)

Hua, X.; Wang, J.; Buseck, P. R.

2002-01-01

Antarctic CM meteorites Allan Hills (ALH) 8 1002 and Lewis Cliff (LEW) 90500 contain abundant fine-grained rims (FGRs) that surround a variety of coarse-grained objects. FGRs from both meteorites have similar compositions and petrographic features, independent of their enclosed objects. The FGRs are chemically homogeneous at the 10 m scale for major and minor elements and at the 25 m scale for trace elements. They display accretionary features and contain large amounts of volatiles, presumably water. They are depleted in Ca, Mn, and S but enriched in P. All FGRs show a slightly fractionated rare earth element (REE) pattern, with enrichments of Gd and Yb and depletion of Er. Gd is twice as abundant as Er. Our results indicate that those FGRs are not genetically related to their enclosed cores. They were sampled from a reservoir of homogeneously mixed dust, prior to accretion to their parent body. The rim materials subsequently experienced aqueous alteration under identical conditions. Based on their mineral, textural, and especially chemical similarities, we conclude that ALH 8 1002 and LEW 90500 likely have a similar or identical source.

Forecasting currency circulation data of Bank Indonesia by using hybrid ARIMAX-ANN model

NASA Astrophysics Data System (ADS)

Prayoga, I. Gede Surya Adi; Suhartono, Rahayu, Santi Puteri

2017-05-01

The purpose of this study is to forecast currency inflow and outflow data of Bank Indonesia. Currency circulation in Indonesia is highly influenced by the presence of Eid al-Fitr. One way to forecast the data with Eid al-Fitr effect is using autoregressive integrated moving average with exogenous input (ARIMAX) model. However, ARIMAX is a linear model, which cannot handle nonlinear correlation structures of the data. In the field of forecasting, inaccurate predictions can be considered caused by the existence of nonlinear components that are uncaptured by the model. In this paper, we propose a hybrid model of ARIMAX and artificial neural networks (ANN) that can handle both linear and nonlinear correlation. This method was applied for 46 series of currency inflow and 46 series of currency outflow. The results showed that based on out-of-sample root mean squared error (RMSE), the hybrid models are up to10.26 and 10.65 percent better than ARIMAX for inflow and outflow series, respectively. It means that ANN performs well in modeling nonlinear correlation of the data and can increase the accuracy of linear model.

Design of a MATLAB(registered trademark) Image Comparison and Analysis Tool for Augmentation of the Results of the Ann Arbor Distortion Test

DTIC Science & Technology

2016-06-25

The equipment used in this procedure includes: Ann Arbor distortion tester with 50-line grating reticule, IQeye 720 digital video camera with 12...and import them into MATLAB. In order to digitally capture images of the distortion in an optical sample, an IQeye 720 video camera with a 12... video camera and Ann Arbor distortion tester. Figure 8. Computer interface for capturing images seen by IQeye 720 camera. Once an image was

77 FR 66547 - Approval and Promulgation of Implementation Plans; Michigan; Detroit-Ann Arbor Nonattainment Area...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-06

... 2005 Base Year Emissions Inventory AGENCY: Environmental Protection Agency (EPA). ACTION: Final rule. SUMMARY: EPA is approving the fine particulate matter (PM 2.5 ) 2005 base year emissions inventory, a... 2005 base year emissions inventory for the Detroit-Ann Arbor area. EPA did not receive any comments...

The Sally-Anne test: an interactional analysis of a dyadic assessment.

PubMed

Korkiakangas, Terhi; Dindar, Katja; Laitila, Aarno; Kärnä, Eija

2016-11-01

The Sally-Anne test has been extensively used to examine children's theory of mind understanding. Many task-related factors have been suggested to impact children's performance on this test. Yet little is known about the interactional aspects of such dyadic assessment situations that might contribute to the ways in which children respond to the test questions. To examine the interactional factors contributing to the performance of two children in the Sally-Anne test. To identify the interactional practices used by the tester administering the task and to describe how interactional features can pose challenges in the critical belief and reality questions for both the tester and the testee. The Sally-Anne test was carried out as part of a project examining children's interactions in a technology-enhanced environment. The present study uses video recordings of two children with communication disorders (one with a current diagnosis of autism spectrum disorder [ASD]) and an adult tester. We draw on a multimodal approach to conversation analysis (CA) to examine the sequential organization of the test questions and answers. The children drew on diverse resources when producing responses to the test questions: responding verbally, pointing or manually handling objects. The tester treated these responses differently depending on how they were produced. When the child pointed at an object and verbally indicated their response, the tester moved on to the next question apparently accepting the child's answer. When the child manually handled an object or produced a quiet verbal response, the tester repeated the question indicating that the child's actions did not constitute an adequate response to a test question. In response to this, both children modified or changed their previous responses. Through monitoring each other, the tester and the child produced actions highly responsive to the features of each other's conduct, which underpinned the conduct of the test itself

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

PubMed

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

Geology-based method of assessing sensitivity of streams to acidic deposition in Charles and Anne Arundel Counties, Maryland

USGS Publications Warehouse

Rice, Karen C.; Bricker, Owen P.

1991-01-01

The report describes the results of a study to assess the sensitivity of streams to acidic deposition in Charles and Anne Arundel Counties, Maryland using a geology-based method. Water samples were collected from streams in July and August 1988 when streams were at base-flow conditions. Eighteen water samples collected from streams in Charles County, and 17 water samples from streams in Anne Arundel County were analyzed in the field for pH, specific conductance, and acid-neutralizing capacity (ANC); 8 water samples from streams in Charles County were analyzed in the laboratory for chloride and sulfate concentrations. The assessment revealed that streams in these counties are sensitive to acidification by acidic deposition.

Dynamically stable associative learning: a neurobiologically based ANN and its applications

NASA Astrophysics Data System (ADS)

Vogl, Thomas P.; Blackwell, Kim L.; Barbour, Garth; Alkon, Daniel L.

1992-07-01

Most currently popular artificial neural networks (ANN) are based on conceptions of neuronal properties that date back to the 1940s and 50s, i.e., to the ideas of McCullough, Pitts, and Hebb. Dystal is an ANN based on current knowledge of neurobiology at the cellular and subcellular level. Networks based on these neurobiological insights exhibit the following advantageous properties: (1) A theoretical storage capacity of bN non-orthogonal memories, where N is the number of output neurons sharing common inputs and b is the number of distinguishable (gray shade) levels. (2) The ability to learn, store, and recall associations among noisy, arbitrary patterns. (3) A local synaptic learning rule (learning depends neither on the output of the post-synaptic neuron nor on a global error term), some of whose consequences are: (4) Feed-forward, lateral, and feed-back connections (as well as time-sensitive connections) are possible without alteration of the learning algorithm; (5) Storage allocation (patch creation) proceeds dynamically as associations are learned (self- organizing); (6) The number of training set presentations required for learning is small (< 10) and does not change with pattern size or content; and (7) The network exhibits monotonic convergence, reaching equilibrium (fully trained) values without oscillating. The performance of Dystal on pattern completion tasks such as faces with different expressions and/or corrupted by noise, and on reading hand-written digits (98% accuracy) and hand-printed Japanese Kanji (90% accuracy) is demonstrated.

Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study

PubMed Central

Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

2007-01-01

Background Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis Methods The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. Results By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus

Transfer of Downy Mildew Resistance from Wild Basil (Ocimum americanum) to Sweet Basil (O. basilicum).

PubMed

Ben-Naim, Yariv; Falach, Lidan; Cohen, Yigal

2018-01-01

Sweet basil (Ocimum basilicum) is susceptible to downy mildew caused by the oomycete foliar pathogen Peronospora belbahrii. No resistant varieties of sweet basil are commercially available. Here, we report on the transfer of resistance gene Pb1 from the highly resistant tetraploid wild basil O. americanum var. americanum (PI 500945, 2n = 4x = 48) to the tetraploid susceptible O. basilicum 'Sweet basil' (2n = 4x = 48). F1 progeny plants derived from the interspecific hybridization PI 500945 × Sweet basil were resistant, indicating that the gene controlling resistance (Pb1) is dominant, but sterile due to the genetic distance between the parents. Despite their sterility, F1 plants were pollinated with the susceptible parent and 115 first backcross generation to the susceptible parent (BCs1) embryos were rescued in vitro. The emerging BCs1 plants segregated, upon inoculation, 5:1 resistant/susceptible, suggesting that resistance in F1 was controlled by a pair of dominant genes (Pb1A and Pb1A'). Thirty-one partially fertile BCs1 plants were self-pollinated to obtain BCs1-F2 or were backcrossed to Sweet basil to obtain the second backcross generation to the susceptible parent (BCs2). In total, 1 BCs1-F2 and 22 BCs2 progenies were obtained. The BCs1-F2 progeny segregated 35:1 resistant/susceptible, as expected from a tetraploid parent with two dominant resistant genes. The 22 BCs2 progenies segregated 1:1 resistant/susceptible (for a BCs1 parent that carried one dominant gene for resistance) or 5:1 (for a BCs1 parent that carried two dominant genes for resistance) at a ratio of 4:1. The data suggest that a pair of dominant genes (Pb1A and Pb1A') residing on a two homeologous chromosomes is responsible for resistance of PI 500945 against P. belbahrii.

76 FR 36151 - Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-21

... of Anthropology, University of Michigan, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The Museum of Anthropology, University of Michigan, has completed an inventory... the Museum of Anthropology, University of Michigan. Repatriation of the human remains to the tribe...

Research on Mechanical Fault Prediction Algorithm for Circuit Breaker Based on Sliding Time Window and ANN

NASA Astrophysics Data System (ADS)

Wang, Xiaohua; Rong, Mingzhe; Qiu, Juan; Liu, Dingxin; Su, Biao; Wu, Yi

A new type of algorithm for predicting the mechanical faults of a vacuum circuit breaker (VCB) based on an artificial neural network (ANN) is proposed in this paper. There are two types of mechanical faults in a VCB: operation mechanism faults and tripping circuit faults. An angle displacement sensor is used to measure the main axle angle displacement which reflects the displacement of the moving contact, to obtain the state of the operation mechanism in the VCB, while a Hall current sensor is used to measure the trip coil current, which reflects the operation state of the tripping circuit. Then an ANN prediction algorithm based on a sliding time window is proposed in this paper and successfully used to predict mechanical faults in a VCB. The research results in this paper provide a theoretical basis for the realization of online monitoring and fault diagnosis of a VCB.

Bodies in Space/Bodies in Motion/Bodies in Character: Adolescents Bear Witness to Anne Frank

ERIC Educational Resources Information Center

Chisholm, James S.; Whitmore, Kathryn F.

2016-01-01

Situated at the intersection of research on Holocaust education and embodied literacies this study examines how an arts-based instructional approach engaged middle school learners in developing empathetic perspectives on the Anne Frank narrative. We addressed the research question: What can adolescents who are using their bodies to gain empathy…

76 FR 80392 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-23

...: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION... Michigan officials and its Museum of Anthropology professional staff in consultation with representatives... accessioned into the Museum of Anthropology. Between 2007 and 2009 the remains were inventoried at the...

77 FR 34991 - Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-12

... DEPARTMENT OF THE INTERIOR National Park Service [NPS-WASO-NAGPRA-10375; 2200-1100-665] Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI; Correction AGENCY: National Park Service, Interior. ACTION: Notice; correction. Notice is here given in accordance with the...

Modeling of biosorption of Cu(II) by alkali-modified spent tea leaves using response surface methodology (RSM) and artificial neural network (ANN)

NASA Astrophysics Data System (ADS)

Ghosh, Arpita; Das, Papita; Sinha, Keka

2015-06-01

In the present work, spent tea leaves were modified with Ca(OH)2 and used as a new, non-conventional and low-cost biosorbent for the removal of Cu(II) from aqueous solution. Response surface methodology (RSM) and artificial neural network (ANN) were used to develop predictive models for simulation and optimization of the biosorption process. The influence of process parameters (pH, biosorbent dose and reaction time) on the biosorption efficiency was investigated through a two-level three-factor (23) full factorial central composite design with the help of Design Expert. The same design was also used to obtain a training set for ANN. Finally, both modeling methodologies were statistically compared by the root mean square error and absolute average deviation based on the validation data set. Results suggest that RSM has better prediction performance as compared to ANN. The biosorption followed Langmuir adsorption isotherm and it followed pseudo-second-order kinetic. The optimum removal efficiency of the adsorbent was found as 96.12 %.

Mineral resource potential map of the Dolly Ann Roadless Area, Alleghany County, Virginia

USGS Publications Warehouse

Lesure, Frank G.; Jones, Jay G.

1983-01-01

The Dolly Ann Roadless Area comprises 7,900 acres (3,200 ha) in the George Washington National Forest in the Valley and Ridge physiographic province of west-central Virginia. The area is at the southern ·end of Warm Springs Mountain in Alleghany County just northeast of Covington, the county seat (index map). U.S. Highway 220 forms part of the western boundary, and U.S. Forest Service Road 125, which parallels Pounding Mill Creek, forms the eastern boundary. The principal streams draining the area are Pounding Mill Creek, Dry Run, and Roaring Run, all tributaries of the Jackson River. The highest point in the area is Big Knob at the north end, 4,072 ft (1241 m) above sea level; the lowest points, about 1,400 ft (427 m) above sea level, are at the south side, along Dry Run and Pounding Mill Creek. In general, the hill slopes are steep and heavily wooded with second- or third-growth hardwoods and scattered pine and hemlock. Dolly Ann Hollow near the east end of the area is a steep, boulder-strewn gorge, quite picturesque, but containing no good trails. A good trail up Dry Run connects a trail crossing the ridge between Bald Knob and Big Knob. No other trails cross the area.

ANN based Real-Time Estimation of Power Generation of Different PV Module Types

NASA Astrophysics Data System (ADS)

Syafaruddin; Karatepe, Engin; Hiyama, Takashi

Distributed generation is expected to become more important in the future generation system. Utilities need to find solutions that help manage resources more efficiently. Effective smart grid solutions have been experienced by using real-time data to help refine and pinpoint inefficiencies for maintaining secure and reliable operating conditions. This paper proposes the application of Artificial Neural Network (ANN) for the real-time estimation of the maximum power generation of PV modules of different technologies. An intelligent technique is necessary required in this case due to the relationship between the maximum power of PV modules and the open circuit voltage and temperature is nonlinear and can't be easily expressed by an analytical expression for each technology. The proposed ANN method is using input signals of open circuit voltage and cell temperature instead of irradiance and ambient temperature to determine the estimated maximum power generation of PV modules. It is important for the utility to have the capability to perform this estimation for optimal operating points and diagnostic purposes that may be an early indicator of a need for maintenance and optimal energy management. The proposed method is accurately verified through a developed real-time simulator on the daily basis of irradiance and cell temperature changes.

The first description of the complete natural history of uveal melanoma by two Scottish surgeons, Allan Burns and James Wardrop.

PubMed

Kivelä, Tero T

2018-03-01

James Wardrop (1782-1869), a young Scottish surgeon and an early ophthalmologist in Edinburgh, is credited for describing in 1809 retinoblastoma as an entity in his treatise 'Observations on Fungus Haematodes or Soft Cancer'. His treatise also reveals that Allan Burns (1781-1813), another young Scottish surgeon and anatomist, had invited Wardrop to assist in enucleating an eye from a 41-year-old Glasgow woman who, in retrospect, had a uveal melanoma. Her eye had become blind 4 months after symptoms of exudative retinal detachment had appeared, and it had become painful after a further 2-4 months. The tumour eventually perforated the sclera, and she died within a year thereafter of hepatic metastases. Burns and Wardrop went on to publish detailed parallel accounts of the symptoms, signs, ophthalmic pathology and post-mortem findings regarding the primary, recurrent and metastatic tumour. Burns may have performed the post-mortem after exhuming the body, a common occurrence in early 19th Century Scotland, a thriving hub for teaching morbid anatomy to young surgeons at the time. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

78 FR 67086 - Safety Zone, Submarine Cable Replacement Operations, Kent Island Narrows; Queen Anne's County, MD

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-08

... 1625-AA00 Safety Zone, Submarine Cable Replacement Operations, Kent Island Narrows; Queen Anne's County... Guard proposes to establish a temporary safety zone encompassing certain waters of Kent Island Narrows... potential safety hazards associated with the bridge project. Entry into this zone would be prohibited unless...

Tribological behaviour predictions of r-GO reinforced Mg composite using ANN coupled Taguchi approach

NASA Astrophysics Data System (ADS)

Kavimani, V.; Prakash, K. Soorya

2017-11-01

This paper deals with the fabrication of reduced graphene oxide (r-GO) reinforced Magnesium Metal Matrix Composite (MMC) through a novel solvent based powder metallurgy route. Investigations over basic and functional properties of developed MMC reveals that addition of r-GO improvises the microhardness upto 64 HV but however decrement in specific wear rate is also notified. Visualization of worn out surfaces through SEM images clearly explains for the occurrence of plastic deformation and the presence of wear debris because of ploughing out action. Taguchi coupled Artificial Neural Network (ANN) technique is adopted to arrive at optimal values of the input parameters such as load, reinforcement weight percentage, sliding distance and sliding velocity and thereby achieve minimal target output value viz. specific wear rate. Influence of any of the input parameter over specific wear rate studied through ANOVA reveals that load acting on pin has a major influence with 38.85% followed by r-GO wt. % of 25.82%. ANN model developed to predict specific wear rate value based on the variation of input parameter facilitates better predictability with R-value of 98.4% when compared with the outcomes of regression model.

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

NASA Astrophysics Data System (ADS)

Aytaç Korkmaz, Sevcan; Binol, Hamidullah

2018-03-01

Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

Joseph Campbell, Jung, Anne Tyler, and "The Cards": The Spiritual Journey in "Searching for Caleb."

ERIC Educational Resources Information Center

Thomson, Karen M.

Joseph Campbell, Carl Jung, and Anne Tyler have all dealt with spiritual journeys and card reading in their writings. In his book "Tarot Revelations," Joseph Campbell discusses his first association with tarot cards, dating from 1943, when he was introduced to the symoblism of playing cards by his friend and mentor, Heinrich Zimmer. Carl…

76 FR 73670 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-29

...: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION... Museum of Anthropology NAGPRA collections staff in consultation with representatives of the Bay Mills... Anthropology purchased the human remains from Reverend L. P. Rowland in November of 1924 as part of a larger...

78 FR 76169 - Patuxent Research Refuge, Prince George's and Anne Arundel Counties, MD; Final Comprehensive...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-16

...We, the U.S. Fish and Wildlife Service (Service), announce the availability of the final comprehensive conservation plan (CCP) and finding of no significant impact (FONSI) for Patuxent Research Refuge (Patuxent RR, refuge), located in Prince George's and Anne Arundel Counties, Maryland. In this final CCP, we describe how we will manage the refuge for the next 15 years.

Mathematical Modeling and Optimizing of in Vitro Hormonal Combination for G × N15 Vegetative Rootstock Proliferation Using Artificial Neural Network-Genetic Algorithm (ANN-GA)

PubMed Central

Arab, Mohammad M.; Yadollahi, Abbas; Ahmadi, Hamed; Eftekhari, Maliheh; Maleki, Masoud

2017-01-01

The efficiency of a hybrid systems method which combined artificial neural networks (ANNs) as a modeling tool and genetic algorithms (GAs) as an optimizing method for input variables used in ANN modeling was assessed. Hence, as a new technique, it was applied for the prediction and optimization of the plant hormones concentrations and combinations for in vitro proliferation of Garnem (G × N15) rootstock as a case study. Optimizing hormones combination was surveyed by modeling the effects of various concentrations of cytokinin–auxin, i.e., BAP, KIN, TDZ, IBA, and NAA combinations (inputs) on four growth parameters (outputs), i.e., micro-shoots number per explant, length of micro-shoots, developed callus weight (CW) and the quality index (QI) of plantlets. Calculation of statistical values such as R2 (coefficient of determination) related to the accuracy of ANN-GA models showed a considerably higher prediction accuracy for ANN models, i.e., micro-shoots number: R2 = 0.81, length of micro-shoots: R2 = 0.87, CW: R2 = 0.88, QI: R2 = 0.87. According to the results, among the input variables, BAP (19.3), KIN (9.64), and IBA (2.63) showed the highest values of variable sensitivity ratio for proliferation rate. The GA showed that media containing 1.02 mg/l BAP in combination with 0.098 mg/l IBA could lead to the optimal proliferation rate (10.53) for G × N15 rootstock. Another objective of the present study was to compare the performance of predicted and optimized cytokinin–auxin combination with the best optimized obtained concentrations of our other experiments. Considering three growth parameters (length of micro-shoots, micro-shoots number, and proliferation rate), the last treatment was found to be superior to the rest of treatments for G × N15 rootstock in vitro multiplication. Very little difference between the ANN predicted and experimental data confirmed high capability of ANN-GA method in predicting new optimized protocols for plant in vitro propagation

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Evaluation Of Automatic Vehicle Location Accuracy

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

Expression profiling during arabidopsis/downy mildew interaction reveals a highly-expressed effector that attenuates responses to salicylic acid.

PubMed

Asai, Shuta; Rallapalli, Ghanasyam; Piquerez, Sophie J M; Caillaud, Marie-Cécile; Furzer, Oliver J; Ishaque, Naveed; Wirthmueller, Lennart; Fabro, Georgina; Shirasu, Ken; Jones, Jonathan D G

2014-10-01

Plants have evolved strong innate immunity mechanisms, but successful pathogens evade or suppress plant immunity via effectors delivered into the plant cell. Hyaloperonospora arabidopsidis (Hpa) causes downy mildew on Arabidopsis thaliana, and a genome sequence is available for isolate Emoy2. Here, we exploit the availability of genome sequences for Hpa and Arabidopsis to measure gene-expression changes in both Hpa and Arabidopsis simultaneously during infection. Using a high-throughput cDNA tag sequencing method, we reveal expression patterns of Hpa predicted effectors and Arabidopsis genes in compatible and incompatible interactions, and promoter elements associated with Hpa genes expressed during infection. By resequencing Hpa isolate Waco9, we found it evades Arabidopsis resistance gene RPP1 through deletion of the cognate recognized effector ATR1. Arabidopsis salicylic acid (SA)-responsive genes including PR1 were activated not only at early time points in the incompatible interaction but also at late time points in the compatible interaction. By histochemical analysis, we found that Hpa suppresses SA-inducible PR1 expression, specifically in the haustoriated cells into which host-translocated effectors are delivered, but not in non-haustoriated adjacent cells. Finally, we found a highly-expressed Hpa effector candidate that suppresses responsiveness to SA. As this approach can be easily applied to host-pathogen interactions for which both host and pathogen genome sequences are available, this work opens the door towards transcriptome studies in infection biology that should help unravel pathogen infection strategies and the mechanisms by which host defense responses are overcome.

Clearance Rate and BP-ANN Model in Paraquat Poisoned Patients Treated with Hemoperfusion

PubMed Central

Hu, Lufeng; Hong, Guangliang; Ma, Jianshe; Wang, Xianqin; Lin, Guanyang; Zhang, Xiuhua; Lu, Zhongqiu

2015-01-01

In order to investigate the effect of hemoperfusion (HP) on the clearance rate of paraquat (PQ) and develop a clearance model, 41 PQ-poisoned patients who acquired acute PQ intoxication received HP treatment. PQ concentrations were determined by high performance liquid chromatography (HPLC). According to initial PQ concentration, study subjects were divided into two groups: Low-PQ group (0.05–1.0 μg/mL) and High-PQ group (1.0–10 μg/mL). After initial HP treatment, PQ concentrations decreased in both groups. However, in the High-PQ group, PQ levels remained in excess of 0.05 μg/mL and increased when the second HP treatment was initiated. Based on the PQ concentrations before and after HP treatment, the mean clearance rate of PQ calculated was 73 ± 15%. We also established a backpropagation artificial neural network (BP-ANN) model, which set PQ concentrations before HP treatment as input data and after HP treatment as output data. When it is used to predict PQ concentration after HP treatment, high prediction accuracy (R = 0.9977) can be obtained in this model. In conclusion, HP is an effective way to clear PQ from the blood, and the PQ concentration after HP treatment can be predicted by BP-ANN model. PMID:25695058

The modelling of lead removal from water by deep eutectic solvents functionalized CNTs: artificial neural network (ANN) approach.

PubMed

Fiyadh, Seef Saadi; AlSaadi, Mohammed Abdulhakim; AlOmar, Mohamed Khalid; Fayaed, Sabah Saadi; Hama, Ako R; Bee, Sharifah; El-Shafie, Ahmed

2017-11-01

The main challenge in the lead removal simulation is the behaviour of non-linearity relationships between the process parameters. The conventional modelling technique usually deals with this problem by a linear method. The substitute modelling technique is an artificial neural network (ANN) system, and it is selected to reflect the non-linearity in the interaction among the variables in the function. Herein, synthesized deep eutectic solvents were used as a functionalized agent with carbon nanotubes as adsorbents of Pb 2+ . Different parameters were used in the adsorption study including pH (2.7 to 7), adsorbent dosage (5 to 20 mg), contact time (3 to 900 min) and Pb 2+ initial concentration (3 to 60 mg/l). The number of experimental trials to feed and train the system was 158 runs conveyed in laboratory scale. Two ANN types were designed in this work, the feed-forward back-propagation and layer recurrent; both methods are compared based on their predictive proficiency in terms of the mean square error (MSE), root mean square error, relative root mean square error, mean absolute percentage error and determination coefficient (R 2 ) based on the testing dataset. The ANN model of lead removal was subjected to accuracy determination and the results showed R 2 of 0.9956 with MSE of 1.66 × 10 -4 . The maximum relative error is 14.93% for the feed-forward back-propagation neural network model.

Noble gas isotopic composition, cosmic ray exposure history, and terrestrial age of the meteorite Allan Hills A81005 from the moon

NASA Astrophysics Data System (ADS)

Eugster, O.; Geiss, J.; Kraehenbuehl, U.; Niedermann, S.

1986-06-01

A comprehensive study of the elemental and isotopic abundances of the noble gases He, Ne, Ar, Kr, and Xe in the meteorite Allan Hills A81005 from the moon is presented. In addition to a bulk sample, five grain-size fractions were analyzed. Chemical abundances relevant to the interpretation of the cosmic-ray-produced noble gases were determined and indicate that the grain size fractions are chemically uniform. Except for the fact that the trapped noble gas concentrations appear to be grain size correlated, the isotopic and elemental pattern of the trapped solar wind noble gases in A81005 are very similar to those observed in lunar soils and breccias. The A81005 material resided during (580 + or - 180) Myr in the nuclear active zone of the lunar regolith at an average shielding depth of about 40 g/sq cm. From literature data, it is concluded that the moon-earth transit time lasted less than a few million years. Finally, A81005 was captured by the earth more than 140,000 years ago, as indicated by the abundance of cosmic-ray-produced Kr-81.

A comparison of two adaptive multivariate analysis methods (PLSR and ANN) for winter wheat yield forecasting using Landsat-8 OLI images

NASA Astrophysics Data System (ADS)

Chen, Pengfei; Jing, Qi

2017-02-01

An assumption that the non-linear method is more reasonable than the linear method when canopy reflectance is used to establish the yield prediction model was proposed and tested in this study. For this purpose, partial least squares regression (PLSR) and artificial neural networks (ANN), represented linear and non-linear analysis method, were applied and compared for wheat yield prediction. Multi-period Landsat-8 OLI images were collected at two different wheat growth stages, and a field campaign was conducted to obtain grain yields at selected sampling sites in 2014. The field data were divided into a calibration database and a testing database. Using calibration data, a cross-validation concept was introduced for the PLSR and ANN model construction to prevent over-fitting. All models were tested using the test data. The ANN yield-prediction model produced R2, RMSE and RMSE% values of 0.61, 979 kg ha-1, and 10.38%, respectively, in the testing phase, performing better than the PLSR yield-prediction model, which produced R2, RMSE, and RMSE% values of 0.39, 1211 kg ha-1, and 12.84%, respectively. Non-linear method was suggested as a better method for yield prediction.

Facteurs prédictifs de succès des étudiants en première année de médecine à l'université de Parakou

PubMed Central

Adoukonou, Thierry; Tognon-Tchegnonsi, Francis; Mensah, Emile; Allodé, Alexandre; Adovoekpe, Jean-Marie; Gandaho, Prosper; Akpona, Simon

2016-01-01

Introduction Plusieurs facteurs dont les notes obtenues au BAC peuvent influencer les performances académiques des étudiants en première année de médecine. L'objectif de cette étude était d’évaluer la relation entre les résultats des étudiants au BAC et le succès en première année de médecine. Méthodes Nous avons réalisé une étude analytique ayant inclus l'ensemble des étudiants régulièrement inscrits en première année à la Faculté de Médecine de l'université de Parakou durant l'année académique 2010-2011. Les données concernant les notes par discipline et mention obtenue au BAC ont été collectées. Une analyse multivariée utilisant la régression logistique et la régression linéaire multiple a permis d’établir les meilleurs prédicteurs du succès et de la moyenne de l’étudiant en fin d'année. Le logiciel SPSS version 17.0 a été utilisé pour l'analyse des données et un p<0,05 a été considéré comme statistiquement significatif. Résultats Parmi les 414 étudiants régulièrement inscrits les données de 407 ont pu être exploitées. Ils étaient âgés de 15 à 31 ans; 262 (64,4%) étaient de sexe masculin. 98 étaient admis avec un taux de succès de 23,7%. Le sexe masculin, la note obtenue en mathématiques, en sciences physiques, la moyenne au BAC et la mention étaient associés au succès en fin d'année mais en analyse multivariée seule une note en sciences physiques > 15/20 était associée au succès (OR: 2,8 [1,32- 6,00]). Pour la moyenne générale obtenue en fin d'année seule une mention bien obtenue au BAC était associée (coefficient de l'erreur standard: 0,130 Bêta =0,370 et p=0,00001). Conclusion Les meilleurs prédicateurs du succès en première année étaient une bonne moyenne en sciences physiques au BAC et une mention bien. La prise en compte de ces éléments dans le recrutement des étudiants en première année pourrait améliorer les résultats académiques. PMID:27313819

English for Specific Purposes: The State of the Art (An Online Interview with Ann M. Johns)

ERIC Educational Resources Information Center

Johns, Ann M.; Salmani Nodoushan, M. A.

2015-01-01

This forum paper is based on a friendly and informative interview conducted with Professor Ann M. Johns. In providing answers to the interview questions, Professor Johns suggests that all good teaching is ESP, and also distinguishes between EOP and ESP in that the former entails much more "just in time" learning while the latter may be…

The application of ANN for zone identification in a complex reservoir

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

White, A.C.; Molnar, D.; Aminian, K.

1995-12-31

Reservoir characterization plays a critical role in appraising the economic success of reservoir management and development methods. Nearly all reservoirs show some degree of heterogeneity, which invariably impacts production. As a result, the production performance of a complex reservoir cannot be realistically predicted without accurate reservoir description. Characterization of a heterogeneous reservoir is a complex problem. The difficulty stems from the fact that sufficient data to accurately predict the distribution of the formation attributes are not usually available. Generally the geophysical logs are available from a considerable number of wells in the reservoir. Therefore, a methodology for reservoir description andmore » characterization utilizing only well logs data represents a significant technical as well as economic advantage. One of the key issues in the description and characterization of heterogeneous formations is the distribution of various zones and their properties. In this study, several artificial neural networks (ANN) were successfully designed and developed for zone identification in a heterogeneous formation from geophysical well logs. Granny Creek Field in West Virginia has been selected as the study area in this paper. This field has produced oil from Big Injun Formation since the early 1900`s. The water flooding operations were initiated in the 1970`s and are currently still in progress. Well log data on a substantial number of wells in this reservoir were available and were collected. Core analysis results were also available from a few wells. The log data from 3 wells along with the various zone definitions were utilized to train the networks for zone recognition. The data from 2 other wells with previously determined zones, based on the core and log data, were then utilized to verify the developed networks predictions. The results indicated that ANN can be a useful tool for accurately identifying the zones in complex reservoirs.« less

FE-ANN based modeling of 3D Simple Reinforced Concrete Girders for Objective Structural Health Evaluation : Tech Transfer Summary

DOT National Transportation Integrated Search

2017-06-01

The objective of this study was to develop an objective, quantitative method for evaluating damage to bridge girders by using artificial neural networks (ANNs). This evaluation method, which is a supplement to visual inspection, requires only the res...

76 FR 44947 - Notice of Intent To Repatriate Cultural Items: University of Michigan Museum of Anthropology, Ann...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-27

... the appropriate Indian tribe, has determined that the items meet the definition of sacred objects and.... Representatives of any Indian tribe that believes itself to be culturally affiliated with the sacred objects may... of Anthropology, Ann Arbor, MI, that meet the definition of sacred objects under 25 U.S.C. 3001. This...

Support vector machine regression (LS-SVM)--an alternative to artificial neural networks (ANNs) for the analysis of quantum chemistry data?

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-06-28

A multilayer feed-forward artificial neural network (MLP-ANN) with a single, hidden layer that contains a finite number of neurons can be regarded as a universal non-linear approximator. Today, the ANN method and linear regression (MLR) model are widely used for quantum chemistry (QC) data analysis (e.g., thermochemistry) to improve their accuracy (e.g., Gaussian G2-G4, B3LYP/B3-LYP, X1, or W1 theoretical methods). In this study, an alternative approach based on support vector machines (SVMs) is used, the least squares support vector machine (LS-SVM) regression. It has been applied to ab initio (first principle) and density functional theory (DFT) quantum chemistry data. So, QC + SVM methodology is an alternative to QC + ANN one. The task of the study was to estimate the Møller-Plesset (MPn) or DFT (B3LYP, BLYP, BMK) energies calculated with large basis sets (e.g., 6-311G(3df,3pd)) using smaller ones (6-311G, 6-311G*, 6-311G**) plus molecular descriptors. A molecular set (BRM-208) containing a total of 208 organic molecules was constructed and used for the LS-SVM training, cross-validation, and testing. MP2, MP3, MP4(DQ), MP4(SDQ), and MP4/MP4(SDTQ) ab initio methods were tested. Hartree-Fock (HF/SCF) results were also reported for comparison. Furthermore, constitutional (CD: total number of atoms and mole fractions of different atoms) and quantum-chemical (QD: HOMO-LUMO gap, dipole moment, average polarizability, and quadrupole moment) molecular descriptors were used for the building of the LS-SVM calibration model. Prediction accuracies (MADs) of 1.62 ± 0.51 and 0.85 ± 0.24 kcal mol(-1) (1 kcal mol(-1) = 4.184 kJ mol(-1)) were reached for SVM-based approximations of ab initio and DFT energies, respectively. The LS-SVM model was more accurate than the MLR model. A comparison with the artificial neural network approach shows that the accuracy of the LS-SVM method is similar to the accuracy of ANN. The extrapolation and interpolation results show that LS-SVM is

Prediction of moving bed biofilm reactor (MBBR) performance for the treatment of aniline using artificial neural networks (ANN).

PubMed

Delnavaz, M; Ayati, B; Ganjidoust, H

2010-07-15

In this study, the results of 1-year efficiency forecasting using artificial neural networks (ANN) models of a moving bed biofilm reactor (MBBR) for a toxic and hard biodegradable aniline removal were investigated. The reactor was operated in an aerobic batch and continuous condition with 50% by volume which was filled with light expanded clay aggregate (LECA) as carrier. Efficiency evaluation of the reactors was obtained at different retention time (RT) of 8, 24, 48 and 72 h with an influent COD from 100 to 4000 mg/L. Exploratory data analysis was used to detect relationships between the data and dependent evaluated one. The appropriate architecture of the neural network models was determined using several steps of training and testing of the models. The ANN-based models were found to provide an efficient and a robust tool in predicting MBBR performance for treating aromatic amine compounds. 2010 Elsevier B.V. All rights reserved.

Prediction of coagulation and flocculation processes using ANN models and fuzzy regression.

PubMed

Zangooei, Hossein; Delnavaz, Mohammad; Asadollahfardi, Gholamreza

2016-09-01

Coagulation and flocculation are two main processes used to integrate colloidal particles into larger particles and are two main stages of primary water treatment. Coagulation and flocculation processes are only needed when colloidal particles are a significant part of the total suspended solid fraction. Our objective was to predict turbidity of water after the coagulation and flocculation process while other parameters such as types and concentrations of coagulants, pH, and influent turbidity of raw water were known. We used a multilayer perceptron (MLP), a radial basis function (RBF) of artificial neural networks (ANNs) and various kinds of fuzzy regression analysis to predict turbidity after the coagulation and flocculation processes. The coagulant used in the pilot plant, which was located in water treatment plant, was poly aluminum chloride. We used existing data, including the type and concentrations of coagulant, pH and influent turbidity, of the raw water because these types of data were available from the pilot plant for simulation and data was collected by the Tehran water authority. The results indicated that ANNs had more ability in simulating the coagulation and flocculation process and predicting turbidity removal with different experimental data than did the fuzzy regression analysis, and may have the ability to reduce the number of jar tests, which are time-consuming and expensive. The MLP neural network proved to be the best network compared to the RBF neural network and fuzzy regression analysis in this study. The MLP neural network can predict the effluent turbidity of the coagulation and the flocculation process with a coefficient of determination (R 2 ) of 0.96 and root mean square error of 0.0106.

Biosurfactant-biopolymer driven microbial enhanced oil recovery (MEOR) and its optimization by an ANN-GA hybrid technique.

PubMed

Dhanarajan, Gunaseelan; Rangarajan, Vivek; Bandi, Chandrakanth; Dixit, Abhivyakti; Das, Susmita; Ale, Kranthikiran; Sen, Ramkrishna

2017-08-20

A lipopeptide biosurfactant produced by marine Bacillus megaterium and a biopolymer produced by thermophilic Bacillus licheniformis were tested for their application potential in the enhanced oil recovery. The crude biosurfactant obtained after acid precipitation effectively reduced the surface tension of deionized water from 70.5 to 28.25mN/m and the interfacial tension between lube oil and water from 18.6 to 1.5mN/m at a concentration of 250mgL -1 . The biosurfactant exhibited a maximum emulsification activity (E 24 ) of 81.66% against lube oil. The lipopeptide micelles were stabilized by addition of Ca 2+ ions to the biosurfactant solution. The oil recovery efficiency of Ca 2+ conditioned lipopeptide solution from a sand-packed column was optimized by using artificial neural network (ANN) modelling coupled with genetic algorithm (GA) optimization. Three important parameters namely lipopeptide concentration, Ca 2+ concentration and solution pH were considered for optimization studies. In order to further improve the recovery efficiency, a water soluble biopolymer produced by Bacillus licheniformis was used as a flooding agent after biosurfactant incubation. Upon ANN-GA optimization, 45% tertiary oil recovery was achieved, when biopolymer at a concentration of 3gL -1 was used as a flooding agent. Oil recovery was only 29% at optimal conditions predicted by ANN-GA, when only water was used as flooding solution. The important characteristics of biopolymers such as its viscosity, pore plugging capabilities and bio-cementing ability have also been tested. Thus, as a result of biosurfactant incubation and biopolymer flooding under the optimal process conditions, a maximum oil recovery of 45% was achieved. Therefore, this study is novel, timely and interesting for it showed the combined influence of biosurfactant and biopolymer on solubilisation and mobilization of oil from the soil. Copyright © 2017 Elsevier B.V. All rights reserved.

Valorization of aquaculture waste in removal of cadmium from aqueous solution: optimization by kinetics and ANN analysis

NASA Astrophysics Data System (ADS)

Aditya, Gautam; Hossain, Asif

2018-05-01

Cadmium is one of the most hazardous heavy metal concerning human health and aquatic pollution. The removal of cadmium through biosorption is a feasible option for restoration of the ecosystem health of the contaminated freshwater ecosystems. In compliance with this proposition and considering the efficiency of calcium carbonate as biosorbent, the shell dust of the economically important snail Bellamya bengalensis was tested for the removal of cadmium from aqueous medium. Following use of the flesh as a cheap source of protein, the shells of B. bengalensis made up of CaCO3 are discarded as aquaculture waste. The biosorption was assessed through batch sorption studies along with studies to characterize the morphology and surface structures of waste shell dust. The data on the biosorption were subjected to the artificial neural network (ANN) model for optimization of the process. The biosorption process changed as functions of pH of the solution, concentration of heavy metal, biomass of the adsorbent and time of exposure. The kinetic process was well represented by pseudo second order ( R 2 = 0.998), and Langmuir equilibrium ( R 2 = 0.995) had better fits in the equilibrium process with 30.33 mg g-1 of maximum sorption capacity. The regression equation ( R 2 = 0.948) in the ANN model supports predicted values of Cd removal satisfactorily. The normalized importance analysis in ANN predicts Cd2+ concentration, and pH has the most influence in removal than biomass dose and time. The SEM and EDX studies show clear peaks for Cd confirming the biosorption process while the FTIR study depicts the main functional groups (-OH, C-H, C=O, C=C) responsible for the biosorption process. The study indicated that the waste shell dust can be used as an efficient, low cost, environment friendly, sustainable adsorbent for the removal of cadmium from aqueous solution.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

Intelligent estimation of noise and blur variances using ANN for the restoration of ultrasound images.

PubMed

Uddin, Muhammad Shahin; Halder, Kalyan Kumar; Tahtali, Murat; Lambert, Andrew J; Pickering, Mark R; Marchese, Margaret; Stuart, Iain

2016-11-01

Ultrasound (US) imaging is a widely used clinical diagnostic tool in medical imaging techniques. It is a comparatively safe, economical, painless, portable, and noninvasive real-time tool compared to the other imaging modalities. However, the image quality of US imaging is severely affected by the presence of speckle noise and blur during the acquisition process. In order to ensure a high-quality clinical diagnosis, US images must be restored by reducing their speckle noise and blur. In general, speckle noise is modeled as a multiplicative noise following a Rayleigh distribution and blur as a Gaussian function. Hereto, we propose an intelligent estimator based on artificial neural networks (ANNs) to estimate the variances of noise and blur, which, in turn, are used to obtain an image without discernible distortions. A set of statistical features computed from the image and its complex wavelet sub-bands are used as input to the ANN. In the proposed method, we solve the inverse Rayleigh function numerically for speckle reduction and use the Richardson-Lucy algorithm for de-blurring. The performance of this method is compared with that of the traditional methods by applying them to a synthetic, physical phantom and clinical data, which confirms better restoration results by the proposed method.

An ANN-based HRV classifier for cardiac health prognosis.

PubMed

Sunkaria, Ramesh Kumar; Kumar, Vinod; Saxena, Suresh Chandra; Singhal, Achala M

2014-01-01

A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists. On the basis of symptoms and other investigations, the attending cardiologists advised them to be classified into four categories as per the severity of cardiac health. Out of 46, the HRV data of 28 patients were used for training and data of 18 patients were used for testing of the proposed classifier. The cardiac health classification of each tested patient with the proposed classifier matches with the medical opinion of the cardiologists.

The Picture of the Century with Floyd Thompsona and Ann Hitch Kilgore, Former Mayor of Hampton VA.

NASA Image and Video Library

1966-12-14

Langley Center Director Floyd Thompson shows Ann Kilgore the "picture of the century." This was the first picture of the earth taken from space. From Spaceflight Revolution: "On 23 August 1966 just as Lunar Orbiter I was about to pass behind the moon, mission controllers executed the necessary maneuvers to point the camera away from the lunar surface and toward the earth. The result was the world's first view of the earth from space. It was called "the picture of the century' and "the greatest shot taken since the invention of photography." Not even the color photos of the earth taken during the Apollo missions superseded the impact of this first image of our planet as a little island of life floating in the black and infinite sea of space." -- Published in James R. Hansen, Spaceflight Revolution: NASA Langley Research Center From Sputnik to Apollo, (Washington: NASA, 1995), pp. 345-346. Mayor Ann Kilgore was married to NASA researcher Edwin Carroll Kilgore. Mrs, Kilgore was Mayor from 1963-1971 and again from 1974-1978.

Modeling of policies for reduction of GHG emissions in energy sector using ANN: case study-Croatia (EU).

PubMed

Bolanča, Tomislav; Strahovnik, Tomislav; Ukić, Šime; Stankov, Mirjana Novak; Rogošić, Marko

2017-07-01

This study describes the development of tool for testing different policies for reduction of greenhouse gas (GHG) emissions in energy sector using artificial neural networks (ANNs). The case study of Croatia was elaborated. Two different energy consumption scenarios were used as a base for calculations and predictions of GHG emissions: the business as usual (BAU) scenario and sustainable scenario. Both of them are based on predicted energy consumption using different growth rates; the growth rates within the second scenario resulted from the implementation of corresponding energy efficiency measures in final energy consumption and increasing share of renewable energy sources. Both ANN architecture and training methodology were optimized to produce network that was able to successfully describe the existing data and to achieve reliable prediction of emissions in a forward time sense. The BAU scenario was found to produce continuously increasing emissions of all GHGs. The sustainable scenario was found to decrease the GHG emission levels of all gases with respect to BAU. The observed decrease was attributed to the group of measures termed the reduction of final energy consumption through energy efficiency measures.

A Report to the Board of Education of Anne Arundel County on the Status of the Schools.

ERIC Educational Resources Information Center

Anne Arundel County Board of Education, Annapolis, MD.

This annual report for the 1979-1980 school year summarizes and gives the status of the main objectives of the major programs within the public school system of Anne Arundel County. Project objectives for the 1981-82 school year as well as the one immediately following are also presented and explained. In his statement, the Superintendent of…

Disentangling Peronospora on Papaver: Phylogenetics, Taxonomy, Nomenclature and Host Range of Downy Mildew of Opium Poppy (Papaver somniferum) and Related Species

PubMed Central

Voglmayr, Hermann; Montes-Borrego, Miguel; Landa, Blanca B.

2014-01-01

Based on sequence data from ITS rDNA, cox1 and cox2, six Peronospora species are recognised as phylogenetically distinct on various Papaver species. The host ranges of the four already described species P. arborescens, P. argemones, P. cristata and P. meconopsidis are clarified. Based on sequence data and morphology, two new species, P. apula and P. somniferi, are described from Papaver apulum and P. somniferum, respectively. The second Peronospora species parasitizing Papaver somniferum, that was only recently recorded as Peronospora cristata from Tasmania, is shown to represent a distinct taxon, P. meconopsidis, originally described from Meconopsis cambrica. It is shown that P. meconopsidis on Papaver somniferum is also present and widespread in Europe and Asia, but has been overlooked due to confusion with P. somniferi and due to less prominent, localized disease symptoms. Oospores are reported for the first time for P. meconopsidis from Asian collections on Papaver somniferum. Morphological descriptions, illustrations and a key are provided for all described Peronospora species on Papaver. cox1 and cox2 sequence data are confirmed as equally good barcoding loci for reliable Peronospora species identification, whereas ITS rDNA does sometimes not resolve species boundaries. Molecular phylogenetic data reveal high host specificity of Peronospora on Papaver, which has the important phytopathological implication that wild Papaver spp. cannot play any role as primary inoculum source for downy mildew epidemics in cultivated opium poppy crops. PMID:24806292

COORDINATED ANALYSES OF PRESOLAR GRAINS IN THE ALLAN HILLS 77307 AND QUEEN ELIZABETH RANGE 99177 METEORITES

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

Nguyen, Ann N.; Nittler, Larry R.; Alexander, Conel M. O'D.

2010-08-10

We report the identification of presolar silicates ({approx}177 ppm), presolar oxides ({approx}11 ppm), and one presolar SiO{sub 2} grain in the Allan Hills (ALHA) 77307 chondrite. Three grains having Si-isotopic compositions similar to SiC X and Z grains were also identified, though the mineral phases are unconfirmed. Similar abundances of presolar silicates ({approx}152 ppm) and oxides ({approx}8 ppm) were also uncovered in the primitive CR chondrite Queen Elizabeth Range (QUE) 99177, along with 13 presolar SiC grains and one presolar silicon nitride. The O-isotopic compositions of the presolar silicates and oxides indicate that most of the grains condensed in low-massmore » red giant and asymptotic giant branch stars. Interestingly, unlike presolar oxides, few presolar silicate grains have isotopic compositions pointing to low-metallicity, low-mass stars (Group 3). The {sup 18}O-rich (Group 4) silicates, along with the few Group 3 silicates that were identified, likely have origins in supernova outflows. This is supported by their O- and Si-isotopic compositions. Elemental compositions for 74 presolar silicate grains were determined by scanning Auger spectroscopy. Most of the grains have non-stoichiometric elemental compositions inconsistent with pyroxene or olivine, the phases commonly used to fit astronomical spectra, and have comparable Mg and Fe contents. Non-equilibrium condensation and/or secondary alteration could produce the high Fe contents. Transmission electron microscopic analysis of three silicate grains also reveals non-stoichiometric compositions, attributable to non-equilibrium or multistep condensation, and very fine scale elemental heterogeneity, possibly due to subsequent annealing. The mineralogies of presolar silicates identified in meteorites thus far seem to differ from those in interplanetary dust particles.« less

A soft computing scheme incorporating ANN and MOV energy in fault detection, classification and distance estimation of EHV transmission line with FSC.

PubMed

Khadke, Piyush; Patne, Nita; Singh, Arvind; Shinde, Gulab

2016-01-01

In this article, a novel and accurate scheme for fault detection, classification and fault distance estimation for a fixed series compensated transmission line is proposed. The proposed scheme is based on artificial neural network (ANN) and metal oxide varistor (MOV) energy, employing Levenberg-Marquardt training algorithm. The novelty of this scheme is the use of MOV energy signals of fixed series capacitors (FSC) as input to train the ANN. Such approach has never been used in any earlier fault analysis algorithms in the last few decades. Proposed scheme uses only single end measurement energy signals of MOV in all the 3 phases over one cycle duration from the occurrence of a fault. Thereafter, these MOV energy signals are fed as input to ANN for fault distance estimation. Feasibility and reliability of the proposed scheme have been evaluated for all ten types of fault in test power system model at different fault inception angles over numerous fault locations. Real transmission system parameters of 3-phase 400 kV Wardha-Aurangabad transmission line (400 km) with 40 % FSC at Power Grid Wardha Substation, India is considered for this research. Extensive simulation experiments show that the proposed scheme provides quite accurate results which demonstrate complete protection scheme with high accuracy, simplicity and robustness.

Molecular characterization of two types of resistance in sunflower to Plasmopara halstedii, the causal agent of downy mildew.

PubMed

Radwan, Osman; Bouzidi, Mohamed Fouad; Mouzeyar, Said

2011-08-01

Depending on host-pathotype combination, two types of sunflower-Plasmopara halstedii incompatibility reactions have previously been identified. Type I resistance can restrict the growth of the pathogen in the basal region of the hypocotyls, whereas type II cannot, thus allowing the pathogen to reach the cotyledons. In type II resistance, a large portion of the hypocotyls is invaded by the pathogen and, subsequently, a hypersensitive reaction (HR) is activated over a long portion of the hypocotyls. Thus, the HR in type II resistance coincides with a higher induction of hsr203j sunflower homologue in comparison with type I resistance, where the HR is activated only in the basal part of hypocotyls. Although the pathogen was not detected in cotyledons of type I resistant plants, semiquantitative polymerase chain reaction confirmed the early abundant growth of the pathogen in cotyledons of susceptible plants by 6 days postinfection (dpi). This was in contrast to scarce growth of the pathogen in cotyledons of type II-resistant plants at a later time point (12 dpi). This suggests that pathogen growth differs according to the host-pathogen combination. To get more information about sunflower downy mildew resistance genes, the full-length cDNAs of RGC151 and RGC203, which segregated with the PlARG gene (resistance type I) and Pl14 gene (resistance type II), were cloned and sequenced. Sequence analyses revealed that RGC151 belongs to the Toll/interleukin-1 receptor (TIR) nucleotide-binding site leucine-rich repeat (NBS-LRR) class whereas RGC203 belongs to class coiled-coil (CC)-NBS-LRR. This study suggests that type II resistance may be controlled by CC-NBS-LRR gene transcripts which are enhanced upon infection by P. halstedii, rather than by the TIR-NBS-LRR genes that might control type I resistance.

A downy mildew effector attenuates salicylic acid-triggered immunity in Arabidopsis by interacting with the host mediator complex.

PubMed

Caillaud, Marie-Cécile; Asai, Shuta; Rallapalli, Ghanasyam; Piquerez, Sophie; Fabro, Georgina; Jones, Jonathan D G

2013-12-01

Plants are continually exposed to pathogen attack but usually remain healthy because they can activate defences upon perception of microbes. However, pathogens have evolved to overcome plant immunity by delivering effectors into the plant cell to attenuate defence, resulting in disease. Recent studies suggest that some effectors may manipulate host transcription, but the specific mechanisms by which such effectors promote susceptibility remain unclear. We study the oomycete downy mildew pathogen of Arabidopsis, Hyaloperonospora arabidopsidis (Hpa), and show here that the nuclear-localized effector HaRxL44 interacts with Mediator subunit 19a (MED19a), resulting in the degradation of MED19a in a proteasome-dependent manner. The Mediator complex of ∼25 proteins is broadly conserved in eukaryotes and mediates the interaction between transcriptional regulators and RNA polymerase II. We found MED19a to be a positive regulator of immunity against Hpa. Expression profiling experiments reveal transcriptional changes resembling jasmonic acid/ethylene (JA/ET) signalling in the presence of HaRxL44, and also 3 d after infection with Hpa. Elevated JA/ET signalling is associated with a decrease in salicylic acid (SA)-triggered immunity (SATI) in Arabidopsis plants expressing HaRxL44 and in med19a loss-of-function mutants, whereas SATI is elevated in plants overexpressing MED19a. Using a PR1::GUS reporter, we discovered that Hpa suppresses PR1 expression specifically in cells containing haustoria, into which RxLR effectors are delivered, but not in nonhaustoriated adjacent cells, which show high PR1::GUS expression levels. Thus, HaRxL44 interferes with Mediator function by degrading MED19, shifting the balance of defence transcription from SA-responsive defence to JA/ET-signalling, and enhancing susceptibility to biotrophs by attenuating SA-dependent gene expression.

A Downy Mildew Effector Attenuates Salicylic Acid–Triggered Immunity in Arabidopsis by Interacting with the Host Mediator Complex

PubMed Central

Caillaud, Marie-Cécile; Asai, Shuta; Rallapalli, Ghanasyam; Piquerez, Sophie; Fabro, Georgina; Jones, Jonathan D. G.

2013-01-01

Plants are continually exposed to pathogen attack but usually remain healthy because they can activate defences upon perception of microbes. However, pathogens have evolved to overcome plant immunity by delivering effectors into the plant cell to attenuate defence, resulting in disease. Recent studies suggest that some effectors may manipulate host transcription, but the specific mechanisms by which such effectors promote susceptibility remain unclear. We study the oomycete downy mildew pathogen of Arabidopsis, Hyaloperonospora arabidopsidis (Hpa), and show here that the nuclear-localized effector HaRxL44 interacts with Mediator subunit 19a (MED19a), resulting in the degradation of MED19a in a proteasome-dependent manner. The Mediator complex of ∼25 proteins is broadly conserved in eukaryotes and mediates the interaction between transcriptional regulators and RNA polymerase II. We found MED19a to be a positive regulator of immunity against Hpa. Expression profiling experiments reveal transcriptional changes resembling jasmonic acid/ethylene (JA/ET) signalling in the presence of HaRxL44, and also 3 d after infection with Hpa. Elevated JA/ET signalling is associated with a decrease in salicylic acid (SA)–triggered immunity (SATI) in Arabidopsis plants expressing HaRxL44 and in med19a loss-of-function mutants, whereas SATI is elevated in plants overexpressing MED19a. Using a PR1::GUS reporter, we discovered that Hpa suppresses PR1 expression specifically in cells containing haustoria, into which RxLR effectors are delivered, but not in nonhaustoriated adjacent cells, which show high PR1::GUS expression levels. Thus, HaRxL44 interferes with Mediator function by degrading MED19, shifting the balance of defence transcription from SA-responsive defence to JA/ET-signalling, and enhancing susceptibility to biotrophs by attenuating SA-dependent gene expression. PMID:24339748

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Driver And Dispatcher Perceptions Of AATA'S Advanced Operating System

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

Applications of AnnAGNPS model for soil loss estimation and nutrient loading for Malaysian conditions

NASA Astrophysics Data System (ADS)

Shamshad, A.; Leow, C. S.; Ramlah, A.; Wan Hussin, W. M. A.; Sanusi, S. A. Mohd.

2008-09-01

The study evaluated the performance and suitability of AnnAGNPS model in assessing runoff, sediment loading and nutrient loading under Malaysian conditions. The watershed of River Kuala Tasik in Malaysia, a combination of two sub-watersheds, was selected as the area of study. The data for the year 2004 was used to calibrate the model and the data for the year 2005 was used for validation purposes. Several input parameters were computed using methods suggested by other researchers and studies carried out in Malaysia. The study shows that runoff was predicted well with an overall R2 value of 0.90 and E value of 0.70. Sediment loading was able to produce a moderate result of R2 = 0.66 and E = 0.49, nitrogen loading predictions were slightly better with R2 = 0.68 and E = 0.53, and phosphorus loading performance was slightly poor with an R2 = 0.63 and E = 0.33. The erosion map developed was in agreement with the erosion risk map produced by the Department of Agriculture, Malaysia. Rubber estates and urban areas were found to be the main contributors to soil erosion. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for planning and management of watersheds under Malaysian conditions.

DRDC Technical Stream Integrated Capabilities and Vision

DTIC Science & Technology

2011-09-01

Brenda Fraser Allan Keefe Nada Pavlovic Doug Saunders Phil Terhaar Defence R&D Canada Technical Memorandum DRDC Toronto...Beechinor Hamid Boland Brenda Fraser Allan Keefe Nada Pavlovic Doug Saunders Phil Terhaar Defence R&D Canada – Toronto...Technical Memorandum DRDC Toronto TM 2011-017 September 2011 Principal Author Original signed by Allan Keefe Allan Keefe Technical

Effect of hydrogen fluoride on pollen germination and pollen tube growth in Prunus avium L. cv. Royal Ann

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

Facteau, T.J.; Wang, S.Y.; Rowe, K.E.

1973-05-01

Increased fluoride (F) fumigation levels resulted in decrease in percent Royal Ann pollen germination and pollen tube growth. As dose (hour x concentration in ..mu.. gF/m/sup 3/) increased, Van pollen tube growth in vivo decreased. A linear relationship between increased dose and fluoride residue in the flowers was shown. 14 references, 5 figures.

"Anne of Green Gables": A One-Act Musical Based on Lucy Maud Montgomery's Novel. Cue Sheet for Teachers.

ERIC Educational Resources Information Center

Flynn, Rosalind

This performance guide is designed for teachers to use with students before and after a performance of the one-act musical based on Lucy Maud Montgomery's novel, "Anne of Green Gables," with music by Richard DeRosa and book and lyrics by Greg Gunning. The guide is designed to help teachers foster students' appreciation of theatre, dance,…

Weed-Suppressive Soil Bacteria to Reduce Cheatgrass and Improve Vegetation Diversity on ITD Rights-of-Way

DOT National Transportation Integrated Search

2017-06-01

Transportation departments are challenged by the invasion of downy brome (cheatgrass) and medusahead. The reduction of downy brome (cheat grass) by Weed Suppressive Bacteria (WSB) Pseudomonas fluorescens strain ACK55 was evaluated on roadsides of I-8...

Meeting report for Odd Pols 2016: Ann Arbor 2.0.

PubMed

Roy-Engel, Astrid M

2017-05-15

The Tenth International Conference on Transcription by RNA Polymerases I, III, IV and V (the 'Odd Pols') was held June 24-28, 2016 at the University of Michigan, Ann Arbor, USA and organized by David Engelke, Deborah Johnson, Richard Maraia, Lawrence Rothblum, David Schneider, Andrzej Wierzbicki and Astrid Engel. The organizers are grateful for the support from the Rackham Graduate School of the University of Michigan for providing the meeting venue. The environment provided a great background with unexpected encounters with fireflies, free live music and a festive fireworks display. The meeting was composed of eleven oral sessions and a poster session. The keynote speaker, Dave Engelke, opened the meeting with his presentation entitled "A personal history of pol III transcription - how we got here from the 'good old days'." The meeting drew attendees from sixteen countries that shared their research discoveries. Here we present some of the highlights from the meeting using summaries provided by the participants. Copyright © 2016 Elsevier B.V. All rights reserved.

Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for

NASA Technical Reports Server (NTRS)

1993-01-01

Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for pictures in the NASA Magazine aritcle 'How it Feels to be a Human Test Subject' as they prepare for a bed rest study to simulate the efects of microgravity on the human body.

Two Different Approaches to Teaching Final-Year Projects for Mechanical Engineers and Biotechnologists at Ngee Ann Polytechnic--Case Studies Approach.

ERIC Educational Resources Information Center

Walsh, Kath; Rebaczonok-Padulo, Michael

1993-01-01

Ngee Ann Polytechnic, a leading postsecondary technical institution in Singapore, offers English for academic and occupational purposes to prepare students for writing their final year projects. This article discusses the approaches used in Mechanical Engineering and Biotechnology projects. A sample exercise is appended. (Contains two references.)…

Evaluation of the AnnAGNPS model for predicting runoff and sediment yield in a small Mediterranean agricultural watershed in Navarre (Spain)

USDA-ARS?s Scientific Manuscript database

AnnAGNPS (Annualized Agricultural Non-Point Source Pollution Model) is a system of computer models developed to predict non-point source pollutant loadings within agricultural watersheds. It contains a daily time step distributed parameter continuous simulation surface runoff model designed to assis...

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction

PubMed Central

Jaddi, Najmeh Sadat; Abdullah, Salwani; Abdul Malek, Marlinda

2017-01-01

Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results. PMID:28125609

Determining degree of roasting in cocoa beans by artificial neural network (ANN)-based electronic nose system and gas chromatography/mass spectrometry (GC/MS).

PubMed

Tan, Juzhong; Kerr, William L

2018-08-01

Roasting is a critical step in chocolate processing, where moisture content is decreased and unique flavors and texture are developed. The determination of the degree of roasting in cocoa beans is important to ensure the quality of chocolate. Determining the degree of roasting relies on human specialists or sophisticated chemical analyses that are inaccessible to small manufacturers and farmers. In this study, an electronic nose system was constructed consisting of an array of gas sensors and used to detect volatiles emanating from cocoa beans roasted for 0, 20, 30 and 40 min. The several signals were used to train a three-layer artificial neural network (ANN). Headspace samples were also analyzed by gas chromatography/mass spectrometry (GC/MS), with 23 select volatiles used to train a separate ANN. Both ANNs were used to predict the degree of roasting of cocoa beans. The electronic nose had a prediction accuracy of 94.4% using signals from sensors TGS 813, 826, 822, 830, 830, 2620, 2602 and 2610. In comparison, the GC/MS predicted the degree of roasting with an accuracy of 95.8%. The electronic nose system is able to predict the extent of roasting, as well as a more sophisticated approach using GC/MS. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction.

PubMed

Jaddi, Najmeh Sadat; Abdullah, Salwani; Abdul Malek, Marlinda

2017-01-01

Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results.

The adventures of Ann: A case study of a kindergarten teacher and her beliefs as she explored integrating science into her literacy curriculum

NASA Astrophysics Data System (ADS)

Potter, Gregory Ralph

Science education is an often neglected portion of the curriculum in elementary school, particularly in the primary grades. While early childhood educators have many choices in their curricula, two constants remain, literacy and math education. Ideally, young children need science along with literacy and mathematics. This study investigated how one kindergarten teacher used science to enhance her literacy program and how this use of science in her classroom affected her teaching beliefs. The case study took place in a publicly funded early childhood education center devoted to teaching kindergarten children in the small town of Summers in rural northern California. "Ann" was a master kindergarten teacher who historically used developmentally appropriate activities to support her literacy instruction. She was posed with the suggestion of infusing science into her literacy program and over the course of one school year, she was observed planning, implementing, and reflecting on six integrated science and literacy units. Ann's general teaching beliefs as well as her beliefs about teaching literacy and science were explored in order to investigate whether her experience with the integrated science and literacy units had altered her teaching beliefs. It was discovered that not only had Ann significantly changed the way she taught science, her beliefs about teaching science had changed and had moved towards mimicking her pro-active and positive beliefs about teaching literacy.

Design of an Experiment to Measure ann Using 3H(γ, pn)n at HIγS★

NASA Astrophysics Data System (ADS)

Friesen, F. Q. L.; Ahmed, M. W.; Crowe, B. J.; Crowell, A. S.; Cumberbatch, L. C.; Fallin, B.; Han, Z.; Howell, C. R.; Malone, R. M.; Markoff, D.; Tornow, W.; Witała, H.

2016-03-01

We provide an update on the development of an experiment at TUNL for determining the 1S0 neutron-neutron (nn) scattering length (ann) from differential cross-section measurements of three-body photodisintegration of the triton. The experiment will be conducted using a linearly polarized gamma-ray beam at the High Intensity Gamma-ray Source (HIγS) and tritium gas contained in thin-walled cells. The main components of the planned experiment are a 230 Ci gas target system, a set of wire chambers and silicon strip detectors on each side of the beam axis, and an array of neutron detectors on each side beyond the silicon detectors. The protons emitted in the reaction are tracked in the wire chambers and their energy and position are measured in silicon strip detectors. The first iteration of the experiment will be simplified, making use of a collimator system, and silicon detectors to interrogate the main region of interest near 90° in the polar angle. Monte-Carlo simulations based on rigorous 3N calculations have been conducted to validate the sensitivity of the experimental setup to ann. This research supported in part by the DOE Office of Nuclear Physics Grant Number DE-FG02-97ER41033

Detection of latent infections of Peronospora effusa in spinach

USDA-ARS?s Scientific Manuscript database

Downy mildew, caused by Peronospora effusa, is the most serious disease of spinach in central coastal California. The disease is managed in conventional production fields by a combination of host resistance and calendar-based fungicide applications, in which fungicides are applied to prevent downy ...

Ali, Cunich: Halley's Churches: Halley and the London Queen Anne Churches

NASA Astrophysics Data System (ADS)

Ali, Jason R.; Cunich, Peter

2005-04-01

Edmond Halley's enormous contribution to science has received much attention. New research adds an intriguing chapter to his story and concerns his hitherto unexplored association with the baroque architectural visionary Nicholas Hawksmoor, and some important Temple-inspired churches that were built in London in the early 1700s. We argue that Christchurch Spitalfields and St Anne's Limehouse, which were both started in the summer of 1714, were aligned exactly eastwards using ``corrected'' magnetic-compass bearings and that Halley influenced or aided Hawksmoor. By this time the men had probably known each other for 30 years and had recently worked together on the Clarendon Building in Oxford. Despite there being more than 1500 years of Chinese and about 500 years of Western compass technology at the time, these probably represent the first constructions planned using a modern-day ``scientific'' technique. The research also throws light on Halley's contended religious position.

Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

PubMed

Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

2017-08-15

Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

Two Different Approaches to Teaching Final-Year Projects for Mechanical Engineers and Biotechnologists at Ngee Ann Polytechnic: Case Studies Approach.

ERIC Educational Resources Information Center

Walsh, Kath; Rebaczonok-Padulo, Michael

The Oral and Written Communication (OWC) course at Ngee Ann Polytechnic was originally intended to equip students with occupational skills (e.g., report- and letter-writing, public speaking) but has expanded to be a course aimed at helping third-year mechanical engineering students to develop third-year project reports. This has been done through…

Modeling and Investigation of the Wear Resistance of Salt Bath Nitrided Aisi 4140 via ANN

NASA Astrophysics Data System (ADS)

Ekinci, Şerafettin; Akdemir, Ahmet; Kahramanli, Humar

2013-05-01

Nitriding is usually used to improve the surface properties of steel materials. In this way, the wear resistance of steels is improved. We conducted a series of studies in order to investigate the microstructural, mechanical and tribological properties of salt bath nitrided AISI 4140 steel. The present study has two parts. For the first phase, the tribological behavior of the AISI 4140 steel which was nitrided in sulfinuz salt bath (SBN) was compared to the behavior of the same steel which was untreated. After surface characterization using metallography, microhardness and sliding wear tests were performed on a block-on-cylinder machine in which carbonized AISI 52100 steel discs were used as the counter face. For the examined AISI 4140 steel samples with and without surface treatment, the evolution of both the friction coefficient and of the wear behavior were determined under various loads, at different sliding velocities and a total sliding distance of 1000 m. The test results showed that wear resistance increased with the nitriding process, friction coefficient decreased due to the sulfur in salt bath and friction coefficient depended systematically on surface hardness. For the second part of this study, four artificial neural network (ANN) models were designed to predict the weight loss and friction coefficient of the nitrided and unnitrided AISI 4140 steel. Load, velocity and sliding distance were used as input. Back-propagation algorithm was chosen for training the ANN. Statistical measurements of R2, MAE and RMSE were employed to evaluate the success of the systems. The results showed that all the systems produced successful results.

Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

PubMed

Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

2015-05-01

The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

Carbonates in the Martian meteorite Allan Hills 84001 formed at 18 ± 4 °C in a near-surface aqueous environment

PubMed Central

Halevy, Itay; Fischer, Woodward W.; Eiler, John M.

2011-01-01

Despite evidence for liquid water at the surface of Mars during the Noachian epoch, the temperature of early aqueous environments has been impossible to establish, raising questions of whether the surface of Mars was ever warmer than today. We address this problem by determining the precipitation temperature of secondary carbonate minerals preserved in the oldest known sample of Mars’ crust—the approximately 4.1 billion-year-old meteorite Allan Hills 84001 (ALH84001). The formation environment of these carbonates, which are constrained to be slightly younger than the crystallization age of the rock (i.e., 3.9 to 4.0 billion years), has been poorly understood, hindering insight into the hydrologic and carbon cycles of earliest Mars. Using “clumped” isotope thermometry we find that the carbonates in ALH84001 precipitated at a temperature of approximately 18 °C, with water and carbon dioxide derived from the ancient Martian atmosphere. Furthermore, covarying carbonate carbon and oxygen isotope ratios are constrained to have formed at constant, low temperatures, pointing to deposition from a gradually evaporating, subsurface water body—likely a shallow aquifer (meters to tens of meters below the surface). Despite the mild temperatures, the apparently ephemeral nature of water in this environment leaves open the question of its habitability. PMID:21969543

Prediction of GWL with the help of GRACE TWS for unevenly spaced time series data in India : Analysis of comparative performances of SVR, ANN and LRM

NASA Astrophysics Data System (ADS)

Mukherjee, Amritendu; Ramachandran, Parthasarathy

2018-03-01

Prediction of Ground Water Level (GWL) is extremely important for sustainable use and management of ground water resource. The motivations for this work is to understand the relationship between Gravity Recovery and Climate Experiment (GRACE) derived terrestrial water change (ΔTWS) data and GWL, so that ΔTWS could be used as a proxy measurement for GWL. In our study, we have selected five observation wells from different geographic regions in India. The datasets are unevenly spaced time series data which restricts us from applying standard time series methodologies and therefore in order to model and predict GWL with the help of ΔTWS, we have built Linear Regression Model (LRM), Support Vector Regression (SVR) and Artificial Neural Network (ANN). Comparative performances of LRM, SVR and ANN have been evaluated with the help of correlation coefficient (ρ) and Root Mean Square Error (RMSE) between the actual and fitted (for training dataset) or predicted (for test dataset) values of GWL. It has been observed in our study that ΔTWS is highly significant variable to model GWL and the amount of total variations in GWL that could be explained with the help of ΔTWS varies from 36.48% to 74.28% (0.3648 ⩽R2 ⩽ 0.7428) . We have found that for the model GWL ∼ Δ TWS, for both training and test dataset, performances of SVR and ANN are better than that of LRM in terms of ρ and RMSE. It also has been found in our study that with the inclusion of meteorological variables along with ΔTWS as input parameters to model GWL, the performance of SVR improves and it performs better than ANN. These results imply that for modelling irregular time series GWL data, ΔTWS could be very useful.

Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

NASA Astrophysics Data System (ADS)

Rahmati, Mehdi

2017-08-01

Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed

Applying of the Artificial Neural Networks (ANN) to Identify and Characterize Sweet Spots in Shale Gas Formations

NASA Astrophysics Data System (ADS)

Puskarczyk, Edyta

2018-03-01

The main goal of the study was to enhance and improve information about the Ordovician and Silurian gas-saturated shale formations. Author focused on: firstly, identification of the shale gas formations, especially the sweet spots horizons, secondly, classification and thirdly, the accurate characterization of divisional intervals. Data set comprised of standard well logs from the selected well. Shale formations are represented mainly by claystones, siltstones, and mudstones. The formations are also partially rich in organic matter. During the calculations, information about lithology of stratigraphy weren't taken into account. In the analysis, selforganizing neural network - Kohonen Algorithm (ANN) was used for sweet spots identification. Different networks and different software were tested and the best network was used for application and interpretation. As a results of Kohonen networks, groups corresponding to the gas-bearing intervals were found. The analysis showed diversification between gas-bearing formations and surrounding beds. It is also shown that internal diversification in sweet spots is present. Kohonen algorithm was also used for geological interpretation of well log data and electrofacies prediction. Reliable characteristic into groups shows that Ja Mb and Sa Fm which are usually treated as potential sweet spots only partially have good reservoir conditions. It is concluded that ANN appears to be useful and quick tool for preliminary classification of members and sweet spots identification.

Workshop on Surface Science and Technology Held in Ann Arbor, Michigan on 7-9 November 1990

DTIC Science & Technology

1992-03-01

assess the state of the art of surface science and technology as well as to identify new research opportunities essential for the understanding and control...The objective of this workshop was to review and assess the state of the art of surface science and technology as well as to identify new research...AD-A253 566 ’ # 4 - m~~i n~nl lInIir ~~ na Ri1 ?epoi’rt: EN 1Workshop on Surface Science and Technology DTIC ft , L-CTE I OUG0 3192 Ann Arbor

Evaluation of a non-point source pollution model, AnnAGNPS, in a tropical watershed

USGS Publications Warehouse

Polyakov, V.; Fares, A.; Kubo, D.; Jacobi, J.; Smith, C.

2007-01-01

Impaired water quality caused by human activity and the spread of invasive plant and animal species has been identified as a major factor of degradation of coastal ecosystems in the tropics. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized Non-Point Source Pollution Model), in simulating runoff and soil erosion in a 48 km2 watershed located on the Island of Kauai, Hawaii. The model was calibrated and validated using 2 years of observed stream flow and sediment load data. Alternative scenarios of spatial rainfall distribution and canopy interception were evaluated. Monthly runoff volumes predicted by AnnAGNPS compared well with the measured data (R2 = 0.90, P < 0.05); however, up to 60% difference between the actual and simulated runoff were observed during the driest months (May and July). Prediction of daily runoff was less accurate (R2 = 0.55, P < 0.05). Predicted and observed sediment yield on a daily basis was poorly correlated (R2 = 0.5, P < 0.05). For the events of small magnitude, the model generally overestimated sediment yield, while the opposite was true for larger events. Total monthly sediment yield varied within 50% of the observed values, except for May 2004. Among the input parameters the model was most sensitive to the values of ground residue cover and canopy cover. It was found that approximately one third of the watershed area had low sediment yield (0-1 t ha-1 y-1), and presented limited erosion threat. However, 5% of the area had sediment yields in excess of 5 t ha-1 y-1. Overall, the model performed reasonably well, and it can be used as a management tool on tropical watersheds to estimate and compare sediment loads, and identify "hot spots" on the landscape. ?? 2007 Elsevier Ltd. All rights reserved.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Cost Study : Before, During And After AOS Implementation (October 1996-May 1999)

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority (AATA) began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such te...

Proceedings of Workshop on Priority Great Lakes Environmental Research Initiatives (Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan, October 10-11, 1974).

ERIC Educational Resources Information Center

Pinsak, Arthur P., Ed.

This publication contains the proceedings of a workshop held in Ann Arbor, Michigan to identify the priority Great Lakes environmental research initiatives. The five major objectives of the workshop include the determination of research initiatives, opportunities for university research communities to discuss and recommend future research…

The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data

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

Behrang, M.A.; Assareh, E.; Ghanbarzadeh, A.

2010-08-15

The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output.more » (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)« less

An Experimental Investigation into the Optimal Processing Conditions for the CO2 Laser Cladding of 20 MnCr5 Steel Using Taguchi Method and ANN

NASA Astrophysics Data System (ADS)

Mondal, Subrata; Bandyopadhyay, Asish.; Pal, Pradip Kumar

2010-10-01

This paper presents the prediction and evaluation of laser clad profile formed by means of CO2 laser applying Taguchi method and the artificial neural network (ANN). Laser cladding is one of the surface modifying technologies in which the desired surface characteristics of any component can be achieved such as good corrosion resistance, wear resistance and hardness etc. Laser is used as a heat source to melt the anti-corrosive powder of Inconel-625 (Super Alloy) to give a coating on 20 MnCr5 substrate. The parametric study of this technique is also attempted here. The data obtained from experiments have been used to develop the linear regression equation and then to develop the neural network model. Moreover, the data obtained from regression equations have also been used as supporting data to train the neural network. The artificial neural network (ANN) is used to establish the relationship between the input/output parameters of the process. The established ANN model is then indirectly integrated with the optimization technique. It has been seen that the developed neural network model shows a good degree of approximation with experimental data. In order to obtain the combination of process parameters such as laser power, scan speed and powder feed rate for which the output parameters become optimum, the experimental data have been used to develop the response surfaces.

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.

PubMed

Leng, Xiang'zi; Wang, Jinhua; Ji, Haibo; Wang, Qin'geng; Li, Huiming; Qian, Xin; Li, Fengying; Yang, Meng

2017-08-01

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM 2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m 3 . Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5 μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5 μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of ANN and SVM for classification of eye movements in EOG signals

NASA Astrophysics Data System (ADS)

Qi, Lim Jia; Alias, Norma

2018-03-01

Nowadays, electrooculogram is regarded as one of the most important biomedical signal in measuring and analyzing eye movement patterns. Thus, it is helpful in designing EOG-based Human Computer Interface (HCI). In this research, electrooculography (EOG) data was obtained from five volunteers. The (EOG) data was then preprocessed before feature extraction methods were employed to further reduce the dimensionality of data. Three feature extraction approaches were put forward, namely statistical parameters, autoregressive (AR) coefficients using Burg method, and power spectral density (PSD) using Yule-Walker method. These features would then become input to both artificial neural network (ANN) and support vector machine (SVM). The performance of the combination of different feature extraction methods and classifiers was presented and analyzed. It was found that statistical parameters + SVM achieved the highest classification accuracy of 69.75%.

An Emotional ANN (EANN) approach to modeling rainfall-runoff process

NASA Astrophysics Data System (ADS)

Nourani, Vahid

2017-01-01

This paper presents the first hydrological implementation of Emotional Artificial Neural Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall-runoff (r-r) modeling of the watersheds. Inspired by neurophysiological form of brain, in addition to conventional weights and bias, an EANN includes simulated emotional parameters aimed at improving the network learning process. EANN trained by a modified version of back-propagation (BP) algorithm was applied to single and multi-step-ahead runoff forecasting of two watersheds with two distinct climatic conditions. Also to evaluate the ability of EANN trained by smaller training data set, three data division strategies with different number of training samples were considered for the training purpose. The overall comparison of the obtained results of the r-r modeling indicates that the EANN could outperform the conventional feed forward neural network (FFNN) model up to 13% and 34% in terms of training and verification efficiency criteria, respectively. The superiority of EANN over classic ANN is due to its ability to recognize and distinguish dry (rainless days) and wet (rainy days) situations using hormonal parameters of the artificial emotional system.

An experimental study of interstitial lung tissue classification in HRCT images using ANN and role of cost functions

NASA Astrophysics Data System (ADS)

Dash, Jatindra K.; Kale, Mandar; Mukhopadhyay, Sudipta; Khandelwal, Niranjan; Prabhakar, Nidhi; Garg, Mandeep; Kalra, Naveen

2017-03-01

In this paper, we investigate the effect of the error criteria used during a training phase of the artificial neural network (ANN) on the accuracy of the classifier for classification of lung tissues affected with Interstitial Lung Diseases (ILD). Mean square error (MSE) and the cross-entropy (CE) criteria are chosen being most popular choice in state-of-the-art implementations. The classification experiment performed on the six interstitial lung disease (ILD) patterns viz. Consolidation, Emphysema, Ground Glass Opacity, Micronodules, Fibrosis and Healthy from MedGIFT database. The texture features from an arbitrary region of interest (AROI) are extracted using Gabor filter. Two different neural networks are trained with the scaled conjugate gradient back propagation algorithm with MSE and CE error criteria function respectively for weight updation. Performance is evaluated in terms of average accuracy of these classifiers using 4 fold cross-validation. Each network is trained for five times for each fold with randomly initialized weight vectors and accuracies are computed. Significant improvement in classification accuracy is observed when ANN is trained by using CE (67.27%) as error function compared to MSE (63.60%). Moreover, standard deviation of the classification accuracy for the network trained with CE (6.69) error criteria is found less as compared to network trained with MSE (10.32) criteria.

[Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

PubMed

Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

2010-01-01

Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

77 FR 27357 - IFR Altitudes; Miscellaneous Amendments

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-10

... Hygen, CO FIX *Allan, CO FIX **13500 *16000--MRA *15400--MCA ALLAN, CO FIX, NW BND **12900--MOCA *CHART... *Allan, CO FIX Laramie, WY VOR/DME..... 16000 *16000--MRA Sec. 95.6106 VOR Federal Airway V106 Is Amended... in Part Olympia, WA VORTAC *Carro, WA FIX **4000 *4000--MRA **2000--MOCA *CARRO, WA FIX Diggn, WA FIX...

Constitutive Equations and ANN Approach to Predict the Flow Stress of Ti-6Al-4V Alloy Based on ABI Tests

NASA Astrophysics Data System (ADS)

Wang, Fuzeng; Zhao, Jun; Zhu, Ningbo

2016-11-01

The flow behavior of Ti-6Al-4V alloy was studied by automated ball indentation (ABI) tests in a wide range of temperatures (293, 493, 693, and 873 K) and strain rates (10-6, 10-5, and 10-4 s-1). Based on the experimental true stress-plastic strain data derived from the ABI tests, the Johnson-Cook (JC), Khan-Huang-Liang (KHL) and modified Zerilli-Armstrong (ZA) constitutive models, as well as artificial neural network (ANN) methods, were employed to predict the flow behavior of Ti-6Al-4V. A comparative study was made on the reliability of the four models, and their predictability was evaluated in terms of correlation coefficient ( R) and mean absolute percentage error. It is found that the flow stresses of Ti-6Al-4V alloy are more sensitive to temperature than strain rate under current experimental conditions. The predicted flow stresses obtained from JC model and KHL model show much better agreement with the experimental results than modified ZA model. Moreover, the ANN model is much more efficient and shows a higher accuracy in predicting the flow behavior of Ti-6Al-4V alloy than the constitutive equations.

The heart of Blessed Anne-Madeleine Remuzat: a biomedical approach of "miraculous" heart conservation.

PubMed

Charlier, Philippe; Huynh-Charlier, Isabelle; Poupon, Joël; Fox, Carles Lalueza; Keyser, Christine; Mougniot, Christian; Popescu, Spéranta-Maria; Brun, Luc; Pietri, Sylvia; Thévenard, Frédéric; Laquay, Laëtitia; Hurel, Agathe; Ellul, Jean-Pierre; Hervé, Christian

2014-01-01

We present here the results of our inter-disciplinary examination of the mummified heart of Blessed Anne-Madeleine Remuzat (1696-1730). This organ has been examined in the context of a canonization process. This analysis is related to important aspects of the early history of anatomy in Europe, that of "Holy autopsies", and to the relationship between anatomical investigations, Catholic theology, and religious/medical customs. According to anatomical, genetic, toxicological, and palynological analyses, it has been shown that this organ has not been naturally ("miraculously") conserved but embalmed using myrtle, honey, and lime. Moreover, a right ventricle dilatation has been diagnosed, that may represent a post-tuberculosis condition and may have played a role in the cause of death of this religious figure. Copyright © 2014 Elsevier Inc. All rights reserved.

[The utility boiler low NOx combustion optimization based on ANN and simulated annealing algorithm].

PubMed

Zhou, Hao; Qian, Xinping; Zheng, Ligang; Weng, Anxin; Cen, Kefa

2003-11-01

With the developing restrict environmental protection demand, more attention was paid on the low NOx combustion optimizing technology for its cheap and easy property. In this work, field experiments on the NOx emissions characteristics of a 600 MW coal-fired boiler were carried out, on the base of the artificial neural network (ANN) modeling, the simulated annealing (SA) algorithm was employed to optimize the boiler combustion to achieve a low NOx emissions concentration, and the combustion scheme was obtained. Two sets of SA parameters were adopted to find a better SA scheme, the result show that the parameters of T0 = 50 K, alpha = 0.6 can lead to a better optimizing process. This work can give the foundation of the boiler low NOx combustion on-line control technology.

Optimization of delignification of two Pennisetum grass species by NaOH pretreatment using Taguchi and ANN statistical approach.

PubMed

Mohaptra, Sonali; Dash, Preeti Krishna; Behera, Sudhanshu Shekar; Thatoi, Hrudayanath

2016-01-01

In the bioconversion of lignocelluloses for bioethanol, pretreatment seems to be the most important step which improves the elimination of the lignin and hemicelluloses content, exposing cellulose to further hydrolysis. The present study discusses the application of dynamic statistical techniques like the Taguchi method and artificial neural network (ANN) in the optimization of pretreatment of lignocellulosic biomasses such as Hybrid Napier grass (HNG) (Pennisetum purpureum) and Denanath grass (DG) (Pennisetum pedicellatum), using alkali sodium hydroxide. This study analysed and determined a parameter combination with a low number of experiments by using the Taguchi method in which both the substrates can be efficiently pretreated. The optimized parameters obtained from the L16 orthogonal array are soaking time (18 and 26 h), temperature (60°C and 55°C), and alkali concentration (1%) for HNG and DG, respectively. High performance liquid chromatography analysis of the optimized pretreated grass varieties confirmed the presence of glucan (47.94% and 46.50%), xylan (9.35% and 7.95%), arabinan (2.15% and 2.2%), and galactan/mannan (1.44% and 1.52%) for HNG and DG, respectively. Physicochemical characterization studies of native and alkali-pretreated grasses were carried out by scanning electron microscopy and Fourier transformation Infrared spectroscopy which revealed some morphological differences between the native and optimized pretreated samples. Model validation by ANN showed a good agreement between experimental results and the predicted responses.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Transfer And On-Time Performance Study : Before And After AOS Implementation, October 1996 - May 1999

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

Tell it to someone who cares. The health care industry wants more information--and Anne Arundel Health Care Systems is giving it to them.

PubMed

Appleby, C

1995-10-20

The way to succeed in the health care industry these days is to stay ahead of the information curve. With a lot of ingenuity and a stern eye on the bottom line, Anne Arundel Health Care Systems in Maryland is doing just that. Here's how and why they did it, and how much they paid.

The use of artificial neural network (ANN) for the prediction and simulation of oil degradation in wastewater by AOP.

PubMed

Mustafa, Yasmen A; Jaid, Ghydaa M; Alwared, Abeer I; Ebrahim, Mothana

2014-06-01

The application of advanced oxidation process (AOP) in the treatment of wastewater contaminated with oil was investigated in this study. The AOP investigated is the homogeneous photo-Fenton (UV/H2O2/Fe(+2)) process. The reaction is influenced by the input concentration of hydrogen peroxide H2O2, amount of the iron catalyst Fe(+2), pH, temperature, irradiation time, and concentration of oil in the wastewater. The removal efficiency for the used system at the optimal operational parameters (H2O2 = 400 mg/L, Fe(+2) = 40 mg/L, pH = 3, irradiation time = 150 min, and temperature = 30 °C) for 1,000 mg/L oil load was found to be 72%. The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of oil degradation in aqueous solution by photo-Fenton process. The multilayered feed-forward networks were trained by using a backpropagation algorithm; a three-layer network with 22 neurons in the hidden layer gave optimal results. The results show that the ANN model can predict the experimental results with high correlation coefficient (R (2) = 0.9949). The sensitivity analysis showed that all studied variables (H2O2, Fe(+2), pH, irradiation time, temperature, and oil concentration) have strong effect on the oil degradation. The pH was found to be the most influential parameter with relative importance of 20.6%.

Identification of a New Blend of Host Fruit Volatiles from Red Downy Hawthorn, Crataegus mollis, Attractive to Rhagoletis pomonella Flies from the Northeastern United States.

PubMed

Cha, Dong H; Powell, Thomas H Q; Feder, Jeffrey L; Linn, Charles E

2018-06-20

A new blend of volatiles was identified for the fruit of downy red hawthorn, Crataegus mollis, that is attractive to Rhagoletis pomonella flies infesting this host in the northeastern USA. The new blend was as attractive as the previously identified mixture but is more complex in the number of odorants (six in the old versus ten in the new) and differs significantly in the ratio of three volatiles, 3-methylbutan-1-ol, butyl hexanoate, and dihydro-β-ionone, that are common to both blends and exerted agonist or antagonist effects on behavior in a flight tunnel assay. However, behavioral results with the old and new northern hawthorn blends, as well as modified blends with substituted ratios of 3-methylbutan-1-ol, butyl hexanoate, dihydro-β-ionone, indicated that the 'agonist' or 'antagonist' effects of these volatiles depended on the ratio, or balance of compounds within the blend. In addition, the new blend contains a number of esters identified from the headspace of domesticated apple, Malus domestica, that are attractive to apple-origin R. pomonella, and present in the five other blends from southern hawthorns, including the southern C. mollis var. texana blend, but are not part of the previously identified blend from northern C. mollis fruit. This finding supports the hypothesis that in addition to providing specificity to the odor blends of the northern and southern hawthorn populations, the presence of the significant amounts of ester compounds in the new northern hawthorn blend might have provided a source of standing variation that could help explain the shift in host preference by C. mollis-infesting flies to introduced apple in the mid-1800's.

Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

PubMed

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

Women's translations of scientific texts in the 18th century: a case study of Marie-Anne Lavoisier.

PubMed

Kawashima, Keiko

2011-01-01

In the 18th century, many outstanding translations of scientific texts were done by women. These women were important mediators of science. However, I would like to raise the issue that the 'selection,' which is the process by which intellectual women chose to conduct translation works, and those 'selections' made by male translators, would not be made at the same level. For example, Émilie du Châtelet (1706-1749), the only French translator of Newton's "Principia," admitted her role as participating in important work, but, still, she was not perfectly satisfied with the position. For du Châtelet, the role as a translator was only an option under the current conditions that a female was denied the right to be a creator by society. In the case of Marie-Anne Lavoisier (1743-1794), like du Châtelet, we find an acute feeling in her mind that translation was not the work of creators. Because of her respect toward creative geniuses and her knowledge about the practical situation and concrete results of scientific studies, the translation works done by Marie-Anne Lavoisier were excellent. At the same time, the source of this excellence appears paradoxical at a glance: this excellence of translation was related closely with her low self-estimation in the field of science. Hence, we should not forget the gender problem that is behind such translations of scientific works done by women in that era. Such a possibility was a ray of light that was grasped by females, the sign of a gender that was eliminated from the center of scientific study due to social systems and norms and one of the few valuable opportunities to let people know of her own existence in the field of science.

Determination of zinc oxide content of mineral medicine calamine using near-infrared spectroscopy based on MIV and BP-ANN algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Chen, Long; Sun, Yangbo; Bai, Yu; Huang, Bisheng; Chen, Keli

2018-03-01

Near-infrared (NIR) spectroscopy has been widely used in the analysis fields of traditional Chinese medicine. It has the advantages of fast analysis, no damage to samples and no pollution. In this research, a fast quantitative model for zinc oxide (ZnO) content in mineral medicine calamine was explored based on NIR spectroscopy. NIR spectra of 57 batches of calamine samples were collected and the first derivative (FD) method was adopted for conducting spectral pretreatment. The content of ZnO in calamine sample was determined using ethylenediaminetetraacetic acid (EDTA) titration and taken as reference value of NIR spectroscopy. 57 batches of calamine samples were categorized into calibration and prediction set using the Kennard-Stone (K-S) algorithm. Firstly, in the calibration set, to calculate the correlation coefficient (r) between the absorbance value and the ZnO content of corresponding samples at each wave number. Next, according to the square correlation coefficient (r2) value to obtain the top 50 wave numbers to compose the characteristic spectral bands (4081.8-4096.3, 4188.9-4274.7, 4335.4, 4763.6,4794.4-4802.1, 4809.9, 4817.6-4875.4 cm- 1), which were used to establish the quantitative model of ZnO content using back propagation artificial neural network (BP-ANN) algorithm. Then, the 50 wave numbers were operated by the mean impact value (MIV) algorithm to choose wave numbers whose absolute value of MIV greater than or equal to 25, to obtain the optimal characteristic spectral bands (4875.4-4836.9, 4223.6-4080.9 cm- 1). And then, both internal cross and external validation were used to screen the number of hidden layer nodes of BP-ANN. Finally, the number 4 of hidden layer nodes was chosen as the best. At last, the BP-ANN model was found to enjoy a high accuracy and strong forecasting capacity for analyzing ZnO content in calamine samples ranging within 42.05-69.98%, with relative mean square error of cross validation (RMSECV) of 1.66% and coefficient of

A frequency-domain approach to improve ANNs generalization quality via proper initialization.

PubMed

Chaari, Majdi; Fekih, Afef; Seibi, Abdennour C; Hmida, Jalel Ben

2018-08-01

The ability to train a network without memorizing the input/output data, thereby allowing a good predictive performance when applied to unseen data, is paramount in ANN applications. In this paper, we propose a frequency-domain approach to evaluate the network initialization in terms of quality of training, i.e., generalization capabilities. As an alternative to the conventional time-domain methods, the proposed approach eliminates the approximate nature of network validation using an excess of unseen data. The benefits of the proposed approach are demonstrated using two numerical examples, where two trained networks performed similarly on the training and the validation data sets, yet they revealed a significant difference in prediction accuracy when tested using a different data set. This observation is of utmost importance in modeling applications requiring a high degree of accuracy. The efficiency of the proposed approach is further demonstrated on a real-world problem, where unlike other initialization methods, a more conclusive assessment of generalization is achieved. On the practical front, subtle methodological and implementational facets are addressed to ensure reproducibility and pinpoint the limitations of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

NASA Astrophysics Data System (ADS)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells.

PubMed

Yetilmezsoy, Kaan; Demirel, Sevgi

2008-05-30

A three-layer artificial neural network (ANN) model was developed to predict the efficiency of Pb(II) ions removal from aqueous solution by Antep pistachio (Pistacia Vera L.) shells based on 66 experimental sets obtained in a laboratory batch study. The effect of operational parameters such as adsorbent dosage, initial concentration of Pb(II) ions, initial pH, operating temperature, and contact time were studied to optimise the conditions for maximum removal of Pb(II) ions. On the basis of batch test results, optimal operating conditions were determined to be an initial pH of 5.5, an adsorbent dosage of 1.0 g, an initial Pb(II) concentration of 30 ppm, and a temperature of 30 degrees C. Experimental results showed that a contact time of 45 min was generally sufficient to achieve equilibrium. After backpropagation (BP) training combined with principal component analysis (PCA), the ANN model was able to predict adsorption efficiency with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and a linear transfer function (purelin) at output layer. The Levenberg-Marquardt algorithm (LMA) was found as the best of 11 BP algorithms with a minimum mean squared error (MSE) of 0.000227875. The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of about 0.936 for five model variables used in this study.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake.

PubMed

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-09-02

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

PubMed Central

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-01-01

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds. PMID:26364642

Application of Particle Swarm Optimization Algorithm for Optimizing ANN Model in Recognizing Ripeness of Citrus

NASA Astrophysics Data System (ADS)

Diyana Rosli, Anis; Adenan, Nur Sabrina; Hashim, Hadzli; Ezan Abdullah, Noor; Sulaiman, Suhaimi; Baharudin, Rohaiza

2018-03-01

This paper shows findings of the application of Particle Swarm Optimization (PSO) algorithm in optimizing an Artificial Neural Network that could categorize between ripeness and unripeness stage of citrus suhuensis. The algorithm would adjust the network connections weights and adapt its values during training for best results at the output. Initially, citrus suhuensis fruit’s skin is measured using optically non-destructive method via spectrometer. The spectrometer would transmit VIS (visible spectrum) photonic light radiation to the surface (skin of citrus) of the sample. The reflected light from the sample’s surface would be received and measured by the same spectrometer in terms of reflectance percentage based on VIS range. These measured data are used to train and test the best optimized ANN model. The accuracy is based on receiver operating characteristic (ROC) performance. The result outcomes from this investigation have shown that the achieved accuracy for the optimized is 70.5% with a sensitivity and specificity of 60.1% and 80.0% respectively.

Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA)

PubMed Central

Shi, Xuedan; Ruan, Wenqian; Hu, Jiwei; Fan, Mingyi; Cao, Rensheng; Wei, Xionghui

2017-01-01

Rhodamine B (Rh B) is a toxic dye that is harmful to the environment, humans, and animals, and thus the discharge of Rh B wastewater has become a critical concern. In the present study, reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) was used to treat Rh B aqueous solutions. The nZVI/rGO composites were synthesized with the chemical deposition method and were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, N2-sorption, and X-ray photoelectron spectroscopy (XPS) analysis. The effects of several important parameters (initial pH, initial concentration, temperature, and contact time) on the removal of Rh B by nZVI/rGO were optimized by response surface methodology (RSM) and artificial neural network hybridized with genetic algorithm (ANN-GA). The results suggest that the ANN-GA model was more accurate than the RSM model. The predicted optimum value of Rh B removal efficiency (90.0%) was determined using the ANN-GA model, which was compatible with the experimental value (86.4%). Moreover, the Langmuir, Freundlich, and Temkin isotherm equations were applied to fit the adsorption equilibrium data, and the Freundlich isotherm was the most suitable model for describing the process for sorption of Rh B onto the nZVI/rGO composites. The maximum adsorption capacity based on the Langmuir isotherm was 87.72 mg/g. The removal process of Rh B could be completed within 20 min, which was well described by the pseudo-second order kinetic model. PMID:28587196

Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA).

PubMed

Shi, Xuedan; Ruan, Wenqian; Hu, Jiwei; Fan, Mingyi; Cao, Rensheng; Wei, Xionghui

2017-06-03

Rhodamine B (Rh B) is a toxic dye that is harmful to the environment, humans, and animals, and thus the discharge of Rh B wastewater has become a critical concern. In the present study, reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) was used to treat Rh B aqueous solutions. The nZVI/rGO composites were synthesized with the chemical deposition method and were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, N₂-sorption, and X-ray photoelectron spectroscopy (XPS) analysis. The effects of several important parameters (initial pH, initial concentration, temperature, and contact time) on the removal of Rh B by nZVI/rGO were optimized by response surface methodology (RSM) and artificial neural network hybridized with genetic algorithm (ANN-GA). The results suggest that the ANN-GA model was more accurate than the RSM model. The predicted optimum value of Rh B removal efficiency (90.0%) was determined using the ANN-GA model, which was compatible with the experimental value (86.4%). Moreover, the Langmuir, Freundlich, and Temkin isotherm equations were applied to fit the adsorption equilibrium data, and the Freundlich isotherm was the most suitable model for describing the process for sorption of Rh B onto the nZVI/rGO composites. The maximum adsorption capacity based on the Langmuir isotherm was 87.72 mg/g. The removal process of Rh B could be completed within 20 min, which was well described by the pseudo-second order kinetic model.

Estimation of runoff and sediment yield in the Redrock Creek watershed using AnnAGNPS and GIS

USGS Publications Warehouse

Tsou, Ming‐shu; Zhan, X.-Y.

2004-01-01

Sediment has been identified as a significant threat to water quality and channel clogging that in turn may lead to river flooding. With the increasing awareness of the impairment from sediment to water bodies in a watershed, identifying the locations of the major sediment sources and reducing the sediment through management practices will be important for an effective watershed management. The annualized agricultural non-point source pollution (AnnAGNPS) model and newly developed GIS interface for it were applied in a small agricultural watershed, Redrock Creek watershed, Kansas, in this pilot study for exploring the effectiveness of using this model as a management tool. The calibrated model appropriately simulated monthly runoff and sediment yield through the practices in this study and potentially suggested the ways of sediment reduction through evaluating the changes of land use and field operation in the model for the purpose of watershed management.

Detection of Verticillium wilt of olive trees and downy mildew of opium poppy using hyperspectral and thermal UAV imagery

NASA Astrophysics Data System (ADS)

Calderón Madrid, Rocío; Navas Cortés, Juan Antonio; Montes Borrego, Miguel; Landa del Castillo, Blanca Beatriz; Lucena León, Carlos; Jesús Zarco Tejada, Pablo

2014-05-01

The present study explored the use of high-resolution thermal, multispectral and hyperspectral imagery as indicators of the infections caused by Verticillium wilt (VW) in olive trees and downy mildew (DM) in opium poppy fields. VW, caused by the soil-borne fungus Verticillium dahliae, and DM, caused by the biotrophic obligate oomycete Peronospora arborescens, are the most economically limiting diseases of olive trees and opium poppy, respectively, worldwide. V. dahliae infects the plant by the roots and colonizes its vascular system, blocking water flow and eventually inducing water stress. P. arborescens colonizes the mesophyll, appearing the first symptoms as small chlorotic leaf lesions, which can evolve to curled and thickened tissues and systemic infections that become deformed and necrotic as the disease develops. The work conducted to detect VW and DM infection consisted on the acquisition of time series of airborne thermal, multispectral and hyperspectral imagery using 2-m and 5-m wingspan electric Unmanned Aerial Vehicles (UAVs) in spring and summer of three consecutive years (2009 to 2011) for VW detection and on three dates in spring of 2009 for DM detection. Two 7-ha commercial olive orchards naturally infected with V. dahliae and two opium poppy field plots artificially infected by P. arborescens were flown. Concurrently to the airborne campaigns, olive orchards and opium poppy fields were assessed "in situ" to assess actual VW severity and DM incidence. Furthermore, field measurements were conducted at leaf and crown level. The field results related to VW detection showed a significant increase in crown temperature (Tc) minus air temperature (Ta) and a decrease in leaf stomatal conductance (G) as VW severity increased. This reduction in G was associated with a significant increase in the Photochemical Reflectance Index (PRI570) and a decrease in chlorophyll fluorescence. DM asymptomatic leaves showed significantly higher NDVI and lower green/red index

Something Spacey for Everyone

NASA Astrophysics Data System (ADS)

Bonett, D.; Cabana, C.; Thompson, P.; Noel, M.; Johnson, K.

2001-12-01

LPI scientists, education/outreach staff, and library staff participated in Space Day at K.E. Little Elementary in Bacliff, Texas on May 3. The school, which serves 925 students and more than 50 faculty, suspended regular classes for the entire day so that all could participate. Dr. Allan Treiman gave a talk on meteorites; Dr. Joe Hahn gave a talk on comets; Dr. Paul Spudis gave a talk on the Moon; Dr. Carl Allen (JSC) gave a presentation on Mars exploration; and Dr. Paul Schenk presented the solar system in 3D in the computer lab. Sandra Cherry, Delilah Cranford, Mary Ann Hager, Diane Myers, Mary Noel, and Pam Thompson gave presentations to K-5 classes on rocketry and space capsules and guided students in doing a related hands-on activity project. These activities were part of the EXPLORE Fun with Science program. Ms. Thompson also led a hands-on reflectance spectrometry lab with the 5th grade gifted and talented cluster. Space Day 2001 was a full day of hands on interactive space experience for all students pre-kindergarten to fifth grade. With the permission of principal, Mary Ann Cole, the school shut down the normal and went into outer space. Whether making moon cookies out of rice krispies and peanut butter, parachuting an "eggstronaut" from a fire truck, throwing a frisbee across the scaled solar system or listening to a planetary geologist discuss man's discoveries on the moon, Space Day 2001 at KE Little Elementary school wet the appetites of it's students and faculty and had everyone saying, "Lets do this again next year"!

A comparison RSM and ANN surface roughness models in thin-wall machining of Ti6Al4V using vegetable oils under MQL-condition

NASA Astrophysics Data System (ADS)

Mohruni, Amrifan Saladin; Yanis, Muhammad; Sharif, Safian; Yani, Irsyadi; Yuliwati, Erna; Ismail, Ahmad Fauzi; Shayfull, Zamree

2017-09-01

Thin-wall components as usually applied in the structural parts of aeronautical industry require significant challenges in machining. Unacceptable surface roughness can occur during machining of thin-wall. Titanium product such Ti6Al4V is mostly applied to get the appropriate surface texture in thin wall designed requirements. In this study, the comparison of the accuracy between Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) in the prediction of surface roughness was conducted. Furthermore, the machining tests were carried out under Minimum Quantity Lubrication (MQL) using AlCrN-coated carbide tools. The use of Coconut oil as cutting fluids was also chosen in order to evaluate its performance when involved in end milling. This selection of cutting fluids is based on the better performance of oxidative stability than that of other vegetable based cutting fluids. The cutting speed, feed rate, radial and axial depth of cut were used as independent variables, while surface roughness is evaluated as the dependent variable or output. The results showed that the feed rate is the most significant factors in increasing the surface roughness value followed by the radial depth of cut and lastly the axial depth of cut. In contrary, the surface becomes smoother with increasing the cutting speed. From a comparison of both methods, the ANN model delivered a better accuracy than the RSM model.

The educational challenge of Paediatric Virology: An interview with Professor of Neonatology Anne Greenough.

PubMed

Mammas, Ioannis N; Spandidos, Demetrios A

2017-10-01

According to Professor Anne Greenough, Professor of Neonatology and Clinical Respiratory Physiology at the King's College London (London, UK), Paediatric Virology is indeed a rapidly increasing educational challenge. Professor Greenough, who in 1992 wrote her book on congenital, perinatal and neonatal infections, believes that during the past 3 decades, paediatric health professionals are becoming increasingly involved in specialised care and follow-up of paediatric patients with viral diseases, who require advanced medical care and innovative technological services. Moreover, she highlights the expected role of new vaccines and antiviral agents that are currently under investigation, as well as the impact of emerging viral diseases that require novel prevention strategies and therapeutic protocols. However, she notes that the number of Paediatric Virologists in any one country is likely to be small; hence, a separate paediatric subspecialty needs to be considered carefully. In the context of the 3rd Workshop on Paediatric Virology, which will be held in Athens, Greece, on October 7th, 2017, Professor Greenough will give her plenary lecture on the impact of viral infections on the long term outcomes of prematurely born infants.

The educational challenge of Paediatric Virology: An interview with Professor of Neonatology Anne Greenough

PubMed Central

Mammas, Ioannis N.; Spandidos, Demetrios A.

2017-01-01

According to Professor Anne Greenough, Professor of Neonatology and Clinical Respiratory Physiology at the King's College London (London, UK), Paediatric Virology is indeed a rapidly increasing educational challenge. Professor Greenough, who in 1992 wrote her book on congenital, perinatal and neonatal infections, believes that during the past 3 decades, paediatric health professionals are becoming increasingly involved in specialised care and follow-up of paediatric patients with viral diseases, who require advanced medical care and innovative technological services. Moreover, she highlights the expected role of new vaccines and antiviral agents that are currently under investigation, as well as the impact of emerging viral diseases that require novel prevention strategies and therapeutic protocols. However, she notes that the number of Paediatric Virologists in any one country is likely to be small; hence, a separate paediatric subspecialty needs to be considered carefully. In the context of the 3rd Workshop on Paediatric Virology, which will be held in Athens, Greece, on October 7th, 2017, Professor Greenough will give her plenary lecture on the impact of viral infections on the long term outcomes of prematurely born infants. PMID:29042914

Biosorption of chromium (VI) from aqueous solutions and ANN modelling.

PubMed

Nag, Soma; Mondal, Abhijit; Bar, Nirjhar; Das, Sudip Kumar

2017-08-01

The use of sustainable, green and biodegradable natural wastes for Cr(VI) detoxification from the contaminated wastewater is considered as a challenging issue. The present research is aimed to assess the effectiveness of seven different natural biomaterials, such as jackfruit leaf, mango leaf, onion peel, garlic peel, bamboo leaf, acid treated rubber leaf and coconut shell powder, for Cr(VI) eradication from aqueous solution by biosorption process. Characterizations were conducted using SEM, BET and FTIR spectroscopy. The effects of operating parameters, viz., pH, initial Cr(VI) ion concentration, adsorbent dosages, contact time and temperature on metal removal efficiency, were studied. The biosorption mechanism was described by the pseudo-second-order model and Langmuir isotherm model. The biosorption process was exothermic, spontaneous and chemical (except garlic peel) in nature. The sequence of adsorption capacity was mango leaf > jackfruit leaf > acid treated rubber leaf > onion peel > bamboo leaf > garlic peel > coconut shell with maximum Langmuir adsorption capacity of 35.7 mg g -1 for mango leaf. The treated effluent can be reused. Desorption study suggested effective reuse of the adsorbents up to three cycles, and safe disposal method of the used adsorbents suggested biodegradability and sustainability of the process by reapplication of the spent adsorbent and ultimately leading towards zero wastages. The performances of the adsorbents were verified with wastewater from electroplating industry. The scale-up study reported for industrial applications. ANN modelling using multilayer perception with gradient descent (GD) and Levenberg-Marquart (LM) algorithm had been successfully used for prediction of Cr(VI) removal efficiency. The study explores the undiscovered potential of the natural waste materials for sustainable existence of small and medium sector industries, especially in the third world countries by protecting the environment by eco-innovation.

Bennett, Bloom and Boyer: Toward a Critical Discussion.

ERIC Educational Resources Information Center

Reitz, Charles

An overview is provided of the educational philosophies of Allan Bloom, Lynne V. Cheney, William Bennett, and Ernest Boyer, with special focus on their political underpinnings. The essay begins with an examination of the issues discussed in "The Closing of the American Mind," by Allan Bloom. Concern and disagreement is expressed about:…

Radioactivities in returned lunar materials and in meteorites

NASA Technical Reports Server (NTRS)

Fireman, E. L.

1984-01-01

Carbon 14 terrestial ages were determined with low level minicomputers and accelerator mass spectrometry on 1 Yamato and 18 Allan Hills and nearby sited meteorites. Techniques for an accelerator mass spectrometer which make C(14) measurements on small samples were developed. Also Be(10) concentrations were measured in Byrd core and Allan Hills ice samples.

40th Annual Armament Systems: Guns-Ammunition-Rockets-Missiles Conference and Exhibition

DTIC Science & Technology

2005-04-28

Session: Medium Caliber System Oerlikon Ammunition for New Defense Environment, Mr. Allan N. Buckley, BTECH Oerlikon Contraves Pyrotec AG Multi...Environment Mr. Allan N. Buckley, BTECH Oerlikon Contraves Pyrotec AG Force Protection - Multi Mission Vehicle Armament & Air Burst Munition for...determine homogeneity – Propellant contains ~3% by weight of FS grains to adjust K

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

PubMed

Yu, Peigen; Low, Mei Yin; Zhou, Weibiao

2018-01-01

In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R 2 ) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R 2 (0.875) and RMSE (2.41%). Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of FrontPage 98 to the Development of Web Sites for the Science Division and the Center for the Advancement of Learning and Teaching (CALT) at Anne Arundel Community College.

ERIC Educational Resources Information Center

Bird, Bruce

This paper discusses the development of two World Wide Web sites at Anne Arundel Community College (Maryland). The criteria for the selection of hardware and software for Web site development that led to the decision to use Microsoft FrontPage 98 are described along with its major components and features. The discussion of the Science Division Web…

Optimum coagulant forecasting by modeling jar test experiments using ANNs

NASA Astrophysics Data System (ADS)

Haghiri, Sadaf; Daghighi, Amin; Moharramzadeh, Sina

2018-01-01

Currently, the proper utilization of water treatment plants and optimizing their use is of particular importance. Coagulation and flocculation in water treatment are the common ways through which the use of coagulants leads to instability of particles and the formation of larger and heavier particles, resulting in improvement of sedimentation and filtration processes. Determination of the optimum dose of such a coagulant is of particular significance. A high dose, in addition to adding costs, can cause the sediment to remain in the filtrate, a dangerous condition according to the standards, while a sub-adequate dose of coagulants can result in the reducing the required quality and acceptable performance of the coagulation process. Although jar tests are used for testing coagulants, such experiments face many constraints with respect to evaluating the results produced by sudden changes in input water because of their significant costs, long time requirements, and complex relationships among the many factors (turbidity, temperature, pH, alkalinity, etc.) that can influence the efficiency of coagulant and test results. Modeling can be used to overcome these limitations; in this research study, an artificial neural network (ANN) multi-layer perceptron (MLP) with one hidden layer has been used for modeling the jar test to determine the dosage level of used coagulant in water treatment processes. The data contained in this research have been obtained from the drinking water treatment plant located in Ardabil province in Iran. To evaluate the performance of the model, the mean squared error (MSE) and correlation coefficient (R2) parameters have been used. The obtained values are within an acceptable range that demonstrates the high accuracy of the models with respect to the estimation of water-quality characteristics and the optimal dosages of coagulants; so using these models will allow operators to not only reduce costs and time taken to perform experimental jar tests

Neuronal 3',3,5-triiodothyronine (T3) uptake and behavioral phenotype of mice deficient in Mct8, the neuronal T3 transporter mutated in Allan-Herndon-Dudley syndrome.

PubMed

Wirth, Eva K; Roth, Stephan; Blechschmidt, Cristiane; Hölter, Sabine M; Becker, Lore; Racz, Ildiko; Zimmer, Andreas; Klopstock, Thomas; Gailus-Durner, Valerie; Fuchs, Helmut; Wurst, Wolfgang; Naumann, Thomas; Bräuer, Anja; de Angelis, Martin Hrabé; Köhrle, Josef; Grüters, Annette; Schweizer, Ulrich

2009-07-29

Thyroid hormone transport into cells requires plasma membrane transport proteins. Mutations in one of these, monocarboxylate transporter 8 (MCT8), have been identified as underlying cause for the Allan-Herndon-Dudley syndrome, an X-linked mental retardation in which the patients also present with abnormally high 3',3,5-triiodothyronine (T(3)) plasma levels. Mice deficient in Mct8 replicate the thyroid hormone abnormalities observed in the human condition. However, no neurological deficits have been described in mice lacking Mct8. Therefore, we subjected Mct8-deficient mice to a comprehensive immunohistochemical, neurological, and behavioral screen. Several behavioral abnormalities were found in the mutants. Interestingly, some of these behavioral changes are compatible with hypothyroidism, whereas others rather indicate hyperthyroidism. We thus hypothesized that neurons exclusively dependent on Mct8 are in a hypothyroid state, whereas neurons expressing other T(3) transporters become hyperthyroid, if they are exposed directly to the high plasma T(3). The majority of T(3) uptake in primary cortical neurons is mediated by Mct8, but pharmacological inhibition suggested functional expression of additional T(3) transporter classes. mRNAs encoding six T(3) transporters, including L-type amino acid transporters (LATs), were coexpressed with Mct8 in isolated neurons. We then demonstrated Lat2 expression in cultured neurons and throughout murine brain development. In contrast, LAT2 is expressed in microglia in the developing human brain during gestation, but not in neurons. We suggest that lack of functional complementation by alternative thyroid hormone transporters in developing human neurons precipitates the devastating neurodevelopmental phenotype in MCT8-deficient patients, whereas Mct8-deficient mouse neurons are functionally complemented by other transporters, for possibly Lat2.

Antarctic Meteorite Location Map Series

NASA Technical Reports Server (NTRS)

Schutt, John (Editor); Fessler, Brian (Editor); Cassidy, William (Editor)

1989-01-01

Antarctica has been a prolific source of meteorites since meteorite concentrations were discovered in 1969. The Antarctic Search For Meteorites (ANSMET) project has been active over much of the Trans-Antarctic Mountain Range. The first ANSMET expedition (a joint U.S.-Japanese effort) discovered what turned out to be a significant concentration of meteorites at the Allan Hills in Victoria Land. Later reconnaissance in this region resulted in the discovery of meteorite concentrations on icefields to the west of the Allan Hills, at Reckling Moraine, and Elephant Moraine. Antarctic meteorite location maps (reduced versions) of the Allan Hills main, near western, middle western, and far western icefields and the Elephant Moraine icefield are presented. Other Antarctic meteorite location maps for the specimens found by the ANSMET project are being prepared.

Gaydar, Marriage, and Rip-Roaring Homosexuals: Discourses About Homosexuality in Dear Abby and Ann Landers Advice Columns, 1967-1982.

PubMed

Johnson, Patrick M; Holmes, Kwame A

2017-12-04

Over the past 70 years, the history of acceptance of the lesbian, gay and bisexual (LGB) community within the United States has seen much change and fluctuation. One of the places that this dialogue has been preserved is through the syndicated advice columns of Dear Abby and Ann Landers, in which individuals in the United States were writing in for advice to deal with their anxiety over a newly emerging and highly visible new community of individuals once considered to be mentally ill and dangerous. Using discourse analysis, this article traces the evolution of public and scientific opinions about the LGBT community during the years leading up to the Stonewall riots all the way to right before the AIDs epidemic. This analysis sheds light on several moral panics that emerged regarding this newly visible population, especially in regard to disturbances within the domestic sphere and a stigmatization of bisexuality.

The Problem of Disobedience and the Intelligence Community

DTIC Science & Technology

1990-06-01

focus on the technological and analytical aspects of the profession. Despite some highly successful but less-than- savory operations in the past,3 there... Allan Bloom, The Closing of the American Mind (New York: Simon & Schuster, 1987), p. 26. 23. Thomas B. Allen and Norman Polmar, Merchants of Treason...Waldo Emerson. New York: Modern Library, 1940. Bloom, Allan . The Closing of the American Mind. New York: Simon & Schuster, 1942. Carter, Jimmy

Artificial neural network (ANN) method for modeling of sunset yellow dye adsorption using zinc oxide nanorods loaded on activated carbon: Kinetic and isotherm study.

PubMed

Maghsoudi, M; Ghaedi, M; Zinali, A; Ghaedi, A M; Habibi, M H

2015-01-05

In this research, ZnO nanoparticle loaded on activated carbon (ZnO-NPs-AC) was synthesized simply by a low cost and nontoxic procedure. The characterization and identification have been completed by different techniques such as SEM and XRD analysis. A three layer artificial neural network (ANN) model is applicable for accurate prediction of dye removal percentage from aqueous solution by ZnO-NRs-AC following conduction of 270 experimental data. The network was trained using the obtained experimental data at optimum pH with different ZnO-NRs-AC amount (0.005-0.015 g) and 5-40 mg/L of sunset yellow dye over contact time of 0.5-30 min. The ANN model was applied for prediction of the removal percentage of present systems with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 6 neurons. The minimum mean squared error (MSE) of 0.0008 and coefficient of determination (R(2)) of 0.998 were found for prediction and modeling of SY removal. The influence of parameters including adsorbent amount, initial dye concentration, pH and contact time on sunset yellow (SY) removal percentage were investigated and optimal experimental conditions were ascertained. Optimal conditions were set as follows: pH, 2.0; 10 min contact time; an adsorbent dose of 0.015 g. Equilibrium data fitted truly with the Langmuir model with maximum adsorption capacity of 142.85 mg/g for 0.005 g adsorbent. The adsorption of sunset yellow followed the pseudo-second-order rate equation. Copyright © 2014 Elsevier B.V. All rights reserved.

Artificial neural network (ANN) method for modeling of sunset yellow dye adsorption using zinc oxide nanorods loaded on activated carbon: Kinetic and isotherm study

NASA Astrophysics Data System (ADS)

Maghsoudi, M.; Ghaedi, M.; Zinali, A.; Ghaedi, A. M.; Habibi, M. H.

2015-01-01

In this research, ZnO nanoparticle loaded on activated carbon (ZnO-NPs-AC) was synthesized simply by a low cost and nontoxic procedure. The characterization and identification have been completed by different techniques such as SEM and XRD analysis. A three layer artificial neural network (ANN) model is applicable for accurate prediction of dye removal percentage from aqueous solution by ZnO-NRs-AC following conduction of 270 experimental data. The network was trained using the obtained experimental data at optimum pH with different ZnO-NRs-AC amount (0.005-0.015 g) and 5-40 mg/L of sunset yellow dye over contact time of 0.5-30 min. The ANN model was applied for prediction of the removal percentage of present systems with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 6 neurons. The minimum mean squared error (MSE) of 0.0008 and coefficient of determination (R2) of 0.998 were found for prediction and modeling of SY removal. The influence of parameters including adsorbent amount, initial dye concentration, pH and contact time on sunset yellow (SY) removal percentage were investigated and optimal experimental conditions were ascertained. Optimal conditions were set as follows: pH, 2.0; 10 min contact time; an adsorbent dose of 0.015 g. Equilibrium data fitted truly with the Langmuir model with maximum adsorption capacity of 142.85 mg/g for 0.005 g adsorbent. The adsorption of sunset yellow followed the pseudo-second-order rate equation.

Temperature variation effects on stochastic characteristics for low-cost MEMS-based inertial sensor error

NASA Astrophysics Data System (ADS)

El-Diasty, M.; El-Rabbany, A.; Pagiatakis, S.

2007-11-01

We examine the effect of varying the temperature points on MEMS inertial sensors' noise models using Allan variance and least-squares spectral analysis (LSSA). Allan variance is a method of representing root-mean-square random drift error as a function of averaging times. LSSA is an alternative to the classical Fourier methods and has been applied successfully by a number of researchers in the study of the noise characteristics of experimental series. Static data sets are collected at different temperature points using two MEMS-based IMUs, namely MotionPakII and Crossbow AHRS300CC. The performance of the two MEMS inertial sensors is predicted from the Allan variance estimation results at different temperature points and the LSSA is used to study the noise characteristics and define the sensors' stochastic model parameters. It is shown that the stochastic characteristics of MEMS-based inertial sensors can be identified using Allan variance estimation and LSSA and the sensors' stochastic model parameters are temperature dependent. Also, the Kaiser window FIR low-pass filter is used to investigate the effect of de-noising stage on the stochastic model. It is shown that the stochastic model is also dependent on the chosen cut-off frequency.

Quality of water in the White River and Lake Tapps, Pierce County, Washington, May-December 2010

USGS Publications Warehouse

Embrey, S.S.; Wagner, R.J.; Huffman, R.L.; Vanderpool-Kimura, A. M.; Foreman, J.R.

2012-01-01

Water samples collected at the Allan Yorke, Snag Island, and Lake Outlet study sites were screened for the presence of more than 250 organic chemicals. A total of 14 compounds were detected in trace amounts (or determined to be present) at one or more of the 3 sites. The Allan Yorke site had 9 detections, the Snag Island site had 10 detections, and the Lake Outlet site had 5 detections of compounds mostly belonging to the group of wastewater indicator chemicals. Compounds detected (or with verified presence) at all three sites included the herbicide 2,4-D, the insecticide and mosquito repellant DEET, the herbicide fluridone used for Eurasian watermilfoil eradication, and the herbicide prometon. The largest concentrations of these compounds were in samples from the Allan Yorke site; the lowest concentrations were from the Lake Outlet site.

MHD memes

NASA Astrophysics Data System (ADS)

Dewar, R. L.; Mills, R.; Hole, M. J.

2009-05-01

The celebration of Allan Kaufman's 80th birthday was an occasion to reflect on a career that has stimulated the mutual exchange of ideas (or memes in the terminology of Richard Dawkins) between many researchers. This paper will revisit a meme Allan encountered in his early career in magnetohydrodynamics, the continuation of a magnetohydrodynamic mode through a singularity, and will also mention other problems where Allan's work has had a powerful cross-fertilizing effect in plasma physics and other areas of physics and mathematics. To resolve the continuation problem we regularize the Newcomb equation, solve it in terms of Legendre functions of imaginary argument, and define the small weak solutions of the Newcomb equation as generalized functions in the manner of Lighthill, i.e. via a limiting sequence of analytic functions that connect smoothly across the singularity.

Army Transformaton: A View from the U.S. Army War College

DTIC Science & Technology

2001-07-01

military, see particularly Allan R. Millett, The General: Robert L . Bullard and Officership in the United States Army, 1881-1925, Westport, CT: Greenwood...Westport, CT: Greenwood, 1986, p. 182. 2. Captain Carl Reichman, “In Pace Para Bellum,” Infantry Journal, Vol. II, January 1906, p. 5, quoted in James L ...United States Army, enlarged edition, Bloomington: Indiana University Press, 1984, pp. 265-354; Allan R. Millett, The General: Robert L . Bullard and

A novel and generalized approach in the inversion of geoelectrical resistivity data using Artificial Neural Networks (ANN)

NASA Astrophysics Data System (ADS)

Raj, A. Stanley; Srinivas, Y.; Oliver, D. Hudson; Muthuraj, D.

2014-03-01

The non-linear apparent resistivity problem in the subsurface study of the earth takes into account the model parameters in terms of resistivity and thickness of individual subsurface layers using the trained synthetic data by means of Artificial Neural Networks (ANN). Here we used a single layer feed-forward neural network with fast back propagation learning algorithm. So on proper training of back propagation networks it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data with reference to the synthetic data trained in the appropriate network. During training, the weights and biases of the network are iteratively adjusted to make network performance function level more efficient. On adequate training, errors are minimized and the best result is obtained using the artificial neural networks. The network is trained with more number of VES data and this trained network is demonstrated by the field data. The accuracy of inversion depends upon the number of data trained. In this novel and specially designed algorithm, the interpretation of the vertical electrical sounding has been done successfully with the more accurate layer model.

The Anne Frank Haven: A case of an alternative educational program in an integrative Kibbutz setting

NASA Astrophysics Data System (ADS)

Ben-Peretz, Miriam; Giladi, Moshe; Dror, Yuval

1992-01-01

The essential features of the programme of the Anne Frank Haven are the complete integration of children from low SES and different cultural backgrounds with Kibbutz children; a holistic approach to education; and the involvement of the whole community in an "open" residential school. After 33 years, it is argued that the experiment has proved successful in absorbing city-born youth in the Kibbutz, enabling at-risk populations to reach significant academic achievements, and ensuring their continued participation in the dominant culture. The basic integration model consists of "layers" of concentric circles, in dynamic interaction. The innermost circle is the class, the learning community. The Kibbutz community and the foster parents form a supportive, enveloping circle, which enables students to become part of the outer community and to intervene in it. A kind of meta-environment, the inter-Kibbutz partnership and the Israeli educational system, influence the program through decision making and guidance. Some of the principles of the Haven — integration, community involvement, a year's induction for all new students, and open residential settings — could be useful for cultures and societies outside the Kibbutz. The real "secret" of success of an alternative educational program is the dedicated, motivated and highly trained staff.

Hourly predictive Levenberg-Marquardt ANN and multi linear regression models for predicting of dew point temperature

NASA Astrophysics Data System (ADS)

Zounemat-Kermani, Mohammad

2012-08-01

In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.

50 Div in Normandy: A Critical Analysis of the British 50th (Northumbrian) Division on D-Day and in the Battle of Normandy

DTIC Science & Technology

2007-12-14

University Press, 1997), 90-92. 5House, 47-48. 6Kier, 89-90. 7Brian Bond and Williamson Murray, The British Armed Forces, 1918-39 in Allan R. Millet ...Figure 5. The German Defenses on June 6, 1944. nage, Jean -Pierre Benamou, BSource: Georges Ber ernard Crochet, François de Lannoy, Laurent Mari, and...Murray, “British Military Effectiveness in the Second World War” Military Effectiveness, Vol. 3, ed. Allan R. Millet and Williamson Murray (Boston

DSN system performance test Doppler noise models; noncoherent configuration

NASA Technical Reports Server (NTRS)

Bunce, R.

1977-01-01

The newer model for variance, the Allan technique, now adopted for testing, is analyzed in the subject mode. A model is generated (including considerable contribution from the station secondary frequency standard), and rationalized with existing data. The variance model is definitely sound; the Allan technique mates theory and measure. The mean-frequency model is an estimate; this problem is yet to be rigorously resolved. The unaltered defining expressions are noncovergent, and the observed mean is quite erratic.

Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

PubMed

Verma, Rajeshwar P; Matthews, Edwin J

2015-03-01

This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of hazard identification and labeling of industrial and consumer products to ensure occupational and consumer safety. There is an urgent need to develop an alternative to the Draize test because EU's 7th amendment to the Cosmetic Directive (EC, 2003; 76/768/EEC) and recast Regulation now bans animal testing on all cosmetic product ingredients and EU's REACH Program limits animal testing for chemicals in commerce. Although in silico methods have been reported for eye irritation (reversible damage), QSARs specific for eye corrosion (irreversible damage) have not been published. This report describes the development of 21 ANN c-QSAR models (QSAR-21) for assessing eye corrosion potential of chemicals using a large and diverse CFSAN data set of 504 chemicals, ADMET Predictor's three sensitivity analyses and ANNE classification functionalities with 20% test set selection from seven different methods. QSAR-21 models were internally and externally validated and exhibited high predictive performance: average statistics for the training, verification, and external test sets of these models were 96/96/94% sensitivity and 91/91/90% specificity. Copyright © 2014 Elsevier Inc. All rights reserved.

3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

NASA Astrophysics Data System (ADS)

Saeed, R. A.; Galybin, A. N.; Popov, V.

2013-01-01

This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

Autonomous cryogenic sapphire oscillators employing low vibration pulse-tube cryocoolers at NMIJ

NASA Astrophysics Data System (ADS)

Ikegami, Takeshi; Watabe, Ken-ichi; Yanagimachi, Shinya; Takamizawa, Akifumi; Hartnett, John G.

2016-06-01

Two liquid-helium-cooled cryogenic sapphire-resonator oscillators (CSOs), have been modified to operate using cryo-refrigerators and low-vibration cryostats. The Allan deviation of the first CSO was evaluated to be better than 2 x 10-15 for averaging times of 1 s to 30 000 s, which is better than that of the original liquid helium cooled CSO. The Allan deviation of the second CSO is better than 4 x 10-15 from 1 s to 6 000 s averaging time.

Waking the Sleeping Giant at Pearl Harbor: A Case for Intelligence and Operations Fusion

DTIC Science & Technology

2013-05-23

York: Random House Inc., 2002), 7. 9Allan R. Millet and Peter Maslowski, For the Common Defense A Military History of the United States of America...the complexity of a major war.”40 37Keegan, Intelligence in War, 188-89. 38Ball, Of Responsible Command, 189; Allan R. Millet & Peter Maslowski...65Gole, The Road to Rainbow, 114; Miller, War Plan Orange, 270; Millet and Maslowski, For the Common Defense, 418; Ross, U.S. War Plans 1938-1945, 55

Preliminary Analysis of the efficacy of Artificial neural Network (ANN) and Cellular Automaton (CA) based Land Use Models in Urban Land-Use Planning

NASA Astrophysics Data System (ADS)

Harun, R.

2013-05-01

This research provides an opportunity of collaboration between urban planners and modellers by providing a clear theoretical foundations on the two most widely used urban land use models, and assessing the effectiveness of applying the models in urban planning context. Understanding urban land cover change is an essential element for sustainable urban development as it affects ecological functioning in urban ecosystem. Rapid urbanization due to growing inclination of people to settle in urban areas has increased the complexities in predicting that at what shape and size cities will grow. The dynamic changes in the spatial pattern of urban landscapes has exposed the policy makers and environmental scientists to great challenge. But geographic science has grown in symmetry to the advancements in computer science. Models and tools are developed to support urban planning by analyzing the causes and consequences of land use changes and project the future. Of all the different types of land use models available in recent days, it has been found by researchers that the most frequently used models are Cellular Automaton (CA) and Artificial Neural Networks (ANN) models. But studies have demonstrated that the existing land use models have not been able to meet the needs of planners and policy makers. There are two primary causes identified behind this prologue. First, there is inadequate understanding of the fundamental theories and application of the models in urban planning context i.e., there is a gap in communication between modellers and urban planners. Second, the existing models exclude many key drivers in the process of simplification of the complex urban system that guide urban spatial pattern. Thus the models end up being effective in assessing the impacts of certain land use policies, but cannot contribute in new policy formulation. This paper is an attempt to increase the knowledge base of planners on the most frequently used land use model and also assess the

Evaluation of Effect of Postoperative Wound Drainage Reinfusion Using the Solcotrans Orthopaedic Drainage/Reinfusion System in Reducing the Need for Whole Blood Transfusion (HSC)

DTIC Science & Technology

1991-03-01

REINFUSION SYSTEM IN REDUCING THE NEED FOR WHOLE BLOOD TRANSFUSION (HSC) PRINCIPAL INVESTIGATOR: Allan L. Bucknell, M.D. AUTHORS: Michael B. Simpson, M.D...einfysion SVt8T in Reducing the Need for whole Blood rans uson , 61102A Allan L. Bucknell, M.D.; Michael B. Simpson, M.D. 3MI61102BS12.ZZ Kevin P...for transfusion. J Bone Joint Suig. 1987; 6,QA:319). 3. Tlhomson JD), C al laghan JJ, Savory C’G, Stanton RP, Pierce RN. P’rior deposition of

The Effects of Laser Phase Noise on Laser Radar Performance

DTIC Science & Technology

1992-12-01

Laboratory 5. Figure 3 shows Allan variance plots of the above ultrastable C02 laser which has an open Fabry - Perot cavity 5. The open and solid circles...the same measurement time -r) by more than 10 dB. Therefore, the root Allan variance for the Fabry - Perot cavity ultrastable C02 laser can be...variance so that the SSB phase noise for the Fabry - Perot cavity ultrastable CO 2 laser is about 20 dB (because of the squaring operation) below that of the

Maps and seismic profiles showing geology of the inner continental shelf, Cape Ann, Massachusetts to New Hampshire

USGS Publications Warehouse

Oldale, R.N.; Wommack, L.E.

1987-01-01

Early studies in the western Gulf of Maine have outlined the general geology and geologic history of the region. Seismic-reflection data have defined the major stratigraphic units and unconformities (Oldale and Uchupi, 1970; Ballard and Uchupi, 1972; Oldale and others, 1973). Two long cores provided information on the glacial and postglacial sediments in the deep offshore basins (Tucholke and Hollister, 1973). Generalized bottom-sediment type and distribution were determined by Schlee and others (1973) and by Folger and others (1975). Investigations on land, which have provided information on the late Quaternary history of the offshore area, include descriptions of ice retreat and marine submergence (Bloom, 1963; Smith, 1982; Stone and Peper, 1982; Thompson, 1982). Radiocarbon dates from coastal marsh peats have established the middle to late Holocene sea-level-rise history (McIntire and Morgan, 1964; Keene, 1971). Submarine moraincs that recently were recognized off Cape Ann provide additional information on the nature and chronology of ice retreat (Oldale, 1985a). A submerged delta of the Merrimack River and a submerged barrier spit have been used to establish an early IIolocene lowstand of 588 level of about 50 meters (m) below present sea level (Oldale and others, 1983; Oldale, 1985b).

Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

PubMed

Verma, Rajeshwar P; Matthews, Edwin J

2015-03-01

Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Amendment to the Cosmetic Directive (76/768/EEC) and recast Regulation now bans marketing of new cosmetics having animal testing of their ingredients and requires non-animal alternative tests for safety assessments. Thus, in silico and/or in vitro tests are advocated. QSAR models for eye irritation have been reported for several small (congeneric) data sets; however, large global models have not been described. This report describes FDA/CFSAN's development of 21 ANN c-QSAR models (QSAR-21) to predict eye irritation using the ADMET Predictor program and a diverse training data set of 2928 chemicals. The 21 models had external (20% test set) and internal validation and average training/verification/test set statistics were: 88/88/85(%) sensitivity and 82/82/82(%) specificity, respectively. The new method utilized multiple artificial neural network (ANN) molecular descriptor selection functionalities to maximize the applicability domain of the battery. The eye irritation models will be used to provide information to fill the critical data gaps for the safety assessment of cosmetic ingredient chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh.

PubMed

Rahman, M Tauhid Ur; Tabassum, Faheemah; Rasheduzzaman, Md; Saba, Humayra; Sarkar, Lina; Ferdous, Jannatul; Uddin, Syed Zia; Zahedul Islam, A Z M

2017-10-17

Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. "Bare lands" decreased by 21% being occupied by other land uses, especially by "shrimp farms." Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in "settlement" area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy

Psychophysics of associative learning: Quantitative properties of subjective contingency.

PubMed

Maia, Susana; Lefèvre, Françoise; Jozefowiez, Jérémie

2018-01-01

Allan and collaborators (Allan, Hannah, Crump, & Siegel, 2008; Allan, Siegel, & Tangen, 2005; Siegel, Allan, Hannah, & Crump, 2009) recently proposed to apply signal detection theory to the analysis of contingency judgment tasks. When exposed to a flow of stimuli, participants are asked to judge whether there is a contingent relation between a cue and an outcome, that is, whether the subjective cue-outcome contingency exceeds a decision threshold. In this context, we tested the following hypotheses regarding the relation between objective and subjective cue-outcome contingency: (a) The underlying distributions of subjective cue-outcome contingency are Gaussian; (b) The mean distribution of subjective contingency is a linear function of objective cue-outcome contingency; and (c) The variance in the distribution of subjective contingency is constant. The hypotheses were tested by combining a streamed-trial contingency assessment task with a confidence rating procedure. Participants were exposed to rapid flows of stimuli at the end of which they had to judge whether an outcome was more (Experiment 1) or less (Experiment 2) likely to appear following a cue and how sure they were of their judgment. We found that although Hypothesis A seems reasonable, Hypotheses B and C were not. Regarding Hypothesis B, participants were more sensitive to positive than to negative contingencies. Regarding Hypothesis C, the perceived cue-outcome contingency became more variable when the contingency became more positive or negative, but only to a slight extent. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

AI-based (ANN and SVM) statistical downscaling methods for precipitation estimation under climate change scenarios

NASA Astrophysics Data System (ADS)

Mehrvand, Masoud; Baghanam, Aida Hosseini; Razzaghzadeh, Zahra; Nourani, Vahid

2017-04-01

Since statistical downscaling methods are the most largely used models to study hydrologic impact studies under climate change scenarios, nonlinear regression models known as Artificial Intelligence (AI)-based models such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been used to spatially downscale the precipitation outputs of Global Climate Models (GCMs). The study has been carried out using GCM and station data over GCM grid points located around the Peace-Tampa Bay watershed weather stations. Before downscaling with AI-based model, correlation coefficient values have been computed between a few selected large-scale predictor variables and local scale predictands to select the most effective predictors. The selected predictors are then assessed considering grid location for the site in question. In order to increase AI-based downscaling model accuracy pre-processing has been developed on precipitation time series. In this way, the precipitation data derived from various GCM data analyzed thoroughly to find the highest value of correlation coefficient between GCM-based historical data and station precipitation data. Both GCM and station precipitation time series have been assessed by comparing mean and variances over specific intervals. Results indicated that there is similar trend between GCM and station precipitation data; however station data has non-stationary time series while GCM data does not. Finally AI-based downscaling model have been applied to several GCMs with selected predictors by targeting local precipitation time series as predictand. The consequences of recent step have been used to produce multiple ensembles of downscaled AI-based models.

Leaf Treatments with a Protein-Based Resistance Inducer Partially Modify Phyllosphere Microbial Communities of Grapevine

PubMed Central

Cappelletti, Martina; Perazzolli, Michele; Antonielli, Livio; Nesler, Andrea; Torboli, Esmeralda; Bianchedi, Pier L.; Pindo, Massimo; Puopolo, Gerardo; Pertot, Ilaria

2016-01-01

Protein derivatives and carbohydrates can stimulate plant growth, increase stress tolerance, and activate plant defense mechanisms. However, these molecules can also act as a nutritional substrate for microbial communities living on the plant phyllosphere and possibly affect their biocontrol activity against pathogens. We investigated the mechanisms of action of a protein derivative (nutrient broth, NB) against grapevine downy mildew, specifically focusing on the effects of foliar treatments on plant defense stimulation and on the composition and biocontrol features of the phyllosphere microbial populations. NB reduced downy mildew symptoms and induced the expression of defense-related genes in greenhouse- and in vitro-grown plants, indicating the activation of grapevine resistance mechanisms. Furthermore, NB increased the number of culturable phyllosphere bacteria and altered the composition of bacterial and fungal populations on leaves of greenhouse-grown plants. Although, NB-induced changes on microbial populations were affected by the structure of indigenous communities originally residing on grapevine leaves, degrees of disease reduction and defense gene modulation were consistent among the experiments. Thus, modifications in the structure of phyllosphere populations caused by NB application could partially contribute to downy mildew control by competition for space or other biocontrol strategies. Particularly, changes in the abundance of phyllosphere microorganisms may provide a contribution to resistance induction, partially affecting the hormone-mediated signaling pathways involved. Modifying phyllosphere populations by increasing natural biocontrol agents with the application of selected nutritional factors can open new opportunities in terms of sustainable plant protection strategies. PMID:27486468