Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

NASA Astrophysics Data System (ADS)

Canas, Liane S.; Yvernault, Benjamin; Cash, David M.; Molteni, Erika; Veale, Tom; Benzinger, Tammie; Ourselin, Sébastien; Mead, Simon; Modat, Marc

2018-02-01

Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome this limitation, we propose a framework to identify the optimal covariance kernel function to model the data.The optimal kernel is defined as a composition of base kernel functions used to identify correlation patterns between data points. Our approach includes a modified version of the Compositional Kernel Learning (CKL) algorithm, in which we score the kernel families using a new energy function that depends both the Bayesian Information Criterion (BIC) and the explained variance score. We applied the proposed framework to model the progression of neurodegenerative diseases over time, in particular the progression of autosomal dominantly-inherited Alzheimer's disease, and use it to predict the time to clinical onset of subjects carrying genetic mutation.

Automatic classification of retinal three-dimensional optical coherence tomography images using principal component analysis network with composite kernels.

PubMed

Fang, Leyuan; Wang, Chong; Li, Shutao; Yan, Jun; Chen, Xiangdong; Rabbani, Hossein

2017-11-01

We present an automatic method, termed as the principal component analysis network with composite kernel (PCANet-CK), for the classification of three-dimensional (3-D) retinal optical coherence tomography (OCT) images. Specifically, the proposed PCANet-CK method first utilizes the PCANet to automatically learn features from each B-scan of the 3-D retinal OCT images. Then, multiple kernels are separately applied to a set of very important features of the B-scans and these kernels are fused together, which can jointly exploit the correlations among features of the 3-D OCT images. Finally, the fused (composite) kernel is incorporated into an extreme learning machine for the OCT image classification. We tested our proposed algorithm on two real 3-D spectral domain OCT (SD-OCT) datasets (of normal subjects and subjects with the macular edema and age-related macular degeneration), which demonstrated its effectiveness. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Fruit position within the canopy affects kernel lipid composition of hazelnuts.

PubMed

Pannico, Antonio; Cirillo, Chiara; Giaccone, Matteo; Scognamiglio, Pasquale; Romano, Raffaele; Caporaso, Nicola; Sacchi, Raffaele; Basile, Boris

2017-11-01

The aim of this research was to study the variability in kernel composition within the canopy of hazelnut trees. Kernel fresh and dry weight increased linearly with fruit height above the ground. Fat content decreased, while protein and ash content increased, from the bottom to the top layers of the canopy. The level of unsaturation of fatty acids decreased from the bottom to the top of the canopy. Thus, the kernels located in the bottom layers of the canopy appear to be more interesting from a nutritional point of view, but their lipids may be more exposed to oxidation. The content of different phytosterols increased progressively from bottom to top canopy layers. Most of these effects correlated with the pattern in light distribution inside the canopy. The results of this study indicate that fruit position within the canopy is an important factor in determining hazelnut kernel growth and composition. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Searching Remote Homology with Spectral Clustering with Symmetry in Neighborhood Cluster Kernels

PubMed Central

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of “recent” paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. Contact: sarkar@labri.fr. PMID:23457439

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

PubMed

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. sarkar@labri.fr.

ELECTRON PROBE MICROANALYSIS OF IRRADIATED AND 1600°C SAFETY-TESTED AGR-1 TRISO FUEL PARTICLES WITH LOW AND HIGH RETAINED 110MAG

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

Wright, Karen E.; van Rooyen, Isabella J.

2016-11-01

AGR-1 fuel Compact 4-3-3 achieved 18.63% FIMA and was exposed subsequently to a safety test at 1600°C. Two particles, AGR1-433-003 and AGR1-433-007, with measured-to-calculated 110mAg inventories of <22% and 100%, respectively, were selected for comparative electron microprobe analysis to determine whether the distribution or abundance of fission products differed proximally and distally from the deformed kernel in AGR1-433-003, and how this compared to fission product distribution in AGR1-433-007. On the deformed side of AGR1-433-003, Xe, Cs, I, Eu, Sr, and Te concentrations in the kernel buffer interface near the protruded kernel were up to six times higher than on themore » opposite, non-deformed side. At the SiC-inner pyrolytic carbon (IPyC) interface proximal to the deformed kernel, Pd and Ag concentrations were 1.2 wt% and 0.04 wt% respectively, whereas on the SiC-IPyC interface distal from the kernel deformation those elements measured 0.4 and 0.01 wt%, respectively. Palladium and Ag concentrations at the SiC-IPyC interface of AGR1-433-007 were 2.05 and 0.05 wt.%, respectively. Rare earth element concentrations at the SiC-IPyC interface of AGR1-433-007 were a factor of ten higher than at the SiC-IPyC interfaces measured in particle AGR1-433-003. Palladium permeated the SiC layer of AGR1-433-007 and the non-deformed SiC layer of AGR1-433-003.« less

Optimization method of superpixel analysis for multi-contrast Jones matrix tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Miyazawa, Arata; Hong, Young-Joo; Makita, Shuichi; Kasaragod, Deepa K.; Miura, Masahiro; Yasuno, Yoshiaki

2017-02-01

Local statistics are widely utilized for quantification and image processing of OCT. For example, local mean is used to reduce speckle, local variation of polarization state (degree-of-polarization-uniformity (DOPU)) is used to visualize melanin. Conventionally, these statistics are calculated in a rectangle kernel whose size is uniform over the image. However, the fixed size and shape of the kernel result in a tradeoff between image sharpness and statistical accuracy. Superpixel is a cluster of pixels which is generated by grouping image pixels based on the spatial proximity and similarity of signal values. Superpixels have variant size and flexible shapes which preserve the tissue structure. Here we demonstrate a new superpixel method which is tailored for multifunctional Jones matrix OCT (JM-OCT). This new method forms the superpixels by clustering image pixels in a 6-dimensional (6-D) feature space (spatial two dimensions and four dimensions of optical features). All image pixels were clustered based on their spatial proximity and optical feature similarity. The optical features are scattering, OCT-A, birefringence and DOPU. The method is applied to retinal OCT. Generated superpixels preserve the tissue structures such as retinal layers, sclera, vessels, and retinal pigment epithelium. Hence, superpixel can be utilized as a local statistics kernel which would be more suitable than a uniform rectangle kernel. Superpixelized image also can be used for further image processing and analysis. Since it reduces the number of pixels to be analyzed, it reduce the computational cost of such image processing.

Nature and composition of fat bloom from palm kernel stearin and hydrogenated palm kernel stearin compound chocolates.

PubMed

Smith, Kevin W; Cain, Fred W; Talbot, Geoff

2004-08-25

Palm kernel stearin and hydrogenated palm kernel stearin can be used to prepare compound chocolate bars or coatings. The objective of this study was to characterize the chemical composition, polymorphism, and melting behavior of the bloom that develops on bars of compound chocolate prepared using these fats. Bars were stored for 1 year at 15, 20, or 25 degrees C. At 15 and 20 degrees C the bloom was enriched in cocoa butter triacylglycerols, with respect to the main fat phase, whereas at 25 degrees C the enrichment was with palm kernel triacylglycerols. The bloom consisted principally of solid fat and was sharper melting than was the fat in the chocolate. Polymorphic transitions from the initial beta' phase to the beta phase accompanied the formation of bloom at all temperatures.

Tocochromanols composition in kernels recovered from different apricot varieties: RP-HPLC/FLD and RP-UPLC-ESI/MS(n) study.

PubMed

Górnaś, Paweł; Mišina, Inga; Grāvīte, Ilze; Soliven, Arianne; Kaufmane, Edīte; Segliņa, Dalija

2015-01-01

Composition of tocochromanols in kernels recovered from 16 different apricot varieties (Prunus armeniaca L.) was studied. Three tocopherol (T) homologues, namely α, γ and δ, were quantified in all tested samples by an RP-HPLC/FLD method. The γ-T was the main tocopherol homologue identified in apricot kernels and constituted approximately 93% of total detected tocopherols. The RP-UPLC-ESI/MS(n) method detected trace amounts of two tocotrienol homologues α and γ in the apricot kernels. The concentration of individual tocopherol homologues in kernels of different apricots varieties, expressed in mg/100 g dwb, was in the following range: 1.38-4.41 (α-T), 42.48-73.27 (γ-T) and 0.77-2.09 (δ-T). Moreover, the ratio between individual tocopherol homologues α:γ:δ was nearly constant in all varieties and amounted to approximately 2:39:1.

Characterisation of agroindustrial solid residues as biofuels and potential application in thermochemical processes.

PubMed

Virmond, Elaine; De Sena, Rennio F; Albrecht, Waldir; Althoff, Christine A; Moreira, Regina F P M; José, Humberto J

2012-10-01

In the present work, selected agroindustrial solid residues from Brazil - biosolids from meat processing wastewater treatment and mixture of sawdust with these biosolids; residues from apple and orange juice industries; sugarcane bagasse; açaí kernels (Euterpe oleracea) and rice husk - were characterised as solid fuels and an evaluation of their properties, including proximate and ultimate composition, energy content, thermal behaviour, composition and fusibility of the ashes was performed. The lower heating value of the biomasses ranged from 14.31 MJkg(-1) to 29.14 MJkg(-1), on a dry and ash free basis (daf), all presenting high volatile matter content, varying between 70.57 wt.% and 85.36 wt.% (daf) what improves the thermochemical conversion of the solids. The fouling and slagging tendency of the ashes was predicted based on the fuel ash composition and on the ash fusibility correlations proposed in the literature, which is important to the project and operation of biomass conversion systems. The potential for application of the Brazilian agroindustrial solid residues studied as alternative energy sources in thermochemical processes has been identified, especially concerning direct combustion for steam generation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparative Lipidomics and Proteomics of Lipid Droplets in the Mesocarp and Seed Tissues of Chinese Tallow (Triadica sebifera)

PubMed Central

Zhi, Yao; Taylor, Matthew C.; Campbell, Peter M.; Warden, Andrew C.; Shrestha, Pushkar; El Tahchy, Anna; Rolland, Vivien; Vanhercke, Thomas; Petrie, James R.; White, Rosemary G.; Chen, Wenli; Singh, Surinder P.; Liu, Qing

2017-01-01

Lipid droplets (LDs) are composed of a monolayer of phospholipids (PLs), surrounding a core of non-polar lipids that consist mostly of triacylglycerols (TAGs) and to a lesser extent diacylglycerols. In this study, lipidome analysis illustrated striking differences in non-polar lipids and PL species between LDs derived from Triadica sebifera seed kernels and mesocarp. In mesocarp LDs, the most abundant species of TAG contained one C18:1 and two C16:0 and fatty acids, while TAGs containing three C18 fatty acids with higher level of unsaturation were dominant in the seed kernel LDs. This reflects the distinct differences in fatty acid composition of mesocarp (palmitate-rich) and seed-derived oil (α-linoleneate-rich) in T. sebifera. Major PLs in seed LDs were found to be rich in polyunsaturated fatty acids, in contrast to those with relatively shorter carbon chain and lower level of unsaturation in mesocarp LDs. The LD proteome analysis in T. sebifera identified 207 proteins from mesocarp, and 54 proteins from seed kernel, which belong to various functional classes including lipid metabolism, transcription and translation, trafficking and transport, cytoskeleton, chaperones, and signal transduction. Oleosin and lipid droplets associated proteins (LDAP) were found to be the predominant proteins associated with LDs in seed and mesocarp tissues, respectively. We also show that LDs appear to be in close proximity to a number of organelles including the endoplasmic reticulum, mitochondria, peroxisomes, and Golgi apparatus. This comparative study between seed and mesocarp LDs may shed some light on the structure of plant LDs and improve our understanding of their functionality and cellular metabolic networks in oleaginous plant tissues. PMID:28824675

Comparative Lipidomics and Proteomics of Lipid Droplets in the Mesocarp and Seed Tissues of Chinese Tallow (Triadica sebifera).

PubMed

Zhi, Yao; Taylor, Matthew C; Campbell, Peter M; Warden, Andrew C; Shrestha, Pushkar; El Tahchy, Anna; Rolland, Vivien; Vanhercke, Thomas; Petrie, James R; White, Rosemary G; Chen, Wenli; Singh, Surinder P; Liu, Qing

2017-01-01

Lipid droplets (LDs) are composed of a monolayer of phospholipids (PLs), surrounding a core of non-polar lipids that consist mostly of triacylglycerols (TAGs) and to a lesser extent diacylglycerols. In this study, lipidome analysis illustrated striking differences in non-polar lipids and PL species between LDs derived from Triadica sebifera seed kernels and mesocarp. In mesocarp LDs, the most abundant species of TAG contained one C18:1 and two C16:0 and fatty acids, while TAGs containing three C18 fatty acids with higher level of unsaturation were dominant in the seed kernel LDs. This reflects the distinct differences in fatty acid composition of mesocarp (palmitate-rich) and seed-derived oil (α-linoleneate-rich) in T. sebifera . Major PLs in seed LDs were found to be rich in polyunsaturated fatty acids, in contrast to those with relatively shorter carbon chain and lower level of unsaturation in mesocarp LDs. The LD proteome analysis in T. sebifera identified 207 proteins from mesocarp, and 54 proteins from seed kernel, which belong to various functional classes including lipid metabolism, transcription and translation, trafficking and transport, cytoskeleton, chaperones, and signal transduction. Oleosin and lipid droplets associated proteins (LDAP) were found to be the predominant proteins associated with LDs in seed and mesocarp tissues, respectively. We also show that LDs appear to be in close proximity to a number of organelles including the endoplasmic reticulum, mitochondria, peroxisomes, and Golgi apparatus. This comparative study between seed and mesocarp LDs may shed some light on the structure of plant LDs and improve our understanding of their functionality and cellular metabolic networks in oleaginous plant tissues.

Performance and meat quality characteristics of broilers fed fermented mixture of grated cassava roots and palm kernel cake as replacement for maize.

PubMed

Chukwukaelo, A K; Aladi, N O; Okeudo, N J; Obikaonu, H O; Ogbuewu, I P; Okoli, I C

2018-03-01

Performance and meat quality characteristics of broilers fed fermented mixture of grated cassava roots and palm kernel cake (FCP-mix) as a replacement for maize were studied. One hundred and eighty (180), 7-day-old broiler chickens were divided into six groups of 30 birds, and each group replicated thrice. Six experimental diets were formulated for both starter and finisher stages with diets 1 and 6 as controls. Diet 1 contained maize whereas diet 6 contained a 1:1 mixture of cassava root meal (CRM) and palm kernel cake (PKC). In diets 2, 3, 4, and 5, the FCP-mix replaced maize at the rate of 25, 50, 75, and 100%, respectively. Each group was assigned to one experimental diet in a completely randomized design. The proximate compositions of the diets were evaluated. Live weight, feed intake, feed conversion ratio (FCR), carcass weight, and sensory attributes of the meats were obtained from each replicate and data obtained was analyzed statistically. The results showed that live weight, average daily weight gain (ADWG), average daily feed intake (ADFI), and FCR of birds on treatment diets were better than those on the control diets (Diets 1 and 6). The feed cost per kilogram weight gained decreased with inclusion levels of FCP-mix. Birds on diet 1 recorded significantly (p < 0.05) higher dressing percentage than those on the other five treatments. The sensory attributes of the chicken meats were not significantly (p > 0.05) affected by the inclusion of FCP-mix in the diets. FCP-mix is a suitable substitute for maize in broiler diet at a replacement level of up to 100% for best live weight, carcass weight yield, and meat quality.

Effect of kernel size and mill type on protein, milling yield, and baking quality of hard red spring wheat

USDA-ARS?s Scientific Manuscript database

Optimization of flour yield and quality is important in the milling industry. The objective of this study was to determine the effect of kernel size and mill type on flour yield and end-use quality. A hard red spring wheat composite sample was segregated, based on kernel size, into large, medium, ...

Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data

USGS Publications Warehouse

Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.

2016-01-01

Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.

Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data

NASA Astrophysics Data System (ADS)

Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.

2016-04-01

Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.

Discriminant analysis for fast multiclass data classification through regularized kernel function approximation.

PubMed

Ghorai, Santanu; Mukherjee, Anirban; Dutta, Pranab K

2010-06-01

In this brief we have proposed the multiclass data classification by computationally inexpensive discriminant analysis through vector-valued regularized kernel function approximation (VVRKFA). VVRKFA being an extension of fast regularized kernel function approximation (FRKFA), provides the vector-valued response at single step. The VVRKFA finds a linear operator and a bias vector by using a reduced kernel that maps a pattern from feature space into the low dimensional label space. The classification of patterns is carried out in this low dimensional label subspace. A test pattern is classified depending on its proximity to class centroids. The effectiveness of the proposed method is experimentally verified and compared with multiclass support vector machine (SVM) on several benchmark data sets as well as on gene microarray data for multi-category cancer classification. The results indicate the significant improvement in both training and testing time compared to that of multiclass SVM with comparable testing accuracy principally in large data sets. Experiments in this brief also serve as comparison of performance of VVRKFA with stratified random sampling and sub-sampling.

Influence of dietary fiber from coconut kernel (Cocos nucifera) on the 1,2-dimethylhydrazine-induced lipid peroxidation in rats.

PubMed

Pillai, M G; Thampi, B S; Menon, V P; Leelamma, S

1999-09-01

The influence of dietary fiber from coconut kernel isolated by the neutral detergent fiber method on the antioxidant status in rats treated with the colon specific carcinogen 1,2-dimethylhydrazine (DMH) was studied in rats fed a high-fat diet for 15 weeks. The DMH-treated fiber group showed higher levels of lipid peroxides than the control group treated with DMH at the preneoplastic and neoplastic stages. Free fatty acid levels were found to decrease significantly in the DMH-treated control group, whereas it was near normal in the fiber groups. Superoxide dismutase and catalase activity also were found to be increased in the liver, intestine, proximal colon, and distal colon. Glutathione levels in all the tissues studied showed significant decreases in the fiber group. The results suggest that coconut kernel fiber can protect cells from loss of oxidative capacity with the administration of the procarcinogen DMH.

Composition and Free Radical Scavenging Activity of Kernel Oil from Torreya grandis, Carya Cathayensis, and Myrica Rubra

PubMed Central

Ni, Liang; Shi, Wei-Yong

2014-01-01

In this study, we measured the composition and free radical scavenging activity of several species of nuts, namely, Torreya grandis, Carya cathayensis, and Myrica rubra. The nut kernels of the aforementioned species are rich in fatty acids, particularly in unsaturated fatty acids, and have 51% oil content. T. grandis and C. cathayensis are mostly produced in ZheJiang province. The trace elements in the kernels of T. grandis and C. cathayensis were generally higher than those in M. rubra, except for Fe with a value of 64.41 mg/Kg. T. grandis is rich in selenium (52.91−68.71 mg/Kg). All three kernel oils have a certain free radical scavenging capacity, with the highest value in M. rubra. In the DPPH assay, the IC50 of M. rubra kernel oil was 60 μg/mL, and OH was 100 μg/mL. The results of this study provide basic data for the future development of the edible nut resources in ZheJiang province. PMID:24734074

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

PubMed Central

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

PubMed

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

Reconsidering access: park facilities and neighborhood disamenities in New York City.

PubMed

Weiss, Christopher C; Purciel, Marnie; Bader, Michael; Quinn, James W; Lovasi, Gina; Neckerman, Kathryn M; Rundle, Andrew G

2011-04-01

With increasing concern about rising rates of obesity, public health researchers have begun to examine the availability of parks and other spaces for physical activity, particularly in cities, to assess whether access to parks reduces the risk of obesity. Much of the research in this field has shown that proximity to parks may support increased physical activity in urban environments; however, as yet, there has been limited consideration of environmental impediments or disamenities that might influence individuals' perceptions or usage of public recreation opportunities. Prior research suggests that neighborhood disamenities, for instance crime, pedestrian safety, and noxious land uses, might dissuade people from using parks or recreational facilities and vary by neighborhood composition. Motivated by such research, this study estimates the relationship between neighborhood compositional characteristics and measures of park facilities, controlling for variation in neighborhood disamenities, using geographic information systems (GIS) data for New York City parks and employing both kernel density estimation and distance measures. The central finding is that attention to neighborhood disamenities can appreciably alter the relationship between neighborhood composition and spatial access to parks. Policy efforts to enhance the recreational opportunities in urban areas should expand beyond a focus on availability to consider also the hazards and disincentives that may influence park usage.

The effect of microwave roasting on bioactive compounds, antioxidant activity and fatty acid composition of apricot kernel and oils.

PubMed

Al Juhaimi, Fahad; Musa Özcan, Mehmet; Ghafoor, Kashif; Babiker, Elfadıl E

2018-03-15

In this study, the effect of microwave (360W, 540W and 720W) oven roasting on oil yields, phenolic compounds, antioxidant activity, and fatty acid composition of some apricot kernel and oils was investigated. While total phenol contents of control group of apricot kernels change between 54.41mgGAE/100g (Soğancıoğlu) and 59.61mgGAE/100g (Hasanbey), total phenol contents of kernel samples roasted in 720W were determined between 27.41mgGAE/100g (Çataloğlu) and 34.52mgGAE/100g (Soğancıoğlu). Roasting process in microwave at 720W caused the reduction of some phenolic compounds of apricot kernels. The gallic acid contents of control apricot kernels ranged between 7.23mg/100g (Kabaaşı) and 11.23mg/100g (Çataloğlu) whereas the gallic acid contents of kernels roasted in 540W changed between 15.35mg/100g (Soğancıoğlu) and 21.17mg/100g (Çataloğlu). In addition, oleic acid contents of control group oils vary between 65.98% (Soğancıoğlu) and 71.86% (Hasanbey), the same fatty acid ranged from 63.48% (Soğancıoğlu) to 70.36% (Hasanbey). Copyright © 2017 Elsevier Ltd. All rights reserved.

Kernel Machine SNP-set Testing under Multiple Candidate Kernels

PubMed Central

Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

2013-01-01

Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

Fatty acids and bioactive compounds of the pulps and kernels of Brazilian palm species, guariroba (Syagrus oleraces), jerivá (Syagrus romanzoffiana) and macaúba (Acrocomia aculeata).

PubMed

Coimbra, Michelle C; Jorge, Neuza

2012-02-01

Bioactive compounds are capable of providing health benefits, reducing disease incidence or favoring body functioning. There is a growing search for vegetable oils containing such compounds. This study aimed to characterize the pulp and kernel oils of the Brazilian palm species guariroba (Syagrus oleracea), jerivá (Syagrus romanzoffiana) and macaúba (Acrocomia aculeata), aiming at possible uses in several industries. Fatty acid composition, phenolic and carotenoid contents, tocopherol composition were evaluated. The majority of the fatty acids in pulps were oleic and linoleic; macaúba pulp contained 526 g kg⁻¹ of oleic acid. Lauric acid was detected in the kernels of all three species as the major saturated fatty acid, in amounts ranging from 325.8 to 424.3 g kg⁻¹. The jerivá pulp contained carotenoids and tocopherols on average of 1219 µg g⁻¹ and 323.50 mg kg⁻¹, respectively. The pulps contained more unsaturated fatty acids than the kernels, mainly oleic and linoleic. Moreover, the pulps showed higher carotenoid and tocopherol contents. The kernels showed a predominance of saturated fatty acids, especially lauric acid. The fatty acid profiles of the kernels suggest that these oils may be better suited for the cosmetic and pharmaceutical industries than for use in foods. Copyright © 2011 Society of Chemical Industry.

Electron beam lithographic modeling assisted by artificial intelligence technology

NASA Astrophysics Data System (ADS)

Nakayamada, Noriaki; Nishimura, Rieko; Miura, Satoru; Nomura, Haruyuki; Kamikubo, Takashi

2017-07-01

We propose a new concept of tuning a point-spread function (a "kernel" function) in the modeling of electron beam lithography using the machine learning scheme. Normally in the work of artificial intelligence, the researchers focus on the output results from a neural network, such as success ratio in image recognition or improved production yield, etc. In this work, we put more focus on the weights connecting the nodes in a convolutional neural network, which are naturally the fractions of a point-spread function, and take out those weighted fractions after learning to be utilized as a tuned kernel. Proof-of-concept of the kernel tuning has been demonstrated using the examples of proximity effect correction with 2-layer network, and charging effect correction with 3-layer network. This type of new tuning method can be beneficial to give researchers more insights to come up with a better model, yet it might be too early to be deployed to production to give better critical dimension (CD) and positional accuracy almost instantly.

Phenolic compounds and fatty acid composition of organic and conventional grown pecan kernels

USDA-ARS?s Scientific Manuscript database

In this study, differences in contents of phenolic compounds and fatty acids in pecan kernels of organically versus conventionally grown pecan cultivars (‘Desirable’, ‘Cheyenne’, and ‘Wichita’) were evaluated. Although we were able to identify nine phenolic compounds (gallic acid, catechol, catechin...

Genetic variability of the phloem sap metabolite content of maize (Zea mays L.) during the kernel-filling period.

PubMed

Yesbergenova-Cuny, Zhazira; Dinant, Sylvie; Martin-Magniette, Marie-Laure; Quilleré, Isabelle; Armengaud, Patrick; Monfalet, Priscilla; Lea, Peter J; Hirel, Bertrand

2016-11-01

Using a metabolomic approach, we have quantified the metabolite composition of the phloem sap exudate of seventeen European and American lines of maize that had been previously classified into five main groups on the basis of molecular marker polymorphisms. In addition to sucrose, glutamate and aspartate, which are abundant in the phloem sap of many plant species, large quantities of aconitate and alanine were also found in the phloem sap exudates of maize. Genetic variability of the phloem sap composition was observed in the different maize lines, although there was no obvious relationship between the phloem sap composition and the five previously classified groups. However, following hierarchical clustering analysis there was a clear relationship between two of the subclusters of lines defined on the basis of the composition of the phloem sap exudate and the earliness of silking date. A comparison between the metabolite contents of the ear leaves and the phloem sap exudates of each genotype, revealed that the relative content of most of the carbon- and nitrogen-containing metabolites was similar. Correlation studies performed between the metabolite content of the phloem sap exudates and yield-related traits also revealed that for some carbohydrates such as arabitol and sucrose there was a negative or positive correlation with kernel yield and kernel weight respectively. A posititive correlation was also found between kernel number and soluble histidine. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Evaluation of Multiple Kernel Learning Algorithms for Crop Mapping Using Satellite Image Time-Series Data

NASA Astrophysics Data System (ADS)

Niazmardi, S.; Safari, A.; Homayouni, S.

2017-09-01

Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.

Kernel machines for epilepsy diagnosis via EEG signal classification: a comparative study.

PubMed

Lima, Clodoaldo A M; Coelho, André L V

2011-10-01

We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely, Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). Copyright © 2011 Elsevier B.V. All rights reserved.

Anthocyanin composition and oxygen radical scavenging capacity (ORAC) of milled and pearled purple, black, and common barley.

PubMed

Bellido, Guillermo G; Beta, Trust

2009-02-11

The importance of anthocyanins to the total antioxidant capacity of various fruits and vegetables has been well established, but less attention has been focused on cereal grains. This study investigated the antioxidant capacity and anthocyanin composition of a bran-rich pearling fraction (10% outer kernel layers) and whole kernel flour of purple (CI-1248), black (PERU-35), and yellow (EX-83) barley genotypes. HPLC analysis showed that as much as 6 times more anthocyanin per unit weight (microg/g) was present in the bran-rich fractions of yellow and purple barley (1587 and 3534, respectively) than in their corresponding whole kernel flours (210 and 573, respectively). Delphinidin 3-glucoside, delphinidin 3-rutinoside, cyanidin 3-glucoside, petunidin 3-glucoside, and cyanidin chloride were positively identified in barley, with as many as 9 and 15 anthocyanins being detected in yellow and purple barley, respectively. Antioxidant activity analysis showed that the ORAC values for the bran-rich fractions were significantly (p < 0.05) higher than for the whole kernel flour.

Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

PubMed Central

Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A.; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing. PMID:24800230

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

PubMed

Baharuddin, Mohd Yusof; Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

The partial replacement of palm kernel shell by carbon black and halloysite nanotubes as fillers in natural rubber composites

NASA Astrophysics Data System (ADS)

Daud, Shuhairiah; Ismail, Hanafi; Bakar, Azhar Abu

2017-07-01

The effect of partial replacement of palm kernel shell powder by carbon black (CB) and halloysite nanotube (HNT) on the tensile properties, rubber-filler interaction, thermal properties and morphological studies of natural rubber (NR) composites were investigated. Four different compositions of NR/PKS/CB and NR/PKS/HNT composites i.e 20/0, 15/5, 10/10,5/15 and 0/20 parts per hundred rubber (phr) were prepared on a two roll mill. The results showed that the tensile strength and modulus at 100% elongation (M100) and 300% elongation (M300) were higher for NR/PKS/CB compared to NR/PKS/HNT composites. NR/PKS/CB composites had the lowest elongation at break (Eb). The effect of commercial fillers in NR/PKS composites on tensile properties was confirmed by the rubber-filler interaction and scanning electron microscopy (SEM) study. The thermal stability of PKS filled NR composites with partially replaced by commercial fillers also determined by Thermo gravimetric Analysis (TGA).

Chemical components of cold pressed kernel oils from different Torreya grandis cultivars.

PubMed

He, Zhiyong; Zhu, Haidong; Li, Wangling; Zeng, Maomao; Wu, Shengfang; Chen, Shangwei; Qin, Fang; Chen, Jie

2016-10-15

The chemical compositions of cold pressed kernel oils of seven Torreya grandis cultivars from China were analyzed in this study. The contents of the chemical components of T. grandis kernels and kernel oils varied to different extents with the cultivar. The T. grandis kernels contained relatively high oil and protein content (45.80-53.16% and 10.34-14.29%, respectively). The kernel oils were rich in unsaturated fatty acids including linoleic (39.39-47.77%), oleic (30.47-37.54%) and eicosatrienoic acid (6.78-8.37%). The kernel oils contained some abundant bioactive substances such as tocopherols (0.64-1.77mg/g) consisting of α-, β-, γ- and δ-isomers; sterols including β-sitosterol (0.90-1.29mg/g), campesterol (0.06-0.32mg/g) and stigmasterol (0.04-0.18mg/g) in addition to polyphenols (9.22-22.16μgGAE/g). The results revealed that the T. grandis kernel oils possessed the potentially important nutrition and health benefits and could be used as oils in the human diet or functional ingredients in the food industry. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

NASA Astrophysics Data System (ADS)

Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

2017-03-01

Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

Influence of Kernel Age on Fumonisin B1 Production in Maize by Fusarium moniliforme

PubMed Central

Warfield, Colleen Y.; Gilchrist, David G.

1999-01-01

Production of fumonisins by Fusarium moniliforme on naturally infected maize ears is an important food safety concern due to the toxic nature of this class of mycotoxins. Assessing the potential risk of fumonisin production in developing maize ears prior to harvest requires an understanding of the regulation of toxin biosynthesis during kernel maturation. We investigated the developmental-stage-dependent relationship between maize kernels and fumonisin B1 production by using kernels collected at the blister (R2), milk (R3), dough (R4), and dent (R5) stages following inoculation in culture at their respective field moisture contents with F. moniliforme. Highly significant differences (P ≤ 0.001) in fumonisin B1 production were found among kernels at the different developmental stages. The highest levels of fumonisin B1 were produced on the dent stage kernels, and the lowest levels were produced on the blister stage kernels. The differences in fumonisin B1 production among kernels at the different developmental stages remained significant (P ≤ 0.001) when the moisture contents of the kernels were adjusted to the same level prior to inoculation. We concluded that toxin production is affected by substrate composition as well as by moisture content. Our study also demonstrated that fumonisin B1 biosynthesis on maize kernels is influenced by factors which vary with the developmental age of the tissue. The risk of fumonisin contamination may begin early in maize ear development and increases as the kernels reach physiological maturity. PMID:10388675

Allograft-prosthesis composites after bone tumor resection at the proximal tibia.

PubMed

Biau, David Jean; Dumaine, Valérie; Babinet, Antoine; Tomeno, Bernard; Anract, Philippe

2007-03-01

The survival of irradiated allograft-prosthesis composites at the proximal tibia is mostly unknown. However, allograft-prosthesis composites have proved beneficial at other reconstruction sites. We presumed allograft-prosthesis composites at the proximal tibia would improve survival and facilitate reattachment of the extensor mechanism compared with that of conventional (megaprostheses) reconstructions. We retrospectively reviewed 26 patients who underwent resection of proximal tibia tumors followed by reconstruction with allo-graft-prosthesis composites. Patients received Guepar massive custom-made fully constrained prostheses. Allografts were sterilized with gamma radiation, and the stems were cemented into the allograft and host bone. The minimum followup was 6 months (median, 128 months; range, 6-195 months). Fourteen patients had one or more components removed. The median allograft-prosthesis composite survival was 102 months (95% confidence interval, 64.2-infinity). Of the 26 allografts, seven fractured, six showed signs of partial resorption, and six had infections develop. Seven allografts showed signs of fusion with the host bone. Six extensor mechanism reconstructions failed. Allograft-prosthesis composites sterilized by gamma radiation yielded poor results for proximal tibial reconstruction as complications and failures were common. We do not recommend irradiated allograft-prosthesis composites for proximal tibia reconstruction.

Effects of roasting temperature and duration on fatty acid composition, phenolic composition, Maillard reaction degree and antioxidant attribute of almond (Prunus dulcis) kernel.

PubMed

Lin, Jau-Tien; Liu, Shih-Chun; Hu, Chao-Chin; Shyu, Yung-Shin; Hsu, Chia-Ying; Yang, Deng-Jye

2016-01-01

Roasting treatment increased levels of unsaturated fatty acids (linoleic, oleic and elaidic acids) as well as saturated fatty acids (palmitic and stearic acids) in almond (Prunus dulcis) kernel oils with temperature (150 or 180 °C) and duration (5, 10 or 20 min). Nonetheless, higher temperature (200 °C) and longer duration (10 or 20 min) roasting might result in breakdown of fatty acids especially for unsaturated fatty acids. Phenolic components (total phenols, flavonoids, condensed tannins and phenolic acids) of almond kernels substantially lost in the initial phase; afterward these components gradually increased with roasting temperature and duration. Similar results also observed for their antioxidant activities (scavenging DPPH and ABTS(+) radicals and ferric reducing power). The changes of phenolic acid and flavonoid compositions were also determined by HPLC. Maillard reaction products (estimated with non-enzymatic browning index) also increased with roasting temperature and duration; they might also contribute to enhancing the antioxidant attributes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Change of digestive physiology in sea cucumber Apostichopus japonicus (Selenka) induced by corn kernels meal and soybean meal in diets

NASA Astrophysics Data System (ADS)

Yu, Haibo; Gao, Qinfeng; Dong, Shuanglin; Hou, Yiran; Wen, Bin

2016-08-01

The present study was conducted to determine the change of digestive physiology in sea cucumber Apostichopus japonicus (Selenka) induced by corn kernels meal and soybean meal in diets. Four experimental diets were tested, in which Sargassum thunbergii was proportionally replaced by the mixture of corn kernels meal and soybean meal. The growth performance, body composition and intestinal digestive enzyme activities in A. japonicus fed these 4 diets were examined. Results showed that the sea cucumber exhibited the maximum growth rate when 20% of S. thunbergii in the diet was replaced by corn kernels meal and soybean meal, while 40% of S. thunbergii in the diet can be replaced by the mixture of corn kernels meal and soybean meal without adversely affecting growth performance of A. japonicus. The activities of intestinal trypsin and amylase in A. japonicus can be significantly altered by corn kernels meal and soybean meal in diets. Trypsin activity in the intestine of A. japonicus significantly increased in the treatment groups compared to the control, suggesting that the supplement of corn kernels meal and soybean meal in the diets might increase the intestinal trypsin activity of A. japonicus. However, amylase activity in the intestine of A. japonicus remarkably decreased with the increasing replacement level of S. thunbergii by the mixture of corn kernels meal and soybean meal, suggesting that supplement of corn kernels meal and soybean meal in the diets might decrease the intestinal amylase activity of A. japonicus.

Phenolic compounds and antioxidant activity of kernels and shells of Mexican pecan (Carya illinoinensis).

PubMed

de la Rosa, Laura A; Alvarez-Parrilla, Emilio; Shahidi, Fereidoon

2011-01-12

The phenolic composition and antioxidant activity of pecan kernels and shells cultivated in three regions of the state of Chihuahua, Mexico, were analyzed. High concentrations of total extractable phenolics, flavonoids, and proanthocyanidins were found in kernels, and 5-20-fold higher concentrations were found in shells. Their concentrations were significantly affected by the growing region. Antioxidant activity was evaluated by ORAC, DPPH•, HO•, and ABTS•-- scavenging (TAC) methods. Antioxidant activity was strongly correlated with the concentrations of phenolic compounds. A strong correlation existed among the results obtained using these four methods. Five individual phenolic compounds were positively identified and quantified in kernels: ellagic, gallic, protocatechuic, and p-hydroxybenzoic acids and catechin. Only ellagic and gallic acids could be identified in shells. Seven phenolic compounds were tentatively identified in kernels by means of MS and UV spectral comparison, namely, protocatechuic aldehyde, (epi)gallocatechin, one gallic acid-glucose conjugate, three ellagic acid derivatives, and valoneic acid dilactone.

Kernel machine methods for integrative analysis of genome-wide methylation and genotyping studies.

PubMed

Zhao, Ni; Zhan, Xiang; Huang, Yen-Tsung; Almli, Lynn M; Smith, Alicia; Epstein, Michael P; Conneely, Karen; Wu, Michael C

2018-03-01

Many large GWAS consortia are expanding to simultaneously examine the joint role of DNA methylation in addition to genotype in the same subjects. However, integrating information from both data types is challenging. In this paper, we propose a composite kernel machine regression model to test the joint epigenetic and genetic effect. Our approach works at the gene level, which allows for a common unit of analysis across different data types. The model compares the pairwise similarities in the phenotype to the pairwise similarities in the genotype and methylation values; and high correspondence is suggestive of association. A composite kernel is constructed to measure the similarities in the genotype and methylation values between pairs of samples. We demonstrate through simulations and real data applications that the proposed approach can correctly control type I error, and is more robust and powerful than using only the genotype or methylation data in detecting trait-associated genes. We applied our method to investigate the genetic and epigenetic regulation of gene expression in response to stressful life events using data that are collected from the Grady Trauma Project. Within the kernel machine testing framework, our methods allow for heterogeneity in effect sizes, nonlinear, and interactive effects, as well as rapid P-value computation. © 2017 WILEY PERIODICALS, INC.

Nutritional composition of shea products and chemical properties of shea butter: a review.

PubMed

Honfo, Fernande G; Akissoe, Noel; Linnemann, Anita R; Soumanou, Mohamed; Van Boekel, Martinus A J S

2014-01-01

Increasing demand of shea products (kernels and butter) has led to the assessment of the state-of-the-art of these products. In this review, attention has been focused on macronutrients and micronutrients of pulp, kernels, and butter of shea tree and also the physicochemical properties of shea butter. Surveying the literature revealed that the pulp is rich in vitamin C (196.1 mg/100 g); consumption of 50 g covers 332% and 98% of the recommended daily intake (RDI) of children (4-8 years old) and pregnant women, respectively. The kernels contain a high level of fat (17.4-59.1 g/100 g dry weight). Fat extraction is mainly done by traditional methods that involve roasting and pressing of the kernels, churning the obtained liquid with water, boiling, sieving, and cooling. The fat (butter) is used in food preparation and medicinal and cosmetics industries. Its biochemical properties indicate some antioxidant and anti-inflammatory activities. Large variations are observed in the reported values for the composition of shea products. Recommendations for future research are presented to improve the quality and the shelf-life of the butter. In addition, more attention should be given to the accuracy and precision in experimental analyses to obtain more reliable information about biological variation.

Prediction of heterotrimeric protein complexes by two-phase learning using neighboring kernels

PubMed Central

2014-01-01

Background Protein complexes play important roles in biological systems such as gene regulatory networks and metabolic pathways. Most methods for predicting protein complexes try to find protein complexes with size more than three. It, however, is known that protein complexes with smaller sizes occupy a large part of whole complexes for several species. In our previous work, we developed a method with several feature space mappings and the domain composition kernel for prediction of heterodimeric protein complexes, which outperforms existing methods. Results We propose methods for prediction of heterotrimeric protein complexes by extending techniques in the previous work on the basis of the idea that most heterotrimeric protein complexes are not likely to share the same protein with each other. We make use of the discriminant function in support vector machines (SVMs), and design novel feature space mappings for the second phase. As the second classifier, we examine SVMs and relevance vector machines (RVMs). We perform 10-fold cross-validation computational experiments. The results suggest that our proposed two-phase methods and SVM with the extended features outperform the existing method NWE, which was reported to outperform other existing methods such as MCL, MCODE, DPClus, CMC, COACH, RRW, and PPSampler for prediction of heterotrimeric protein complexes. Conclusions We propose two-phase prediction methods with the extended features, the domain composition kernel, SVMs and RVMs. The two-phase method with the extended features and the domain composition kernel using SVM as the second classifier is particularly useful for prediction of heterotrimeric protein complexes. PMID:24564744

Studies of fatty acid composition, physicochemical and thermal properties, and crystallization behavior of mango kernel fats from various Thai varieties.

PubMed

Sonwai, Sopark; Ponprachanuvut, Punnee

2014-01-01

Mango kernel fat (MKF) has received attention in recent years due to the resemblance between its characteristics and those of cocoa butter (CB). In this work, fatty acid (FA) composition, physicochemical and thermal properties and crystallization behavior of MKFs obtained from four varieties of Thai mangoes: Keaw-Morakot (KM), Keaw-Sawoey (KS), Nam-Dokmai (ND) and Aok-Rong (AR), were characterized. The fat content of the mango kernels was 6.40, 5.78, 5.73 and 7.74% (dry basis) for KM, KS, ND and AR, respectively. The analysis of FA composition revealed that all four cultivars had oleic and stearic acids as the main FA components with ND and AR exhibiting highest and lowest stearic acid content, respectively. ND had the highest slip melting point and solid fat content (SFC) followed by KS, KM and AR. All fat samples exhibited high SFC at 20℃ and below. They melted slowly as the temperature increased and became complete liquids as the temperature approached 35°C. During static isothermal crystallization at 20°C, ND displayed the highest Avrami rate constant k followed by KS, KM and AR, indicating that the crystallization was fastest for ND and slowest for AR. The Avrami exponent n of all samples ranged from 0.89 to 1.73. The x-ray diffraction analysis showed that all MKFs crystallized into a mixture of pseudo-β', β', sub-β and β structures with β' being the predominant polymorph. Finally, the crystals of the kernel fats from all mango varieties exhibited spherulitic morphology.

Proximate analysis of five wild fruits of Mozambique.

PubMed

Magaia, Telma; Uamusse, Amália; Sjöholm, Ingegerd; Skog, Kerstin

2013-01-01

Mozambique is rich in wild fruit trees, most of which produce fleshy fruits commonly consumed in rural communities, especially during dry seasons. However, information on their content of macronutrients is scarce. Five wild fruit species (Adansonia digitata, Landolphia kirkii, Sclerocarya birrea, Salacia kraussii, and Vangueria infausta) from different districts in Mozambique were selected for the study. The contents of dry matter, fat, protein, ash, sugars, pH, and titratable acidity were determined in the fruit pulps. Also kernels of A. digitata and S. birrea were included in the study. The protein content in the pulp was below 5 g/100 g of dry matter, but a daily intake of 100 g fresh wild fruits would provide up to 11% of the recommended daily intake for children from 4 to 8 years old. The sugar content varied between 2.3% and 14.4% fresh weight. The pH was below 3, except for Salacia kraussii, for which it was slightly below 7. Kernels of A. digitata contained, on average, 39.2% protein and 38.0% fat, and S. birrea kernels 32.6% protein and 60.7% fat. The collection of nutritional information may serve as a basis for increased consumption and utilization.

Proximate Analysis of Five Wild Fruits of Mozambique

PubMed Central

Uamusse, Amália; Sjöholm, Ingegerd

2013-01-01

Mozambique is rich in wild fruit trees, most of which produce fleshy fruits commonly consumed in rural communities, especially during dry seasons. However, information on their content of macronutrients is scarce. Five wild fruit species (Adansonia digitata, Landolphia kirkii, Sclerocarya birrea, Salacia kraussii, and Vangueria infausta) from different districts in Mozambique were selected for the study. The contents of dry matter, fat, protein, ash, sugars, pH, and titratable acidity were determined in the fruit pulps. Also kernels of A. digitata and S. birrea were included in the study. The protein content in the pulp was below 5 g/100 g of dry matter, but a daily intake of 100 g fresh wild fruits would provide up to 11% of the recommended daily intake for children from 4 to 8 years old. The sugar content varied between 2.3% and 14.4% fresh weight. The pH was below 3, except for Salacia kraussii, for which it was slightly below 7. Kernels of A. digitata contained, on average, 39.2% protein and 38.0% fat, and S. birrea kernels 32.6% protein and 60.7% fat. The collection of nutritional information may serve as a basis for increased consumption and utilization. PMID:23983641

Optimization of the acceptance of prebiotic beverage made from cashew nut kernels and passion fruit juice.

PubMed

Rebouças, Marina Cabral; Rodrigues, Maria do Carmo Passos; Afonso, Marcos Rodrigues Amorim

2014-07-01

The aim of this research was to develop a prebiotic beverage from a hydrosoluble extract of broken cashew nut kernels and passion fruit juice using response surface methodology in order to optimize acceptance of its sensory attributes. A 2(2) central composite rotatable design was used, which produced 9 formulations, which were then evaluated using different concentrations of hydrosoluble cashew nut kernel, passion fruit juice, oligofructose, and 3% sugar. The use of response surface methodology to interpret the sensory data made it possible to obtain a formulation with satisfactory acceptance which met the criteria of bifidogenic action and use of hydrosoluble cashew nut kernels by using 14% oligofructose and 33% passion fruit juice. As a result of this study, it was possible to obtain a new functional prebiotic product, which combined the nutritional and functional properties of cashew nut kernels and oligofructose with the sensory properties of passion fruit juice in a beverage with satisfactory sensory acceptance. This new product emerges as a new alternative for the industrial processing of broken cashew nut kernels, which have very low market value, enabling this sector to increase its profits. © 2014 Institute of Food Technologists®

Kolkhoung (Pistacia khinjuk) Hull Oil and Kernel Oil as Antioxidative Vegetable Oils with High Oxidative Stability 
and Nutritional Value.

PubMed

Asnaashari, Maryam; Hashemi, Seyed Mohammad Bagher; Mehr, Hamed Mahdavian; Yousefabad, Seyed Hossein Asadi

2015-03-01

In this study, in order to introduce natural antioxidative vegetable oil in food industry, the kolkhoung hull oil and kernel oil were extracted. To evaluate their antioxidant efficiency, gas chromatography analysis of the composition of kolkhoung hull and kernel oil fatty acids and high-performance liquid chromatography analysis of tocopherols were done. Also, the oxidative stability of the oil was considered based on the peroxide value and anisidine value during heating at 100, 110 and 120 °C. Gas chromatography analysis showed that oleic acid was the major fatty acid of both types of oil (hull and kernel) and based on a low content of saturated fatty acids, high content of monounsaturated fatty acids, and the ratio of ω-6 and ω-3 polyunsaturated fatty acids, they were nutritionally well--balanced. Moreover, both hull and kernel oil showed high oxidative stability during heating, which can be attributed to high content of tocotrienols. Based on the results, kolkhoung hull oil acted slightly better than its kernel oil. However, both of them can be added to oxidation-sensitive oils to improve their shelf life.

Effects of Cerium and Titanium Oxide Nanoparticles in Soil on the Nutrient Composition of Barley (Hordeum vulgare L.) Kernels

PubMed Central

Pošćić, Filip; Mattiello, Alessandro; Fellet, Guido; Miceli, Fabiano; Marchiol, Luca

2016-01-01

The implications of metal nanoparticles (MeNPs) are still unknown for many food crops. The purpose of this study was to evaluate the effects of cerium oxide (nCeO2) and titanium oxide (nTiO2) nanoparticles in soil at 0, 500 and 1000 mg·kg−1 on the nutritional parameters of barley (Hordeum vulgare L.) kernels. Mineral nutrients, amylose, β-glucans, amino acid and crude protein (CP) concentrations were measured in kernels. Whole flour samples were analyzed by ICP-AES/MS, HPLC and Elemental CHNS Analyzer. Results showed that Ce and Ti accumulation under MeNPs treatments did not differ from the control treatment. However, nCeO2 and nTiO2 had an impact on composition and nutritional quality of barley kernels in contrasting ways. Both MeNPs left β-glucans unaffected but reduced amylose content by approximately 21%. Most amino acids and CP increased. Among amino acids, lysine followed by proline saw the largest increase (51% and 37%, respectively). Potassium and S were both negatively impacted by MeNPs, while B was only affected by 500 mg nCeO2·kg−1. On the contrary Zn and Mn concentrations were improved by 500 mg nTiO2·kg−1, and Ca by both nTiO2 treatments. Generally, our findings demonstrated that kernels are negatively affected by nCeO2 while nTiO2 can potentially have beneficial effects. However, both MeNPs have the potential to negatively impact malt and feed production. PMID:27294945

Urban Transmission of American Cutaneous Leishmaniasis in Argentina: Spatial Analysis Study

PubMed Central

Gil, José F.; Nasser, Julio R.; Cajal, Silvana P.; Juarez, Marisa; Acosta, Norma; Cimino, Rubén O.; Diosque, Patricio; Krolewiecki, Alejandro J.

2010-01-01

We used kernel density and scan statistics to examine the spatial distribution of cases of pediatric and adult American cutaneous leishmaniasis in an urban disease-endemic area in Salta Province, Argentina. Spatial analysis was used for the whole population and stratified by women > 14 years of age (n = 159), men > 14 years of age (n = 667), and children < 15 years of age (n = 213). Although kernel density for adults encompassed nearly the entire city, distribution in children was most prevalent in the peripheral areas of the city. Scan statistic analysis for adult males, adult females, and children found 11, 2, and 8 clusters, respectively. Clusters for children had the highest odds ratios (P < 0.05) and were located in proximity of plantations and secondary vegetation. The data from this study provide further evidence of the potential urban transmission of American cutaneous leishmaniasis in northern Argentina. PMID:20207869

Nutrient database improvement project: the influence of U.S.D.A. Quality and Yield Grade on the separable components and proximate composition of raw and cooked retail cuts from the beef rib and plate.

PubMed

Martin, J N; Brooks, J C; Thompson, L D; Savell, J W; Harris, K B; May, L L; Haneklaus, A N; Schutz, J L; Belk, K E; Engle, T; Woerner, D R; Legako, J F; Luna, A M; Douglass, L W; Douglass, S E; Howe, J; Duvall, M; Patterson, K Y; Leheska, J L

2013-11-01

Beef nutrition is important to the worldwide beef industry. The objective of this study was to analyze proximate composition of eight beef rib and plate cuts to update the USDA National Nutrient Database for Standard Reference (SR). Furthermore, this study aimed to determine the influence of USDA Quality Grade on the separable components and proximate composition of the examined retail cuts. Carcasses (n=72) representing a composite of Yield Grade, Quality Grade, gender and genetic type were identified from six regions across the U.S. Beef plates and ribs (IMPS #109 and 121C and D) were collected from the selected carcasses and shipped to three university meat laboratories for storage, retail fabrication, cooking, and dissection and analysis of proximate composition. These data provide updated information regarding the nutrient content of beef and emphasize the influence of common classification systems (Yield Grade and Quality Grade) on the separable components, cooking yield, and proximate composition of retail beef cuts. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of gamma irradiation on tropomyosin allergen, proximate composition and mineral elements in giant freshwater prawn (Macrobrachium rosenbergii).

PubMed

Muanghorn, Wipawan; Konsue, Nattaya; Sham, Hasan; Othman, Zainon; Mohamed, Faizal; Mohd Noor, Noramaliza; Othman, Norsyafiqah; Mohd Noor Akmal, Nur Shamin Shyamimi; Ahmad Fauzi, Nurulhuda; Packiamuthu Dewaprigam Solomen, Mary Margaret; Abdull Razis, Ahmad Faizal

2018-05-01

Effects of food irradiation on allergen and nutritional composition of giant freshwater prawn are not well documented. Thus, this study aimed to investigate the effects of gamma irradiation on tropomyosin allergen, proximate composition, and mineral elements in Macrobrachium rosenbergii . In this study, prawn was peeled, cut into small pieces, vacuum packaged and gamma irradiated at 0, 5, 7, 10 and 15 kGy with a dose rate of 0.5 kGy/h using cobalt-60 as the source, subsequently determined the level of tropomyosin, proximate composition and mineral elements respectively. The results showed that band density of tropomyosin irradiated at 10 and 15 kGy is markedly decreased. Proximate analysis revealed that moisture, protein, and carbohydrate content were significantly different as compared with non-irradiated prawn. Meanwhile, gamma irradiated M. rosenbergii at 15 kGy was observed to be significantly higher in nickel and zinc than the non-irradiated prawn. The findings provide a new information that food irradiation may affect the tropomyosin allergen, proximate composition and mineral elements of the prawn.

Identification of Fourier transform infrared photoacoustic spectral features for detection of Aspergillus flavus infection in corn.

PubMed

Gordon, S H; Schudy, R B; Wheeler, B C; Wicklow, D T; Greene, R V

1997-04-01

Aspergillus flavus and other pathogenic fungi display typical infrared spectra which differ significantly from spectra of substrate materials such as corn. On this basis, specific spectral features have been identified which permit detection of fungal infection on the surface of corn kernels by photoacoustic infrared spectroscopy. In a blind study, ten corn kernels showing bright greenish yellow fluorescence (BGYF) in the germ or endosperm and ten BGYF-negative kernels were correctly classified as infected or not infected by Fourier transform infrared photoacoustic spectroscopy. Earlier studies have shown that BGYF-positive kernels contain the bulk of the aflatoxin contaminating grain at harvest. Ten major spectral features, identified by visual inspection of the photoacoustic spectra of A. flavus mycelium grown in culture versus uninfected corn, were interpreted and assigned by theoretical comparisons of the relative chemical compositions of fungi and corn. The spectral features can be built into either empirical or knowledge-based computer models (expert systems) for automatic infrared detection and segregation of grains or kernels containing aflatoxin from the food and feed supply.

Characterization of Mesocarp and Kernel Lipids from Elaeis guineensis Jacq., Elaeis oleifera [Kunth] Cortés, and Their Interspecific Hybrids.

PubMed

Lieb, Veronika M; Kerfers, Margarete R; Kronmüller, Amrei; Esquivel, Patricia; Alvarado, Amancio; Jiménez, Víctor M; Schmarr, Hans-Georg; Carle, Reinhold; Schweiggert, Ralf M; Steingass, Christof B

2017-05-10

Morphological traits, total lipid contents, and fatty acid profiles were assessed in fruits of several accessions of Elaeis oleifera [Kunth] Cortés, Elaeis guineensis Jacq., and their interspecific hybrids. The latter featured the highest mesocarp-to-fruit ratios (77.9-78.2%). The total lipid contents of both E. guineensis mesocarp and kernel were significantly higher than for E. oleifera accessions. Main fatty acids comprised C16:0, C18:1n9, and C18:2n6 in mesocarp and C12:0, C14:0, and C18:1n9 in kernels. E. oleifera samples were characterized by higher proportions of unsaturated long-chain fatty acids. Saturated medium-chain fatty acids supported the clustering of E. guineensis kernels in multivariate statistics. Hybrid mesocarp lipids had an intermediate fatty acid composition, whereas their kernel lipids resembled those of E. oleifera genotypes. Principal component analysis based on lipid contents and proportions of individual fatty acids permitted clear-cut distinction of E. oleifera, E. guineensis, and their hybrids.

Proximal composition and in vitro digestibility of starch in lima bean (Phaseolus lunatus) varieties.

PubMed

Bello-Pérez, Luis A; Sáyago-Ayerdi, Sonia G; Chávez-Murillo, Carolina E; Agama-Acevedo, Edith; Tovar, Juscelino

2007-11-01

Beans are rich and inexpensive sources of proteins and carbohydrates around the world, but particularly in developing countries. However, many legume varieties are still underutilized. In this study, physical characteristics of the seeds of three Phaseolus lunatus cultivars were characterized. Also, the chemical composition and starch digestibility in the cooked beans were assessed. 'Comba floja' variety exhibited the highest thousand-kernel weight whereas the lowest was found in 'comba violenta'. This agrees with seed dimensions: 'comba floja' had the Longest seeds (16.36 mm) and 'comba violenta' the shortest ones (13.98 mm). All samples exhibited high protein content, but levels in 'comba blanca' variety (216 g kg(-1)) were lower than the in other two cultivars. Total starch (370-380 g kg(-1)) and potentially available starch content (330-340 g kg(-1)) were similar in the three varieties. Resistant starch level in the cooked seeds ranged between 38 and 45 g kg(-1). Low enzymatic hydrolysis indices (HI) were recorded (30.2-35%), indicating a low digestion rate for Phaseolus lunatus starch. HI-based predicted glycemic indices ranged between 34% and 39%, which suggests a 'slow carbohydrate' feature for this legume. Phaseolus lunatus beans appear to be a good source of protein and slow-release carbohydrates with potential benefits for human health. Copyright © 2007 Society of Chemical Industry.

Analysis of fractionation in corn-to-ethanol plants

NASA Astrophysics Data System (ADS)

Nelson, Camille

As the dry grind ethanol industry has grown, the research and technology surrounding ethanol production and co-product value has increased. Including use of back-end oil extraction and front-end fractionation. Front-end fractionation is pre-fermentation separation of the corn kernel into 3 fractions: endosperm, bran, and germ. The endosperm fraction enters the existing ethanol plant, and a high protein DDGS product remains after fermentation. High value oil is extracted out of the germ fraction. This leaves corn germ meal and bran as co-products from the other two streams. These 3 co-products have a very different composition than traditional corn DDGS. Installing this technology allows ethanol plants to increase profitability by tapping into more diverse markets, and ultimately could allow for an increase in profitability. An ethanol plant model was developed to evaluate both back-end oil extraction and front-end fractionation technology and predict the change in co-products based on technology installed. The model runs in Microsoft Excel and requires inputs of whole corn composition (proximate analysis), amino acid content, and weight to predict the co-product quantity and quality. User inputs include saccharification and fermentation efficiencies, plant capacity, and plant process specifications including front-end fractionation and backend oil extraction, if applicable. This model provides plants a way to assess and monitor variability in co-product composition due to the variation in whole corn composition. Additionally the co-products predicted in this model are entered into the US Pork Center of Excellence, National Swine Nutrition Guide feed formulation software. This allows the plant user and animal nutritionists to evaluate the value of new co-products in existing animal diets.

The effect of smelting time and composition of palm kernel shell charcoal reductant toward extractive Pomalaa nickel laterite ore in mini electric arc furnace

NASA Astrophysics Data System (ADS)

Sihotang, Iqbal Huda; Supriyatna, Yayat Iman; Ismail, Ika; Sulistijono

2018-04-01

Indonesia is a country that is rich in natural resources. Being a third country which has a nickel laterite ore in the world after New Caledonia and Philippines. However, the processing of nickel laterite ore to increase its levels in Indonesia is still lacking. In the processing of nickel laterite ore into metal, it can be processed by pyrometallurgy method that typically use coal as a reductant. However, coal is a non-renewable energy and have high enough levels of pollution. One potentially replace is the biomass, that is a renewable energy. Palm kernel shell are biomass that can be used as a reductant because it has a fairly high fix carbon content. This research aims to make nickel laterite ores become metal using palm kernel shell charcoal as reductant in mini electric arc furnace. The result show that the best smelting time of this research is 60 minutes with the best composition of the reductant is 2,000 gram.

Shell cracking strength in almond (Prunus dulcis [Mill.] D.A. Webb.) and its implication in uses as a value-added product.

PubMed

Ledbetter, C A

2008-09-01

Researchers are currently developing new value-added uses for almond shells, an abundant agricultural by-product. Almond varieties are distinguished by processors as being either hard or soft shelled, but these two broad classes of almond also exhibit varietal diversity in shell morphology and physical characters. By defining more precisely the physical and chemical characteristics of almond shells from different varieties, researchers will better understand which specific shell types are best suited for specific industrial processes. Eight diverse almond accessions were evaluated in two consecutive harvest seasons for nut and kernel weight, kernel percentage and shell cracking strength. Shell bulk density was evaluated in a separate year. Harvest year by almond accession interactions were highly significant (p0.01) for each of the analyzed variables. Significant (p0.01) correlations were noted for average nut weight with kernel weight, kernel percentage and shell cracking strength. A significant (p0.01) negative correlation for shell cracking strength with kernel percentage was noted. In some cases shell cracking strength was independent of the kernel percentage which suggests that either variety compositional differences or shell morphology affect the shell cracking strength. The varietal characterization of almond shell materials will assist in determining the best value-added uses for this abundant agricultural by-product.

Modelling and estimating pollen movement in oilseed rape (Brassica napus) at the landscape scale using genetic markers.

PubMed

Devaux, C; Lavigne, C; Austerlitz, F; Klein, E K

2007-02-01

Understanding patterns of pollen movement at the landscape scale is important for establishing management rules following the release of genetically modified (GM) crops. We use here a mating model adapted to cultivated species to estimate dispersal kernels from the genotypes of the progenies of male-sterile plants positioned at different sampling sites within a 10 x 10-km oilseed rape production area. Half of the pollen clouds sampled by the male-sterile plants originated from uncharacterized pollen sources that could consist of both large volunteer and feral populations, and fields within and outside the study area. The geometric dispersal kernel was the most appropriate to predict pollen movement in the study area. It predicted a much larger proportion of long-distance pollination than previously fitted dispersal kernels. This best-fitting mating model underestimated the level of differentiation among pollen clouds but could predict its spatial structure. The estimation method was validated on simulated genotypic data, and proved to provide good estimates of both the shape of the dispersal kernel and the rate and composition of pollen issued from uncharacterized pollen sources. The best dispersal kernel fitted here, the geometric kernel, should now be integrated into models that aim at predicting gene flow at the landscape level, in particular between GM and non-GM crops.

Genetic architecture of kernel composition in global sorghum germplasm

USDA-ARS?s Scientific Manuscript database

Sorghum [Sorghum bicolor (L.) Moench] is an important cereal crop for dryland areas in the United States and for small-holder farmers in Africa. Natural variation of sorghum grain composition (protein, fat, and starch) between accessions can be used for crop improvement, but the genetic controls are...

The effects of food irradiation on quality of pine nut kernels

NASA Astrophysics Data System (ADS)

Gölge, Evren; Ova, Gülden

2008-03-01

Pine nuts ( Pinus pinae) undergo gamma irradiation process with the doses 0.5, 1.0, 3.0, and 5.0 kGy. The changes in chemical, physical and sensory attributes were observed in the following 3 months of storage period. The data obtained from the experiments showed the peroxide values of the pine nut kernels increased proportionally to the dose. On contrary, irradiation process has no effect on the physical quality such as texture and color, fatty acid composition and sensory attributes.

Allograft-prosthetic composite reverse total shoulder arthroplasty for reconstruction of proximal humerus tumor resections.

PubMed

King, Joseph J; Nystrom, Lukas M; Reimer, Nickolas B; Gibbs, C Parker; Scarborough, Mark T; Wright, Thomas W

2016-01-01

Proximal humerus reconstructions after resection of tumors are challenging. Early success of the reverse shoulder arthroplasty for reconstructions has recently been reported. The reverse allograft-prosthetic composite offers the advantage of improved glenohumeral stability compared with hemiarthroplasty for proximal humeral reconstructions as it uses the deltoid for stability. This article describes the technique for treating proximal humeral tumors, including preoperative planning, biopsy principles, resection pearls, soft tissue tensioning, and specifics about reconstruction using the reverse allograft-prosthetic composite. Two cases are presented along with the functional outcomes with use of this technique. Biomechanical considerations during reconstruction are reviewed, including techniques to improve the deltoid compression force. Reported instability rates are less with reverse shoulder arthroplasty reconstruction as opposed to hemiarthroplasty or total shoulder arthroplasty reconstructions of tumor resections. Reported functional outcomes are promising for the reverse allograft-prosthetic composite reconstructions, although complications are reported. Reverse allograft-prosthetic composites are a promising option for proximal humeral reconstructions, although nonunion of the allograft-host bone junction continues to be a challenge for this technique. Copyright © 2016 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Determining the minimum required uranium carbide content for HTGR UCO fuel kernels

DOE PAGES

McMurray, Jacob W.; Lindemer, Terrence B.; Brown, Nicholas R.; ...

2017-03-10

There are three important failure mechanisms that must be controlled in high-temperature gas-cooled reactor (HTGR) fuel for certain higher burnup applications are SiC layer rupture, SiC corrosion by CO, and coating compromise from kernel migration. All are related to high CO pressures stemming from free O generated when uranium present as UO 2 fissions and the O is not subsequently bound by other elements. Furthermore, in the HTGR UCO kernel design, CO buildup from excess O is controlled by the inclusion of additional uranium in the form of a carbide, UC x. An approach for determining the minimum UC xmore » content to ensure negligible CO formation was developed and demonstrated using CALPHAD models and the Serpent 2 reactor physics and depletion analysis tool. Our results are intended to be more accurate than previous estimates by including more nuclear and chemical factors, in particular the effect of transmutation products on the oxygen distribution as the fuel kernel composition evolves with burnup.« less

Relationship between processing score and kernel-fraction particle size in whole-plant corn silage.

PubMed

Dias Junior, G S; Ferraretto, L F; Salvati, G G S; de Resende, L C; Hoffman, P C; Pereira, M N; Shaver, R D

2016-04-01

Kernel processing increases starch digestibility in whole-plant corn silage (WPCS). Corn silage processing score (CSPS), the percentage of starch passing through a 4.75-mm sieve, is widely used to assess degree of kernel breakage in WPCS. However, the geometric mean particle size (GMPS) of the kernel-fraction that passes through the 4.75-mm sieve has not been well described. Therefore, the objectives of this study were (1) to evaluate particle size distribution and digestibility of kernels cut in varied particle sizes; (2) to propose a method to measure GMPS in WPCS kernels; and (3) to evaluate the relationship between CSPS and GMPS of the kernel fraction in WPCS. Composite samples of unfermented, dried kernels from 110 corn hybrids commonly used for silage production were kept whole (WH) or manually cut in 2, 4, 8, 16, 32 or 64 pieces (2P, 4P, 8P, 16P, 32P, and 64P, respectively). Dry sieving to determine GMPS, surface area, and particle size distribution using 9 sieves with nominal square apertures of 9.50, 6.70, 4.75, 3.35, 2.36, 1.70, 1.18, and 0.59 mm and pan, as well as ruminal in situ dry matter (DM) digestibilities were performed for each kernel particle number treatment. Incubation times were 0, 3, 6, 12, and 24 h. The ruminal in situ DM disappearance of unfermented kernels increased with the reduction in particle size of corn kernels. Kernels kept whole had the lowest ruminal DM disappearance for all time points with maximum DM disappearance of 6.9% at 24 h and the greatest disappearance was observed for 64P, followed by 32P and 16P. Samples of WPCS (n=80) from 3 studies representing varied theoretical length of cut settings and processor types and settings were also evaluated. Each WPCS sample was divided in 2 and then dried at 60 °C for 48 h. The CSPS was determined in duplicate on 1 of the split samples, whereas on the other split sample the kernel and stover fractions were separated using a hydrodynamic separation procedure. After separation, the kernel fraction was redried at 60°C for 48 h in a forced-air oven and dry sieved to determine GMPS and surface area. Linear relationships between CSPS from WPCS (n=80) and kernel fraction GMPS, surface area, and proportion passing through the 4.75-mm screen were poor. Strong quadratic relationships between proportion of kernel fraction passing through the 4.75-mm screen and kernel fraction GMPS and surface area were observed. These findings suggest that hydrodynamic separation and dry sieving of the kernel fraction may provide a better assessment of kernel breakage in WPCS than CSPS. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Composition and toxigenic potential of the Fusarium graminearum species complex from maize ears, stalks and stubble in Brazil

USDA-ARS?s Scientific Manuscript database

Detailed knowledge of the composition and toxigenic potential of the Fusarium graminearum species complex affecting maize crops in Brazil is lacking. A multilocus genotype approach was used to identify 539 isolates from three sub-collections: 1) maize kernels (n= 110) from five states spanning sout...

Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

Development and analysis of composite flour bread.

PubMed

Menon, Lakshmi; Majumdar, Swarnali Dutta; Ravi, Usha

2015-07-01

The study elucidates the effect of utilizing cereal-pulse-fruit seed composite flour in the development and quality analysis of leavened bread. The composite flour was prepared using refined wheat flour (WF), high protein soy flour (SF), sprouted mung bean flour (MF) and mango kernel flour (MKF). Three variations were formulated such as V-I (WF: SF: MF: MKF = 85:5:5:5), V-II (WF: SF: MF: MKF = 70:10:10:10), and V-III (WF: SF: MF: MKF = 60:14:13:13). Pertinent functional, physico-chemical and organoleptic attributes were studied in composite flour variations and their bread preparations. Physical characteristics of the bread variations revealed a percentage decrease in loaf height (14 %) and volume (25 %) and 20 % increase in loaf weight with increased substitution of composite flour. The sensory evaluation of experimental breads on a nine-point hedonic scale revealed that V-I score was 5 % higher than the standard bread. Hence, the present study highlighted the nutrient enrichment of bread on incorporation of a potential waste material mango kernel, soy and sprouted legume. Relevant statistical tests were done to analyze the significance of means for all tested parameters.

Proximate composition, nutritional attributes and mineral composition of Peperomia pellucida L. (Ketumpangan Air) grown in Malaysia.

PubMed

Ooi, Der-Jiun; Iqbal, Shahid; Ismail, Maznah

2012-09-17

This study presents the proximate and mineral composition of Peperomia pellucida L., an underexploited weed plant in Malaysia. Proximate analysis was performed using standard AOAC methods and mineral contents were determined using atomic absorption spectrometry. The results indicated Peperomia pellucida to be rich in crude protein, carbohydrate and total ash contents. The high amount of total ash (31.22%)suggests a high-value mineral composition comprising potassium, calcium and iron as the main elements. The present study inferred that Peperomia pellucida would serve as a good source of protein and energy as well as micronutrients in the form of a leafy vegetable for human consumption.

Proximate composition and nutritional evaluation of the adductor muscle of pen shell.

PubMed

Wu, Shengjun; Wu, Yuping

2017-07-01

The proximate composition of pen shell adductor muscle (PSAM) was determined, and its nutrition value was evaluated. Proximate composition analysis indicated that PSAM contained 91.07% (w/w) protein, 5.77% (w/w) ash, and 2.46% (w/w) fat. Calcium was the predominant mineral followed by zinc and then iron. The amino acid profile was in accordance with the recommended pattern of FAO/WHO except for histidine. At the same time, the first limiting amino acid was histidine. Fatty acid composition showed that docosahexaenoic acid was the major fatty acid, followed by palmitic, stearic, and arachidonic acids. Results indicated that PSAM was rich in nutrition and may be developed as a functional food.

Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

PubMed Central

Meinicke, Peter; Tech, Maike; Morgenstern, Burkhard; Merkl, Rainer

2004-01-01

Background Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. Results We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. Conclusions We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems. PMID:15511290

Evaluation of various carbon blacks and dispersing agents for use in the preparation of uranium microspheres with carbon

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

Hunt, Rodney Dale; Johnson, Jared A.; Collins, Jack Lee

A comparison study on carbon blacks and dispersing agents was performed to determine their impacts on the final properties of uranium fuel kernels with carbon. The main target compositions in this internal gelation study were 10 and 20 mol % uranium dicarbide (UC 2), which is UC 1.86, with the balance uranium dioxide. After heat treatment at 1900 K in flowing carbon monoxide in argon for 12 h, the density of the kernels produced using a X-energy proprietary carbon suspension, which is commercially available, ranged from 96% to 100% of theoretical density (TD), with full conversion of UC to UCmore » 2 at both carbon concentrations. However, higher carbon concentrations such as a 2.5 mol ratio of carbon to uranium in the feed solutions failed to produce gel spheres with the proprietary carbon suspension. The kernels using our former baseline of Mogul L carbon black and Tamol SN were 90–92% of TD with full conversion of UC to UC 2 at a variety of carbon levels. Raven 5000 carbon black and Tamol SN were used to produce 10 mol % UC2 kernels with 95% of TD. However, an increase in the Raven 5000 concentration led to a kernel density below 90% of TD. Raven 3500 carbon black and Tamol SN were used to make very dense kernels without complete conversion to UC 2. Lastly, the selection of the carbon black and dispersing agent is highly dependent on the desired final properties of the target kernels.« less

Evaluation of various carbon blacks and dispersing agents for use in the preparation of uranium microspheres with carbon

NASA Astrophysics Data System (ADS)

Hunt, R. D.; Johnson, J. A.; Collins, J. L.; McMurray, J. W.; Reif, T. J.; Brown, D. R.

2018-01-01

A comparison study on carbon blacks and dispersing agents was performed to determine their impacts on the final properties of uranium fuel kernels with carbon. The main target compositions in this internal gelation study were 10 and 20 mol % uranium dicarbide (UC2), which is UC1.86, with the balance uranium dioxide. After heat treatment at 1900 K in flowing carbon monoxide in argon for 12 h, the density of the kernels produced using a X-energy proprietary carbon suspension, which is commercially available, ranged from 96% to 100% of theoretical density (TD), with full conversion of UC to UC2 at both carbon concentrations. However, higher carbon concentrations such as a 2.5 mol ratio of carbon to uranium in the feed solutions failed to produce gel spheres with the proprietary carbon suspension. The kernels using our former baseline of Mogul L carbon black and Tamol SN were 90-92% of TD with full conversion of UC to UC2 at a variety of carbon levels. Raven 5000 carbon black and Tamol SN were used to produce 10 mol % UC2 kernels with 95% of TD. However, an increase in the Raven 5000 concentration led to a kernel density below 90% of TD. Raven 3500 carbon black and Tamol SN were used to make very dense kernels without complete conversion to UC2. The selection of the carbon black and dispersing agent is highly dependent on the desired final properties of the target kernels.

Evaluation of various carbon blacks and dispersing agents for use in the preparation of uranium microspheres with carbon

DOE PAGES

Hunt, Rodney Dale; Johnson, Jared A.; Collins, Jack Lee; ...

2017-10-12

A comparison study on carbon blacks and dispersing agents was performed to determine their impacts on the final properties of uranium fuel kernels with carbon. The main target compositions in this internal gelation study were 10 and 20 mol % uranium dicarbide (UC 2), which is UC 1.86, with the balance uranium dioxide. After heat treatment at 1900 K in flowing carbon monoxide in argon for 12 h, the density of the kernels produced using a X-energy proprietary carbon suspension, which is commercially available, ranged from 96% to 100% of theoretical density (TD), with full conversion of UC to UCmore » 2 at both carbon concentrations. However, higher carbon concentrations such as a 2.5 mol ratio of carbon to uranium in the feed solutions failed to produce gel spheres with the proprietary carbon suspension. The kernels using our former baseline of Mogul L carbon black and Tamol SN were 90–92% of TD with full conversion of UC to UC 2 at a variety of carbon levels. Raven 5000 carbon black and Tamol SN were used to produce 10 mol % UC2 kernels with 95% of TD. However, an increase in the Raven 5000 concentration led to a kernel density below 90% of TD. Raven 3500 carbon black and Tamol SN were used to make very dense kernels without complete conversion to UC 2. Lastly, the selection of the carbon black and dispersing agent is highly dependent on the desired final properties of the target kernels.« less

Validation of commercial business lists as a proxy for licensed alcohol outlets.

PubMed

Carlos, Heather A; Gabrielli, Joy; Sargent, James D

2017-05-19

Studies of retail alcohol outlets are restricted to regions due to lack of U.S. national data. Commercial business lists (BL) offer a possible solution, but no data exists to determine if BLs could serve as an adequate proxy for license data. This paper compares geospatial measures of alcohol outlets derived from a commercial BL with license data for a large US state. We validated BL data as a measure of off-premise alcohol outlet density and proximity compared to license data for 5528 randomly selected California residential addresses. We calculated three proximity measures (Euclidean distance, road network travel time and distance) and two density measures (kernel density estimation and the count within a 2-mile radius) for each dataset. The data was acquired in 2015 and processed and analyzed in 2015 and 2016. Correlations and reliabilities between density (correlation 0.98; Cronbach's α 0.97-0.99) and proximity (correlations 0.77-0.86; α 0.87-0.92) measures were high. For proximity, BL data matched license in 55-57% of addresses, overstated distance in 19%, and understated in 24-26%. BL data can serve as a reliable proxy for licensed alcohol outlets, thus extending the work that can be performed in studies on associations between retail alcohol outlets and drinking outcomes.

Ward's area location, physical activity, and body composition in 8- and 9-year-old boys and girls.

PubMed

Cardadeiro, Graça; Baptista, Fátima; Zymbal, Vera; Rodrigues, Luís A; Sardinha, Luís B

2010-11-01

Bone strength is the result of its material composition and structural design, particularly bone mass distribution. The purpose of this study was to analyze femoral neck bone mass distribution by Ward's area location and its relationship with physical activity (PA) and body composition in children 8 and 9 years of age. The proximal femur shape was defined by geometric morphometric analysis in 88 participants (48 boys and 40 girls). Using dual-energy X-ray absorptiometry (DXA) images, 18 landmarks were digitized to define the proximal femur shape and to identify Ward's area position. Body weight, lean and fat mass, and bone mineral were assessed by DXA, PA by accelerometry, and bone age by the Tanner-Whitehouse III method. Warps analysis with Thin-Plate Spline software showed that the first axis explained 63% of proximal femur shape variation in boys and 58% in girls. Most of this variation was associated with differences in Ward's area location, from the central zone to the superior aspect of the femoral neck in both genders. Regression analysis demonstrated that body composition explained 4% to 7% of the proximal femur shape variation in girls. In boys, body composition variables explained a similar amount of variance, but moderate plus vigorous PA (MVPA) also accounted for 6% of proximal femur shape variation. In conclusion, proximal femur shape variation in children ages 8 and 9 was due mainly to differences in Ward's area position determined, in part, by body composition in both genders and by MVPA in boys. These variables were positively associated with a central Ward's area and thus with a more balanced femoral neck bone mass distribution. © 2010 American Society for Bone and Mineral Research.

Tumour model with intrusive morphology, progressive phenotypical heterogeneity and memory

NASA Astrophysics Data System (ADS)

Atangana, Abdon; Alqahtani, Rubayyi T.

2018-03-01

The model of a tumour, taking into account invasive morphology, progressive phenotypical heterogeneity and also memory, is developed and analyzed in this paper. Three models are investigated: first we consider the model describing the proliferation concentrates in proximity of tumour boundaries, in which the oxygen levels are pronounced. Then we consider the model where the oxygen around the tumour is considered to be unchanged by the vascular system. Finally, we investigate the model of growth of tumours using the concept of non-local operators with the Mittag-Leffler kernel. We provide the numerical solution using the extended 3/8 Simpson method for the new trends of fractional integration for the proliferation concentrates in the proximity of the tumour model. Then we provide the exact solutions of the Gompertz model with three different fractional differentiations involving power law, exponential decay law and the Mittag-Leffler law.

Common relationships among proximate composition components in fishes

USGS Publications Warehouse

Hartman, K.J.; Margraf, F.J.

2008-01-01

Relationships between the various body proximate components and dry matter content were examined for five species of fishes, representing anadromous, marine and freshwater species: chum salmon Oncorhynchus keta, Chinook salmon Oncorhynchus tshawytscha, brook trout Salvelinus fontinalis, bluefish Pomatomus saltatrix and striped bass Morone saxatilis. The dry matter content or per cent dry mass of these fishes can be used to reliably predict the per cent composition of the other components. Therefore, with validation it is possible to estimate fat, protein and ash content of fishes from per cent dry mass information, reducing the need for costly and time-consuming laboratory proximate analysis. This approach coupled with new methods of non-lethal estimation of per cent dry mass, such as from bioelectrical impedance analysis, can provide non-destructive measurements of proximate composition of fishes. ?? 2008 The Authors.

Characteristics of uranium carbonitride microparticles synthesized using different reaction conditions

NASA Astrophysics Data System (ADS)

Silva, Chinthaka M.; Lindemer, Terrence B.; Voit, Stewart R.; Hunt, Rodney D.; Besmann, Theodore M.; Terrani, Kurt A.; Snead, Lance L.

2014-11-01

Three sets of experimental conditions were tested to synthesize uranium carbonitride (UC1-xNx) kernels from gel-derived urania-carbon microspheres. Primarily, three sequences of gases were used, N2 to N2-4%H2 to Ar, Ar to N2 to Ar, and Ar-4%H2 to N2-4%H2 to Ar-4%H2. Physical and chemical characteristics such as geometrical density, phase purity, and chemical compositions of the synthesized UC1-xNx were measured. Single-phase kernels were commonly obtained with densities generally ranging from 85% to 93% TD and values of x as high as 0.99. In-depth analysis of the microstrutures of UC1-xNx has been carried out and is discussed with the objective of large batch fabrication of high density UC1-xNx kernels.

Chlorogenic acid and maize ear rot resistance: a dynamic study investigating Fusarium graminearum development, deoxynivalenol production, and phenolic acid accumulation.

PubMed

Atanasova-Penichon, Vessela; Pons, Sebastien; Pinson-Gadais, Laetitia; Picot, Adeline; Marchegay, Gisèle; Bonnin-Verdal, Marie-Noelle; Ducos, Christine; Barreau, Christian; Roucolle, Joel; Sehabiague, Pierre; Carolo, Pierre; Richard-Forget, Florence

2012-12-01

Fusarium graminearum is the causal agent of Gibberella ear rot and produces trichothecene mycotoxins. Basic questions remain unanswered regarding the kernel stages associated with trichothecene biosynthesis and the kernel metabolites potentially involved in the regulation of trichothecene production in planta. In a two-year field study, F. graminearum growth, trichothecene accumulation, and phenolic acid composition were monitored in developing maize kernels of a susceptible and a moderately resistant variety using quantitative polymerase chain reaction and liquid chromatography coupled with photodiode array or mass spectrometry detection. Infection started as early as the blister stage and proceeded slowly until the dough stage. Then, a peak of trichothecene accumulation occurred and infection progressed exponentially until the final harvest time. Both F. graminearum growth and trichothecene production were drastically reduced in the moderately resistant variety. We found that chlorogenic acid is more abundant in the moderately resistant variety, with levels spiking in the earliest kernel stages induced by Fusarium infection. This is the first report that precisely describes the kernel stage associated with the initiation of trichothecene production and provides in planta evidence that chlorogenic acid may play a role in maize resistance to Gibberella ear rot and trichothecene accumulation.

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

Pavlou, A. T.; Betzler, B. R.; Burke, T. P.

Uncertainties in the composition and fabrication of fuel compacts for the Fort St. Vrain (FSV) high temperature gas reactor have been studied by performing eigenvalue sensitivity studies that represent the key uncertainties for the FSV neutronic analysis. The uncertainties for the TRISO fuel kernels were addressed by developing a suite of models for an 'average' FSV fuel compact that models the fuel as (1) a mixture of two different TRISO fuel particles representing fissile and fertile kernels, (2) a mixture of four different TRISO fuel particles representing small and large fissile kernels and small and large fertile kernels and (3)more » a stochastic mixture of the four types of fuel particles where every kernel has its diameter sampled from a continuous probability density function. All of the discrete diameter and continuous diameter fuel models were constrained to have the same fuel loadings and packing fractions. For the non-stochastic discrete diameter cases, the MCNP compact model arranged the TRISO fuel particles on a hexagonal honeycomb lattice. This lattice-based fuel compact was compared to a stochastic compact where the locations (and kernel diameters for the continuous diameter cases) of the fuel particles were randomly sampled. Partial core configurations were modeled by stacking compacts into fuel columns containing graphite. The differences in eigenvalues between the lattice-based and stochastic models were small but the runtime of the lattice-based fuel model was roughly 20 times shorter than with the stochastic-based fuel model. (authors)« less

Characteristics and composition of watermelon, pumpkin, and paprika seed oils and flours.

PubMed

El-Adawy, T A; Taha, K M

2001-03-01

The nutritional quality and functional properties of paprika seed flour and seed kernel flours of pumpkin and watermelon were studied, as were the characteristics and structure of their seed oils. Paprika seed and seed kernels of pumpkin and watermelon were rich in oil and protein. All flour samples contained considerable amounts of P, K, Mg, Mn, and Ca. Paprika seed flour was superior to watermelon and pumpkin seed kernel flours in content of lysine and total essential amino acids. Oil samples had high amounts of unsaturated fatty acids with linoleic and oleic acids as the major acids. All oil samples fractionated into seven classes including triglycerides as a major lipid class. Data obtained for the oils' characteristics compare well with those of other edible oils. Antinutritional compounds such as stachyose, raffinose, verbascose, trypsin inhibitor, phytic acid, and tannins were detected in all flours. Pumpkin seed kernel flour had higher values of chemical score, essential amino acid index, and in vitro protein digestibility than the other flours examined. The first limiting amino acid was lysine for both watermelon and pumpkin seed kernel flours, but it was leucine in paprika seed flour. Protein solubility index, water and fat absorption capacities, emulsification properties, and foam stability were excellent in watermelon and pumpkin seed kernel flours and fairly good in paprika seed flour. Flour samples could be potentially added to food systems such as bakery products and ground meat formulations not only as a nutrient supplement but also as a functional agent in these formulations.

Relative ratios of collagen composition of periarticular tissue of joints of the upper limb.

PubMed

Cheah, A; Harris, A; Le, W; Huang, Y; Yao, J

2017-07-01

We investigated the relative ratios of collagen composition of periarticular tissue of the elbow, wrist, metacarpophalangeal, proximal and distal interphalangeal joints. Periarticulat tissue, which we defined as the ligaments, palmar plate and capsule, was harvested from ten fresh-frozen cadaveric upper limbs, yielding 50 samples. The mean paired differences (95% confidence interval) of the relative ratios of collagen between the five different joints were estimated using mRNA expression of collagen in the periarticular tissue. We found that the relative collagen composition of the elbow was not significantly different to that of the proximal interphalangeal joint, nor between the proximal interphalangeal joint and distal interphalangeal joint, whereas the differences in collagen composition between all the other paired comparisons of the joints had confidence intervals that did not include zero.

Mango kernel starch-gum composite films: Physical, mechanical and barrier properties.

PubMed

Nawab, Anjum; Alam, Feroz; Haq, Muhammad Abdul; Lutfi, Zubala; Hasnain, Abid

2017-05-01

Composite films were developed by the casting method using mango kernel starch (MKS) and guar and xanthan gums. The concentration of both gums ranged from 0% to 30% (w/w of starch; db). Mechanical properties, oxygen permeability (OP), water vapor permeability (WVP), solubility in water and color parameters of composite films were evaluated. The crystallinity and homogeneity between the starch and gums were also evaluated by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The scanning electron micrographs showed homogeneous matrix, with no signs of phase separation between the components. XRD analysis demonstrated diminished crystalline peak. Regardless of gum type the tensile strength (TS) of composite films increased with increasing gum concentration while reverse trend was noted for elongation at break (EAB) which found to be decreased with increasing gum concentration. The addition of both guar and xanthan gums increased solubility and WVP of the composite films. However, the OP was found to be lower than that of the control with both gums. Furthermore, addition of both gums led to changes in transparency and opacity of MKS films. Films containing 10% (w/w) xanthan gum showed lower values for solubility, WVP and OP, while film containing 20% guar gum showed good mechanical properties. Copyright © 2017 Elsevier B.V. All rights reserved.

Production of Low Enriched Uranium Nitride Kernels for TRISO Particle Irradiation Testing

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

McMurray, J. W.; Silva, C. M.; Helmreich, G. W.

2016-06-01

A large batch of UN microspheres to be used as kernels for TRISO particle fuel was produced using carbothermic reduction and nitriding of a sol-gel feedstock bearing tailored amounts of low-enriched uranium (LEU) oxide and carbon. The process parameters, established in a previous study, produced phasepure NaCl structure UN with dissolved C on the N sublattice. The composition, calculated by refinement of the lattice parameter from X-ray diffraction, was determined to be UC 0.27N 0.73. The final accepted product weighed 197.4 g. The microspheres had an average diameter of 797±1.35 μm and a composite mean theoretical density of 89.9±0.5% formore » a solid solution of UC and UN with the same atomic ratio; both values are reported with their corresponding calculated standard error.« less

Pecan walnut (Carya illinoinensis (Wangenh.) K. Koch) oil quality and phenolic compounds as affected by microwave and conventional roasting.

PubMed

Juhaimi, Fahad Al; Özcan, Mehmet Musa; Uslu, Nurhan; Doğu, Süleyman

2017-12-01

In this study, the effects of conventional and microwave roasting on phenolic compounds, free acidity, peroxide value, fatty acid composition and tocopherol content of pecan walnut kernel and oil was investigated. The oil content of pecan kernels was 73.78% for microwave oven roasted at 720 W and 73.56% for conventional oven roasted at 110 °C. The highest free fatty acid content (0.50%) and the lowest peroxide value (2.48 meq O 2 /kg) were observed during microwave roasting at 720 W. The fatty acid profiles and tocopherol contents of pecan kernel oils did not show significant differences compared to raw samples. Roasting process in microwave oven at 720 W caused the reduction of some phenolic compounds, while the content of gallic acid exhibited a significant increase.

The correlation of chemical and physical corn kernel traits with production performance in broiler chickens and laying hens.

PubMed

Moore, S M; Stalder, K J; Beitz, D C; Stahl, C H; Fithian, W A; Bregendahl, K

2008-04-01

A study was conducted to determine the influence on broiler chicken growth and laying hen performance of chemical and physical traits of corn kernels from different hybrids. A total of 720 male 1-d-old Ross-308 broiler chicks were allotted to floor pens in 2 replicated experiments with a randomized complete block design. A total of 240 fifty-two-week-old Hy-Line W-36 laying hens were allotted to cages in a randomized complete block design. Corn-soybean meal diets were formulated for 3 broiler growth phases and one 14-wk-long laying hen phase to be marginally deficient in Lys and TSAA to allow for the detection of differences or correlations attributable to corn kernel chemical or physical traits. The broiler chicken diets were also marginally deficient in Ca and nonphytate P. Within a phase, corn- and soybean-based diets containing equal amounts of 1 of 6 different corn hybrids were formulated. The corn hybrids were selected to vary widely in chemical and physical traits. Feed consumption and BW were recorded for broiler chickens every 2 wk from 0 to 6 wk of age. Egg production was recorded daily, and feed consumption and egg weights were recorded weekly for laying hens between 53 and 67 wk of age. Physical and chemical composition of kernels was correlated with performance measures by multivariate ANOVA. Chemical and physical kernel traits were weakly correlated with performance in broiler chickens from 0 to 2 wk of age (P<0.05, | r |<0.42). However, from 4 to 6 wk of age and 0 to 6 wk of age, only kernel chemical traits were correlated with broiler chicken performance (P<0.05, | r |<0.29). From 53 to 67 wk of age, correlations were observed between both kernel physical and chemical traits and laying hen performance (P<0.05, | r |<0.34). In both experiments, the correlations of performance measures with individual kernel chemical and physical traits for any single kernel trait were not large enough to base corn hybrid selection on for feeding poultry.

A locally adaptive kernel regression method for facies delineation

NASA Astrophysics Data System (ADS)

Fernàndez-Garcia, D.; Barahona-Palomo, M.; Henri, C. V.; Sanchez-Vila, X.

2015-12-01

Facies delineation is defined as the separation of geological units with distinct intrinsic characteristics (grain size, hydraulic conductivity, mineralogical composition). A major challenge in this area stems from the fact that only a few scattered pieces of hydrogeological information are available to delineate geological facies. Several methods to delineate facies are available in the literature, ranging from those based only on existing hard data, to those including secondary data or external knowledge about sedimentological patterns. This paper describes a methodology to use kernel regression methods as an effective tool for facies delineation. The method uses both the spatial and the actual sampled values to produce, for each individual hard data point, a locally adaptive steering kernel function, self-adjusting the principal directions of the local anisotropic kernels to the direction of highest local spatial correlation. The method is shown to outperform the nearest neighbor classification method in a number of synthetic aquifers whenever the available number of hard data is small and randomly distributed in space. In the case of exhaustive sampling, the steering kernel regression method converges to the true solution. Simulations ran in a suite of synthetic examples are used to explore the selection of kernel parameters in typical field settings. It is shown that, in practice, a rule of thumb can be used to obtain suboptimal results. The performance of the method is demonstrated to significantly improve when external information regarding facies proportions is incorporated. Remarkably, the method allows for a reasonable reconstruction of the facies connectivity patterns, shown in terms of breakthrough curves performance.

Amino acid and proximate composition of fish bone gelatin from different warm-water species: A comparative study

NASA Astrophysics Data System (ADS)

Atma, Y.

2017-03-01

Research on fish bone gelatin has been increased in the last decade. The quality of gelatin depends on its physicochemical properties. Fish bone gelatin from warm-water fishes has a superior amino acid composition than cold-water fishes. The composition of amino acid can determine the strength and stability of gelatin. Thus, it is important to analyze the composition of amino acid as well as proximate composition for potential gelatin material. The warm water fish species used in this study were Grass carp, Pangasius catfish, Catfish, Lizard fish, Tiger-toothed croaker, Pink perch, Red snapper, Brown spotted grouper, and King weakfish. There werre five dominant amino acid in fish bone gelatin including glycine (21.2-36.7%), proline (8.7-11.7%), hydroxyproline (5.3-9.6%), alanine (8.48-12.9%), and glutamic acid (7.23-10.15%). Different warm-water species has some differences in amino acid composition. The proximate composition showed that fishbone gelatin from Pangasius catfish has the highest protein content. The water composition of all fishbone gelatin was well suited to the standard. Meanwhile, based on ash content, only gelatin from gelatin Pangasius catfish met the standard for food industries.

Determination of Proximate, Minerals, Vitamin and Anti-Nutrients Composition of Solanum verbascifolium Linn.

NASA Astrophysics Data System (ADS)

Sam, S. M.; Udosen, I. R.; Mensah, S. I.

2012-07-01

The proximate, minerals, vitamins and anti-nutrients composition of Solanum verbascifolium Linn were determined. The proximate composition showed that moisture content was (85.5%), protein was (32.55%), lipid was (2.90%), ash was (7.20%), fibre was (4.80%), carbohydrate was (52.55%) and caloric value was (366.50%) respectively. This was found to be rich in protein and considerably high amount of carbohydrate. The anti-nutrient composition analysis revealed the presence of hydrocyanide (1.39mg/100g), Oxalate (114.40mg/100g), all of which are below toxic level except for oxalic acid. For mineral and vitamin compositions, potassium was significantly (P>0.05) higher than iron, sodium, calcium and phosphorus while vitamin A retinol was (371.72mg/100g) and vitamin C ascorbic acid (39.99mg/100g). Based on these findings the plant is recommended for consumption and for further investigation as a potential raw material for pharmaceutical industry.

Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions

PubMed Central

Ruan, Peiying; Hayashida, Morihiro; Maruyama, Osamu; Akutsu, Tatsuya

2013-01-01

Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes. PMID:23776458

Electron-beam irradiation effects on phytochemical constituents and antioxidant capacity of pecan kernels [ Carya illinoinensis (Wangenh.) K. Koch] during storage.

PubMed

Villarreal-Lozoya, Jose E; Lombardini, Leonardo; Cisneros-Zevallos, Luis

2009-11-25

Pecans kernels (Kanza and Desirable cultivars) were irradiated with 0, 1.5, and 3.0 kGy using electron-beam (E-beam) irradiation and stored under accelerated conditions [40 degrees C and 55-60% relative humidity (RH)] for 134 days. Antioxidant capacity (AC) using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and oxygen radical absorbance capacity (ORAC) assays, phenolic (TP) and condensed tannin (CT) content, high-performance liquid chromatography (HPLC) phenolic profile, tocopherol content, peroxide value (PV), and fatty acid profiles were determined during storage. Irradiation decreased TP and CT with no major detrimental effects in AC. Phenolic profiles after hydrolysis were similar among treatments (e.g., gallic and ellagic acid, catechin, and epicatechin). Tocopherol content decreased with irradiation (>21 days), and PV increased at later stages (>55 days), with no change in fatty acid composition among treatments. Color lightness decreased, and a reddish brown hue developed during storage. A proposed mechanism of kernel oxidation is presented, describing the events taking place. In general, E-beam irradiation had slight effects on phytochemical constituents and could be considered a potential tool for pecan kernel decontamination.

Proximate composition, antihypertensive and antioxidative properties of the semimembranosus muscle from pork and beef after cooking and in vitro digestion.

PubMed

Jensen, Ida-Johanne; Dort, Junio; Eilertsen, Karl-Erik

2014-02-01

The aims of this study were to evaluate and compare proximate composition, antihypertensive activity and antioxidative capacity of the semimembranosus muscle from pork and beef and to study how these characteristics were affected by household preparation and subsequent digestion. The proximate composition was similar between pork and beef. Both pork and beef contained protein with the essential amino acids. Cooking in a heated pan did not affect the retention of lipid or sum of amino acids, but reduced the amount of the free amino acid taurine. The antihypertensive effect did not differ significantly between pork and beef, whereas the antioxidative capacity did. Cooking affected the antioxidative capacity negatively. The results from this study show that pork and beef are equally good sources of protein and bioactive properties, and whereas the nutritional composition is not affected, bioactive properties may be reduced after household preparations. © 2013.

[Composition of chicken and quail eggs].

PubMed

Closa, S J; Marchesich, C; Cabrera, M; Morales, J C

1999-06-01

Qualified food composition data on lipids composition are needed to evaluate intakes as a risk factor in the development of heart disease. Proximal composition, cholesterol and fatty acid content of chicken and quail eggs, usually consumed or traded, were analysed. Proximal composition were determined using AOAC (1984) specific techniques; lipids were extracted by a Folch's modified technique and cholesterol and fatty acids were determined by gas chromatography. Results corroborate the stability of eggs composition. Cholesterol content of quail eggs is similar to chicken eggs, but it is almost the half content of data registered in Handbook 8. Differences may be attributed to the analytical methodology used to obtain them. This study provides data obtained with up-date analytical techniques and accessory information useful for food composition tables.

Genetic mapping of new seed-expressed polyphenol oxidase genes in wheat (Triticum aestivum L.).

PubMed

Beecher, Brian S; Carter, Arron H; See, Deven R

2012-05-01

Polyphenol oxidase (PPO) enzymatic activity is a major cause in time-dependent discoloration in wheat dough products. The PPO-A1 and PPO-D1 genes have been shown to contribute to wheat kernel PPO activity. Recently a novel PPO gene family consisting of the PPO-A2, PPO-B2, and PPO-D2 genes has been identified and shown to be expressed in wheat kernels. In this study, the sequences of these five kernel PPO genes were determined for the spring wheat cultivars Louise and Penawawa. The two cultivars were found to be polymorphic at each of the PPO loci. Three novel alleles were isolated from Louise. The Louise X Penawawa mapping population was used to genetically map all five PPO genes. All map to the long arm of homeologous group 2 chromosomes. PPO-A2 was found to be located 8.9 cM proximal to PPO-A1 on the long arm of chromosome 2A. Similarly, PPO-D1 and PPO-D2 were separated by 10.7 cM on the long arm of chromosome 2D. PPO-B2 mapped to the long arm of chromosome 2B and was the site of a novel QTL for polyphenol oxidase activity. Five other PPO QTL were identified in this study. One QTL corresponds to the previously described PPO-D1 locus, one QTL corresponds to the PPO-D2 locus, whereas the remaining three are located on chromosome 2B.

Composite Material Hazard Assessment at Crash Sites

DTIC Science & Technology

2015-01-01

advanced composite materials. All personnel involved in rescue in close crash-site proximity are required to wear self -contained breathing apparatus...close crash-site proximity are required to wear self -contained breathing apparatus, chemical protective clothing, leather gloves, and neoprene...Take extra precaution when handling these materials. Nitrile rubber gloves can be worn underneath the leather gloves to provide chemical hazard

Antioxidant properties, physico-chemical characteristics and proximate composition of five wild fruits of Manipur, India.

PubMed

Sharma, Ph Baleshwor; Handique, Pratap Jyoti; Devi, Huidrom Sunitibala

2015-02-01

Antioxidant properties, physico-chemical characteristics and proximate composition of five wild fruits viz., Garcinia pedunculata, Garcinia xanthochymus, Docynia indica, Rhus semialata and Averrhoa carambola grown in Manipur, India were presented in the current study. The order of the antioxidant activity and reducing power of the fruit samples was found as R. semialata > D. indica > G. xanthochymus > A. carambola > G. pedunculata. Good correlation coefficient (R(2) > 0.99) was found among the three methods applied to determine antioxidant activity. Total phenolic content was positively correlated (R(2) = 0.960) with the antioxidant activity however, total flavonoid content was not positively correlated with the antioxidant activity. Physico-chemical and proximate composition of these fruits is documented for the first time.

Fatty acid, triacylglycerol, phytosterol, and tocopherol variations in kernel oil of Malatya apricots from Turkey.

PubMed

Turan, Semra; Topcu, Ali; Karabulut, Ihsan; Vural, Halil; Hayaloglu, Ali Adnan

2007-12-26

The fatty acid, sn-2 fatty acid, triacyglycerol (TAG), tocopherol, and phytosterol compositions of kernel oils obtained from nine apricot varieties grown in the Malatya region of Turkey were determined ( P<0.05). The names of the apricot varieties were Alyanak (ALY), Cataloglu (CAT), Cöloglu (COL), Hacihaliloglu (HAC), Hacikiz (HKI), Hasanbey (HSB), Kabaasi (KAB), Soganci (SOG), and Tokaloglu (TOK). The total oil contents of apricot kernels ranged from 40.23 to 53.19%. Oleic acid contributed 70.83% to the total fatty acids, followed by linoleic (21.96%), palmitic (4.92%), and stearic (1.21%) acids. The s n-2 position is mainly occupied with oleic acid (63.54%), linoleic acid (35.0%), and palmitic acid (0.96%). Eight TAG species were identified: LLL, OLL, PLL, OOL+POL, OOO+POO, and SOO (where P, palmitoyl; S, stearoyl; O, oleoyl; and L, linoleoyl), among which mainly OOO+POO contributed to 48.64% of the total, followed by OOL+POL at 32.63% and OLL at 14.33%. Four tocopherol and six phytosterol isomers were identified and quantified; among these, gamma-tocopherol (475.11 mg/kg of oil) and beta-sitosterol (273.67 mg/100 g of oil) were predominant. Principal component analysis (PCA) was applied to the data from lipid components of apricot kernel oil in order to explore the distribution of the apricot variety according to their kernel's lipid components. PCA separated some varieties including ALY, COL, KAB, CAT, SOG, and HSB in one group and varieties TOK, HAC, and HKI in another group based on their lipid components of apricot kernel oil. So, in the present study, PCA was found to be a powerful tool for classification of the samples.

Two-stage autoignition and edge flames in a high pressure turbulent jet

DOE PAGES

Krisman, Alex; Hawkes, Evatt R.; Chen, Jacqueline H.

2017-07-04

A three-dimensional direct numerical simulation is conducted for a temporally evolving planar jet of n-heptane at a pressure of 40 atmospheres and in a coflow of air at 1100 K. At these conditions, n-heptane exhibits a two-stage ignition due to low- and high-temperature chemistry, which is reproduced by the global chemical model used in this study. The results show that ignition occurs in several overlapping stages and multiple modes of combustion are present. Low-temperature chemistry precedes the formation of multiple spatially localised high-temperature chemistry autoignition events, referred to as ‘kernels’. These kernels form within the shear layer and core ofmore » the jet at compositions with short homogeneous ignition delay times and in locations experiencing low scalar dissipation rates. An analysis of the kernel histories shows that the ignition delay time is correlated with the mixing rate history and that the ignition kernels tend to form in vortically dominated regions of the domain, as corroborated by an analysis of the topology of the velocity gradient tensor. Once ignited, the kernels grow rapidly and establish edge flames where they envelop the stoichiometric isosurface. A combination of kernel formation (autoignition) and the growth of existing burning surface (via edge-flame propagation) contributes to the overall ignition process. In conclusion, an analysis of propagation speeds evaluated on the burning surface suggests that although the edge-flame speed is promoted by the autoignitive conditions due to an increase in the local laminar flame speed, edge-flame propagation of existing burning surfaces (triggered initially by isolated autoignition kernels) is the dominant ignition mode in the present configuration.« less

Proximate composition and caloric content of eight Lake Michigan fishes

USGS Publications Warehouse

Rottiers, Donald V.; Tucker, Robert M.

1982-01-01

We measured the proximate composition (percentage lipid, water, fat-free dry material, ash) and caloric content of eight species of Lake Michigan fish: lake trout (Salvelinus namaycush), coho salmon (Oncorhynchus kisutch), lake whitefish (Coregonus clupeaformis), bloater (Coregonus hoyi), alewife (Alosa pseudoharengus), rainbow smelt (Osmerus mordax), deepwater sculpin (Myoxocephalus quadricornis), and slimy sculpin (Cottus cognatus). Except for alewives, proximate composition and caloric content did not differ significantly between males and females. And, for coho salmon, there was no significant difference in composition between fish collected in different years. Lipid and caloric content of lake trout increased directly with age. In all species examined, lipids and caloric contents were significantly lower in small, presumably immature, fish than in larger, older fish. Lipid content of lake trout, lake whitefish, and bloaters (range of means, 16-22%) was nearly 3 times higher than that of coho salmon, sculpins, rainbow smelt, and alewives (range of means, 5.2-7.0%). The mean caloric content ranged from 6.9 to 7.1 kcal/g for species high in lipids and from 5.8 to 6.3 kcal/g for species low in lipids. Although the caloric content of all species varied directly with lipid content and inversely with water content, an increase in lipid content did not always coincide with a proportional increase in caloric content when other components of fish composition were essentially unchanged. This observation suggests that the energy content of fish estimated from the proximate composition by using universal conversion factors may not necessarily be accurate.

Investigating light curve modulation via kernel smoothing. II. New additional modes in single-mode OGLE classical Cepheids

NASA Astrophysics Data System (ADS)

Süveges, Maria; Anderson, Richard I.

2018-04-01

Detailed knowledge of the variability of classical Cepheids, in particular their modulations and mode composition, provides crucial insight into stellar structure and pulsation. However, tiny modulations of the dominant radial-mode pulsation were recently found to be very frequent, possibly ubiquitous in Cepheids, which makes secondary modes difficult to detect and analyse, since these modulations can easily mask the potentially weak secondary modes. The aim of this study is to re-investigate the secondary mode content in the sample of OGLE-III and -IV single-mode classical Cepheids using kernel regression with adaptive kernel width for pre-whitening, instead of using a constant-parameter model. This leads to a more precise removal of the modulated dominant pulsation, and enables a more complete survey of secondary modes with frequencies outside a narrow range around the primary. Our analysis reveals that significant secondary modes occur more frequently among first overtone Cepheids than previously thought. The mode composition appears significantly different in the Large and Small Magellanic Clouds, suggesting a possible dependence on chemical composition. In addition to the formerly identified non-radial mode at P2 ≈ 0.6…0.65P1 (0.62-mode), and a cluster of modes with near-primary frequency, we find two more candidate non-radial modes. One is a numerous group of secondary modes with P2 ≈ 1.25P1, which may represent the fundamental of the 0.62-mode, supposed to be the first harmonic of an l ∈ {7, 8, 9} non-radial mode. The other new mode is at P2 ≈ 1.46P1, possibly analogous to a similar, rare mode recently discovered among first overtone RR Lyrae stars.

Analysis and Development of A Robust Fuel for Gas-Cooled Fast Reactors

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

Knight, Travis W.

2010-01-31

The focus of this effort was on the development of an advanced fuel for gas-cooled fast reactor (GFR) applications. This composite design is based on carbide fuel kernels dispersed in a ZrC matrix. The choice of ZrC is based on its high temperature properties and good thermal conductivity and improved retention of fission products to temperatures beyond that of traditional SiC based coated particle fuels. A key component of this study was the development and understanding of advanced fabrication techniques for GFR fuels that have potential to reduce minor actinide (MA) losses during fabrication owing to their higher vapor pressuresmore » and greater volatility. The major accomplishments of this work were the study of combustion synthesis methods for fabrication of the ZrC matrix, fabrication of high density UC electrodes for use in the rotating electrode process, production of UC particles by rotating electrode method, integration of UC kernels in the ZrC matrix, and the full characterization of each component. Major accomplishments in the near-term have been the greater characterization of the UC kernels produced by the rotating electrode method and their condition following the integration in the composite (ZrC matrix) following the short time but high temperature combustion synthesis process. This work has generated four journal publications, one conference proceeding paper, and one additional journal paper submitted for publication (under review). The greater significance of the work can be understood in that it achieved an objective of the DOE Generation IV (GenIV) roadmap for GFR Fuel—namely the demonstration of a composite carbide fuel with 30% volume fuel. This near-term accomplishment is even more significant given the expected or possible time frame for implementation of the GFR in the years 2030 -2050 or beyond.« less

Computational investigation of intense short-wavelength laser interaction with rare gas clusters

NASA Astrophysics Data System (ADS)

Bigaouette, Nicolas

Current Very High Temperature Reactor designs incorporate TRi-structural ISOtropic (TRISO) particle fuel, which consists of a spherical fissile fuel kernel surrounded by layers of pyrolytic carbon and silicon carbide. An internal sol-gel process forms the fuel kernel by dropping a cold precursor solution into a column of hot trichloroethylene (TCE). The temperature difference drives the liquid precursor solution to precipitate the metal solution into gel spheres before reaching the bottom of a production column. Over time, gelation byproducts inhibit complete gelation and the TCE must be purified or discarded. The resulting mixed-waste stream is expensive to dispose of or recycle, and changing the forming fluid to a non-hazardous alternative could greatly improve the economics of kernel production. Selection criteria for a replacement forming fluid narrowed a list of ~10,800 chemicals to yield ten potential replacements. The physical properties of the alternatives were measured as a function of temperature between 25 °C and 80 °C. Calculated terminal velocities and heat transfer rates provided an overall column height approximation. 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane were selected for further testing, and surrogate yttria-stabilized zirconia (YSZ) kernels were produced using these selected fluids. The kernels were characterized for density, geometry, composition, and crystallinity and compared to a control group of kernels produced in silicone oil. Production in 1-bromotetradecane showed positive results, producing dense (93.8 %TD) and spherical (1.03 aspect ratio) kernels, but proper gelation did not occur in the other alternative forming fluids. With many of the YSZ kernels not properly gelling within the length of the column, this project further investigated the heat transfer properties of the forming fluids and precursor solution. A sensitivity study revealed that the heat transfer properties of the precursor solution have the strongest impact on gelation time. A COMSOL heat transfer model estimated an effective thermal diffusivity range for the YSZ precursor solution as 1.13x10 -8 m2/s to 3.35x10-8 m 2/s, which is an order of magnitude smaller than the value used in previous studies. 1-bromotetradecane is recommended for further investigation with the production of uranium-based kernels.

Depth related trends in proximate composition of demersal fishes in the eastern North Pacific

NASA Astrophysics Data System (ADS)

Drazen, J. C.

2007-02-01

The proximate chemistry of the white muscle and liver of 18 species of demersal fish from the eastern North Pacific was studied to determine trends with depth, locomotory mode and buoyancy mechanism, foraging strategy and to elucidate energetic strategies. Data for 24 species from shallow water were taken from the literature and included for analysis of muscle water content. Benthopelagic species, primarily gadiforms, have significantly larger lipid-rich livers than benthic species. The benthopelagic species may use this lipid to add buoyancy, but it is also used as energy storage. Buoyancy mechanism was directly related to proximate composition. Fishes using gasbladders had normal muscle composition. The two species of benthopelagic fishes without gasbladders have either very high muscle lipid content ( Anoplopoma fimbria) or gelatinous muscle ( Alepocephalus tenobrosus) to aid in achieving neutral buoyancy. The macrourid, Albatrossia pectoralis, has a very small gasbladder and also has gelatinous muscle. Both of these benthopelagic fishes with gelatinous muscle feed on pelagic organisms. Gelatinous muscle was also found in two flatfishes that inhabit the oxygen minimum zone. For these fishes, high water content may serve to lower metabolic costs while maintaining large body size. Scavengers such as Coryphaenoides armatus and Coryphaenoides acrolepis have lipid rich livers and others such as A. fimbria and Pachycara sp. have high and variable muscle lipid content. Thus foraging mode also acts to influence proximate composition. Several depth-related trends in proximate composition were found. White muscle water content increased significantly with depth, and all four gelatinous species occurred at bathyal depths. This adds evidence in support of the hypothesis that decreasing light levels shorten reactive distances and relax the selective pressure for high locomotory capacity. In addition significant declines in liver protein content were observed, suggesting that the rates of metabolism in this organ also decline with depth. There was little evidence for food availability affecting proximate composition. There were no significant changes in either muscle or liver lipid or caloric density with depth. Total lipid stores actually increased significantly, but they were driven primarily by the abyssal scavenger C. armatus suggesting that foraging strategy rather than depth may be the most important factor determining total lipid stores.

Triacylglycerol and triterpene ester composition of shea nuts from seven African countries.

PubMed

Akihisa, Toshihiro; Kojima, Nobuo; Katoh, Naoko; Kikuchi, Takashi; Fukatsu, Makoto; Shimizu, Naoto; Masters, Eliot T

2011-01-01

The compositions of the triacylglycerol (TAG) and triterpene ester (TE) fractions of the kernel fats (n-hexane extracts; shea butter) of the shea tree (Vitellaria paradoxa; Sapotaceae) were determined for 36 samples from seven sub-Saharan countries, i.e., Cote d' Ivoire, Ghana, Nigeria, Cameroun, Chad, Sudan, and Uganda. The principal TAGs are stearic-oleic-stearic (SOS; mean 31.2%), SOO (27.7%), and OOO (10.8%). The TE fractions contents are in the range of 0.5-6.5%, and contain α-amyrin cinnamate (1c; mean 29.3%) as the predominant TE followed by butyrospermol cinnamate (4c; 14.8%), α-amyrin acetate (1a; 14.1%), lupeol cinnamate (3c; 9.0%), β-amyrin cinnamate (2c; 7.6%), lupeol acetate (3a; 7.2%), butyrospermol acetate (4a; 5.8%), and β-amyrin acetate (2a; 4.9%). Shea kernel fats from West African provenances contained, in general, higher levels of high-melting TAGs such as SOS, and higher amount of TEs than those from East African provenances. No striking regional difference in the composition of the TE fractions was observed. Copyright © 2011 by Japan Oil Chemists' Society

Approach to explosive hazard detection using sensor fusion and multiple kernel learning with downward-looking GPR and EMI sensor data

NASA Astrophysics Data System (ADS)

Pinar, Anthony; Masarik, Matthew; Havens, Timothy C.; Burns, Joseph; Thelen, Brian; Becker, John

2015-05-01

This paper explores the effectiveness of an anomaly detection algorithm for downward-looking ground penetrating radar (GPR) and electromagnetic inductance (EMI) data. Threat detection with GPR is challenged by high responses to non-target/clutter objects, leading to a large number of false alarms (FAs), and since the responses of target and clutter signatures are so similar, classifier design is not trivial. We suggest a method based on a Run Packing (RP) algorithm to fuse GPR and EMI data into a composite confidence map to improve detection as measured by the area-under-ROC (NAUC) metric. We examine the value of a multiple kernel learning (MKL) support vector machine (SVM) classifier using image features such as histogram of oriented gradients (HOG), local binary patterns (LBP), and local statistics. Experimental results on government furnished data show that use of our proposed fusion and classification methods improves the NAUC when compared with the results from individual sensors and a single kernel SVM classifier.

Effect of Temperature and Moisture on the Development of Concealed Damage in Raw Almonds (Prunus dulcis).

PubMed

Rogel-Castillo, Cristian; Zuskov, David; Chan, Bronte Lee; Lee, Jihyun; Huang, Guangwei; Mitchell, Alyson E

2015-09-23

Concealed damage (CD) is a brown discoloration of nutmeat that appears only after kernels are treated with moderate heat (e.g., roasting). Identifying factors that promote CD in almonds is of significant interest to the nut industry. Herein, the effect of temperature (35 and 45 °C) and moisture (<5, 8, and 11%) on the composition of volatiles in raw almonds (Prunus dulcis var. Nonpareil) was studied using HS-SPME-GC/MS. A CIE LCh colorimetric method was developed to identify raw almonds with CD. A significant increase in CD was demonstrated in almonds exposed to moisture (8% kernel moisture content) at 45 °C as compared to 35 °C. Elevated levels of volatiles related to lipid peroxidation and amino acid degradation were observed in almonds with CD. These results suggest that postharvest moisture exposure resulting in an internal kernel moisture ≥ 8% is a key factor in the development of CD in raw almonds and that CD is accelerated by temperature.

Chemical and functional properties of fibre concentrates obtained from by-products of coconut kernel.

PubMed

Yalegama, L L W C; Nedra Karunaratne, D; Sivakanesan, Ramiah; Jayasekara, Chitrangani

2013-11-01

The coconut kernel residues obtained after extraction of coconut milk (MR) and virgin coconut oil (VOR) were analysed for their potential as dietary fibres. VOR was defatted and treated chemically using three solvent systems to isolate coconut cell wall polysaccharides (CCWP). Nutritional composition of VOR, MR and CCWPs indicated that crude fibre, neutral detergent fibre, acid detergent fibre and hemicelluloses contents were higher in CCWPs than in VOR and MR. MR contained a notably higher content of fat than VOR and CCWPs. The oil holding capacity, water holding capacity and swelling capacity were also higher in CCWPs than in VOR and MR. All the isolates and MR and VOR had high metal binding capacities. The CCWPs when compared with commercially available fibre isolates, indicated improved dietary fibre properties. These results show that chemical treatment of coconut kernel by-products can enhance the performance of dietary fibre to yield a better product. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

McMurray, Jacob W.; Lindemer, Terrence B.; Brown, Nicholas R.

There are three important failure mechanisms that must be controlled in high-temperature gas-cooled reactor (HTGR) fuel for certain higher burnup applications are SiC layer rupture, SiC corrosion by CO, and coating compromise from kernel migration. All are related to high CO pressures stemming from free O generated when uranium present as UO 2 fissions and the O is not subsequently bound by other elements. Furthermore, in the HTGR UCO kernel design, CO buildup from excess O is controlled by the inclusion of additional uranium in the form of a carbide, UC x. An approach for determining the minimum UC xmore » content to ensure negligible CO formation was developed and demonstrated using CALPHAD models and the Serpent 2 reactor physics and depletion analysis tool. Our results are intended to be more accurate than previous estimates by including more nuclear and chemical factors, in particular the effect of transmutation products on the oxygen distribution as the fuel kernel composition evolves with burnup.« less

Influence of indigenous minor components on fat crystal network of fully hydrogenated palm kernel oil and fully hydrogenated coconut oil.

PubMed

Chai, Xiu-Hang; Meng, Zong; Cao, Pei-Rang; Liang, Xin-Yu; Piatko, Michael; Campbell, Shawn; Koon Lo, Seong; Liu, Yuan-Fa

2018-07-30

Purification of triglycerides from fully hydrogenated palm kernel oil (FHPKO) and fully hydrogenated coconut oil (FHCNO) was performed by a chromatographic method. Lipid composition, thermal properties, polymorphism, isothermal crystallization behaviour, nanostructure and microstructure of FHPKO, FHPKO-triacylglycerol (TAG), FHCNO and FHCNO-TAG were evaluated. Removal of minor components had no effect on triglycerides composition. However, the presence of the minor components did increase the slip melting point and promote onset of crystallization. Furthermore, the thickness of the nanoscale crystals increased, and polymorphic transformation from β' to β occurred in FHPKO after the removal of minor components, and from α to β' in FHCNO. Sharp changes in the values of the Avrami constant K and exponent n suggested that the presence of minor components changed the crystal growth mechanism. The PLM results indicated that a coarser crystal structure with lower fractal dimension appeared after the removal of minor components from both FHPKO and FHCNO. Copyright © 2018 Elsevier Ltd. All rights reserved.

QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management

PubMed Central

Zou, Jun; Iqbal, Muhammad; Chen, Hua; Asif, Mohammad; N’Diaye, Amidou; Navabi, Alireza; Perez-Lara, Enid; Pozniak, Curtis; Yang, Rong-Cai; Randhawa, Harpinder; Spaner, Dean

2017-01-01

Recently, we investigated the effect of the wheat 90K single nucleotide polymorphic (SNP) array and three gene-specific (Ppd-D1, Vrn-A1 and Rht-B1) markers on quantitative trait loci (QTL) detection in a recombinant inbred lines (RILs) population derived from a cross between two spring wheat (Triticum aestivum L.) cultivars, ‘Attila’ and ‘CDC Go’, and evaluated for eight agronomic traits at three environments under organic management. The objectives of the present study were to investigate the effect of conventional management on QTL detection in the same mapping population using the same set of markers as the organic management and compare the results with organic management. Here, we evaluated 167 RILs for number of tillers (tillering), flowering time, maturity, plant height, test weight (grain volume weight), 1000 kernel weight, grain yield, and grain protein content at seven conventionally managed environments from 2008 to 2014. Using inclusive composite interval mapping (ICIM) on phenotypic data averaged across seven environments and a subset of 1203 informative markers (1200 SNPs and 3 gene specific markers), we identified a total of 14 QTLs associated with flowering time (1), maturity (2), plant height (1), grain yield (1), test weight (2), kernel weight (4), tillering (1) and grain protein content (2). Each QTL individually explained from 6.1 to 18.4% of the phenotypic variance. Overall, the QTLs associated with each trait explained from 9.7 to 35.4% of the phenotypic and from 22.1 to 90.8% of the genetic variance. Three chromosomal regions on chromosomes 2D (61–66 cM), 4B (80–82 cM) and 5A (296–297 cM) harbored clusters of QTLs associated with two to three traits. The coincidental region on chromosome 5A harbored QTL clusters for both flowering and maturity time, and mapped about 2 cM proximal to the Vrn-A1 gene, which was in high linkage disequilibrium (0.70 ≤ r2 ≤ 0.75) with SNP markers that mapped within the QTL confidence interval. Six of the 14 QTLs (one for flowering time and plant height each, and two for maturity and kernel weight each) were common between the conventional and organic management systems, which suggests issues in directly utilizing gene discovery results based on conventional management to make in detail selection (decision) for organic management. PMID:28158253

Novel sorbent materials for environmental remediation via Pyrolysis of biomass

NASA Astrophysics Data System (ADS)

Zabaniotou, Anastasia

2013-04-01

One of the major challenges facing society at this moment is the transition from a non-sustainable, fossil resources-based economy to a sustainable bio-based economy. By producing multiple products, a biorefinery can take advantage of the differences in biomass components and intermediates and maximize the value derived from the biomass feedstock. The high-value products enhance profitability, the high-volume fuel helps meet national energy needs, and the power production reduces costs and avoids greenhouse-gas emissions From pyrolysis, besides gas and liquid products a solid product - char, is derived as well. This char contains the non converted carbon and can be used for activated carbon production and/or as additive in composite material production. Commercially available activated carbons are still considered expensive due to the use of non-renewable and relatively expensive starting material such as coal. The present study describes pyrolysis as a method to produce high added value carbon materials such as activated carbons (AC) from agricultural residues pyrolysis. Olive kernel has been investigated as the precursor of the above materials. The produced activated carbon was characterized by proximate and ultimate analyses, BET method and porosity estimation. Furthermore, its adsorption of pesticide compound in aqueous solution by was studied. Pyrolysis of olive kernel was conducted at 800 oC for 45min in a fixed reactor. For the production of the activated carbon the pyrolytic char was physically activated under steam in the presence of CO2 at 970oC for 3 h in a bench scale reactor. The active carbons obtained from both scales were characterized by N2 adsorption at 77 K, methyl-blue adsorption (MB adsorption) at room temperature and SEM analysis. Surface area and MB adsorption were found to increase with the degree of burn-off. The surface area of the activated carbons was found to increase up to 1500 m2/g at a burn-off level of 60-65wt.%, while SEM analysis showed the appearance of micropores to mesopores in the produced tire active carbons. Activated carbon prepared from olive kernel is a super active carbon and used as an adsorbent for the removal of pesticide from aqueous solutions (Bromopropylate). The higher removal achieved was 100% in 60 min. The produced activated carbon from agricultural residue was proved to be very effective for gas and water stream purification. Biomass can give a wide spectrum of fuels and materials in the integrated concept of biorefinery

Time reversal seismic imaging using laterally reflected surface waves in southern California

NASA Astrophysics Data System (ADS)

Tape, C.; Liu, Q.; Tromp, J.; Plesch, A.; Shaw, J. H.

2010-12-01

We use observed post-surface-wave seismic waveforms to image shallow (upper 10 km) lateral reflectors in southern California. Our imaging technique employs the 3D crustal model m16 of Tape et al. (2009), which is accurate for most local earthquakes over the period range 2-30 s. Model m16 captures the resonance of the major sedimentary basins in southern California, as well as some lateral surface wave reflections associated with these basins. We apply a 3D Gaussian smoothing function (12 km horizontal, 2 km vertical) to model m16. This smoothing has the effect of suppressing synthetic waveforms within the period range of interest (3-10 s) that are associated with reflections (single and multiple) from these basins. The smoothed 3D model serves as the background model within which we propagate an ``adjoint wavefield'' comprised of time-reversed windows of post-surface-wave coda waveforms that are initiated at the respective station locations. This adjoint wavefield constructively interferes with the regular wavefield in the locations of potential reflectors. The potential reflectors are revealed in an ``event kernel,'' which is the time-integrated volumetric field for each earthquake. By summing (or ``stacking'') the event kernels from 28 well-recorded earthquakes, we identify several reflectors using this imaging procedure. The most prominent lateral reflectors occur in proximity to: the southernmost San Joaquin basin, the Los Angeles basin, the San Pedro basin, the Ventura basin, the Manix basin, the San Clemente--Santa Cruz--Santa Barbara ridge, and isolated segments of the San Jacinto and San Andreas faults. The correspondence between observed coherent coda waveforms and the imaged reflectors provides a solid basis for interpreting the kernel features as material contrasts. The 3D spatial extent and amplitude of the kernel features provide constraints on the geometry and material contrast of the imaged reflectors.

Comparative Study of Raw and Boiled Silver Pomfret Fish from Coastal Area and Retail Market in Relation to Trace Metals and Proximate Composition

PubMed Central

Huque, Roksana; Munshi, M. Kamruzzaman; Khatun, Afifa; Islam, Mahfuza; Hossain, Afzal; Hossain, Arzina; Akter, Shirin; Kabir, Jamiul; Nahar Jolly, Yeasmin; Islam, Ashraful

2014-01-01

Trace metals concentration and proximate composition of raw and boiled silver pomfret (Pampus argenteus) from coastal area and retail market were determined to gain the knowledge of the risk and benefits associated with indiscriminate consumption of marine fishes. The effects of cooking (boiling) on trace metal and proximate composition of silver pomfret fish were also investigated. Trace element results were determined by the Energy Dispersive X-ray Fluorescence (EDXRF) Spectrometer wherein fish samples from both areas exceeded the standard limits set by FAO/WHO for manganese, lead, cadmiumm and chromium and boiling has no significant effects on these three metal concentrations. Long-term intake of these contaminated fish samples can pose a health risk to humans who consume them. PMID:26904650

Infrared microspectroscopic imaging of plant tissues: spectral visualization of Triticum aestivum kernel and Arabidopsis leaf microstructure

PubMed Central

Warren, Frederick J; Perston, Benjamin B; Galindez-Najera, Silvia P; Edwards, Cathrina H; Powell, Prudence O; Mandalari, Giusy; Campbell, Grant M; Butterworth, Peter J; Ellis, Peter R

2015-01-01

Infrared microspectroscopy is a tool with potential for studies of the microstructure, chemical composition and functionality of plants at a subcellular level. Here we present the use of high-resolution bench top-based infrared microspectroscopy to investigate the microstructure of Triticum aestivum L. (wheat) kernels and Arabidopsis leaves. Images of isolated wheat kernel tissues and whole wheat kernels following hydrothermal processing and simulated gastric and duodenal digestion were generated, as well as images of Arabidopsis leaves at different points during a diurnal cycle. Individual cells and cell walls were resolved, and large structures within cells, such as starch granules and protein bodies, were clearly identified. Contrast was provided by converting the hyperspectral image cubes into false-colour images using either principal component analysis (PCA) overlays or by correlation analysis. The unsupervised PCA approach provided a clear view of the sample microstructure, whereas the correlation analysis was used to confirm the identity of different anatomical structures using the spectra from isolated components. It was then demonstrated that gelatinized and native starch within cells could be distinguished, and that the loss of starch during wheat digestion could be observed, as well as the accumulation of starch in leaves during a diurnal period. PMID:26400058

Carbon partitioning between oil and carbohydrates in developing oat (Avena sativa L.) seeds.

PubMed

Ekman, Asa; Hayden, Daniel M; Dehesh, Katayoon; Bülow, Leif; Stymne, Sten

2008-01-01

Cereals accumulate starch in the endosperm as their major energy reserve in the grain. In most cereals the embryo, scutellum, and aleurone layer are high in oil, but these tissues constitute a very small part of the total seed weight. However, in oat (Avena sativa L.) most of the oil in kernels is deposited in the same endosperm cells that accumulate starch. Thus oat endosperm is a desirable model system to study the metabolic switches responsible for carbon partitioning between oil and starch synthesis. A prerequisite for such investigations is the development of an experimental system for oat that allows for metabolic flux analysis using stable and radioactive isotope labelling. An in vitro liquid culture system, developed for detached oat panicles and optimized to mimic kernel composition during different developmental stages in planta, is presented here. This system was subsequently used in analyses of carbon partitioning between lipids and carbohydrates by the administration of 14C-labelled sucrose to two cultivars having different amounts of kernel oil. The data presented in this study clearly show that a higher amount of oil in the high-oil cultivar compared with the medium-oil cultivar was due to a higher proportion of carbon partitioning into oil during seed filling, predominantly at the earlier stages of kernel development.

Retrobiosynthetic nuclear magnetic resonance analysis of amino acid biosynthesis and intermediary metabolism. Metabolic flux in developing maize kernels.

PubMed

Glawischnig, E; Gierl, A; Tomas, A; Bacher, A; Eisenreich, W

2001-03-01

Information on metabolic networks could provide the basis for the design of targets for metabolic engineering. To study metabolic flux in cereals, developing maize (Zea mays) kernels were grown in sterile culture on medium containing [U-(13)C(6)]glucose or [1,2-(13)C(2)]acetate. After growth, amino acids, lipids, and sitosterol were isolated from kernels as well as from the cobs, and their (13)C isotopomer compositions were determined by quantitative nuclear magnetic resonance spectroscopy. The highly specific labeling patterns were used to analyze the metabolic pathways leading to amino acids and the triterpene on a quantitative basis. The data show that serine is generated from phosphoglycerate, as well as from glycine. Lysine is formed entirely via the diaminopimelate pathway and sitosterol is synthesized entirely via the mevalonate route. The labeling data of amino acids and sitosterol were used to reconstruct the labeling patterns of key metabolic intermediates (e.g. acetyl-coenzyme A, pyruvate, phosphoenolpyruvate, erythrose 4-phosphate, and Rib 5-phosphate) that revealed quantitative information about carbon flux in the intermediary metabolism of developing maize kernels. Exogenous acetate served as an efficient precursor of sitosterol, as well as of amino acids of the aspartate and glutamate family; in comparison, metabolites formed in the plastidic compartments showed low acetate incorporation.

Trichothecene-Genotypes Play a Role in Fusarium Head Blight Disease Spread and Trichothecene Accumulation in Wheat

USDA-ARS?s Scientific Manuscript database

In the current study, we evaluated the impact of the observed North American evolutionary shift in the Fusarium graminearum complex on disease spread, kernel damage, and trichothecene accumulation in resistant and susceptible wheat genotypes. Four inocula were prepared using composites of F. gramin...

Genetic analysis of teosinte alleles for kernel composition traits in maize

USDA-ARS?s Scientific Manuscript database

Teosinte (Zea mays ssp. parviglumis) is the wild ancestor of modern maize (Zea mays ssp. mays). Teosinte contains greater genetic diversity compared to maize inbreds and landraces, but its use is limited by insufficient genetic resources to evaluate its value. A population of teosinte near isogenic ...

Functional and nutritional characteristics of soft wheat grown in no-till and conventional cropping systems

USDA-ARS?s Scientific Manuscript database

The effects of no-till vs. conventional farming practices were evaluated on soft wheat functional and nutritional characteristics, including kernel physical properties, whole wheat composition, antioxidant activity and end-product quality. Soft white winter wheat cv. ORCF 102 was evaluated over a tw...

Influence of restorative material and proximal cavity design on the fracture resistance of MOD inlay restoration.

PubMed

Liu, Xiaozhou; Fok, Alex; Li, Haiyan

2014-03-01

This study aimed to evaluate the effects of the restorative material and cavity design on the facture resistance of inlay restorations under a compressive load using acoustic emission (AE) measurement. Two restorative materials, a composite resin (MZ100, 3M ESPE) and a ceramic (IPS Empress CAD, Ivoclar Vivadent), and two cavity designs, non-proximal box and proximal box, were studied. Thirty-two extracted human third molars were selected and divided into 4 groups. The restorative materials and cavity designs used for the four groups were: (1) composite and non-proximal box; (2) ceramic and non-proximal box; (3) composite and proximal box; (4) ceramic and proximal box. The restored molars were loaded in a MTS machine via a loading head of diameter 10mm. The rate of loading was 0.1mm/min. During loading, an AE system was used to monitor the debonding and fracture of the specimens. The load corresponding to the first AE event, the final maximum load sustained, as well as the total number of AE events recorded were used to evaluate the fracture resistance of the restored teeth. For the initial fracture load, Group 2 (236.15N)Group 2 (1685)>Group 3 (239)>Group 1 (221). The differences from pairwise comparisons in the initial fracture load and final load were mostly insignificant statistically (p>0.05), the only exception being that between Groups 2 and 3 in the initial fracture load (p=0.039). For the total number of AE events, statistically significant differences (p<0.05) were found between all group pairs that involved different materials, with the composite groups giving much fewer AE events than the ceramic groups. Conversely, no statistically significant difference in the AE results was found between groups with the same material, irrespective of the cavity design. For teeth restored with MOD inlays, the use of composite resin as the restorative material may provide higher fracture resistance than using ceramic. Using a proximal box design for the cavity may further improve the fracture resistance of the inlay restoration, although the improvement was not statistically significant under axial compression. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

The influence of maturity of VMAC5 (Cocos nucifera L. ‘makapuno’) on its physicochemical, proximate composition and fatty acid profile

NASA Astrophysics Data System (ADS)

Leorna, M.; Israel, K. A.

2018-01-01

“Makapuno” is one of the promising commodities of the Philippines with good nutritional quality. VMAC5 is the most recent “makapuno” variety developed by the Visayas State University, Baybay City, Leyte, Philippines. Maximum utilization of this commodity is dependent on its thorough characterization. This study aimed to determine the influence of nut maturity on its physicochemical, proximate composition and fatty acid profile. Results revealed that VMAC5 nuts were affected by maturity. An 8-month old nuts exhibited heavier weight compared to mature nuts. The total sugar decreased with maturity. TSS and pH were not affected by maturity. Proximate composition were affected by maturity with moisture content of 59.17-86.88%, crude protein of 1.58-2.62%, crude fiber of 2.24-5.43% and crude fat of 3.06-12.14% of which >50% were medium chain fatty acids (MCFA).

Effects of whole-plant corn silage hybrid type on intake, digestion, ruminal fermentation, and lactation performance by dairy cows through a meta-analysis.

PubMed

Ferraretto, L F; Shaver, R D

2015-04-01

Understanding the effect of whole-plant corn silage (WPCS) hybrids in dairy cattle diets may allow for better decisions on hybrid selection by dairy producers, as well as indicate potential strategies for the seed corn industry with regard to WPCS hybrids. Therefore, the objective of this study was to perform a meta-analysis using literature data on the effects of WPCS hybrid type on intake, digestibility, rumen fermentation, and lactation performance by dairy cows. The meta-analysis was performed using a data set of 162 treatment means from 48 peer-reviewed articles published between 1995 and 2014. Hybrids were divided into 3 categories before analysis. Comparative analysis of WPCS hybrid types differing in stalk characteristics were in 4 categories: conventional, dual-purpose, isogenic, or low-normal fiber digestibility (CONS), brown midrib (BMR), hybrids with greater NDF but lower lignin (%NDF) contents or high in vitro NDF digestibility (HFD), and leafy (LFY). Hybrid types differing in kernel characteristics were in 4 categories: conventional or yellow dent (CONG), NutriDense (ND), high oil (HO), and waxy. Genetically modified (GM) hybrids were compared with their genetically similar non-biotech counterpart (ISO). Except for lower lignin content for BMR and lower starch content for HFD than CONS and LFY, silage nutrient composition was similar among hybrids of different stalk types. A 1.1 kg/d greater intake of DM and 1.5 and 0.05 kg/d greater milk and protein yields, respectively, were observed for BMR compared with CONS and LFY. Likewise, DMI and milk yield were greater for HFD than CONS, but the magnitude of the difference was smaller. Total-tract NDF digestibility was greater, but starch digestibility was reduced, for BMR and HFD compared with CONS or LFY. Silage nutrient composition was similar for hybrids of varied kernel characteristics, except for lower CP and EE content for CONG than ND and HO. Feeding HO WPCS to dairy cows decreased milk fat content and yield and protein content compared with the other kernel-type hybrids. Hybrids varying in kernel characteristics did not affect intake, milk production, or total-tract nutrient digestibilities by lactating dairy cows. Nutrient composition and lactation performance were similar between GM and ISO. Positive effects of BMR and HFD on intake and milk yield were observed for lactating dairy cows, but the reduced total-tract starch digestibility for these hybrids merits further study. Except for negative effects of HO on milk components, differences were minimal among corn silage hybrids differing in kernel type. Feeding GM WPCS did not affect lactation performance by dairy cows. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Formulation, sensory evaluation, proximate composition and storage stability of cassava strips produced from the composite flour of cassava and cowpea.

PubMed

Dada, Toluwase A; Barber, Lucretia I; Ngoma, Lubanza; Mwanza, Mulunda

2018-03-01

The study developed an acceptable formula for the production of cassava strips (a deep fried product) using composite flour of cassava/cowpea at four different levels of cowpea substitutions (100:0, 90:10, 80:20, and 70:30). Sensory properties, proximate composition, and shelf life at ambient temperature were determined. Proximate composition, shelf life, and microbial analysis were further done on the most preferred sample (80:20) and the control (100:0). Results showed a significant difference between the tested sample and the control, except in their moisture (4.1%-4.2%) and fiber (5.0%) contents which were similar. Protein content increased from 0.9% to 2.6%, fat 24.6% to 28.5%, carbohydrate 59.7% to 61.1%, and ash 1.8% to 2.5% in both control and most preferred sample. Results showed no changes in their peroxide value (2.4 mEq/kg), moisture content (4.1%), and bacterial count of 0 × 10 2  CFU/g at ambient storage temperature for 4 weeks. The addition of cowpea flour increased the nutritional quality of the cassava strips.

Colonisation of winter wheat grain by Fusarium spp. and mycotoxin content as dependent on a wheat variety, crop rotation, a crop management system and weather conditions.

PubMed

Czaban, Janusz; Wróblewska, Barbara; Sułek, Alicja; Mikos, Marzena; Boguszewska, Edyta; Podolska, Grażyna; Nieróbca, Anna

2015-01-01

Field experiments were conducted during three consecutive growing seasons (2007/08, 2008/09 and 2009/10) with four winter wheat (Triticum aestivum L.) cultivars - 'Bogatka', 'Kris', 'Satyna' and 'Tonacja' - grown on fields with a three-field crop rotation (winter triticale, spring barley, winter wheat) and in a four-field crop rotation experiment (spring wheat, spring cereals, winter rapeseed, winter wheat). After the harvest, kernels were surface disinfected with 2% NaOCl and then analysed for the internal infection by different species of Fusarium. Fusaria were isolated on Czapek-Dox iprodione dichloran agar medium and identified on the basis of macro- and micro-morphology on potato dextrose agar and synthetic nutrient agar media. The total wheat grain infection by Fusarium depended mainly on relative humidity (RH) and a rainfall during the flowering stage. Intensive rainfall and high RH in 2009 and 2010 in the period meant the proportions of infected kernels by the fungi were much higher than those in 2008 (lack of precipitation during anthesis). Weather conditions during the post-anthesis period changed the species composition of Fusarium communities internally colonising winter wheat grain. The cultivars significantly varied in the proportion of infected kernels by Fusarium spp. The growing season and type of crop rotation had a distinct effect on species composition of Fusarium communities colonising the grain inside. A trend of a higher percentage of the colonised kernels by the fungi in the grain from the systems using more fertilisers and pesticides as well as the buried straw could be perceived. The most frequent species in the grain were F. avenaceum, F. tricinctum and F. poae in 2008, and F. avenaceum, F. graminearum, F. tricinctum and F. poae in 2009 and 2010. The contents of deoxynivalenol and zearalenon in the grain were correlated with the percentage of kernels colonised by F. graminearum and were the highest in 2009 in the grain from the four-field crop rotation. The content of T-2/HT-2 toxins was the highest in 2010 in grain from the three-field crop rotation and it was correlated with the isolation frequency of F. langsethiae.

Island composite nasal flap for nasal dorsum skin defects.

PubMed

Skitarelić, Neven; Mladina, Ranko; Mraovic, Boris; Simurina, Tatjana; Skitarelić, Nataa; Vuković, Katarina

2009-08-01

Skin defects on the nasal dorsum remain a challenge for the plastic surgeon. There are few local nasal flap options for the repair of proximally positioned nasal skin defects. During a 3-year period, 22 patients were treated after excision of skin cancer in the proximal two-thirds of the nose. Nine patients (41%) were female and 13 (59%) were male, with an average age of 69 years. All patients were operated on under local anesthesia. The average follow-up was 25 months. In all patients, after tumor ablation, the skin defect was closed with an island composite nasal skin flap. Pathohistologic analysis confirmed that the margins of the removed tumor were free of malignant cells. Six patients (27.3%) had squamous cell and 16 (72.7%) had basal cell carcinoma. There was no total or partial flap loss. None of the patients has suffered from recurrence of the tumor. The island composite nasal flap is a reliable technique for the closure of proximal nasal skin defects. Complications in the elevation of the island composite flap were rare, and the final result was acceptable.

Classification of Astrocytomas and Oligodendrogliomas from Mass Spectrometry Data Using Sparse Kernel Machines

PubMed Central

Huang, Jacob; Gholami, Behnood; Agar, Nathalie Y. R.; Norton, Isaiah; Haddad, Wassim M.; Tannenbaum, Allen R.

2013-01-01

Glioma histologies are the primary factor in prognostic estimates and are used in determining the proper course of treatment. Furthermore, due to the sensitivity of cranial environments, real-time tumor-cell classification and boundary detection can aid in the precision and completeness of tumor resection. A recent improvement to mass spectrometry known as desorption electrospray ionization operates in an ambient environment without the application of a preparation compound. This allows for a real-time acquisition of mass spectra during surgeries and other live operations. In this paper, we present a framework using sparse kernel machines to determine a glioma sample’s histopathological subtype by analyzing its chemical composition acquired by desorption electrospray ionization mass spectrometry. PMID:22256188

Effects of vibratory microscreening on proximate composition and recovery of poultry processing wastewater particulate matter.

PubMed

Kiepper, B H; Merka, W C; Fletcher, D L

2008-12-01

Experiments were conducted to compare the effects of tertiary microscreen gap size on the proximate composition and rate of recovery of particulate matter from poultry processing wastewater (PPW). A high-speed vibratory screen was installed within the wastewater treatment area of a southeast US broiler slaughter plant after the existing primary and secondary mechanical rotary screens. Microscreen panels with nominal gap size openings of 212, 106 and 45mum were investigated. The particulate matter samples recovered were subjected to proximate analysis to determine percent moisture, fat, protein, crude fiber and ash. The average percent wet weight moisture (%WW) content for all samples was 79.1. The average percent dry matter (%DM) fat, protein, crude fiber and ash were 63.5, 17.5, 4.8 and 1.5, respectively. The mean concentration of total solids (TS) recovered from all microscreen runs was 668mg/L, which represents a potential additional daily offal recovery rate of 12.1metric tons (MT) per 3.78 million L (1.0 million gallons US) of PPW. There was no significant difference in the performance of the three microscreen gap sizes with regard to proximate composition or mass of particulate matter recovered.

Mango kernel fat fractions as potential healthy food ingredients: A review.

PubMed

Jin, Jun; Jin, Qingzhe; Akoh, Casimir C; Wang, Xingguo

2018-01-16

Mango kernel fat (MKF) has been reported to have high functional and nutritional potential. However, its application in food industry has not been fully explored or developed. In this review, the chemical compositions, physical properties and potential health benefits of MKF are described. MKF is a unique fat consisting of 28.9-65.0% of 1,3-distearoyl-2-oleoyl-glycerol with excellent oxidative stability index (58.8-85.2 h at 110 °C), making the fat and its fractions suitable for use as high-value added food ingredients such as cocoa butter alternatives, trans-free shortenings, and a source of natural antioxidants (e.g., sterol, tocopherol and squalene). Unfortunately, the long period of dehydration of mango kernels at hot temperature results in the hydrolysis of triacylglycerols. The high levels of hydrolysates (mainly free fatty acids and diacylglycerols) limit the application of MKF in manufacturing these food ingredients. It is suggested that the physico-chemical and functional properties of MKF could be further improved through moderated refining (e.g., degumming and physical deacidification), fractionation, and interesterification.

Transition of phenolics and cyanogenic glycosides from apricot and cherry fruit kernels into liqueur.

PubMed

Senica, Mateja; Stampar, Franci; Veberic, Robert; Mikulic-Petkovsek, Maja

2016-07-15

Popular liqueurs made from apricot/cherry pits were evaluated in terms of their phenolic composition and occurrence of cyanogenic glycosides (CGG). Analyses consisted of detailed phenolic and cyanogenic profiles of cherry and apricot seeds as well as beverages prepared from crushed kernels. Phenolic groups and cyanogenic glycosides were analyzed with the aid of high-performance liquid chromatography (HPLC) and mass spectrophotometry (MS). Lower levels of cyanogenic glycosides and phenolics have been quantified in liqueurs compared to fruit kernels. During fruit pits steeping in the alcohol, the phenolics/cyanogenic glycosides ratio increased and at the end of beverage manufacturing process higher levels of total analyzed phenolics were detected compared to cyanogenic glycosides (apricot liqueur: 38.79 μg CGG per ml and 50.57 μg phenolics per ml; cherry liqueur 16.08 μg CGG per ml and 27.73 μg phenolics per ml). Although higher levels of phenolics are characteristic for liqueurs made from apricot and cherry pits these beverages nevertheless contain considerable amounts of cyanogenic glycosides. Copyright © 2016 Elsevier Ltd. All rights reserved.

Kinetic study of nickel laterite reduction roasting by palm kernel shell charcoal

NASA Astrophysics Data System (ADS)

Sugiarto, E.; Putera, A. D. P.; Petrus, H. T. B. M.

2017-05-01

Demand to process nickel-bearing laterite ore increase as continuous depletion of high-grade nickel-bearing sulfide ore takes place. Due to its common nickel association with iron, processing nickel laterite ore into nickel pig iron (NPI) has been developed by some industries. However, to achieve satisfying nickel recoveries, the process needs massive high-grade metallurgical coke consumption. Concerning on the sustainability of coke supply and positive carbon emission, reduction of nickel laterite ore using biomass-based reductor was being studied.In this study, saprolitic nickel laterite ore was being reduced by palm kernel shell charcoal at several temperatures (800-1000 °C). Variation of biomass-laterite composition was also conducted to study the reduction mechanism. X-ray diffraction and gravimetry analysis were applied to justify the phenomenon and predict kinetic model of the reduction. Results of this study provide information that palm kernel shell charcoal has similar reducing result compared with the conventional method. Reduction, however, was carried out by carbon monoxide rather than solid carbon. Regarding kinetics, Ginstling-Brouhnstein kinetic model provides satisfying results to predict the reduction phenomenon.

A Study of Term Proximity and Document Weighting Normalization in Pseudo Relevance Feedback - UIUC at TREC 2009 Million Query Track

DTIC Science & Technology

2009-11-01

is estimated using the Gaussian kernel function: c′(w, i) = N∑ j =1 c(w, j ) exp [−(i− j )2 2σ2 ] (2) where i and j are absolute positions of the...corresponding terms in the document, and N is the length of the document; c(w, j ) is the actual count of term w at position j . The PLM P (·|D, i) needs to...probability of rel- evance well. The distribution of relevance can be approximated as fol- lows: p(i|θrel) = ∑ j δ(Qj , i)∑ i ∑ j δ(Qj , i) (10

Infrared microspectroscopic imaging of plant tissues: spectral visualization of Triticum aestivum kernel and Arabidopsis leaf microstructure.

PubMed

Warren, Frederick J; Perston, Benjamin B; Galindez-Najera, Silvia P; Edwards, Cathrina H; Powell, Prudence O; Mandalari, Giusy; Campbell, Grant M; Butterworth, Peter J; Ellis, Peter R

2015-11-01

Infrared microspectroscopy is a tool with potential for studies of the microstructure, chemical composition and functionality of plants at a subcellular level. Here we present the use of high-resolution bench top-based infrared microspectroscopy to investigate the microstructure of Triticum aestivum L. (wheat) kernels and Arabidopsis leaves. Images of isolated wheat kernel tissues and whole wheat kernels following hydrothermal processing and simulated gastric and duodenal digestion were generated, as well as images of Arabidopsis leaves at different points during a diurnal cycle. Individual cells and cell walls were resolved, and large structures within cells, such as starch granules and protein bodies, were clearly identified. Contrast was provided by converting the hyperspectral image cubes into false-colour images using either principal component analysis (PCA) overlays or by correlation analysis. The unsupervised PCA approach provided a clear view of the sample microstructure, whereas the correlation analysis was used to confirm the identity of different anatomical structures using the spectra from isolated components. It was then demonstrated that gelatinized and native starch within cells could be distinguished, and that the loss of starch during wheat digestion could be observed, as well as the accumulation of starch in leaves during a diurnal period. © 2015 The Authors The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

Sentence Combining: A Literature Review.

ERIC Educational Resources Information Center

Phillips, Sylvia E.

Sentence combining--a technique of putting strings of sentence kernels together in a variety of ways so that completed sentences possess greater syntactic maturity--is a method offering much promise in the teaching of writing and composition. The purpose of this document is to provide a literature review of this procedure. After defining the term…

Proximate composition, fatty acid analysis and protein digestibility-corrected amino acid score of three Mediterranean cephalopods.

PubMed

Zlatanos, Spiros; Laskaridis, Kostas; Feist, Christian; Sagredos, Angelos

2006-10-01

Proximate composition, fatty acid analysis and protein digestibility-corrected amino acid score (PDCAAS) in three commercially important cephalopods of the Mediterranean sea (cuttlefish, octopus and squid) were determined. The results of the proximate analysis showed that these species had very high protein:fat ratios similar to lean beef. Docosahexaenoic, palmitic and eicosipentaenoic acid were the most abundant fatty acids among analyzed species. The amount of n-3 fatty acids was higher than that of saturated, monounsaturated and n-6 fatty acids. Despite the fact that cephalopods contain small amounts of fat they were found quite rich in n-3 fatty acids. Finally, PDCAAS indicated that these organisms had a very good protein quality.

Multilevel image recognition using discriminative patches and kernel covariance descriptor

NASA Astrophysics Data System (ADS)

Lu, Le; Yao, Jianhua; Turkbey, Evrim; Summers, Ronald M.

2014-03-01

Computer-aided diagnosis of medical images has emerged as an important tool to objectively improve the performance, accuracy and consistency for clinical workflow. To computerize the medical image diagnostic recognition problem, there are three fundamental problems: where to look (i.e., where is the region of interest from the whole image/volume), image feature description/encoding, and similarity metrics for classification or matching. In this paper, we exploit the motivation, implementation and performance evaluation of task-driven iterative, discriminative image patch mining; covariance matrix based descriptor via intensity, gradient and spatial layout; and log-Euclidean distance kernel for support vector machine, to address these three aspects respectively. To cope with often visually ambiguous image patterns for the region of interest in medical diagnosis, discovery of multilabel selective discriminative patches is desired. Covariance of several image statistics summarizes their second order interactions within an image patch and is proved as an effective image descriptor, with low dimensionality compared with joint statistics and fast computation regardless of the patch size. We extensively evaluate two extended Gaussian kernels using affine-invariant Riemannian metric or log-Euclidean metric with support vector machines (SVM), on two medical image classification problems of degenerative disc disease (DDD) detection on cortical shell unwrapped CT maps and colitis detection on CT key images. The proposed approach is validated with promising quantitative results on these challenging tasks. Our experimental findings and discussion also unveil some interesting insights on the covariance feature composition with or without spatial layout for classification and retrieval, and different kernel constructions for SVM. This will also shed some light on future work using covariance feature and kernel classification for medical image analysis.

Proximate, Antinutrients and Mineral Composition of Raw and Processed (Boiled and Roasted) Sphenostylis stenocarpa Seeds from Southern Kaduna, Northwest Nigeria

PubMed Central

Ndidi, Uche Samuel; Ndidi, Charity Unekwuojo; Olagunju, Abbas; Muhammad, Aliyu; Billy, Francis Graham; Okpe, Oche

2014-01-01

This research was aimed at evaluating the proximate composition, level of anti-nutrients, and the mineral composition of raw and processed Sphenostylis stenocarpa seeds and at examining the effect of processing on the parameters. From the proximate composition analysis, the ash content showed no significant difference (P > 0.05) between the processed and unprocessed (raw) samples. However, there was significant difference (P < 0.05) in the levels of moisture, crude lipid, nitrogen-free extract, gross energy, true protein, and crude fiber between the processed and unprocessed S. stenocarpa. Analyses of the antinutrient composition show that the processed S. stenocarpa registered significant reduction in levels of hydrogen cyanide, trypsin inhibitor, phytate, oxalate, and tannins compared to the unprocessed. Evaluation of the mineral composition showed that the level of sodium, calcium, and potassium was high in both the processed and unprocessed sample (150–400 mg/100 g). However, the level of iron, copper, zinc, and magnesium was low in both processed and unprocessed samples (2–45 mg/100 g). The correlation analysis showed that tannins and oxalate affected the levels of ash and nitrogen-free extract of processed and unprocessed seeds. These results suggest that the consumption of S. stenocarpa will go a long way in reducing the level of malnutrition in northern Nigeria. PMID:24967265

Certain composition formulae for the fractional integral operators

NASA Astrophysics Data System (ADS)

Agarwal, Praveen; Harjule, Priyanka

2017-09-01

In this paper we establish some (presumably new) interesting expressions for the composition of some well known fractional integral operators Ia+ μ,Da+ μ,Ia+ γ ,μ and also derive an integral operator ℋa+;p ,q ;β w ;m ,n ;α whose kernel involves the Fox's H- function. By suitably specializing the coefficients and the parameters in these functions we can get a large number of (new and known) interesting expressions for the composition formulae which occur rather frequently in many problems of engineering and mathematical analysis but here we can mention only those which follow as particular cases of the Srivastava et al.

Characterization and optimization of flexible dual mode sensor based on Carbon Micro Coils

NASA Astrophysics Data System (ADS)

Dat Nguyen, Tien; Kim, Taeseung; Han, Hyoseung; Shin, Hyun Yeong; Nguyen, Canh Toan; Phung, Hoa; Ryeol Choi, Hyouk

2018-01-01

Carbon Microcoils (CMCs) is a 3D helical micro structure grown via a chemical vapor deposition process. It is noted that composites in which CMCs are embedded in polymer matrixes, called CMC sheets, experience a drastic change of electrical impedance depending on the proximity and contact of external objects. In this paper, a dual functional sensor, that is, tactile and proximity sensor fabricated with CMC/silicone composite is presented to demonstrate the advanced characteristics of CMCs sheets. Characteristics of sensor responses depending on CMC compositions are investigated and optimal conditions are determined. The candidates of polymer matrices are also investigated. As the results, the CMC sheet consisting of Ecoflex 30, CMC 30 {{wt}} % , and multiwall carbon nanotubes 1 {{wt}} % shows the most appropriate tactile sensing characteristics with more than 1 mm of thickness. The proximity sensing capability is the maximum when the 1.5 {{wt}} % CMC content is mixed with Dragon skin 30 silicone substrate. Finally, multiple target objects are recognized with the results and their feasibilities are experimentally validated.

Proximate composition and energy content of beef steaks as influenced by USDA quality grade and degree of doneness.

PubMed

Smith, A M; Harris, K B; Haneklaus, A N; Savell, J W

2011-10-01

This study evaluated the influence of various degrees of doneness on proximate composition and energy content of beef. Ten steaks were obtained from each of five USDA Prime, five USDA Choice, and five USDA Select strip loins and assigned to one of five degree of doneness treatments (two sets of treatments per strip loin): raw, medium rare (63 °C), medium (71 °C), well done (77 °C), and very well done (82 °C). After cooking, steaks were dissected into separable tissue components consisting of lean, fat, and refuse. Lean tissue was used to obtain proximate analyses of protein, moisture, fat, and ash. Degree of doneness did influence (P<0.05) the nutrient composition of beef steaks. As the degree of doneness increased, percent fat and protein increased, while percent moisture decreased. Cooking steaks to a higher degree of doneness resulted in a higher caloric value when reported per 100g basis. Copyright © 2011 Elsevier Ltd. All rights reserved.

A procedure to estimate proximate analysis of mixed organic wastes.

PubMed

Zaher, U; Buffiere, P; Steyer, J P; Chen, S

2009-04-01

In waste materials, proximate analysis measuring the total concentration of carbohydrate, protein, and lipid contents from solid wastes is challenging, as a result of the heterogeneous and solid nature of wastes. This paper presents a new procedure that was developed to estimate such complex chemical composition of the waste using conventional practical measurements, such as chemical oxygen demand (COD) and total organic carbon. The procedure is based on mass balance of macronutrient elements (carbon, hydrogen, nitrogen, oxygen, and phosphorus [CHNOP]) (i.e., elemental continuity), in addition to the balance of COD and charge intensity that are applied in mathematical modeling of biological processes. Knowing the composition of such a complex substrate is crucial to study solid waste anaerobic degradation. The procedure was formulated to generate the detailed input required for the International Water Association (London, United Kingdom) Anaerobic Digestion Model number 1 (IWA-ADM1). The complex particulate composition estimated by the procedure was validated with several types of food wastes and animal manures. To make proximate analysis feasible for validation, the wastes were classified into 19 types to allow accurate extraction and proximate analysis. The estimated carbohydrates, proteins, lipids, and inerts concentrations were highly correlated to the proximate analysis; correlation coefficients were 0.94, 0.88, 0.99, and 0.96, respectively. For most of the wastes, carbohydrate was the highest fraction and was estimated accurately by the procedure over an extended range with high linearity. For wastes that are rich in protein and fiber, the procedure was even more consistent compared with the proximate analysis. The new procedure can be used for waste characterization in solid waste treatment design and optimization.

Proximate and fatty acid composition and cholesterol content of different cuts of guinea fowl meat as affected by cooking method.

PubMed

Hoffman, Louwrens C; Tlhong, Tumelo M

2012-10-01

Poultry is one of the leading meat products in South Africa, and its nutritional composition can be affected by the cut and cooking method. Limited food composition data are available for typical South African poultry products. This study investigated the effect of different cuts and cooking methods on the proximate and fatty acid composition as well as the cholesterol content of guinea fowl (Numida meleagris) meat. The open-roasting method produced the highest moisture content for all cuts, and the baking bag method the lowest. The baking bag method resulted in the highest protein content. Cooking method had no effect on fat content, although breast had the lowest and thigh the highest fat content. Ash content was highest in the open-roasted drumstick. All cuts, regardless of cooking method, had a favourable polyunsaturated/saturated fatty acid (P/S) ratio (>0.4). Their n-6/n-3 ratio was also within the recommended beneficial range (<4:1). Both cooking method and cut affected cholesterol content. Different cuts of guinea fowl vary in proximate and fatty acid composition as well as in cholesterol content, which in turn is affected to varying degrees by cooking method. Copyright © 2012 Society of Chemical Industry.

Nutritional and antioxidant profiles of pumpkin (Cucurbita pepo Linn.) immature and mature fruits as influenced by NPK fertilizer.

PubMed

Oloyede, F M; Agbaje, G O; Obuotor, E M; Obisesan, I O

2012-11-15

This study evaluated the influence of NPK fertilizer on protein, fibre, ash, fat, carbohydrate, antioxidant activities and antioxidant phenolic compounds in immature and mature fruits of pumpkin. The treatment consisted of six NPK levels (0, 50, 100, 150, 200 and 250 kg/ha), and was replicated six times in a randomized complete block design (RCBD). Proximate analysis and antioxidant assays were done using standard analytical methods. At control and lower NPK rates, the proximate compositions and antioxidant profile of pumpkin fruits decreased with increasing NPK fertilizer. Between the control and the highest fertilizer rate, proximate compositions decreased by 7-62% while the antioxidant profile decreased by 13-79% for both immature and mature fruits. Across all the measured parameters, mature fruit had higher proximate contents and higher antioxidant concentrations. For the high health value of pumpkin fruits to be maintained, little or no NPK fertilizer should be applied. Copyright © 2012 Elsevier Ltd. All rights reserved.

Influence of Stenocarpella maydis infected corn on the composition of corn kernel and its conversion into ethanol

USDA-ARS?s Scientific Manuscript database

Stenocarpella ear rot (formerly Diplodia ear rot) is resurfacing as a concern in the central United States Corn Belt. There are reports of some fields containing more than 50% mummified ears. Ears infected within two weeks of silking may be completely mummified with white to grayish brown mycelium c...

Influence of Stenocarpella maydis infected corn on the composition of corn kernel and its conversion into ethanol

USDA-ARS?s Scientific Manuscript database

Widespread epidemics of Stenocarpella ear rot (formerly Diplodia ear rot) have occurred throughout the central U.S. Corn Belt in recent years, but the influence of S. maydis infected grain on corn ethanol production is unknown. In this study, S. maydis infected ears of variety 'Heritage 4646' were h...

Food Environment and Weight Change: Does Residential Mobility Matter?

PubMed Central

Laraia, Barbara A.; Downing, Janelle M.; Zhang, Y. Tara; Dow, William H.; Kelly, Maggi; Blanchard, Samuel D.; Adler, Nancy; Schillinger, Dean; Moffet, Howard; Warton, E. Margaret; Karter, Andrew J.

2017-01-01

Abstract Associations between neighborhood food environment and adult body mass index (BMI; weight (kg)/height (m)2) derived using cross-sectional or longitudinal random-effects models may be biased due to unmeasured confounding and measurement and methodological limitations. In this study, we assessed the within-individual association between change in food environment from 2006 to 2011 and change in BMI among adults with type 2 diabetes using clinical data from the Kaiser Permanente Diabetes Registry collected from 2007 to 2011. Healthy food environment was measured using the kernel density of healthful food venues. Fixed-effects models with a 1-year-lagged BMI were estimated. Separate models were fitted for persons who moved and those who did not. Sensitivity analysis using different lag times and kernel density bandwidths were tested to establish the consistency of findings. On average, patients lost 1 pound (0.45 kg) for each standard-deviation improvement in their food environment. This relationship held for persons who remained in the same location throughout the 5-year study period but not among persons who moved. Proximity to food venues that promote nutritious foods alone may not translate into clinically meaningful diet-related health changes. Community-level policies for improving the food environment need multifaceted strategies to invoke clinically meaningful change in BMI among adult patients with diabetes. PMID:28387785

Mechanical response of common millet (Panicum miliaceum) seeds under quasi-static compression: Experiments and modeling.

PubMed

Hasseldine, Benjamin P J; Gao, Chao; Collins, Joseph M; Jung, Hyun-Do; Jang, Tae-Sik; Song, Juha; Li, Yaning

2017-09-01

The common millet (Panicum miliaceum) seedcoat has a fascinating complex microstructure, with jigsaw puzzle-like epidermis cells articulated via wavy intercellular sutures to form a compact layer to protect the kernel inside. However, little research has been conducted on linking the microstructure details with the overall mechanical response of this interesting biological composite. To this end, an integrated experimental-numerical-analytical investigation was conducted to both characterize the microstructure and ascertain the microscale mechanical properties and to test the overall response of kernels and full seeds under macroscale quasi-static compression. Scanning electron microscopy (SEM) was utilized to examine the microstructure of the outer seedcoat and nanoindentation was performed to obtain the material properties of the seedcoat hard phase material. A multiscale computational strategy was applied to link the microstructure to the macroscale response of the seed. First, the effective anisotropic mechanical properties of the seedcoat were obtained from finite element (FE) simulations of a microscale representative volume element (RVE), which were further verified from sophisticated analytical models. Then, macroscale FE models of the individual kernel and full seed were developed. Good agreement between the compression experiments and FE simulations were obtained for both the kernel and the full seed. The results revealed the anisotropic property and the protective function of the seedcoat, and showed that the sutures of the seedcoat play an important role in transmitting and distributing loads in responding to external compression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Proximate Composition Analysis.

PubMed

2016-01-01

The proximate composition of foods includes moisture, ash, lipid, protein and carbohydrate contents. These food components may be of interest in the food industry for product development, quality control (QC) or regulatory purposes. Analyses used may be rapid methods for QC or more accurate but time-consuming official methods. Sample collection and preparation must be considered carefully to ensure analysis of a homogeneous and representative sample, and to obtain accurate results. Estimation methods of moisture content, ash value, crude lipid, total carbohydrates, starch, total free amino acids and total proteins are put together in a lucid manner.

Polishing and parboiling effect on the nutritional and technological properties of pigmented rice

USDA-ARS?s Scientific Manuscript database

This study aims to evaluate the effects of polishing and parboiling on proximate composition, structure, phenolic compounds, antioxidant activity, cooking time and hardness of IAC-600 black rice cultivar and MPB-10 red rice lineage. Proximate analysis and light micrographs revealed higher migration ...

Chemical properties and oxidative stability of Arjan (Amygdalus reuteri) kernel oil as emerging edible oil.

PubMed

Tavakoli, Javad; Emadi, Teymour; Hashemi, Seyed Mohammad Bagher; Mousavi Khaneghah, Amin; Munekata, Paulo Eduardo Sichetti; Lorenzo, Jose Manuel; Brnčić, Mladen; Barba, Francisco J

2018-05-01

The oxidative stability, as well as the chemical composition of Amygdalus reuteri kernel oil (ARKO), were evaluated and compared to those of Amygdalus scoparia kernel oil (ASKO) and extra virgin olive oil (EVOO) during and after holding in the oven (170 °C for 8 h). The oxidative stability analysis was carried out by measuring the changes in conjugated dienes, carbonyl and acid values as well as oil/oxidative stability index and their correlation with the antioxidant compounds (tocopherol, polyphenols, and sterol compounds). The oleic acid was determined as the predominant fatty acid of ARKO (65.5%). Calculated oxidizability value and an iodine value of ARKO, ASKO and EVOO were reported as 3.29 and 3.24, 2.00 and 100.0, 101.4 and 81.9, respectively. Due to the high wax content (4.5% and 3.3%, respectively), the saponification number of ARKO and ASKO (96.4 and 99.8, respectively) was lower than that of EVOO (169.7). ARKO had the highest oxidative stability, followed by ASKO and EVOO. Therefore, ARKO can be introduced as a new source of edible oil with high oxidative stability. Copyright © 2018. Published by Elsevier Ltd.

A new kernel-based fuzzy level set method for automated segmentation of medical images in the presence of intensity inhomogeneity.

PubMed

Rastgarpour, Maryam; Shanbehzadeh, Jamshid

2014-01-01

Researchers recently apply an integrative approach to automate medical image segmentation for benefiting available methods and eliminating their disadvantages. Intensity inhomogeneity is a challenging and open problem in this area, which has received less attention by this approach. It has considerable effects on segmentation accuracy. This paper proposes a new kernel-based fuzzy level set algorithm by an integrative approach to deal with this problem. It can directly evolve from the initial level set obtained by Gaussian Kernel-Based Fuzzy C-Means (GKFCM). The controlling parameters of level set evolution are also estimated from the results of GKFCM. Moreover the proposed algorithm is enhanced with locally regularized evolution based on an image model that describes the composition of real-world images, in which intensity inhomogeneity is assumed as a component of an image. Such improvements make level set manipulation easier and lead to more robust segmentation in intensity inhomogeneity. The proposed algorithm has valuable benefits including automation, invariant of intensity inhomogeneity, and high accuracy. Performance evaluation of the proposed algorithm was carried on medical images from different modalities. The results confirm its effectiveness for medical image segmentation.

Proximate composition, amino acid and fatty acid composition of fish maws.

PubMed

Wen, Jing; Zeng, Ling; Xu, Youhou; Sun, Yulin; Chen, Ziming; Fan, Sigang

2016-01-01

Fish maws are commonly recommended and consumed in Asia over many centuries because it is believed to have some traditional medical properties. This study highlights and provides new information on the proximate composition, amino acid and fatty acid composition of fish maws of Cynoscion acoupa, Congresox talabonoides and Sciades proops. The results indicated that fish maws were excellent protein sources and low in fat content. The proteins in fish maws were rich in functional amino acids (FAAs) and the ratio of FAAs and total amino acids in fish maws ranged from 0.68 to 0.69. Among species, croaker C. acoupa contained the most polyunsaturated fatty acids, arachidonic acid, docosahexaenoic acid and eicosapntemacnioc acid, showing the lowest value of index of atherogenicity and index of thrombogenicity, showing the highest value of hypocholesterolemic/hypercholesterolemic ratio, which is the most desirable.

Rediscovering the Kernels of Truth in the Urban Legends of the Freshman Composition Classroom

ERIC Educational Resources Information Center

Lovoy, Thomas

2004-01-01

English teachers, as well as teachers within other disciplines, often boil down abstract principles to easily explainable bullet points. Students often pick up and retain these points but fail to grasp the broader contexts that make them relevant. It is therefore sometimes helpful to revisit some of the more common of these "rules of thumb" to…

A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits.

PubMed

Yan, Kang K; Zhao, Hongyu; Pang, Herbert

2017-12-06

High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order to provide a holistic understanding of human health and diseases, it is necessary to integrate multiple data sources. Several algorithms have been proposed so far, however, a comprehensive comparison of data integration algorithms for classification of binary traits is currently lacking. In this paper, we focus on two common classes of integration algorithms, graph-based that depict relationships with subjects denoted by nodes and relationships denoted by edges, and kernel-based that can generate a classifier in feature space. Our paper provides a comprehensive comparison of their performance in terms of various measurements of classification accuracy and computation time. Seven different integration algorithms, including graph-based semi-supervised learning, graph sharpening integration, composite association network, Bayesian network, semi-definite programming-support vector machine (SDP-SVM), relevance vector machine (RVM) and Ada-boost relevance vector machine are compared and evaluated with hypertension and two cancer data sets in our study. In general, kernel-based algorithms create more complex models and require longer computation time, but they tend to perform better than graph-based algorithms. The performance of graph-based algorithms has the advantage of being faster computationally. The empirical results demonstrate that composite association network, relevance vector machine, and Ada-boost RVM are the better performers. We provide recommendations on how to choose an appropriate algorithm for integrating data from multiple sources.

A flexible dual mode tactile and proximity sensor using carbon microcoils

NASA Astrophysics Data System (ADS)

Han, Hyo Seung; Park, Junwoo; Nguyen, Tien Dat; Kim, Uikyum; Jeong, Soon Cheol; Kang, Doo In; Choi, Hyouk Ryeol

2016-04-01

This paper proposes a flexible dual mode tactile and proximity sensor using Carbon Microcoils (CMCs). The sensor consists of a Flexible Printed Circuit Board (FPCB) electrode layer and a dielectric layer of CMCs composite. In order to avoid damage from frequent contacts, the sensor has all electrodes on the same plane and a polymer covering is placed on the top of the sensor. CMCs can be modeled as complex LCR circuit and the sensitivity of the sensor highly depends on the CMC content. Proper CMC content is experimentally investigated and applied to make the CMCs composite for the dielectric layer. The CMC sensor measures the capacitance for tactile stimulus and inductance for proximity stimulus. A prototype with a size of 30 × 30 × 0.6 𝑚𝑚3, is manufactured and its feasibility is experimentally validated.

Kernel abortion in maize : I. Carbohydrate concentration patterns and Acid invertase activity of maize kernels induced to abort in vitro.

PubMed

Hanft, J M; Jones, R J

1986-06-01

Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.

An implementation of support vector machine on sentiment classification of movie reviews

NASA Astrophysics Data System (ADS)

Yulietha, I. M.; Faraby, S. A.; Adiwijaya; Widyaningtyas, W. C.

2018-03-01

With technological advances, all information about movie is available on the internet. If the information is processed properly, it will get the quality of the information. This research proposes to the classify sentiments on movie review documents. This research uses Support Vector Machine (SVM) method because it can classify high dimensional data in accordance with the data used in this research in the form of text. Support Vector Machine is a popular machine learning technique for text classification because it can classify by learning from a collection of documents that have been classified previously and can provide good result. Based on number of datasets, the 90-10 composition has the best result that is 85.6%. Based on SVM kernel, kernel linear with constant 1 has the best result that is 84.9%

On processed splitting methods and high-order actions in path-integral Monte Carlo simulations.

PubMed

Casas, Fernando

2010-10-21

Processed splitting methods are particularly well adapted to carry out path-integral Monte Carlo (PIMC) simulations: since one is mainly interested in estimating traces of operators, only the kernel of the method is necessary to approximate the thermal density matrix. Unfortunately, they suffer the same drawback as standard, nonprocessed integrators: kernels of effective order greater than two necessarily involve some negative coefficients. This problem can be circumvented, however, by incorporating modified potentials into the composition, thus rendering schemes of higher effective order. In this work we analyze a family of fourth-order schemes recently proposed in the PIMC setting, paying special attention to their linear stability properties, and justify their observed behavior in practice. We also propose a new fourth-order scheme requiring the same computational cost but with an enlarged stability interval.

7 CFR 810.602 - Definition of other terms.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Damaged kernels. Kernels and pieces of flaxseed kernels that are badly ground-damaged, badly weather... instructions. Also, underdeveloped, shriveled, and small pieces of flaxseed kernels removed in properly... recleaning. (c) Heat-damaged kernels. Kernels and pieces of flaxseed kernels that are materially discolored...

Proximate and mineral composition of crab meat consumed in Bahrain.

PubMed

Musaiger, Abdulrahman O; Al-Rumaidh, Mohammed J

2005-06-01

The proximate, mineral and heavy metals of raw and cooked crab meat, Portunus pelagicus, consumed in Bahrain were studied. The crab meat contains a good level of protein (17.5-18.8%), with very low proportion of fat (0.6-1.4%). The levels of sodium, potassium, calcium and phosphorus were found to be higher than other minerals. Traces of heavy metals (lead, mercury, cadmium) were also reported. Traditional cooking had a considerable effect on proximate and mineral contents of crab meat.

Kernel Abortion in Maize 1

PubMed Central

Hanft, Jonathan M.; Jones, Robert J.

1986-01-01

Kernels cultured in vitro were induced to abort by high temperature (35°C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35°C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth. PMID:16664846

The spectral details of observed and simulated short-term water vapor feedbacks of El Niño-Southern Oscillation

NASA Astrophysics Data System (ADS)

Pan, F.; Huang, X.; Chen, X.

2015-12-01

Radiative kernel method has been validated and widely used in the study of climate feedbacks. This study uses spectrally resolved longwave radiative kernels to examine the short-term water vapor feedbacks associated with the ENSO cycles. Using a 500-year GFDL CM3 and a 100-year NCAR CCSM4 pre-industry control simulation, we have constructed two sets of longwave spectral radiative kernels. We then composite El Niño, La Niña and ENSO-neutral states and estimate the water vapor feedbacks associated with the El Niño and La Niña phases of ENSO cycles in both simulations. Similar analysis is also applied to 35-year (1979-2014) ECMWF ERA-interim reanalysis data, which is deemed as observational results here. When modeled and observed broadband feedbacks are compared to each other, they show similar geographic patterns but with noticeable discrepancies in the contrast between the tropics and extra-tropics. Especially, in El Niño phase, the feedback estimated from reanalysis is much greater than those from the model simulations. Considering the observational data span, we carry out a sensitivity test to explore the variability of feedback-deriving using 35-year data. To do so, we calculate the water vapor feedback within every 35-year segment of the GFDL CM3 control run by two methods: one is to composite El Nino or La Nina phases as mentioned above and the other is to regressing the TOA flux perturbation caused by water vapor change (δR_H­2O) against the global-mean surface temperature a­­­­nomaly. We find that the short-term feedback strengths derived from composite method can change considerably from one segment to another segment, while the feedbacks by regression method are less sensitive to the choice of segment and their strengths are also much smaller than those from composite analysis. This study suggests that caution is warranted in order to infer long-term feedbacks from a few decades of observations. When spectral details of the global-mean feedbacks are examined, more inconsistencies can be revealed in many spectral bands, especially H2O continuum absorption bands and window regions. These discrepancies can be attributed back to differences in observed and modeled water vapor profiles in responses to tropical SST.

Out-of-Sample Extensions for Non-Parametric Kernel Methods.

PubMed

Pan, Binbin; Chen, Wen-Sheng; Chen, Bo; Xu, Chen; Lai, Jianhuang

2017-02-01

Choosing suitable kernels plays an important role in the performance of kernel methods. Recently, a number of studies were devoted to developing nonparametric kernels. Without assuming any parametric form of the target kernel, nonparametric kernel learning offers a flexible scheme to utilize the information of the data, which may potentially characterize the data similarity better. The kernel methods using nonparametric kernels are referred to as nonparametric kernel methods. However, many nonparametric kernel methods are restricted to transductive learning, where the prediction function is defined only over the data points given beforehand. They have no straightforward extension for the out-of-sample data points, and thus cannot be applied to inductive learning. In this paper, we show how to make the nonparametric kernel methods applicable to inductive learning. The key problem of out-of-sample extension is how to extend the nonparametric kernel matrix to the corresponding kernel function. A regression approach in the hyper reproducing kernel Hilbert space is proposed to solve this problem. Empirical results indicate that the out-of-sample performance is comparable to the in-sample performance in most cases. Experiments on face recognition demonstrate the superiority of our nonparametric kernel method over the state-of-the-art parametric kernel methods.

7 CFR 810.1202 - Definition of other terms.

Code of Federal Regulations, 2010 CFR

2010-01-01

... kernels. Kernels, pieces of rye kernels, and other grains that are badly ground-damaged, badly weather.... Also, underdeveloped, shriveled, and small pieces of rye kernels removed in properly separating the...-damaged kernels. Kernels, pieces of rye kernels, and other grains that are materially discolored and...

The Genetic Basis of Natural Variation in Kernel Size and Related Traits Using a Four-Way Cross Population in Maize.

PubMed

Chen, Jiafa; Zhang, Luyan; Liu, Songtao; Li, Zhimin; Huang, Rongrong; Li, Yongming; Cheng, Hongliang; Li, Xiantang; Zhou, Bo; Wu, Suowei; Chen, Wei; Wu, Jianyu; Ding, Junqiang

2016-01-01

Kernel size is an important component of grain yield in maize breeding programs. To extend the understanding on the genetic basis of kernel size traits (i.e., kernel length, kernel width and kernel thickness), we developed a set of four-way cross mapping population derived from four maize inbred lines with varied kernel sizes. In the present study, we investigated the genetic basis of natural variation in seed size and other components of maize yield (e.g., hundred kernel weight, number of rows per ear, number of kernels per row). In total, ten QTL affecting kernel size were identified, three of which (two for kernel length and one for kernel width) had stable expression in other components of maize yield. The possible genetic mechanism behind the trade-off of kernel size and yield components was discussed.

The Genetic Basis of Natural Variation in Kernel Size and Related Traits Using a Four-Way Cross Population in Maize

PubMed Central

Liu, Songtao; Li, Zhimin; Huang, Rongrong; Li, Yongming; Cheng, Hongliang; Li, Xiantang; Zhou, Bo; Wu, Suowei; Chen, Wei; Wu, Jianyu; Ding, Junqiang

2016-01-01

Kernel size is an important component of grain yield in maize breeding programs. To extend the understanding on the genetic basis of kernel size traits (i.e., kernel length, kernel width and kernel thickness), we developed a set of four-way cross mapping population derived from four maize inbred lines with varied kernel sizes. In the present study, we investigated the genetic basis of natural variation in seed size and other components of maize yield (e.g., hundred kernel weight, number of rows per ear, number of kernels per row). In total, ten QTL affecting kernel size were identified, three of which (two for kernel length and one for kernel width) had stable expression in other components of maize yield. The possible genetic mechanism behind the trade-off of kernel size and yield components was discussed. PMID:27070143

7 CFR 810.802 - Definition of other terms.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Damaged kernels. Kernels and pieces of grain kernels for which standards have been established under the.... (d) Heat-damaged kernels. Kernels and pieces of grain kernels for which standards have been...

Compositional variability of nutrients and phytochemicals in corn after processing.

PubMed

Prasanthi, P S; Naveena, N; Vishnuvardhana Rao, M; Bhaskarachary, K

2017-04-01

The result of various process strategies on the nutrient and phytochemical composition of corn samples were studied. Fresh and cooked baby corn, sweet corn, dent corn and industrially processed and cooked popcorn, corn grits, corn flour and corn flakes were analysed for the determination of proximate, minerals, xanthophylls and phenolic acids content. This study revealed that the proximate composition of popcorn is high compared to the other corn products analyzed while the mineral composition of these maize products showed higher concentration of magnesium, phosphorus, potassium and low concentration of calcium, manganese, zinc, iron, copper, and sodium. Popcorn was high in iron, zinc, copper, manganese, sodium, magnesium and phosphorus. The xanthophylls lutein and zeaxanthin were predominant in the dent corn and the total polyphenolic content was highest in dent corn while the phenolic acids distribution was variable in different corn products. This study showed preparation and processing brought significant reduction of xanthophylls and polyphenols.

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2014 CFR

2014-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2011 CFR

2011-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2012 CFR

2012-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2013 CFR

2013-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

Proximate composition and mineral content of two edible species of Cnidoscolus (tree spinach).

PubMed

Kuti, J O; Kuti, H O

1999-01-01

Proximate composition and mineral content of raw and cooked leaves of two edible tree spinach species (Cnidoscolus chayamansa and C. aconitifolius), known locally as 'chaya', were determined and compared with that of a traditional green vegetable, spinach (Spinicia oleraceae). Results of the study indicated that the edible leafy parts of the two chaya species contained significantly (p<0.05) greater amounts of crude protein, crude fiber, Ca, K, Fe, ascorbic acid and beta-carotene than the spinach leaf. However, no significant (p>0.05) differences were found in nutritional composition and mineral content between the chaya species, except minor differences in the relative composition of fatty acids, protein and amino acids. Cooking of chaya leaves slightly reduced nutritional composition of both chaya species. Cooking is essential prior to consumption to inactivate the toxic hydrocyanic glycosides present in chaya leaves. Based on the results of this study, the edible chaya leaves may be good dietary sources of minerals (Ca, K and Fe) and vitamins (ascorbic acid and beta-carotene).

Classification With Truncated Distance Kernel.

PubMed

Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

2018-05-01

This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

Between-Group Variation in Female Dispersal, Kin Composition of Groups, and Proximity Patterns in a Black-and-White Colobus Monkey (Colobus vellerosus)

PubMed Central

Wikberg, Eva C.; Sicotte, Pascale; Campos, Fernando A.; Ting, Nelson

2012-01-01

A growing body of evidence shows within-population variation in natal dispersal, but the effects of such variation on social relationships and the kin composition of groups remain poorly understood. We investigate the link between dispersal, the kin composition of groups, and proximity patterns in a population of black-and-white colobus (Colobus vellerosus) that shows variation in female dispersal. From 2006 to 2011, we collected behavioral data, demographic data, and fecal samples of 77 males and 92 females residing in eight groups at Boabeng-Fiema, Ghana. A combination of demographic data and a genetic network analysis showed that although philopatry was female-biased, only about half of the females resided in their natal groups. Only one group contained female-female dyads with higher average relatedness than randomly drawn animals of both sexes from the same group. Despite between-group variation in female dispersal and kin composition, female-female dyads in most of the study groups had higher proximity scores than randomly drawn dyads from the same group. We conclude that groups fall along a continuum from female dispersed, not kin-based, and not bonded to female philopatric, kin-based, and bonded. We found only partial support for the predicted link between dispersal, kin composition, and social relationships. In contrast to most mammals where the kin composition of groups is a good predictor of the quality of female-female relationships, this study provides further support for the notion that kinship is not necessary for the development and maintenance of social bonds in some gregarious species. PMID:23144951

Design of Composite Hip Prostheses Considering the Long-Term Behavior of the Femur

NASA Astrophysics Data System (ADS)

Lim, Jong Wan; Jeong, Jae Youn; Ha, Sung Kyu

A design method for the hip prosthesis is proposed which can alleviate problems associated with stress shielding, proximal loosening and the high stress of bone-implant interfaces after total hip replacement. The stress shielding which may lead to bone resorption, can cause a loosening of the stem and a fracture of femoral bone. Generally the composites were more suitable for hip prosthesis material in the long-term stability than metallic alloy because design cases of composite materials produced less stress shielding than titanium alloy. A bone remodeling algorithm was implemented in a nonlinear finite element program to predict the long-term performance of the hip prosthesis. The three neck shapes and three cross sections of composite hip were examined. It was found that the stress concentration in the distal region of the titanium stem which may cause the patient's thigh pains was reduced using composite material. The head neck shape was closely related with the cortical bone resorption and the cancellous bone apposition at proximal region whereas the cross-section was closely related with the relative micromotion between interfaces. The convex head neck type with the quadrangle cross-section produced less subsidence at proximal region on the medial side than the others. For all composite material cases, the cancellous bone apposition occurred at partial interfaces, which may result in a stable bio-fixation. The design performances of the convex neck head type with the hexagonal cross-section designed to insure the long-term stability were found to be more suitable than the others.

Fruit physical characteristics, proximate, mineral and starch characterization of FHIA 19 and FHIA 20 plantain and FHIA 03 cooking banana hybrids.

PubMed

Annor, George Amponsah; Asamoah-Bonti, Prudence; Sakyi-Dawson, Esther

2016-01-01

Cooking banana and plantain (Musa spp. AAB and ABB groups), have over the years been affected by pest and diseases, resulting in various organizations developing disease resistant hybrids with superior agronomic potential. The characteristics of these improved varieties needs to be studied to ascertain their suitability for use in various food systems. This study aimed at evaluating the physical characteristics, proximate and minerals composition, and characterizing the starch of plantain and a cooking banana hybrid release by Fundación Hondureña de Investigación Agrícola (FHIA), and comparing them to a local landrace in Ghana. FHIA 19 and FHIA 20 plantain, Apentu pa (a local landrace) and FHIA 03 cooking banana hybrid were used for the study. Their physical characteristics, proximate and mineral composition were determined at the proximal, midsection and distal hand positions. Starch granules and cells were then examined under light microscope. Ranges obtained for protein content for FHIA 20, FHIA 03 and FHIA 19 were 3.01-3.40, 2.66-2.91 and 2.81-2.91 %. Potassium was found to be the most abundant mineral in all the cultivars. The highest mean value of 982.5-1013.76 mg/100 g was obtained for FHIA 19. There were significant differences (p < 0.05) in the proximate and mineral composition of the varieties, however no significant difference exited between the hand positions. The largest starch granule size was found in FHIA 19 hybrid. FHIA 03 was also composed predominantly of two types: longitudinal and rounded granules with each type grouped together. The new plantain hybrids compared very well with the local landrace hence making them suitable to be incorporated into local food systems.

Windfalls for wilderness: land protection and land value in the Green Mountains

Treesearch

Spencer Phillips

2000-01-01

Land is a composite good, the price of which varies with its characteristics, including proximity to amenities. Using data from sales of land near Green Mountain National Forest wilderness areas in a hedonic price model, a positive relationship between proximity to protected wilderness and market values is revealed. The applications of this result include improved...

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

A multi-label learning based kernel automatic recommendation method for support vector machine.

PubMed

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

PubMed Central

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance. PMID:25893896

Determination of Optimal Harvest Time of Chuchung Variety Green Rice® (Oryza sativa L.) with High Contents of GABA, γ-Oryzanol, and α-Tocopherol

PubMed Central

Kim, Hoon; Kim, Oui-Woung; Ha, Ae Wha; Park, Soojin

2016-01-01

In our previous study, an early-maturing variety of rice (Oryza sativa L.), Jinbu can have feature with unique green color, various phytochemicals as well as nutritive components by the optimal early harvesting, called Green Rice® (GR). The aims of the present field experiments were to evaluate the changes in the weight of 1,000 kernels, yield, and contents of proximate and bioactive compounds in Chuchung, a mid-late maturing variety, during the pre-harvest maturation of rough rice and to research the appropriate harvest time and potent bioactivity of Chuchung GR. The weights of 1,000 kernels of Chuchung GR dramatically increased until 27 days after heading (DAH). The yields of Chuchung GR declined after 27 DAH and significantly declined to 0.0% after 45 DAH. The caloric value and total mineral contents were higher in the GR than in the full ripe stage, the brown rice (BR). In the GR, the contents of bioactive compounds, such as γ-aminobutyric acid, γ-oryzanol, and α-tocopherol, were much higher (P<0.05) than those in the BR, specifically during 24~27 DAH. Therefore, bioactive Chuchung GR can be produced with a reasonable yield at 24~27 DAH and it could be useful for applications in various nutritive and functional food products. PMID:27390725

Determination of Optimal Harvest Time of Chuchung Variety Green Rice(®) (Oryza sativa L.) with High Contents of GABA, γ-Oryzanol, and α-Tocopherol.

PubMed

Kim, Hoon; Kim, Oui-Woung; Ha, Ae Wha; Park, Soojin

2016-06-01

In our previous study, an early-maturing variety of rice (Oryza sativa L.), Jinbu can have feature with unique green color, various phytochemicals as well as nutritive components by the optimal early harvesting, called Green Rice(®) (GR). The aims of the present field experiments were to evaluate the changes in the weight of 1,000 kernels, yield, and contents of proximate and bioactive compounds in Chuchung, a mid-late maturing variety, during the pre-harvest maturation of rough rice and to research the appropriate harvest time and potent bioactivity of Chuchung GR. The weights of 1,000 kernels of Chuchung GR dramatically increased until 27 days after heading (DAH). The yields of Chuchung GR declined after 27 DAH and significantly declined to 0.0% after 45 DAH. The caloric value and total mineral contents were higher in the GR than in the full ripe stage, the brown rice (BR). In the GR, the contents of bioactive compounds, such as γ-aminobutyric acid, γ-oryzanol, and α-tocopherol, were much higher (P<0.05) than those in the BR, specifically during 24~27 DAH. Therefore, bioactive Chuchung GR can be produced with a reasonable yield at 24~27 DAH and it could be useful for applications in various nutritive and functional food products.

7 CFR 981.7 - Edible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible. [41 FR 26852, June 30, 1976] ...

Kernel K-Means Sampling for Nyström Approximation.

PubMed

He, Li; Zhang, Hong

2018-05-01

A fundamental problem in Nyström-based kernel matrix approximation is the sampling method by which training set is built. In this paper, we suggest to use kernel -means sampling, which is shown in our works to minimize the upper bound of a matrix approximation error. We first propose a unified kernel matrix approximation framework, which is able to describe most existing Nyström approximations under many popular kernels, including Gaussian kernel and polynomial kernel. We then show that, the matrix approximation error upper bound, in terms of the Frobenius norm, is equal to the -means error of data points in kernel space plus a constant. Thus, the -means centers of data in kernel space, or the kernel -means centers, are the optimal representative points with respect to the Frobenius norm error upper bound. Experimental results, with both Gaussian kernel and polynomial kernel, on real-world data sets and image segmentation tasks show the superiority of the proposed method over the state-of-the-art methods.

The crack problem in a reinforced cylindrical shell

NASA Technical Reports Server (NTRS)

Yahsi, O. S.; Erdogan, F.

1986-01-01

In this paper a partially reinforced cylinder containing an axial through crack is considered. The reinforcement is assumed to be fully bonded to the main cylinder. The composite cylinder is thus modelled by a nonhomogeneous shell having a step change in the elastic properties at the z=0 plane, z being the axial coordinate. Using a Reissner type transverse shear theory the problem is reduced to a pair of singular integral equations. In the special case of a crack tip touching the bimaterial interface it is shown that the dominant parts of the kernels of the integral equations associated with both membrane loading and bending of the shell reduce to the generalized Cauchy kernel obtained for the corresponding plane stress case. The integral equations are solved and the stress intensity factors are given for various crack and shell dimensions. A bonded fiberglass reinforcement which may serve as a crack arrestor is used as an example.

The crack problem in a reinforced cylindrical shell

NASA Technical Reports Server (NTRS)

Yahsi, O. S.; Erdogan, F.

1986-01-01

A partially reinforced cylinder containing an axial through crack is considered. The reinforcement is assumed to be fully bonded to the main cylinder. The composite cylinder is thus modelled by a nonhomogeneous shell having a step change in the elastic properties at the z = 0 plane, z being the axial coordinate. Using a Reissner type transverse shear theory the problem is reduced to a pair of singular integral equations. In the special case of a crack tip touching the bimaterial interface it is shown that the dominant parts of the kernels of the integral equations associated with both membrane loading and bending of the shell reduce to the generalized Cauchy kernel obtained for the corresponding plane stress case. The integral equations are solved and the stress intensity factors are given for various crack and shell dimensions. A bonded fiberglass reinforcement which may serve as a crack arrestor is used as an example.

Accumulation of primary and secondary metabolites in edible jackfruit seed tissues and scavenging of reactive nitrogen species.

PubMed

Fernandes, Fátima; Ferreres, Federico; Gil-Izquierdo, Angel; Oliveira, Andreia P; Valentão, Patrícia; Andrade, Paula B

2017-10-15

Studies involving jackfruit tree (Artocarpus heterophyllus Lam.) focus on its fruit. Nevertheless a considerable part of jackfruit weight is represented by its seeds. Despite being consumed in several countries, knowledge about the chemical composition of these seeds is scarce. In this work, the accumulation of primary and secondary metabolites in jackfruit seed kernel and seed coating membrane was studied. Sixty-seven compounds were identified, sixty of them being reported for the first time in jackfruit seed. Both tissues had a similar qualitative profile, but significant quantitative differences were found. The capacity of aqueous extracts from jackfruit seed kernel and seed coating membranes to scavenge nitric oxide radical was also evaluated for the first time, the extract prepared from the seed coating membrane being the most potent. This work increases the potential revenue from a food that is still largely wasted. Copyright © 2017 Elsevier Ltd. All rights reserved.

Isolation and Structural Characterization of Antioxidant Peptides from Degreased Apricot Seed Kernels.

PubMed

Zhang, Haisheng; Xue, Jing; Zhao, Huanxia; Zhao, Xinshuai; Xue, Huanhuan; Sun, Yuhan; Xue, Wanrui

2018-05-03

Background : The composition and sequence of amino acids have a prominent influence on theantioxidant activities of peptides. Objective : A series of isolation and purification experiments was conducted to explore the amino acid sequence of antioxidant peptides, which led to its antioxidation causes. Methods : The degreased apricot seed kernels were hydrolyzed by compound proteases of alkaline protease and flavor protease (3:2, u/u) to prepare apricot seed kernel hydrolysates (ASKH). ASKH were separated into ASKH-A and ASKH-B by dialysis bag. ASKH-B (MW < 3.5 kDa) was further separated into fractions by Sephadex G-25 and G-15 gel-filtration chromatography. Reversed-phase HPLC (RP-HPLC) was performed to separate fraction B4b into two antioxidant peptides (peptide B4b-4 and B4b-6). Results : The amino acid sequences were Val-Leu-Tyr-Ile-Trp and Ser-Val-Pro-Tyr-Glu, respectively. Conclusions : The results suggested that ASKH antioxidant peptides may have potential utility as healthy ingredients and as food preservatives due to their antioxidant activity. Highlights : Materials with regional characteristics were selected to explore, and hydrolysates were identified by RP-HPLC and matrix-assisted laser desorption ionization-time-of-flight-MS to obtain amino acid sequences.

Exploiting graph kernels for high performance biomedical relation extraction.

PubMed

Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

2018-01-30

Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM performed better than APG kernel for the BioInfer dataset, in the Area Under Curve (AUC) measure (74% vs 69%). However, for all the other PPI datasets, namely AIMed, HPRD50, IEPA and LLL, ASM is substantially outperformed by the APG kernel in F-score and AUC measures. We demonstrate a high performance Chemical Induced Disease relation extraction, without employing external knowledge sources or task specific heuristics. Our work shows that graph kernels are effective in extracting relations that are expressed in multiple sentences. We also show that the graph kernels, namely the ASM and APG kernels, substantially outperform the tree kernels. Among the graph kernels, we showed the ASM kernel as effective for biomedical relation extraction, with comparable performance to the APG kernel for datasets such as the CID-sentence level relation extraction and BioInfer in PPI. Overall, the APG kernel is shown to be significantly more accurate than the ASM kernel, achieving better performance on most datasets.

[Proximal composition, lipid and cholesterol content of meat from pigs fed peach-palm meal (Bactris gasipaes Kunth) and synthetic lysine].

PubMed

Jerez-Timaure, Nancy; Rivero, Janeth Colina; Araque, Humberto; Jiménez, Paola; Velazco, Mariela; Colmenares, Ciolys

2011-03-01

Two experiments were conducted to evaluate the proximal composition, lipids and cholesterol content of meat from pigs fed diets with peach-palm meal (PPM), with or without addition of synthetic lysine (LYS). In experiment 1, 24 pigs were randomly allotted into six treatments with three levels of PPM (0.16 and 32%) and two levels of LYS (0 and 0.27%). In experiment II, 16 finishing pigs were fed with two levels of PPM (0 and 17.50%) and two levels of LYS (0 and 0.27%). At the end of each experiment (42 and 35 d, respectively), pigs were slaughtered and loin samples were obtained to determine crude protein, dry matter, moisture, ash, total lipids, and cholesterol content. In experiment I, pork loin from 16% PPM had more dry matter (26.45 g/100 g) and less moisture (73.49 g/100g) than pork loin from 32% PPM (25.11 y 75.03 g/100g, respectively). Meat samples from pigs without LYS had higher (p < 0.05) content of lipids (2.11 g/100 g) than meat from pigs that consumed LYS (1.72 g/100 g). In experiment II, the proximal, lipids and cholesterol content were similar among treatments. The PPM addition to pig diets did not affect the proximal composition of pork, while LYS addition indicated a reduction of total lipids, which could result as an alternative to obtain leaner meat.

7 CFR 810.2202 - Definition of other terms.

Code of Federal Regulations, 2014 CFR

2014-01-01

... kernels, foreign material, and shrunken and broken kernels. The sum of these three factors may not exceed... the removal of dockage and shrunken and broken kernels. (g) Heat-damaged kernels. Kernels, pieces of... sample after the removal of dockage and shrunken and broken kernels. (h) Other grains. Barley, corn...

7 CFR 981.8 - Inedible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel, or...

7 CFR 51.1415 - Inedible kernels.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Inedible kernels. 51.1415 Section 51.1415 Agriculture... Standards for Grades of Pecans in the Shell 1 Definitions § 51.1415 Inedible kernels. Inedible kernels means that the kernel or pieces of kernels are rancid, moldy, decayed, injured by insects or otherwise...

An Approximate Approach to Automatic Kernel Selection.

PubMed

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

[Seasonal variation in proximate composition of mussels Tagelus peruvianus (Bivalvia: Solecurtidae) from the Gulf of Nicoya, Puntarenas, Costa Rica].

PubMed

Fonseca Rodríguez, Cristian; Marín-Vindas, Carolina; Chavarría-Solera, Fabián; Agüero Pedro, Toledo

2011-12-01

Marine bivalves are a very important food source for human consumption, and species that has not been of traditional use as a fishery resource are gaining interest. Seasonal variation in proximate composition, condition index and energy or caloric content of the mussel Tagelus peruvianus were studied in the Gulf of Nicoya, Puntarenas, Costa Rica. From November 2007 to October 2008, a total of 35 to 40 specimens per month were collected. The proximate composition using the AOAC methods was determined. Results showed that the condition index during December, January and May decreased, indicative of two spawning periods and one gonadal resting phase. Soft tissues were respectively characterized by protein (61.9 +/- 4.3%), carbohydrates (15.7 +/- 2.4%), ash (14.0 +/- 1.9%) and lipids (8.5 +/- 1.7%). The average caloric content was 5.0 +/- 0.1 kcal/g. The results showed that the decrease in protein and fat percentage, and calories content, occurred during the spawning seasons. We suggest that T. peruvianus has an optimal nutritional value for human consumption because of the low-fat and moderate protein content.

Aflatoxin, proximate composition and mineral profile of stored broiler feed treated with medicinal plant leaves.

PubMed

Hassan, S M; Sultana, B; Atta, A; Qureshi, N; Iqbal, M; Abbas, M

2017-09-01

In the present investigation, the Morus alba (M. alba), Vitis vinifera (V. vinifera), Ficus religiosa (F. religiosa) and Citrus paradisi (C. paradisi) leaves anti-aflatoxigenic activities were evaluated in Aspergillus flavus (A. flavus) inoculated feed. The broiler feed inoculated with A. flavus was treated with selected medicinal plant leaf powder (5%, 10% and 15% w/w) and stored for the period of six months at 28°C and 16% moisture. The aflatoxins (AFTs) were estimated at the end of each month by Reversed Phase High Performance Liquid Chromatography (RP-HPLC) method along with proximate composition and mineral contents. Plant leaves controlled AFTs efficiently without affecting the feed proximate composition and mineral contents. The M. alba leaves completely inhibition (100%) the AFTs (B 1 and B 2 ) in feed at very low concentration (5%). Other plants also showed significant (P<0.05) inhibition of AFTs production without affecting the feed quality over the storage period of six months. Based on promising efficiency of selected medicinal plant leaves, A. flavus produced AFTs could possibly be controlled in stored poultry feed. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Competing factors of compost concentration and proximity to root affect the distribution of streptomycetes.

PubMed

Inbar, Ehud; Green, Stefan J; Hadar, Yitzhak; Minz, Dror

2005-07-01

Streptomycetes are important members of soil microbial communities and are particularly active in the degradation of recalcitrant macromolecules and have been implicated in biological control of plant disease. Using a streptomycetes-specific polymerase chain reaction (PCR)-denaturing gradient gel electrophoresis (PCR-DGGE) methodology coupled with band excision and sequence analysis, we examined the effect of grape marc compost amendment to soil on cucumber plant-associated streptomycetes community composition. We observed that both compost amendment and proximity to the root surface influenced the streptomycetes community composition. A strong root selection for a soil-derived Streptomycete, most closely related to Streptomyces thermotolerans, S. iakyrus, and S. thermocarboxydus, was independent of compost amendment rate. However, while the impact of compost amendment was mitigated with increasing proximity to the root, high levels of compost amendment resulted in the detection of compost-derived species on the root surface. Conversely, in rhizosphere and non-rhizosphere soils, the community composition of streptomycetes was affected strongly even by modest compost amendment. The application of a streptomycetes-specific PCR primer set combined with DGGE analysis provided a rapid means of examining the distribution and ecology of streptomycetes in soils and plant-associated environments.

Understanding API-polymer proximities in amorphous stabilized composite drug products using fluorine-carbon 2D HETCOR solid-state NMR.

PubMed

Abraham, Anuji; Crull, George

2014-10-06

A simple and robust method for obtaining fluorine-carbon proximities was established using a (19)F-(13)C heteronuclear correlation (HETCOR) two-dimensional (2D) solid-state nuclear magnetic resonance (ssNMR) experiment under magic-angle spinning (MAS). The method was applied to study a crystalline active pharmaceutical ingredient (API), avagacestat, containing two types of fluorine atoms and its API-polymer composite drug product. These results provide insight into the molecular structure, aid with assigning the carbon resonances, and probe API-polymer proximities in amorphous spray dried dispersions (SDD). This method has an advantage over the commonly used (1)H-(13)C HETCOR because of the large chemical shift dispersion in the fluorine dimension. In the present study, fluorine-carbon distances up to 8 Å were probed, giving insight into the API structure, crystal packing, and assignments. Most importantly, the study demonstrates a method for probing an intimate molecular level contact between an amorphous API and a polymer in an SDD, giving insights into molecular association and understanding of the role of the polymer in API stability (such as recrystallization, degradation, etc.) in such novel composite drug products.

Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

PubMed

Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

2018-02-13

Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Unconventional protein sources: apricot seed kernels.

PubMed

Gabrial, G N; El-Nahry, F I; Awadalla, M Z; Girgis, S M

1981-09-01

Hamawy apricot seed kernels (sweet), Amar apricot seed kernels (bitter) and treated Amar apricot kernels (bitterness removed) were evaluated biochemically. All kernels were found to be high in fat (42.2--50.91%), protein (23.74--25.70%) and fiber (15.08--18.02%). Phosphorus, calcium, and iron were determined in all experimental samples. The three different apricot seed kernels were used for extensive study including the qualitative determination of the amino acid constituents by acid hydrolysis, quantitative determination of some amino acids, and biological evaluation of the kernel proteins in order to use them as new protein sources. Weanling albino rats failed to grow on diets containing the Amar apricot seed kernels due to low food consumption because of its bitterness. There was no loss in weight in that case. The Protein Efficiency Ratio data and blood analysis results showed the Hamawy apricot seed kernels to be higher in biological value than treated apricot seed kernels. The Net Protein Ratio data which accounts for both weight, maintenance and growth showed the treated apricot seed kernels to be higher in biological value than both Hamawy and Amar kernels. The Net Protein Ratio for the last two kernels were nearly equal.

An introduction to kernel-based learning algorithms.

PubMed

Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

2001-01-01

This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as...

Design of CT reconstruction kernel specifically for clinical lung imaging

NASA Astrophysics Data System (ADS)

Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

2005-04-01

In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

Quality changes in macadamia kernel between harvest and farm-gate.

PubMed

Walton, David A; Wallace, Helen M

2011-02-01

Macadamia integrifolia, Macadamia tetraphylla and their hybrids are cultivated for their edible kernels. After harvest, nuts-in-shell are partially dried on-farm and sorted to eliminate poor-quality kernels before consignment to a processor. During these operations, kernel quality may be lost. In this study, macadamia nuts-in-shell were sampled at five points of an on-farm postharvest handling chain from dehusking to the final storage silo to assess quality loss prior to consignment. Shoulder damage, weight of pieces and unsound kernel were assessed for raw kernels, and colour, mottled colour and surface damage for roasted kernels. Shoulder damage, weight of pieces and unsound kernel for raw kernels increased significantly between the dehusker and the final silo. Roasted kernels displayed a significant increase in dark colour, mottled colour and surface damage during on-farm handling. Significant loss of macadamia kernel quality occurred on a commercial farm during sorting and storage of nuts-in-shell before nuts were consigned to a processor. Nuts-in-shell should be dried as quickly as possible and on-farm handling minimised to maintain optimum kernel quality. 2010 Society of Chemical Industry.

A random walk description of individual animal movement accounting for periods of rest

NASA Astrophysics Data System (ADS)

Tilles, Paulo F. C.; Petrovskii, Sergei V.; Natti, Paulo L.

2016-11-01

Animals do not move all the time but alternate the period of actual movement (foraging) with periods of rest (e.g. eating or sleeping). Although the existence of rest times is widely acknowledged in the literature and has even become a focus of increased attention recently, the theoretical approaches to describe animal movement by calculating the dispersal kernel and/or the mean squared displacement (MSD) rarely take rests into account. In this study, we aim to bridge this gap. We consider a composite stochastic process where the periods of active dispersal or `bouts' (described by a certain baseline probability density function (pdf) of animal dispersal) alternate with periods of immobility. For this process, we derive a general equation that determines the pdf of this composite movement. The equation is analysed in detail in two special but important cases such as the standard Brownian motion described by a Gaussian kernel and the Levy flight described by a Cauchy distribution. For the Brownian motion, we show that in the large-time asymptotics the effect of rests results in a rescaling of the diffusion coefficient. The movement occurs as a subdiffusive transition between the two diffusive asymptotics. Interestingly, the Levy flight case shows similar properties, which indicates a certain universality of our findings.

An Experimental Study of Briquetting Process of Torrefied Rubber Seed Kernel and Palm Oil Shell.

PubMed

Hamid, M Fadzli; Idroas, M Yusof; Ishak, M Zulfikar; Zainal Alauddin, Z Alimuddin; Miskam, M Azman; Abdullah, M Khalil

2016-01-01

Torrefaction process of biomass material is essential in converting them into biofuel with improved calorific value and physical strength. However, the production of torrefied biomass is loose, powdery, and nonuniform. One method of upgrading this material to improve their handling and combustion properties is by densification into briquettes of higher density than the original bulk density of the material. The effects of critical parameters of briquetting process that includes the type of biomass material used for torrefaction and briquetting, densification temperature, and composition of binder for torrefied biomass are studied and characterized. Starch is used as a binder in the study. The results showed that the briquette of torrefied rubber seed kernel (RSK) is better than torrefied palm oil shell (POS) in both calorific value and compressive strength. The best quality of briquettes is yielded from torrefied RSK at the ambient temperature of briquetting process with the composition of 60% water and 5% binder. The maximum compressive load for the briquettes of torrefied RSK is 141 N and the calorific value is 16 MJ/kg. Based on the economic evaluation analysis, the return of investment (ROI) for the mass production of both RSK and POS briquettes is estimated in 2-year period and the annual profit after payback was approximately 107,428.6 USD.

A random walk description of individual animal movement accounting for periods of rest.

PubMed

Tilles, Paulo F C; Petrovskii, Sergei V; Natti, Paulo L

2016-11-01

Animals do not move all the time but alternate the period of actual movement (foraging) with periods of rest (e.g. eating or sleeping). Although the existence of rest times is widely acknowledged in the literature and has even become a focus of increased attention recently, the theoretical approaches to describe animal movement by calculating the dispersal kernel and/or the mean squared displacement (MSD) rarely take rests into account. In this study, we aim to bridge this gap. We consider a composite stochastic process where the periods of active dispersal or 'bouts' (described by a certain baseline probability density function (pdf) of animal dispersal) alternate with periods of immobility. For this process, we derive a general equation that determines the pdf of this composite movement. The equation is analysed in detail in two special but important cases such as the standard Brownian motion described by a Gaussian kernel and the Levy flight described by a Cauchy distribution. For the Brownian motion, we show that in the large-time asymptotics the effect of rests results in a rescaling of the diffusion coefficient. The movement occurs as a subdiffusive transition between the two diffusive asymptotics. Interestingly, the Levy flight case shows similar properties, which indicates a certain universality of our findings.

A random walk description of individual animal movement accounting for periods of rest

PubMed Central

Tilles, Paulo F. C.

2016-01-01

Animals do not move all the time but alternate the period of actual movement (foraging) with periods of rest (e.g. eating or sleeping). Although the existence of rest times is widely acknowledged in the literature and has even become a focus of increased attention recently, the theoretical approaches to describe animal movement by calculating the dispersal kernel and/or the mean squared displacement (MSD) rarely take rests into account. In this study, we aim to bridge this gap. We consider a composite stochastic process where the periods of active dispersal or ‘bouts’ (described by a certain baseline probability density function (pdf) of animal dispersal) alternate with periods of immobility. For this process, we derive a general equation that determines the pdf of this composite movement. The equation is analysed in detail in two special but important cases such as the standard Brownian motion described by a Gaussian kernel and the Levy flight described by a Cauchy distribution. For the Brownian motion, we show that in the large-time asymptotics the effect of rests results in a rescaling of the diffusion coefficient. The movement occurs as a subdiffusive transition between the two diffusive asymptotics. Interestingly, the Levy flight case shows similar properties, which indicates a certain universality of our findings. PMID:28018645

Physical modification of palm kernel meal improved available carbohydrate, physicochemical properties and in vitro digestibility in economic freshwater fish.

PubMed

Thongprajukaew, Karun; Yawang, Pinya; Dudae, Lateepah; Bilanglod, Husna; Dumrongrittamatt, Terdtoon; Tantikitti, Chutima; Kovitvadhi, Uthaiwan

2013-12-01

Unavailable carbohydrates are an important limiting factor for utilization of palm kernel meal (PKM) as aquafeed ingredients. The aim of this study was to improve available carbohydrate from PKM. Different physical modifications including water soaking, microwave irradiation, gamma irradiation and electron beam, were investigated in relation to chemical composition, physicochemical properties and in vitro carbohydrate digestibility using digestive enzymes from economic freshwater fish. Modified methods had significant (P < 0.05) effects on chemical composition by decreasing crude fiber and increasing available carbohydrates. Improvements in physicochemical properties of PKM, such as water solubility, microstructure, relative crystallinity and lignocellulosic spectra, were mainly achieved by soaking and microwave irradiation. Carbohydrate digestibility varied among the physical modifications tested (P < 0.05) and three fish species had different abilities to digest PKM. Soaking was the appropriate modification for increasing carbohydrate digestion specifically in Nile tilapia (Oreochromis niloticus), whereas either soaking or microwave irradiation was effective for striped snakehead (Channa striata). For walking catfish (Clarias batrachus), carbohydrate digestibility was similar among raw, soaked and microwave-irradiated PKM. These findings suggest that soaking and microwave irradiation could be practical methods for altering appropriate physicochemical properties of PKM as well as increasing carbohydrate digestibility in select economic freshwater fish. © 2013 Society of Chemical Industry.

A new discriminative kernel from probabilistic models.

PubMed

Tsuda, Koji; Kawanabe, Motoaki; Rätsch, Gunnar; Sonnenburg, Sören; Müller, Klaus-Robert

2002-10-01

Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived; from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

Support vector machine in crash prediction at the level of traffic analysis zones: Assessing the spatial proximity effects.

PubMed

Dong, Ni; Huang, Helai; Zheng, Liang

2015-09-01

In zone-level crash prediction, accounting for spatial dependence has become an extensively studied topic. This study proposes Support Vector Machine (SVM) model to address complex, large and multi-dimensional spatial data in crash prediction. Correlation-based Feature Selector (CFS) was applied to evaluate candidate factors possibly related to zonal crash frequency in handling high-dimension spatial data. To demonstrate the proposed approaches and to compare them with the Bayesian spatial model with conditional autoregressive prior (i.e., CAR), a dataset in Hillsborough county of Florida was employed. The results showed that SVM models accounting for spatial proximity outperform the non-spatial model in terms of model fitting and predictive performance, which indicates the reasonableness of considering cross-zonal spatial correlations. The best model predictive capability, relatively, is associated with the model considering proximity of the centroid distance by choosing the RBF kernel and setting the 10% of the whole dataset as the testing data, which further exhibits SVM models' capacity for addressing comparatively complex spatial data in regional crash prediction modeling. Moreover, SVM models exhibit the better goodness-of-fit compared with CAR models when utilizing the whole dataset as the samples. A sensitivity analysis of the centroid-distance-based spatial SVM models was conducted to capture the impacts of explanatory variables on the mean predicted probabilities for crash occurrence. While the results conform to the coefficient estimation in the CAR models, which supports the employment of the SVM model as an alternative in regional safety modeling. Copyright © 2015 Elsevier Ltd. All rights reserved.

Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

PubMed

Kwak, Nojun

2016-05-20

Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

Does the choice of neighbourhood supermarket access measure influence associations with individual-level fruit and vegetable consumption? A case study from Glasgow.

PubMed

Thornton, Lukar E; Pearce, Jamie R; Macdonald, Laura; Lamb, Karen E; Ellaway, Anne

2012-07-27

Previous studies have provided mixed evidence with regards to associations between food store access and dietary outcomes. This study examines the most commonly applied measures of locational access to assess whether associations between supermarket access and fruit and vegetable consumption are affected by the choice of access measure and scale. Supermarket location data from Glasgow, UK (n = 119), and fruit and vegetable intake data from the 'Health and Well-Being' Survey (n = 1041) were used to compare various measures of locational access. These exposure variables included proximity estimates (with different points-of-origin used to vary levels of aggregation) and density measures using three approaches (Euclidean and road network buffers and Kernel density estimation) at distances ranging from 0.4 km to 5 km. Further analysis was conducted to assess the impact of using smaller buffer sizes for individuals who did not own a car. Associations between these multiple access measures and fruit and vegetable consumption were estimated using linear regression models. Levels of spatial aggregation did not impact on the proximity estimates. Counts of supermarkets within Euclidean buffers were associated with fruit and vegetable consumption at 1 km, 2 km and 3 km, and for our road network buffers at 2 km, 3 km, and 4 km. Kernel density estimates provided the strongest associations and were significant at a distance of 2 km, 3 km, 4 km and 5 km. Presence of a supermarket within 0.4 km of road network distance from where people lived was positively associated with fruit consumption amongst those without a car (coef. 0.657; s.e. 0.247; p0.008). The associations between locational access to supermarkets and individual-level dietary behaviour are sensitive to the method by which the food environment variable is captured. Care needs to be taken to ensure robust and conceptually appropriate measures of access are used and these should be grounded in a clear a priori reasoning.

Does the choice of neighbourhood supermarket access measure influence associations with individual-level fruit and vegetable consumption? A case study from Glasgow

PubMed Central

2012-01-01

Background Previous studies have provided mixed evidence with regards to associations between food store access and dietary outcomes. This study examines the most commonly applied measures of locational access to assess whether associations between supermarket access and fruit and vegetable consumption are affected by the choice of access measure and scale. Method Supermarket location data from Glasgow, UK (n = 119), and fruit and vegetable intake data from the ‘Health and Well-Being’ Survey (n = 1041) were used to compare various measures of locational access. These exposure variables included proximity estimates (with different points-of-origin used to vary levels of aggregation) and density measures using three approaches (Euclidean and road network buffers and Kernel density estimation) at distances ranging from 0.4 km to 5 km. Further analysis was conducted to assess the impact of using smaller buffer sizes for individuals who did not own a car. Associations between these multiple access measures and fruit and vegetable consumption were estimated using linear regression models. Results Levels of spatial aggregation did not impact on the proximity estimates. Counts of supermarkets within Euclidean buffers were associated with fruit and vegetable consumption at 1 km, 2 km and 3 km, and for our road network buffers at 2 km, 3 km, and 4 km. Kernel density estimates provided the strongest associations and were significant at a distance of 2 km, 3 km, 4 km and 5 km. Presence of a supermarket within 0.4 km of road network distance from where people lived was positively associated with fruit consumption amongst those without a car (coef. 0.657; s.e. 0.247; p0.008). Conclusions The associations between locational access to supermarkets and individual-level dietary behaviour are sensitive to the method by which the food environment variable is captured. Care needs to be taken to ensure robust and conceptually appropriate measures of access are used and these should be grounded in a clear a priori reasoning. PMID:22839742

Estimating peer density effects on oral health for community-based older adults.

PubMed

Chakraborty, Bibhas; Widener, Michael J; Mirzaei Salehabadi, Sedigheh; Northridge, Mary E; Kum, Susan S; Jin, Zhu; Kunzel, Carol; Palmer, Harvey D; Metcalf, Sara S

2017-12-29

As part of a long-standing line of research regarding how peer density affects health, researchers have sought to understand the multifaceted ways that the density of contemporaries living and interacting in proximity to one another influence social networks and knowledge diffusion, and subsequently health and well-being. This study examined peer density effects on oral health for racial/ethnic minority older adults living in northern Manhattan and the Bronx, New York, NY. Peer age-group density was estimated by smoothing US Census data with 4 kernel bandwidths ranging from 0.25 to 1.50 mile. Logistic regression models were developed using these spatial measures and data from the ElderSmile oral and general health screening program that serves predominantly racial/ethnic minority older adults at community centers in northern Manhattan and the Bronx. The oral health outcomes modeled as dependent variables were ordinal dentition status and binary self-rated oral health. After construction of kernel density surfaces and multiple imputation of missing data, logistic regression analyses were performed to estimate the effects of peer density and other sociodemographic characteristics on the oral health outcomes of dentition status and self-rated oral health. Overall, higher peer density was associated with better oral health for older adults when estimated using smaller bandwidths (0.25 and 0.50 mile). That is, statistically significant relationships (p < 0.01) between peer density and improved dentition status were found when peer density was measured assuming a more local social network. As with dentition status, a positive significant association was found between peer density and fair or better self-rated oral health when peer density was measured assuming a more local social network. This study provides novel evidence that the oral health of community-based older adults is affected by peer density in an urban environment. To the extent that peer density signifies the potential for social interaction and support, the positive significant effects of peer density on improved oral health point to the importance of place in promoting social interaction as a component of healthy aging. Proximity to peers and their knowledge of local resources may facilitate utilization of community-based oral health care.

Effect of isolation techniques on the characteristics of pigeon pea (Cajanus cajan) protein isolates.

PubMed

Adenekan, Monilola K; Fadimu, Gbemisola J; Odunmbaku, Lukumon A; Oke, Emmanuel K

2018-01-01

In this study, the effect of different isolation techniques on the isolated proteins from pigeon pea was investigated. Water, methanol, ammonium sulfate, and acetone were used for the precipitation of proteins from pigeon pea. Proximate composition, and antinutritional and functional properties of the pigeon pea flour and the isolated proteins were measured. Data generated were statistically analyzed. The proximate composition of the water-extracted protein isolate was moisture 8.30%, protein 91.83%, fat 0.25%, ash 0.05%, and crude fiber 0.05%. The methanol-extracted protein isolate composition was moisture 7.87%, protein 91.83%, fat 0.17%, and ash 0.13%, while crude fiber and carbohydrates were not detected. The composition of the ammonium sulfate-extracted protein isolate was moisture 7.73%, protein 91.73%, fat 0.36, ash 0.13%, and crude fiber 0.67%. The acetone-extracted protein isolate composition was moisture 8.03%, protein 91.50%, ash 0.67%, and fat 0.30%, but crude fiber and carbohydrates were not detected. The isolate precipitated with ammonium sulfate displayed the highest foaming capacity (37.63%) and foaming stability (55.75%). Isolates precipitated with methanol and acetone had the highest water absorption capacity (160%). Pigeon pea protein isolates extracted with methanol and ammonium sulfate had the highest oil absorption capacity of 145%. Protein isolates recovered through acetone and methanol had the highest emulsifying capacity of 2.23% and emulsifying stability of 91.47%, respectively. The proximate composition of the recovered protein isolates were of high purity. This shows the efficiency of the extraction techniques. The isolates had desirable solubility index. All the isolation techniques brought significant impact on the characteristics of the isolated pigeon pea protein.

Increasing accuracy of dispersal kernels in grid-based population models

USGS Publications Warehouse

Slone, D.H.

2011-01-01

Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels (σ > 10 cells), the total kernel error was <10 &sup-11; compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10-11 and invasion time error to <5%.

Anthraquinones isolated from the browned Chinese chestnut kernels (Castanea mollissima blume)

NASA Astrophysics Data System (ADS)

Zhang, Y. L.; Qi, J. H.; Qin, L.; Wang, F.; Pang, M. X.

2016-08-01

Anthraquinones (AQS) represent a group of secondary metallic products in plants. AQS are often naturally occurring in plants and microorganisms. In a previous study, we found that AQS were produced by enzymatic browning reaction in Chinese chestnut kernels. To find out whether non-enzymatic browning reaction in the kernels could produce AQS too, AQS were extracted from three groups of chestnut kernels: fresh kernels, non-enzymatic browned kernels, and browned kernels, and the contents of AQS were determined. High performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) methods were used to identify two compounds of AQS, rehein(1) and emodin(2). AQS were barely exists in the fresh kernels, while both browned kernel groups sample contained a high amount of AQS. Thus, we comfirmed that AQS could be produced during both enzymatic and non-enzymatic browning process. Rhein and emodin were the main components of AQS in the browned kernels.

Colour and oxidative stability of mince produced from fresh and frozen/thawed fallow deer (Dama dama) meat.

PubMed

Chakanya, Chido; Arnaud, Elodie; Muchenje, Voster; Hoffman, Louwrens C

2017-04-01

Colour and oxidative stability of minced meat from fresh and frozen/thawed fallow deer was investigated. For the seven fallow deer harvested, half of the meat was minced fresh and half was frozen (-20°C) for 2months under vacuum prior to grinding. Surface colour attributes, myoglobin content and surface redox forms, pH and lipid oxidation of the mince were measured during eight days of display storage. Proximate composition was determined in mince on day 0, fatty acid composition on day 0 and 8. Freezing had no effect on the proximate composition or fatty acid composition of the mince. Frozen meat mince had lower (P≤0.05) total myoglobin content but higher (P≤0.05) decrease in redness (a*) during display storage, higher (P≤0.05) accumulation of metmyoglobin at the surface from day 2 and higher (P≤0.05) TBARS values. Results showed shorter colour and oxidative stability for frozen meat mince as compared to mince from fresh meat. Display storage however did not affect fatty acid composition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chemical, mineral composition, and sensory acceptability of cocoyam-based recipes enriched with cowpea flour.

PubMed

Olayiwola, Ibiyemi; Folaranmi, Funmi; Adebowale, Abdul-Rasaq A; Oluseye, Onabanjo; Ajoke, Sanni; Wasiu, Afolabi

2013-05-01

The study was conducted to improve cocoyam-based recipes (steamed cocoyam paste [ ebiripo ], ikokore, and fried cocoyam balls [ ojojo ]) using different blends of cocoyam and cowpea flours (100:0, 80:20, 70:30, 60:40, and 50:50). The proximate composition, mineral composition, and sensory qualities of the recipes were determined using standard analytical procedures. The recipes had significantly ( P  <   0.05) higher contents of protein, fat, crude fiber, iron, zinc, sodium, and phosphorus compared with the control recipe (100% cocoyam flour). The protein content was highest in all recipes containing 50:50 cocoyam: cowpea flour (10.79%, 10.56%, 10.36% for ojojo, ikokore, and ebiripo , respectively). However, ikokore had higher iron (2.5 mg), phosphorus (92.5 mg), and zinc (1.92 mg) contents than ebiripo and ojojo . While the 80:20 recipe for ebiripo had significantly ( P  <   0.05) higher flavor and overall acceptability scores compared with other recipes. In conclusion, enrichment of cocoyam-based recipes with cowpea flour improved the proximate composition, mineral composition, and sensory acceptability of the foods.

Nutrient database improvement project: Separable components and proximate composition of raw and cooked retail cuts from the beef loin and round.

PubMed

Acheson, R J; Woerner, D R; Martin, J N; Belk, K E; Engle, T E; Brown, T R; Brooks, J C; Luna, A M; Thompson, L D; Grimes, H L; Arnold, A N; Savell, J W; Gehring, K B; Douglass, L W; Howe, J C; Patterson, K Y; Roseland, J M; Williams, J R; Cifelli, A; Leheska, J M; McNeill, S H

2015-12-01

Beef nutrition research has become increasingly important domestically and internationally for the beef industry and its consumers. The objective of this study was to analyze the nutrient composition of ten beef loin and round cuts to update the nutrient data in the USDA National Nutrient Database for Standard Reference. Seventy-two carcasses representing a national composite of Yield Grade, Quality Grade, sex classification, and genetic type were identified from six regions across the U.S. Beef short loins, strip loins, tenderloins, inside rounds, and eye of rounds (NAMP # 173, 175, 190A, 169A, and 171C) were collected from the selected carcasses and shipped to three university meat laboratories for storage, retail fabrication, and raw/cooked analysis of nutrients. Sample homogenates from each animal were analyzed for proximate composition. These data provide updated information regarding the nutrient status of beef, in addition, to determining the influence of Quality Grade, Yield Grade, and sex classification on nutrient composition. Copyright © 2015. Published by Elsevier Ltd.

Effects of incorporating agro-industrial by-products into diet of New Zealand rabbits: Case of rebus of date and apricot kernel meal.

PubMed

Mennani, Achour; Arbouche, Rafik; Arbouche, Yasmine; Montaigne, Etienne; Arbouche, Fodil; Arbouche, Halima Saâdia

2017-12-01

The aim of this study was to determine the effects of incorporating the by-products complex of date and apricot on the fattening performance of the New Zealand breed of rabbits, to reduce the economic costs of the food formula. A total of 288 young New Zealand rabbits aged 35 days were divided into four equal groups each containing 72 animals and into sub-groups of 6 rabbits per cage, depending on the rate of substitution of corn by date rebus and of soybean meal by apricot kernel meal (0%, 10%, 20%, and 30%). The change in weight from day 35 to 77 and the average daily gain are not significantly different, regardless of the diet. The pH and water content are proportional to the substitution rates (6.4-6.6% and 66.5-68.8%). Meat protein levels increased significantly, in particular for the 10% and 30% groups (+8.1% and 6%) while the fat and mineral content levels decreased significantly, in particular for the 30% group displaying -16% and -17%, respectively. Incorporation of dates and apricot kernel meal into the ration of rabbits reduces the cost of the kilogram of food produced of -9%, with an opportunity cost of 165 Algerian dinars (DZD). The date rebus/apricot kernel meal complex can be used as an alternative to the corn/soybean meal complex at substitution rates of up to 30% without adverse effects on growth rates, feed contribution, or slaughter yield. It improves the chemical composition of the meat and reduces the cost price of the quintal of feed produced.

Effects of incorporating agro-industrial by-products into diet of New Zealand rabbits: Case of rebus of date and apricot kernel meal

PubMed Central

Mennani, Achour; Arbouche, Rafik; Arbouche, Yasmine; Montaigne, Etienne; Arbouche, Fodil; Arbouche, Halima Saâdia

2017-01-01

Aim: The aim of this study was to determine the effects of incorporating the by-products complex of date and apricot on the fattening performance of the New Zealand breed of rabbits, to reduce the economic costs of the food formula. Materials and Methods: A total of 288 young New Zealand rabbits aged 35 days were divided into four equal groups each containing 72 animals and into sub-groups of 6 rabbits per cage, depending on the rate of substitution of corn by date rebus and of soybean meal by apricot kernel meal (0%, 10%, 20%, and 30%). Results: The change in weight from day 35 to 77 and the average daily gain are not significantly different, regardless of the diet. The pH and water content are proportional to the substitution rates (6.4-6.6% and 66.5-68.8%). Meat protein levels increased significantly, in particular for the 10% and 30% groups (+8.1% and 6%) while the fat and mineral content levels decreased significantly, in particular for the 30% group displaying −16% and −17%, respectively. Incorporation of dates and apricot kernel meal into the ration of rabbits reduces the cost of the kilogram of food produced of −9%, with an opportunity cost of 165 Algerian dinars (DZD). Conclusion: The date rebus/apricot kernel meal complex can be used as an alternative to the corn/soybean meal complex at substitution rates of up to 30% without adverse effects on growth rates, feed contribution, or slaughter yield. It improves the chemical composition of the meat and reduces the cost price of the quintal of feed produced. PMID:29391686

A point kernel algorithm for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Debus, Charlotte; Oelfke, Uwe; Bartzsch, Stefan

2017-11-01

Microbeam radiation therapy (MRT) is a treatment approach in radiation therapy where the treatment field is spatially fractionated into arrays of a few tens of micrometre wide planar beams of unusually high peak doses separated by low dose regions of several hundred micrometre width. In preclinical studies, this treatment approach has proven to spare normal tissue more effectively than conventional radiation therapy, while being equally efficient in tumour control. So far dose calculations in MRT, a prerequisite for future clinical applications are based on Monte Carlo simulations. However, they are computationally expensive, since scoring volumes have to be small. In this article a kernel based dose calculation algorithm is presented that splits the calculation into photon and electron mediated energy transport, and performs the calculation of peak and valley doses in typical MRT treatment fields within a few minutes. Kernels are analytically calculated depending on the energy spectrum and material composition. In various homogeneous materials peak, valley doses and microbeam profiles are calculated and compared to Monte Carlo simulations. For a microbeam exposure of an anthropomorphic head phantom calculated dose values are compared to measurements and Monte Carlo calculations. Except for regions close to material interfaces calculated peak dose values match Monte Carlo results within 4% and valley dose values within 8% deviation. No significant differences are observed between profiles calculated by the kernel algorithm and Monte Carlo simulations. Measurements in the head phantom agree within 4% in the peak and within 10% in the valley region. The presented algorithm is attached to the treatment planning platform VIRTUOS. It was and is used for dose calculations in preclinical and pet-clinical trials at the biomedical beamline ID17 of the European synchrotron radiation facility in Grenoble, France.

Broken rice kernels and the kinetics of rice hydration and texture during cooking.

PubMed

Saleh, Mohammed; Meullenet, Jean-Francois

2013-05-01

During rice milling and processing, broken kernels are inevitably present, although to date it has been unclear as to how the presence of broken kernels affects rice hydration and cooked rice texture. Therefore, this work intended to study the effect of broken kernels in a rice sample on rice hydration and texture during cooking. Two medium-grain and two long-grain rice cultivars were harvested, dried and milled, and the broken kernels were separated from unbroken kernels. Broken rice kernels were subsequently combined with unbroken rice kernels forming treatments of 0, 40, 150, 350 or 1000 g kg(-1) broken kernels ratio. Rice samples were then cooked and the moisture content of the cooked rice, the moisture uptake rate, and rice hardness and stickiness were measured. As the amount of broken rice kernels increased, rice sample texture became increasingly softer (P < 0.05) but the unbroken kernels became significantly harder. Moisture content and moisture uptake rate were positively correlated, and cooked rice hardness was negatively correlated to the percentage of broken kernels in rice samples. Differences in the proportions of broken rice in a milled rice sample play a major role in determining the texture properties of cooked rice. Variations in the moisture migration kinetics between broken and unbroken kernels caused faster hydration of the cores of broken rice kernels, with greater starch leach-out during cooking affecting the texture of the cooked rice. The texture of cooked rice can be controlled, to some extent, by varying the proportion of broken kernels in milled rice. © 2012 Society of Chemical Industry.

Scale, Composition, and Technology

ERIC Educational Resources Information Center

Victor, Peter A.

2009-01-01

Scale (gross domestic product), composition (goods and services), and technology (impacts per unit of goods and services) in combination are the proximate determinants in an economy of the resources used, wastes generated, and land transformed. In this article, we examine relationships among these determinants to understand better the contribution…

Seasonal biochemical changes in composition of body wall tissues of sea cucumber Apostichopus japonicus

NASA Astrophysics Data System (ADS)

Gao, Fei; Xu, Qiang; Yang, Hongsheng

2011-03-01

Seasonal Variation in proximate, amino acid and fatty acid composition of the body wall of sea cucumber Apostichopus japonicus was evaluated. The proximate composition, except for ash content, changed significantly among seasons ( P<0.05). Alanine, glycine, glutamic acid and asparagic acid were the most abundant amino acids. Total amino acid and essential amino acid Contents both varied clearly with seasons ( P<0.05). 16:0 and 16:ln7 were the primary saturated fatty acid (SFA) and monounsaturated fatty acid (MUFA) respectively for all months. EPA (20:5n-3), AA (20:4n-6) and DHA (22:6n-3) were the major polyunsaturated fatty acids (PUFA). The proportions of SFA and PUFA yielded significant seasonal variations ( P<0.001), but MUFA did not changed significantly. The results indicated that the biochemical compositions of the body wall in A. japonicus were significantly influenced by seasons and that the body wall tissue is an excellent source of protein, MUFA and n-3 PUFA for humans.

Composition of forage and grain from second-generation insect-protected corn MON 89034 is equivalent to that of conventional corn (Zea mays L.).

PubMed

Drury, Suzanne M; Reynolds, Tracey L; Ridley, William P; Bogdanova, Natalia; Riordan, Susan; Nemeth, Margaret A; Sorbet, Roy; Trujillo, William A; Breeze, Matthew L

2008-06-25

Insect-protected corn hybrids containing Cry insecticidal proteins derived from Bacillus thuringiensis have protection from target pests and provide effective management of insect resistance. MON 89034 hybrids have been developed that produce both the Cry1A.105 and Cry2Ab2 proteins, which provide two independent modes of insecticidal action against the European corn borer ( Ostrinia nubilalis ) and other lepidopteran insect pests of corn. The composition of MON 89034 corn was compared to conventional corn by measuring proximates, fiber, and minerals in forage and by measuring proximates, fiber, amino acids, fatty acids, vitamins, minerals, antinutrients, and secondary metabolites in grain collected from 10 replicated field sites across the United States and Argentina during the 2004-2005 growing seasons. Analyses established that the forage and grain from MON 89034 are compositionally comparable to the control corn hybrid and conventional corn reference hybrids. These findings support the conclusion that MON 89034 is compositionally equivalent to conventional corn hybrids.

Organic-inorganic Interface in Nacre: Learning Lessons from Nature

NASA Astrophysics Data System (ADS)

Rahbar, Nima; Askarinejad, Sina

Problem-solving strategies of naturally growing composites such as nacre give us a fantastic vision to design and fabricate tough, stiff while strong composites. To provide the outstanding mechanical functions, nature has evolved complex and effective functionally graded interfaces. Particularly in nacre, organic-inorganic interface in which the proteins behave stiffer and stronger in proximity of calcium carbonate minerals provide an impressive role in structural integrity and mechanical deformation of the natural composite. The well-known shear-lag theory was employed on a simplified two-dimensional unit-cell of the multilayered composite considering the interface properties. The closed-form solutions for the displacements in the elastic components as a function of constituent properties can be used to calculate the effective mechanical properties of composite such as elastic modulus, strength and work-to-failure. The results solve the important mysteries about nacre and emphasize on the role of organic-inorganic interface properties and mineral bridges. Our results show that the properties of proteins in proximity of mineral bridges are also significant. More studies need to be performed on the strategies to enhance the interface properties in manmade composites. NSF Career Award no. 1281264.

Nonlinear Deep Kernel Learning for Image Annotation.

PubMed

Jiu, Mingyuan; Sahbi, Hichem

2017-02-08

Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

Multineuron spike train analysis with R-convolution linear combination kernel.

PubMed

Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Study on Energy Productivity Ratio (EPR) at palm kernel oil processing factory: case study on PT-X at Sumatera Utara Plantation

NASA Astrophysics Data System (ADS)

Haryanto, B.; Bukit, R. Br; Situmeang, E. M.; Christina, E. P.; Pandiangan, F.

2018-02-01

The purpose of this study was to determine the performance, productivity and feasibility of the operation of palm kernel processing plant based on Energy Productivity Ratio (EPR). EPR is expressed as the ratio of output to input energy and by-product. Palm Kernel plan is process in palm kernel to become palm kernel oil. The procedure started from collecting data needed as energy input such as: palm kernel prices, energy demand and depreciation of the factory. The energy output and its by-product comprise the whole production price such as: palm kernel oil price and the remaining products such as shells and pulp price. Calculation the equality of energy of palm kernel oil is to analyze the value of Energy Productivity Ratio (EPR) bases on processing capacity per year. The investigation has been done in Kernel Oil Processing Plant PT-X at Sumatera Utara plantation. The value of EPR was 1.54 (EPR > 1), which indicated that the processing of palm kernel into palm kernel oil is feasible to be operated based on the energy productivity.

Phytochemical investigation and proximate analysis on the leaves of Cnidoscolus aconitifolius.

PubMed

Oyagbemi, Ademola A; Odetola, Adebimpe A; Azeez, Odunayo I

2011-03-01

The study was designed to carry out the phytochemical screening and the proximate analysis of Cnidoscolus aconitifolius leaves. The results obtained showed the presence of tannins, saponin, alkaloids, and flavonoids with the absence of glycosides. The proximate analysis and mineral composition of C. aconitifolius leaves showed high levels of crude protein, ash, and fiber, in that order, and low fat content with concomitant presence of minerals such as sodium, manganese, magnesium, potassium, calcium, iron, phosphate, and zinc. The leaves of C. aconitifolius have high nutrient potentials and could be used as nutraceuticals in complementary foods, especially in sub-Saharan Africa.

Proximate and polyphenolic characterization of cranberry pomace.

PubMed

White, Brittany L; Howard, Luke R; Prior, Ronald L

2010-04-14

The proximate composition and identification and quantification of polyphenolic compounds in dried cranberry pomace were determined. Proximate analysis was conducted based on AOAC methods for moisture, protein, fat, dietary fiber, and ash. Other carbohydrates were determined by the difference method. Polyphenolic compounds were identified and quantified by HPLC-ESI-MS. The composition of dried cranberry pomace was 4.5% moisture, 2.2% protein, 12.0% fat, 65.5% insoluble fiber, 5.7% soluble fiber, 8.4% other carbohydrates, 1.1% ash, and 0.6% total polyphenolics. It contained six anthocyanins (111.5 mg/100 g of DW) including derivatives of cyanidin and peonidin. Thirteen flavonols were identified (358.4 mg/100 g of DW), and the aglycones myricetin (55.6 mg/100 g of DW) and quercetin (146.2 mg/100 g of DW) were the most prominent. Procyanidins with degrees of polymerization (DP) of 1-6 were identified (167.3 mg/100 g of DW), the most abundant being an A-type of DP2 (82.6 mg/100 g of DW).

Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

PubMed Central

2013-01-01

Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

Relative effects of climatic and local factors on fire occurrence in boreal forest landscapes of northeastern China.

PubMed

Wu, Zhiwei; He, Hong S; Yang, Jian; Liu, Zhihua; Liang, Yu

2014-09-15

Fire significantly affects species composition, structure, and ecosystem processes in boreal forests. Our study objective was to identify the relative effects of climate, vegetation, topography, and human activity on fire occurrence in Chinese boreal forest landscapes. We used historical fire ignition for 1966-2005 and the statistical method of Kernel Density Estimation to derive fire-occurrence density (number of fires/km(2)). The Random Forest models were used to quantify the relative effects of climate, vegetation, topography, and human activity on fire-occurrence density. Our results showed that fire-occurrence density tended to be spatially clustered. Human-caused fire occurrence was highly clustered at the southern part of the region, where human population density is high (comprising about 75% of the area's population). In the north-central areas where elevations are the highest in the region and less densely populated, lightning-caused fires were clustered. Climate factors (e.g., fine fuel and duff moisture content) were important at both regional and landscape scales. Human activity factors (e.g., distance to nearest settlement and road) were secondary to climate as the primary fire occurrence factors. Predictions of fire regimes often assume a strong linkage between climate and fire but usually with less emphasis placed on the effects of local factors such as human activity. We therefore suggest that accurate forecasting of fire regime should include human influences such as those measured by forest proximity to roads and human settlements. Copyright © 2014 Elsevier B.V. All rights reserved.

7 CFR 981.9 - Kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels, including...

An SVM model with hybrid kernels for hydrological time series

NASA Astrophysics Data System (ADS)

Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

2017-12-01

Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

Nutritional composition of the seeds of wild melon (Citrullus ecirrhosus).

PubMed

Umar, K J; Hassan, L G; Usman, H; Wasagu, R S U

2013-06-01

The proximate, minerals and amino acids contents of wild melon (Citrullus ecirrhosus) seeds were determined. The results for proximate analysis (% DW) showed a composition of 3.73 +/- 0.25 moisture, 2.12 +/- 0.08 ash 26.36 +/- 0.10 crude protein, 50.67 +/- 10.76 crude lipid, 2.17 +/- 0.29 crude fibre, 18.69 +/- 0.82 available carbohydrate and energy value of 601.7 +/- 8.75 kcal/100 g. The seeds amino acids profile revealed that for adults but leucine, lysine and threonine are below the requirement value for children. The overall result implies that seed of the wild melon possessed the potential to be used as a source of nutrition.

ANOTHER LOOK AT THE FAST ITERATIVE SHRINKAGE/THRESHOLDING ALGORITHM (FISTA)*

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2017-01-01

This paper provides a new way of developing the “Fast Iterative Shrinkage/Thresholding Algorithm (FISTA)” [3] that is widely used for minimizing composite convex functions with a nonsmooth term such as the ℓ1 regularizer. In particular, this paper shows that FISTA corresponds to an optimized approach to accelerating the proximal gradient method with respect to a worst-case bound of the cost function. This paper then proposes a new algorithm that is derived by instead optimizing the step coefficients of the proximal gradient method with respect to a worst-case bound of the composite gradient mapping. The proof is based on the worst-case analysis called Performance Estimation Problem in [11]. PMID:29805242

Investigation of redshift- and duration-dependent clustering of gamma-ray bursts

DOE PAGES

Ukwatta, T. N.; Woźniak, P. R.

2015-11-05

Gamma-ray bursts (GRBs) are detectable out to very large distances and as such are potentially powerful cosmological probes. Historically, the angular distribution of GRBs provided important information about their origin and physical properties. As a general population, GRBs are distributed isotropically across the sky. However, there are published reports that once binned by duration or redshift, GRBs display significant clustering. We have studied the redshift- and duration-dependent clustering of GRBs using proximity measures and kernel density estimation. Utilizing bursts detected by Burst and Transient Source Experiment, Fermi/gamma-ray burst monitor, and Swift/Burst Alert Telescope, we found marginal evidence for clustering inmore » very short duration GRBs lasting less than 100 ms. As a result, our analysis provides little evidence for significant redshift-dependent clustering of GRBs.« less

Approximate kernel competitive learning.

PubMed

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparative study on proximate, functional, mineral, and antinutrient composition of fermented, defatted, and protein isolate of Parkia biglobosa seed.

PubMed

Ogunyinka, Bolajoko I; Oyinloye, Babatunji E; Osunsanmi, Foluso O; Kappo, Abidemi P; Opoku, Andrew R

2017-01-01

The use of plant-derived foods in the prevention, treatment, and management of metabolic diseases especially diabetes has gained prominence; this has been associated with their physicochemical properties. This study was conducted to compare the proximate, functional, mineral, and antinutrient composition of the fermented seeds, the defatted seeds, and the protein isolate from Parkia biglobosa seeds. The results showed that the fermented, defatted, and protein isolate varied in composition within the parameters studied. The proximate analysis revealed that the protein isolate had the highest ash (6.0%) and protein (59.4%) as well as the lowest fat (5.7%) and moisture (5.1%) content when compared to the fermented and defatted samples. In like manner, the functional properties of the protein isolate were relatively better than those of the fermented and defatted samples, with oil absorption capacity of 4.2% and emulsion capacity of 82%. The magnesium and zinc content of the protein isolate were significantly higher when compared with the fermented and defatted samples, while a negligible amount of antinutrient was present in all the samples, with the protein isolate having the lowest quantity. The overall data suggest that the protein isolate had better proximate, mineral, functional, and antinutrient properties when compared to the fermented and defatted samples. Therefore, the synergistic effect of all these components present in the protein isolate from P. biglobosa seed in association with its low carbohydrate and high protein/ash contents could play a vital role in the management of diabetes and its associated complications.

Multiple kernels learning-based biological entity relationship extraction method.

PubMed

Dongliang, Xu; Jingchang, Pan; Bailing, Wang

2017-09-20

Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the most authoritative textual database in the field of biomedicine, and follow an exponential growth over time. This frantic expansion of the biomedical literature can often be difficult to absorb or manually analyze. Thus efficient and automated search engines are necessary to efficiently explore the biomedical literature using text mining techniques. The P, R, and F value of tag graph method in Aimed corpus are 50.82, 69.76, and 58.61%, respectively. The P, R, and F value of tag graph kernel method in other four evaluation corpuses are 2-5% higher than that of all-paths graph kernel. And The P, R and F value of feature kernel and tag graph kernel fuse methods is 53.43, 71.62 and 61.30%, respectively. The P, R and F value of feature kernel and tag graph kernel fuse methods is 55.47, 70.29 and 60.37%, respectively. It indicated that the performance of the two kinds of kernel fusion methods is better than that of simple kernel. In comparison with the all-paths graph kernel method, the tag graph kernel method is superior in terms of overall performance. Experiments show that the performance of the multi-kernels method is better than that of the three separate single-kernel method and the dual-mutually fused kernel method used hereof in five corpus sets.

Clinical assessment of class II resin-based composites versus preformed metal crowns performed on primary molars in patients at high risk of caries.

PubMed

Alyahya, A; Khanum, A; Qudeimat, M

2018-02-01

To compare class II resin composite with preformed metal crowns (PMC) in the treatment of proximal dentinal caries in high caries-risk patients. The charts (270) of paediatric patients with proximal caries of their primary molars were reviewed. Success or failure of a procedure was assessed using the dental notes. Survival analysis was used to calculate the mean survival time (MST) for both procedures. The influence of variables on the mean survival time was investigated. A total of 593 class II resin composites and 243 PMCs were placed in patients ranging between 4-13 years of age. The failure percentage of class II resin composites was 22.6% with the majority having been due to recurrent caries, while the failure percentage of PMCs was 15.2% with the majority due to loss of the crown. There was no significant difference between the MST of class II resin composites and PMCs, 41.3 and 45.6 months respectively (p value = 0.06). In class II resin composites, mesial restorations were associated with lower MST compared to distal restorations (p-value < 0.001). The MST of resin composites and PMCs were comparable when performed on high caries-risk patients.

7 CFR 51.2295 - Half kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...

7 CFR 810.206 - Grades and grade requirements for barley.

Code of Federal Regulations, 2010 CFR

2010-01-01

... weight per bushel (pounds) Sound barley (percent) Maximum Limits of— Damaged kernels 1 (percent) Heat damaged kernels (percent) Foreign material (percent) Broken kernels (percent) Thin barley (percent) U.S... or otherwise of distinctly low quality. 1 Includes heat-damaged kernels. Injured-by-frost kernels and...

7 CFR 51.1449 - Damage.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) Kernel which is “dark amber” or darker color; (e) Kernel having more than one dark kernel spot, or one dark kernel spot more than one-eighth inch in greatest dimension; (f) Shriveling when the surface of the kernel is very conspicuously wrinkled; (g) Internal flesh discoloration of a medium shade of gray...

7 CFR 51.1449 - Damage.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) Kernel which is “dark amber” or darker color; (e) Kernel having more than one dark kernel spot, or one dark kernel spot more than one-eighth inch in greatest dimension; (f) Shriveling when the surface of the kernel is very conspicuously wrinkled; (g) Internal flesh discoloration of a medium shade of gray...

7 CFR 51.2125 - Split or broken kernels.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Split or broken kernels. 51.2125 Section 51.2125 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards... kernels. Split or broken kernels means seven-eighths or less of complete whole kernels but which will not...

7 CFR 51.2296 - Three-fourths half kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...

The Classification of Diabetes Mellitus Using Kernel k-means

NASA Astrophysics Data System (ADS)

Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

2018-01-01

Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

UNICOS Kernel Internals Application Development

NASA Technical Reports Server (NTRS)

Caredo, Nicholas; Craw, James M. (Technical Monitor)

1995-01-01

Having an understanding of UNICOS Kernel Internals is valuable information. However, having the knowledge is only half the value. The second half comes with knowing how to use this information and apply it to the development of tools. The kernel contains vast amounts of useful information that can be utilized. This paper discusses the intricacies of developing utilities that utilize kernel information. In addition, algorithms, logic, and code will be discussed for accessing kernel information. Code segments will be provided that demonstrate how to locate and read kernel structures. Types of applications that can utilize kernel information will also be discussed.

Detection of maize kernels breakage rate based on K-means clustering

NASA Astrophysics Data System (ADS)

Yang, Liang; Wang, Zhuo; Gao, Lei; Bai, Xiaoping

2017-04-01

In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means clustering algorithm. First, the collected RGB images are converted into Lab images, then the original images clarity evaluation are evaluated by the energy function of Sobel 8 gradient. Finally, the detection of maize kernels breakage using different pixel acquisition equipments and different shooting angles. In this paper, the broken maize kernels are identified by the color difference between integrity kernels and broken kernels. The original images clarity evaluation and different shooting angles are taken to verify that the clarity and shooting angles of the images have a direct influence on the feature extraction. The results show that K-means clustering algorithm can distinguish the broken maize kernels effectively.

Modeling adaptive kernels from probabilistic phylogenetic trees.

PubMed

Nicotra, Luca; Micheli, Alessio

2009-01-01

Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species. We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel. The new kernels are used in the context of support vector machine learning. The kernels adaptivity is obtained through the estimation of the parameters of a tree structured model of evolution using as observed data phylogenetic profiles encoding the presence or absence of specific genes in a set of fully sequenced genomes. We report results obtained in the prediction of the functional class of the proteins of the budding yeast Saccharomyces cerevisae which favorably compare to a standard vector based kernel and to a non-adaptive tree kernel function. A further comparative analysis is performed in order to assess the impact of the different components of the proposed approach. We show that the key features of the proposed kernels are the adaptivity to the input domain and the ability to deal with structured data interpreted through a graphical model representation.

Aflatoxin and nutrient contents of peanut collected from local market and their processed foods

NASA Astrophysics Data System (ADS)

Ginting, E.; Rahmianna, A. A.; Yusnawan, E.

2018-01-01

Peanut is succeptable to aflatoxin contamination and the sources of peanut as well as processing methods considerably affect aflatoxin content of the products. Therefore, the study on aflatoxin and nutrient contents of peanut collected from local market and their processed foods were performed. Good kernels of peanut were prepared into fried peanut, pressed-fried peanut, peanut sauce, peanut press cake, fermented peanut press cake (tempe) and fried tempe, while blended kernels (good and poor kernels) were processed into peanut sauce and tempe and poor kernels were only processed into tempe. The results showed that good and blended kernels which had high number of sound/intact kernels (82,46% and 62,09%), contained 9.8-9.9 ppb of aflatoxin B1, while slightly higher level was seen in poor kernels (12.1 ppb). However, the moisture, ash, protein, and fat contents of the kernels were similar as well as the products. Peanut tempe and fried tempe showed the highest increase in protein content, while decreased fat contents were seen in all products. The increase in aflatoxin B1 of peanut tempe prepared from poor kernels > blended kernels > good kernels. However, it averagely decreased by 61.2% after deep-fried. Excluding peanut tempe and fried tempe, aflatoxin B1 levels in all products derived from good kernels were below the permitted level (15 ppb). This suggests that sorting peanut kernels as ingredients and followed by heat processing would decrease the aflatoxin content in the products.

Partial Deconvolution with Inaccurate Blur Kernel.

PubMed

Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

2017-10-17

Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.

In Vitro Continuous Fermentation Model (PolyFermS) of the Swine Proximal Colon for Simultaneous Testing on the Same Gut Microbiota

PubMed Central

Tanner, Sabine A.; Zihler Berner, Annina; Rigozzi, Eugenia; Grattepanche, Franck; Chassard, Christophe; Lacroix, Christophe

2014-01-01

In vitro gut modeling provides a useful platform for a fast and reproducible assessment of treatment-related changes. Currently, pig intestinal fermentation models are mainly batch models with important inherent limitations. In this study we developed a novel in vitro continuous fermentation model, mimicking the porcine proximal colon, which we validated during 54 days of fermentation. This model, based on our recent PolyFermS design, allows comparing different treatment effects on the same microbiota. It is composed of a first-stage inoculum reactor seeded with immobilized fecal swine microbiota and used to constantly inoculate (10% v/v) five second-stage reactors, with all reactors fed with fresh nutritive chyme medium and set to mimic the swine proximal colon. Reactor effluents were analyzed for metabolite concentrations and bacterial composition by HPLC and quantitative PCR, and microbial diversity was assessed by 454 pyrosequencing. The novel PolyFermS featured stable microbial composition, diversity and metabolite production, consistent with bacterial activity reported for swine proximal colon in vivo. The constant inoculation provided by the inoculum reactor generated reproducible microbial ecosystems in all second-stage reactors, allowing the simultaneous investigation and direct comparison of different treatments on the same porcine gut microbiota. Our data demonstrate the unique features of this novel PolyFermS design for the swine proximal colon. The model provides a tool for efficient, reproducible and cost-effective screening of environmental factors, such as dietary additives, on pig colonic fermentation. PMID:24709947

In vitro continuous fermentation model (PolyFermS) of the swine proximal colon for simultaneous testing on the same gut microbiota.

PubMed

Tanner, Sabine A; Zihler Berner, Annina; Rigozzi, Eugenia; Grattepanche, Franck; Chassard, Christophe; Lacroix, Christophe

2014-01-01

In vitro gut modeling provides a useful platform for a fast and reproducible assessment of treatment-related changes. Currently, pig intestinal fermentation models are mainly batch models with important inherent limitations. In this study we developed a novel in vitro continuous fermentation model, mimicking the porcine proximal colon, which we validated during 54 days of fermentation. This model, based on our recent PolyFermS design, allows comparing different treatment effects on the same microbiota. It is composed of a first-stage inoculum reactor seeded with immobilized fecal swine microbiota and used to constantly inoculate (10% v/v) five second-stage reactors, with all reactors fed with fresh nutritive chyme medium and set to mimic the swine proximal colon. Reactor effluents were analyzed for metabolite concentrations and bacterial composition by HPLC and quantitative PCR, and microbial diversity was assessed by 454 pyrosequencing. The novel PolyFermS featured stable microbial composition, diversity and metabolite production, consistent with bacterial activity reported for swine proximal colon in vivo. The constant inoculation provided by the inoculum reactor generated reproducible microbial ecosystems in all second-stage reactors, allowing the simultaneous investigation and direct comparison of different treatments on the same porcine gut microbiota. Our data demonstrate the unique features of this novel PolyFermS design for the swine proximal colon. The model provides a tool for efficient, reproducible and cost-effective screening of environmental factors, such as dietary additives, on pig colonic fermentation.

Proximate nutritional composition of CELSS crops grown at different CO2 partial pressures

NASA Technical Reports Server (NTRS)

Wheeler, R. M.; Mackowiak, C. L.; Sager, J. C.; Knott, W. M.; Berry, W. L.

1994-01-01

Two Controlled Ecological Life Support System (CELSS) candidate crops, soybean (Glycine max) and potato (Solanum tuberosum), were grown hydroponically in controlled environments maintained at carbon dioxide (CO2) partial pressures ranging from 0.05 to 1.00 kPa (500 to 10,000 ppm at 101 kPa atmospheric pressure). Plants were harvested at maturity (90 days for soybean and 105 days for potato) and all tissues analyzed for proximate nutritional composition (i.e. protein, fat, carbohydrate, crude fiber, and ash content). Soybean seed ash and crude fiber were higher and carbohydrate was lower than values reported for field-grown seed. Potato tubers showed little difference from field-grown tubers. Crude fiber of soybean stems and leaves increased with increased CO2, as did soybean leaf protein (total nitrogen). Potato leaf and stem (combined) protein levels also increased with increased CO2, while leaf and stem carbohydrates decreased. Values for leaf and stem protein and ash were higher than values generally reported for field-grown plants for both species. Results suggest that CO2 partial pressure should have little influence on proximate composition of potato tubers or soybean seed, but that high ash and protein levels might be expected from leaves and stems of crops grown in controlled environments of a CELSS.

Effect of storage temperatures and humidity on proximate composition, peroxide value and iodine value of raw cashew nuts.

PubMed

Ajith, Sabna; Pramod, S; Prabha Kumari, C; Potty, V P

2015-07-01

The equilibrium moisture content (EMC) of raw cashew nuts (RCN) were determined using the standard static gravimetric method at 30 °C, 40 °C and 50 °C for relative humidity (RH) ranging from 43 to 90 %. The proximate composition analysis, peroxide value and iodine value of RCN were assessed at this equilibrium stage. The RCN kept under the humidity of 86 and 90 percentage at all studied temperatures developed mold growth within 24-48 h of time. The better storage condition assessed for raw cashew nut is 67 % of RH at 30 °C and the values obtained for EMC, proximate composition analysis, peroxide value and iodine value are within the same range as observed with harvested RCN. Highlights • Raw cashew nut storage condition identified • It was analysed with different temperature (30 (°)C, 40 (°)C and 50 (°)C) and relative humidity (43 %-90 %) • Better storage condition for raw cashew nut is in 67 % of RH at 30 (°)C • In this condition the EMC was 8.11 % as within the range of moisture in harvested RCN.

Minimization of diauxic growth lag-phase for high-efficiency biogas production.

PubMed

Kim, Min Jee; Kim, Sang Hun

2017-02-01

The objective of this study was to develop a minimization method of a diauxic growth lag-phase for the biogas production from agricultural by-products (ABPs). Specifically, the effects of proximate composition on the biogas production and degradation rates of the ABPs were investigated, and a new method based on proximate composition combinations was developed to minimize the diauxic growth lag-phase. Experiments were performed using biogas potential tests at a substrate loading of 2.5 g VS/L and feed to microorganism ratio (F/M) of 0.5 under the mesophilic condition. The ABPs were classified based on proximate composition (carbohydrate, protein, and fat etc.). The biogas production patterns, lag phase, and times taken for 90% biogas production (T90) were used for the evaluation of the biogas production with biochemical methane potential (BMP) test. The high- or medium-carbohydrate and low-fat ABPs (cheese whey, cabbage, and skim milk) showed a single step digestion process and low-carbohydrate and high-fat ABPs (bean curd and perilla seed) showed a two-step digestion process. The mixture of high-fat ABPs and high-carbohydrate ABPs reduced the lag-phase and increased the biogas yield more than that from single ABP by 35-46%. Copyright © 2016 Elsevier Ltd. All rights reserved.

An initial non-targeted analysis of the peanut seed metabolome

USDA-ARS?s Scientific Manuscript database

There are likely a large number of compounds that constitute the peanut seed metabolome that have yet to be elucidated. Although the proximate composition and nutrients such as vitamins and minerals are well known, the composition of many other small molecule metabolites present have not been syste...

Impact of power index, hydroureteronephrosis, stone size, and composition on the efficacy of in situ boosted ESWL for primary proximal ureteral calculi.

PubMed

Singh, I; Gupta, N P; Hemal, A K; Dogra, P N; Ansari, M S; Seth, A; Aron, M

2001-07-01

The efficacy, safety, feasibility, and outcome of in situ treatment applied to select proximal ureteral calculi was assessed and analyzed with a view to avoiding auxiliary interventions and providing high clearance rates in the shortest possible time. We studied the impact of several clinically important variables, including power index, degree of hydroureteronephrosis (HDUN), stone size, and composition on the efficacy of sequential in situ boosted extracorporeal shock wave lithotripsy (ESWL) in a select group. The power index requirement for the in situ boosted protocol and the impact of the stone size/composition, degree of HDUN, and clearance rates were also analyzed. An in situ (no instrumentation) boosted protocol was applied to 130 primary unimpacted proximal ureteral calculi with no prior intervention. A typical session with the Siemens Lithostar Plus comprised 3000 shock waves, in installments of 500, deployed at a power setting of 1 to 4 kV with a gradual stepwise escalation. Sequential boosted additional sessions of ESWL were administered on days 2, 7, and 14, tailored to the degree of fragmentation, clearance status, and amount of residual stone bulk. Several parameters (shock waves, kilovolts used, fluoroscopy time, number of sessions, stone size, composition, fragmentation, clearance, and HDUN) were recorded and the results analyzed statistically. The results were excellent in 83.8%, with a mean duration to complete clearance of 11.3 days. In situ ESWL failed in 7.69%, and the auxiliary intervention rate was 10.7%. Pre-ESWL HDUN was present in 78.3%, the mean power index was 184.6/session/case, and the average stone burden was 8.9 mm(2). Calcium oxalate monohydrate was the most common stone (56%). Renal colic was the most common side effect observed. The power index, fragmentation at the first session, and stone size were found to be the most favorable significant variables affecting stone clearance. The degree of HDUN, number of sessions, and stone composition did not significantly impact the clearance rates. In situ boosted ESWL should be the first-line therapeutic modality in select unimpacted primary proximal ureteral stones.

Identification of subsurface structures using electromagnetic data and shape priors

NASA Astrophysics Data System (ADS)

Tveit, Svenn; Bakr, Shaaban A.; Lien, Martha; Mannseth, Trond

2015-03-01

We consider the inverse problem of identifying large-scale subsurface structures using the controlled source electromagnetic method. To identify structures in the subsurface where the contrast in electric conductivity can be small, regularization is needed to bias the solution towards preserving structural information. We propose to combine two approaches for regularization of the inverse problem. In the first approach we utilize a model-based, reduced, composite representation of the electric conductivity that is highly flexible, even for a moderate number of degrees of freedom. With a low number of parameters, the inverse problem is efficiently solved using a standard, second-order gradient-based optimization algorithm. Further regularization is obtained using structural prior information, available, e.g., from interpreted seismic data. The reduced conductivity representation is suitable for incorporation of structural prior information. Such prior information cannot, however, be accurately modeled with a gaussian distribution. To alleviate this, we incorporate the structural information using shape priors. The shape prior technique requires the choice of kernel function, which is application dependent. We argue for using the conditionally positive definite kernel which is shown to have computational advantages over the commonly applied gaussian kernel for our problem. Numerical experiments on various test cases show that the methodology is able to identify fairly complex subsurface electric conductivity distributions while preserving structural prior information during the inversion.

Documentation of the appearance of a caviar-type deposit in Oven 1 following a large scale experiment for heating oil with Upper Silesian coal (in German)

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

Rank

1942-03-26

When the oven was disassembled after the test, small kernels of porous material were found in both the upper and lower portion of the oven to a depth of about 2 m. The kernels were of various sizes up to 4 mm. From 1,300 metric ..cap alpha..ons of dry coal, there were 330 kg or the residue of 0.025% of the coal input. These kernels brought to mind deposits of spheroidal material termed ''caviar'', since they had rounded tops. However, they were irregularly long. After multiaxis micrography, no growth rings were found as in Leuna's lignite caviar. So, it wasmore » a question of small particles consisting almost totally of ash. The majority of the composition was Al, Fe, Na, silicic acid, S and Cl. The sulfur was found to be in sulfide form and Cl in a volatile form. The remains did not turn to caviar form since the CaO content was slight. The Al, Fe, Na, silicic acid, S and Cl were concentrated in comparison to coal ash and originate apparently from the catalysts (FeSO/sub 4/, Bayermasse, and Na/sub 2/S). It was notable that the Cl content was so high. 2 graphs, 1 table« less

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2012 CFR

2012-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2011 CFR

2011-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2013 CFR

2013-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2014 CFR

2014-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 51.1441 - Half-kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume missing...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

7 CFR 51.1450 - Serious damage.

Code of Federal Regulations, 2010 CFR

2010-01-01

...; (c) Decay affecting any portion of the kernel; (d) Insects, web, or frass or any distinct evidence of insect feeding on the kernel; (e) Internal discoloration which is dark gray, dark brown, or black and...) Dark kernel spots when more than three are on the kernel, or when any dark kernel spot or the aggregate...

7 CFR 51.1450 - Serious damage.

Code of Federal Regulations, 2011 CFR

2011-01-01

...; (c) Decay affecting any portion of the kernel; (d) Insects, web, or frass or any distinct evidence of insect feeding on the kernel; (e) Internal discoloration which is dark gray, dark brown, or black and...) Dark kernel spots when more than three are on the kernel, or when any dark kernel spot or the aggregate...

7 CFR 51.1450 - Serious damage.

Code of Federal Regulations, 2012 CFR

2012-01-01

...; (c) Decay affecting any portion of the kernel; (d) Insects, web, or frass or any distinct evidence of insect feeding on the kernel; (e) Internal discoloration which is dark gray, dark brown, or black and...) Dark kernel spots when more than three are on the kernel, or when any dark kernel spot or the aggregate...

Wavelet SVM in Reproducing Kernel Hilbert Space for hyperspectral remote sensing image classification

NASA Astrophysics Data System (ADS)

Du, Peijun; Tan, Kun; Xing, Xiaoshi

2010-12-01

Combining Support Vector Machine (SVM) with wavelet analysis, we constructed wavelet SVM (WSVM) classifier based on wavelet kernel functions in Reproducing Kernel Hilbert Space (RKHS). In conventional kernel theory, SVM is faced with the bottleneck of kernel parameter selection which further results in time-consuming and low classification accuracy. The wavelet kernel in RKHS is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. Implications on semiparametric estimation are proposed in this paper. Airborne Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing image with 64 bands and Reflective Optics System Imaging Spectrometer (ROSIS) data with 115 bands were used to experiment the performance and accuracy of the proposed WSVM classifier. The experimental results indicate that the WSVM classifier can obtain the highest accuracy when using the Coiflet Kernel function in wavelet transform. In contrast with some traditional classifiers, including Spectral Angle Mapping (SAM) and Minimum Distance Classification (MDC), and SVM classifier using Radial Basis Function kernel, the proposed wavelet SVM classifier using the wavelet kernel function in Reproducing Kernel Hilbert Space is capable of improving classification accuracy obviously.

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

PubMed

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Hadamard Kernel SVM with applications for breast cancer outcome predictions.

PubMed

Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

2017-12-21

Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

Ceramic superconductor/metal composite materials employing the superconducting proximity effect

DOEpatents

Holcomb, Matthew J.

2002-01-01

Superconducting composite materials having particles of superconducting material disposed in a metal matrix material with a high electron-boson coupling coefficient (.lambda.). The superconducting particles can comprise any type of superconductor including Laves phase materials, Chevrel phase materials, A15 compounds, and perovskite cuprate ceramics. The particles preferably have dimensions of about 10-500 nanometers. The particles preferably have dimensions larger than the superconducting coherence length of the superconducting material. The metal matrix material has a .lambda. greater than 0.2, preferably the .lambda. is much higher than 0.2. The metal matrix material is a good proximity superconductor due to its high .lambda.. When cooled, the superconductor particles cause the metal matrix material to become superconducting due to the proximity effect. In cases where the particles and the metal matrix material are chemically incompatible (i.e., reactive in a way that destroys superconductivity), the particles are provided with a thin protective metal coating. The coating is chemically compatible with the particles and metal matrix material. High Temperature Superconducting (HTS) cuprate ceramic particles are reactive and therefore require a coating of a noble metal resistant to oxidation (e.g., silver, gold). The proximity effect extends through the metal coating. With certain superconductors, non-noble metals can be used for the coating.

LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

PubMed

Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

2018-05-07

Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

The Geographic Information System applied to study schistosomiasis in Pernambuco

PubMed Central

Barbosa, Verônica Santos; Loyo, Rodrigo Moraes; Guimarães, Ricardo José de Paula Souza e; Barbosa, Constança Simões

2017-01-01

ABSTRACT OBJECTIVE Diagnose risk environments for schistosomiasis in coastal localities of Pernambuco using geoprocessing techniques. METHODS A coproscopic and malacological survey were carried out in the Forte Orange and Serrambi areas. Environmental variables (temperature, salinity, pH, total dissolved solids and water fecal coliform dosage) were collected from Biomphalaria breeding sites or foci. The spatial analysis was performed using ArcGis 10.1 software, applying the kernel estimator, elevation map, and distance map. RESULTS In Forte Orange, 4.3% of the population had S. mansoni and were found two B. glabrata and 26 B. straminea breeding sites. The breeding sites had temperatures of 25ºC to 41ºC, pH of 6.9 to 11.1, total dissolved solids between 148 and 661, and salinity of 1,000 d. In Serrambi, 4.4% of the population had S. mansoni and were found seven B. straminea and seven B. glabrata breeding sites. Breeding sites had temperatures of 24ºC to 36ºC, pH of 7.1 to 9.8, total dissolved solids between 116 and 855, and salinity of 1,000 d. The kernel estimator shows the clusters of positive patients and foci of Biomphalaria, and the digital elevation map indicates areas of rainwater concentration. The distance map shows the proximity of the snail foci with schools and health facilities. CONCLUSIONS Geoprocessing techniques prove to be a competent tool for locating and scaling the risk areas for schistosomiasis, and can subsidize the health services control actions. PMID:29166439

Activated carbons from waste of oil-palm kernel shells, sawdust and tannery leather scraps and application to chromium(VI), phenol, and methylene blue dye adsorption.

PubMed

Montoya-Suarez, Sergio; Colpas-Castillo, Fredy; Meza-Fuentes, Edgardo; Rodríguez-Ruiz, Johana; Fernandez-Maestre, Roberto

2016-01-01

Phenol, chromium, and dyes are continuously dumped into water bodies; the adsorption of these contaminants on activated carbon is a low-cost alternative for water remediation. We synthesized activated carbons from industrial waste of palm oil seed husks (kernel shells), sawdust, and tannery leather scraps. These materials were heated for 24 h at 600, 700 or 800°C, activated at 900°C with CO2 and characterized by proximate analysis and measurement of specific surface area (Brunauer-Emmett-Teller (BET) and Langmuir), and microporosity (t-plot). Isotherms showed micropores and mesopores in activated carbons. Palm seed activated carbon showed the highest fixed carbon content (96%), and Langmuir specific surface areas up to 1,268 m2/g, higher than those from sawdust (581 m2/g) and leather scraps (400 m2/g). The carbons were applied to adsorption of Cr(VI), phenol, and methylene blue dye from aqueous solutions. Phenol adsorption on activated carbons was 78-82 mg/g; on palm seed activated carbons, Cr(VI) adsorption at pH 7 was 0.35-0.37 mg/g, and methylene blue adsorption was 40-110 mg/g, higher than those from sawdust and leather scraps. Activated carbons from palm seed are promising materials to remove contaminants from the environment and represent an alternative application for vegetal wastes instead of dumping into landfills.

Multi-kernel aggregation of local and global features in long-wave infrared for detection of SWAT teams in challenging environments

NASA Astrophysics Data System (ADS)

Arya, Ankit S.; Anderson, Derek T.; Bethel, Cindy L.; Carruth, Daniel

2013-05-01

A vision system was designed for people detection to provide support to SWAT team members operating in challenging environments such as low-to-no light, smoke, etc. When the vision system is mounted on a mobile robot platform: it will enable the robot to function as an effective member of the SWAT team; to provide surveillance information; to make first contact with suspects; and provide safe entry for team members. The vision task is challenging because SWAT team members are typically concealed, carry various equipment such as shields, and perform tactical and stealthy maneuvers. Occlusion is a particular challenge because team members operate in close proximity to one another. An uncooled electro-opticaljlong wav e infrared (EO/ LWIR) camera, 7.5 to 13.5 m, was used. A unique thermal dataset was collected of SWAT team members from multiple teams performing tactical maneuvers during monthly training exercises. Our approach consisted of two stages: an object detector trained on people to find candidate windows, and a secondary feature extraction, multi-kernel (MK) aggregation and classification step to distinguish between SWAT team members and civilians. Two types of thermal features, local and global, are presented based on ma ximally stable extremal region (MSER) blob detection. Support vector machine (SVM) classification results of approximately [70, 93]% for SWAT team member detection are reported based on the exploration of different combinations of visual information in terms of training data.

Spatial analysis of environment and population at risk of natural gas fracking in the state of Pennsylvania, USA.

PubMed

Meng, Qingmin

2015-05-15

Hydraulic fracturing, also known as fracking, has been increasing exponentially across the United States, which holds the largest known shale gas reserves in the world. Studies have found that the high-volume horizontal hydraulic fracturing process (HVHFP) threatens water resources, harms air quality, changes landscapes, and damages ecosystems. However, there is minimal research focusing on the spatial study of environmental and human risks of HVHFP, which is necessary for state and federal governments to administer, regulate, and assess fracking. Integrating GIS and spatial kernel functions, we study the presently operating fracking wells across the state of Pennsylvania (PA), which is the main part of the current hottest Marcellus Shale in US. We geographically process the location data of hydraulic fracturing wells, 2010 census block data, urbanized region data, railway data, local road data, open water data, river data, and wetland data for the state of PA. From this we develop a distance based risk assessment in order to understand the environmental and urban risks. We generate the surface data of fracking well intensity and population intensity by integrating spatial dependence, semivariogram modeling, and a quadratic kernel function. The surface data of population risk generated by the division of fracking well intensity and population intensity provide a novel insight into the local and regional regulation of hydraulic fracturing activities in terms of environmental and health related risks due to the proximity of fracking wells. Copyright © 2015 Elsevier B.V. All rights reserved.

Locality Aware Concurrent Start for Stencil Applications

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

Shrestha, Sunil; Gao, Guang R.; Manzano Franco, Joseph B.

Stencil computations are at the heart of many physical simulations used in scientific codes. Thus, there exists a plethora of optimization efforts for this family of computations. Among these techniques, tiling techniques that allow concurrent start have proven to be very efficient in providing better performance for these critical kernels. Nevertheless, with many core designs being the norm, these optimization techniques might not be able to fully exploit locality (both spatial and temporal) on multiple levels of the memory hierarchy without compromising parallelism. It is no longer true that the machine can be seen as a homogeneous collection of nodesmore » with caches, main memory and an interconnect network. New architectural designs exhibit complex grouping of nodes, cores, threads, caches and memory connected by an ever evolving network-on-chip design. These new designs may benefit greatly from carefully crafted schedules and groupings that encourage parallel actors (i.e. threads, cores or nodes) to be aware of the computational history of other actors in close proximity. In this paper, we provide an efficient tiling technique that allows hierarchical concurrent start for memory hierarchy aware tile groups. Each execution schedule and tile shape exploit the available parallelism, load balance and locality present in the given applications. We demonstrate our technique on the Intel Xeon Phi architecture with selected and representative stencil kernels. We show improvement ranging from 5.58% to 31.17% over existing state-of-the-art techniques.« less

Robust sparse image reconstruction of radio interferometric observations with PURIFY

NASA Astrophysics Data System (ADS)

Pratley, Luke; McEwen, Jason D.; d'Avezac, Mayeul; Carrillo, Rafael E.; Onose, Alexandru; Wiaux, Yves

2018-01-01

Next-generation radio interferometers, such as the Square Kilometre Array, will revolutionize our understanding of the Universe through their unprecedented sensitivity and resolution. However, to realize these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions while providing a computational saving and an analytic form. Secondly, we apply PURIFY to real interferometric observations from the Very Large Array and the Australia Telescope Compact Array and find that images recovered by PURIFY are of higher quality than those recovered by CLEAN. Thirdly, we discuss how PURIFY reconstructions exhibit additional advantages over those recovered by CLEAN. The latest version of PURIFY, with developments presented in this work, is made publicly available.

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluating the Gradient of the Thin Wire Kernel

NASA Technical Reports Server (NTRS)

Wilton, Donald R.; Champagne, Nathan J.

2008-01-01

Recently, a formulation for evaluating the thin wire kernel was developed that employed a change of variable to smooth the kernel integrand, canceling the singularity in the integrand. Hence, the typical expansion of the wire kernel in a series for use in the potential integrals is avoided. The new expression for the kernel is exact and may be used directly to determine the gradient of the wire kernel, which consists of components that are parallel and radial to the wire axis.

Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

PubMed

Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

2014-01-01

The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

Proximate composition of poultry processing wastewater particulate matter from broiler slaughter plants.

PubMed

Kiepper, B H; Merka, W C; Fletcher, D L

2008-08-01

An experiment was conducted to compare the proximate composition of particulate matter recovered from poultry processing wastewater (PPW) generated by broiler slaughter plants. Poultry processing wastewater is the cumulative wastewater stream generated during the processing of poultry following primary and secondary physical screening (typically to 500 mum) that removes gross offal. Composite samples of PPW from 3 broiler slaughter plants (southeast United States) were collected over 8 consecutive weeks. All 3 broiler slaughter plants process young chickens with an average live weight of 2.0 kg. At each plant, a single 72-L composite sample was collected using an automatic sampler programmed to collect 1 L of wastewater every 20 min for 24 h during one normal processing day each week. Each composite sample was thoroughly mixed, and 60 L was passed through a series of sieves (2.0 mm, 1.0 mm, 500 mum, and 53 mum). The amount of particulate solids collected on the 2.0 mm, 1.0 mm, and 500 mum sieves was insignificant. The solids recovered from the 53-mum sieve were subjected to proximate analysis to determine percent moisture, fat, protein, ash, and fiber. The average percentages of fat, protein, ash, and fiber for all samples on a dry-weight basis were 55.3, 27.1, 6.1, and 4.1, respectively. Fat made up over half of the dry-weight matter recovered, representing PPW particulate matter between 500 and 53 mum. Despite the variation in number of birds processed daily, further processing operations, and number and type of wastewater screens utilized, there were no significance differences in percentage of fat and fiber between the slaughter plants. There were significant differences in percent protein and ash between the slaughter plants.

7 CFR 810.202 - Definition of other terms.

Code of Federal Regulations, 2014 CFR

2014-01-01

... barley kernels, other grains, and wild oats that are badly shrunken and distinctly discolored black or... kernels. Kernels and pieces of barley kernels that are distinctly indented, immature or shrunken in...

7 CFR 810.202 - Definition of other terms.

Code of Federal Regulations, 2013 CFR

2013-01-01

... barley kernels, other grains, and wild oats that are badly shrunken and distinctly discolored black or... kernels. Kernels and pieces of barley kernels that are distinctly indented, immature or shrunken in...

7 CFR 810.202 - Definition of other terms.

Code of Federal Regulations, 2012 CFR

2012-01-01

... barley kernels, other grains, and wild oats that are badly shrunken and distinctly discolored black or... kernels. Kernels and pieces of barley kernels that are distinctly indented, immature or shrunken in...

graphkernels: R and Python packages for graph comparison

PubMed Central

Ghisu, M Elisabetta; Llinares-López, Felipe; Borgwardt, Karsten

2018-01-01

Abstract Summary Measuring the similarity of graphs is a fundamental step in the analysis of graph-structured data, which is omnipresent in computational biology. Graph kernels have been proposed as a powerful and efficient approach to this problem of graph comparison. Here we provide graphkernels, the first R and Python graph kernel libraries including baseline kernels such as label histogram based kernels, classic graph kernels such as random walk based kernels, and the state-of-the-art Weisfeiler-Lehman graph kernel. The core of all graph kernels is implemented in C ++ for efficiency. Using the kernel matrices computed by the package, we can easily perform tasks such as classification, regression and clustering on graph-structured samples. Availability and implementation The R and Python packages including source code are available at https://CRAN.R-project.org/package=graphkernels and https://pypi.python.org/pypi/graphkernels. Contact mahito@nii.ac.jp or elisabetta.ghisu@bsse.ethz.ch Supplementary information Supplementary data are available online at Bioinformatics. PMID:29028902

Aflatoxin variability in pistachios.

PubMed Central

Mahoney, N E; Rodriguez, S B

1996-01-01

Pistachio fruit components, including hulls (mesocarps and epicarps), seed coats (testas), and kernels (seeds), all contribute to variable aflatoxin content in pistachios. Fresh pistachio kernels were individually inoculated with Aspergillus flavus and incubated 7 or 10 days. Hulled, shelled kernels were either left intact or wounded prior to inoculation. Wounded kernels, with or without the seed coat, were readily colonized by A. flavus and after 10 days of incubation contained 37 times more aflatoxin than similarly treated unwounded kernels. The aflatoxin levels in the individual wounded pistachios were highly variable. Neither fungal colonization nor aflatoxin was detected in intact kernels without seed coats. Intact kernels with seed coats had limited fungal colonization and low aflatoxin concentrations compared with their wounded counterparts. Despite substantial fungal colonization of wounded hulls, aflatoxin was not detected in hulls. Aflatoxin levels were significantly lower in wounded kernels with hulls than in kernels of hulled pistachios. Both the seed coat and a water-soluble extract of hulls suppressed aflatoxin production by A. flavus. PMID:8919781

graphkernels: R and Python packages for graph comparison.

PubMed

Sugiyama, Mahito; Ghisu, M Elisabetta; Llinares-López, Felipe; Borgwardt, Karsten

2018-02-01

Measuring the similarity of graphs is a fundamental step in the analysis of graph-structured data, which is omnipresent in computational biology. Graph kernels have been proposed as a powerful and efficient approach to this problem of graph comparison. Here we provide graphkernels, the first R and Python graph kernel libraries including baseline kernels such as label histogram based kernels, classic graph kernels such as random walk based kernels, and the state-of-the-art Weisfeiler-Lehman graph kernel. The core of all graph kernels is implemented in C ++ for efficiency. Using the kernel matrices computed by the package, we can easily perform tasks such as classification, regression and clustering on graph-structured samples. The R and Python packages including source code are available at https://CRAN.R-project.org/package=graphkernels and https://pypi.python.org/pypi/graphkernels. mahito@nii.ac.jp or elisabetta.ghisu@bsse.ethz.ch. Supplementary data are available online at Bioinformatics. © The Author(s) 2017. Published by Oxford University Press.

Investigation of various energy deposition kernel refinements for the convolution/superposition method

PubMed Central

Huang, Jessie Y.; Eklund, David; Childress, Nathan L.; Howell, Rebecca M.; Mirkovic, Dragan; Followill, David S.; Kry, Stephen F.

2013-01-01

Purpose: Several simplifications used in clinical implementations of the convolution/superposition (C/S) method, specifically, density scaling of water kernels for heterogeneous media and use of a single polyenergetic kernel, lead to dose calculation inaccuracies. Although these weaknesses of the C/S method are known, it is not well known which of these simplifications has the largest effect on dose calculation accuracy in clinical situations. The purpose of this study was to generate and characterize high-resolution, polyenergetic, and material-specific energy deposition kernels (EDKs), as well as to investigate the dosimetric impact of implementing spatially variant polyenergetic and material-specific kernels in a collapsed cone C/S algorithm. Methods: High-resolution, monoenergetic water EDKs and various material-specific EDKs were simulated using the EGSnrc Monte Carlo code. Polyenergetic kernels, reflecting the primary spectrum of a clinical 6 MV photon beam at different locations in a water phantom, were calculated for different depths, field sizes, and off-axis distances. To investigate the dosimetric impact of implementing spatially variant polyenergetic kernels, depth dose curves in water were calculated using two different implementations of the collapsed cone C/S method. The first method uses a single polyenergetic kernel, while the second method fully takes into account spectral changes in the convolution calculation. To investigate the dosimetric impact of implementing material-specific kernels, depth dose curves were calculated for a simplified titanium implant geometry using both a traditional C/S implementation that performs density scaling of water kernels and a novel implementation using material-specific kernels. Results: For our high-resolution kernels, we found good agreement with the Mackie et al. kernels, with some differences near the interaction site for low photon energies (<500 keV). For our spatially variant polyenergetic kernels, we found that depth was the most dominant factor affecting the pattern of energy deposition; however, the effects of field size and off-axis distance were not negligible. For the material-specific kernels, we found that as the density of the material increased, more energy was deposited laterally by charged particles, as opposed to in the forward direction. Thus, density scaling of water kernels becomes a worse approximation as the density and the effective atomic number of the material differ more from water. Implementation of spatially variant, polyenergetic kernels increased the percent depth dose value at 25 cm depth by 2.1%–5.8% depending on the field size, while implementation of titanium kernels gave 4.9% higher dose upstream of the metal cavity (i.e., higher backscatter dose) and 8.2% lower dose downstream of the cavity. Conclusions: Of the various kernel refinements investigated, inclusion of depth-dependent and metal-specific kernels into the C/S method has the greatest potential to improve dose calculation accuracy. Implementation of spatially variant polyenergetic kernels resulted in a harder depth dose curve and thus has the potential to affect beam modeling parameters obtained in the commissioning process. For metal implants, the C/S algorithms generally underestimate the dose upstream and overestimate the dose downstream of the implant. Implementation of a metal-specific kernel mitigated both of these errors. PMID:24320507

Characteristics of uranium carbonitride microparticles synthesized using different reaction conditions

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

Silva, Chinthaka M; Lindemer, Terrence; Voit, Stewart L

2014-11-01

Three sets of different experimental conditions by changing the cover gases during the sample preparation were tested to synthesize uranium carbonitride (UC1-xNx) microparticles. In the first two sets of experiments using (N2 to N2-4%H2 to Ar) and (Ar to N2 to Ar) environments, single phase UC1-xNx was synthesized. When reducing environments (Ar-4%H2 to N2-4%H2 to Ar-4%H2) were utilized, theoretical densities up to 97% of single phase UC1-xNx kernels were obtained. Physical and chemical characteristics such as density, phase purity, and chemical compositions of the synthesized UC1-xNx materials for the diferent experimental conditions used are provided. In-depth analysis of the microstruturesmore » of UC1-xNx has been carried out and is discussed with the objective of large batch fabrication of high density UC1-xNx kernels.« less

Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

PubMed

Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K

2015-05-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.

Depth of cure of proximal composite resin restorations using a new perforated metal matrix.

PubMed

Nguyen, Duke P; Motyka, Nancy C; Meyers, Erik J; Vandewalle, Kraig S

2018-01-01

The purpose of this study was to compare the depths of cure of a proximal box preparation filled in bulk with various approaches: filled with a bulk-fill or conventional composite; placed with a new perforated metal matrix, a traditional metal matrix, or a clear matrix; and polymerized with either occlusal-only or tri-sited light curing. After tri-sited curing, the use of the new perforated metal matrix band resulted in a depth of cure that was not significantly different from that achieved with the use of metal bands (removed during curing) or transparent matrix bands. Adequate polymerization was obtained at depths of more than 5.0 mm for the bulk-fill composite and more than 4.0 mm for the conventional composite when tri-sited light curing was used. Tri-sited light curing resulted in a significantly greater depth of cure than occlusal-only curing. The perforated metal band may be used as an alternative to the use of solid metal bands or transparent matrix bands to provide similar depths of cure for composite resins, with the possible benefits of malleability and the ability to leave the band in place during tri-sited light curing.

Single-screw Fixation of Adolescent Salter-II Proximal Humeral Fractures: Biomechanical Analysis of the "One Pass Door Lock" Technique.

PubMed

Miller, Mark Carl; Redman, Christopher N; Mistovich, R Justin; Muriuki, Muturi; Sangimino, Mark J

2017-09-01

Pin fixation of Salter-II proximal humeral fractures in adolescents approaching skeletal maturity has potential complications that can be avoided with single-screw fixation. However, the strength of screw fixation relative to parallel and diverging pin fixation is unknown. To compare the biomechanical fixation strength between these fixation modalities, we used synthetic composite humeri, and then compared these results in composite bone with cadaveric humeri specimens. Parallel pinning, divergent pinning, and single-screw fixation repairs were performed on synthetic composite humeri with simulated fractures. Six specimens of each type were tested in axial loading and other 6 were tested in torsion. Five pair of cadaveric humeri were tested with diverging pins and single screws for comparison. Single-screw fixation was statistically stronger than pin fixation in axial and torsional loading in both composite and actual bone. There was no statistical difference between composite and cadaveric bone specimens. Single-screw fixation can offer greater stability to adolescent Salter-II fractures than traditional pinning. Single-screw fixation should be considered as a viable alternative to percutaneous pin fixation in transitional patients with little expected remaining growth.

Chemokine (C-C Motif) Receptor 2 Mediates Dendritic Cell Recruitment to the Human Colon but Is Not Responsible for Differences Observed in Dendritic Cell Subsets, Phenotype, and Function Between the Proximal and Distal Colon.

PubMed

Bernardo, David; Durant, Lydia; Mann, Elizabeth R; Bassity, Elizabeth; Montalvillo, Enrique; Man, Ripple; Vora, Rakesh; Reddi, Durga; Bayiroglu, Fahri; Fernández-Salazar, Luis; English, Nick R; Peake, Simon T C; Landy, Jon; Lee, Gui H; Malietzis, George; Siaw, Yi Harn; Murugananthan, Aravinth U; Hendy, Phil; Sánchez-Recio, Eva; Phillips, Robin K S; Garrote, Jose A; Scott, Paul; Parkhill, Julian; Paulsen, Malte; Hart, Ailsa L; Al-Hassi, Hafid O; Arranz, Eduardo; Walker, Alan W; Carding, Simon R; Knight, Stella C

2016-01-01

Most knowledge about gastrointestinal (GI)-tract dendritic cells (DC) relies on murine studies where CD103 + DC specialize in generating immune tolerance with the functionality of CD11b +/- subsets being unclear. Information about human GI-DC is scarce, especially regarding regional specifications. Here, we characterized human DC properties throughout the human colon. Paired proximal (right/ascending) and distal (left/descending) human colonic biopsies from 95 healthy subjects were taken; DC were assessed by flow cytometry and microbiota composition assessed by 16S rRNA gene sequencing. Colonic DC identified were myeloid (mDC, CD11c + CD123 - ) and further divided based on CD103 and SIRPα (human analog of murine CD11b) expression. CD103 - SIRPα + DC were the major population and with CD103 + SIRPα + DC were CD1c + ILT3 + CCR2 + (although CCR2 was not expressed on all CD103 + SIRPα + DC). CD103 + SIRPα - DC constituted a minor subset that were CD141 + ILT3 - CCR2 - . Proximal colon samples had higher total DC counts and fewer CD103 + SIRPα + cells. Proximal colon DC were more mature than distal DC with higher stimulatory capacity for CD4 + CD45RA + T-cells. However, DC and DC-invoked T-cell expression of mucosal homing markers (β7, CCR9) was lower for proximal DC. CCR2 was expressed on circulating CD1c + , but not CD141 + mDC, and mediated DC recruitment by colonic culture supernatants in transwell assays. Proximal colon DC produced higher levels of cytokines. Mucosal microbiota profiling showed a lower microbiota load in the proximal colon, but with no differences in microbiota composition between compartments. Proximal colonic DC subsets differ from those in distal colon and are more mature. Targeted immunotherapy using DC in T-cell mediated GI tract inflammation may therefore need to reflect this immune compartmentalization.

Statistics and Machine Learning based Outlier Detection Techniques for Exoplanets

NASA Astrophysics Data System (ADS)

Goel, Amit; Montgomery, Michele

2015-08-01

Architectures of planetary systems are observable snapshots in time that can indicate formation and dynamic evolution of planets. The observable key parameters that we consider are planetary mass and orbital period. If planet masses are significantly less than their host star masses, then Keplerian Motion is defined as P^2 = a^3 where P is the orbital period in units of years and a is the orbital period in units of Astronomical Units (AU). Keplerian motion works on small scales such as the size of the Solar System but not on large scales such as the size of the Milky Way Galaxy. In this work, for confirmed exoplanets of known stellar mass, planetary mass, orbital period, and stellar age, we analyze Keplerian motion of systems based on stellar age to seek if Keplerian motion has an age dependency and to identify outliers. For detecting outliers, we apply several techniques based on statistical and machine learning methods such as probabilistic, linear, and proximity based models. In probabilistic and statistical models of outliers, the parameters of a closed form probability distributions are learned in order to detect the outliers. Linear models use regression analysis based techniques for detecting outliers. Proximity based models use distance based algorithms such as k-nearest neighbour, clustering algorithms such as k-means, or density based algorithms such as kernel density estimation. In this work, we will use unsupervised learning algorithms with only the proximity based models. In addition, we explore the relative strengths and weaknesses of the various techniques by validating the outliers. The validation criteria for the outliers is if the ratio of planetary mass to stellar mass is less than 0.001. In this work, we present our statistical analysis of the outliers thus detected.

[Determination of proximal chemical composition of squid (dosidicus gigas) and development of gel products].

PubMed

Abugoch, L; Guarda, A; Pérez, L M; Paredes, M P

1999-06-01

The good nutritional properties of meat from big squid (Dosidicus gigas) living on the Chilean coast, was determined through its proximal composition 70 cal/100 g fresh meat; 82.23 +/- 0.98% moisture; 15.32 +/- 0.93% protein; 1.31 +/- 0.12% ashes; 0.87 +/- 0.18% fat and 0.27% NNE (non-nitrogen extract). The big squid meat was used to develop a gel product which contained NaCl and TPP. It was necessary to use additives for gel preparation, such as carragenin or alginate or egg albumin, due to the lack of gelation properties of squid meat. Formulations containing egg albumin showed the highest gel force measured by penetration as compared to those that contained carragenin or alginate.

Comparing Alternative Kernels for the Kernel Method of Test Equating: Gaussian, Logistic, and Uniform Kernels. Research Report. ETS RR-08-12

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; von Davier, Alina A.

2008-01-01

The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…

7 CFR 810.204 - Grades and grade requirements for Six-rowed Malting barley and Six-rowed Blue Malting barley.

Code of Federal Regulations, 2010 CFR

2010-01-01

...— Damaged kernels 1 (percent) Foreign material (percent) Other grains (percent) Skinned and broken kernels....0 10.0 15.0 1 Injured-by-frost kernels and injured-by-mold kernels are not considered damaged kernels or considered against sound barley. Notes: Malting barley shall not be infested in accordance with...

Processing and property evaluation of metal matrix superconducting materials

NASA Technical Reports Server (NTRS)

Rao, Appajosula S.

1995-01-01

Metal - superconductor (YBCO) systems have been prepared and characterized by resistivity, ac susceptibility and dc SQUID magnetic moment measurements. The silver composites showed superconducting transition for all the composites processed and the superconducting transition temperature tends to depend upon the concentration of the silver in the composite. Aluminum composites showed an unusual resistivity results with two transitions around 90 K and 120 K. The superconducting property of silver composites can be explained qualitatively in terms of the proximity theory that has been suggested for the low temperature superconductors.

7 CFR 51.1413 - Damage.

Code of Federal Regulations, 2013 CFR

2013-01-01

... well cured; (e) Poorly developed kernels; (f) Kernels which are dark amber in color; (g) Kernel spots when more than one dark spot is present on either half of the kernel, or when any such spot is more...

7 CFR 51.1413 - Damage.

Code of Federal Regulations, 2014 CFR

2014-01-01

... well cured; (e) Poorly developed kernels; (f) Kernels which are dark amber in color; (g) Kernel spots when more than one dark spot is present on either half of the kernel, or when any such spot is more...

7 CFR 810.205 - Grades and grade requirements for Two-rowed Malting barley.

Code of Federal Regulations, 2010 CFR

2010-01-01

... (percent) Maximum limits of— Wild oats (percent) Foreign material (percent) Skinned and broken kernels... Injured-by-frost kernels and injured-by-mold kernels are not considered damaged kernels or considered...

Effects of almond and pistachio consumption on gut microbiota composition in a randomised cross-over human feeding study

USDA-ARS?s Scientific Manuscript database

Modifying microbiota towards a 'beneficial' composition is a promising approach for improving intestinal as well as overall health. Natural fibers and phytochemicals that reach the proximal colon, such as those present in various nuts, provide substrates for maintaining a healthy and diverse microbi...

Influence of retainer design on two-unit cantilever resin-bonded glass fiber reinforced composite fixed dental prostheses: an in vitro and finite element analysis study.

PubMed

Keulemans, Filip; De Jager, Niek; Kleverlaan, Cornelis J; Feilzer, Albert J

2008-10-01

The aim of this study was to evaluate in vitro the influence of retainer design on the strength of two-unit cantilever resin-bonded glass fiber-reinforced composite (FRC) fixed dental prostheses (FDP). Four retainer designs were tested: a proximal box, a step-box, a dual wing, and a step-box-wing. Of each design on 8 human mandibular molars, FRC-FDPs of a premolar size were produced. The FRC framework was made of resin impregnated unidirectional glass fibers (Estenia C&B EG Fiber, Kuraray) and veneered with hybrid resin composite (Estenia C&B, Kuraray). Panavia F 2.0 (Kuraray) was used as resin luting cement. FRC-FDPs were loaded to failure in a universal testing machine. One-way ANOVA and Tukey's post-hoc test were used to evaluate the data. The four designs were analyzed with finite element analysis (FEA) to reveal the stress distribution within the tooth/restoration complex. Significantly lower fracture strengths were observed with inlay-retained FDPs (proximal box: 300 +/- 65 N; step-box: 309 +/- 37 N) compared to wing-retained FDPs (p < 0.05) (step-box-wing: 662 +/- 99 N; dual wing: 697 +/- 67 N). Proximal-box-, step-box-, and step-box-wing-retained FDPs mainly failed with catastrophic cusp fracture (proximal box 100%, step-box 100%, and step-box-wing 75%), while dual-wing-retained FDPs mainly failed at the adhesive interface and/or due to pontic failure (75%). FEA showed more favorable stress distributions within the tooth/restoration complex for dual wing retainers. A dual-wing retainer is the optimal design for replacement of a single premolar by means of a two-unit cantilever FRC-FDPs.

Detection of ochratoxin A contamination in stored wheat using near-infrared hyperspectral imaging

NASA Astrophysics Data System (ADS)

Senthilkumar, T.; Jayas, D. S.; White, N. D. G.; Fields, P. G.; Gräfenhan, T.

2017-03-01

Near-infrared (NIR) hyperspectral imaging system was used to detect five concentration levels of ochratoxin A (OTA) in contaminated wheat kernels. The wheat kernels artificially inoculated with two different OTA producing Penicillium verrucosum strains, two different non-toxigenic P. verrucosum strains, and sterile control wheat kernels were subjected to NIR hyperspectral imaging. The acquired three-dimensional data were reshaped into readable two-dimensional data. Principal Component Analysis (PCA) was applied to the two dimensional data to identify the key wavelengths which had greater significance in detecting OTA contamination in wheat. Statistical and histogram features extracted at the key wavelengths were used in the linear, quadratic and Mahalanobis statistical discriminant models to differentiate between sterile control, five concentration levels of OTA contamination in wheat kernels, and five infection levels of non-OTA producing P. verrucosum inoculated wheat kernels. The classification models differentiated sterile control samples from OTA contaminated wheat kernels and non-OTA producing P. verrucosum inoculated wheat kernels with a 100% accuracy. The classification models also differentiated between five concentration levels of OTA contaminated wheat kernels and between five infection levels of non-OTA producing P. verrucosum inoculated wheat kernels with a correct classification of more than 98%. The non-OTA producing P. verrucosum inoculated wheat kernels and OTA contaminated wheat kernels subjected to hyperspectral imaging provided different spectral patterns.

Application of kernel method in fluorescence molecular tomography

NASA Astrophysics Data System (ADS)

Zhao, Yue; Baikejiang, Reheman; Li, Changqing

2017-02-01

Reconstruction of fluorescence molecular tomography (FMT) is an ill-posed inverse problem. Anatomical guidance in the FMT reconstruction can improve FMT reconstruction efficiently. We have developed a kernel method to introduce the anatomical guidance into FMT robustly and easily. The kernel method is from machine learning for pattern analysis and is an efficient way to represent anatomical features. For the finite element method based FMT reconstruction, we calculate a kernel function for each finite element node from an anatomical image, such as a micro-CT image. Then the fluorophore concentration at each node is represented by a kernel coefficient vector and the corresponding kernel function. In the FMT forward model, we have a new system matrix by multiplying the sensitivity matrix with the kernel matrix. Thus, the kernel coefficient vector is the unknown to be reconstructed following a standard iterative reconstruction process. We convert the FMT reconstruction problem into the kernel coefficient reconstruction problem. The desired fluorophore concentration at each node can be calculated accordingly. Numerical simulation studies have demonstrated that the proposed kernel-based algorithm can improve the spatial resolution of the reconstructed FMT images. In the proposed kernel method, the anatomical guidance can be obtained directly from the anatomical image and is included in the forward modeling. One of the advantages is that we do not need to segment the anatomical image for the targets and background.

Credit scoring analysis using kernel discriminant

NASA Astrophysics Data System (ADS)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

PubMed Central

Chung, Moo K.; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K.

2014-01-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface. PMID:25791435

Correlation and classification of single kernel fluorescence hyperspectral data with aflatoxin concentration in corn kernels inoculated with Aspergillus flavus spores.

PubMed

Yao, H; Hruska, Z; Kincaid, R; Brown, R; Cleveland, T; Bhatnagar, D

2010-05-01

The objective of this study was to examine the relationship between fluorescence emissions of corn kernels inoculated with Aspergillus flavus and aflatoxin contamination levels within the kernels. Aflatoxin contamination in corn has been a long-standing problem plaguing the grain industry with potentially devastating consequences to corn growers. In this study, aflatoxin-contaminated corn kernels were produced through artificial inoculation of corn ears in the field with toxigenic A. flavus spores. The kernel fluorescence emission data were taken with a fluorescence hyperspectral imaging system when corn kernels were excited with ultraviolet light. Raw fluorescence image data were preprocessed and regions of interest in each image were created for all kernels. The regions of interest were used to extract spectral signatures and statistical information. The aflatoxin contamination level of single corn kernels was then chemically measured using affinity column chromatography. A fluorescence peak shift phenomenon was noted among different groups of kernels with different aflatoxin contamination levels. The fluorescence peak shift was found to move more toward the longer wavelength in the blue region for the highly contaminated kernels and toward the shorter wavelengths for the clean kernels. Highly contaminated kernels were also found to have a lower fluorescence peak magnitude compared with the less contaminated kernels. It was also noted that a general negative correlation exists between measured aflatoxin and the fluorescence image bands in the blue and green regions. The correlation coefficients of determination, r(2), was 0.72 for the multiple linear regression model. The multivariate analysis of variance found that the fluorescence means of four aflatoxin groups, <1, 1-20, 20-100, and >or=100 ng g(-1) (parts per billion), were significantly different from each other at the 0.01 level of alpha. Classification accuracy under a two-class schema ranged from 0.84 to 0.91 when a threshold of either 20 or 100 ng g(-1) was used. Overall, the results indicate that fluorescence hyperspectral imaging may be applicable in estimating aflatoxin content in individual corn kernels.

Classification of Phylogenetic Profiles for Protein Function Prediction: An SVM Approach

NASA Astrophysics Data System (ADS)

Kotaru, Appala Raju; Joshi, Ramesh C.

Predicting the function of an uncharacterized protein is a major challenge in post-genomic era due to problems complexity and scale. Having knowledge of protein function is a crucial link in the development of new drugs, better crops, and even the development of biochemicals such as biofuels. Recently numerous high-throughput experimental procedures have been invented to investigate the mechanisms leading to the accomplishment of a protein’s function and Phylogenetic profile is one of them. Phylogenetic profile is a way of representing a protein which encodes evolutionary history of proteins. In this paper we proposed a method for classification of phylogenetic profiles using supervised machine learning method, support vector machine classification along with radial basis function as kernel for identifying functionally linked proteins. We experimentally evaluated the performance of the classifier with the linear kernel, polynomial kernel and compared the results with the existing tree kernel. In our study we have used proteins of the budding yeast saccharomyces cerevisiae genome. We generated the phylogenetic profiles of 2465 yeast genes and for our study we used the functional annotations that are available in the MIPS database. Our experiments show that the performance of the radial basis kernel is similar to polynomial kernel is some functional classes together are better than linear, tree kernel and over all radial basis kernel outperformed the polynomial kernel, linear kernel and tree kernel. In analyzing these results we show that it will be feasible to make use of SVM classifier with radial basis function as kernel to predict the gene functionality using phylogenetic profiles.

Intraear Compensation of Field Corn, Zea mays, from Simulated and Naturally Occurring Injury by Ear-Feeding Larvae.

PubMed

Steckel, S; Stewart, S D

2015-06-01

Ear-feeding larvae, such as corn earworm, Helicoverpa zea Boddie (Lepidoptera: Noctuidae), can be important insect pests of field corn, Zea mays L., by feeding on kernels. Recently introduced, stacked Bacillus thuringiensis (Bt) traits provide improved protection from ear-feeding larvae. Thus, our objective was to evaluate how injury to kernels in the ear tip might affect yield when this injury was inflicted at the blister and milk stages. In 2010, simulated corn earworm injury reduced total kernel weight (i.e., yield) at both the blister and milk stage. In 2011, injury to ear tips at the milk stage affected total kernel weight. No differences in total kernel weight were found in 2013, regardless of when or how much injury was inflicted. Our data suggested that kernels within the same ear could compensate for injury to ear tips by increasing in size, but this increase was not always statistically significant or sufficient to overcome high levels of kernel injury. For naturally occurring injury observed on multiple corn hybrids during 2011 and 2012, our analyses showed either no or a minimal relationship between number of kernels injured by ear-feeding larvae and the total number of kernels per ear, total kernel weight, or the size of individual kernels. The results indicate that intraear compensation for kernel injury to ear tips can occur under at least some conditions. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Identity and relationships of the Arboreal Caatinga among other floristic units of seasonally dry tropical forests (SDTFs) of north-eastern and Central Brazil.

PubMed

Santos, Rubens M; Oliveira-Filho, Ary T; Eisenlohr, Pedro V; Queiroz, Luciano P; Cardoso, Domingos B O S; Rodal, Maria J N

2012-02-01

The tree species composition of seasonally dry tropical forests (SDTF) in north-eastern and central Brazil is analyzed to address the following hypotheses: (1) variations in species composition are related to both environment (climate and substrate) and spatial proximity; (2) SDTF floristic units may be recognized based on peculiar composition and environment; and (3) the Arboreal Caatinga, a deciduous forest occurring along the hinterland borders of the Caatinga Domain, is one of these units and its flora is more strongly related to the caatinga vegetation than to outlying forests. The study region is framed by the Brazilian coastline, 50th meridian west and 21st parallel south, including the Caatinga Domain and extensions into the Atlantic Forest and Cerrado Domains. Multivariate and geostatistic analyses were performed on a database containing 16,226 occurrence records of 1332 tree species in 187 georeferenced SDTF areas and respective environmental variables. Tree species composition varied significantly with both environmental variables and spatial proximity. Eight SDTF floristic units were recognized in the region, including the Arboreal Caatinga. In terms of species composition, its tree flora showed a stronger link with that of the Cerrado Dry Forest Enclaves. On the other hand, in terms of species frequency across sample areas, the links were stronger with two other units: Rock Outcrops Caatinga and Agreste and Brejo Dry Forests. There is a role for niche-based control of tree species composition across the SDTFs of the region determined primarily by the availability of ground water across time and secondarily by the amount of soil mineral nutrients. Spatial proximity also contributes significantly to the floristic cohesion of SDTF units suggesting a highly dispersal-limited tree flora. These units should be given the status of eco-regions to help driving the conservation policy regarding the protection of their biodiversity.

Identity and relationships of the Arboreal Caatinga among other floristic units of seasonally dry tropical forests (SDTFs) of north-eastern and Central Brazil

PubMed Central

Santos, Rubens M; Oliveira-Filho, Ary T; Eisenlohr, Pedro V; Queiroz, Luciano P; Cardoso, Domingos B O S; Rodal, Maria J N

2012-01-01

The tree species composition of seasonally dry tropical forests (SDTF) in north-eastern and central Brazil is analyzed to address the following hypotheses: (1) variations in species composition are related to both environment (climate and substrate) and spatial proximity; (2) SDTF floristic units may be recognized based on peculiar composition and environment; and (3) the Arboreal Caatinga, a deciduous forest occurring along the hinterland borders of the Caatinga Domain, is one of these units and its flora is more strongly related to the caatinga vegetation than to outlying forests. The study region is framed by the Brazilian coastline, 50th meridian west and 21st parallel south, including the Caatinga Domain and extensions into the Atlantic Forest and Cerrado Domains. Multivariate and geostatistic analyses were performed on a database containing 16,226 occurrence records of 1332 tree species in 187 georeferenced SDTF areas and respective environmental variables. Tree species composition varied significantly with both environmental variables and spatial proximity. Eight SDTF floristic units were recognized in the region, including the Arboreal Caatinga. In terms of species composition, its tree flora showed a stronger link with that of the Cerrado Dry Forest Enclaves. On the other hand, in terms of species frequency across sample areas, the links were stronger with two other units: Rock Outcrops Caatinga and Agreste and Brejo Dry Forests. There is a role for niche-based control of tree species composition across the SDTFs of the region determined primarily by the availability of ground water across time and secondarily by the amount of soil mineral nutrients. Spatial proximity also contributes significantly to the floristic cohesion of SDTF units suggesting a highly dispersal-limited tree flora. These units should be given the status of eco-regions to help driving the conservation policy regarding the protection of their biodiversity. PMID:22423333

Management bone loss of the proximal femur in revision hip arthroplasty: Update on reconstructive options

PubMed Central

Sakellariou, Vasileios I; Babis, George C

2014-01-01

The number of revision total hip arthroplasties is expected to rise as the indications for arthroplasty will expand due to the aging population. The prevalence of extensive proximal femoral bone loss is expected to increase subsequently. The etiology of bone loss from the proximal femur after total hip arthroplasty is multifactorial. Stress shielding, massive osteolysis, extensive loosening and history of multiple surgeries consist the most common etiologies. Reconstruction of extensive bone loss of the proximal femur during a revision hip arthroplasty is a major challenge for even the most experienced orthopaedic surgeon. The amount of femoral bone loss and the bone quality of the remaining metaphyseal and diaphyseal bone dictate the selection of appropriate reconstructive option. These include the use of impaction allografting, distal press-fit fixation, allograft-prosthesis composites and tumor megaprostheses. This review article is a concise review of the current literature and provides an algorithmic approach for reconstruction of different types of proximal femoral bone defects. PMID:25405090

Evidence-based Kernels: Fundamental Units of Behavioral Influence

PubMed Central

Biglan, Anthony

2008-01-01

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior. PMID:18712600

Integrating the Gradient of the Thin Wire Kernel

NASA Technical Reports Server (NTRS)

Champagne, Nathan J.; Wilton, Donald R.

2008-01-01

A formulation for integrating the gradient of the thin wire kernel is presented. This approach employs a new expression for the gradient of the thin wire kernel derived from a recent technique for numerically evaluating the exact thin wire kernel. This approach should provide essentially arbitrary accuracy and may be used with higher-order elements and basis functions using the procedure described in [4].When the source and observation points are close, the potential integrals over wire segments involving the wire kernel are split into parts to handle the singular behavior of the integrand [1]. The singularity characteristics of the gradient of the wire kernel are different than those of the wire kernel, and the axial and radial components have different singularities. The characteristics of the gradient of the wire kernel are discussed in [2]. To evaluate the near electric and magnetic fields of a wire, the integration of the gradient of the wire kernel needs to be calculated over the source wire. Since the vector bases for current have constant direction on linear wire segments, these integrals reduce to integrals of the form

Ranking Support Vector Machine with Kernel Approximation

PubMed Central

Dou, Yong

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms. PMID:28293256

Ranking Support Vector Machine with Kernel Approximation.

PubMed

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Three edible wild mushrooms from Nigeria: their proximate and mineral composition.

PubMed

Alofe, F V; Odeyemi, O; Oke, O L

1996-01-01

The pilei (caps) and the stipes (stalks) of the button and early open-cap (cup) stages of Lentinus subnudus, Psathyrella atroumbonata and Termitomyces striatus were assayed separately for their proximate and mineral composition. The differences observed in the contents of some of the proximate components seem to be related to species and mushroom parts. P. atroumbonata was richest in crude and true protein, L. subnudus was richer in crude fiber, ash and carbohydrates. Mineral contents appeared to be dependent on type and parts of the mushrooms analysed. The three mushrooms were good sources of magnesium, zinc and iron. L. subnudus contained between 14.83 and 20.00 ppm of iron, P. atroumbonata contained between 20.01 and 22.09 ppm and T. striatus contained between 17.13 and 22.93 ppm of iron. The pilei of P. atroumbonata and T. striatus are very good sources of zinc. Zinc contents for the pilei of P. atroumbonata were 63.81 and 64.94 ppm respectively. Zinc contents for T. striatus were 90.45 and 92.49 ppm respectively.

Nutrient database improvement project: the influence of USDA quality and yield grade on the separable components and proximate composition of raw and cooked retail cuts from the beef chuck.

PubMed

West, S E; Harris, K B; Haneklaus, A N; Savell, J W; Thompson, L D; Brooks, J C; Pool, J K; Luna, A M; Engle, T E; Schutz, J S; Woerner, D R; Arcibeque, S L; Belk, K E; Douglass, L; Leheska, J M; McNeill, S; Howe, J C; Holden, J M; Duvall, M; Patterson, K

2014-08-01

This study was designed to provide updated information on the separable components, cooking yields, and proximate composition of retail cuts from the beef chuck. Additionally, the impact the United States Department of Agriculture (USDA) Quality and Yield Grade may have on such factors was investigated. Ultimately, these data will be used in the USDA - Nutrient Data Laboratory's (NDL) National Nutrient Database for Standard Reference (SR). To represent the current United States beef supply, seventy-two carcasses were selected from six regions of the country based on USDA Yield Grade, USDA Quality Grade, gender, and genetic type. Whole beef chuck primals from selected carcasses were shipped to three university laboratories for subsequent retail cut fabrication, raw and cooked cut dissection, and proximate analyses. The incorporation of these data into the SR will improve dietary education, product labeling, and other applications both domestically and abroad, thus emphasizing the importance of accurate and relevant beef nutrient data. Copyright © 2014. Published by Elsevier Ltd.

Ceramic/metal and A15/metal superconducting composite materials exploiting the superconducting proximity effect and method of making the same

DOEpatents

Holcomb, Matthew J.

1999-01-01

A composite superconducting material made of coated particles of ceramic superconducting material and a metal matrix material. The metal matrix material fills the regions between the coated particles. The coating material is a material that is chemically nonreactive with the ceramic. Preferably, it is silver. The coating serves to chemically insulate the ceramic from the metal matrix material. The metal matrix material is a metal that is susceptible to the superconducting proximity effect. Preferably, it is a NbTi alloy. The metal matrix material is induced to become superconducting by the superconducting proximity effect when the temperature of the material goes below the critical temperature of the ceramic. The material has the improved mechanical properties of the metal matrix material. Preferably, the material consists of approximately 10% NbTi, 90% coated ceramic particles (by volume). Certain aspects of the material and method will depend upon the particular ceramic superconductor employed. An alternative embodiment of the invention utilizes A15 compound superconducting particles in a metal matrix material which is preferably a NbTi alloy.

DIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins.

PubMed

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Banchariya, Anjali; Rao, Atmakuri Ramakrishna

2017-03-24

Insecticide resistance is a major challenge for the control program of insect pests in the fields of crop protection, human and animal health etc. Resistance to different insecticides is conferred by the proteins encoded from certain class of genes of the insects. To distinguish the insecticide resistant proteins from non-resistant proteins, no computational tool is available till date. Thus, development of such a computational tool will be helpful in predicting the insecticide resistant proteins, which can be targeted for developing appropriate insecticides. Five different sets of feature viz., amino acid composition (AAC), di-peptide composition (DPC), pseudo amino acid composition (PAAC), composition-transition-distribution (CTD) and auto-correlation function (ACF) were used to map the protein sequences into numeric feature vectors. The encoded numeric vectors were then used as input in support vector machine (SVM) for classification of insecticide resistant and non-resistant proteins. Higher accuracies were obtained under RBF kernel than that of other kernels. Further, accuracies were observed to be higher for DPC feature set as compared to others. The proposed approach achieved an overall accuracy of >90% in discriminating resistant from non-resistant proteins. Further, the two classes of resistant proteins i.e., detoxification-based and target-based were discriminated from non-resistant proteins with >95% accuracy. Besides, >95% accuracy was also observed for discrimination of proteins involved in detoxification- and target-based resistance mechanisms. The proposed approach not only outperformed Blastp, PSI-Blast and Delta-Blast algorithms, but also achieved >92% accuracy while assessed using an independent dataset of 75 insecticide resistant proteins. This paper presents the first computational approach for discriminating the insecticide resistant proteins from non-resistant proteins. Based on the proposed approach, an online prediction server DIRProt has also been developed for computational prediction of insecticide resistant proteins, which is accessible at http://cabgrid.res.in:8080/dirprot/ . The proposed approach is believed to supplement the efforts needed to develop dynamic insecticides in wet-lab by targeting the insecticide resistant proteins.

Operator based integration of information in multimodal radiological search mission with applications to anomaly detection

NASA Astrophysics Data System (ADS)

Benedetto, J.; Cloninger, A.; Czaja, W.; Doster, T.; Kochersberger, K.; Manning, B.; McCullough, T.; McLane, M.

2014-05-01

Successful performance of radiological search mission is dependent on effective utilization of mixture of signals. Examples of modalities include, e.g., EO imagery and gamma radiation data, or radiation data collected during multiple events. In addition, elevation data or spatial proximity can be used to enhance the performance of acquisition systems. State of the art techniques in processing and exploitation of complex information manifolds rely on diffusion operators. Our approach involves machine learning techniques based on analysis of joint data- dependent graphs and their associated diffusion kernels. Then, the significant eigenvectors of the derived fused graph Laplace and Schroedinger operators form the new representation, which provides integrated features from the heterogeneous input data. The families of data-dependent Laplace and Schroedinger operators on joint data graphs, shall be integrated by means of appropriately designed fusion metrics. These fused representations are used for target and anomaly detection.

[Seasonal variation of proximate composition in three commercially important species in the Gulf of Nicoya, Puntarenas, Costa Rica].

PubMed

Rodríguez, Cristian Fonseca; Solera, Fabián Chavarriá; Mejía-Arana, Fernando

2013-03-01

Nutritional value of seafood for human consumption is worldwide recognized. Some information have been generated in other countries, nevertheless, there is limited information describing the chemical composition of some fishery important species caught in the Gulf of Nicoya. For this reason, we studied the levels of proximal components of the edible parts (fresh) of three commercially important species. The meat samples of snook Centropomus unionesis, the shrimp Trachypenaeus byrdi and the bivalve Polymesoda radiata, were collected from the Puntarenas local fish market during the fishing season of February 2009 to January 2010. Proximate composition analysis was determined according to AOAC methodology, and evaluated the moisture content, and protein and lipid composition of shellfish meats. The results indicated that the moisture content ranged from 74.6-80.6g/100g for snook 76.9-80.0g/100g for shrimp and 77.9-89.5g/100g for green mussel. After the moisture, the protein was the most abundant chemical fraction (6.8 to 21g/100g) showing the highest values in February for the shrimp and green mussel, and December for snook. The largest fluctuations in the lipid content were found in the snook, ranging from 0.7g/100g to 5.6g/100g; the highest values in this fraction were found in shrimp, green mussel and snook, for July, February and April samples respectively. Considering these results, we concluded that fish and shrimp species studied are a good alternative for human consumption as a source of protein and low lipid content.

21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

Code of Federal Regulations, 2011 CFR

2011-04-01

... source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed...

21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

Code of Federal Regulations, 2013 CFR

2013-04-01

... source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed...

21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

Code of Federal Regulations, 2012 CFR

2012-04-01

... source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed...

Wigner functions defined with Laplace transform kernels.

PubMed

Oh, Se Baek; Petruccelli, Jonathan C; Tian, Lei; Barbastathis, George

2011-10-24

We propose a new Wigner-type phase-space function using Laplace transform kernels--Laplace kernel Wigner function. Whereas momentum variables are real in the traditional Wigner function, the Laplace kernel Wigner function may have complex momentum variables. Due to the property of the Laplace transform, a broader range of signals can be represented in complex phase-space. We show that the Laplace kernel Wigner function exhibits similar properties in the marginals as the traditional Wigner function. As an example, we use the Laplace kernel Wigner function to analyze evanescent waves supported by surface plasmon polariton. © 2011 Optical Society of America

Online learning control using adaptive critic designs with sparse kernel machines.

PubMed

Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

2013-05-01

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

Influence of wheat kernel physical properties on the pulverizing process.

PubMed

Dziki, Dariusz; Cacak-Pietrzak, Grażyna; Miś, Antoni; Jończyk, Krzysztof; Gawlik-Dziki, Urszula

2014-10-01

The physical properties of wheat kernel were determined and related to pulverizing performance by correlation analysis. Nineteen samples of wheat cultivars about similar level of protein content (11.2-12.8 % w.b.) and obtained from organic farming system were used for analysis. The kernel (moisture content 10 % w.b.) was pulverized by using the laboratory hammer mill equipped with round holes 1.0 mm screen. The specific grinding energy ranged from 120 kJkg(-1) to 159 kJkg(-1). On the basis of data obtained many of significant correlations (p < 0.05) were found between wheat kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

Composite Replacement of Amalgam Restoration Versus Freshly Cut Dentin: An In Vitro Microleakage Comparison.

PubMed

Redwan, H; Bardwell, D N; Ali, A; Finkelman, M; Khayat, S; Weber, H-P

2016-01-01

The aim of this study was to evaluate the microleakage of the composite restorations when bonded to tooth structure previously restored with amalgam material compared with that of freshly cut dentin. Thirty intact, extracted intact human molars were mounted in autopolymerizing acrylic resin. Class II box preparations were prepared on the occluso-proximal surfaces of each tooth (4-mm bucco-lingual width and 2-mm mesio-distal depth) with the gingival cavosurface margin 1 mm above the CEJ. Each cavity was then restored using high copper amalgam restoration (Disperalloy, Dentsply) and then thermocycled for 10,000 thermal cycles. Twenty-five of the amalgam restorations were then carefully removed and replaced with Filtek Supreme Ultra Universal (3M ESPE); the remaining five were used for scanning electron microscopy and energy dispersive x-ray spectroscopy analysis. A preparation of the same dimensions was performed on the opposite surface of the tooth and restored with composite resin and thermocycled for 5000 thermal cycles. Twenty samples were randomly selected for dye penetration testing using silver nitrate staining to detect the microleakage. The specimens were analyzed with a stereomicroscope at a magnification of 20×. All of the measurements were done in micrometers; two readings were taken for each cavity at the occlusal and proximal margins. Two measurements were taken using a 0-3 scale and the percentage measurements. Corrosion products were not detected in either group (fresh cut dentin and teeth previously restored with amalgam). No statistically significant difference was found between the microleakage of the two groups using a 0-3 scale at the occlusal margins (McNemar test, p=0.727) or proximal margins (Wilcoxon signed-rank test, p=0.174). No significance difference was found between the two groups using the percentage measurements and a Wilcoxon signed-rank test at either the occlusal (p=0.675) or proximal (p=0.513) margins. However, marginal microleakage was statistically significant between the proximal and occlusal margins (p<0.001). Within the limitations of this in vitro study, no significant difference was found between the microleakage of nondiscolored dentin in teeth that were previously restored with amalgam compared with freshly cut dentin. However, marginal microleakage in the proximal surface was higher than that in the occlusal surface.

Classification of corn kernels contaminated with aflatoxins using fluorescence and reflectance hyperspectral images analysis

NASA Astrophysics Data System (ADS)

Zhu, Fengle; Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Brown, Robert; Bhatnagar, Deepak; Cleveland, Thomas

2015-05-01

Aflatoxins are secondary metabolites produced by certain fungal species of the Aspergillus genus. Aflatoxin contamination remains a problem in agricultural products due to its toxic and carcinogenic properties. Conventional chemical methods for aflatoxin detection are time-consuming and destructive. This study employed fluorescence and reflectance visible near-infrared (VNIR) hyperspectral images to classify aflatoxin contaminated corn kernels rapidly and non-destructively. Corn ears were artificially inoculated in the field with toxigenic A. flavus spores at the early dough stage of kernel development. After harvest, a total of 300 kernels were collected from the inoculated ears. Fluorescence hyperspectral imagery with UV excitation and reflectance hyperspectral imagery with halogen illumination were acquired on both endosperm and germ sides of kernels. All kernels were then subjected to chemical analysis individually to determine aflatoxin concentrations. A region of interest (ROI) was created for each kernel to extract averaged spectra. Compared with healthy kernels, fluorescence spectral peaks for contaminated kernels shifted to longer wavelengths with lower intensity, and reflectance values for contaminated kernels were lower with a different spectral shape in 700-800 nm region. Principal component analysis was applied for data compression before classifying kernels into contaminated and healthy based on a 20 ppb threshold utilizing the K-nearest neighbors algorithm. The best overall accuracy achieved was 92.67% for germ side in the fluorescence data analysis. The germ side generally performed better than endosperm side. Fluorescence and reflectance image data achieved similar accuracy.

The effect of season, sex, and portion on the carcass characteristics, pH, color, and proximate composition of Egyptian Goose (Alopochen aegyptiacus) meat.

PubMed

Geldenhuys, Greta; Hoffman, Louwrens C; Muller, Nina

2013-12-01

The carcass yield, physical characteristics, and proximate composition of Egyptian geese (Alopochen aegyptiacus), a southern African gamebird species, have been studied. A total of 69 geese were harvested during 2 seasons: summer (n = 36) and winter (n = 33). This total group of geese consisted of 27 female birds and 42 male birds. Sex alone affected (P ≤ 0.05) the live and carcass weights, and the average muscle weight (g) of each portion was higher for the male fowl. The data does not indicate differences between the meat's physical characteristics on account of sex; however, the meat from the female birds did have a higher intramuscular fat content. Season (winter vs. summer) did not influence the average muscle weights (g) of the breast, thigh, and drumstick portions, but the intramuscular fat content content of the birds hunted in winter was higher. Muscle color and pH differed as a result of season with the summer meat having a higher pH and more vivid red color compared with winter. The physical characteristics and the proximate composition of the breast, thigh, and drumstick portions varied considerably. This is essentially connected to a difference in physical activity of the muscles in the portions. Overall, this study revealed that to ensure a consistent eating quality the harvesting periods of Egyptian geese should be considered.

Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

2015-10-01

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

Design of a multiple kernel learning algorithm for LS-SVM by convex programming.

PubMed

Jian, Ling; Xia, Zhonghang; Liang, Xijun; Gao, Chuanhou

2011-06-01

As a kernel based method, the performance of least squares support vector machine (LS-SVM) depends on the selection of the kernel as well as the regularization parameter (Duan, Keerthi, & Poo, 2003). Cross-validation is efficient in selecting a single kernel and the regularization parameter; however, it suffers from heavy computational cost and is not flexible to deal with multiple kernels. In this paper, we address the issue of multiple kernel learning for LS-SVM by formulating it as semidefinite programming (SDP). Furthermore, we show that the regularization parameter can be optimized in a unified framework with the kernel, which leads to an automatic process for model selection. Extensive experimental validations are performed and analyzed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Novel near-infrared sampling apparatus for single kernel analysis of oil content in maize.

PubMed

Janni, James; Weinstock, B André; Hagen, Lisa; Wright, Steve

2008-04-01

A method of rapid, nondestructive chemical and physical analysis of individual maize (Zea mays L.) kernels is needed for the development of high value food, feed, and fuel traits. Near-infrared (NIR) spectroscopy offers a robust nondestructive method of trait determination. However, traditional NIR bulk sampling techniques cannot be applied successfully to individual kernels. Obtaining optimized single kernel NIR spectra for applied chemometric predictive analysis requires a novel sampling technique that can account for the heterogeneous forms, morphologies, and opacities exhibited in individual maize kernels. In this study such a novel technique is described and compared to less effective means of single kernel NIR analysis. Results of the application of a partial least squares (PLS) derived model for predictive determination of percent oil content per individual kernel are shown.

Computed tomography coronary stent imaging with iterative reconstruction: a trade-off study between medium kernel and sharp kernel.

PubMed

Zhou, Qijing; Jiang, Biao; Dong, Fei; Huang, Peiyu; Liu, Hongtao; Zhang, Minming

2014-01-01

To evaluate the improvement of iterative reconstruction in image space (IRIS) technique in computed tomographic (CT) coronary stent imaging with sharp kernel, and to make a trade-off analysis. Fifty-six patients with 105 stents were examined by 128-slice dual-source CT coronary angiography (CTCA). Images were reconstructed using standard filtered back projection (FBP) and IRIS with both medium kernel and sharp kernel applied. Image noise and the stent diameter were investigated. Image noise was measured both in background vessel and in-stent lumen as objective image evaluation. Image noise score and stent score were performed as subjective image evaluation. The CTCA images reconstructed with IRIS were associated with significant noise reduction compared to that of CTCA images reconstructed using FBP technique in both of background vessel and in-stent lumen (the background noise decreased by approximately 25.4% ± 8.2% in medium kernel (P

Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

PubMed

Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

2016-07-07

Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population.

PubMed

Cheng, Ruiru; Kong, Zhongxin; Zhang, Liwei; Xie, Quan; Jia, Haiyan; Yu, Dong; Huang, Yulong; Ma, Zhengqiang

2017-07-01

Seven kernel dimension QTLs were identified in wheat, and kernel thickness was found to be the most important dimension for grain weight improvement. Kernel morphology and weight of wheat (Triticum aestivum L.) affect both yield and quality; however, the genetic basis of these traits and their interactions has not been fully understood. In this study, to investigate the genetic factors affecting kernel morphology and the association of kernel morphology traits with kernel weight, kernel length (KL), width (KW) and thickness (KT) were evaluated, together with hundred-grain weight (HGW), in a recombinant inbred line population derived from Nanda2419 × Wangshuibai, with data from five trials (two different locations over 3 years). The results showed that HGW was more closely correlated with KT and KW than with KL. A whole genome scan revealed four QTLs for KL, one for KW and two for KT, distributed on five different chromosomes. Of them, QKl.nau-2D for KL, and QKt.nau-4B and QKt.nau-5A for KT were newly identified major QTLs for the respective traits, explaining up to 32.6 and 41.5% of the phenotypic variations, respectively. Increase of KW and KT and reduction of KL/KT and KW/KT ratios always resulted in significant higher grain weight. Lines combining the Nanda 2419 alleles of the 4B and 5A intervals had wider, thicker, rounder kernels and a 14% higher grain weight in the genotype-based analysis. A strong, negative linear relationship of the KW/KT ratio with grain weight was observed. It thus appears that kernel thickness is the most important kernel dimension factor in wheat improvement for higher yield. Mapping and marker identification of the kernel dimension-related QTLs definitely help realize the breeding goals.

Kernel learning at the first level of inference.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adaptive kernel function using line transect sampling

NASA Astrophysics Data System (ADS)

Albadareen, Baker; Ismail, Noriszura

2018-04-01

The estimation of f(0) is crucial in the line transect method which is used for estimating population abundance in wildlife survey's. The classical kernel estimator of f(0) has a high negative bias. Our study proposes an adaptation in the kernel function which is shown to be more efficient than the usual kernel estimator. A simulation study is adopted to compare the performance of the proposed estimators with the classical kernel estimators.

Kernel Partial Least Squares for Nonlinear Regression and Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Clancy, Daniel (Technical Monitor)

2002-01-01

This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

Pollen source effects on growth of kernel structures and embryo chemical compounds in maize.

PubMed

Tanaka, W; Mantese, A I; Maddonni, G A

2009-08-01

Previous studies have reported effects of pollen source on the oil concentration of maize (Zea mays) kernels through modifications to both the embryo/kernel ratio and embryo oil concentration. The present study expands upon previous analyses by addressing pollen source effects on the growth of kernel structures (i.e. pericarp, endosperm and embryo), allocation of embryo chemical constituents (i.e. oil, protein, starch and soluble sugars), and the anatomy and histology of the embryos. Maize kernels with different oil concentration were obtained from pollinations with two parental genotypes of contrasting oil concentration. The dynamics of the growth of kernel structures and allocation of embryo chemical constituents were analysed during the post-flowering period. Mature kernels were dissected to study the anatomy (embryonic axis and scutellum) and histology [cell number and cell size of the scutellums, presence of sub-cellular structures in scutellum tissue (starch granules, oil and protein bodies)] of the embryos. Plants of all crosses exhibited a similar kernel number and kernel weight. Pollen source modified neither the growth period of kernel structures, nor pericarp growth rate. By contrast, pollen source determined a trade-off between embryo and endosperm growth rates, which impacted on the embryo/kernel ratio of mature kernels. Modifications to the embryo size were mediated by scutellum cell number. Pollen source also affected (P < 0.01) allocation of embryo chemical compounds. Negative correlations among embryo oil concentration and those of starch (r = 0.98, P < 0.01) and soluble sugars (r = 0.95, P < 0.05) were found. Coincidently, embryos with low oil concentration had an increased (P < 0.05-0.10) scutellum cell area occupied by starch granules and fewer oil bodies. The effects of pollen source on both embryo/kernel ratio and allocation of embryo chemicals seems to be related to the early established sink strength (i.e. sink size and sink activity) of the embryos.

7 CFR 868.254 - Broken kernels determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.254 Section 868.254 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Governing Application of Standards § 868.254 Broken kernels determination. Broken kernels shall be...

7 CFR 51.2090 - Serious damage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... defect which makes a kernel or piece of kernel unsuitable for human consumption, and includes decay...: Shriveling when the kernel is seriously withered, shrunken, leathery, tough or only partially developed: Provided, that partially developed kernels are not considered seriously damaged if more than one-fourth of...

Anisotropic hydrodynamics with a scalar collisional kernel

NASA Astrophysics Data System (ADS)

Almaalol, Dekrayat; Strickland, Michael

2018-04-01

Prior studies of nonequilibrium dynamics using anisotropic hydrodynamics have used the relativistic Anderson-Witting scattering kernel or some variant thereof. In this paper, we make the first study of the impact of using a more realistic scattering kernel. For this purpose, we consider a conformal system undergoing transversally homogenous and boost-invariant Bjorken expansion and take the collisional kernel to be given by the leading order 2 ↔2 scattering kernel in scalar λ ϕ4 . We consider both classical and quantum statistics to assess the impact of Bose enhancement on the dynamics. We also determine the anisotropic nonequilibrium attractor of a system subject to this collisional kernel. We find that, when the near-equilibrium relaxation-times in the Anderson-Witting and scalar collisional kernels are matched, the scalar kernel results in a higher degree of momentum-space anisotropy during the system's evolution, given the same initial conditions. Additionally, we find that taking into account Bose enhancement further increases the dynamically generated momentum-space anisotropy.

Ideal regularization for learning kernels from labels.

PubMed

Pan, Binbin; Lai, Jianhuang; Shen, Lixin

2014-08-01

In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently. Copyright © 2014 Elsevier Ltd. All rights reserved.

Straight-chain halocarbon forming fluids for TRISO fuel kernel production - Tests with yttria-stabilized zirconia microspheres

NASA Astrophysics Data System (ADS)

Baker, M. P.; King, J. C.; Gorman, B. P.; Braley, J. C.

2015-03-01

Current methods of TRISO fuel kernel production in the United States use a sol-gel process with trichloroethylene (TCE) as the forming fluid. After contact with radioactive materials, the spent TCE becomes a mixed hazardous waste, and high costs are associated with its recycling or disposal. Reducing or eliminating this mixed waste stream would not only benefit the environment, but would also enhance the economics of kernel production. Previous research yielded three candidates for testing as alternatives to TCE: 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane. This study considers the production of yttria-stabilized zirconia (YSZ) kernels in silicone oil and the three chosen alternative formation fluids, with subsequent characterization of the produced kernels and used forming fluid. Kernels formed in silicone oil and bromotetradecane were comparable to those produced by previous kernel production efforts, while those produced in chlorooctadecane and iodododecane experienced gelation issues leading to poor kernel formation and geometry.

Numerical study of the ignition behavior of a post-discharge kernel injected into a turbulent stratified cross-flow

NASA Astrophysics Data System (ADS)

Jaravel, Thomas; Labahn, Jeffrey; Ihme, Matthias

2017-11-01

The reliable initiation of flame ignition by high-energy spark kernels is critical for the operability of aviation gas turbines. The evolution of a spark kernel ejected by an igniter into a turbulent stratified environment is investigated using detailed numerical simulations with complex chemistry. At early times post ejection, comparisons of simulation results with high-speed Schlieren data show that the initial trajectory of the kernel is well reproduced, with a significant amount of air entrainment from the surrounding flow that is induced by the kernel ejection. After transiting in a non-flammable mixture, the kernel reaches a second stream of flammable methane-air mixture, where the successful of the kernel ignition was found to depend on the local flow state and operating conditions. By performing parametric studies, the probability of kernel ignition was identified, and compared with experimental observations. The ignition behavior is characterized by analyzing the local chemical structure, and its stochastic variability is also investigated.

The site, size, spatial stability, and energetics of an X-ray flare kernel

NASA Technical Reports Server (NTRS)

Petrasso, R.; Gerassimenko, M.; Nolte, J.

1979-01-01

The site, size evolution, and energetics of an X-ray kernel that dominated a solar flare during its rise and somewhat during its peak are investigated. The position of the kernel remained stationary to within about 3 arc sec over the 30-min interval of observations, despite pulsations in the kernel X-ray brightness in excess of a factor of 10. This suggests a tightly bound, deeply rooted magnetic structure, more plausibly associated with the near chromosphere or low corona rather than with the high corona. The H-alpha flare onset coincided with the appearance of the kernel, again suggesting a close spatial and temporal coupling between the chromospheric H-alpha event and the X-ray kernel. At the first kernel brightness peak its size was no larger than about 2 arc sec, when it accounted for about 40% of the total flare flux. In the second rise phase of the kernel, a source power input of order 2 times 10 to the 24th ergs/sec is minimally required.

Methods and compositions for controlling gene expression by RNA processing

DOEpatents

Doudna, Jennifer A.; Qi, Lei S.; Haurwitz, Rachel E.; Arkin, Adam P.

2017-08-29

The present disclosure provides nucleic acids encoding an RNA recognition sequence positioned proximal to an insertion site for the insertion of a sequence of interest; and host cells genetically modified with the nucleic acids. The present disclosure also provides methods of modifying the activity of a target RNA, and kits and compositions for carrying out the methods.

Porosity Formation and Microleakage of Composite Resins Using the Snowplow Technique

DTIC Science & Technology

2012-05-04

on a proximal surface of mounted 3rd molar tooth samples. A bonding agent (Optibond FL, Kerr) was placed and light cured (Bluephase 16i, Ivoclar...Page Figure 1 Tooth preparation........................................................................ 20 Figure 2 Skyscan...al., 2010). Combined with dental adhesives, composites provide esthetically conservative restorations due to their ability to bond to tooth structure

Nutrient database improvement project: Separable components and proximate composition of retail cuts from the beef loin and round

USDA-ARS?s Scientific Manuscript database

Beef nutrition research has become increasingly important domestically and internationally for the beef industry and its consumers. The objective of this study was to analyze the nutrient composition of ten beef loin and round cuts to update the nutrient data in the USDA National Nutrient Database f...

Class II glass ionomer cermet tunnel, resin sandwich and amalgam restorations over 2 years.

PubMed

Wilkie, R; Lidums, A; Smales, R

1993-08-01

This study compared the clinical behavior of a glass ionomer (polyalkenoate) silver cermet, a posterior resin composite used with the "tunnel" technique, a posterior resin composite used with the "closed sandwich" technique, and a high-copper amalgam for restoring small, proximal surface carious lesions. Two dentists placed 86 restorations in the posterior permanent teeth of 26 adults treated at a dental hospital. Restorations were assessed at 6-month intervals over 2 years for gingivitis adjacent to them, the tightness of proximal contacts, occlusal wear, surface voids, roughness and cracking, surface and marginal staining, and marginal fracture. Small filling defects, surface voids and occlusal wear were obvious with the cermet material, with surface crazing and cracking present in 48% of the tunnel restorations. Two of the posterior resin composites, but none of the amalgam restorations, also failed. The cermet cannot be recommended as a long-term permanent restorative material in situations where it is likely to be subjected to heavy occlusal stresses and abrasive wear.

Effect of chitosan coatings enriched with cinnamon oil on proximate composition of rainbow trout fillets

NASA Astrophysics Data System (ADS)

Yıldız, Pınar Oǧuzhan

2017-04-01

The effects of chitosan coating enriched with cinnamon oil on proximate composition of rainbow trout (Oncorhynchus mykiss) during storage at 4°C was investigated. The treatments included the following: C1 (control samples), C2 (chitosan coating) and C3 (chitosan + 1 % [v/w] cinnamon EO added). The control and the coated fish samples were analysed for chemical (moisture, protein, lipid and ash) composition. The mean of moisture, protein, lipid and ash in the control samples (C1) were 70.3%, 20.1%, 2.6% and 1.2%, in coated samples (C2) 69.70%, 24.21%, 2.4% and 2.2% and coated+cinnamon oil samples (C3) 69.70%, 25.05%, 2.5% and 2.2%, respectively. Moisture and lipid contents in control groups were higher than other groups, but protein and ash contents were lower. Significant increases (p<0.05) in protein content were observed between samples, which subsequently decreased the moisture content of these samples.

Altered fish community and feeding behaviour in close proximity to boat moorings in an urban estuary.

PubMed

Lanham, Brendan S; Vergés, Adriana; Hedge, Luke H; Johnston, Emma L; Poore, Alistair G B

2018-04-01

Coastal urbanization has led to large-scale transformation of estuaries, with artificial structures now commonplace. Boat moorings are known to reduce seagrass cover, but little is known about their effect on fish communities. We used underwater video to quantify abundance, diversity, composition and feeding behaviour of fish assemblages on two scales: with increasing distance from moorings on fine scales, and among locations where moorings were present or absent. Fish were less abundant in close proximity to boat moorings, and the species composition varied on fine scales, leading to lower predation pressure near moorings. There was no relationship at the location with seagrass. On larger scales, we detected no differences in abundance or community composition among locations where moorings were present or absent. These findings show a clear impact of moorings on fish and highlight the importance of fine-scale assessments over location-scale comparisons in the detection of the effects of artificial structures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Improving the visualization of 3D ultrasound data with 3D filtering

NASA Astrophysics Data System (ADS)

Shamdasani, Vijay; Bae, Unmin; Managuli, Ravi; Kim, Yongmin

2005-04-01

3D ultrasound imaging is quickly gaining widespread clinical acceptance as a visualization tool that allows clinicians to obtain unique views not available with traditional 2D ultrasound imaging and an accurate understanding of patient anatomy. The ability to acquire, manipulate and interact with the 3D data in real time is an important feature of 3D ultrasound imaging. Volume rendering is often used to transform the 3D volume into 2D images for visualization. Unlike computed tomography (CT) and magnetic resonance imaging (MRI), volume rendering of 3D ultrasound data creates noisy images in which surfaces cannot be readily discerned due to speckles and low signal-to-noise ratio. The degrading effect of speckles is especially severe when gradient shading is performed to add depth cues to the image. Several researchers have reported that smoothing the pre-rendered volume with a 3D convolution kernel, such as 5x5x5, can significantly improve the image quality, but at the cost of decreased resolution. In this paper, we have analyzed the reasons for the improvement in image quality with 3D filtering and determined that the improvement is due to two effects. The filtering reduces speckles in the volume data, which leads to (1) more accurate gradient computation and better shading and (2) decreased noise during compositing. We have found that applying a moderate-size smoothing kernel (e.g., 7x7x7) to the volume data before gradient computation combined with some smoothing of the volume data (e.g., with a 3x3x3 lowpass filter) before compositing yielded images with good depth perception and no appreciable loss in resolution. Providing the clinician with the flexibility to control both of these effects (i.e., shading and compositing) independently could improve the visualization of the 3D ultrasound data. Introducing this flexibility into the ultrasound machine requires 3D filtering to be performed twice on the volume data, once before gradient computation and again before compositing. 3D filtering of an ultrasound volume containing millions of voxels requires a large amount of computation, and doing it twice decreases the number of frames that can be visualized per second. To address this, we have developed several techniques to make computation efficient. For example, we have used the moving average method to filter a 128x128x128 volume with a 3x3x3 boxcar kernel in 17 ms on a single MAP processor running at 400 MHz. The same methods reduced the computing time on a Pentium 4 running at 3 GHz from 110 ms to 62 ms. We believe that our proposed method can improve 3D ultrasound visualization without sacrificing resolution and incurring an excessive computing time.

The pre-image problem in kernel methods.

PubMed

Kwok, James Tin-yau; Tsang, Ivor Wai-hung

2004-11-01

In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applications, such as on using kernel principal component analysis (PCA) for image denoising. Unlike the traditional method which relies on nonlinear optimization, our proposed method directly finds the location of the pre-image based on distance constraints in the feature space. It is noniterative, involves only linear algebra and does not suffer from numerical instability or local minimum problems. Evaluations on performing kernel PCA and kernel clustering on the USPS data set show much improved performance.

Effects of Amygdaline from Apricot Kernel on Transplanted Tumors in Mice.

PubMed

Yamshanov, V A; Kovan'ko, E G; Pustovalov, Yu I

2016-03-01

The effects of amygdaline from apricot kernel added to fodder on the growth of transplanted LYO-1 and Ehrlich carcinoma were studied in mice. Apricot kernels inhibited the growth of both tumors. Apricot kernels, raw and after thermal processing, given 2 days before transplantation produced a pronounced antitumor effect. Heat-processed apricot kernels given in 3 days after transplantation modified the tumor growth and prolonged animal lifespan. Thermal treatment did not considerably reduce the antitumor effect of apricot kernels. It was hypothesized that the antitumor effect of amygdaline on Ehrlich carcinoma and LYO-1 lymphosarcoma was associated with the presence of bacterial genome in the tumor.

Development of a kernel function for clinical data.

PubMed

Daemen, Anneleen; De Moor, Bart

2009-01-01

For most diseases and examinations, clinical data such as age, gender and medical history guides clinical management, despite the rise of high-throughput technologies. To fully exploit such clinical information, appropriate modeling of relevant parameters is required. As the widely used linear kernel function has several disadvantages when applied to clinical data, we propose a new kernel function specifically developed for this data. This "clinical kernel function" more accurately represents similarities between patients. Evidently, three data sets were studied and significantly better performances were obtained with a Least Squares Support Vector Machine when based on the clinical kernel function compared to the linear kernel function.

Manycore Performance-Portability: Kokkos Multidimensional Array Library

DOE PAGES

Edwards, H. Carter; Sunderland, Daniel; Porter, Vicki; ...

2012-01-01

Large, complex scientific and engineering application code have a significant investment in computational kernels to implement their mathematical models. Porting these computational kernels to the collection of modern manycore accelerator devices is a major challenge in that these devices have diverse programming models, application programming interfaces (APIs), and performance requirements. The Kokkos Array programming model provides library-based approach to implement computational kernels that are performance-portable to CPU-multicore and GPGPU accelerator devices. This programming model is based upon three fundamental concepts: (1) manycore compute devices each with its own memory space, (2) data parallel kernels and (3) multidimensional arrays. Kernel executionmore » performance is, especially for NVIDIA® devices, extremely dependent on data access patterns. Optimal data access pattern can be different for different manycore devices – potentially leading to different implementations of computational kernels specialized for different devices. The Kokkos Array programming model supports performance-portable kernels by (1) separating data access patterns from computational kernels through a multidimensional array API and (2) introduce device-specific data access mappings when a kernel is compiled. An implementation of Kokkos Array is available through Trilinos [Trilinos website, http://trilinos.sandia.gov/, August 2011].« less

Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

PubMed

Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

2017-12-15

Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

Impact of deep learning on the normalization of reconstruction kernel effects in imaging biomarker quantification: a pilot study in CT emphysema

NASA Astrophysics Data System (ADS)

Jin, Hyeongmin; Heo, Changyong; Kim, Jong Hyo

2018-02-01

Differing reconstruction kernels are known to strongly affect the variability of imaging biomarkers and thus remain as a barrier in translating the computer aided quantification techniques into clinical practice. This study presents a deep learning application to CT kernel conversion which converts a CT image of sharp kernel to that of standard kernel and evaluates its impact on variability reduction of a pulmonary imaging biomarker, the emphysema index (EI). Forty cases of low-dose chest CT exams obtained with 120kVp, 40mAs, 1mm thickness, of 2 reconstruction kernels (B30f, B50f) were selected from the low dose lung cancer screening database of our institution. A Fully convolutional network was implemented with Keras deep learning library. The model consisted of symmetric layers to capture the context and fine structure characteristics of CT images from the standard and sharp reconstruction kernels. Pairs of the full-resolution CT data set were fed to input and output nodes to train the convolutional network to learn the appropriate filter kernels for converting the CT images of sharp kernel to standard kernel with a criterion of measuring the mean squared error between the input and target images. EIs (RA950 and Perc15) were measured with a software package (ImagePrism Pulmo, Seoul, South Korea) and compared for the data sets of B50f, B30f, and the converted B50f. The effect of kernel conversion was evaluated with the mean and standard deviation of pair-wise differences in EI. The population mean of RA950 was 27.65 +/- 7.28% for B50f data set, 10.82 +/- 6.71% for the B30f data set, and 8.87 +/- 6.20% for the converted B50f data set. The mean of pair-wise absolute differences in RA950 between B30f and B50f is reduced from 16.83% to 1.95% using kernel conversion. Our study demonstrates the feasibility of applying the deep learning technique for CT kernel conversion and reducing the kernel-induced variability of EI quantification. The deep learning model has a potential to improve the reliability of imaging biomarker, especially in evaluating the longitudinal changes of EI even when the patient CT scans were performed with different kernels.

Metabolic network prediction through pairwise rational kernels.

PubMed

Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

2014-09-26

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy values have been improved, while maintaining lower construction and execution times. The power of using kernels is that almost any sort of data can be represented using kernels. Therefore, completely disparate types of data can be combined to add power to kernel-based machine learning methods. When we compared our proposal using PRKs with other similar kernel, the execution times were decreased, with no compromise of accuracy. We also proved that by combining PRKs with other kernels that include evolutionary information, the accuracy can also also be improved. As our proposal can use any type of sequence data, genes do not need to be properly annotated, avoiding accumulation errors because of incorrect previous annotations.

Differential metabolome analysis of field-grown maize kernels in response to drought stress

USDA-ARS?s Scientific Manuscript database

Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...

Occurrence of 'super soft' wheat kernel texture in hexaploid and tetraploid wheats

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture is a key trait that governs milling performance, flour starch damage, flour particle size, flour hydration properties, and baking quality. Kernel texture is commonly measured using the Perten Single Kernel Characterization System (SKCS). The SKCS returns texture values (Hardness...

7 CFR 868.203 - Basis of determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... FOR CERTAIN AGRICULTURAL COMMODITIES United States Standards for Rough Rice Principles Governing..., heat-damaged kernels, red rice and damaged kernels, chalky kernels, other types, color, and the special grade Parboiled rough rice shall be on the basis of the whole and large broken kernels of milled rice...

7 CFR 868.203 - Basis of determination.

Code of Federal Regulations, 2011 CFR

2011-01-01

... FOR CERTAIN AGRICULTURAL COMMODITIES United States Standards for Rough Rice Principles Governing..., heat-damaged kernels, red rice and damaged kernels, chalky kernels, other types, color, and the special grade Parboiled rough rice shall be on the basis of the whole and large broken kernels of milled rice...

7 CFR 868.304 - Broken kernels determination.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 7 2011-01-01 2011-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

7 CFR 868.304 - Broken kernels determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

WE-EF-207-01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task-Driven Imaging for Cone-Beam CT in Interventional Guidance

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

Gang, G; Stayman, J; Ouadah, S

2015-06-15

Purpose: This work introduces a task-driven imaging framework that utilizes a patient-specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task-based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view-dependent reconstruction kernel in filtered-backprojection reconstruction and non-circular orbit design in model-based reconstruction. Methods: The system model is based on a cascaded systems analysis of cone-beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and amore » wide range of imaging parameters. Detectability index for a non-prewhitening observer model is used as the objective function in a task-driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient-based optimization of reconstruction kernel. The non-circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task-driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit. Results: The task-driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non-circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil. Conclusion: The task-driven imaging framework leverages a knowledge of the imaging task within a patient-specific anatomical model to optimize image acquisition and reconstruction techniques, thereby improving imaging performance beyond that achievable with conventional approaches. 2R01-CA-112163; R01-EB-017226; U01-EB-018758; Siemens Healthcare (Forcheim, Germany)« less

Mapping Fire Severity Using Imaging Spectroscopy and Kernel Based Image Analysis

NASA Astrophysics Data System (ADS)

Prasad, S.; Cui, M.; Zhang, Y.; Veraverbeke, S.

2014-12-01

Improved spatial representation of within-burn heterogeneity after wildfires is paramount to effective land management decisions and more accurate fire emissions estimates. In this work, we demonstrate feasibility and efficacy of airborne imaging spectroscopy (hyperspectral imagery) for quantifying wildfire burn severity, using kernel based image analysis techniques. Two different airborne hyperspectral datasets, acquired over the 2011 Canyon and 2013 Rim fire in California using the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) sensor, were used in this study. The Rim Fire, covering parts of the Yosemite National Park started on August 17, 2013, and was the third largest fire in California's history. Canyon Fire occurred in the Tehachapi mountains, and started on September 4, 2011. In addition to post-fire data for both fires, half of the Rim fire was also covered with pre-fire images. Fire severity was measured in the field using Geo Composite Burn Index (GeoCBI). The field data was utilized to train and validate our models, wherein the trained models, in conjunction with imaging spectroscopy data were used for GeoCBI estimation wide geographical regions. This work presents an approach for using remotely sensed imagery combined with GeoCBI field data to map fire scars based on a non-linear (kernel based) epsilon-Support Vector Regression (e-SVR), which was used to learn the relationship between spectra and GeoCBI in a kernel-induced feature space. Classification of healthy vegetation versus fire-affected areas based on morphological multi-attribute profiles was also studied. The availability of pre- and post-fire imaging spectroscopy data over the Rim Fire provided a unique opportunity to evaluate the performance of bi-temporal imaging spectroscopy for assessing post-fire effects. This type of data is currently constrained because of limited airborne acquisitions before a fire, but will become widespread with future spaceborne sensors such as those on the planned NASA HyspIRI mission.

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

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

Carter, L.L.; Hendricks, J.S.

1983-01-01

The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays.

Performance Characteristics of a Kernel-Space Packet Capture Module

DTIC Science & Technology

2010-03-01

Defense, or the United States Government . AFIT/GCO/ENG/10-03 PERFORMANCE CHARACTERISTICS OF A KERNEL-SPACE PACKET CAPTURE MODULE THESIS Presented to the...3.1.2.3 Prototype. The proof of concept for this research is the design, development, and comparative performance analysis of a kernel level N2d capture...changes to kernel code 5. Can be used for both user-space and kernel-space capture applications in order to control comparative performance analysis to

High-throughput method for ear phenotyping and kernel weight estimation in maize using ear digital imaging.

PubMed

Makanza, R; Zaman-Allah, M; Cairns, J E; Eyre, J; Burgueño, J; Pacheco, Ángela; Diepenbrock, C; Magorokosho, C; Tarekegne, A; Olsen, M; Prasanna, B M

2018-01-01

Grain yield, ear and kernel attributes can assist to understand the performance of maize plant under different environmental conditions and can be used in the variety development process to address farmer's preferences. These parameters are however still laborious and expensive to measure. A low-cost ear digital imaging method was developed that provides estimates of ear and kernel attributes i.e., ear number and size, kernel number and size as well as kernel weight from photos of ears harvested from field trial plots. The image processing method uses a script that runs in a batch mode on ImageJ; an open source software. Kernel weight was estimated using the total kernel number derived from the number of kernels visible on the image and the average kernel size. Data showed a good agreement in terms of accuracy and precision between ground truth measurements and data generated through image processing. Broad-sense heritability of the estimated parameters was in the range or higher than that for measured grain weight. Limitation of the method for kernel weight estimation is discussed. The method developed in this work provides an opportunity to significantly reduce the cost of selection in the breeding process, especially for resource constrained crop improvement programs and can be used to learn more about the genetic bases of grain yield determinants.

A Kernel-based Lagrangian method for imperfectly-mixed chemical reactions

NASA Astrophysics Data System (ADS)

Schmidt, Michael J.; Pankavich, Stephen; Benson, David A.

2017-05-01

Current Lagrangian (particle-tracking) algorithms used to simulate diffusion-reaction equations must employ a certain number of particles to properly emulate the system dynamics-particularly for imperfectly-mixed systems. The number of particles is tied to the statistics of the initial concentration fields of the system at hand. Systems with shorter-range correlation and/or smaller concentration variance require more particles, potentially limiting the computational feasibility of the method. For the well-known problem of bimolecular reaction, we show that using kernel-based, rather than Dirac delta, particles can significantly reduce the required number of particles. We derive the fixed width of a Gaussian kernel for a given reduced number of particles that analytically eliminates the error between kernel and Dirac solutions at any specified time. We also show how to solve for the fixed kernel size by minimizing the squared differences between solutions over any given time interval. Numerical results show that the width of the kernel should be kept below about 12% of the domain size, and that the analytic equations used to derive kernel width suffer significantly from the neglect of higher-order moments. The simulations with a kernel width given by least squares minimization perform better than those made to match at one specific time. A heuristic time-variable kernel size, based on the previous results, performs on par with the least squares fixed kernel size.

Optimized Kernel Entropy Components.

PubMed

Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

2017-06-01

This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

Brain tumor image segmentation using kernel dictionary learning.

PubMed

Jeon Lee; Seung-Jun Kim; Rong Chen; Herskovits, Edward H

2015-08-01

Automated brain tumor image segmentation with high accuracy and reproducibility holds a big potential to enhance the current clinical practice. Dictionary learning (DL) techniques have been applied successfully to various image processing tasks recently. In this work, kernel extensions of the DL approach are adopted. Both reconstructive and discriminative versions of the kernel DL technique are considered, which can efficiently incorporate multi-modal nonlinear feature mappings based on the kernel trick. Our novel discriminative kernel DL formulation allows joint learning of a task-driven kernel-based dictionary and a linear classifier using a K-SVD-type algorithm. The proposed approaches were tested using real brain magnetic resonance (MR) images of patients with high-grade glioma. The obtained preliminary performances are competitive with the state of the art. The discriminative kernel DL approach is seen to reduce computational burden without much sacrifice in performance.

SEMI-SUPERVISED OBJECT RECOGNITION USING STRUCTURE KERNEL

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Ling, Fan

2013-01-01

Object recognition is a fundamental problem in computer vision. Part-based models offer a sparse, flexible representation of objects, but suffer from difficulties in training and often use standard kernels. In this paper, we propose a positive definite kernel called “structure kernel”, which measures the similarity of two part-based represented objects. The structure kernel has three terms: 1) the global term that measures the global visual similarity of two objects; 2) the part term that measures the visual similarity of corresponding parts; 3) the spatial term that measures the spatial similarity of geometric configuration of parts. The contribution of this paper is to generalize the discriminant capability of local kernels to complex part-based object models. Experimental results show that the proposed kernel exhibit higher accuracy than state-of-art approaches using standard kernels. PMID:23666108

Burrower bugs (Heteroptera: Cydnidae) in peanut: seasonal species abundance, tillage effects, grade reduction effects, insecticide efficacy, and management.

PubMed

Chapin, Jay W; Thomas, James S

2003-08-01

Pitfall traps placed in South Carolina peanut, Arachis hypogaea (L.), fields collected three species of burrower bugs (Cydnidae): Cyrtomenus ciliatus (Palisot de Beauvois), Sehirus cinctus cinctus (Palisot de Beauvois), and Pangaeus bilineatus (Say). Cyrtomenus ciliatus was rarely collected. Sehirus cinctus produced a nymphal cohort in peanut during May and June, probably because of abundant henbit seeds, Lamium amplexicaule L., in strip-till production systems. No S. cinctus were present during peanut pod formation. Pangaeus bilineatus was the most abundant species collected and the only species associated with peanut kernel feeding injury. Overwintering P. bilineatus adults were present in a conservation tillage peanut field before planting and two to three subsequent generations were observed. Few nymphs were collected until the R6 (full seed) growth stage. Tillage and choice of cover crop affected P. bilineatus populations. Peanuts strip-tilled into corn or wheat residue had greater P. bilineatus populations and kernel-feeding than conventional tillage or strip-tillage into rye residue. Fall tillage before planting a wheat cover crop also reduced burrower bug feeding on peanut. At-pegging (early July) granular chlorpyrifos treatments were most consistent in suppressing kernel feeding. Kernels fed on by P. bilineatus were on average 10% lighter than unfed on kernels. Pangaeus bilineatus feeding reduced peanut grade by reducing individual kernel weight, and increasing the percentage damaged kernels. Each 10% increase in kernels fed on by P. bilineatus was associated with a 1.7% decrease in total sound mature kernels, and kernel feeding levels above 30% increase the risk of damaged kernel grade penalties.

Imaging and automated detection of Sitophilus oryzae (Coleoptera: Curculionidae) pupae in hard red winter wheat.

PubMed

Toews, Michael D; Pearson, Tom C; Campbell, James F

2006-04-01

Computed tomography, an imaging technique commonly used for diagnosing internal human health ailments, uses multiple x-rays and sophisticated software to recreate a cross-sectional representation of a subject. The use of this technique to image hard red winter wheat, Triticum aestivm L., samples infested with pupae of Sitophilus oryzae (L.) was investigated. A software program was developed to rapidly recognize and quantify the infested kernels. Samples were imaged in a 7.6-cm (o.d.) plastic tube containing 0, 50, or 100 infested kernels per kg of wheat. Interkernel spaces were filled with corn oil so as to increase the contrast between voids inside kernels and voids among kernels. Automated image processing, using a custom C language software program, was conducted separately on each 100 g portion of the prepared samples. The average detection accuracy in the five infested kernels per 100-g samples was 94.4 +/- 7.3% (mean +/- SD, n = 10), whereas the average detection accuracy in the 10 infested kernels per 100-g sample was 87.3 +/- 7.9% (n = 10). Detection accuracy in the 10 infested kernels per 100-g samples was slightly less than the five infested kernels per 100-g samples because of some infested kernels overlapping with each other or air bubbles in the oil. A mean of 1.2 +/- 0.9 (n = 10) bubbles (per tube) was incorrectly classed as infested kernels in replicates containing no infested kernels. In light of these positive results, future studies should be conducted using additional grains, insect species, and life stages.

Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models.

PubMed

Cuevas, Jaime; Crossa, José; Soberanis, Víctor; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino; Campos, Gustavo de Los; Montesinos-López, O A; Burgueño, Juan

2016-11-01

In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an empirical Bayesian method (RKHS EB). We performed single-environment analyses and extended to account for G × E interaction (GBLUP-G × E, RKHS KA-G × E and RKHS EB-G × E) in wheat ( L.) and maize ( L.) data sets. For single-environment analyses of wheat and maize data sets, RKHS EB and RKHS KA had higher prediction accuracy than GBLUP for all environments. For the wheat data, the RKHS KA-G × E and RKHS EB-G × E models did show up to 60 to 68% superiority over the corresponding single environment for pairs of environments with positive correlations. For the wheat data set, the models with Gaussian kernels had accuracies up to 17% higher than that of GBLUP-G × E. For the maize data set, the prediction accuracy of RKHS EB-G × E and RKHS KA-G × E was, on average, 5 to 6% higher than that of GBLUP-G × E. The superiority of the Gaussian kernel models over the linear kernel is due to more flexible kernels that accounts for small, more complex marker main effects and marker-specific interaction effects. Copyright © 2016 Crop Science Society of America.

Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

PubMed

Zhang, Zhanhui; Wu, Xiangyuan; Shi, Chaonan; Wang, Rongna; Li, Shengfei; Wang, Zhaohui; Liu, Zonghua; Xue, Yadong; Tang, Guiliang; Tang, Jihua

2016-02-01

Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

Image quality of mixed convolution kernel in thoracic computed tomography.

PubMed

Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

2016-11-01

The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing, manufacturing, packing, processing, preparing, treating...

Local Observed-Score Kernel Equating

ERIC Educational Resources Information Center

Wiberg, Marie; van der Linden, Wim J.; von Davier, Alina A.

2014-01-01

Three local observed-score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias--as defined by Lord's criterion of equity--and percent relative error. The local kernel item response…

7 CFR 51.1241 - Damage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... which have been broken to the extent that the kernel within is plainly visible without minute... discoloration beneath, but the peanut shall be judged as it appears with the talc. (c) Kernels which are rancid or decayed. (d) Moldy kernels. (e) Kernels showing sprouts extending more than one-eighth inch from...

7 CFR 981.61 - Redetermination of kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Redetermination of kernel weight. 981.61 Section 981... GROWN IN CALIFORNIA Order Regulating Handling Volume Regulation § 981.61 Redetermination of kernel weight. The Board, on the basis of reports by handlers, shall redetermine the kernel weight of almonds...

7 CFR 981.60 - Determination of kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Determination of kernel weight. 981.60 Section 981.60... Regulating Handling Volume Regulation § 981.60 Determination of kernel weight. (a) Almonds for which settlement is made on kernel weight. All lots of almonds, whether shelled or unshelled, for which settlement...

Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

USDA-ARS?s Scientific Manuscript database

Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...

7 CFR 999.400 - Regulation governing the importation of filberts.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Definitions. (1) Filberts means filberts or hazelnuts. (2) Inshell filberts means filberts, the kernels or edible portions of which are contained in the shell. (3) Shelled filberts means the kernels of filberts... Filbert kernels or portions of filbert kernels shall meet the following requirements: (1) Well dried and...

7 CFR 51.1404 - Tolerances.

Code of Federal Regulations, 2010 CFR

2010-01-01

.... (2) For kernel defects, by count. (i) 12 percent for pecans with kernels which fail to meet the... kernels which are seriously damaged: Provided, That not more than six-sevenths of this amount, or 6 percent, shall be allowed for kernels which are rancid, moldy, decayed or injured by insects: And provided...

Enhanced gluten properties in soft kernel durum wheat

USDA-ARS?s Scientific Manuscript database

Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...

End-use quality of soft kernel durum wheat

USDA-ARS?s Scientific Manuscript database

Kernel texture is a major determinant of end-use quality of wheat. Durum wheat has very hard kernels. We developed soft kernel durum wheat via Ph1b-mediated homoeologous recombination. The Hardness locus was transferred from Chinese Spring to Svevo durum wheat via back-crossing. ‘Soft Svevo’ had SKC...

7 CFR 51.2560 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... are excessively thin kernels and can have black, brown or gray surface with a dark interior color and the immaturity has adversely affected the flavor of the kernel. (2) Kernel spotting refers to dark brown or dark gray spots aggregating more than one-eighth of the surface of the kernel. (g) Serious...

7 CFR 51.2560 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... are excessively thin kernels and can have black, brown or gray surface with a dark interior color and the immaturity has adversely affected the flavor of the kernel. (2) Kernel spotting refers to dark brown or dark gray spots aggregating more than one-eighth of the surface of the kernel. (g) Serious...

7 CFR 51.1416 - Optional determinations.

Code of Federal Regulations, 2010 CFR

2010-01-01

... throughout the lot. (a) Edible kernel content. A minimum sample of at least 500 grams of in-shell pecans shall be used for determination of edible kernel content. After the sample is weighed and shelled... determine edible kernel content for the lot. (b) Poorly developed kernel content. A minimum sample of at...

Foraging location and site fidelity of the Double-crested Cormorant on Oneida Lake, New York

USGS Publications Warehouse

Coleman, J.T.H.; Richmond, M.E.; Rudstam, L. G.; Mattison, P.M.

2005-01-01

We studied the foraging behavior of the Double-crested Cormorant (Phalacrocorax auritus) on Oneida Lake, New York, by monitoring the activities of 27 radio-tagged birds in July and August of 1999 and 2000. A total of 224 locations were obtained of cormorants actively diving, and presumed foraging, at the time of detection. A geographic information system was used to examine foraging distances from the nesting island, the water depth and type of substrate at preferred foraging sites, and to estimate kernel home ranges for analysis of individual foraging site fidelity. An explanatory model was developed to determine parameters affecting the distance to cormorant foraging sites. The mean distance to foraging locations of tagged cormorants from the colony site was 2,920 m (SE ?? 180 m, max = 14,190 m), and 52% of the locations were within 2,000 m of the nesting island. No cormorant was observed making daily foraging trips to outside water bodies. Mean foraging distance was greater during morning than in the afternoon, and there was a significant effect of the time of day on distance. There was no significant effect of sex date, a seasonal measure on distance to foraging location. Individual cormorants exhibited fidelity to specific foraging sites. Most cormorants foraged in close proximity to the nesting island much of the time, while those detected further from the island tended to return repeatedly to the same locations. Ninety percent of the foraging locations were in water depths ???7.5 m, and most were in water 2.5-5 m deep. Compositional analysis of habitat use revealed a preference for these depths, along with substrates of cobble with rubble, and silt with clay.

3DRT-MPASS

NASA Technical Reports Server (NTRS)

Lickly, Ben

2005-01-01

Data from all current JPL missions are stored in files called SPICE kernels. At present, animators who want to use data from these kernels have to either read through the kernels looking for the desired data, or write programs themselves to retrieve information about all the needed objects for their animations. In this project, methods of automating the process of importing the data from the SPICE kernels were researched. In particular, tools were developed for creating basic scenes in Maya, a 3D computer graphics software package, from SPICE kernels.

Relationships between botanical and chemical composition of forages: a multivariate approach to grasslands in the Western Italian Alps.

PubMed

Ravetto Enri, Simone; Renna, Manuela; Probo, Massimiliano; Lussiana, Carola; Battaglini, Luca M; Lonati, Michele; Lombardi, Giampiero

2017-03-01

Plant composition of species-rich mountain grasslands can affect the sensorial and chemical attributes of dairy and meat products, with implications for human health. A multivariate approach was used to analyse the complex relationships between vegetation characteristics (botanical composition and plant community variables) and chemical composition (proximate constituents and fatty acid profile) in mesophilic and dry vegetation ecological groups, comprising six different semi-natural grassland types in the Western Italian Alps. Mesophilic and dry grasslands were comparable in terms of phenology, biodiversity indices and proportion of botanical families. The content of total fatty acids and that of the most abundant fatty acids (alpha-linolenic, linoleic and palmitic acids) were mainly associated to nutrient-rich plant species, belonging to the mesophilic grassland ecological group. Mesophilic grasslands showed also higher values of crude protein, lower values of fibre content and they were related to higher pastoral values of vegetation compared to dry grasslands. The proximate composition and fatty acid profile appeared mainly single species dependent rather than botanical family dependent. These findings highlight that forage from mesophilic grasslands can provide higher nutritive value for ruminants and may be associated to ruminant-derived food products with a healthier fatty acid profile. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Alterations in juvenile diploid and triploid African catfish skin gelatin yield and amino acid composition: Effects of chlorpyrifos and butachlor exposures.

PubMed

Karami, Ali; Karbalaei, Samaneh; Zad Bagher, Fariba; Ismail, Amin; Simpson, Stuart L; Courtenay, Simon C

2016-08-01

Skin is a major by-product of the fisheries and aquaculture industries and is a valuable source of gelatin. This study examined the effect of triploidization on gelatin yield and proximate composition of the skin of African catfish (Clarias gariepinus). We further investigated the effects of two commonly used pesticides, chlorpyrifos (CPF) and butachlor (BUC), on the skin gelatin yield and amino acid composition in juvenile full-sibling diploid and triploid African catfish. In two separate experiments, diploid and triploid C. gariepinus were exposed for 21 days to graded CPF [mean measured: 10, 16, or 31 μg/L] or BUC concentrations [Mean measured: 22, 44, or 60 μg/L]. No differences in skin gelatin yield, amino acid or proximate compositions were observed between diploid and triploid control groups. None of the pesticide treatments affected the measured parameters in diploid fish. In triploids, however, gelatin yield was affected by CPF treatments while amino acid composition remained unchanged. Butachlor treatments did not alter any of the measured variables in triploid fish. To our knowledge, this study is the first to investigate changes in the skin gelatin yield and amino acid composition in any animal as a response to polyploidization and/or contaminant exposure. Copyright © 2016 Elsevier Ltd. All rights reserved.

Generalization Performance of Regularized Ranking With Multiscale Kernels.

PubMed

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Graph wavelet alignment kernels for drug virtual screening.

PubMed

Smalter, Aaron; Huan, Jun; Lushington, Gerald

2009-06-01

In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.

Oecophylla longinoda (Hymenoptera: Formicidae) Lead to Increased Cashew Kernel Size and Kernel Quality.

PubMed

Anato, F M; Sinzogan, A A C; Offenberg, J; Adandonon, A; Wargui, R B; Deguenon, J M; Ayelo, P M; Vayssières, J-F; Kossou, D K

2017-06-01

Weaver ants, Oecophylla spp., are known to positively affect cashew, Anacardium occidentale L., raw nut yield, but their effects on the kernels have not been reported. We compared nut size and the proportion of marketable kernels between raw nuts collected from trees with and without ants. Raw nuts collected from trees with weaver ants were 2.9% larger than nuts from control trees (i.e., without weaver ants), leading to 14% higher proportion of marketable kernels. On trees with ants, the kernel: raw nut ratio from nuts damaged by formic acid was 4.8% lower compared with nondamaged nuts from the same trees. Weaver ants provided three benefits to cashew production by increasing yields, yielding larger nuts, and by producing greater proportions of marketable kernel mass. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Small convolution kernels for high-fidelity image restoration

NASA Technical Reports Server (NTRS)

Reichenbach, Stephen E.; Park, Stephen K.

1991-01-01

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

Kernels, Degrees of Freedom, and Power Properties of Quadratic Distance Goodness-of-Fit Tests

PubMed Central

Lindsay, Bruce G.; Markatou, Marianthi; Ray, Surajit

2014-01-01

In this article, we study the power properties of quadratic-distance-based goodness-of-fit tests. First, we introduce the concept of a root kernel and discuss the considerations that enter the selection of this kernel. We derive an easy to use normal approximation to the power of quadratic distance goodness-of-fit tests and base the construction of a noncentrality index, an analogue of the traditional noncentrality parameter, on it. This leads to a method akin to the Neyman-Pearson lemma for constructing optimal kernels for specific alternatives. We then introduce a midpower analysis as a device for choosing optimal degrees of freedom for a family of alternatives of interest. Finally, we introduce a new diffusion kernel, called the Pearson-normal kernel, and study the extent to which the normal approximation to the power of tests based on this kernel is valid. Supplementary materials for this article are available online. PMID:24764609

The quantitative properties of three soft X-ray flare kernels observed with the AS&E X-ray telescope on Skylab

NASA Technical Reports Server (NTRS)

Kahler, S. W.; Petrasso, R. D.; Kane, S. R.

1976-01-01

The physical parameters for the kernels of three solar X-ray flare events have been deduced using photographic data from the S-054 X-ray telescope on Skylab as the primary data source and 1-8 and 8-20 A fluxes from Solrad 9 as the secondary data source. The kernels had diameters of about 5-7 seconds of arc and in two cases electron densities at least as high as 0.3 trillion per cu cm. The lifetimes of the kernels were 5-10 min. The presence of thermal conduction during the decay phases is used to argue: (1) that kernels are entire, not small portions of, coronal loop structures, and (2) that flare heating must continue during the decay phase. We suggest a simple geometric model to explain the role of kernels in flares in which kernels are identified with emerging flux regions.

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 3 2011-04-01 2011-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2013-01-01 2013-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2014-01-01 2014-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

Study on impact of habitat degradation on proximate composition and amino acid profile of Indian major carps from different habitats.

PubMed

Hussain, Bilal; Sultana, Tayyaba; Sultana, Salma; Ahmed, Z; Mahboob, Shahid

2018-05-01

This investigation is aimed to study an impact of habitat degradation on proximate composition and amino acid (AAs) profile of Catla catla, Labeo rohita and Cirrhinus mrigala collected from polluted, non-polluted area (upstream) and a commercial fish farm. The amino acid profile was estimated by the amino acid analyzer. C. catla collected from the polluted environment had highest lipid, protein and ash contents (12.04 ± 0.01, 13.45 ± 0.01 and 0.93 ± 0.03%, respectively). The high protein content (14.73 ± 0.01 and 14.12 ± 0. 01%) was recorded in C. catla procured from non-polluted (upstream) wild habitat of River Chenab and controlled commercial fish farm. Farmed fish species showed comparatively higher moisture contents followed by upstream and polluted area fishes. C. mrigala showed significant differences in amino acid and proximate composition collected from a polluted site of the river Chenab. C. catla collected from non-polluted site of the river showed an excellent nutrient profile, followed by L. rohita (wild and farmed) and C. mrigala (polluted area), respectively. All fishes from the polluted areas of the River Chenab indicated a significant decrease in the concentration of some AAs when compared to farmed and wild (upstream) major carps. Omitting of some important AAs was also observed in the meat of fish harvested from polluted habitat of this river. C. mrigala and L. rohita exhibited a significant increase in the concentration of some of non-essential amino acids such as cysteine in their meat. The results indicated that wild fish (upstream) and farmed fish species had highest protein contents and amino acid profile and hence appeared to be the best for human consumption. The proximate composition and AAs profiles of fish harvested from the polluted area of the river clearly indicated that efforts shall be made for the restoration of habitat to continue the requirement of high quality fish meat at a low cost to the human population.

Oil point and mechanical behaviour of oil palm kernels in linear compression

NASA Astrophysics Data System (ADS)

Kabutey, Abraham; Herak, David; Choteborsky, Rostislav; Mizera, Čestmír; Sigalingging, Riswanti; Akangbe, Olaosebikan Layi

2017-07-01

The study described the oil point and mechanical properties of roasted and unroasted bulk oil palm kernels under compression loading. The literature information available is very limited. A universal compression testing machine and vessel diameter of 60 mm with a plunger were used by applying maximum force of 100 kN and speed ranging from 5 to 25 mm min-1. The initial pressing height of the bulk kernels was measured at 40 mm. The oil point was determined by a litmus test for each deformation level of 5, 10, 15, 20, and 25 mm at a minimum speed of 5 mmmin-1. The measured parameters were the deformation, deformation energy, oil yield, oil point strain and oil point pressure. Clearly, the roasted bulk kernels required less deformation energy compared to the unroasted kernels for recovering the kernel oil. However, both kernels were not permanently deformed. The average oil point strain was determined at 0.57. The study is an essential contribution to pursuing innovative methods for processing palm kernel oil in rural areas of developing countries.

Dynamic Changes in Phenolics and Antioxidant Capacity during Pecan (Carya illinoinensis) Kernel Ripening and Its Phenolics Profiles.

PubMed

Jia, Xiaodong; Luo, Huiting; Xu, Mengyang; Zhai, Min; Guo, Zhongren; Qiao, Yushan; Wang, Liangju

2018-02-16

Pecan ( Carya illinoinensis ) kernels have a high phenolics content and a high antioxidant capacity compared to other nuts-traits that have attracted great interest of late. Changes in the total phenolic content (TPC), condensed tannins (CT), total flavonoid content (TFC), five individual phenolics, and antioxidant capacity of five pecan cultivars were investigated during the process of kernel ripening. Ultra-performance liquid chromatography coupled with quadruple time-of-flight mass (UPLC-Q/TOF-MS) was also used to analyze the phenolics profiles in mixed pecan kernels. TPC, CT, TFC, individual phenolics, and antioxidant capacity were changed in similar patterns, with values highest at the water or milk stages, lowest at milk or dough stages, and slightly varied at kernel stages. Forty phenolics were tentatively identified in pecan kernels, of which two were first reported in the genus Carya , six were first reported in Carya illinoinensis , and one was first reported in its kernel. The findings on these new phenolic compounds provide proof of the high antioxidant capacity of pecan kernels.

Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2016-02-03

A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.

Novel characterization method of impedance cardiography signals using time-frequency distributions.

PubMed

Escrivá Muñoz, Jesús; Pan, Y; Ge, S; Jensen, E W; Vallverdú, M

2018-03-16

The purpose of this document is to describe a methodology to select the most adequate time-frequency distribution (TFD) kernel for the characterization of impedance cardiography signals (ICG). The predominant ICG beat was extracted from a patient and was synthetized using time-frequency variant Fourier approximations. These synthetized signals were used to optimize several TFD kernels according to a performance maximization. The optimized kernels were tested for noise resistance on a clinical database. The resulting optimized TFD kernels are presented with their performance calculated using newly proposed methods. The procedure explained in this work showcases a new method to select an appropriate kernel for ICG signals and compares the performance of different time-frequency kernels found in the literature for the case of ICG signals. We conclude that, for ICG signals, the performance (P) of the spectrogram with either Hanning or Hamming windows (P = 0.780) and the extended modified beta distribution (P = 0.765) provided similar results, higher than the rest of analyzed kernels. Graphical abstract Flowchart for the optimization of time-frequency distribution kernels for impedance cardiography signals.

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

NASA Astrophysics Data System (ADS)

Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

The effect of access to contraceptive services on injectable use and demand for family planning in Malawi.

PubMed

Skiles, Martha Priedeman; Cunningham, Marc; Inglis, Andrew; Wilkes, Becky; Hatch, Ben; Bock, Ariella; Barden-O'Fallon, Janine

2015-03-01

Previous studies have identified positive relationships between geographic proximity to family planning services and contraceptive use, but have not accounted for the effect of contraceptive supply reliability or the diminishing influence of facility access with increasing distance. Kernel density estimation was used to geographically link Malawi women's use of injectable contraceptives and demand for birth spacing or limiting, as drawn from the 2010 Demographic and Health Survey, with contraceptive logistics data from family planning service delivery points. Linear probability models were run to identify associations between access to injectable services-measured by distance alone and by distance combined with supply reliability-and injectable use and family planning demand among rural and urban populations. Access to services was an important predictor of injectable use. The probability of injectable use among rural women with the most access by both measures was 7‒8 percentage points higher than among rural dwellers with the least access. The probability of wanting to space or limit births among urban women who had access to the most reliable supplies was 18 percentage points higher than among their counterparts with the least access. Product availability in the local service environment plays a critical role in women's demand for and use of contraceptive methods. Use of kernel density estimation in creating facility service environments provides a refined approach to linking women with services and accounts for both distance to facilities and supply reliability. Urban and rural differences should be considered when seeking to improve contraceptive access.

Food Environment and Weight Change: Does Residential Mobility Matter?: The Diabetes Study of Northern California (DISTANCE).

PubMed

Laraia, Barbara A; Downing, Janelle M; Zhang, Y Tara; Dow, William H; Kelly, Maggi; Blanchard, Samuel D; Adler, Nancy; Schillinger, Dean; Moffet, Howard; Warton, E Margaret; Karter, Andrew J

2017-05-01

Associations between neighborhood food environment and adult body mass index (BMI; weight (kg)/height (m)2) derived using cross-sectional or longitudinal random-effects models may be biased due to unmeasured confounding and measurement and methodological limitations. In this study, we assessed the within-individual association between change in food environment from 2006 to 2011 and change in BMI among adults with type 2 diabetes using clinical data from the Kaiser Permanente Diabetes Registry collected from 2007 to 2011. Healthy food environment was measured using the kernel density of healthful food venues. Fixed-effects models with a 1-year-lagged BMI were estimated. Separate models were fitted for persons who moved and those who did not. Sensitivity analysis using different lag times and kernel density bandwidths were tested to establish the consistency of findings. On average, patients lost 1 pound (0.45 kg) for each standard-deviation improvement in their food environment. This relationship held for persons who remained in the same location throughout the 5-year study period but not among persons who moved. Proximity to food venues that promote nutritious foods alone may not translate into clinically meaningful diet-related health changes. Community-level policies for improving the food environment need multifaceted strategies to invoke clinically meaningful change in BMI among adult patients with diabetes. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

PubMed

Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

2017-06-21

We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

PubMed

Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.

Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

PubMed

Cid, Jaime A; von Davier, Alina A

2015-05-01

Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

PubMed Central

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

PubMed

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Antioxidant and antimicrobial activities of bitter and sweet apricot (Prunus armeniaca L.) kernels.

PubMed

Yiğit, D; Yiğit, N; Mavi, A

2009-04-01

The present study describes the in vitro antimicrobial and antioxidant activity of methanol and water extracts of sweet and bitter apricot (Prunus armeniaca L.) kernels. The antioxidant properties of apricot kernels were evaluated by determining radical scavenging power, lipid peroxidation inhibition activity and total phenol content measured with a DPPH test, the thiocyanate method and the Folin method, respectively. In contrast to extracts of the bitter kernels, both the water and methanol extracts of sweet kernels have antioxidant potential. The highest percent inhibition of lipid peroxidation (69%) and total phenolic content (7.9 +/- 0.2 microg/mL) were detected in the methanol extract of sweet kernels (Hasanbey) and in the water extract of the same cultivar, respectively. The antimicrobial activities of the above extracts were also tested against human pathogenic microorganisms using a disc-diffusion method, and the minimal inhibitory concentration (MIC) values of each active extract were determined. The most effective antibacterial activity was observed in the methanol and water extracts of bitter kernels and in the methanol extract of sweet kernels against the Gram-positive bacteria Staphylococcus aureus. Additionally, the methanol extracts of the bitter kernels were very potent against the Gram-negative bacteria Escherichia coli (0.312 mg/mL MIC value). Significant anti-candida activity was also observed with the methanol extract of bitter apricot kernels against Candida albicans, consisting of a 14 mm in diameter of inhibition zone and a 0.625 mg/mL MIC value.

Detecting peanuts inoculated with toxigenic and atoxienic Aspergillus flavus strains with fluorescence hyperspectral imagery

NASA Astrophysics Data System (ADS)

Xing, Fuguo; Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Zhu, Fengle; Brown, Robert L.; Bhatnagar, Deepak; Liu, Yang

2017-05-01

Aflatoxin contamination in peanut products has been an important and long-standing problem around the world. Produced mainly by Aspergillus flavus and Aspergillus parasiticus, aflatoxins are the most toxic and carcinogenic compounds among toxins. This study investigated the application of fluorescence visible near-infrared (VNIR) hyperspectral images to assess the spectral difference between peanut kernels inoculated with toxigenic and atoxigenic inocula of A. flavus and healthy kernels. Peanut kernels were inoculated with NRRL3357, a toxigenic strain of A. flavus, and AF36, an atoxigenic strain of A. flavus, respectively. Fluorescence hyperspectral images under ultraviolet (UV) excitation were recorded on peanut kernels with and without skin. Contaminated kernels exhibited different fluorescence features compared with healthy kernels. For the kernels without skin, the inoculated kernels had a fluorescence peaks shifted to longer wavelengths with lower intensity than healthy kernels. In addition, the fluorescence intensity of peanuts without skin was higher than that of peanuts with skin (10 times). The fluorescence spectra of kernels with skin are significantly different from that of the control group (p<0.001). Furthermore, the fluorescence intensity of the toxigenic, AF3357 peanuts with skin was lower than that of the atoxigenic AF36 group. Discriminate analysis showed that the inoculation group can be separated from the controls with 100% accuracy. However, the two inoculation groups (AF3357 vis AF36) can be separated with only ∼80% accuracy. This study demonstrated the potential of fluorescence hyperspectral imaging techniques for screening of peanut kernels contaminated with A. flavus, which could potentially lead to the production of rapid and non-destructive scanning-based detection technology for the peanut industry.

Salt stress reduces kernel number of corn by inhibiting plasma membrane H+-ATPase activity.

PubMed

Jung, Stephan; Hütsch, Birgit W; Schubert, Sven

2017-04-01

Salt stress affects yield formation of corn (Zea mays L.) at various physiological levels resulting in an overall grain yield decrease. In this study we investigated how salt stress affects kernel development of two corn cultivars (cvs. Pioneer 3906 and Fabregas) at and shortly after pollination. In an earlier study, we found an accumulation of hexoses in the kernel tissue. Therefore, it was hypothesized that hexose uptake into developing endosperm and embryo might be inhibited. Hexoses are transported into the developing endosperm by carriers localized in the plasma membrane (PM). The transport is driven by the pH gradient which is built up by the PM H + -ATPase. It was investigated whether the PM H + -ATPase activity in developing corn kernels was inhibited by salt stress, which would cause a lower pH gradient resulting in impaired hexose import and finally in kernel abortion. Corn grown under control and salt stress conditions was harvested 0 and 2 days after pollination (DAP). Under salt stress sucrose and hexose concentrations in kernel tissue were higher 0 and 2 DAP. Kernel PM H + -ATPase activity was not affected at 0 DAP, but it was reduced at 2 DAP. This is in agreement with the finding, that kernel growth and thus kernel setting was not affected in the salt stress treatment at pollination, but it was reduced 2 days later. It is concluded that inhibition of PM H + -ATPase under salt stress impaired the energization of hexose transporters into the cells, resulting in lower kernel growth and finally in kernel abortion. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Diagnostic accuracy of different display types in detection of recurrent caries under restorations by using CBCT.

PubMed

Baltacıoĝlu, İsmail H; Eren, Hakan; Yavuz, Yasemin; Kamburoğlu, Kıvanç

To assess the in vitro diagnostic ability of CBCT images using seven different display types in the detection of recurrent caries. Our study comprised 128 extracted human premolar and molar teeth. 8 groups each containing 16 teeth were obtained as follows: (1) Black Class I (Occlusal) amalgam filling without caries; (2) Black Class I (Occlusal) composite filling without caries; (3) Black Class II (Proximal) amalgam filling without caries; (4) Black Class II (Proximal) composite filling without caries; (5) Black Class I (Occlusal) amalgam filling with caries; (6) Black Class I (Occlusal) composite filling with caries; (7) Black Class II (Proximal) amalgam filling with caries; and (8) Black Class II (Proximal) composite filling with caries. Teeth were imaged using 100 × 90 mm field of view at three different voxel sizes of a CBCT unit (Planmeca ProMax(®) 3D ProFace™; Planmeca, Helsinki, Finland). CBCT TIFF images were opened and viewed using custom-designed software for computers on different display types. Intra- and interobserver agreements were calculated. The highest area under the receiver operating characteristic curve (Az) values for each image type, observer, reading and restoration were compared using z-tests against Az = 0.5. The significance level was set at p = 0.05. We found poor and moderate agreements. In general, Az values were found when software and medical diagnostic monitor were utilized. For Observer 2, Az values were statistically significantly higher when software was used on medical monitor [p = 0.036, p = 0.015 and p = 0.002, for normal-resolution mode (0.200 mm(3) voxel size), high-resolution mode (0.150 mm(3) voxel size) and low-resolution mode (0.400 mm(3) voxel size), respectively]. No statistically significant differences were found among other display types for all modes (p > 0.05). In general, no difference was found among 3 different voxel sizes (p > 0.05). In general, higher Az values were obtained for composite restorations than for amalgam restorations for all observers. For Observer 1, Az values for composite restorations were statistically significantly higher than those of amalgam restorations for MacBook and iPhone (Apple Inc., Cupertino, CA) assessments (p = 0.002 and p = 0.048, respectively). Higher Az values were observed with medical monitors when used with dedicated software compared to other display types which performed similarly in the diagnosis of recurrent caries under restorations. In addition, observers performed better in detection of recurrent caries when assessing composite restorations than amalgams.

Diagnostic accuracy of different display types in detection of recurrent caries under restorations by using CBCT

PubMed Central

Baltacıoĝlu, İsmail H; Eren, Hakan; Yavuz, Yasemin

2016-01-01

Objectives: To assess the in vitro diagnostic ability of CBCT images using seven different display types in the detection of recurrent caries. Methods: Our study comprised 128 extracted human premolar and molar teeth. 8 groups each containing 16 teeth were obtained as follows: (1) Black Class I (Occlusal) amalgam filling without caries; (2) Black Class I (Occlusal) composite filling without caries; (3) Black Class II (Proximal) amalgam filling without caries; (4) Black Class II (Proximal) composite filling without caries; (5) Black Class I (Occlusal) amalgam filling with caries; (6) Black Class I (Occlusal) composite filling with caries; (7) Black Class II (Proximal) amalgam filling with caries; and (8) Black Class II (Proximal) composite filling with caries. Teeth were imaged using 100 × 90 mm field of view at three different voxel sizes of a CBCT unit (Planmeca ProMax® 3D ProFace™; Planmeca, Helsinki, Finland). CBCT TIFF images were opened and viewed using custom-designed software for computers on different display types. Intra- and interobserver agreements were calculated. The highest area under the receiver operating characteristic curve (Az) values for each image type, observer, reading and restoration were compared using z-tests against Az = 0.5. The significance level was set at p = 0.05. Results: We found poor and moderate agreements. In general, Az values were found when software and medical diagnostic monitor were utilized. For Observer 2, Az values were statistically significantly higher when software was used on medical monitor [p = 0.036, p = 0.015 and p = 0.002, for normal-resolution mode (0.200 mm3 voxel size), high-resolution mode (0.150 mm3 voxel size) and low-resolution mode (0.400 mm3 voxel size), respectively]. No statistically significant differences were found among other display types for all modes (p > 0.05). In general, no difference was found among 3 different voxel sizes (p > 0.05). In general, higher Az values were obtained for composite restorations than for amalgam restorations for all observers. For Observer 1, Az values for composite restorations were statistically significantly higher than those of amalgam restorations for MacBook and iPhone (Apple Inc., Cupertino, CA) assessments (p = 0.002 and p = 0.048, respectively). Conclusions: Higher Az values were observed with medical monitors when used with dedicated software compared to other display types which performed similarly in the diagnosis of recurrent caries under restorations. In addition, observers performed better in detection of recurrent caries when assessing composite restorations than amalgams. PMID:27319604

Three-Dimensional Sensitivity Kernels of Z/H Amplitude Ratios of Surface and Body Waves

NASA Astrophysics Data System (ADS)

Bao, X.; Shen, Y.

2017-12-01

The ellipticity of Rayleigh wave particle motion, or Z/H amplitude ratio, has received increasing attention in inversion for shallow Earth structures. Previous studies of the Z/H ratio assumed one-dimensional (1D) velocity structures beneath the receiver, ignoring the effects of three-dimensional (3D) heterogeneities on wave amplitudes. This simplification may introduce bias in the resulting models. Here we present 3D sensitivity kernels of the Z/H ratio to Vs, Vp, and density perturbations, based on finite-difference modeling of wave propagation in 3D structures and the scattering-integral method. Our full-wave approach overcomes two main issues in previous studies of Rayleigh wave ellipticity: (1) the finite-frequency effects of wave propagation in 3D Earth structures, and (2) isolation of the fundamental mode Rayleigh waves from Rayleigh wave overtones and converted Love waves. In contrast to the 1D depth sensitivity kernels in previous studies, our 3D sensitivity kernels exhibit patterns that vary with azimuths and distances to the receiver. The laterally-summed 3D sensitivity kernels and 1D depth sensitivity kernels, based on the same homogeneous reference model, are nearly identical with small differences that are attributable to the single period of the 1D kernels and a finite period range of the 3D kernels. We further verify the 3D sensitivity kernels by comparing the predictions from the kernels with the measurements from numerical simulations of wave propagation for models with various small-scale perturbations. We also calculate and verify the amplitude kernels for P waves. This study shows that both Rayleigh and body wave Z/H ratios provide vertical and lateral constraints on the structure near the receiver. With seismic arrays, the 3D kernels afford a powerful tool to use the Z/H ratios to obtain accurate and high-resolution Earth models.

Considering causal genes in the genetic dissection of kernel traits in common wheat.

PubMed

Mohler, Volker; Albrecht, Theresa; Castell, Adelheid; Diethelm, Manuela; Schweizer, Günther; Hartl, Lorenz

2016-11-01

Genetic factors controlling thousand-kernel weight (TKW) were characterized for their association with other seed traits, including kernel width, kernel length, ratio of kernel width to kernel length (KW/KL), kernel area, and spike number per m 2 (SN). For this purpose, a genetic map was established utilizing a doubled haploid population derived from a cross between German winter wheat cultivars Pamier and Format. Association studies in a diversity panel of elite cultivars supplemented genetic analysis of kernel traits. In both populations, genomic signatures of 13 candidate genes for TKW and kernel size were analyzed. Major quantitative trait loci (QTL) for TKW were identified on chromosomes 1B, 2A, 2D, and 4D, and their locations coincided with major QTL for kernel size traits, supporting the common belief that TKW is a function of other kernel traits. The QTL on chromosome 2A was associated with TKW candidate gene TaCwi-A1 and the QTL on chromosome 4D was associated with dwarfing gene Rht-D1. A minor QTL for TKW on chromosome 6B coincided with TaGW2-6B. The QTL for kernel dimensions that did not affect TKW were detected on eight chromosomes. A major QTL for KW/KL located at the distal tip of chromosome arm 5AS is being reported for the first time. TaSus1-7A and TaSAP-A1, closely linked to each other on chromosome 7A, could be related to a minor QTL for KW/KL. Genetic analysis of SN confirmed its negative correlation with TKW in this cross. In the diversity panel, TaSus1-7A was associated with TKW. Compared to the Pamier/Format bi-parental population where TaCwi-A1a was associated with higher TKW, the same allele reduced grain yield in the diversity panel, suggesting opposite effects of TaCwi-A1 on these two traits.

Effect of Fungal Colonization of Wheat Grains with Fusarium spp. on Food Choice, Weight Gain and Mortality of Meal Beetle Larvae (Tenebrio molitor)

PubMed Central

Guo, Zhiqing; Döll, Katharina; Dastjerdi, Raana; Karlovsky, Petr; Dehne, Heinz-Wilhelm; Altincicek, Boran

2014-01-01

Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F. proliferatum or F. poae-colonized ones suggesting that T. molitor can tolerate or metabolize those toxins. PMID:24932485

Nutrient database improvement project: Separable components and proximate composition of raw and cooked retail cuts from the beef rib and plate

USDA-ARS?s Scientific Manuscript database

Beef nutrition is very important to the worldwide beef industry and its consumers. The objective of this study was to analyze nutrient composition of eight beef rib and plate cuts to update the nutrient data in the USDA National Nutrient Database for Standard Reference (SR). Seventy-two carcasses ...

Coronary Stent Artifact Reduction with an Edge-Enhancing Reconstruction Kernel - A Prospective Cross-Sectional Study with 256-Slice CT.

PubMed

Tan, Stéphanie; Soulez, Gilles; Diez Martinez, Patricia; Larrivée, Sandra; Stevens, Louis-Mathieu; Goussard, Yves; Mansour, Samer; Chartrand-Lefebvre, Carl

2016-01-01

Metallic artifacts can result in an artificial thickening of the coronary stent wall which can significantly impair computed tomography (CT) imaging in patients with coronary stents. The objective of this study is to assess in vivo visualization of coronary stent wall and lumen with an edge-enhancing CT reconstruction kernel, as compared to a standard kernel. This is a prospective cross-sectional study involving the assessment of 71 coronary stents (24 patients), with blinded observers. After 256-slice CT angiography, image reconstruction was done with medium-smooth and edge-enhancing kernels. Stent wall thickness was measured with both orthogonal and circumference methods, averaging thickness from diameter and circumference measurements, respectively. Image quality was assessed quantitatively using objective parameters (noise, signal to noise (SNR) and contrast to noise (CNR) ratios), as well as visually using a 5-point Likert scale. Stent wall thickness was decreased with the edge-enhancing kernel in comparison to the standard kernel, either with the orthogonal (0.97 ± 0.02 versus 1.09 ± 0.03 mm, respectively; p<0.001) or the circumference method (1.13 ± 0.02 versus 1.21 ± 0.02 mm, respectively; p = 0.001). The edge-enhancing kernel generated less overestimation from nominal thickness compared to the standard kernel, both with the orthogonal (0.89 ± 0.19 versus 1.00 ± 0.26 mm, respectively; p<0.001) and the circumference (1.06 ± 0.26 versus 1.13 ± 0.31 mm, respectively; p = 0.005) methods. The edge-enhancing kernel was associated with lower SNR and CNR, as well as higher background noise (all p < 0.001), in comparison to the medium-smooth kernel. Stent visual scores were higher with the edge-enhancing kernel (p<0.001). In vivo 256-slice CT assessment of coronary stents shows that the edge-enhancing CT reconstruction kernel generates thinner stent walls, less overestimation from nominal thickness, and better image quality scores than the standard kernel.

The effect of heat treatment on phenolic compounds and fatty acid composition of Brazilian nut and hazelnut.

PubMed

Özcan, Mehmet Musa; Juhaimi, Fahad Al; Uslu, Nurhan

2018-01-01

Brazilian peanut oil content increased with oven heating (65.08%) and decreased with microwave heating process (61.00%). While the phenolic content of untreated Brazilian nut was the highest of 68.97 mg GAE/100 g. Hazelnut (Sivri) contained the highest antioxidant activity (86.52%, untreated). Results reflected significantly differences between the antioxidant effect and total phenol contents of Brazilian nut and hazelnut (Sivri) kernels heated in the oven and microwave. Microwave heating caused a decrease in antioxidant activity of hazelnut. Gallic acid, 3,4-dihydroxybenzoic acid and (+)- and catechin were the main phenolic compounds of raw Brazilian nut with the value of 5.33, 4.33 and 4.88 mg/100 g, respectively, while the dominant phenolics of raw hazelnut (Sivri) kernels were gallic acid (4.81 mg/100 g), 3,4-dihydroxybenzoic acid (4.61 mg/100 g), (+)-catechin (6.96 mg/100 g) and 1,2-dihydroxybenzene (4.14 mg/100 g). Both conventional and microwave heating caused minor reduction in phenolic compounds. The main fatty acids of Brazilian nut oil were linoleic (44.39-48.18%), oleic (27.74-31.74%), palmitic (13.09-13.70%) and stearic (8.20-8.91%) acids, while the dominant fatty acids of hazelnut (Sivri) oil were oleic acid (80.84%), respectively. The heating process caused noticeable change in fatty acid compositions of both nut oils.

Renal stone characterization using high resolution imaging mode on a photon counting detector CT system

NASA Astrophysics Data System (ADS)

Ferrero, A.; Gutjahr, R.; Henning, A.; Kappler, S.; Halaweish, A.; Abdurakhimova, D.; Peterson, Z.; Montoya, J.; Leng, S.; McCollough, C.

2017-03-01

In addition to the standard-resolution (SR) acquisition mode, a high-resolution (HR) mode is available on a research photon-counting-detector (PCD) whole-body CT system. In the HR mode each detector consists of a 2x2 array of 0.225 mm x 0.225 mm subpixel elements. This is in contrast to the SR mode that consists of a 4x4 array of the same subelements, and results in 0.25 mm isotropic resolution at iso-center for the HR mode. In this study, we quantified ex vivo the capabilities of the HR mode to characterize renal stones in terms of morphology and mineral composition. Forty pure stones - 10 uric acid (UA), 10 cystine (CYS), 10 calcium oxalate monohydrate (COM) and 10 apatite (APA) - and 14 mixed stones were placed in a 20 cm water phantom and scanned in HR mode, at radiation dose matched to that of routine dual-energy stone exams. Data from micro CT provided a reference for the quantification of morphology and mineral composition of the mixed stones. The area under the ROC curve was 1.0 for discriminating UA from CYS, 0.89 for CYS vs COM and 0.84 for COM vs APA. The root mean square error (RMSE) of the percent UA in mixed stones was 11.0% with a medium-sharp kernel and 15.6% with the sharpest kernel. The HR showed qualitatively accurate characterization of stone morphology relative to micro CT.

Renal Stone Characterization using High Resolution Imaging Mode on a Photon Counting Detector CT System.

PubMed

Ferrero, A; Gutjahr, R; Henning, A; Kappler, S; Halaweish, A; Abdurakhimova, D; Peterson, Z; Montoya, J; Leng, S; McCollough, C

2017-03-09

In addition to the standard-resolution (SR) acquisition mode, a high-resolution (HR) mode is available on a research photon-counting-detector (PCD) whole-body CT system. In the HR mode each detector consists of a 2x2 array of 0.225 mm × 0.225 mm subpixel elements. This is in contrast to the SR mode that consists of a 4x4 array of the same sub-elements, and results in 0.25 mm isotropic resolution at iso-center for the HR mode. In this study, we quantified ex vivo the capabilities of the HR mode to characterize renal stones in terms of morphology and mineral composition. Forty pure stones - 10 uric acid (UA), 10 cystine (CYS), 10 calcium oxalate monohydrate (COM) and 10 apatite (APA) - and 14 mixed stones were placed in a 20 cm water phantom and scanned in HR mode, at radiation dose matched to that of routine dual-energy stone exams. Data from micro CT provided a reference for the quantification of morphology and mineral composition of the mixed stones. The area under the ROC curve was 1.0 for discriminating UA from CYS, 0.89 for CYS vs COM and 0.84 for COM vs APA. The root mean square error (RMSE) of the percent UA in mixed stones was 11.0% with a medium-sharp kernel and 15.6% with the sharpest kernel. The HR showed qualitatively accurate characterization of stone morphology relative to micro CT.

Characterization of groups using composite kernels and multi-source fMRI analysis data: application to schizophrenia

PubMed Central

Castro, Eduardo; Martínez-Ramón, Manel; Pearlson, Godfrey; Sui, Jing; Calhoun, Vince D.

2011-01-01

Pattern classification of brain imaging data can enable the automatic detection of differences in cognitive processes of specific groups of interest. Furthermore, it can also give neuroanatomical information related to the regions of the brain that are most relevant to detect these differences by means of feature selection procedures, which are also well-suited to deal with the high dimensionality of brain imaging data. This work proposes the application of recursive feature elimination using a machine learning algorithm based on composite kernels to the classification of healthy controls and patients with schizophrenia. This framework, which evaluates nonlinear relationships between voxels, analyzes whole-brain fMRI data from an auditory task experiment that is segmented into anatomical regions and recursively eliminates the uninformative ones based on their relevance estimates, thus yielding the set of most discriminative brain areas for group classification. The collected data was processed using two analysis methods: the general linear model (GLM) and independent component analysis (ICA). GLM spatial maps as well as ICA temporal lobe and default mode component maps were then input to the classifier. A mean classification accuracy of up to 95% estimated with a leave-two-out cross-validation procedure was achieved by doing multi-source data classification. In addition, it is shown that the classification accuracy rate obtained by using multi-source data surpasses that reached by using single-source data, hence showing that this algorithm takes advantage of the complimentary nature of GLM and ICA. PMID:21723948

Temporal Effects on Internal Fluorescence Emissions Associated with Aflatoxin Contamination from Corn Kernel Cross-Sections Inoculated with Toxigenic and Atoxigenic Aspergillus flavus.

PubMed

Hruska, Zuzana; Yao, Haibo; Kincaid, Russell; Brown, Robert L; Bhatnagar, Deepak; Cleveland, Thomas E

2017-01-01

Non-invasive, easy to use and cost-effective technology offers a valuable alternative for rapid detection of carcinogenic fungal metabolites, namely aflatoxins, in commodities. One relatively recent development in this area is the use of spectral technology. Fluorescence hyperspectral imaging, in particular, offers a potential rapid and non-invasive method for detecting the presence of aflatoxins in maize infected with the toxigenic fungus Aspergillus flavus . Earlier studies have shown that whole maize kernels contaminated with aflatoxins exhibit different spectral signatures from uncontaminated kernels based on the external fluorescence emission of the whole kernels. Here, the effect of time on the internal fluorescence spectral emissions from cross-sections of kernels infected with toxigenic and atoxigenic A. flavus , were examined in order to elucidate the interaction between the fluorescence signals emitted by some aflatoxin contaminated maize kernels and the fungal invasion resulting in the production of aflatoxins. First, the difference in internal fluorescence emissions between cross-sections of kernels incubated in toxigenic and atoxigenic inoculum was assessed. Kernels were inoculated with each strain for 5, 7, and 9 days before cross-sectioning and imaging. There were 270 kernels (540 halves) imaged, including controls. Second, in a different set of kernels (15 kernels/group; 135 total), the germ of each kernel was separated from the endosperm to determine the major areas of aflatoxin accumulation and progression over nine growth days. Kernels were inoculated with toxigenic and atoxigenic fungal strains for 5, 7, and 9 days before the endosperm and germ were separated, followed by fluorescence hyperspectral imaging and chemical aflatoxin determination. A marked difference in fluorescence intensity was shown between the toxigenic and atoxigenic strains on day nine post-inoculation, which may be a useful indicator of the location of aflatoxin contamination. This finding suggests that both, the fluorescence peak shift and intensity as well as timing, may be essential in distinguishing toxigenic and atoxigenic fungi based on spectral features. Results also reveal a possible preferential difference in the internal colonization of maize kernels between the toxigenic and atoxigenic strains of A. flavus suggesting a potential window for differentiating the strains based on fluorescence spectra at specific time points.

Temporal Effects on Internal Fluorescence Emissions Associated with Aflatoxin Contamination from Corn Kernel Cross-Sections Inoculated with Toxigenic and Atoxigenic Aspergillus flavus

PubMed Central

Hruska, Zuzana; Yao, Haibo; Kincaid, Russell; Brown, Robert L.; Bhatnagar, Deepak; Cleveland, Thomas E.

2017-01-01

Non-invasive, easy to use and cost-effective technology offers a valuable alternative for rapid detection of carcinogenic fungal metabolites, namely aflatoxins, in commodities. One relatively recent development in this area is the use of spectral technology. Fluorescence hyperspectral imaging, in particular, offers a potential rapid and non-invasive method for detecting the presence of aflatoxins in maize infected with the toxigenic fungus Aspergillus flavus. Earlier studies have shown that whole maize kernels contaminated with aflatoxins exhibit different spectral signatures from uncontaminated kernels based on the external fluorescence emission of the whole kernels. Here, the effect of time on the internal fluorescence spectral emissions from cross-sections of kernels infected with toxigenic and atoxigenic A. flavus, were examined in order to elucidate the interaction between the fluorescence signals emitted by some aflatoxin contaminated maize kernels and the fungal invasion resulting in the production of aflatoxins. First, the difference in internal fluorescence emissions between cross-sections of kernels incubated in toxigenic and atoxigenic inoculum was assessed. Kernels were inoculated with each strain for 5, 7, and 9 days before cross-sectioning and imaging. There were 270 kernels (540 halves) imaged, including controls. Second, in a different set of kernels (15 kernels/group; 135 total), the germ of each kernel was separated from the endosperm to determine the major areas of aflatoxin accumulation and progression over nine growth days. Kernels were inoculated with toxigenic and atoxigenic fungal strains for 5, 7, and 9 days before the endosperm and germ were separated, followed by fluorescence hyperspectral imaging and chemical aflatoxin determination. A marked difference in fluorescence intensity was shown between the toxigenic and atoxigenic strains on day nine post-inoculation, which may be a useful indicator of the location of aflatoxin contamination. This finding suggests that both, the fluorescence peak shift and intensity as well as timing, may be essential in distinguishing toxigenic and atoxigenic fungi based on spectral features. Results also reveal a possible preferential difference in the internal colonization of maize kernels between the toxigenic and atoxigenic strains of A. flavus suggesting a potential window for differentiating the strains based on fluorescence spectra at specific time points. PMID:28966606

Direct restoration of endodontically treated maxillary central incisors: post or no post at all?

PubMed

von Stein-Lausnitz, Manja; Bruhnke, M; Rosentritt, M; Sterzenbach, G; Bitter, K; Frankenberger, R; Naumann, M

2018-04-30

The aim of this ex-vivo study was to evaluate the impact of cavity size and glass-fiber post (GFP) placement on the load capability of endodontically treated maxillary incisors directly restored with resin composite. Ninety-six extracted human maxillary central incisors were endodontically treated and distributed to four groups (n = 24): access cavity (A), access cavity and uni-proximal class III cavity (U), access cavity and bi-proximal class III cavity (B), and decoronated tooth (D). Specimens were restored with resin composite, and 12 specimen of each group received an adhesively placed glass-fiber post (P). Prior to linear loading, specimens were exposed to thermo-mechanical loading (TCML). Statistical analysis was performed using log-rank test after TCML, Kruskall-Wallis and Mann-Whitney U test to compare load capabilities (F max) . Significantly more failures occurred in group D for specimens without GFP during TCML (p = 0.001). F max (mean (SD) in N was (A) 513 (124), (AP) 554 (201), (U) 438 (171), (UP) 537 (232) (B) 483 (219), (BP) 536 (281), D 143 (181), and DP 500 (331), and differed significantly among groups (p = 0.003). Pair-wise comparison revealed lower F max values for group D compared to all other groups (p < 0.034) except group DP. Endodontically treated maxillary central incisors with cavity sizes up to bi-proximal class III may be successfully directly restored with resin composite. Post placement shows no additional effect except for decoronated endodontically treated incisors. Endodontically treated incisors with access cavities to class III cavities can be successfully restored with resin composite. Post placement for decoronated ETT is recommended.

Muscle strength in patients with acromegaly at diagnosis and during long-term follow-up.

PubMed

Füchtbauer, Laila; Olsson, Daniel S; Bengtsson, Bengt-Åke; Norrman, Lise-Lott; Sunnerhagen, Katharina S; Johannsson, Gudmundur

2017-08-01

Patients with acromegaly have decreased body fat (BF) and increased extracellular water (ECW) and muscle mass. Although there is a lack of systematic studies on muscle function, it is believed that patients with acromegaly may suffer from proximal muscle weakness despite their increased muscle mass. We studied body composition and muscle function in untreated acromegaly and after biochemical remission. Prospective observational study. Patients with acromegaly underwent measurements of muscle strength (dynamometers) and body composition (four-compartment model) at diagnosis ( n  = 48), 1 year after surgery ( n  = 29) and after long-term follow-up (median 11 years) ( n  = 24). Results were compared to healthy subjects. Untreated patients had increased body cell mass (113 ± 9% of predicted) and ECW (110 ± 20%) and decreased BF (67 ± 7.6%). At one-year follow-up, serum concentration of IGF-I was reduced and body composition had normalized. At baseline, isometric muscle strength in knee flexors and extensors was normal and concentric strength was modestly increased whereas grip strength and endurance was reduced. After one year, muscle strength was normal in both patients with still active disease and patients in remission. At long-term follow-up, all patients were in remission. Most muscle function tests remained normal, but isometric flexion and the fatigue index were increased to 153 ± 42% and 139 ± 28% of predicted values, respectively. Patients with untreated acromegaly had increased body cell mass and normal or modestly increased proximal muscle strength, whereas their grip strength was reduced. After biochemical improvement and remission, body composition was normalized, hand grip strength was increased, whereas proximal muscle fatigue increased. © 2017 European Society of Endocrinology.

Agricultural factors affecting Fusarium communities in wheat kernels.

PubMed

Karlsson, Ida; Friberg, Hanna; Kolseth, Anna-Karin; Steinberg, Christian; Persson, Paula

2017-07-03

Fusarium head blight (FHB) is a devastating disease of cereals caused by Fusarium fungi. The disease is of great economic importance especially owing to reduced grain quality due to contamination by a range of mycotoxins produced by Fusarium. Disease control and prediction is difficult because of the many Fusarium species associated with FHB. Different species may respond differently to control methods and can have both competitive and synergistic interactions. Therefore, it is important to understand how agricultural practices affect Fusarium at the community level. Lower levels of Fusarium mycotoxin contamination of organically produced cereals compared with conventionally produced have been reported, but the causes of these differences are not well understood. The aim of our study was to investigate the effect of agricultural factors on Fusarium abundance and community composition in different cropping systems. Winter wheat kernels were collected from 18 organically and conventionally cultivated fields in Sweden, paired based on their geographical distance and the wheat cultivar grown. We characterised the Fusarium community in harvested wheat kernels using 454 sequencing of translation elongation factor 1-α amplicons. In addition, we quantified Fusarium spp. using real-time PCR to reveal differences in biomass between fields. We identified 12 Fusarium operational taxonomic units (OTUs) with a median of 4.5 OTUs per field. Fusarium graminearum was the most abundant species, while F. avenaceum had the highest occurrence. The abundance of Fusarium spp. ranged two orders of magnitude between fields. Two pairs of Fusarium species co-occurred between fields: F. poae with F. tricinctum and F. culmorum with F. sporotrichoides. We could not detect any difference in Fusarium communities between the organic and conventional systems. However, agricultural intensity, measured as the number of pesticide applications and the amount of nitrogen fertiliser applied, had an impact on Fusarium communities, specifically increasing the abundance of F. tricinctum. There were geographical differences in the Fusarium community composition where F. graminearum was more abundant in the western part of Sweden. The application of amplicon sequencing provided a comprehensive view of the Fusarium community in cereals. This gives us better opportunities to understand the ecology of Fusarium spp., which is important in order to limit FHB and mycotoxin contamination in cereals.

Using the Intel Math Kernel Library on Peregrine | High-Performance

Science.gov Websites

Computing | NREL the Intel Math Kernel Library on Peregrine Using the Intel Math Kernel Library on Peregrine Learn how to use the Intel Math Kernel Library (MKL) with Peregrine system software. MKL architectures. Core math functions in MKL include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier

21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

Code of Federal Regulations, 2014 CFR

2014-04-01

... the Act, are as follows: Common name Botanical name of plant source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed Cydonia oblonga Miller. [42 FR 14640, Mar...

7 CFR 51.2954 - Tolerances for grade defects.

Code of Federal Regulations, 2010 CFR

2010-01-01

... chart. Tolerances for Grade Defects Grade External (shell) defects Internal (kernel) defects Color of kernel U.S. No. 1. 10 pct, by count for splits. 5 pct. by count, for other shell defects, including not... tolerance to reduce the required 70 pct of “light amber” kernels or the required 40 pct of “light” kernels...

7 CFR 51.2284 - Size classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

...: “Halves”, “Pieces and Halves”, “Pieces” or “Small Pieces”. The size of portions of kernels in the lot... consists of 85 percent or more, by weight, half kernels, and the remainder three-fourths half kernels. (See § 51.2285.) (b) Pieces and halves. Lot consists of 20 percent or more, by weight, half kernels, and the...

Measurements of oleic acid among individual kernels harvested from test plots of purified runner and spanish high oleic seed

USDA-ARS?s Scientific Manuscript database

Normal oleic peanuts are often found within commercial lots of high oleic peanuts when sampling among individual kernels. Kernels not meeting high oleic threshold could be true contamination with normal oleic peanuts introduced via poor handling, or kernels not meeting threshold could be immature a...

THERMOS. 30-Group ENDF/B Scattered Kernels

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

McCrosson, F.J.; Finch, D.R.

1973-12-01

These data are 30-group THERMOS thermal scattering kernels for P0 to P5 Legendre orders for every temperature of every material from s(alpha,beta) data stored in the ENDF/B library. These scattering kernels were generated using the FLANGE2 computer code. To test the kernels, the integral properties of each set of kernels were determined by a precision integration of the diffusion length equation and compared to experimental measurements of these properties. In general, the agreement was very good. Details of the methods used and results obtained are contained in the reference. The scattering kernels are organized into a two volume magnetic tapemore » library from which they may be retrieved easily for use in any 30-group THERMOS library.« less

A study of bone marrow and subcutaneous fatty acid composition in subjects of varying bone mineral density.

PubMed

Griffith, James F; Yeung, David K W; Ahuja, Anil T; Choy, Carol W Y; Mei, Wong Yin; Lam, Sherlock S L; Lam, T P; Chen, Zhen-Yu; Leung, Ping C

2009-06-01

Osteoporosis is associated with an increase in marrow fat. Fats, particularly polyunsaturated fats, either in co-cultures or diet, have been shown to significantly influence bone remodeling. Whether the increase in marrow fat seen in osteoporosis is also associated with a change in fatty acid composition is not known. This study was undertaken to investigate the fatty acid composition in subjects of varying bone mineral density (BMD). Samples of marrow fat and subcutaneous fat from 126 subjects (98 females, 34 males, mean age 69.7+/-10.5 years) undergoing orthopedic surgery were analyzed for fatty acid composition by gas chromatography. These results were correlated with BMD assessed by DXA. A total of 22 fatty acids were identified in marrow and subcutaneous fat. Significant differences in fatty acid composition existed between marrow and subcutaneous fat as well as between marrow fat samples obtained from the proximal femur and proximal tibia. Other than cis-7-hexadecenoic acid [C16:1 (n=9)] and docosanoic acid [C22:0], no difference in marrow fatty acid composition was evident between subject groups of varying BMD (normal, low bone mass, and osteoporosis). In conclusion, there exists a wide range of individual fatty acids in marrow fat. Marrow fatty acid composition differs from that of subcutaneous fat and varies between predominantly erythropoetic and fatty marrow sites. Other than cis-7-hexadecenoic acid [C16:1 (n=9)] and docosanoic acid [C22:0], no difference in marrow fatty acid composition was evident between subjects of varying BMD.

Regional oesophageal sensitivity to acid and weakly acidic reflux in patients with non-erosive reflux disease.

PubMed

Emerenziani, S; Ribolsi, M; Sifrim, D; Blondeau, K; Cicala, M

2009-03-01

The mechanisms underlying symptoms in non-erosive reflux disease (NERD) remain to be elucidated. Non-erosive reflux disease patients appear to be more sensitive to intraluminal stimula than erosive patients, the proximal oesophagus being the most sensitive. In order to assess regional oesophageal changes in reflux acidity and sensitivity to reflux, according either to the acidity or the composition of the refluxate, combined multiple pH and multiple pH-impedance (pH-MII) was performed in 16 NERD patients. According to multiple pH-metry, 29% and 12% of reflux events reached the middle and proximal oesophagus respectively, and 35% and 19% according to conventional pH-MII (P < 0.05). The per-individual analysis confirmed the difference between the two techniques. According to combined distal and proximal pH-MII, approximately 30% of distal acid reflux became weakly acidic at the proximal oesophagus. In all patients, the frequency of symptomatic refluxes, both acid and weakly acidic, was significantly higher at the proximal, compared with distal oesophagus (25 +/- 8%vs 11 +/- 2% for acid reflux and 27 +/- 8%vs 8 +/- 2% for weakly acidic reflux; P < 0.05). Compared with multiple pH-metry, pH-MII shows a higher sensitivity in the detection of proximal reflux. As approximately 30% of acid reflux becomes weakly acidic along the oesophageal body, to better characterize proximal reflux, in clinical practice, combined proximal pH-impedance monitoring should be used. In NERD patients, the proximal oesophagus seems to be more sensitive to both acid and weakly acidic reflux.

Virgin coconut oil maintains redox status and improves glycemic conditions in high fructose fed rats.

PubMed

Narayanankutty, Arunaksharan; Mukesh, Reshma K; Ayoob, Shabna K; Ramavarma, Smitha K; Suseela, Indu M; Manalil, Jeksy J; Kuzhivelil, Balu T; Raghavamenon, Achuthan C

2016-01-01

Virgin Coconut Oil (VCO), extracted from fresh coconut kernel possess similar fatty acid composition to that of Copra Oil (CO), a product of dried kernel. Although CO forms the predominant dietary constituent in south India, VCO is being promoted for healthy life due to its constituent antioxidant molecules. High fructose containing CO is an established model for insulin resistance and steatohepatitis in rodents. In this study, replacement of CO with VCO in high fructose diet markedly improved the glucose metabolism and dyslipidemia. The animals fed VCO diet had only 17 % increase in blood glucose level compared to CO fed animals (46 %). Increased level of GSH and antioxidant enzyme activities in VCO fed rats indicate improved hepatic redox status. Reduced lipid peroxidation and carbonyl adducts in VCO fed rats well corroborate with the histopathological findings that hepatic damage and steatosis were comparatively reduced than the CO fed animals. These results suggest that VCO could be an efficient nutraceutical in preventing the development of diet induced insulin resistance and associated complications possibly through its antioxidant efficacy.

Phenolic and triterpenoid composition and inhibition of α-amylase of pistachio kernels (Pistacia vera L.) as affected by rootstock and irrigation treatment.

PubMed

Noguera-Artiaga, Luis; Pérez-López, David; Burgos-Hernández, Armando; Wojdyło, Aneta; Carbonell-Barrachina, Ángel A

2018-09-30

The current water scarcity forces farmers to adopt new irrigation strategies to save water without jeopardizing the fruit yield and quality. In this study, the influence of 3 regulated deficit irrigation (RDI) treatments and 3 rootstocks on the functional quality of pistachios were studied. The functional parameters studied included, polyphenols, triterpenoids, and inhibition of α-amylase. The results showed that P. terebinthus and P. atlantica rootstocks led to pistachio kernels with higher contents of polyphenols and triterpenoids (mainly betulinic acid with 111 and 102 µg g -1 , respectively) than pistachios obtained using P. integerrima rootstock (81 µg g -1 ). On the other hand, the use of moderate RDI (T1 treatment) increased the total content of polyphenols (∼10%), quercetin-O-galloyl-hexoside (∼15%), keampferol-3-O-glucoside (∼19%), and polymeric procyanidins (∼20%), as compared to the control trees, resulting in pistachios with a better functional profile, lower economic cost and with a lesser environmental impact. Copyright © 2018 Elsevier Ltd. All rights reserved.

Production of sn-1,3-distearoyl-2-oleoyl-glycerol-rich fats from mango kernel fat by selective fractionation using 2-methylpentane based isohexane.

PubMed

Jin, Jun; Zheng, Liyou; Mwinyi Pembe, Warda; Zhang, Jinfang; Xie, Dan; Wang, Xiaosan; Huang, Jianhua; Jin, Qingzhe; Wang, Xingguo

2017-11-01

High-purity isohexane containing 88.12% 2-methylpentane, which has a higher polarity than industrial hexane, was selected to selectively fractionate mango kernel fat to produce 1,3-distearoyl-2-oleoyl-glycerol (SOS)-rich fat. The three-stage fractionation process was optimized by considering the stearin yield and its SOS content to obtain a third stearin (TS). This fat contained a high percentage of SOS (69.2%) with only 0.8% diacylglycerol. Mass spectra and sn-2 fatty acid analyses further revealed that the TS was mainly composed of symmetrical monounsaturated triacylglycerols. Compared with cocoa butter (CB), the unique composition of the TS improved its thermal properties (35.6% and 0% solid fat content at 35°C for the TS and CB, respectively). In particular, tempered binary fat blends, which were composed of 20-50% TS and 50-80% CB, showed acceptable compatibility at 20-28°C. The TS could be utilized by chocolate manufacturers to make products suitable for sale and consumption in tropical conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Preparation of UC0.07-0.10N0.90-0.93 spheres for TRISO coated fuel particles

NASA Astrophysics Data System (ADS)

Hunt, R. D.; Silva, C. M.; Lindemer, T. B.; Johnson, J. A.; Collins, J. L.

2014-05-01

The US Department of Energy is considering a new nuclear fuel that would be less susceptible to ruptures during a loss-of-coolant accident. The fuel would consist of tristructural isotropic coated particles with dense uranium nitride (UN) kernels with diameters of 650 or 800 μm. The objectives of this effort are to make uranium oxide microspheres with adequately dispersed carbon nanoparticles and to convert these microspheres into UN spheres, which could be then sintered into kernels. Recent improvements to the internal gelation process were successfully applied to the production of uranium gel spheres with different concentrations of carbon black. After the spheres were washed and dried, a simple two-step heat profile was used to produce porous microspheres with a chemical composition of UC0.07-0.10N0.90-0.93. The first step involved heating the microspheres to 2023 K in a vacuum, and in the second step, the microspheres were held at 1873 K for 6 h in flowing nitrogen.

Support vector machine with a Pearson VII function kernel for discriminating halophilic and non-halophilic proteins.

PubMed

Zhang, Guangya; Ge, Huihua

2013-10-01

Understanding of proteins adaptive to hypersaline environment and identifying them is a challenging task and would help to design stable proteins. Here, we have systematically analyzed the normalized amino acid compositions of 2121 halophilic and 2400 non-halophilic proteins. The results showed that halophilic protein contained more Asp at the expense of Lys, Ile, Cys and Met, fewer small and hydrophobic residues, and showed a large excess of acidic over basic amino acids. Then, we introduce a support vector machine method to discriminate the halophilic and non-halophilic proteins, by using a novel Pearson VII universal function based kernel. In the three validation check methods, it achieved an overall accuracy of 97.7%, 91.7% and 86.9% and outperformed other machine learning algorithms. We also address the influence of protein size on prediction accuracy and found the worse performance for small size proteins might be some significant residues (Cys and Lys) were missing in the proteins. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Characteristics and Composition of African Oil Bean Seed (Pentaclethra macrophylla Benth)

NASA Astrophysics Data System (ADS)

Ikhuoria, Esther U.; Aiwonegbe, Anthony E.; Okoli, Peace; Idu, Macdonald

The African oil bean (Pentaclethra macrophylla) seed was analyzed for its proximate composition. The seed oil was also analyzed for mineral content and physicochemical characteristics. Proximate analysis revealed that the percentage crude protein, crude fibre, moisture and carbohydrate were 9.31, 21.66, 39.05 and 38.95%, respectively. The percentage oil content was 47.90% while the ash content was 3.27%. Results of minerals analysis showed that calcium had the highest concentration of all the elements analyzed and were found to be of the order: Ca > Mg > Pb > Fe > Mn > P > Cu. The low iodine value of the seed oil showed that it can be classified as non-drying oil and thus not suitable for paint and polish production. However, the low acid and free fatty acid values suggest its utilization as edible oil.

7 CFR 810.2003 - Basis of determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Basis of determination. Each determination of heat-damaged kernels, damaged kernels, material other than... shrunken and broken kernels. Other determinations not specifically provided for under the general...

DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

PubMed

Ma, Wenxiu; Yang, Lin; Rohs, Remo; Noble, William Stafford

2017-10-01

Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of adjacent base pairs, etc. Several methods have been developed to jointly account for DNA sequence and shape properties in predicting TF binding affinity. However, a limitation of these methods is that they typically require a training set of aligned TF binding sites. We describe a sequence + shape kernel that leverages DNA sequence and shape information to better understand protein-DNA binding preference and affinity. This kernel extends an existing class of k-mer based sequence kernels, based on the recently described di-mismatch kernel. Using three in vitro benchmark datasets, derived from universal protein binding microarrays (uPBMs), genomic context PBMs (gcPBMs) and SELEX-seq data, we demonstrate that incorporating DNA shape information improves our ability to predict protein-DNA binding affinity. In particular, we observe that (i) the k-spectrum + shape model performs better than the classical k-spectrum kernel, particularly for small k values; (ii) the di-mismatch kernel performs better than the k-mer kernel, for larger k; and (iii) the di-mismatch + shape kernel performs better than the di-mismatch kernel for intermediate k values. The software is available at https://bitbucket.org/wenxiu/sequence-shape.git. rohs@usc.edu or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Fine-mapping of qGW4.05, a major QTL for kernel weight and size in maize.

PubMed

Chen, Lin; Li, Yong-xiang; Li, Chunhui; Wu, Xun; Qin, Weiwei; Li, Xin; Jiao, Fuchao; Zhang, Xiaojing; Zhang, Dengfeng; Shi, Yunsu; Song, Yanchun; Li, Yu; Wang, Tianyu

2016-04-12

Kernel weight and size are important components of grain yield in cereals. Although some information is available concerning the map positions of quantitative trait loci (QTL) for kernel weight and size in maize, little is known about the molecular mechanisms of these QTLs. qGW4.05 is a major QTL that is associated with kernel weight and size in maize. We combined linkage analysis and association mapping to fine-map and identify candidate gene(s) at qGW4.05. QTL qGW4.05 was fine-mapped to a 279.6-kb interval in a segregating population derived from a cross of Huangzaosi with LV28. By combining the results of regional association mapping and linkage analysis, we identified GRMZM2G039934 as a candidate gene responsible for qGW4.05. Candidate gene-based association mapping was conducted using a panel of 184 inbred lines with variable kernel weights and kernel sizes. Six polymorphic sites in the gene GRMZM2G039934 were significantly associated with kernel weight and kernel size. The results of linkage analysis and association mapping revealed that GRMZM2G039934 is the most likely candidate gene for qGW4.05. These results will improve our understanding of the genetic architecture and molecular mechanisms underlying kernel development in maize.

Abiotic stress growth conditions induce different responses in kernel iron concentration across genotypically distinct maize inbred varieties

PubMed Central

Kandianis, Catherine B.; Michenfelder, Abigail S.; Simmons, Susan J.; Grusak, Michael A.; Stapleton, Ann E.

2013-01-01

The improvement of grain nutrient profiles for essential minerals and vitamins through breeding strategies is a target important for agricultural regions where nutrient poor crops like maize contribute a large proportion of the daily caloric intake. Kernel iron concentration in maize exhibits a broad range. However, the magnitude of genotype by environment (GxE) effects on this trait reduces the efficacy and predictability of selection programs, particularly when challenged with abiotic stress such as water and nitrogen limitations. Selection has also been limited by an inverse correlation between kernel iron concentration and the yield component of kernel size in target environments. Using 25 maize inbred lines for which extensive genome sequence data is publicly available, we evaluated the response of kernel iron density and kernel mass to water and nitrogen limitation in a managed field stress experiment using a factorial design. To further understand GxE interactions we used partition analysis to characterize response of kernel iron and weight to abiotic stressors among all genotypes, and observed two patterns: one characterized by higher kernel iron concentrations in control over stress conditions, and another with higher kernel iron concentration under drought and combined stress conditions. Breeding efforts for this nutritional trait could exploit these complementary responses through combinations of favorable allelic variation from these already well-characterized genetic stocks. PMID:24363659

Single kernel ionomic profiles are highly heritable indicators of genetic and environmental influences on elemental accumulation in maize grain (Zea mays)

USDA-ARS?s Scientific Manuscript database

The ionome, or elemental profile, of a maize kernel represents at least two distinct ideas. First, the collection of elements within the kernel are food, feed and feedstocks for people, animals and industrial processes. Second, the ionome of the kernel represents a developmental end point that can s...

Detection of aflatoxin B1 (AFB1) in individual maize kernels using short wave infrared (SWIR) hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Short wave infrared hyperspectral imaging (SWIR) (1000-2500 nm) was used to detect aflatoxin B1 (AFB1) in individual maize kernels. A total of 120 kernels of four varieties (or 30 kernels per variety) that had been artificially inoculated with a toxigenic strain of Aspergillus flavus and harvested f...

New durum wheat with soft kernel texture: end-use quality analysis of the Hardness locus in Triticum turgidum ssp. durum

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture dictates U.S. wheat market class. Durum wheat has limited demand and culinary end-uses compared to bread wheat because of its extremely hard kernel texture which precludes conventional milling. ‘Soft Svevo’, a new durum cultivar with soft kernel texture comparable to a soft whit...

Modulation of antioxidant potential in liver of mice by kernel oil of cashew nut (Anacardium occidentale) and its lack of tumour promoting ability in DMBA induced skin papillomagenesis.

PubMed

Singh, Bimala; Kale, R K; Rao, A R

2004-04-01

Cashew nut shell oil has been reported to possess tumour promoting property. Therefore an attempt has been made to study the modulatory effect of cashew nut (Anlacardium occidentale) kernel oil on antioxidant potential in liver of Swiss albino mice and also to see whether it has tumour promoting ability like the shell oil. The animals were treated orally with two doses (50 and 100 microl/animal/day) of kernel oil of cashew nut for 10 days. The kernel oil was found to enhance the specific activities of SOD, catalase, GST, methylglyoxalase I and levels of GSH. These results suggested that cashew nut kernel oil had an ability to increase the antioxidant status of animals. The decreased level of lipid peroxidation supported this possibility. The tumour promoting property of the kernel oil was also examined and found that cashew nut kernel oil did not exhibit any solitary carcinogenic activity.