Global mRNA expression analysis in myosin II deficient strains of Saccharomyces cerevisiae reveals an impairment of cell integrity functions

Directory of Open Access Journals (Sweden)

Rivera-Molina Félix E

2008-01-01

Full Text Available Abstract Background The Saccharomyces cerevisiae MYO1 gene encodes the myosin II heavy chain (Myo1p, a protein required for normal cytokinesis in budding yeast. Myo1p deficiency in yeast (myo1Δ causes a cell separation defect characterized by the formation of attached cells, yet it also causes abnormal budding patterns, formation of enlarged and elongated cells, increased osmotic sensitivity, delocalized chitin deposition, increased chitin synthesis, and hypersensitivity to the chitin synthase III inhibitor Nikkomycin Z. To determine how differential expression of genes is related to these diverse cell wall phenotypes, we analyzed the global mRNA expression profile of myo1Δ strains. Results Global mRNA expression profiles of myo1Δ strains and their corresponding wild type controls were obtained by hybridization to yeast oligonucleotide microarrays. Results for selected genes were confirmed by real time RT-PCR. A total of 547 differentially expressed genes (p ≤ 0.01 were identified with 263 up regulated and 284 down regulated genes in the myo1Δ strains. Gene set enrichment analysis revealed the significant over-representation of genes in the protein biosynthesis and stress response categories. The SLT2/MPK1 gene was up regulated in the microarray, and a myo1Δslt2Δ double mutant was non-viable. Overexpression of ribosomal protein genes RPL30 and RPS31 suppressed the hypersensitivity to Nikkomycin Z and increased the levels of phosphorylated Slt2p in myo1Δ strains. Increased levels of phosphorylated Slt2p were also observed in wild type strains under these conditions. Conclusion Following this analysis of global mRNA expression in yeast myo1Δ strains, we conclude that 547 genes were differentially regulated in myo1Δ strains and that the stress response and protein biosynthesis gene categories were coordinately regulated in this mutant. The SLT2/MPK1 gene was confirmed to be essential for myo1Δ strain viability, supporting that the up

An Improved User Selection Algorithm in Multiuser MIMO Broadcast with Channel Prediction

Science.gov (United States)

Min, Zhi; Ohtsuki, Tomoaki

In multiuser MIMO-BC (Multiple-Input Multiple-Output Broadcasting) systems, user selection is important to achieve multiuser diversity. The optimal user selection algorithm is to try all the combinations of users to find the user group that can achieve the multiuser diversity. Unfortunately, the high calculation cost of the optimal algorithm prevents its implementation. Thus, instead of the optimal algorithm, some suboptimal user selection algorithms were proposed based on semiorthogonality of user channel vectors. The purpose of this paper is to achieve multiuser diversity with a small amount of calculation. For this purpose, we propose a user selection algorithm that can improve the orthogonality of a selected user group. We also apply a channel prediction technique to a MIMO-BC system to get more accurate channel information at the transmitter. Simulation results show that the channel prediction can improve the accuracy of channel information for user selections, and the proposed user selection algorithm achieves higher sum rate capacity than the SUS (Semiorthogonal User Selection) algorithm. Also we discuss the setting of the algorithm threshold. As the result of a discussion on the calculation complexity, which uses the number of complex multiplications as the parameter, the proposed algorithm is shown to have a calculation complexity almost equal to that of the SUS algorithm, and they are much lower than that of the optimal user selection algorithm.

Phage display selects for amylases with improved low pH starch-binding

NARCIS (Netherlands)

Verhaert, RMD; Beekwilder, J; Olsthoorn, R; Quax, WJ; Duin, Jan van

2002-01-01

Directed evolution of secreted industrial enzymes is hampered by the lack of powerful selection techniques. We have explored surface display to select for enzyme variants with improved binding performance on complex polymeric substrates. By a combination of saturation mutagenesis and phage display

Solid Catalyst with Ionic Liquid Layer (SCILL). A concept to improve the selectivity of selective hydrogenations

Energy Technology Data Exchange (ETDEWEB)

Jess, A.; Korth, W. [Bayreuth Univ. (Germany). Chair of Chemical Engineering

2011-07-01

Catalytic hydrogenations are important for refinery processes, petrochemical applications as well as for numerous processes of the fine chemicals industry. In some cases, hydrogenations consist of a sequence of consecutive reactions, and the desired product is the intermediate. An important goal is then a high yield and selectivity to the intermediate, if possible at a high conversion degree. The selectivity to an intermediate primarily depends on the chemical nature of the catalyst, but may also be influenced by diffusion processes. Ionic liquids (ILs) are low melting salts (< 100 C) and represent a promising solvent class. This paper focuses on the concept of a Solid Catalyst with Ionic Liquid Layer (SCILL), where the solid catalyst is coated with a thin IL layer to improve the selectivity. (orig.)

Wind scatterometry with improved ambiguity selection and rain modeling

Science.gov (United States)

Draper, David Willis

Although generally accurate, the quality of SeaWinds on QuikSCAT scatterometer ocean vector winds is compromised by certain natural phenomena and retrieval algorithm limitations. This dissertation addresses three main contributors to scatterometer estimate error: poor ambiguity selection, estimate uncertainty at low wind speeds, and rain corruption. A quality assurance (QA) analysis performed on SeaWinds data suggests that about 5% of SeaWinds data contain ambiguity selection errors and that scatterometer estimation error is correlated with low wind speeds and rain events. Ambiguity selection errors are partly due to the "nudging" step (initialization from outside data). A sophisticated new non-nudging ambiguity selection approach produces generally more consistent wind than the nudging method in moderate wind conditions. The non-nudging method selects 93% of the same ambiguities as the nudged data, validating both techniques, and indicating that ambiguity selection can be accomplished without nudging. Variability at low wind speeds is analyzed using tower-mounted scatterometer data. According to theory, below a threshold wind speed, the wind fails to generate the surface roughness necessary for wind measurement. A simple analysis suggests the existence of the threshold in much of the tower-mounted scatterometer data. However, the backscatter does not "go to zero" beneath the threshold in an uncontrolled environment as theory suggests, but rather has a mean drop and higher variability below the threshold. Rain is the largest weather-related contributor to scatterometer error, affecting approximately 4% to 10% of SeaWinds data. A simple model formed via comparison of co-located TRMM PR and SeaWinds measurements characterizes the average effect of rain on SeaWinds backscatter. The model is generally accurate to within 3 dB over the tropics. The rain/wind backscatter model is used to simultaneously retrieve wind and rain from SeaWinds measurements. The simultaneous

Optimized Policies for Improving Fairness of Location-based Relay Selection

DEFF Research Database (Denmark)

Nielsen, Jimmy Jessen; Olsen, Rasmus Løvenstein; Madsen, Tatiana Kozlova

2013-01-01

For WLAN systems in which relaying is used to improve throughput performance for nodes located at the cell edge, node mobility and information collection delays can have a significant impact on the performance of a relay selection scheme. In this paper we extend our existing Markov Chain modeling...... framework for relay selection to allow for efficient calculation of relay policies given either mean throughput or kth throughput percentile as optimization criterium. In a scenario with static access point, static relay, and a mobile destination node, the kth throughput percentile optimization...

Escape windows to improve the size selectivity in the Baltic cod trawl fishery

DEFF Research Database (Denmark)

Madsen, Niels; Holst, René; Foldager, L.

2002-01-01

A rapid decrease of the stock of Baltic cod (Gadus morhua) has provided the incentive to improve the size selectivity in the trawl fishery. Use of escape windows is permitted in the legislation to give means of improving the size selectivity of cod as an alternative to a traditional standard codend....... The history of the use of escape windows in the Baltic Sea cod fishery is reviewed. The present escape windows do not function optimally. The objective of this new experiment was to compare an improved design of escape window, which is placed in the upper panel, with that of standard codend. Three standard...... of the codend selectivity was formulated to analyse the results and determine the effects of codend type, mesh size and other recorded variables. L50 and SR increased significantly with the mesh size. L50 was significantly increased and SR significantly reduced for a window codend with the same window mesh size...

Magnetically-focusing biochip structures for high-speed active biosensing with improved selectivity

Science.gov (United States)

Yoo, Haneul; Lee, Dong Jun; Kim, Daesan; Park, Juhun; Chen, Xing; Hong, Seunghun

2018-06-01

We report a magnetically-focusing biochip structure enabling a single layered magnetic trap-and-release cycle for biosensors with an improved detection speed and selectivity. Here, magnetic beads functionalized with specific receptor molecules were utilized to trap target molecules in a solution and transport actively to and away from the sensor surfaces to enhance the detection speed and reduce the non-specific bindings, respectively. Using our method, we demonstrated the high speed detection of IL-13 antigens with the improved detection speed by more than an order of magnitude. Furthermore, the release step in our method was found to reduce the non-specific bindings and improve the selectivity and sensitivity of biosensors. This method is a simple but powerful strategy and should open up various applications such as ultra-fast biosensors for point-of-care services.

The use of vector bootstrapping to improve variable selection precision in Lasso models

NARCIS (Netherlands)

Laurin, C.; Boomsma, D.I.; Lubke, G.H.

2016-01-01

The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections.

Genomic selection improves response to selection in resilience by exploiting genotype by environment interactions

Directory of Open Access Journals (Sweden)

Han Mulder

2016-10-01

Full Text Available Genotype by environment interactions (GxE are very common in livestock and hamper genetic improvement. On the other hand, GxE is a source of genetic variation: genetic variation in response to environment, e.g. environmental perturbations such as heat stress or disease. In livestock breeding, there is tendency to ignore GxE because of increased complexity of models for genetic evaluations and lack of accuracy in extreme environments. GxE, however, creates opportunities to increase resilience of animals towards environmental perturbations. The main aim of the paper is to investigate to which extent GxE can be exploited with traditional and genomic selection methods. Furthermore, we investigated the benefit of reaction norm models compared to conventional methods ignoring GxE. The questions were addressed with selection index theory. GxE was modelled according to a linear reaction norm model in which the environmental gradient is the contemporary group mean. Economic values were based on linear and non-linear profit equations.Accuracies of environment-specific (GEBV were highest in intermediate environments and lowest in extreme environments. Reaction norm models had higher accuracies of (GEBV in extreme environments than conventional models ignoring GxE. Genomic selection always resulted in higher response to selection in all environments than sib or progeny testing schemes. The increase in response was with genomic selection between 9% and 140% compared to sib testing and between 11% and 114% compared to progeny testing when the reference population consisted of 1 million animals across all environments. When the aim was to decrease environmental sensitivity, the response in slope of the reaction norm model with genomic selection was between 1.09 and 319 times larger than with sib or progeny testing and in the right direction in contrast to sib and progeny testing that still increased environmental sensitivity. This shows that genomic selection

Improvement of resistance to rust through recurrent selection in pearl millet

Energy Technology Data Exchange (ETDEWEB)

Tapsoba, H. [Univ. of Georgia, Athens, GA (United States); Wilson, J.P.; Hanna, W.W. [Univ. of Georgia Coastal Plain Experimental Station, Tifton, GA (United States)

1997-04-01

Two pearl millet [Pennisetum glaucum (L.) R.Br. = P. typhoides (Burm.) Staff & Hubb., P. americanum (L.) K. Schum.] bulk populations, Tift No. 2 and Tift No. 5, served as base populations for four cycles of recurrent selection against susceptibility to Puccinia substriata Ell. & Barth, var. indica Ramachar & Cumm. A bulk inoculum of the pathogen was used. The objectives were to evaluate the progress achieved regarding overall resistance to the pathogen in the field and resistance to different races of the pathogen, and also to evaluate changes in unselected traits. During selection, the frequency of rust resistant plants continuously increased from about 30% in each base population to more than 85% by the third cycle of selection in both populations. An average increase of about 21 and 18% per cycle was obtained in Tift No. 2 and Tift No. 5, respectively. A continuous increase of the frequency of plants resistant to some races of the pathogen was also obtained. In Tift No. 5, 80% of the plants were resistant to eight races by the third cycle of selection. The accumulation of resistance observed in the seedlings was manifested in the field, both in 1993 and 1994, by a reduction of the final rust severity from the base population to the fourth selection cycle of both populations. This improvement in resistance to the rust pathogen was accompanied by an increase in the frequency of plants resistant to Pyricularia grisea (Cooke) Sacc. only in Tift No. 2. Despite the improvement in the selected character, genetic variability for agronomic traits such as plant height, number of culms/plant, flowering date, and panicle length was successfully maintained within each population. 20 refs., 1 fig., 7 tabs.

Supplier selection based on improved MOGA and its application in nuclear power equipment procurement

International Nuclear Information System (INIS)

Yan Zhaojun; Wang Dezhong; Zhou Lei

2007-01-01

Considering the fact that there are few objective and available methods supporting the supplier selection in nuclear power equipment purchasing process, a supplier selection method based on improved multi-objective genetic algorithm (MOGA) is proposed. The simulation results demonstrate the effectiveness and efficiency of this method for the supplier selection in nuclear power equipment procurement process. (authors)

Could non-grade based selection improve medical student socio-demographic diversity?

DEFF Research Database (Denmark)

O'Neill, Lotte Dyhrberg

2013-01-01

selected with a non-grade-based or ’non-cognitive’ admission program. The two admission groups were compared on seven social indices (doctor parent, ethnic origin, father’s education, mother’s education, parenthood, parents live together, parent on benefit). Result: Selection strategy made no difference...... to the social diversity of admitted medical students. The non-cognitive admission program studied was not a useful initiative for improving medical student diversity nor did it further disadvantaged educationally vulnerable population groups in these cohorts. Discussion: The social heritage and general...

An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO

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Xiaofeng Lv

2018-01-01

Full Text Available Sensor data-based test selection optimization is the basis for designing a test work, which ensures that the system is tested under the constraint of the conventional indexes such as fault detection rate (FDR and fault isolation rate (FIR. From the perspective of equipment maintenance support, the ambiguity isolation has a significant effect on the result of test selection. In this paper, an improved test selection optimization model is proposed by considering the ambiguity degree of fault isolation. In the new model, the fault test dependency matrix is adopted to model the correlation between the system fault and the test group. The objective function of the proposed model is minimizing the test cost with the constraint of FDR and FIR. The improved chaotic discrete particle swarm optimization (PSO algorithm is adopted to solve the improved test selection optimization model. The new test selection optimization model is more consistent with real complicated engineering systems. The experimental result verifies the effectiveness of the proposed method.

Using Improved Entropy-Cloud Model to Select High-Speed Railway Express Freight Train Service Sites

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Wencheng Huang

2017-01-01

Full Text Available High-speed railway (HSR express freight train service sites selection is critical to the development of China’s Third Party Logistics market. In this paper, we formulate an improved entropy-cloud model based approach to solve the HSR express sites selection problem for the first time. The basic data of the indicators, for example, existing railway network conditions, traffic environment, express freight market demand, and policy, will be used as the inputs. We apply improved entropy method to obtain each subindicator’s weight. The cloud model will be used to select and classify each station under evaluation.

Efficient Generation and Selection of Combined Features for Improved Classification

KAUST Repository

Shono, Ahmad N.

2014-05-01

This study contributes a methodology and associated toolkit developed to allow users to experiment with the use of combined features in classification problems. Methods are provided for efficiently generating combined features from an original feature set, for efficiently selecting the most discriminating of these generated combined features, and for efficiently performing a preliminary comparison of the classification results when using the original features exclusively against the results when using the selected combined features. The potential benefit of considering combined features in classification problems is demonstrated by applying the developed methodology and toolkit to three sample data sets where the discovery of combined features containing new discriminating information led to improved classification results.

Selecting Health Care Improvement Projects: A Methodology Integrating Cause-and-Effect Diagram and Analytical Hierarchy Process.

Science.gov (United States)

Testik, Özlem Müge; Shaygan, Amir; Dasdemir, Erdi; Soydan, Guray

It is often vital to identify, prioritize, and select quality improvement projects in a hospital. Yet, a methodology, which utilizes experts' opinions with different points of view, is needed for better decision making. The proposed methodology utilizes the cause-and-effect diagram to identify improvement projects and construct a project hierarchy for a problem. The right improvement projects are then prioritized and selected using a weighting scheme of analytical hierarchy process by aggregating experts' opinions. An approach for collecting data from experts and a graphical display for summarizing the obtained information are also provided. The methodology is implemented for improving a hospital appointment system. The top-ranked 2 major project categories for improvements were identified to be system- and accessibility-related causes (45%) and capacity-related causes (28%), respectively. For each of the major project category, subprojects were then ranked for selecting the improvement needs. The methodology is useful in cases where an aggregate decision based on experts' opinions is expected. Some suggestions for practical implementations are provided.

Rac1 selective activation improves retina ganglion cell survival and regeneration.

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Erika Lorenzetto

Full Text Available In adult mammals, after optic nerve injury, retinal ganglion cells (RGCs do not regenerate their axons and most of them die by apoptosis within a few days. Recently, several strategies that activate neuronal intracellular pathways were proposed to prevent such degenerative processes. The rho-related small GTPase Rac1 is part of a complex, still not fully understood, intracellular signaling network, mediating in neurons many effects, including axon growth and cell survival. However, its role in neuronal survival and regeneration in vivo has not yet been properly investigated. To address this point we intravitreally injected selective cell-penetrating Rac1 mutants after optic nerve crush and studied the effect on RGC survival and axonal regeneration. We injected two well-characterized L61 constitutively active Tat-Rac1 fusion protein mutants, in which a second F37A or Y40C mutation confers selectivity in downstream signaling pathways. Results showed that, 15 days after crush, both mutants were able to improve survival and to prevent dendrite degeneration, while the one harboring the F37A mutation also improved axonal regeneration. The treatment with F37A mutant for one month did not improve the axonal elongation respect to 15 days. Furthermore, we found an increase of Pak1 T212 phosphorylation and ERK1/2 expression in RGCs after F37A treatment, whereas ERK1/2 was more activated in glial cells after Y40C administration. Our data suggest that the selective activation of distinct Rac1-dependent pathways could represent a therapeutic strategy to counteract neuronal degenerative processes in the retina.

Improved targeted immunization strategies based on two rounds of selection

Science.gov (United States)

Xia, Ling-Ling; Song, Yu-Rong; Li, Chan-Chan; Jiang, Guo-Ping

2018-04-01

In the case of high degree targeted immunization where the number of vaccine is limited, when more than one node associated with the same degree meets the requirement of high degree centrality, how can we choose a certain number of nodes from those nodes, so that the number of immunized nodes will not exceed the limit? In this paper, we introduce a new idea derived from the selection process of second-round exam to solve this problem and then propose three improved targeted immunization strategies. In these proposed strategies, the immunized nodes are selected through two rounds of selection, where we increase the quotas of first-round selection according the evaluation criterion of degree centrality and then consider another characteristic parameter of node, such as node's clustering coefficient, betweenness and closeness, to help choose targeted nodes in the second-round selection. To validate the effectiveness of the proposed strategies, we compare them with the degree immunizations including the high degree targeted and the high degree adaptive immunizations using two metrics: the size of the largest connected component of immunized network and the number of infected nodes. Simulation results demonstrate that the proposed strategies based on two rounds of sorting are effective for heterogeneous networks and their immunization effects are better than that of the degree immunizations.

Chitin synthases from Saprolegnia are involved in tip growth and represent a potential target for anti-oomycete drugs.

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Gea Guerriero

Full Text Available Oomycetes represent some of the most devastating plant and animal pathogens. Typical examples are Phytophthora infestans, which causes potato and tomato late blight, and Saprolegnia parasitica, responsible for fish diseases. Despite the economical and environmental importance of oomycete diseases, their control is difficult, particularly in the aquaculture industry. Carbohydrate synthases are vital for hyphal growth and represent interesting targets for tackling the pathogens. The existence of 2 different chitin synthase genes (SmChs1 and SmChs2 in Saprolegnia monoica was demonstrated using bioinformatics and molecular biology approaches. The function of SmCHS2 was unequivocally demonstrated by showing its catalytic activity in vitro after expression in Pichia pastoris. The recombinant SmCHS1 protein did not exhibit any activity in vitro, suggesting that it requires other partners or effectors to be active, or that it is involved in a different process than chitin biosynthesis. Both proteins contained N-terminal Microtubule Interacting and Trafficking domains, which have never been reported in any other known carbohydrate synthases. These domains are involved in protein recycling by endocytosis. Enzyme kinetics revealed that Saprolegnia chitin synthases are competitively inhibited by nikkomycin Z and quantitative PCR showed that their expression is higher in presence of the inhibitor. The use of nikkomycin Z combined with microscopy showed that chitin synthases are active essentially at the hyphal tips, which burst in the presence of the inhibitor, leading to cell death. S. parasitica was more sensitive to nikkomycin Z than S. monoica. In conclusion, chitin synthases with species-specific characteristics are involved in tip growth in Saprolegnia species and chitin is vital for the micro-organisms despite its very low abundance in the cell walls. Chitin is most likely synthesized transiently at the apex of the cells before cellulose, the major

Action video games and improved attentional control: Disentangling selection- and response-based processes.

Science.gov (United States)

Chisholm, Joseph D; Kingstone, Alan

2015-10-01

Research has demonstrated that experience with action video games is associated with improvements in a host of cognitive tasks. Evidence from paradigms that assess aspects of attention has suggested that action video game players (AVGPs) possess greater control over the allocation of attentional resources than do non-video-game players (NVGPs). Using a compound search task that teased apart selection- and response-based processes (Duncan, 1985), we required participants to perform an oculomotor capture task in which they made saccades to a uniquely colored target (selection-based process) and then produced a manual directional response based on information within the target (response-based process). We replicated the finding that AVGPs are less susceptible to attentional distraction and, critically, revealed that AVGPs outperform NVGPs on both selection-based and response-based processes. These results not only are consistent with the improved-attentional-control account of AVGP benefits, but they suggest that the benefit of action video game playing extends across the full breadth of attention-mediated stimulus-response processes that impact human performance.

A New Manufacturing Service Selection and Composition Method Using Improved Flower Pollination Algorithm

Directory of Open Access Journals (Sweden)

Wenyu Zhang

2016-01-01

Full Text Available With an increasing number of manufacturing services, the means by which to select and compose these manufacturing services have become a challenging problem. It can be regarded as a multiobjective optimization problem that involves a variety of conflicting quality of service (QoS attributes. In this study, a multiobjective optimization model of manufacturing service composition is presented that is based on QoS and an environmental index. Next, the skyline operator is applied to reduce the solution space. And then a new method called improved Flower Pollination Algorithm (FPA is proposed for solving the problem of manufacturing service selection and composition. The improved FPA enhances the performance of basic FPA by combining the latter with crossover and mutation operators of the Differential Evolution (DE algorithm. Finally, a case study is conducted to compare the proposed method with other evolutionary algorithms, including the Genetic Algorithm, DE, basic FPA, and extended FPA. The experimental results reveal that the proposed method performs best at solving the problem of manufacturing service selection and composition.

Selection for production-related traits in Pelargonium zonale: improved design and analysis make all the difference.

Science.gov (United States)

Molenaar, Heike; Glawe, Martin; Boehm, Robert; Piepho, Hans-Peter

2017-01-01

Ornamental plant variety improvement is limited by current phenotyping approaches and neglected use of experimental designs. The present study was conducted to show the benefits of using an experimental design and corresponding analysis in ornamental breeding regarding simulated response to selection in Pelargonium zonale for production-related traits. This required establishment of phenotyping protocols for root formation and stem cutting counts, with which 974 genotypes were assessed in a two-phase experimental design. The present paper evaluates this protocol. The possibility of varietal improvement through indirect selection on secondary traits such as branch count and flower count was assessed by genetic correlations. Simulated response to selection varied greatly, depending on the genotypic variances of the breeding population and traits. A varietal improvement of over 20% is possible for stem cutting count, root formation, branch count and flower count. In contrast, indirect selection of stem cutting count by branch count or flower count was found to be ineffective. The established phenotypic protocols and two-phase experimental designs are valuable tools for breeding of P. zonale .

Genomic Selection Improves Heat Tolerance in Dairy Cattle

Science.gov (United States)

Garner, J. B.; Douglas, M. L.; Williams, S. R. O; Wales, W. J.; Marett, L. C.; Nguyen, T. T. T.; Reich, C. M.; Hayes, B. J.

2016-01-01

Dairy products are a key source of valuable proteins and fats for many millions of people worldwide. Dairy cattle are highly susceptible to heat-stress induced decline in milk production, and as the frequency and duration of heat-stress events increases, the long term security of nutrition from dairy products is threatened. Identification of dairy cattle more tolerant of heat stress conditions would be an important progression towards breeding better adapted dairy herds to future climates. Breeding for heat tolerance could be accelerated with genomic selection, using genome wide DNA markers that predict tolerance to heat stress. Here we demonstrate the value of genomic predictions for heat tolerance in cohorts of Holstein cows predicted to be heat tolerant and heat susceptible using controlled-climate chambers simulating a moderate heatwave event. Not only was the heat challenge stimulated decline in milk production less in cows genomically predicted to be heat-tolerant, physiological indicators such as rectal and intra-vaginal temperatures had reduced increases over the 4 day heat challenge. This demonstrates that genomic selection for heat tolerance in dairy cattle is a step towards securing a valuable source of nutrition and improving animal welfare facing a future with predicted increases in heat stress events. PMID:27682591

The admissible portfolio selection problem with transaction costs and an improved PSO algorithm

Science.gov (United States)

Chen, Wei; Zhang, Wei-Guo

2010-05-01

In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets. We propose a new admissible efficient portfolio selection model and design an improved particle swarm optimization (PSO) algorithm because traditional optimization algorithms fail to work efficiently for our proposed problem. Finally, we offer a numerical example to illustrate the proposed effective approaches and compare the admissible portfolio efficient frontiers under different constraints.

Improving inspection reliability through operator selection and training

International Nuclear Information System (INIS)

McGrath, Bernard; Carter, Luke

2013-01-01

A number of years ago the UK's Health and Safety Executive sponsored a series of three PANI projects investigating the application of manual ultrasonics, which endeavoured to establish the necessary steps that ensure a reliable inspection is performed. The results of the three projects were each reported separately on completion and also presented at number of international conferences. This paper summarises the results of these projects from the point of view of operator performance. The correlation of operator ultrasonic performance with results of aptitude tests is presented along with observations on the impact of training and qualifications of the operators. The results lead to conclusions on how the selection and training of operators could be modified to improve reliability of inspections.

Improved social force model based on exit selection for microscopic pedestrian simulation in subway station

Institute of Scientific and Technical Information of China (English)

郑勋; 李海鹰; 孟令云; 许心越; 陈旭

2015-01-01

An improved social force model based on exit selection is proposed to simulate pedestrians’ microscopic behaviors in subway station. The modification lies in considering three factors of spatial distance, occupant density and exit width. In addition, the problem of pedestrians selecting exit frequently is solved as follows: not changing to other exits in the affected area of one exit, using the probability of remaining preceding exit and invoking function of exit selection after several simulation steps. Pedestrians in subway station have some special characteristics, such as explicit destinations, different familiarities with subway station. Finally, Beijing Zoo Subway Station is taken as an example and the feasibility of the model results is verified through the comparison of the actual data and simulation data. The simulation results show that the improved model can depict the microscopic behaviors of pedestrians in subway station.

Improving the precision of genotype selection in wheat performance trials

Directory of Open Access Journals (Sweden)

Giovani Benin

2013-12-01

Full Text Available The aim of this study was to verify whether using the Papadakis method improves model assumptions and experimental accuracy in field trials used to determine grain yield for wheat lineages indifferent Value for Cultivation and Use (VCU regions. Grain yield data from 572 field trials at 31 locations in the VCU Regions 1, 2, 3 and 4 in 2007-2011 were used. Each trial was run with and without the use of the Papadakis method. The Papadakis method improved the indices of experimental precision measures and reduced the number of experimental repetitions required to predict grain yield performance among the wheat genotypes. There were differences among the wheat adaptation regions in terms of the efficiency of the Papadakis method, the adjustment coefficient of the genotype averages and the increases in the selective accuracy of grain yield.

Improved Selectivity From a Wavelength Addressable Device for Wireless Stimulation of Neural Tissue

Directory of Open Access Journals (Sweden)

Elif Ç. Seymour

2014-02-01

Full Text Available Electrical neural stimulation with micro electrodes is a promising technique for restoring lost functions in the central nervous system as a result of injury or disease. One of the problems related to current neural stimulators is the tissue response due to the connecting wires and the presence of a rigid electrode inside soft neural tissue. We have developed a novel, optically activated, microscale photovoltaic neurostimulator based on a custom layered compound semiconductor heterostructure that is both wireless and has a comparatively small volume. Optical activation provides a wireless means of energy transfer to the neurostimulator, eliminating wires and the associated complications. This neurostimulator was shown to evoke action potentials and a functional motor response in the rat spinal cord. In this work, we extend our design to include wavelength selectivity and thus allowing independent activation of devices. As a proof of concept, we fabricated two different microscale devices with different spectral responsivities in the near-infrared region. We assessed the improved addressability of individual devices via wavelength selectivity as compared to spatial selectivity alone through on-bench optical measurements of the devices in combination with an in vivo light intensity profile in the rat cortex obtained in a previous study. We show that wavelength selectivity improves the individual addressability of the floating stimulators, thus increasing the number of devices that can be implanted in close proximity to each other.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

Science.gov (United States)

Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

International Nuclear Information System (INIS)

Anderson, Ryan B.; Bell, James F.; Wiens, Roger C.; Morris, Richard V.; Clegg, Samuel M.

2012-01-01

We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO 2 at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by ∼ 3 wt.%. The statistical significance of these improvements was ∼ 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and specifically

Training directionally selective motion pathways can significantly improve reading efficiency

Science.gov (United States)

Lawton, Teri

2004-06-01

This study examined whether perceptual learning at early levels of visual processing would facilitate learning at higher levels of processing. This was examined by determining whether training the motion pathways by practicing leftright movement discrimination, as found previously, would improve the reading skills of inefficient readers significantly more than another computer game, a word discrimination game, or the reading program offered by the school. This controlled validation study found that practicing left-right movement discrimination 5-10 minutes twice a week (rapidly) for 15 weeks doubled reading fluency, and significantly improved all reading skills by more than one grade level, whereas inefficient readers in the control groups barely improved on these reading skills. In contrast to previous studies of perceptual learning, these experiments show that perceptual learning of direction discrimination significantly improved reading skills determined at higher levels of cognitive processing, thereby being generalized to a new task. The deficits in reading performance and attentional focus experienced by the person who struggles when reading are suggested to result from an information overload, resulting from timing deficits in the direction-selectivity network proposed by Russell De Valois et al. (2000), that following practice on direction discrimination goes away. This study found that practicing direction discrimination rapidly transitions the inefficient 7-year-old reader to an efficient reader.

Improving the baking quality of bread wheat by genomic selection in early generations.

Science.gov (United States)

Michel, Sebastian; Kummer, Christian; Gallee, Martin; Hellinger, Jakob; Ametz, Christian; Akgöl, Batuhan; Epure, Doru; Löschenberger, Franziska; Buerstmayr, Hermann

2018-02-01

Genomic selection shows great promise for pre-selecting lines with superior bread baking quality in early generations, 3 years ahead of labour-intensive, time-consuming, and costly quality analysis. The genetic improvement of baking quality is one of the grand challenges in wheat breeding as the assessment of the associated traits often involves time-consuming, labour-intensive, and costly testing forcing breeders to postpone sophisticated quality tests to the very last phases of variety development. The prospect of genomic selection for complex traits like grain yield has been shown in numerous studies, and might thus be also an interesting method to select for baking quality traits. Hence, we focused in this study on the accuracy of genomic selection for laborious and expensive to phenotype quality traits as well as its selection response in comparison with phenotypic selection. More than 400 genotyped wheat lines were, therefore, phenotyped for protein content, dough viscoelastic and mixing properties related to baking quality in multi-environment trials 2009-2016. The average prediction accuracy across three independent validation populations was r = 0.39 and could be increased to r = 0.47 by modelling major QTL as fixed effects as well as employing multi-trait prediction models, which resulted in an acceptable prediction accuracy for all dough rheological traits (r = 0.38-0.63). Genomic selection can furthermore be applied 2-3 years earlier than direct phenotypic selection, and the estimated selection response was nearly twice as high in comparison with indirect selection by protein content for baking quality related traits. This considerable advantage of genomic selection could accordingly support breeders in their selection decisions and aid in efficiently combining superior baking quality with grain yield in newly developed wheat varieties.

Generalized structural equations improve sexual-selection analyses.

Directory of Open Access Journals (Sweden)

Sonia Lombardi

Full Text Available Sexual selection is an intense evolutionary force, which operates through competition for the access to breeding resources. There are many cases where male copulatory success is highly asymmetric, and few males are able to sire most females. Two main hypotheses were proposed to explain this asymmetry: "female choice" and "male dominance". The literature reports contrasting results. This variability may reflect actual differences among studied populations, but it may also be generated by methodological differences and statistical shortcomings in data analysis. A review of the statistical methods used so far in lek studies, shows a prevalence of Linear Models (LM and Generalized Linear Models (GLM which may be affected by problems in inferring cause-effect relationships; multi-collinearity among explanatory variables and erroneous handling of non-normal and non-continuous distributions of the response variable. In lek breeding, selective pressure is maximal, because large numbers of males and females congregate in small arenas. We used a dataset on lekking fallow deer (Dama dama, to contrast the methods and procedures employed so far, and we propose a novel approach based on Generalized Structural Equations Models (GSEMs. GSEMs combine the power and flexibility of both SEM and GLM in a unified modeling framework. We showed that LMs fail to identify several important predictors of male copulatory success and yields very imprecise parameter estimates. Minor variations in data transformation yield wide changes in results and the method appears unreliable. GLMs improved the analysis, but GSEMs provided better results, because the use of latent variables decreases the impact of measurement errors. Using GSEMs, we were able to test contrasting hypotheses and calculate both direct and indirect effects, and we reached a high precision of the estimates, which implies a high predictive ability. In synthesis, we recommend the use of GSEMs in studies on

Post-CMOS selective electroplating technique for the improvement of CMOS-MEMS accelerometers

International Nuclear Information System (INIS)

Liu, Yu-Chia; Tsai, Ming-Han; Fang, Weileun; Tang, Tsung-Lin

2011-01-01

This study presents a simple approach to improve the performance of the CMOS-MEMS capacitive accelerometer by means of the post-CMOS metal electroplating process. The metal layer can be selectively electroplated on the MEMS structures at low temperature and the thickness of the metal layer can be easily adjusted by this process. Thus the performance of the capacitive accelerometer (i.e. sensitivity, noise floor and the minimum detectable signal) can be improved. In application, the proposed accelerometers have been implemented using (1) the standard CMOS 0.35 µm 2P4M process by CMOS foundry, (2) Ti/Au seed layers deposition/patterning by MEMS foundry and (3) in-house post-CMOS electroplating and releasing processes. Measurements indicate that the sensitivity is improved 2.85-fold, noise is decreased near 1.7-fold and the minimum detectable signal is improved from 1 to 0.2 G after nickel electroplating. Moreover, unwanted structure deformation due to the temperature variation is significantly suppressed by electroplated nickel.

Improving Breeding Selection of Seed Quality Traits for Food-Grade Soybeans

OpenAIRE

Escamilla Sanchez, Diana Marcela

2018-01-01

Natto and sprout soybeans are produced using small-seeded soybeans and their production is a high value alternative to grow grain soybeans for food in U.S. The development of soybean cultivars with improved natto and sprout quality is crucial for maintaining and increasing the soyfood market. However, there is insufficient information on sprout soybean characteristics. Therefore, the first objective of this study was to evaluate seed and sprout traits as potential selection criteria and study...

Improving permafrost distribution modelling using feature selection algorithms

Science.gov (United States)

Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

2016-04-01

The availability of an increasing number of spatial data on the occurrence of mountain permafrost allows the employment of machine learning (ML) classification algorithms for modelling the distribution of the phenomenon. One of the major problems when dealing with high-dimensional dataset is the number of input features (variables) involved. Application of ML classification algorithms to this large number of variables leads to the risk of overfitting, with the consequence of a poor generalization/prediction. For this reason, applying feature selection (FS) techniques helps simplifying the amount of factors required and improves the knowledge on adopted features and their relation with the studied phenomenon. Moreover, taking away irrelevant or redundant variables from the dataset effectively improves the quality of the ML prediction. This research deals with a comparative analysis of permafrost distribution models supported by FS variable importance assessment. The input dataset (dimension = 20-25, 10 m spatial resolution) was constructed using landcover maps, climate data and DEM derived variables (altitude, aspect, slope, terrain curvature, solar radiation, etc.). It was completed with permafrost evidences (geophysical and thermal data and rock glacier inventories) that serve as training permafrost data. Used FS algorithms informed about variables that appeared less statistically important for permafrost presence/absence. Three different algorithms were compared: Information Gain (IG), Correlation-based Feature Selection (CFS) and Random Forest (RF). IG is a filter technique that evaluates the worth of a predictor by measuring the information gain with respect to the permafrost presence/absence. Conversely, CFS is a wrapper technique that evaluates the worth of a subset of predictors by considering the individual predictive ability of each variable along with the degree of redundancy between them. Finally, RF is a ML algorithm that performs FS as part of its

Selective REM Sleep Deprivation Improves Expectation-Related Placebo Analgesia.

Science.gov (United States)

Chouchou, Florian; Chauny, Jean-Marc; Rainville, Pierre; Lavigne, Gilles J

2015-01-01

The placebo effect is a neurobiological and psychophysiological process known to influence perceived pain relief. Optimization of placebo analgesia may contribute to the clinical efficacy and effectiveness of medication for acute and chronic pain management. We know that the placebo effect operates through two main mechanisms, expectations and learning, which is also influenced by sleep. Moreover, a recent study suggested that rapid eye movement (REM) sleep is associated with modulation of expectation-mediated placebo analgesia. We examined placebo analgesia following pharmacological REM sleep deprivation and we tested the hypothesis that relief expectations and placebo analgesia would be improved by experimental REM sleep deprivation in healthy volunteers. Following an adaptive night in a sleep laboratory, 26 healthy volunteers underwent classical experimental placebo analgesic conditioning in the evening combined with pharmacological REM sleep deprivation (clonidine: 13 volunteers or inert control pill: 13 volunteers). Medication was administered in a double-blind manner at bedtime, and placebo analgesia was tested in the morning. Results revealed that 1) placebo analgesia improved with REM sleep deprivation; 2) pain relief expectations did not differ between REM sleep deprivation and control groups; and 3) REM sleep moderated the relationship between pain relief expectations and placebo analgesia. These results support the putative role of REM sleep in modulating placebo analgesia. The mechanisms involved in these improvements in placebo analgesia and pain relief following selective REM sleep deprivation should be further investigated.

A Hypothesis and Review of the Relationship between Selection for Improved Production Efficiency, Coping Behavior, and Domestication

Directory of Open Access Journals (Sweden)

Wendy M. Rauw

2017-09-01

Full Text Available Coping styles in response to stressors have been described both in humans and in other animal species. Because coping styles are directly related to individual fitness they are part of the life history strategy. Behavioral styles trade off with other life-history traits through the acquisition and allocation of resources. Domestication and subsequent artificial selection for production traits specifically focused on selection of individuals with energy sparing mechanisms for non-production traits. Domestication resulted in animals with low levels of aggression and activity, and a low hypothalamic–pituitary–adrenal (HPA axis reactivity. In the present work, we propose that, vice versa, selection for improved production efficiency may to some extent continue to favor docile domesticated phenotypes. It is hypothesized that both domestication and selection for improved production efficiency may result in the selection of reactive style animals. Both domesticated and reactive style animals are characterized by low levels of aggression and activity, and increased serotonin neurotransmitter levels. However, whereas domestication quite consistently results in a decrease in the functional state of the HPA axis, the reactive coping style is often found to be dominated by a high HPA response. This may suggest that fearfulness and coping behavior are two independent underlying dimensions to the coping response. Although it is generally proposed that animal welfare improves with selection for calmer animals that are less fearful and reactive to novelty, animals bred to be less sensitive with fewer desires may be undesirable from an ethical point of view.

An improved culture method for selective isolation of Campylobacter jejuni from wastewater

Directory of Open Access Journals (Sweden)

Jinyong Kim

2016-08-01

Full Text Available Campylobacter jejuni is one of the leading foodborne pathogens worldwide. C. jejuni is isolated from a wide range of foods, domestic animals, wildlife, and environmental sources. The currently-available culture-based isolation methods are not highly effective for wastewater samples due to the low number of C. jejuni in the midst of competing bacteria. To detect and isolate C. jejuni from wastewater samples, in this study, we evaluated a few different enrichment conditions using five different antibiotics (i.e., cefoperazone, vancomycin, trimethoprim, polymyxin B, and rifampicin, to which C. jejuni is intrinsically resistant. The selectivity of each enrichment condition was measured with Ct value using quantitative real-time PCR (qRT-PCR, and multiplex PCR to determine Campylobacter species. In addition, the efficacy of Campylobacter isolation on different culture media after selective enrichment was examined by growing on Bolton and Preston agar plates. The addition of polymyxin B, rifampicin, or both to the Bolton selective supplements enhanced the selective isolation of C. jejuni. In particular, rifampicin supplementation and an increased culture temperature (i.e., 42°C had a decisive effect on the selective enrichment of C. jejuni from wastewater. The results of 16S rDNA sequencing also revealed that Enterococcus spp. and Pseudomonas aeruginosa are major competing bacteria in the enrichment conditions. Although it is known to be difficult to isolate Campylobacter from samples with heavy contamination, this study well exhibited that the manipulation of antibiotic selective pressure improves the isolation efficiency of fastidious Campylobacter from wastewater.

Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Anderson, Ryan B., E-mail: randerson@astro.cornell.edu [Cornell University Department of Astronomy, 406 Space Sciences Building, Ithaca, NY 14853 (United States); Bell, James F., E-mail: Jim.Bell@asu.edu [Arizona State University School of Earth and Space Exploration, Bldg.: INTDS-A, Room: 115B, Box 871404, Tempe, AZ 85287 (United States); Wiens, Roger C., E-mail: rwiens@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States); Morris, Richard V., E-mail: richard.v.morris@nasa.gov [NASA Johnson Space Center, 2101 NASA Parkway, Houston, TX 77058 (United States); Clegg, Samuel M., E-mail: sclegg@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States)

2012-04-15

We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO{sub 2} at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by {approx} 3 wt.%. The statistical significance of these improvements was {approx} 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and

Genetic characterization of Russian honey bee stock selected for improved resistance to Varroa destructor.

Science.gov (United States)

Bourgeois, A Lelania; Rinderer, Thomas E

2009-06-01

Maintenance of genetic diversity among breeding lines is important in selective breeding and stock management. The Russian Honey Bee Breeding Program has strived to maintain high levels of heterozygosity among its breeding lines since its inception in 1997. After numerous rounds of selection for resistance to tracheal and varroa mites and improved honey production, 18 lines were selected as the core of the program. These lines were grouped into three breeding blocks that were crossbred to improve overall heterozygosity levels of the population. Microsatellite DNA data demonstrated that the program has been successful. Heterozygosity and allelic richness values are high and there are no indications of inbreeding among the three blocks. There were significant levels of genetic structure measured among the three blocks. Block C was genetically distinct from both blocks A and B (F(ST) = 0.0238), whereas blocks A and B did not differ from each other (F(ST) = 0.0074). The same pattern was seen for genic (based on numbers of alleles) differentiation. Genetic distance, as measured by chord distance, indicates that all of the 18 lines are equally distant, with minimal clustering. The data indicate that the overall design of the breeding program has been successful in maintaining high levels of diversity and avoiding problems associated with inbreeding.

Selection and application of microorganisms to improve oil recovery

Energy Technology Data Exchange (ETDEWEB)

Almeida, P.F.; Moreira, R.S.; Almeida, R.C.C.; Guimaraes, A.K.; Carvalho, A.S. [Laboratorio de Biotecnologia e Ecologia de Microrganismos da Universidade Federal da Bahia, Avenida Reitor Miguel Calmon, s/n, Vale do Canela, CEP 41.160-100 Salvador BA (Brazil); Quintella, C.; Esperidia, M.C.A. [Instituto de Quimica da Universidade Federal da Bahia, Rua Barao de Geremoabo, s/n, Campus Universitario de Ondina, CEP 40.170-290, Salvador BA (Brazil); Taft, C.A. [Centro Brasileiro de Pesquisas Fisicas, Rua Xavier Sigaud, 150, Urca, 22290-180, Rio de Janeiro (Brazil)

2004-08-01

Microbial enhanced oil recovery (Meor) is an incontestably efficient alternative to improve oil recovery, especially in mature fields and in oil reservoirs with high paraffinic content. This is the case for most oil fields in the Reconcavo basin of Bahia, Brazil. Given the diverse conditions of most oil fields, an approach to apply Meor technology should consider primarily: (i) microbiological studies to select the appropriate microorganisms and (ii) mobilization of oil in laboratory experiments before oil field application. A total of 163 bacterial strains, selectively isolated from various sources, were studied to determine their potential to be used in Meor. A laboratory microbial screening based on physiological and metabolic profiles and growth rates under conditions representative for oil fields and reservoirs revealed that 10 bacterial strains identified as Pseudomonas aeruginosa (2), Bacillus licheniformis (2), Bacillus brevis (1), Bacillus polymyxa (1), Micrococcus varians (1), Micrococcus sp. (1), and two Vibrio species demonstrated potential to be used in oil recovery. Strains of B. licheniformis and B. polymyxa produced the most active surfactants and proved to be the most anaerobic and thermotolerant among the selected bacteria. Micrococcus and B. brevis were the most salt-tolerant and polymer producing bacteria, respectively, whereas Vibrio sp. and B. polymyxa strains were the most gas-producing bacteria. Three bacterial consortia were prepared with a mixture of bacteria that showed metabolic and technological complementarity and the ability to grow at a wide range of temperatures and salinity characteristics for the oil fields in Bahia, Brazil. Oil mobilization rates in laboratory column experiments using the three consortia of bacteria varied from 11.2 to 18.3 % [v/v] of the total oil under static conditions. Consortia of B. brevis, B. icheniformis and B. polymyxa exhibited the best oil mobilization rates. Using these consortia under anaerobic

Road network selection for small-scale maps using an improved centrality-based algorithm

Directory of Open Access Journals (Sweden)

Roy Weiss

2014-12-01

Full Text Available The road network is one of the key feature classes in topographic maps and databases. In the task of deriving road networks for products at smaller scales, road network selection forms a prerequisite for all other generalization operators, and is thus a fundamental operation in the overall process of topographic map and database production. The objective of this work was to develop an algorithm for automated road network selection from a large-scale (1:10,000 to a small-scale database (1:200,000. The project was pursued in collaboration with swisstopo, the national mapping agency of Switzerland, with generic mapping requirements in mind. Preliminary experiments suggested that a selection algorithm based on betweenness centrality performed best for this purpose, yet also exposed problems. The main contribution of this paper thus consists of four extensions that address deficiencies of the basic centrality-based algorithm and lead to a significant improvement of the results. The first two extensions improve the formation of strokes concatenating the road segments, which is crucial since strokes provide the foundation upon which the network centrality measure is computed. Thus, the first extension ensures that roundabouts are detected and collapsed, thus avoiding interruptions of strokes by roundabouts, while the second introduces additional semantics in the process of stroke formation, allowing longer and more plausible strokes to built. The third extension detects areas of high road density (i.e., urban areas using density-based clustering and then locally increases the threshold of the centrality measure used to select road segments, such that more thinning takes place in those areas. Finally, since the basic algorithm tends to create dead-ends—which however are not tolerated in small-scale maps—the fourth extension reconnects these dead-ends to the main network, searching for the best path in the main heading of the dead-end.

Improved time series prediction with a new method for selection of model parameters

International Nuclear Information System (INIS)

Jade, A M; Jayaraman, V K; Kulkarni, B D

2006-01-01

A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)

Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning

NARCIS (Netherlands)

Kostons, Danny; Van Gog, Tamara; Paas, Fred

2012-01-01

Kostons, D., Van Gog, T., & Paas, F. (2012). Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning. Learning and Instruction, 22(2), 121-132. doi:10.1016/j.learninstruc.2011.08.004

Improving the Bandwidth Selection in Kernel Equating

Science.gov (United States)

Andersson, Björn; von Davier, Alina A.

2014-01-01

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

Genomic selection: genome-wide prediction in plant improvement.

Science.gov (United States)

Desta, Zeratsion Abera; Ortiz, Rodomiro

2014-09-01

Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Improved detection limits for phthalates by selective solid-phase micro-extraction

KAUST Repository

Zia, Asif I.

2016-03-30

Presented research reports on an improved method and enhanced limits of detection for phthalates; a hazardous additive used in the production of plastics by solid-phase micro-extraction (SPME) polymer in comparison to molecularly imprinted solid-phase extraction (MISPE) polymer. The polymers were functionalized on an interdigital capacitive sensor for selective binding of phthalate molecules from a complex mixture of chemicals. Both polymers owned predetermined selectivity by formation of valuable molecular recognition sites for Bis (2-ethylhexyl) phthalate (DEHP). Polymers were immobilized on planar electrochemical sensor fabricated on a single crystal silicon substrate with 500 nm sputtered gold electrodes fabricated using MEMS fabrication techniques. Impedance spectra were obtained using electrochemical impedance spectroscopy (EIS) to determine sample conductance for evaluation of phthalate concentration in the spiked sample solutions with various phthalate concentrations. Experimental results revealed that the ability of SPME polymer to adsorb target molecules on the sensing surface is better than that of MISPE polymer for phthalates in the sensing system. Testing the extracted samples using high performance liquid chromatography with photodiode array detectors validated the results.

Cermet based solar selective absorbers : further selectivity improvement and developing new fabrication technique

OpenAIRE

Nejati, Mohammadreza

2008-01-01

Spectral selectivity of cermet based selective absorbers were increased by inducing surface roughness on the surface of the cermet layer using a roughening technique (deposition on hot substrates) or by micro-structuring the metallic substrates before deposition of the absorber coating using laser and imprint structuring techniques. Cu-Al2O3 cermet absorbers with very rough surfaces and excellent selectivity were obtained by employing a roughness template layer under the infrared reflective l...

The robust corrective action priority-an improved approach for selecting competing corrective actions in FMEA based on principle of robust design

Science.gov (United States)

Sutrisno, Agung; Gunawan, Indra; Vanany, Iwan

2017-11-01

In spite of being integral part in risk - based quality improvement effort, studies improving quality of selection of corrective action priority using FMEA technique are still limited in literature. If any, none is considering robustness and risk in selecting competing improvement initiatives. This study proposed a theoretical model to select risk - based competing corrective action by considering robustness and risk of competing corrective actions. We incorporated the principle of robust design in counting the preference score among corrective action candidates. Along with considering cost and benefit of competing corrective actions, we also incorporate the risk and robustness of corrective actions. An example is provided to represent the applicability of the proposed model.

A TOTAL MANUFACTURING SOLUTIONS TECHNIQUE TO SELECT APPROPRIATE IMPROVEMENT STRATEGY: CASE STUDY OF A FOOTWEAR FACTORY

Directory of Open Access Journals (Sweden)

Gezahegn Tesfaye

2014-09-01

Full Text Available The Government of Ethiopia is promoting the manufacturing sector to join the global market in a large scale. Due to its comparative advantages, the Ethiopian leather and leather products industry have been given due attention. To fully utilize such advantages, the country shifted its export items from hides/skins to footwear products. Nevertheless, the performance of the leather sector in general and footwear sub-sector in particular is far below the desired standards. The improvement strategies applied hitherto were mainly to tackle a small portion of their total problems. If the Ethiopian footwear companies have to become globally competitive, their entire business spectrum has to be assessed and appropriate improvement strategies must be selected. In this research, we used a Total manufacturing solutions (TMS technique to identify areas of improvement and improvement strategy of one of Ethiopian footwear companies. For this purpose, we conducted two surveys using structured questionnaire. The first survey was to test the TMS technique against the context of footwear industry. The result proved that the original TMS model can be used to measure the performance of footwear companies. The second survey was done to identify company's total problems, map its current position and select appropriate improvement strategy. The result revealed that the company has company-wide problems and its current position is a plodder. For plodders which have company-wide problems, the improvement strategy must include aggressive application of BPR; and the implementation of best practices to develop workers skills that encourages networking and promotion, a market-led manufacturing strategy, employee involvement and team work cultures. According to the findings of this research, we suggested that a BPR technique followed by a continuous improvement programme could be an appropriate improvement strategy for this company. The company requires long-term improvement

Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm

International Nuclear Information System (INIS)

Chitsaz, Hamed; Amjady, Nima; Zareipour, Hamidreza

2015-01-01

Highlights: • Presenting a Morlet wavelet neural network for wind power forecasting. • Proposing improved Clonal selection algorithm for training the model. • Applying Maximum Correntropy Criterion to evaluate the training performance. • Extensive testing of the proposed wind power forecast method on real-world data. - Abstract: With the integration of wind farms into electric power grids, an accurate wind power prediction is becoming increasingly important for the operation of these power plants. In this paper, a new forecasting engine for wind power prediction is proposed. The proposed engine has the structure of Wavelet Neural Network (WNN) with the activation functions of the hidden neurons constructed based on multi-dimensional Morlet wavelets. This forecast engine is trained by a new improved Clonal selection algorithm, which optimizes the free parameters of the WNN for wind power prediction. Furthermore, Maximum Correntropy Criterion (MCC) has been utilized instead of Mean Squared Error as the error measure in training phase of the forecasting model. The proposed wind power forecaster is tested with real-world hourly data of system level wind power generation in Alberta, Canada. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. The obtained results confirm the validity of the developed approach

Working memory load can both improve and impair selective attention: evidence from the Navon paradigm.

Science.gov (United States)

Ahmed, Lubna; de Fockert, Jan W

2012-10-01

Selective attention to relevant targets has been shown to depend on the availability of working memory (WM). Under conditions of high WM load, processing of irrelevant distractors is enhanced. Here we showed that this detrimental effect of WM load on selective attention efficiency is reversed when the task requires global- rather than local-level processing. Participants were asked to attend to either the local or the global level of a hierarchical Navon stimulus while keeping either a low or a high load in WM. In line with previous findings, during attention to the local level, distractors at the global level produced more interference under high than under low WM load. By contrast, loading WM had the opposite effect of improving selective attention during attention to the global level. The findings demonstrate that the impact of WM load on selective attention is not invariant, but rather is dependent on the level of the to-be-attended information.

Improving the Quality of Recycled Fine Aggregate by Selective Removal of Brittle Defects

OpenAIRE

Ogawa, Hideo; Nawa, Toyoharu

2012-01-01

Crushed recycled aggregate contains particles with brittle defects such as cracks, pores, and voids. This study presents a method for improving the quality of recycled fine aggregate by selectively removing these defects. Fourteen recycled fine aggregates were manufactured by three types of processors including a jaw crusher, ball mill, and granulator. The influence of the recycled fine aggregate on the flowability and strength of the mortar was evaluated by multivariate analysis. The results...

Improving the fatigue performance of porous metallic biomaterials produced by Selective Laser Melting.

Science.gov (United States)

Van Hooreweder, Brecht; Apers, Yanni; Lietaert, Karel; Kruth, Jean-Pierre

2017-01-01

This paper provides new insights into the fatigue properties of porous metallic biomaterials produced by additive manufacturing. Cylindrical porous samples with diamond unit cells were produced from Ti6Al4V powder using Selective Laser Melting (SLM). After measuring all morphological and quasi-static properties, compression-compression fatigue tests were performed to determine fatigue strength and to identify important fatigue influencing factors. In a next step, post-SLM treatments were used to improve the fatigue life of these biomaterials by changing the microstructure and by reducing stress concentrators and surface roughness. In particular, the influence of stress relieving, hot isostatic pressing and chemical etching was studied. Analytical and numerical techniques were developed to calculate the maximum local tensile stress in the struts as function of the strut diameter and load. With this method, the variability in the relative density between all samples was taken into account. The local stress in the struts was then used to quantify the exact influence of the applied post-SLM treatments on the fatigue life. A significant improvement of the fatigue life was achieved. Also, the post-SLM treatments, procedures and calculation methods can be applied to different types of porous metallic structures and hence this paper provides useful tools for improving fatigue performance of metallic biomaterials. Additive Manufacturing (AM) techniques such as Selective Laser Melting (SLM) are increasingly being used for producing customized porous metallic biomaterials. These biomaterials are regularly used for biomedical implants and hence a long lifetime is required. In this paper, a set of post-built surface and heat treatments is presented that can be used to significantly improve the fatigue life of porous SLM-Ti6Al4V samples. In addition, a novel and efficient analytical local stress method was developed to accurately quantify the influence of the post

Hand placement near the visual stimulus improves orientation selectivity in V2 neurons

Science.gov (United States)

Sergio, Lauren E.; Crawford, J. Douglas; Fallah, Mazyar

2015-01-01

Often, the brain receives more sensory input than it can process simultaneously. Spatial attention helps overcome this limitation by preferentially processing input from a behaviorally-relevant location. Recent neuropsychological and psychophysical studies suggest that attention is deployed to near-hand space much like how the oculomotor system can deploy attention to an upcoming gaze position. Here we provide the first neuronal evidence that the presence of a nearby hand enhances orientation selectivity in early visual processing area V2. When the hand was placed outside the receptive field, responses to the preferred orientation were significantly enhanced without a corresponding significant increase at the orthogonal orientation. Consequently, there was also a significant sharpening of orientation tuning. In addition, the presence of the hand reduced neuronal response variability. These results indicate that attention is automatically deployed to the space around a hand, improving orientation selectivity. Importantly, this appears to be optimal for motor control of the hand, as opposed to oculomotor mechanisms which enhance responses without sharpening orientation selectivity. Effector-based mechanisms for visual enhancement thus support not only the spatiotemporal dissociation of gaze and reach, but also the optimization of vision for their separate requirements for guiding movements. PMID:25717165

Improved feature selection based on genetic algorithms for real time disruption prediction on JET

International Nuclear Information System (INIS)

Rattá, G.A.; Vega, J.; Murari, A.

2012-01-01

Highlights: ► A new signal selection methodology to improve disruption prediction is reported. ► The approach is based on Genetic Algorithms. ► An advanced predictor has been created with the new set of signals. ► The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called “Advanced Predictor Of Disruptions” (APODIS), developed for the “Joint European Torus” (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals’ parameters in order to maximize the performance of the predictor is reported. The approach is based on “Genetic Algorithms” (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

Selection Criteria for Improving Yield in Chili (Capsicum annuum

Directory of Open Access Journals (Sweden)

S. Chakrabarty

2017-01-01

Full Text Available The present investigation was carried out to estimate the genetic variability and character association. Significant differences were observed among the genotypes for all the 15 traits for 20 chili genotypes. The highest genotypic coefficient of variation and phenotypic coefficient of variation were found for ten edible fruit weight, number of fruits per plant, fruit yield per plant, ten dry fruit weight, fruit length, fruit width, and weight of seeds per fruit. High heritability coupled with very high genetic advance as per cent of mean was observed for ten edible fruit weight, ten dry fruit weight, fruit length, number of fruits per plant, and fruit yield per plant. Phenotypic correlation coefficient among different traits indicated that fruit yield per plant at green stage had significant and positive association with ten edible green fruit weight, number of primary branches, harvest duration, and first fruit maturity and significant negative correlation with days to first picking. The path coefficient analysis revealed that days to first picking had the maximum positive direct effect on fruit yield per plant followed by harvest duration, ten edible fruit weight, ten dry fruit weight, hundred-seed weight, number of fruits per plant, first fruit maturity, and number of primary branches. Days to first picking had the maximum positive direct effect but significant negative effect with fruit yield per plant which indicated that the trait should be selected to expunge the undesirable indirect effect in order to make use of the direct effect. Therefore, selection should be practiced for ten edible fruit weight, ten dry fruit weight, number of fruits per plant, harvest duration, and hundred-seed weight for direct improvement of fruit yield per plant.

An Efficient Adaptive Window Size Selection Method for Improving Spectrogram Visualization

Directory of Open Access Journals (Sweden)

Shibli Nisar

2016-01-01

Full Text Available Short Time Fourier Transform (STFT is an important technique for the time-frequency analysis of a time varying signal. The basic approach behind it involves the application of a Fast Fourier Transform (FFT to a signal multiplied with an appropriate window function with fixed resolution. The selection of an appropriate window size is difficult when no background information about the input signal is known. In this paper, a novel empirical model is proposed that adaptively adjusts the window size for a narrow band-signal using spectrum sensing technique. For wide-band signals, where a fixed time-frequency resolution is undesirable, the approach adapts the constant Q transform (CQT. Unlike the STFT, the CQT provides a varying time-frequency resolution. This results in a high spectral resolution at low frequencies and high temporal resolution at high frequencies. In this paper, a simple but effective switching framework is provided between both STFT and CQT. The proposed method also allows for the dynamic construction of a filter bank according to user-defined parameters. This helps in reducing redundant entries in the filter bank. Results obtained from the proposed method not only improve the spectrogram visualization but also reduce the computation cost and achieves 87.71% of the appropriate window length selection.

Four minutes of in-class high-intensity interval activity improves selective attention in 9- to 11-year olds.

Science.gov (United States)

Ma, Jasmin K; Le Mare, Lucy; Gurd, Brendon J

2015-03-01

The amount of time allocated to physical activity in schools is declining. Time-efficient physical activity solutions that demonstrate their impact on academic achievement-related outcomes are needed to prioritize physical activity within the school curricula. "FUNtervals" are 4-min, high-intensity interval activities that use whole-body actions to complement a storyline. The purpose of this study was to (i) explore whether FUNtervals can improve selective attention, an executive function posited to be essential for learning and academic success; and (ii) examine whether this relationship is predicted by students' classroom off-task behaviour. Seven grade 3-5 classes (n = 88) were exposed to a single-group, repeated cross-over design where each student's selective attention was compared between no-activity and FUNtervals days. In week 1, students were familiarized with the d2 test of attention and FUNterval activities, and baseline off-task behaviour was observed. In both weeks 2 and 3 students completed the d2 test of attention following either a FUNterval break or a no-activity break. The order of these breaks was randomized and counterbalanced between weeks. Neither motor nor passive off-task behaviour predicted changes in selective attention following FUNtervals; however, a weak relationship was observed for verbal off-task behaviour and improvements in d2 test performance. More importantly, students made fewer errors during the d2 test following FUNtervals. In supporting the priority of physical activity inclusion within schools, FUNtervals, a time efficient and easily implemented physical activity break, can improve selective attention in 9- to 11-year olds.

Marker-assisted selection as a potential tool for genetic improvement in developing countries: debating the issues

International Nuclear Information System (INIS)

Robinson, J.; Ruane, J.

2007-01-01

Marker-assisted selection (MAS) is a complementary technology, for use in conjunction with more established conventional methods of genetic selection, for plant and animal improvement. It has generated a good deal of expectations, many of which have yet to be realized. Although documentation is limited, the current impact of MAS on products delivered to farmers seems small. While the future possibilities and potential impacts of MAS are considerable, there are also obstacles to its use, particularly in developing countries. Principal among these are issues relating to current high costs of the technology and its appropriateness, given that publicly funded agricultural research in many developing countries is suboptimal and development priorities do not necessarily include genetic improvement programmes. Other potential obstacles to the uptake of MAS in developing countries include limited infrastructure, the absence of conventional selection and breeding programmes, poor private sector involvement and lack of research on specific crops of importance in developing countries. Intellectual property rights may also be an important constraint to development and uptake of MAS in the developing world. It is hoped that through partnerships between developing and developed country institutions and individuals, including public-private sector collaboration, MAS costs can be reduced, resources pooled and shared and capacity developed. With the assistance of the Consultative Group on International Agricultural Research (CGIAR) and international organizations such as FAO, developing countries can benefit more from MAS. These were some of the outcomes of a moderated e-mail conference, entitled 'Molecular Marker- Assisted Selection as a Potential Tool for Genetic Improvement of Crops, Forest Trees, Livestock and Fish in Developing Countries', that FAO hosted at the end of 2003. During the four-week conference, 627 people subscribed and 85 messages were posted, about 60 percent

Improved performance of molecular bulk-heterojunction photovoltaic cells through predictable selection of solvent additives

Energy Technology Data Exchange (ETDEWEB)

Graham, Kenneth R.; Wieruszewski, Patrick M.; Stalder, Romain; Mei, Jianguo [The George and Josephine Butler, Polymer Research Laboratory, Department of Chemistry and Center for Macromolecular Science and Engineering, University of Florida, Gainesville, FL 32611-7200 (United States); Hartel, Michael J.; So, Franky [Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32611 (United States); Reynolds, John R. [The George and Josephine Butler, Polymer Research Laboratory, Department of Chemistry and Center for Macromolecular Science and Engineering, University of Florida, Gainesville, FL 32611-7200 (United States); School of Chemistry and Biochemistry, School of Materials Science and Engineering and Center for Organic Photonics and Electronics, Georgia Institute of Technology, Atlanta, GA 30332-0400 (United States)

2012-11-21

Solvent additives provide an effective means to alter the morphology and thereby improve the performance of organic bulk-heterojunction photovoltaics, although guidelines for selecting an appropriate solvent additive remain relatively unclear. Here, a family of solvent additives spanning a wide range of Hansen solubility parameters is applied to a molecular bulk-heterojunction system consisting of an isoindigo and thiophene containing oligomer as the electron donor and [6,6]-phenyl-C{sub 61}-butyric acid methyl ester (PC{sub 61}BM) as the electron acceptor. Hansen solubility parameters are calculated using the group contribution method and compared with the measured solubilities for use as a screening method in solvent additive selection. The additives are shown to alter the morphologies in a semipredictable manner, with the poorer solvents generally resulting in decreased domain sizes, increased hole mobilities, and improved photovoltaic performance. The additives with larger hydrogen bonding parameters, namely triethylene glycol (TEG) and N-methyl-2-pyrrolidone (NMP), are demonstrated to increase the open circuit voltage by 0.2 V. Combining a solvent additive observed to increase short circuit current, poly(dimethylsiloxane), with TEG results in an increase in power conversion efficiency from 1.4 to 3.3%. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Study on Quality Improvement Effect and Separate Character of Soybean Male Sterile (MS1) Recurrent Selection Population

Institute of Scientific and Technical Information of China (English)

ZHAO Shuang-jin; ZHANG Meng-chen; JIANG Chun-zhi; YANG Chun-yan; LIU Bing-qiang; CUI Jue

2007-01-01

To solve the problem that soybean has narrow genetic base, we constructed a series of male sterile recurrent selection populations, and studied the effects of quality improvement and practical value. An LD-base population, which fits to our ecology type was constructed by 6 years' gene enrichment through the introduction of new genes from 23 local varieties and recurrent selection. The LD-base populations were then improved by making crosses with high protein and high oil genotypes. As a result we obtained a high protein sub-population (db) and a high oil sub-population (gy). For the db sub-population, the protein content is 1.18% higher than the base population, 22.38% of the individuals contain 45% or more of protein, which is 10.99% higher than the base population. For the gy sub-population, oil content is 0.24% higher than the base population. Individuals with oil content of 20% or more are 11.05% higher than the base population. The quantitative characters such as flowering date, mature date, pod habit, and hilum color, etc., all showed wide range of separation, and the segregation ratio approached balance. The c.v. of branch number of ms1 recurrent population (72.8%) is higher than general cross-population (57.3%), and the c.v. of 100 seed weight of ms1 (18.1%) is higher than general cross population (16.5%), the coefficient of variation of plant height, pods per plant, and seeds per pod were not significantly different. It was demonstrated in this paper that the quality character of ms1 male sterile recurrent selection population was improved by adding new genes. And the segregation of other characters widened, making the populations suitable for the objective of soybean breeding. In this paper, we also discussed the breeding method, key technology, and selection effect of soybean ms1 population.

Physiological improvement in the copepod Eurytemora affinis through thermal and multi-generational selection

DEFF Research Database (Denmark)

Souissi, Anissa; Souissi, Sami; Hansen, Benni Winding

2016-01-01

As a major part of fish larval diet in nature, copepods constitute an appropriate live prey for aquaculture purposes. Considering the difficulty of mastering copepod mass production, studies on their growth performance at different environmental conditions are needed to improve their productivity....... In this study a new selective approach based on temperature control is proposed to improve the physiological (body size, fecundity and lipid storage) performance of copepods. The estuarine copepod Eurytemora affinis known to have a high genetic variance in temperature tolerance was used as a biological model....... First two different copepod lines were obtained after long-term culture at constant cold (7°C) and warm (20°C) temperatures. Then both populations were transferred to a higher temperature of 24°C appropriate for aquaculture use and followed during five generations. During the first two generations (F1–F...

Improved feature selection based on genetic algorithms for real time disruption prediction on JET

Energy Technology Data Exchange (ETDEWEB)

Ratta, G.A., E-mail: garatta@gateme.unsj.edu.ar [GATEME, Facultad de Ingenieria, Universidad Nacional de San Juan, Avda. San Martin 1109 (O), 5400 San Juan (Argentina); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense, 40, 28040 Madrid (Spain); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Murari, A. [Associazione EURATOM-ENEA per la Fusione, Consorzio RFX, 4-35127 Padova (Italy); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom)

2012-09-15

Highlights: Black-Right-Pointing-Pointer A new signal selection methodology to improve disruption prediction is reported. Black-Right-Pointing-Pointer The approach is based on Genetic Algorithms. Black-Right-Pointing-Pointer An advanced predictor has been created with the new set of signals. Black-Right-Pointing-Pointer The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called 'Advanced Predictor Of Disruptions' (APODIS), developed for the 'Joint European Torus' (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals' parameters in order to maximize the performance of the predictor is reported. The approach is based on 'Genetic Algorithms' (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses.

Science.gov (United States)

Lehermeier, Christina; Teyssèdre, Simon; Schön, Chris-Carolin

2017-12-01

A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs. Copyright © 2017 by the Genetics Society of America.

Selection by mating competitiveness improves the performance of Anastrepha ludens males of the genetic sexing strain Tapachula-7.

Science.gov (United States)

Quintero-Fong, L; Toledo, J; Ruiz, L; Rendón, P; Orozco-Dávila, D; Cruz, L; Liedo, P

2016-10-01

The sexual performance of Anastrepha ludens males of the Tapachula-7 genetic sexing strain, produced via selection based on mating success, was compared with that of males produced without selection in competition with wild males. Mating competition, development time, survival, mass-rearing quality parameters and pheromone production were compared. The results showed that selection based on mating competitiveness significantly improved the sexual performance of offspring. Development time, survival of larvae, pupae and adults, and weights of larvae and pupae increased with each selection cycle. Differences in the relative quantity of the pheromone compounds (Z)-3-nonenol and anastrephin were observed when comparing the parental males with the F4 and wild males. The implications of this colony management method on the sterile insect technique are discussed.

Using Deep Learning for Targeted Data Selection, Improving Satellite Observation Utilization for Model Initialization

Science.gov (United States)

Lee, Y. J.; Bonfanti, C. E.; Trailovic, L.; Etherton, B.; Govett, M.; Stewart, J.

2017-12-01

At present, a fraction of all satellite observations are ultimately used for model assimilation. The satellite data assimilation process is computationally expensive and data are often reduced in resolution to allow timely incorporation into the forecast. This problem is only exacerbated by the recent launch of Geostationary Operational Environmental Satellite (GOES)-16 satellite and future satellites providing several order of magnitude increase in data volume. At the NOAA Earth System Research Laboratory (ESRL) we are researching the use of machine learning the improve the initial selection of satellite data to be used in the model assimilation process. In particular, we are investigating the use of deep learning. Deep learning is being applied to many image processing and computer vision problems with great success. Through our research, we are using convolutional neural network to find and mark regions of interest (ROI) to lead to intelligent extraction of observations from satellite observation systems. These targeted observations will be used to improve the quality of data selected for model assimilation and ultimately improve the impact of satellite data on weather forecasts. Our preliminary efforts to identify the ROI's are focused in two areas: applying and comparing state-of-art convolutional neural network models using the analysis data from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) weather model, and using these results as a starting point to optimize convolution neural network model for pattern recognition on the higher resolution water vapor data from GOES-WEST and other satellite. This presentation will provide an introduction to our convolutional neural network model to identify and process these ROI's, along with the challenges of data preparation, training the model, and parameter optimization.

Improvement of chemical shift selective saturation (CHESS) pulse for MR angiography

International Nuclear Information System (INIS)

Ishimori, Yoshiyuki; Sashie, Hiroyuki; Hiraga, Akira; Matsuda, Tsuyoshi

2000-01-01

We improved the fat suppression technique based on chemical shift selective saturation (CHESS). To do this, we shortened the duration of the CHESS pulse to achieve a short repetition time (TR) for MR angiography (MRA). A short-duration CHESS pulse causes broad frequency band saturation, creating extensive offset from the resonance frequency of water. In our phantom experiment, the best parameters of the short-duration CHESS pulse were 3.84 ms in duration, -650 Hz in offset frequency from water resonance, and had a 130-degree flip angle. With this technique, MRA will be able to be carried out without a significant increase in TR. Thus, better vessel contrast will be maintained in time-of-flight (TOF) MRA or contrast-enhanced MRA when using the maximum intensity projection (MIP) method. (author)

Prioritization and selection of electrical vehicle systems to improve its performances: An AHP approach

Energy Technology Data Exchange (ETDEWEB)

Larrode, E.; Muerza, V.; Arroyo, J.B.

2016-07-01

In the study of the improvement of urban transport in terms of energy efficiency and environmental improvement, one of the best options is the use of electric vehicles for both passengers and freight distribution. Depending on the type of transport operation to be performed, it is necessary to select the most appropriate vehicle that meets the necessary requirements, so that the result is an improvement in energy efficiency and low environmental impact. It is therefore necessary to design architectures for electric vehicles, specially adapted to the different scenarios in which are to be used, and where they can optimize the transport operation in both reducing energy consumption and reducing emissions, maintaining a cost competitive with current vehicle operation. The electrical vehicles (EV) are composed of different systems. A typical EV structure involves five subsystems: (i) drive system, (ii) power system, (iii) control system, (iv) vehicle structure and (v) auxiliary systems. This paper focuses on the development of a multicriteria decision procedure based on the use of the Analytic Hierarchy Process (AHP), to prioritize among the five vehicle systems, in which the design efforts should be guided to improve the vehicle. (Author)

Genetic selection and improvement of hard wood tree species for fuelwood production on sodic soil with particular reference to Prosopis juliflora

Energy Technology Data Exchange (ETDEWEB)

Goel, V.L.; Behl, H.M. [National Botanical Research Inst., Lucknow (India). Dept. of Tree Biology

2001-07-01

This study is part of a research programme on selection and improvement of fast growing tree species suitable for wood fuel production on sodic wastelands (pH 8.6-10.5). Field trials of nine legumes (Acacia auriculiformis, A. nilotica, Albizia lebbeck, A. procera, Dalbergia sissoo, Leucaena leucocephala, Pongamia pinnata, Prosopis juliflora, Pithecellobium dulce) and three other tree species (Azadirachta indica, Eucalyptus tereticornis and Terminalai arjuna) were selected for this study. Prosopis juliflora was the most promising species in terms of its biomass productivity (68.7 t ha{sup -1}) and fuel value index (148.8) after 8-yr of growth. Acacia nilotica ranked second. Intra-specific variations were screened at provenance and individual tree level in order to improve fuelwood production potential of P. juliflora through selection and breeding. Successful populations (gene pools) and individuals (genotypes) were closed and conserved in clonal gardens to produce quality germplasm for plantations on sodic wastelands. Genetic testing, selection and multiplication of selected material are under progress. This will optimise gains in future afforestation programmes on sodic soils. (Author)

Improving breast cancer classification with mammography, supported on an appropriate variable selection analysis

Science.gov (United States)

Pérez, Noel; Guevara, Miguel A.; Silva, Augusto

2013-02-01

This work addresses the issue of variable selection within the context of breast cancer classification with mammography. A comprehensive repository of feature vectors was used including a hybrid subset gathering image-based and clinical features. It aimed to gather experimental evidence of variable selection in terms of cardinality, type and find a classification scheme that provides the best performance over the Area Under Receiver Operating Characteristics Curve (AUC) scores using the ranked features subset. We evaluated and classified a total of 300 subsets of features formed by the application of Chi-Square Discretization, Information-Gain, One-Rule and RELIEF methods in association with Feed-Forward Backpropagation Neural Network (FFBP), Support Vector Machine (SVM) and Decision Tree J48 (DTJ48) Machine Learning Algorithms (MLA) for a comparative performance evaluation based on AUC scores. A variable selection analysis was performed for Single-View Ranking and Multi-View Ranking groups of features. Features subsets representing Microcalcifications (MCs), Masses and both MCs and Masses lesions achieved AUC scores of 0.91, 0.954 and 0.934 respectively. Experimental evidence demonstrated that classification performance was improved by combining image-based and clinical features. The most important clinical and image-based features were StromaDistortion and Circularity respectively. Other less important but worth to use due to its consistency were Contrast, Perimeter, Microcalcification, Correlation and Elongation.

New ion selective materials. Application to the selective extraction of caesium

International Nuclear Information System (INIS)

Favre-Reguillon, Alain

1996-01-01

This research thesis addresses the synthesis and assessment of ion selective materials. The first part reports the development of a general method of assessment of ion selective materials. In the second part, the author describes different methods used to insolubilize macro-cycles on hydrophilic polymers. The obtained polyurethanes are synthesised. These hydrophilic polymers display interesting complexing properties and selectivities with respect to cations of alkali metals. Then the author addresses the improvement of selectivity with respect to caesium of ion exchange resorcinol-formaldehyde resins. Different factors affecting selectivity are identified, and the concept of molecular print is used to study the improvement of selectivity. The effect of macro-cyclic structures on phenolic resins with respect to caesium is highlighted [fr

SELECTION OF BUSINESS STRATEGIES FOR QUALITY IMPROVEMENT USING FUZZY ANALYTICAL HIERARCHY PROCESS

Directory of Open Access Journals (Sweden)

Prasun Das

2010-12-01

Full Text Available Fuzzy linguistic concepts are often used to enhance the traditional analytic hierarchy process (AHP in capturing the fuzziness and subjectiveness of decision makers' judgments. In this paper, fuzzy AHP methodology is adopted for selection of the strategies for business improvement in an Indian industry as a decision making problem. Due to simplicity and effectiveness, triangular fuzzy numbers are adopted as a reference to indicate the influence strength of each element in the hierarchy structure. The confidence level and the optimistic levels of multiple decision makers are captured by using ? -cut based fuzzy number methods. This fuzzy set theory based multi-attribute decision making method is found to be quite useful and effective in industrial environment.

Improving the size- and species selectivity of cod (Gadus morhua) in demersal mixed-species trawl fisheries

DEFF Research Database (Denmark)

Krag, Ludvig Ahm

have been published in scientific journals and Paper 3 has been submitted to Fisheries Research. This review will take a broader perspective and will examine the capturing process, which is the basis for the selection process. Moreover, it discusses the existing methods and knowledge in the fields...... different species, including cod, are caught together. Demersal trawling is the predominant fishing method in Denmark, as measured by both catch value and volume. Demersal trawls also account for the highest discard rates of juvenile fish, including cod. The focus of this work was on improving......, and openings. The results show that the morphology-based simulations of size selectivity of cod can be used to explain a large part of both the within-haul and the between-haul variations previously reported from sea trials. The method can further predict the selection parameters (L50 and SR) for cod...

Improving the Classification Accuracy for Near-Infrared Spectroscopy of Chinese Salvia miltiorrhiza Using Local Variable Selection

Directory of Open Access Journals (Sweden)

Lianqing Zhu

2018-01-01

Full Text Available In order to improve the classification accuracy of Chinese Salvia miltiorrhiza using near-infrared spectroscopy, a novel local variable selection strategy is thus proposed. Combining the strengths of the local algorithm and interval partial least squares, the spectra data have firstly been divided into several pairs of classes in sample direction and equidistant subintervals in variable direction. Then, a local classification model has been built, and the most proper spectral region has been selected based on the new evaluation criterion considering both classification error rate and best predictive ability under the leave-one-out cross validation scheme for each pair of classes. Finally, each observation can be assigned to belong to the class according to the statistical analysis of classification results of the local classification model built on selected variables. The performance of the proposed method was demonstrated through near-infrared spectra of cultivated or wild Salvia miltiorrhiza, which are collected from 8 geographical origins in 5 provinces of China. For comparison, soft independent modelling of class analogy and partial least squares discriminant analysis methods are, respectively, employed as the classification model. Experimental results showed that classification performance of the classification model with local variable selection was obvious better than that without variable selection.

Direct phase selection of initial phases from single-wavelength anomalous dispersion (SAD) for the improvement of electron density and ab initio structure determination

International Nuclear Information System (INIS)

Chen, Chung-De; Huang, Yen-Chieh; Chiang, Hsin-Lin; Hsieh, Yin-Cheng; Guan, Hong-Hsiang; Chuankhayan, Phimonphan; Chen, Chun-Jung

2014-01-01

A novel direct phase-selection method to select optimized phases from the ambiguous phases of a subset of reflections to replace the corresponding initial SAD phases has been developed. With the improved phases, the completeness of built residues of protein molecules is enhanced for efficient structure determination. Optimization of the initial phasing has been a decisive factor in the success of the subsequent electron-density modification, model building and structure determination of biological macromolecules using the single-wavelength anomalous dispersion (SAD) method. Two possible phase solutions (ϕ 1 and ϕ 2 ) generated from two symmetric phase triangles in the Harker construction for the SAD method cause the well known phase ambiguity. A novel direct phase-selection method utilizing the θ DS list as a criterion to select optimized phases ϕ am from ϕ 1 or ϕ 2 of a subset of reflections with a high percentage of correct phases to replace the corresponding initial SAD phases ϕ SAD has been developed. Based on this work, reflections with an angle θ DS in the range 35–145° are selected for an optimized improvement, where θ DS is the angle between the initial phase ϕ SAD and a preliminary density-modification (DM) phase ϕ DM NHL . The results show that utilizing the additional direct phase-selection step prior to simple solvent flattening without phase combination using existing DM programs, such as RESOLVE or DM from CCP4, significantly improves the final phases in terms of increased correlation coefficients of electron-density maps and diminished mean phase errors. With the improved phases and density maps from the direct phase-selection method, the completeness of residues of protein molecules built with main chains and side chains is enhanced for efficient structure determination

Improving the selective cancer killing ability of ZnO nanoparticles using Fe doping.

Science.gov (United States)

Thurber, Aaron; Wingett, Denise G; Rasmussen, John W; Layne, Janet; Johnson, Lydia; Tenne, Dmitri A; Zhang, Jianhui; Hanna, Charles B; Punnoose, Alex

2012-06-01

This work reports a new method to improve our recent demonstration of zinc oxide (ZnO) nanoparticles (NPs) selectively killing certain human cancer cells, achieved by incorporating Fe ions into the NPs. Thoroughly characterized cationic ZnO NPs (∼6 nm) doped with Fe ions (Zn(1-x )Fe (x) O, x = 0-0.15) were used in this work, applied at a concentration of 24 μg/ml. Cytotoxicity studies using flow cytometry on Jurkat leukemic cancer cells show cell viability drops from about 43% for undoped ZnO NPs to 15% for ZnO NPs doped with 7.5% Fe. However, the trend reverses and cell viability increases with higher Fe concentrations. The non-immortalized human T cells are markedly more resistant to Fe-doped ZnO NPs than cancerous T cells, confirming that Fe-doped samples still maintain selective toxicity to cancer cells. Pure iron oxide samples displayed no appreciable toxicity. Reactive oxygen species generated with NP introduction to cells increased with increasing Fe up to 7.5% and decreased for >7.5% doping.

An improved selective sampling method

International Nuclear Information System (INIS)

Miyahara, Hiroshi; Iida, Nobuyuki; Watanabe, Tamaki

1986-01-01

The coincidence methods which are currently used for the accurate activity standardisation of radio-nuclides, require dead time and resolving time corrections which tend to become increasingly uncertain as countrates exceed about 10 K. To reduce the dependence on such corrections, Muller, in 1981, proposed the selective sampling method using a fast multichannel analyser (50 ns ch -1 ) for measuring the countrates. It is, in many ways, more convenient and possibly potentially more reliable to replace the MCA with scalers and a circuit is described employing five scalers; two of them serving to measure the background correction. Results of comparisons using our new method and the coincidence method for measuring the activity of 60 Co sources yielded agree-ment within statistical uncertainties. (author)

Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels (Conference Presentation)

Science.gov (United States)

Zhao, Jianhua; Zeng, Haishan; Kalia, Sunil; Lui, Harvey

2017-02-01

Background: Raman spectroscopy is a non-invasive optical technique which can measure molecular vibrational modes within tissue. A large-scale clinical study (n = 518) has demonstrated that real-time Raman spectroscopy could distinguish malignant from benign skin lesions with good diagnostic accuracy; this was validated by a follow-up independent study (n = 127). Objective: Most of the previous diagnostic algorithms have typically been based on analyzing the full band of the Raman spectra, either in the fingerprint or high wavenumber regions. Our objective in this presentation is to explore wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Methods: A wavenumber selection algorithm was implemented using variably-sized wavenumber windows, which were determined by the correlation coefficient between wavenumbers. Wavenumber windows were chosen based on accumulated frequency from leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected wavenumber windows using multivariate statistical analyses, including principal component and general discriminant analysis (PC-GDA) and partial least squares (PLS). A total cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included. Lesion measurements were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. Result: The area under the receiver operating characteristic curve (ROC) improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for sensitivity levels of 0.99-0.90 increased respectively from 0.17-0.65 to 0.20-0.75 by selecting specific wavenumber windows for analysis. Conclusion: Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels.

Local randomization in neighbor selection improves PRM roadmap quality

KAUST Repository

McMahon, Troy; Jacobs, Sam; Boyd, Bryan; Tapia, Lydia; Amato, Nancy M.

2012-01-01

Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K'), that first computes the K' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

Local randomization in neighbor selection improves PRM roadmap quality

KAUST Repository

McMahon, Troy

2012-10-01

Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K\\'), that first computes the K\\' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K\\'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

Improving Blast Resistance of a Thermo-Sensitive Genic Male Sterile Rice Line GD-8S by Molecular Marker-Assisted Selection

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Wu-ge LIU

2008-09-01

Full Text Available The broad-spectrum blast resistance gene Pi-1, from donor line BL122, was introduced into a thermo-sensitive genic male sterile rice line GD-8S, which possessed good grain quality but high susceptibility to rice blast, by using backcross breeding and molecular marker-assisted selection. Five elite improved male sterile lines, RGD8S-1, RGD8S-2, RGD8S-3, RGD8S-4 and RGD8S-5, were selected based on the results of molecular marker analysis, spikelet sterility, recovery rate of genetic background and agronomic traits. Thirty-three representative blast isolates collected from Guangdong Province, China were used to inoculate the improved lines and the original line GD-8S artificially. The resistance frequencies of the improved lines ranged from 76.47% to 100%, much higher than that of the original line GD-8S (9.09%. On the agronomic characters, there were no significant differences between the improved lines and GD-8S except for flag leaf length and panicle number per plant. The improved lines could be used for breeding hybrid rice with high blast resistance.

Improved methods in Agrobacterium-mediated transformation of almond using positive (mannose/pmi) or negative (kanamycin resistance) selection-based protocols.

Science.gov (United States)

Ramesh, Sunita A; Kaiser, Brent N; Franks, Tricia; Collins, Graham; Sedgley, Margaret

2006-08-01

A protocol for Agrobacterium-mediated transformation with either kanamycin or mannose selection was developed for leaf explants of the cultivar Prunus dulcis cv. Ne Plus Ultra. Regenerating shoots were selected on medium containing 15 muM kanamycin (negative selection), while in the positive selection strategy, shoots were selected on 2.5 g/l mannose supplemented with 15 g/l sucrose. Transformation efficiencies based on PCR analysis of individual putative transformed shoots from independent lines relative to the initial numbers of leaf explants tested were 5.6% for kanamycin/nptII and 6.8% for mannose/pmi selection, respectively. Southern blot analysis on six randomly chosen PCR-positive shoots confirmed the presence of the nptII transgene in each, and five randomly chosen lines identified to contain the pmi transgene by PCR showed positive hybridisation to a pmi DNA probe. The positive (mannose/pmi) and the negative (kanamycin) selection protocols used in this study have greatly improved transformation efficiency in almond, which were confirmed with PCR and Southern blot. This study also demonstrates that in almond the mannose/pmi selection protocol is appropriate and can result in higher transformation efficiencies over that of kanamycin/nptII selection protocols.

Improving catalytic selectivity through control of adsorption orientation

Science.gov (United States)

Pang, Simon H.

In this thesis, we present an investigation, starting from surface science experiments, leading to design of supported catalysts, of how adsorption orientation can be used to affect reaction selectivity of highly functional molecules. The surface chemistry of furfuryl alcohol and benzyl alcohol and their respective aldehydes was studied on a Pd(111) single-crystal surface under ultra-high vacuum conditions. Temperature-programmed desorption experiments showed that synergistic chemistry existed between the aromatic ring and the oxygen-containing functional group, each allowing the other to participate in reaction pathways that a monofunctional molecule could not. Most important of these was a deoxygenation reaction that occurred more readily when the surface was crowded by the highest exposures. High-resolution electron energy loss spectroscopy revealed that at these high exposures, molecules were oriented upright on the surface, with the aromatic function extending into vacuum. In contrast, at low exposures, molecules were oriented flat on the surface. The upright adsorption geometry was correlated with deoxygenation, whereas the flat-lying geometry was correlated with decarbonylation. The insight gained from surface science experiments was utilized in catalyst design. Self-assembled monolayers of alkanethiolates were used to systematically reduce the average surface ensemble size, and the reaction selectivity was tracked. When a sparsely-packed monolayer was used, such as one formed by 1-adamantanethiol, the reactant furfural was still able to lie flat on the surface and the reaction selectivity was similar to that of the uncoated catalyst. However, when a densely-packed monolayer, formed by 1-octadecanethiol, was used, furfural was not able to adsorb flat on the surface and instead adopted an upright conformation, leading to a drastic increase in aldehyde hydrogenation and hydrodeoxygenation reaction selectivity. Using an even higher sulfur coverage from a

Quality Improvement in Critical Care: Selection and Development of Quality Indicators

Science.gov (United States)

Martin, Claudio M.; Project, The Quality Improvement in Critical Care

2016-01-01

Background. Caring for critically ill patients is complex and resource intensive. An approach to monitor and compare the function of different intensive care units (ICUs) is needed to optimize outcomes for patients and the health system as a whole. Objective. To develop and implement quality indicators for comparing ICU characteristics and performance within and between ICUs and regions over time. Methods. Canadian jurisdictions with established ICU clinical databases were invited to participate in an iterative series of face-to-face meetings, teleconferences, and web conferences. Eighteen adult intensive care units across 14 hospitals and 5 provinces participated in the process. Results. Six domains of ICU function were identified: safe, timely, efficient, effective, patient/family satisfaction, and staff work life. Detailed operational definitions were developed for 22 quality indicators. The feasibility was demonstrated with the collection of 3.5 years of data. Statistical process control charts and graphs of composite measures were used for data display and comparisons. Medical and nursing leaders as well as administrators found the system to be an improvement over prior methods. Conclusions. Our process resulted in the selection and development of 22 indicators representing 6 domains of ICU function. We have demonstrated the feasibility of such a reporting system. This type of reporting system will demonstrate variation between units and jurisdictions to help identify and prioritize improvement efforts. PMID:27493476

A Very Compact AES-SPIHT Selective Encryption Computer Architecture Design with Improved S-Box

Directory of Open Access Journals (Sweden)

Jia Hao Kong

2013-01-01

Full Text Available The “S-box” algorithm is a key component in the Advanced Encryption Standard (AES due to its nonlinear property. Various implementation approaches have been researched and discussed meeting stringent application goals (such as low power, high throughput, low area, but the ultimate goal for many researchers is to find a compact and small hardware footprint for the S-box circuit. In this paper, we present our version of minimized S-box with two separate proposals and improvements in the overall gate count. The compact S-box is adopted with a compact and optimum processor architecture specifically tailored for the AES, namely, the compact instruction set architecture (CISA. To further justify and strengthen the purpose of the compact crypto-processor’s application, we have also presented a selective encryption architecture (SEA which incorporates the CISA as a part of the encryption core, accompanied by the set partitioning in hierarchical trees (SPIHT algorithm as a complete selective encryption system.

Improving Naive Bayes with Online Feature Selection for Quick Adaptation to Evolving Feature Usefulness

Energy Technology Data Exchange (ETDEWEB)

Pon, R K; Cardenas, A F; Buttler, D J

2007-09-19

The definition of what makes an article interesting varies from user to user and continually evolves even for a single user. As a result, for news recommendation systems, useless document features can not be determined a priori and all features are usually considered for interestingness classification. Consequently, the presence of currently useless features degrades classification performance [1], particularly over the initial set of news articles being classified. The initial set of document is critical for a user when considering which particular news recommendation system to adopt. To address these problems, we introduce an improved version of the naive Bayes classifier with online feature selection. We use correlation to determine the utility of each feature and take advantage of the conditional independence assumption used by naive Bayes for online feature selection and classification. The augmented naive Bayes classifier performs 28% better than the traditional naive Bayes classifier in recommending news articles from the Yahoo! RSS feeds.

Improving Selectivity of 1D Bragg Resonator Using Coupling of Propagating and Trapped Waves

CERN Document Server

Ginzburg, N S; Peskov, Nikolay Yu; Sergeev, A S

2004-01-01

A novel 1D Bragg resonator based on coupling propagated and locked (quasi cut-off) modes should be tested in a JINR- IAP FEM-oscillator to improve selectivity over the transverse mode index. In this scheme the electron beam interacts with only propagating wave, and the latter is coupled with a quasi cut-off mode. This coupling can be realized by either helical or azimuthally-symmetric corrugation. The quasi cut-off mode provides the feedback in the system leading to the absolute instability and the self-excitation of the whole system while efficiency in the steady-state regime of generation is almost completely determined by the propagating mode, synchronous to the beam. Analytical consideration and numerical simulation show that the efficiency of such an FEM can be rather high. The main advantage of this scheme is provision of higher selectivity over the transverse mode index than traditional scheme of Bragg FEL that encourage increasing operating frequency for fixed transverse size of the interaction space.

Data-Driven Derivation of an "Informer Compound Set" for Improved Selection of Active Compounds in High-Throughput Screening.

Science.gov (United States)

Paricharak, Shardul; IJzerman, Adriaan P; Jenkins, Jeremy L; Bender, Andreas; Nigsch, Florian

2016-09-26

Despite the usefulness of high-throughput screening (HTS) in drug discovery, for some systems, low assay throughput or high screening cost can prohibit the screening of large numbers of compounds. In such cases, iterative cycles of screening involving active learning (AL) are employed, creating the need for smaller "informer sets" that can be routinely screened to build predictive models for selecting compounds from the screening collection for follow-up screens. Here, we present a data-driven derivation of an informer compound set with improved predictivity of active compounds in HTS, and we validate its benefit over randomly selected training sets on 46 PubChem assays comprising at least 300,000 compounds and covering a wide range of assay biology. The informer compound set showed improvement in BEDROC(α = 100), PRAUC, and ROCAUC values averaged over all assays of 0.024, 0.014, and 0.016, respectively, compared to randomly selected training sets, all with paired t-test p-values agnostic fashion. This approach led to a consistent improvement in hit rates in follow-up screens without compromising scaffold retrieval. The informer set is adjustable in size depending on the number of compounds one intends to screen, as performance gains are realized for sets with more than 3,000 compounds, and this set is therefore applicable to a variety of situations. Finally, our results indicate that random sampling may not adequately cover descriptor space, drawing attention to the importance of the composition of the training set for predicting actives.

Competitive Strategies and Improved Performance of Selected Nigeria Telecommunication Companies

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Waidi Adeniyi Akingbad

2014-01-01

Full Text Available Abstract The influence of globalization in telecommunication companies has greatly increased the level of competition in the industry and they are forced to be competitive to survive. Different types of strategies are put in place in order to be profitable and competitive. All these strategies are directed to attract, retain and maintain customers for continuous profitability. However, majority of them hardly measure the impact of their strategic innovation on their customers. The paper seeks to explore the influence of competitive strategies embarked upon by selected telecommunication companies in Nigeria on their performance. The paper also examines how competitive strategies could be implemented for improved customer satisfaction, retention and loyalty. Three null hypotheses were postulated to test the relationship between lower prices and customer satisfaction, uninterrupted trunk services and customer loyalty, and customer complaint handling and retention. Only customers using telephone service were selected as respondents from Lagos State. The state was stratified in to 20 local government council area and questionnaires were distributed to 125 respondents in each of them. The completion rate of the questionnaire in each of them is between 103 and 110. Survey research design was adopted to carry out the study. A structured questionnaire was designed and validated through the construct validity and tested for confirmation using the KMO measure of sampling adequacy. It was also made reliable using Cronbach’s Alpha test. From the study, findings revealed relationship between competitive strategies and customer satisfaction, retention and loyalty. The findings revealed that there is a relationship between competitive strategies, its constituents and performance of telecommunication companies. It is recommended that universal mobile telecommunication services (UMTS operators should adopt the culture of competitive strategies since it can

Low concentrations of Rhodamine-6G selectively destroy tumor cells and improve survival of melanoma transplanted mice.

Science.gov (United States)

Kutushov, M; Gorelik, O

2013-01-01

Rhodamine-6G is a fluorescent dye binding to mitochondria, thus reducing the intact mitochondria number and inhibiting mitochondrial metabolic activity. Resultantly, the respiratory chain functioning becomes blocked, the cell "suffocated" and eventually destroyed. Unlike normal cells, malignant cells demonstrate a priori reduced mitochondrial numbers and aberrant metabolism. Therefore, a turning point might exist, when Rhodamine-induced loss of active mitochondria would selectively destroy malignant, but spare normal cells. Various malignant vs. non-malignant cell lines were cultured with Rhodamine-6G at different concentrations. In addition, C57Bl mice were implanted with B16-F10 melanoma and treated with Rhodamine-6G at different dosage/time regimens. Viability and proliferation of cultured tumor cells were time and dose-dependently inhibited, up to 90%, by Rhodamine-6G, with profound histological signs of cell death. By contrast, inhibition of normal control cell proliferation hardly exceeded 15-17%. Melanoma-transplanted mice receiving Rhodamine-6G demonstrated prolonged survival, improved clinical parameters, inhibited tumor growth and metastases count, compared to their untreated counterparts. Twice-a-week 10-6M Rhodamine-6G regimen yielded the most prominent results. We conclude that malignant, but not normal, cells are selectively destroyed by low doses of Rhodamine-6G. In vivo, such treatment selectively suppresses tumor progression and dissemination, thus improving prognosis. We suggest that selective anti-tumor properties of Rhodamine-6G are based on unique physiologic differences in energy metabolism between malignant and normal cells. If found clinically relevant, low concentrations of Rhodamine-6G might be useful for replacing, or backing up, more aggressive nonselective chemotherapeutic compounds.

Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

Science.gov (United States)

Quilty, J.; Adamowski, J. F.

2015-12-01

Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

Sperm selection in natural conception: what can we learn from Mother Nature to improve assisted reproduction outcomes?

Science.gov (United States)

Sakkas, Denny; Ramalingam, Mythili; Garrido, Nicolas; Barratt, Christopher L.R.

2015-01-01

BACKGROUND In natural conception only a few sperm cells reach the ampulla or the site of fertilization. This population is a selected group of cells since only motile cells can pass through cervical mucus and gain initial entry into the female reproductive tract. In animals, some studies indicate that the sperm selected by the reproductive tract and recovered from the uterus and the oviducts have higher fertilization rates but this is not a universal finding. Some species show less discrimination in sperm selection and abnormal sperm do arrive at the oviduct. In contrast, assisted reproductive technologies (ART) utilize a more random sperm population. In this review we contrast the journey of the spermatozoon in vivo and in vitro and discuss this in the context of developing new sperm preparation and selection techniques for ART. METHODS A review of the literature examining characteristics of the spermatozoa selected in vivo is compared with recent developments in in vitro selection and preparation methods. Contrasts and similarities are presented. RESULTS AND CONCLUSIONS New technologies are being developed to aid in the diagnosis, preparation and selection of spermatozoa in ART. To date progress has been frustrating and these methods have provided variable benefits in improving outcomes after ART. It is more likely that examining the mechanisms enforced by nature will provide valuable information in regard to sperm selection and preparation techniques in vitro. Identifying the properties of those spermatozoa which do reach the oviduct will also be important for the development of more effective tests of semen quality. In this review we examine the value of sperm selection to see how much guidance for ART can be gleaned from the natural selection processes in vivo. PMID:26386468

Marker-assisted selection for improving quantitative traits of forage crops

International Nuclear Information System (INIS)

Dolstra, O.; Denneboom, C.; Vos, Ab L.F. de; Loo, E.N. van

2007-01-01

This chapter provides an example of using marker-assisted selection (MAS) for breeding perennial ryegrass (Lolium perenne), a pasture species. A mapping study had shown the presence of quantitative trait loci (QTL) for seven component traits of nitrogen use efficiency (NUE). The NUE-related QTL clustered in five chromosomal regions. These QTL were validated through divergent marker selection in an F 2 population. The criterion used for plant selection was a summation index based on the number of positive QTL alleles. The evaluation studies showed a strong indirect response of marker selection on NUE. Marker selection using a summation index such as applied here proved to be very effective for difficult and complex quantitative traits such as NUE. The strategy is easily applicable in outbreeding crops to raise the frequency of several desirable alleles simultaneously. (author)

Genetic improvement of vegetables

International Nuclear Information System (INIS)

Jaramillo Vasquez, J.G.

2001-01-01

Some genetic bases of the improvement of vegetables are given. The objectives of the genetic improvement and the fundamental stages of this process are done. The sources of genetic variation are indicated and they are related the reproduction systems of the main horticultural species. It is analyzed the concept of genetic inheritance like base to determine the procedures more appropriate of improvement. The approaches are discussed, has more than enough phenotypic value, genetic action and genotypic variance; Equally the heredability concepts and value of improvement. The conventional methods of improvement are described, like they are: the introduction of species or varieties, the selection, the pure line, the pedigree method, the selection for families, the recurrent selection, the selection for unique seed, the haploids method, the selection for heterosis and the synthetic varieties

Frequency Selective Non-Linear Blending to Improve Image Quality in Liver CT.

Science.gov (United States)

Bongers, M N; Bier, G; Kloth, C; Schabel, C; Fritz, J; Nikolaou, K; Horger, M

2016-12-01

Purpose: To evaluate the effects of a new frequency selective non-linear blending (NLB) algorithm on the contrast resolution of liver CT with low intravascular concentration of iodine contrast. Materials and Methods: Our local ethics committee approved this retrospective study. The informed consent requirement was waived. CT exams of 25 patients (60 % female, mean age: 65 ± 16 years of age) with late phase CT scans of the liver were included as a model for poor intrahepatic vascular contrast enhancement. Optimal post-processing settings to enhance the contrast of hepatic vessels were determined. Outcome variables included signal-to-noise (SNR) and contrast-to-noise ratios (CNR) of hepatic vessels and SNR of liver parenchyma of standard and post-processed images. Image quality was quantified by two independent readers using Likert scales. Results: The post-processing settings for the visualization of hepatic vasculature were optimal at a center of 115HU, delta of 25HU, and slope of 5. Image noise was statistically indifferent between standard and post-processed images. The CNR between the hepatic vasculature (HV) and liver parenchyma could be significantly increased for liver veins (CNR Standard 1.62 ± 1.10, CNR NLB 3.6 ± 2.94, p = 0.0002) and portal veins (CNR Standard 1.31 ± 0.85, CNR NLB 2.42 ± 3.03, p = 0.046). The SNR of liver parenchyma was significantly higher on post-processed images (SNR NLB 11.26 ± 3.16, SNR Standard 8.85 ± 2.27, p = 0.008). The overall image quality and depiction of HV were significantly higher on post-processed images (NLB DHV : 4 [3 - 4.75], S tandardDHV : 2 [1.3 - 2.5], p = algorithm increases the contrast resolution of liver CT and can improve the visibility of the hepatic vasculature in the setting of a low contrast ratio between vessels and the parenchyma. Key Points: • Using the new frequency selective non-linear blending algorithm is feasible in contrast

Fasxiator, a novel factor XIa inhibitor from snake venom, and its site-specific mutagenesis to improve potency and selectivity.

Science.gov (United States)

Chen, W; Carvalho, L P D; Chan, M Y; Kini, R M; Kang, T S

2015-02-01

Bleeding remains a major limitation of standard anticoagulant drugs that target the extrinsic and common coagulation pathways. Recently, intrinsic coagulation factors are increasingly being investigated as alternative targets for developing anticoagulant drugs with lower bleeding risk. Goals were to (i) identify novel anticoagulants selectively targeting intrinsic coagulation pathway and (ii) characterize and further improve the properties of the identified anticoagulants. We have isolated and sequenced a specific factor XIa (FXIa) inhibitor, henceforth named Fasxiator, from the venom of the banded krait snake, Bungarus fasciatus. It is a Kunitz-type protease inhibitor that prolonged activated partial thromboplastin time without significant effects on prothrombin time. Fasxiator was recombinantly expressed (rFasxiator), purified, and characterized to be a slow-type inhibitor of FXIa that exerts its anticoagulant activities (doubled activated partial thromboplastin time at ~ 3 μmol L(-1) ) by selectively inhibiting human FXIa in in vitro assays. A series of mutants were subsequently generated to improve the potency and selectivity of recombinant rFasxiator. rFasxiatorN17R,L19E showed the best balance between potency (IC50 ~ 1 nmol L(-1) ) and selectivity (> 100 times). rFasxiatorN17R,L19E is a competitive slow-type inhibitor of FXIa (Ki  = 0.86 nmol L(-1) ), possesses anticoagulant activity that is ~ 10 times stronger in human plasma than in murine plasma, and prolonged the occlusion time of mice carotid artery in FeCl3 -induced thrombosis models. We have isolated an exogenous FXIa specific inhibitor, engineered it to improve its potency by ~ 1000 times and demonstrated its in vitro and in vivo efficacy. These proof-of-principle data supported the further development of Fasxiator as a novel anticoagulant candidate. © 2014 International Society on Thrombosis and Haemostasis.

An Improved Particle Swarm Optimization for Selective Single Machine Scheduling with Sequence Dependent Setup Costs and Downstream Demands

Directory of Open Access Journals (Sweden)

Kun Li

2015-01-01

Full Text Available This paper investigates a special single machine scheduling problem derived from practical industries, namely, the selective single machine scheduling with sequence dependent setup costs and downstream demands. Different from traditional single machine scheduling, this problem further takes into account the selection of jobs and the demands of downstream lines. This problem is formulated as a mixed integer linear programming model and an improved particle swarm optimization (PSO is proposed to solve it. To enhance the exploitation ability of the PSO, an adaptive neighborhood search with different search depth is developed based on the decision characteristics of the problem. To improve the search diversity and make the proposed PSO algorithm capable of getting out of local optimum, an elite solution pool is introduced into the PSO. Computational results based on extensive test instances show that the proposed PSO can obtain optimal solutions for small size problems and outperform the CPLEX and some other powerful algorithms for large size problems.

Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

Science.gov (United States)

Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro

2016-12-15

MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.

Improved Medium for Selecting Nitrate-Nonutilizing (nit) Mutants of Verticillium dahliae.

Science.gov (United States)

Korolev, N; Katan, T

1997-10-01

ABSTRACT Nitrate-nonutilizing (nit) mutants are commonly used to determine vegetative compatibility between isolates of Verticillium dahliae by complementation (heterokaryon) testing. These mutants emerge spontaneously as chlorate-resistant sectors growing out of partially restricted, wild-type colonies on chlorate-amended media. The commonly used chlorate media are based on minimal medium (MMC) or cornmeal agar (CMC), amended with potassium chlorate. nit mutants recovered on these media constituted 10 to 36%(on MMC) and 25 to 45%(on CMC) of the apparently resistant sectors. An improved water agar chlorate medium (WAC) is described that is more effective for selecting chlorate-resistant nit mutants. WAC medium consists of agar (2%), glucose (0.02%), and potassium chlorate (2 to 5%). On WAC, growth of most V. dahliae isolates was strongly inhibited, and 66 to 100%(average >80%) of the chlorate-resistant sectors formed were nit mutants. Most mutants were characterized as nit1, and about 6% as NitM.

An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.

Science.gov (United States)

Kumar, Shiu; Sharma, Alok; Tsunoda, Tatsuhiko

2017-12-28

Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7-30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine. The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets. Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.

Improving accuracy of overhanging structures for selective laser melting through reliability characterization of single track formation on thick powder beds

DEFF Research Database (Denmark)

Mohanty, Sankhya; Hattel, Jesper Henri

2016-01-01

Repeatability and reproducibility of parts produced by selective laser melting is a standing issue, and coupled with a lack of standardized quality control presents a major hindrance towards maturing of selective laser melting as an industrial scale process. Consequently, numerical process...... modelling has been adopted towards improving the predictability of the outputs from the selective laser melting process. Establishing the reliability of the process, however, is still a challenge, especially in components having overhanging structures.In this paper, a systematic approach towards...... establishing reliability of overhanging structure production by selective laser melting has been adopted. A calibrated, fast, multiscale thermal model is used to simulate the single track formation on a thick powder bed. Single tracks are manufactured on a thick powder bed using same processing parameters...

Improvement of potato tolerance to salinity using tissue culture techniques and irradiation with in vitro selection

International Nuclear Information System (INIS)

Al-Safadi, B.; Arabi, M. I. E.

2006-01-01

A mutation breeding program was conducted to improve potato (Solanum tuberosum) tolerance to salinity. In vitro cultured explants from potato cvs. Draga, Diamant, Spunta were irradiated with gamma doses 25, 30, and 35 Gy. Mutants were isolated to get rid of chimeral tissues and subsequently propagated for in vitro and pot selection pressure. Cultivar Sponta produced the highest number of tolerant plants (4) and only one plant was obtained from Diamant. (authors)

Direct phase selection of initial phases from single-wavelength anomalous dispersion (SAD) for the improvement of electron density and ab initio structure determination.

Science.gov (United States)

Chen, Chung-De; Huang, Yen-Chieh; Chiang, Hsin-Lin; Hsieh, Yin-Cheng; Guan, Hong-Hsiang; Chuankhayan, Phimonphan; Chen, Chun-Jung

2014-09-01

Optimization of the initial phasing has been a decisive factor in the success of the subsequent electron-density modification, model building and structure determination of biological macromolecules using the single-wavelength anomalous dispersion (SAD) method. Two possible phase solutions (φ1 and φ2) generated from two symmetric phase triangles in the Harker construction for the SAD method cause the well known phase ambiguity. A novel direct phase-selection method utilizing the θ(DS) list as a criterion to select optimized phases φ(am) from φ1 or φ2 of a subset of reflections with a high percentage of correct phases to replace the corresponding initial SAD phases φ(SAD) has been developed. Based on this work, reflections with an angle θ(DS) in the range 35-145° are selected for an optimized improvement, where θ(DS) is the angle between the initial phase φ(SAD) and a preliminary density-modification (DM) phase φ(DM)(NHL). The results show that utilizing the additional direct phase-selection step prior to simple solvent flattening without phase combination using existing DM programs, such as RESOLVE or DM from CCP4, significantly improves the final phases in terms of increased correlation coefficients of electron-density maps and diminished mean phase errors. With the improved phases and density maps from the direct phase-selection method, the completeness of residues of protein molecules built with main chains and side chains is enhanced for efficient structure determination.

Experience from a multi-country initiative to improve the monitoring of selected reproductive health indicators in Africa.

Science.gov (United States)

Barreix, Maria; Tunçalp, Özge; Mutombo, Namuunda; Adegboyega, Ayotunde A; Say, Lale

2017-05-01

Universal access to sexual and reproductive health remains part of the unfinished business of global development in Africa. To achieve it, health interventions should be monitored using programmatic indicators. WHO's Strengthening Measurement of Reproductive Health Indicators in Africa initiative, implemented in Ghana, Nigeria, Kenya, Uganda, and Zimbabwe, aimed to improve national information systems for routine monitoring of reproductive health indicators. Participating countries developed action plans employing a two-pronged strategy: (1) revising, standardizing, and harmonizing existing reproductive health indicators captured through routine information-systems; and (2) building data-collection capacity through training and supervision at select pilot sites. Country teams evaluated existing and new indicators, and outlined barriers to strengthening routine measurement. Activities included updating abortion-care guidelines (spontaneous and induced abortions), providing training on laws surrounding induced abortions, and improving feedback mechanisms. The country teams updated monitoring and evaluation frameworks, and attempted to build recording/reporting capacity in selected pilot areas. Barriers to implementing the initiative that were encountered included restrictive induced-abortion laws, staff turn-over, and administrative delays, including low capacity among healthcare staff and competing priorities for staff time. The areas identified for further improvement were up-scaling programs to a national level, creating scorecards to record data, increasing collaborations with the private sector, conducting related costing exercises, and performing ex-post evaluations. © 2017 World Health Organization; licensed by Wiley on behalf of International Federation of Gynecology and Obstetrics.

Improving the economy-of-scale of small organic rankine cycle systems through appropriate working fluid selection

International Nuclear Information System (INIS)

White, Martin; Sayma, Abdulnaser I.

2016-01-01

Highlights: • Novel system model coupling turbine and ORC system performance. • Contour plots to characterise working fluid and turbine performance. • Changing working fluid can expand pump and turbine operating envelope. • Possible to improve the economy-of-scale through optimal working fluid selection. - Abstract: Organic Rankine cycles (ORC) are becoming a major research area within the field of sustainable energy systems. However, a major challenge facing the widespread implementation of small and mini-scale ORC systems is the economy-of-scale. To overcome this challenge requires single components that can be manufactured in large volumes and then implemented into a wide variety of different applications where the heat source conditions may vary. The aim of this paper is to investigate whether working fluid selection can improve the current economy-of-scale by enabling the same system components to be used in multiple ORC systems. This is done through coupling analysis and optimisation of the energy process, with a performance map for a small-scale ORC radial turbine. The performance map, obtained using CFD, is adapted to account for additional loss mechanisms not accounted for in the original CFD simulation before being non-dimensionalised using a modified similitude theory developed for subsonic ORC turbines. The updated performance map is then implemented into a thermodynamic model, enabling the construction of a single performance contour that displays the range of heat source conditions that can be accommodated by the existing turbine whilst using a particular working fluid. Constructing this performance map for a range of working fluids, this paper demonstrates that through selecting a suitable working fluid, the same turbine can efficiently utilise heat sources between 360 and 400 K, with mass flow rates ranging between 0.5 and 2.75 kg/s respectively. This corresponds to using the same turbine in ORC applications where the heat available ranges

Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma.

Science.gov (United States)

Thomaz, Ricardo de Lima; Carneiro, Pedro Cunha; Bonin, João Eliton; Macedo, Túlio Augusto Alves; Patrocinio, Ana Claudia; Soares, Alcimar Barbosa

2018-05-01

Detection of early hepatocellular carcinoma (HCC) is responsible for increasing survival rates in up to 40%. One-class classifiers can be used for modeling early HCC in multidetector computed tomography (MDCT), but demand the specific knowledge pertaining to the set of features that best describes the target class. Although the literature outlines several features for characterizing liver lesions, it is unclear which is most relevant for describing early HCC. In this paper, we introduce an unconstrained GA feature selection algorithm based on a multi-objective Mahalanobis fitness function to improve the classification performance for early HCC. We compared our approach to a constrained Mahalanobis function and two other unconstrained functions using Welch's t-test and Gaussian Data Descriptors. The performance of each fitness function was evaluated by cross-validating a one-class SVM. The results show that the proposed multi-objective Mahalanobis fitness function is capable of significantly reducing data dimensionality (96.4%) and improving one-class classification of early HCC (0.84 AUC). Furthermore, the results provide strong evidence that intensity features extracted at the arterial to portal and arterial to equilibrium phases are important for classifying early HCC.

Recurrent Selection and Participatory Plant Breeding for Improvement of Two Organic Open-Pollinated Sweet Corn (Zea mays L. Populations

Directory of Open Access Journals (Sweden)

Adrienne C. Shelton

2015-04-01

Full Text Available Organic growers face unique challenges when raising sweet corn, and benefit from varieties that maintain high eating quality, germinate consistently, deter insect pests, and resist diseases. Genotype by environment rank changes can occur in the performance of cultivars grown on conventional and organic farms, yet few varieties have been bred specifically for organic systems. The objective of this experiment was to evaluate the changes made to open-pollinated sweet corn populations using recurrent selection and a participatory plant breeding (PPB methodology. From 2008 to 2011, four cycles of two open-pollinated (OP sweet corn populations were selected on a certified organic farm in Minnesota using a modified ear-to-row recurrent selection scheme. Selections were made in collaboration with an organic farmer, with selection criteria based on traits identified by the farmer. In 2012 and 2013, the population cycles were evaluated in a randomized complete block design in two certified organic locations in Wisconsin, with multiple replications in each environment. Significant linear trends were found among cycles of selection for quantitative and qualitative traits, suggesting the changes were due to recurrent selection and PPB methodology for these populations. However, further improvement is necessary to satisfy the requirements for a useful cultivar for organic growers.

What can we learn from the neutron clinical experience for improving ion-beam techniques and high-LET patient selection?

International Nuclear Information System (INIS)

Wambersie, A.; Jones, D.T.L.; Gueulette, J.; Gahbauer, R.; DeLuca, P.M.

2010-01-01

Historically, improvements in radiotherapy have been mainly due to improvements in physical selectivity: beam penetration, collimation, dosimetry, treatment planning; and advances in imaging. Neutrons were the first high-LET (linear energy transfer) radiation to be used clinically and showed improvement in the differential response of radiation resistant tumors and normal tissues. The benefits of fast neutrons (and other forms of high LET radiations) are due to their biological effects: a reduction of the OER, a reduction in the differential cell radiosensitivity related to their position in the mitotic cycle, and a reduction in cellular repair capacity (thus less importance of fractionation). The poor physical selectivity of the early neutron therapy beams introduced a systematic bias in comparison with the photon treatments and created a negative perception for neutron therapy. However, significant improvements in the neutron therapy equipment resulted in a physical selectivity similar to modern MV photon therapy. The tumor types or sites where the best therapeutic results were obtained included inoperable or recurrent salivary gland tumors locally extended prostatic adenocarcinomas, and slowly growing well-differentiated sarcomas. The benefit of neutrons for some other well-defined groups of patients was demonstrated in randomized trials. It was estimated that about 20 % of all radiotherapy patients could benefit from fast neutrons (if neutrons are delivered under satisfactory physical conditions). An important issue for fast neutron therapy is the selection of the types of patients who could most benefit from high-LET radiations. The same issue is raised today with other high-LET radiations (e.g., 12 C ions). It is reasonable to assume that the same types of patients would benefit from 12 C irradiation. Of course the better physical selectivity of ion beams enhances the treatment possibilities but this is true for both the high-LET and low-LET radiations (i

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

Science.gov (United States)

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-04-01

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Selectivity/Specificity Improvement Strategies in Surface-Enhanced Raman Spectroscopy Analysis

Directory of Open Access Journals (Sweden)

Feng Wang

2017-11-01

Full Text Available Surface-enhanced Raman spectroscopy (SERS is a powerful technique for the discrimination, identification, and potential quantification of certain compounds/organisms. However, its real application is challenging due to the multiple interference from the complicated detection matrix. Therefore, selective/specific detection is crucial for the real application of SERS technique. We summarize in this review five selective/specific detection techniques (chemical reaction, antibody, aptamer, molecularly imprinted polymers and microfluidics, which can be applied for the rapid and reliable selective/specific detection when coupled with SERS technique.

Binding Mechanisms in Selective Laser Sintering and Selective Laser Melting

NARCIS (Netherlands)

Kruth, J.P.; Mercelis, P.; Van Vaerenbergh, J.; van Vaerenbergh, J.; Froyen, L.; Rombouts, M.

2005-01-01

Purpose – This paper provides an overview of the different binding mechanisms in selective laser sintering (SLS) and selective laser melting (SLM), thus improving the understanding of these processes. Design/methodology/approach – A classification of SLS/SLM processes was developed, based on the

Selection procedures in sports: Improving predictions of athletes’ future performance

NARCIS (Netherlands)

den Hartigh, Jan Rudolf; Niessen, Anna; Frencken, Wouter; Meijer, Rob R.

The selection of athletes has been a central topic in sports sciences for decades. Yet, little consideration has been given to the theoretical underpinnings and predictive validity of the procedures. In this paper, we evaluate current selection procedures in sports given what we know from the

Characterizing the Suitability of Selected Indigenous Soil Improving Legumes in a Humid Tropical Environment Using Shoot and Root Attributes

Directory of Open Access Journals (Sweden)

Anikwe, MAN.

2003-01-01

Full Text Available We studied the biomass accumulation, root length, nodulation, and chemical composition of roots and shoot of ten indigenous soil improving legumes in a humid tropical ecosystem with the view to selecting species for soil improvement programmes. Two cultivars of Vigna unguiculata, and one each of Glycine max, Arachis hypogaea, Crotararia ochroleuca, Cajanus cajan, Pueraria phaseoloides, Lablab purpureus, Mucuna pruriens and Vigna subterranea as treatments were planted in 20 kg pots containing soil from an Oxic paleustalf in Nigeria. The pots were arranged in randomized complete block layout with three replications in a greenhouse at IITA Ibadan, Nigeria. Results from the work show that M. pruriens and C. cajan produced the highest quantity of biomass. Root elongation was highest in M. pruriens whereas A. hypogaea produced the most root nodules with native rhizobia. The highest quantity of nodule dry weight was produced by A. hypogaea and P. phaseoloides whereas most of the legumes except G. max and P. phaseoloides had high and statistically comparable N content of between 2.36 and 3.34 mg.kg-1 N. The results show that the legumes have different root and shoot characteristics, which should be taken into consideration when selecting species for soil improvement programmes.

Single-layer centrifugation through colloid selects improved quality of epididymal cat sperm.

Science.gov (United States)

Chatdarong, K; Thuwanut, P; Morrell, J M

2010-06-01

The objectives were to determine the: 1) extent of epithelial and red blood cell contamination in epididymal cat sperm samples recovered by the cutting method; 2) efficacy of simple washing, single-layer centrifugation (SLC), and swim-up for selecting epididymal cat sperm; and 3) effects of freezing and thawing on cat sperm selected by various techniques. Ten unit samples were studied; each contained sperm from the cauda epididymides of four cats (total, approximately 200 x 10(6) sperm) and was equally allocated into four treatments: 1) simple washing, 2) single-layer centrifugation through colloid prior to cryopreservation (SLC-PC), 3) single-layer centrifugation through colloid after cryopreservation (SLC-AC), and 4) swim-up. Centrifugation (300 x g for 20 min) was done for all methods. The SLC-PC had a better recovery rate than the SLC-AC and swim-up methods (mean+/-SD of 16.4+/-8.7, 10.7+/-8.9, and 2.3+/-1.7%, respectively; Pblood cell contamination than simple washed samples (0.02+/-0.01, 0.02+/-0.04, 0.03+/-0.04, and 0.44+/-0.22 x 10(6) cells/mL, respectively; P0.05), SLC-PC yielded the highest percentage of sperm with normal midpieces and tails (P0.05). In conclusion, both SLC-PC and swim-up improved the quality of epididymal cat sperm, including better morphology, membrane and DNA integrity, and removal of cellular contamination. However, SLC had a better sperm recovery rate than swim-up. 2010 Elsevier Inc. All rights reserved.

Improved Screening Method for the Selection of Wine Yeasts Based on Their Pigment Adsorption Activity

Directory of Open Access Journals (Sweden)

Andrea Caridi

2013-01-01

Full Text Available The aim of this research is to improve an existing low-cost and simple but consistent culturing technique for measuring the adsorption of grape skin pigments on yeasts, comprising: (i growing yeasts in Petri dishes on chromogenic grape-skin-based medium, (ii photographing the yeast biomass, (iii measuring its red, green, and blue colour components, and (iv performing the statistical analysis of the data. Twenty strains of Saccharomyces cerevisiae were grown on different lots of the chromogenic medium, prepared using grape skins from dark cultivars Greco Nero, Magliocco and Nero d’Avola. Microscale wine fermentation trials were also performed. Wide and significant differences among wine yeasts were observed. The chromogenic grape-skin-based medium can be prepared using any grape cultivar, thus allowing the specific selection of the most suitable strain of Saccharomyces cerevisiae for each grape must, mainly for red winemaking. The research provides a useful tool to characterize wine yeasts in relation to pigment adsorption, allowing the improvement of wine colour.

Spectral Collection of Polyethylene Pellets at nearly Cryogenic Temperature to Improve Selectivity of Raman Measurement

International Nuclear Information System (INIS)

Kim, Saetbyeol; Lee, Sanguk; Hwang, Jinyoung; Chung, Hoeil

2010-01-01

Raman spectroscopy has been extensively used for analysis of diverse polymer samples. Normally, Raman spectral collection of samples is routinely performed at room temperature for convenience. However, the feasibility of improving spectral selectivity and the resulting quantitative accuracy, when samples are measured at nearly cryogenic temperature, has not been investigated. For this purpose, we attempted to measure the density of polyethylene (PE) pellets at cryogenic temperatures and the resulting accuracies were compared with that from room temperature measurement. Initially, each of 25 PE sample was allowed to cool down to cryogenic temperature and the corresponding Raman spectra were continuously collected while the temperature of sample increased. When the temperature of sample was at cryogenic temperature, the resulting band widths were narrower compared to those at room temperature, thereby improving the accuracy of density measurement. In overall, the proposed Raman scheme is simple and efficient; therefore, it could be further applied for analysis of other polymers.

Improved Frame Mode Selection for AMR-WB+ Based on Decision Tree

Science.gov (United States)

Kim, Jong Kyu; Kim, Nam Soo

In this letter, we propose a coding mode selection method for the AMR-WB+ audio coder based on a decision tree. In order to reduce computation while maintaining good performance, decision tree classifier is adopted with the closed loop mode selection results as the target classification labels. The size of the decision tree is controlled by pruning, so the proposed method does not increase the memory requirement significantly. Through an evaluation test on a database covering both speech and music materials, the proposed method is found to achieve a much better mode selection accuracy compared with the open loop mode selection module in the AMR-WB+.

Time-lapse culture with morphokinetic embryo selection improves pregnancy and live birth chances and reduces early pregnancy loss: a meta-analysis.

Science.gov (United States)

Pribenszky, Csaba; Nilselid, Anna-Maria; Montag, Markus

2017-11-01

Embryo evaluation and selection is fundamental in clinical IVF. Time-lapse follow-up of embryo development comprises undisturbed culture and the application of the visual information to support embryo evaluation. A meta-analysis of randomized controlled trials was carried out to study whether time-lapse monitoring with the prospective use of a morphokinetic algorithm for selection of embryos improves overall clinical outcome (pregnancy, early pregnancy loss, stillbirth and live birth rate) compared with embryo selection based on single time-point morphology in IVF cycles. The meta-analysis of five randomized controlled trials (n = 1637) showed that the application of time-lapse monitoring was associated with a significantly higher ongoing clinical pregnancy rate (51.0% versus 39.9%), with a pooled odds ratio of 1.542 (P loss (15.3% versus 21.3%; OR: 0.662; P = 0.019) and a significantly increased live birth rate (44.2% versus 31.3%; OR 1.668; P = 0.009). Difference in stillbirth was not significant between groups (4.7% versus 2.4%). Quality of the evidence was moderate to low owing to inconsistencies across the studies. Selective application and variability were also limitations. Although time-lapse is shown to significantly improve overall clinical outcome, further high-quality evidence is needed before universal conclusions can be drawn. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Short communication. Evaluation of castor (Ricinus communis L.) induced mutants for possible selection in the improvement of seed yield

Energy Technology Data Exchange (ETDEWEB)

Sarwar, G.; Boota Chaudhry, M.

2008-07-01

The aim of the present work was to determine selection criteria suitable for developing castor ideotypes with high yield potentials. Nineteen M4 generation castor mutants were obtained by gamma irradiation (100 to 1000 Gy) of DS30 castor seeds, and evaluated alongside this reference variety over 2006-07 for their possible use in the improvement of castor seed yield. Days to ripening, plant height, number of spikes/plant, length of main spike, number of main spike capsules, capsule weight, 100-seed weight and seed yield per plant were recorded for each mutant. Correlation coefficients were calculated, path analyses performed, and the genetic features of the different traits were determined. A significant, positive correlation was seen between capsule weight and seed yield. The 100-seed weight showed a positive but non-significant phenotypic relationship plus a significant genotypic relationship with seed yield. Capsule weight also showed a strong direct effect on seed yield, plus a strong positive and significant genotypic correlation with this variable. More than 50% heritability was observed for all the traits studied except the 100-seed weight and capsule weight. The number of main spike capsules showed the greatest genetic advance, followed by spike length and number of spikes. Traits such as the number of capsules, spike length and number of spikes showed strong heritability and good genetic advance. These traits are therefore governed by additive genes, and for the improvement of seed yield selection may be based directly on these attributes. In conclusion, for the improvement of seed yield the main emphasis should be placed on the number of spikes and capsule weight, via the selection of the highest yielding mutants among those tested. However, spike length and 100-seed weight should also be taken into account. (Author) 18 refs.

The Use of Variable Q1 Isolation Windows Improves Selectivity in LC-SWATH-MS Acquisition.

Science.gov (United States)

Zhang, Ying; Bilbao, Aivett; Bruderer, Tobias; Luban, Jeremy; Strambio-De-Castillia, Caterina; Lisacek, Frédérique; Hopfgartner, Gérard; Varesio, Emmanuel

2015-10-02

As tryptic peptides and metabolites are not equally distributed along the mass range, the probability of cross fragment ion interference is higher in certain windows when fixed Q1 SWATH windows are applied. We evaluated the benefits of utilizing variable Q1 SWATH windows with regards to selectivity improvement. Variable windows based on equalizing the distribution of either the precursor ion population (PIP) or the total ion current (TIC) within each window were generated by an in-house software, swathTUNER. These two variable Q1 SWATH window strategies outperformed, with respect to quantification and identification, the basic approach using a fixed window width (FIX) for proteomic profiling of human monocyte-derived dendritic cells (MDDCs). Thus, 13.8 and 8.4% additional peptide precursors, which resulted in 13.1 and 10.0% more proteins, were confidently identified by SWATH using the strategy PIP and TIC, respectively, in the MDDC proteomic sample. On the basis of the spectral library purity score, some improvement warranted by variable Q1 windows was also observed, albeit to a lesser extent, in the metabolomic profiling of human urine. We show that the novel concept of "scheduled SWATH" proposed here, which incorporates (i) variable isolation windows and (ii) precursor retention time segmentation further improves both peptide and metabolite identifications.

An Improved Nested Sampling Algorithm for Model Selection and Assessment

Science.gov (United States)

Zeng, X.; Ye, M.; Wu, J.; WANG, D.

2017-12-01

Multimodel strategy is a general approach for treating model structure uncertainty in recent researches. The unknown groundwater system is represented by several plausible conceptual models. Each alternative conceptual model is attached with a weight which represents the possibility of this model. In Bayesian framework, the posterior model weight is computed as the product of model prior weight and marginal likelihood (or termed as model evidence). As a result, estimating marginal likelihoods is crucial for reliable model selection and assessment in multimodel analysis. Nested sampling estimator (NSE) is a new proposed algorithm for marginal likelihood estimation. The implementation of NSE comprises searching the parameters' space from low likelihood area to high likelihood area gradually, and this evolution is finished iteratively via local sampling procedure. Thus, the efficiency of NSE is dominated by the strength of local sampling procedure. Currently, Metropolis-Hasting (M-H) algorithm and its variants are often used for local sampling in NSE. However, M-H is not an efficient sampling algorithm for high-dimensional or complex likelihood function. For improving the performance of NSE, it could be feasible to integrate more efficient and elaborated sampling algorithm - DREAMzs into the local sampling. In addition, in order to overcome the computation burden problem of large quantity of repeating model executions in marginal likelihood estimation, an adaptive sparse grid stochastic collocation method is used to build the surrogates for original groundwater model.

Cell Adhesion Selectivity of Stent Material to improve Bio-functionality by Ion Beam Modification

Energy Technology Data Exchange (ETDEWEB)

Lee, Jaesang; Park, JUngchan; Jung, Myunghwan; Kim, Yongki [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Park, Junkyu [Bio alpha., Co. Ltd., Gimhae (Korea, Republic of)

2014-05-15

In this study, ion implantation into collagen coated Co-Cr alloy, which is a cheaper material of the artificial stent product comparing with Ti alloy, has been studied to develop small diameter artificial stent by the cell adhesion control. The size of stent was 1.6mm of the diameter and 18mm of the length. The life-time of artificial stent depends on adhesion property of endothelial-cells. We successfully controlled cell adhesion selectivity between endothelial cell and muscle cell by using collagen coated and He{sup +} ion beam irradiated Co-Cr-alloy to apply to artificial stent. But, we did not achieve the inhibition of platelet adhesion, yet by using collagen coating and He{sup +} ion beam irradiation. Based on this study, we have plan to research about separation between collagen coating effect and ion beam effect. Also, we will have more detail analysis of the mechanism of cell attachment. In recent years, ion implantation has been applied to the surface modification of prosthesis to improve blood compatibility and tissue compatibility in field of biomedical application. As well known, bio compatibility was concerned with the cell adhesion selectivity for bio-functionality. The biomedical application of ion beam technology would be used more widely in the future such as catheter and artificial graft.

Cell Adhesion Selectivity of Stent Material to improve Bio-functionality by Ion Beam Modification

International Nuclear Information System (INIS)

Lee, Jaesang; Park, JUngchan; Jung, Myunghwan; Kim, Yongki; Park, Junkyu

2014-01-01

In this study, ion implantation into collagen coated Co-Cr alloy, which is a cheaper material of the artificial stent product comparing with Ti alloy, has been studied to develop small diameter artificial stent by the cell adhesion control. The size of stent was 1.6mm of the diameter and 18mm of the length. The life-time of artificial stent depends on adhesion property of endothelial-cells. We successfully controlled cell adhesion selectivity between endothelial cell and muscle cell by using collagen coated and He + ion beam irradiated Co-Cr-alloy to apply to artificial stent. But, we did not achieve the inhibition of platelet adhesion, yet by using collagen coating and He + ion beam irradiation. Based on this study, we have plan to research about separation between collagen coating effect and ion beam effect. Also, we will have more detail analysis of the mechanism of cell attachment. In recent years, ion implantation has been applied to the surface modification of prosthesis to improve blood compatibility and tissue compatibility in field of biomedical application. As well known, bio compatibility was concerned with the cell adhesion selectivity for bio-functionality. The biomedical application of ion beam technology would be used more widely in the future such as catheter and artificial graft

Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents

Science.gov (United States)

Guo, Pi; Zeng, Fangfang; Hu, Xiaomin; Zhang, Dingmei; Zhu, Shuming; Deng, Yu; Hao, Yuantao

2015-01-01

Objectives In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this technique is prone to false positives and tends to create excessive biases. It remains challenging to develop robust variable selection methods and enhance predictability. Material and methods Two improved algorithms denoted the two-stage hybrid and bootstrap ranking procedures, both using a LASSO-type penalty, were developed for epidemiological association analysis. The performance of the proposed procedures and other methods including conventional LASSO, Bolasso, stepwise and stability selection models were evaluated using intensive simulation. In addition, methods were compared by using an empirical analysis based on large-scale survey data of hepatitis B infection-relevant factors among Guangdong residents. Results The proposed procedures produced comparable or less biased selection results when compared to conventional variable selection models. In total, the two newly proposed procedures were stable with respect to various scenarios of simulation, demonstrating a higher power and a lower false positive rate during variable selection than the compared methods. In empirical analysis, the proposed procedures yielding a sparse set of hepatitis B infection-relevant factors gave the best predictive performance and showed that the procedures were able to select a more stringent set of factors. The individual history of hepatitis B vaccination, family and individual history of hepatitis B infection were associated with hepatitis B infection in the studied residents according to the proposed procedures. Conclusions The newly proposed procedures improve the identification of

A Selection Method for COTS Systems

DEFF Research Database (Denmark)

Hedman, Jonas

new skills and methods supporting the process of evaluating and selecting information systems. This paper presents a method for selecting COTS systems. The method includes the following phases: problem framing, requirements and appraisal, and selection of systems. The idea and distinguishing feature...... behind the method is that improved understanding of organizational' ends' or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends' (e.g. improved organizational effectiveness) and ‘means' (e.g. implementing COTS systems). This way of approaching...

A novel method of selective removal of human DNA improves PCR sensitivity for detection of Salmonella Typhi in blood samples.

Science.gov (United States)

Zhou, Liqing; Pollard, Andrew J

2012-07-27

Enteric fever is a major public health problem, causing an estimated 21million new cases and 216,000 or more deaths every year. Current diagnosis of the disease is inadequate. Blood culture only identifies 45 to 70% of the cases and is time-consuming. Serological tests have very low sensitivity and specificity. Clinical samples obtained for diagnosis of enteric fever in the field generally have blood, so that even PCR-based methods, widely used for detection of other infectious diseases, are not a straightforward option in typhoid diagnosis. We developed a novel method to enrich target bacterial DNA by selective removal of human DNA from blood samples, enhancing the sensitivity of PCR tests. This method offers the possibility of improving PCR assays directly using clinical specimens for diagnosis of this globally important infectious disease. Blood samples were mixed with ox bile for selective lysis of human blood cells and the released human DNA was then digested with addition of bile resistant micrococcal nuclease. The intact Salmonella Typhi bacteria were collected from the specimen by centrifugation and the DNA extracted with QIAamp DNA mini kit. The presence of Salmonella Typhi bacteria in blood samples was detected by PCR with the fliC-d gene of Salmonella Typhi as the target. Micrococcal nuclease retained activity against human blood DNA in the presence of up to 9% ox bile. Background human DNA was dramatically removed from blood samples through the use of ox bile lysis and micrococcal nuclease for removal of mammalian DNA. Consequently target Salmonella Typhi DNA was enriched in DNA preparations and the PCR sensitivity for detection of Salmonella Typhi in spiked blood samples was enhanced by 1,000 fold. Use of a combination of selective ox-bile blood cell lysis and removal of human DNA with micrococcal nuclease significantly improves PCR sensitivity and offers a better option for improved typhoid PCR assays directly using clinical specimens in diagnosis of

Signatures of selection in tilapia revealed by whole genome resequencing.

Science.gov (United States)

Xia, Jun Hong; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Wan, Zi Yi; Li, Jiale; Lin, Haoran; Yue, Gen Hua

2015-09-16

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10-100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.

Does sex-selective abortion improve girls' well-being? Evidence from India

OpenAIRE

Hu, Luojia; Schlosser, Analía

2010-01-01

The paper studies the impact of prenatal sex selection on the well-being of girls by analyzing changes in children's nutritional status and mortality during the years since the diffusion of prenatal sex determination technologies in India. We use the ratio of male to female births in the year and state in which a child was born as a proxy for parental access to prenatal sex-selection. We find that an increase in the practice of prenatal sex selection appears to be associated with a reduction ...

Improving the Air Force Squadron Command Selection Process

Science.gov (United States)

2017-04-19

8 maturity in the unit, selectively-manned versus non-volunteer members, and individual motivations. These characteristics work in conjunction... maturity among members allows leaders to devote attention to larger problems and issues. Similarly, a solid staff of strong Senior NCOs, NCOs, and...personal interviews combined with psychological testing. Personality tests such as the Myers-Briggs Type Indicator, Judgement Index, Emotional

Selectivity improvement of positive photoionization ion mobility spectrometry for rapid detection of organophosphorus pesticides by switching dopant concentration.

Science.gov (United States)

Zhou, Qinghua; Li, Jia; Wang, Bin; Wang, Shuang; Li, Haiyang; Chen, Jinyuan

2018-01-01

Ion mobility spectrometry (IMS) opened a potential avenue for the rapid detection of organophosphorus pesticides (OPPs), though an improved selectivity of stand-alone IMS was still in high demand. In this study, a stand-alone positive photoionization ion mobility spectrometry (PP-IMS) apparatus was constructed for the rapid detection of OPPs with acetone as dopant. The photoionization of acetone molecules was induced by the ultraviolet irradiation to produce the reactant ions (Ac) 2 H + , which were employed to ionize the OPPs including fenthion, imidan, phosphamidon, dursban, dimethoate and isocarbophos via the proton transfer reaction. Due to the difference in proton affinity, the tested OPPs exhibited the different dopant-dependent manners. Based on this observation, the switching of dopant concentration was implemented to improve the selectivity of PP-IMS for OPPs detection. For instance, a mixture of fenthion, dursban and dimethoate was tested. By switching the concentration of doped acetone from 0.07 to 2.33 to 19.94mgL -1 , the ion peaks of fenthion and dursban were inhibited in succession, achieving the selective detection of dimethoate at last. In addition, another mixture of imidan and phosphamidon was initially detected by PP-IMS with a dose of 0.07mgL -1 acetone, indicating that their ion peaks were severely overlapped; when the concentration of doped acetone was switched to 19.94mgL -1 , the inhibition of imidan signals promised the accurate identification of phosphamidon in mixture. Finally, the PP-IMS in combination of switching dopant concentration was applied to detect the mixed fenthion, dursban and dimethoate in Chinese cabbage, demonstrating the applicability of proposed method to real samples. Copyright © 2017. Published by Elsevier B.V.

Nutrition Report Cards: an opportunity to improve school lunch selection.

Directory of Open Access Journals (Sweden)

Brian Wansink

Full Text Available OBJECTIVE: To explore the feasibility and implementation efficiency of Nutritional Report Cards (NRCs in helping children make healthier food choices at school. METHODS: Pilot testing was conducted in a rural New York school district (K-12. Over a five-week period, 27 parents received a weekly e-mail containing a NRC listing how many meal components (fruits, vegetables, starches, milk, snacks, and a-la-carte foods their child selected. We analyzed choices of students in the NRC group vs. the control group, both prior to and during the intervention period. Point-of-sale system data for a-la-carte items was analyzed using Generalized Least Squares regressions with clustered standard errors. RESULTS: NRCs encouraged more home conversations about nutrition and more awareness of food selections. Despite the small sample, the NRC was associated with reduced selection of some items, such as the percentage of those selecting cookies which decreased from 14.3 to 6.5 percent. Additionally, despite requiring new keys on the check-out registers to generate the NRC, checkout times increased by only 0.16 seconds per transaction, and compiling and sending the NRCs required a total weekly investment of 30 minutes of staff time. CONCLUSIONS: This test of concept suggests that NRCs are a feasible and inexpensive tool to guide children towards healthier choices.

Adaptive selection of heuristics for improving exam timetables

OpenAIRE

Burke, Edmund; Qu, Rong; Soghier, Amr

2014-01-01

This paper presents a hyper-heuristic approach which hybridises low-level heuristic moves to improve timetables. Exams which cause a soft-constraint violation in the timetable are ordered and rescheduled to produce a better timetable. It is observed that both the order in which exams are rescheduled and the heuristic moves used to reschedule the exams and improve the timetable affect the quality of the solution produced. After testing different combinations in a hybrid hyper-heuristic approac...

Improving applicant selection: identifying qualities of the unsuccessful otolaryngology resident.

Science.gov (United States)

Badran, Karam W; Kelley, Kanwar; Conderman, Christian; Mahboubi, Hossein; Armstrong, William B; Bhandarkar, Naveen D

2015-04-01

To identify the prevalence and management of problematic residents. Additionally, we hope to identify the factors associated with successful remediation of unsuccessful otolaryngology residents. Self-reported Internet and paper-based survey. An anonymous survey was distributed to 152 current and former program directors (PDs) in 2012. The factors associated with unsuccessful otolaryngology residents and those associated with the successful remediation of problematic residents were investigated. An unsuccessful resident is defined as one who quit or was removed from the program for any reason, or one whose actions resulted in criminal action or citation against their medical license after graduation from residency. Remediation is defined as an individualized program implemented to correct documented weaknesses. The overall response rate was 26% (40 PDs). Seventy-three unsuccessful or problematic residents were identified. Sixty-six problematic or unsuccessful residents were identified during residency, with 58 of 66 (88%) undergoing remediation. Thirty-one (47%) residents did not graduate. The most commonly identified factors of an unsuccessful resident were: change in specialty (21.5%), interpersonal and communication skills with health professionals (13.9%), and clinical judgment (10.1%). Characteristics of those residents who underwent successful remediation include: poor performance on in-training examination (17%, P otolaryngology PDs in this sample identified at least one unsuccessful resident. Improved methods of applicant screening may assist in optimizing otolaryngology resident selection. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Genetic Gains in Grain Yield of a Maize Population Improved through Marker Assisted Recurrent Selection under Stress and Non-stress Conditions in West Africa

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Rekiya O. Abdulmalik

2017-05-01

Full Text Available Marker-assisted recurrent selection (MARS is a breeding method used to accumulate favorable alleles that for example confer tolerance to drought in inbred lines from several genomic regions within a single population. A bi-parental cross formed from two parents that combine resistance to Striga hermonthica with drought tolerance, which was improved through MARS, was used to assess changes in the frequency of favorable alleles and its impact on inbred line improvement. A total of 200 testcrosses of randomly selected S1 lines derived from the original (C0 and advanced selection cycles of this bi-parental population, were evaluated under drought stress (DS and well-watered (WW conditions at Ikenne and under artificial Striga infestation at Abuja and Mokwa in Nigeria in 2014 and 2015. Also, 60 randomly selected S1 lines each derived from the four cycles (C0, C1, C2, C3 were genotyped with 233 SNP markers using KASP assay. The results showed that the frequency of favorable alleles increased with MARS in the bi-parental population with none of the markers showing fixation. The gain in grain yield was not significant under DS condition due to the combined effect of DS and armyworm infestation in 2015. Because the parents used for developing the bi-parental cross combined tolerance to drought with resistance to Striga, improvement in grain yield under DS did not result in undesirable changes in resistance to the parasite in the bi-parental maize population improved through MARS. MARS increased the mean number of combinations of favorable alleles in S1 lines from 114 in C0 to 124 in C3. The level of heterozygosity decreased by 15%, while homozygosity increased by 13% due to the loss of some genotypes in the population. This study demonstrated the effectiveness of MARS in increasing the frequency of favorable alleles for tolerance to drought without disrupting the level of resistance to Striga in a bi-parental population targeted as a source of improved

Genetic Gains in Grain Yield of a Maize Population Improved through Marker Assisted Recurrent Selection under Stress and Non-stress Conditions in West Africa.

Science.gov (United States)

Abdulmalik, Rekiya O; Menkir, Abebe; Meseka, Silvestro K; Unachukwu, Nnanna; Ado, Shehu G; Olarewaju, Joseph D; Aba, Daniel A; Hearne, Sarah; Crossa, Jose; Gedil, Melaku

2017-01-01

Marker-assisted recurrent selection (MARS) is a breeding method used to accumulate favorable alleles that for example confer tolerance to drought in inbred lines from several genomic regions within a single population. A bi-parental cross formed from two parents that combine resistance to Striga hermonthica with drought tolerance, which was improved through MARS, was used to assess changes in the frequency of favorable alleles and its impact on inbred line improvement. A total of 200 testcrosses of randomly selected S 1 lines derived from the original (C 0 ) and advanced selection cycles of this bi-parental population, were evaluated under drought stress (DS) and well-watered (WW) conditions at Ikenne and under artificial Striga infestation at Abuja and Mokwa in Nigeria in 2014 and 2015. Also, 60 randomly selected S 1 lines each derived from the four cycles (C 0 , C 1 , C 2 , C 3 ) were genotyped with 233 SNP markers using KASP assay. The results showed that the frequency of favorable alleles increased with MARS in the bi-parental population with none of the markers showing fixation. The gain in grain yield was not significant under DS condition due to the combined effect of DS and armyworm infestation in 2015. Because the parents used for developing the bi-parental cross combined tolerance to drought with resistance to Striga , improvement in grain yield under DS did not result in undesirable changes in resistance to the parasite in the bi-parental maize population improved through MARS. MARS increased the mean number of combinations of favorable alleles in S 1 lines from 114 in C 0 to 124 in C 3 . The level of heterozygosity decreased by 15%, while homozygosity increased by 13% due to the loss of some genotypes in the population. This study demonstrated the effectiveness of MARS in increasing the frequency of favorable alleles for tolerance to drought without disrupting the level of resistance to Striga in a bi-parental population targeted as a source of improved

Self-selected music-induced reduction of perceived exertion during moderate-intensity exercise does not interfere with post-exercise improvements in inhibitory control.

Science.gov (United States)

Tanaka, Daichi; Tsukamoto, Hayato; Suga, Tadashi; Takenaka, Saki; Hamaoka, Takafumi; Hashimoto, Takeshi; Isaka, Tadao

2018-05-26

Acute aerobic exercise improves inhibitory control (IC). This improvement is often associated with increases in perceived exertion during exercise. However, listening to music during aerobic exercise mitigates an exercise-induced increase in perceived exertion. Thus, it is hypothesized that such effects of music may interfere with exercise-induced improvements in IC. To test this hypothesis, we examined the effect of music on post-exercise IC improvements that were induced by moderate-intensity exercise. Fifteen healthy young men performed cycle ergometer exercise with music or non-music. The exercise was performed using a moderate-intensity of 60% of VO 2 peak for 30 min. The music condition was performed while listening to self-selected music. The non-music condition involved no music. To evaluate IC, the Stroop task was administered before exercise, immediately after exercise, and during the 30-min post-exercise recovery period. The rate of perceived exertion immediately before moderate-intensity exercise completed was significantly lower in music condition than in non-music condition. The IC significantly improved immediately after exercise and during the post-exercise recovery period compared to before exercise in both music and non-music conditions. The post-exercise IC improvements did not significantly differ between the two conditions. These findings indicate that self-selected music-induced mitigation of the increase in perceived exertion during moderate-intensity exercise dose not interfere with exercise-induced improvements in IC. Therefore, we suggest that listening to music may be a beneficial strategy in mitigating the increase in perceived exertion during aerobic exercise without decreasing the positive effects on IC. Copyright © 2018 Elsevier Inc. All rights reserved.

Improving the food waste composting facilities site selection for sustainable development using a hybrid modified MADM model.

Science.gov (United States)

Liu, Kung-Ming; Lin, Sheng-Hau; Hsieh, Jing-Chzi; Tzeng, Gwo-Hshiung

2018-05-01

With the growth of population and the development of urbanization, waste management has always been a critical global issue. Recently, more and more countries have found that food waste constitutes the majority of municipal waste, if they are disposed of properly, will bring more benefits in sustainable development. Regarding the issue of selecting and improving the location to make the disposal facility towards achieving the aspiration level for sustainable development, since it involves multiple and complicated interaction factors about environment, society, and economy which have to be considered properly in the decision-making process of mutual influence relationship. It is basically a multiple attribute decision making (MADM) issue, a difficult problem which has been obsessing the governments of many countries is widely studied and discussed. This study uses the new hybrid modified MADM model, as follows, first to build an influential network relation map (INRM) via DEMATEL technique, next to confirm the influential weightings via DANP (DEMATEL-based ANP), and then to construct a decision-making model via a hybrid modified VIKOR method to improve and select the location for remaining the best disposal facilities. Finally, an empirical case study is illustrated to demonstrate that the proposed model can be effective and useful. In finding the process of decision making, environmental pollution is the main concern of many people in the area, but actually it is the resistance by the general public that has to be considered with first priority. Copyright © 2018. Published by Elsevier Ltd.

Identification of recently selected mutations driven by artificial selection in hanwoo (korean cattle).

Science.gov (United States)

Lim, Dajeong; Gondro, Cedric; Park, Hye Sun; Cho, Yong Min; Chai, Han Ha; Seong, Hwan Hoo; Yang, Bo Suk; Hong, Seong Koo; Chang, Won Kyung; Lee, Seung Hwan

2013-05-01

Hanwoo have been subjected over the last seventy years to intensive artificial selection with the aim of improving meat production traits such as marbling and carcass weight. In this study, we performed a signature of selection analysis to identify recent positive selected regions driven by a long-term artificial selection process called a breeding program using whole genome SNP data. In order to investigate homozygous regions across the genome, we estimated iES (integrated Extended Haplotype Homozygosity SNP) for the each SNPs. As a result, we identified two highly homozygous regions that seem to be strong and/or recent positive selection. Five genes (DPH5, OLFM3, S1PR1, LRRN1 and CRBN) were included in this region. To go further in the interpretation of the observed signatures of selection, we subsequently concentrated on the annotation of differentiated genes defined according to the iES value of SNPs localized close or within them. We also described the detection of the adaptive evolution at the molecular level for the genes of interest. As a result, this analysis also led to the identification of OLFM3 as having a strong signal of selection in bovine lineage. The results of this study indicate that artificial selection which might have targeted most of these genes was mainly oriented towards improvement of meat production.

Identification of Recently Selected Mutations Driven by Artificial Selection in Hanwoo (Korean Cattle

Directory of Open Access Journals (Sweden)

Dajeong Lim

2013-05-01

Full Text Available Hanwoo have been subjected over the last seventy years to intensive artificial selection with the aim of improving meat production traits such as marbling and carcass weight. In this study, we performed a signature of selection analysis to identify recent positive selected regions driven by a long-term artificial selection process called a breeding program using whole genome SNP data. In order to investigate homozygous regions across the genome, we estimated iES (integrated Extended Haplotype Homozygosity SNP for the each SNPs. As a result, we identified two highly homozygous regions that seem to be strong and/or recent positive selection. Five genes (DPH5, OLFM3, S1PR1, LRRN1 and CRBN were included in this region. To go further in the interpretation of the observed signatures of selection, we subsequently concentrated on the annotation of differentiated genes defined according to the iES value of SNPs localized close or within them. We also described the detection of the adaptive evolution at the molecular level for the genes of interest. As a result, this analysis also led to the identification of OLFM3 as having a strong signal of selection in bovine lineage. The results of this study indicate that artificial selection which might have targeted most of these genes was mainly oriented towards improvement of meat production.

Selective Serotonin Reuptake Inhibitors for Treatment of Selective Mutism

Directory of Open Access Journals (Sweden)

Mazlum Çöpür

2012-03-01

Full Text Available Some authors suggest that selective mutism should be considered as a variant of social phobia or a disorder in the obsessive-compulsive spectrum. Recent studies indicate that pharmacological treatments may be effective in the treatment of selective mutism. In this article, four cases who were treated with citalopram and escitalopram are presented. The results indicate that the drugs were well tolerated, and the level of social and verbal interactions improved significantly. These findings have shown that citalopram and escitalopram can be considered in medication of selective mutism; nevertheless, it is essential that research be done with more cases than previous ones, in order to prove their accuracy

Improvement of Selected Logistics Processes Using Quality Engineering Tools

Science.gov (United States)

Zasadzień, Michał; Žarnovský, Jozef

2018-03-01

Increase in the number of orders, the increasing quality requirements and the speed of order preparation require implementation of new solutions and improvement of logistics processes. Any disruption that occurs during execution of an order often leads to customer dissatisfaction, as well as loss of his/her confidence. The article presents a case study of the use of quality engineering methods and tools to improve the e-commerce logistic process. This made it possible to identify and prioritize key issues, identify their causes, and formulate improvement and prevention measures.

Multiple model analysis with discriminatory data collection (MMA-DDC): A new method for improving measurement selection

Science.gov (United States)

Kikuchi, C.; Ferre, P. A.; Vrugt, J. A.

2011-12-01

Hydrologic models are developed, tested, and refined based on the ability of those models to explain available hydrologic data. The optimization of model performance based upon mismatch between model outputs and real world observations has been extensively studied. However, identification of plausible models is sensitive not only to the models themselves - including model structure and model parameters - but also to the location, timing, type, and number of observations used in model calibration. Therefore, careful selection of hydrologic observations has the potential to significantly improve the performance of hydrologic models. In this research, we seek to reduce prediction uncertainty through optimization of the data collection process. A new tool - multiple model analysis with discriminatory data collection (MMA-DDC) - was developed to address this challenge. In this approach, multiple hydrologic models are developed and treated as competing hypotheses. Potential new data are then evaluated on their ability to discriminate between competing hypotheses. MMA-DDC is well-suited for use in recursive mode, in which new observations are continuously used in the optimization of subsequent observations. This new approach was applied to a synthetic solute transport experiment, in which ranges of parameter values constitute the multiple hydrologic models, and model predictions are calculated using likelihood-weighted model averaging. MMA-DDC was used to determine the optimal location, timing, number, and type of new observations. From comparison with an exhaustive search of all possible observation sequences, we find that MMA-DDC consistently selects observations which lead to the highest reduction in model prediction uncertainty. We conclude that using MMA-DDC to evaluate potential observations may significantly improve the performance of hydrologic models while reducing the cost associated with collecting new data.

Improvement of potato tolerance to salinity using tissue culture techniques and irradiation with in vitro selection

International Nuclear Information System (INIS)

Al-Safadi, B.; Arabi, M. I. E.

2005-06-01

A mutation breeding program was conducted to improve potato (Solanum tuberosum) tolerance to salinity. In vitro cultured explants from potato cvs. Draga, Diamant, Spunta were irradiated with gamma doses 25, 30, and 35 Gy.Growing shoots were cut and re-cultured every 2 weeks until the 4th generation (MV 4 ) to make sure no chimeral tissues still existed in the mutant material. Plantlets were subsequently propagated to obtain enough explants for in vitro selection pressure. Around 3000 plantlets from the three cultivars were subjected to selection pressure. MV 4 explants were cultured on MS medium supplemented with the NaCl in varying concentrations ranging between 50 to 200 mM. Surviving plantlets were propagated and re-cultured on a similar medium to insure their tolerance to salinity. Tolerant plantlets were acclimatized and transferred to pots and grown under glasshouse conditions. Plants were later subjected to another selection pressure, by irrigating them using water containing NaCl in concentrations ranging between 50-250 mM in addition to controls irrigated with normal water. Cultivar Spunta produced the highest number of tolerant plants. Four plants of Spunta appeared to be tolerant to salinity whereas only one plant from Diamant and was tolerant and no plants from cultivar Draga were tolerant. Mutant plants varied in number of produced minitubers from 8 - 14. Also, weight of these minitubers varied from less than 1 to 31 grams. (author)

In situ product removal in fermentation systems: improved process performance and rational extractant selection.

Science.gov (United States)

Dafoe, Julian T; Daugulis, Andrew J

2014-03-01

The separation of inhibitory compounds as they are produced in biotransformation and fermentation systems is termed in situ product removal (ISPR). This review examines recent ISPR strategies employing several classes of extractants including liquids, solids, gases, and combined extraction systems. Improvement through the simple application of an auxiliary phase are tabulated and summarized to indicate the breadth of recent ISPR activities. Studies within the past 5 years that have highlighted and have discussed "second phase" properties, and that have an effect on fermentation performance, are particular focus of this review. ISPR, as a demonstrably effective processing strategy, continues to be widely adopted as more applications are explored; however, focus on the properties of extractants and their rational selection based on first principle considerations will likely be key to successfully applying ISPR to more challenging target molecules.

Design of Soybean Seed Selecting Machine and Its Improvement%大豆种子清选机的设计及改进

Institute of Scientific and Technical Information of China (English)

张军

2015-01-01

在简介国内外大豆清选技术的基础上，设计3LD－ZP型大豆种子清选机。介绍大豆种子清选机的结构组成、工作过程及主要影响因素，提出结构改进方案，为提高大豆种子的分选质量提供适用机具。%In the article, it designed type 3LD-ZP soybean seed selecting machine on the basis of briefly introducing the technology of soybean selecting at home and abroad. It introduced structure components, operating process and main influence factors of soybean seed selecting machine, raised improvement plan for the structure, in order to provide suitable machinery for increasing selecting quality of soybean seed.

Rapid Improvement in Visual Selective Attention Related to Action Video Gaming Experience

Directory of Open Access Journals (Sweden)

Nan Qiu

2018-02-01

Full Text Available A central issue in cognitive science is understanding how learning induces cognitive and neural plasticity, which helps illuminate the biological basis of learning. Research in the past few decades showed that action video gaming (AVG offered new, important perspectives on learning-related cognitive and neural plasticity. However, it is still unclear whether cognitive and neural plasticity is observable after a brief AVG session. Using behavioral and electrophysiological measures, this study examined the plasticity of visual selective attention (VSA associated with a 1 h AVG session. Both AVG experts and non-experts participated in this study. Their VSA was assessed prior to and after the AVG session. Within-group comparisons on the participants' performance before and after the AVG session showed improvements in response time in both groups and modulations of electrophysiological measures in the non-experts. Furthermore, between-group comparisons showed that the experts had superior VSA, relative to the non-experts, prior to the AVG session. These findings suggested an association between the plasticity of VSA and AVG. Most importantly, this study showed that the plasticity of VSA was observable after even a 1 h AVG session.

Rapid Improvement in Visual Selective Attention Related to Action Video Gaming Experience.

Science.gov (United States)

Qiu, Nan; Ma, Weiyi; Fan, Xin; Zhang, Youjin; Li, Yi; Yan, Yuening; Zhou, Zhongliang; Li, Fali; Gong, Diankun; Yao, Dezhong

2018-01-01

A central issue in cognitive science is understanding how learning induces cognitive and neural plasticity, which helps illuminate the biological basis of learning. Research in the past few decades showed that action video gaming (AVG) offered new, important perspectives on learning-related cognitive and neural plasticity. However, it is still unclear whether cognitive and neural plasticity is observable after a brief AVG session. Using behavioral and electrophysiological measures, this study examined the plasticity of visual selective attention (VSA) associated with a 1 h AVG session. Both AVG experts and non-experts participated in this study. Their VSA was assessed prior to and after the AVG session. Within-group comparisons on the participants' performance before and after the AVG session showed improvements in response time in both groups and modulations of electrophysiological measures in the non-experts. Furthermore, between-group comparisons showed that the experts had superior VSA, relative to the non-experts, prior to the AVG session. These findings suggested an association between the plasticity of VSA and AVG. Most importantly, this study showed that the plasticity of VSA was observable after even a 1 h AVG session.

Control room annunciation - problem assessment and selection of improvement priorities

International Nuclear Information System (INIS)

Hartley, P.; Yaraskavitch, E.; Davey, E.

1998-01-01

In 1997, Pickering B undertook a project to examine current annunciation practice and identify improvement opportunities and priorities. The objectives and scope of the study were to: document the deficiencies with control room annunciation and the subsequent operational and financial impacts to station operations, develop an operations-based definition of the requirements for annunciation to adequately support control room staff, propose annunciation improvements based on a comparison of the annunciation deficiencies identified and the operational needs to be met, assess the relative operational impact, and financial benefits and costs of the improvement initiatives proposed, and recommend annunciation improvement priorities that offer a mix of operational and financial return for improvement investment. This paper discusses the rationale for the project, outlines the approaches applied in achieving the assessment objectives, reviews the key assessment findings and describes the improvement initiatives recommended. (author)

Selection for Dutch postgraduate GP training; time for improvement

NARCIS (Netherlands)

Vermeulen, M.I.; Kuyvenhoven, M.M.; Zuithoff, N.P.; Tromp, F.; Graaf, Y. van der; Pieters, R.H.

2012-01-01

Background: In the Netherlands we select candidates for the postgraduate GP training by assessing personal qualities in interviews. Because of differences in the ratio of number of candidates and number of vacancies between the eight departments of GP training we questioned whether the risk of being

Spectroelectrochemistry as a Strategy for Improving Selectivity of Sensors for Security and Defense Applications

Energy Technology Data Exchange (ETDEWEB)

Heineman, William R.; Seliskar, Carl J.; Morris, Laura K.; Bryan, Samuel A.

2012-12-19

Spectroelectrochemistry provides improved selectivity for sensors by electrochemically modulating the optical signal associated with the analyte. The sensor consists of an optically transparent electrode (OTE) coated with a film that preconcentrates the target analyte. The OTE functions as an optical waveguide for attenuated total reflectance (ATR) spectroscopy, which detects the analyte by absorption. Alternatively, the OTE can serve as the excitation light for fluorescence detection, which is generally more sensitive than absorption. The analyte partitions into the film, undergoes an electrochemical redox reaction at the OTE surface, and absorbs or emits light in its oxidized or reduced state. The change in the optical response associated with electrochemical oxidation or reduction at the OTE is used to quantify the analyte. Absorption sensors for metal ion complexes such as [Fe(CN)6]4- and [Ru(bpy)3]2+ and fluorescence sensors for [Ru(bpy)3]2+ and the polycyclic aromatic hydrocarbon 1-hydroxypyrene have been developed. The sensor concept has been extended to binding assays for a protein using avidin–biotin and 17β-estradiol–anti-estradiol antibodies. The sensor has been demonstrated to measure metal complexes in complex samples such as nuclear waste and natural water. This sensor has qualities needed for security and defense applications that require a high level of selectivity and good detection limits for target analytes in complex samples. Quickly monitoring and designating intent of a nuclear program by measuring the Ru/Tc fission product ratio is such an application.

Differential Mobility Spectrometry for Improved Selectivity in Hydrophilic Interaction Liquid Chromatography-Tandem Mass Spectrometry Analysis of Paralytic Shellfish Toxins

Science.gov (United States)

Beach, Daniel G.

2017-08-01

Paralytic shellfish toxins (PSTs) are neurotoxins produced by dinoflagellates and cyanobacteria that cause paralytic shellfish poisoning in humans. PST quantitation by LC-MS is challenging because of their high polarity, lability as gas-phase ions, and large number of potentially interfering analogues. Differential mobility spectrometry (DMS) has the potential to improve the performance of LC-MS methods for PSTs in terms of selectivity and limits of detection. This work describes a comprehensive investigation of the separation of 16 regulated PSTs by DMS and the development of highly selective LC-DMS-MS methods for PST quantitation. The effects of all DMS parameters on the separation of PSTs from one another were first investigated in detail. The labile nature of 11α-gonyautoxin epimers gave unique insight into fragmentation of labile analytes before, during, and after the DMS analyzer. Two sets of DMS parameters were identified that either optimized the resolution of PSTs from one another or transmitted them at a limited number of compensation voltage (CV) values corresponding to structural subclasses. These were used to develop multidimensional LC-DMS-MS/MS methods using existing HILIC-MS/MS parameters. In both cases, improved selectivity was observed when using DMS, and the quantitative capabilities of a rapid UPLC-DMS-MS/MS method were evaluated. Limits of detection of the developed method were similar to those without DMS, and differences were highly analyte-dependant. Analysis of shellfish matrix reference materials showed good agreement with established methods. The developed methods will be useful in cases where specific matrix interferences are encountered in the LC-MS/MS analysis of PSTs in complex biological samples.

Modified Anderson-Darling tests with selective power improvement

OpenAIRE

Cabaña Nigro, Alejandra

2001-01-01

Transformed empirical processes (TEPs) have been used by the authors in a previous paper to construct consistent and selectively efficient goodness-of-fit tests of the Kolmogorov-Smirnov type. A straightforward application of the same ideas to the construction of tests of the Cramér-von-Mises type with the same properties leads to cumbersome computations. This short note of the incovenients encountered, and introduces a new family of quadratic statistics of the Cramér-von Mises type, in order...

Ad Hoc Access Gateway Selection Algorithm

Science.gov (United States)

Jie, Liu

With the continuous development of mobile communication technology, Ad Hoc access network has become a hot research, Ad Hoc access network nodes can be used to expand capacity of multi-hop communication range of mobile communication system, even business adjacent to the community, improve edge data rates. For mobile nodes in Ad Hoc network to internet, internet communications in the peer nodes must be achieved through the gateway. Therefore, the key Ad Hoc Access Networks will focus on the discovery gateway, as well as gateway selection in the case of multi-gateway and handover problems between different gateways. This paper considers the mobile node and the gateway, based on the average number of hops from an average access time and the stability of routes, improved gateway selection algorithm were proposed. An improved gateway selection algorithm, which mainly considers the algorithm can improve the access time of Ad Hoc nodes and the continuity of communication between the gateways, were proposed. This can improve the quality of communication across the network.

Selection indices for yield and quality traits in sweet corn

International Nuclear Information System (INIS)

Asghar, M.J.; Mehdi, S.S.

2010-01-01

The efficiency of three selection indices, viz., Smith-Hazel index (SHI), Desired gain index (DGI) and Base Index (BI) was compared for the improvement of an open pollinated sweet corn (Zea mays L. Saccharata) population. The data of genetic studies on various yield and quality traits among S1 families were used to construct these selection indices. Smith-Hazel index was found to be the most efficient in improving the aggregate genotype of yield traits for most of the selection strategies. Base index proved to be more efficient as compared to Smith-Hazel index in the improvement of aggregate genotype for five out of six selection strategies of quality traits. Both smith-hazel and Base indices were found useful for the improvement of sweetness and sweet flavour for all the selection strategies. When selection was confined to eight yield and four quality traits simultaneously, Base index proved to be more efficient as compared to Smith-Hazel index and desired gain index in improving the aggregate genotype for almost all the selection strategies. (author)

Selective purge for hydrogenation reactor recycle loop

Science.gov (United States)

Baker, Richard W.; Lokhandwala, Kaaeid A.

2001-01-01

Processes and apparatus for providing improved contaminant removal and hydrogen recovery in hydrogenation reactors, particularly in refineries and petrochemical plants. The improved contaminant removal is achieved by selective purging, by passing gases in the hydrogenation reactor recycle loop or purge stream across membranes selective in favor of the contaminant over hydrogen.

Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

Directory of Open Access Journals (Sweden)

J. Sunil Rao

2007-01-01

Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

Improved CT-detection of acute bowel ischemia using frequency selective non-linear image blending.

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Schneeweiss, Sven; Esser, Michael; Thaiss, Wolfgang; Boesmueller, Hans; Ditt, Hendrik; Nikolau, Konstantin; Horger, Marius

2017-07-01

Computed tomography (CT) as a fast and reliable diagnostic technique is the imaging modality of choice for acute bowel ischemia. However, diagnostic is often difficult mainly due to low attenuation differences between ischemic and perfused segments. To compare the diagnostic efficacy of a new post-processing tool based on frequency selective non-linear blending with that of conventional linear contrast-enhanced CT (CECT) image blending for the detection of bowel ischemia. Twenty-seven consecutive patients (19 women; mean age = 73.7 years, age range = 50-94 years) with acute bowel ischemia were scanned using multidetector CT (120 kV; 100-200 mAs). Pre-contrast and portal venous scans (65-70 s delay) were acquired. All patients underwent surgery for acute bowel ischemia and intraoperative diagnosis as well as histologic evaluation of explanted bowel segments was considered "gold standard." First, two radiologists read the conventional CECT images in which linear blending was adapted for optimal contrast, and second (three weeks later) the frequency selective non-linear blending (F-NLB) image. Attenuation values were compared, both in the involved and non-involved bowel segments creating ratios between unenhanced and CECT. The mean attenuation difference between ischemic and non-ischemic wall in the portal venous scan was 69.54 HU (reader 2 = 69.01 HU) higher for F-NLB compared with conventional CECT. Also, the attenuation ratio between contrast-enhanced and pre-contrast CT data for the non-ischemic walls showed significantly higher values for the F-NLB image (CECT: reader 1 = 2.11 (reader 2 = 3.36), F-NLB: reader 1 = 4.46 (reader 2 = 4.98)]. Sensitivity in detecting ischemic areas increased significantly for both readers using F-NLB (CECT: reader 1/2 = 53%/65% versus F-NLB: reader 1/2 = 62%/75%). Frequency selective non-linear blending improves detection of bowel ischemia compared with conventional CECT by increasing

Mechanical properties' improvement of a tricalcium phosphate scaffold with poly-l-lactic acid in selective laser sintering

International Nuclear Information System (INIS)

Liu, Defu; Zhuang, Jingyu; Shuai, Cijun; Peng, Shuping

2013-01-01

To improve the mechanical properties of a scaffold fabricated via selective laser sintering (SLS), a small amount (0.5–3 wt%) of poly-l-lactic acid (PLLA) is added to the β-tricalcium phosphate (β-TCP) powder. The fracture toughness of the scaffold prepared with the mixture powder containing 1 wt% PLLA increases by 18.18% and the compressive strength increases by 4.45% compared to the scaffold prepared from the β-TCP powder. The strengthening and toughening is related to the enhancement of β-TCP sintering characteristics via introducing a transient liquid phase in SLS. Moreover, the microcracks caused by the volume expansion due to the β–α phase transformation of TCP are reduced because of the PLLA inhibition function on the phase transformation. However, PLLA additive above 1 wt% would lead to a PLLA residue which will decrease the mechanical properties. The experimental results show that PLLA is an effective sintering aid to improve the mechanical properties of a TCP scaffold. (paper)

Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops.

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Wasson, A P; Richards, R A; Chatrath, R; Misra, S C; Prasad, S V Sai; Rebetzke, G J; Kirkegaard, J A; Christopher, J; Watt, M

2012-05-01

Wheat yields globally will depend increasingly on good management to conserve rainfall and new varieties that use water efficiently for grain production. Here we propose an approach for developing new varieties to make better use of deep stored water. We focus on water-limited wheat production in the summer-dominant rainfall regions of India and Australia, but the approach is generally applicable to other environments and root-based constraints. Use of stored deep water is valuable because it is more predictable than variable in-season rainfall and can be measured prior to sowing. Further, this moisture is converted into grain with twice the efficiently of in-season rainfall since it is taken up later in crop growth during the grain-filling period when the roots reach deeper layers. We propose that wheat varieties with a deeper root system, a redistribution of branch root density from the surface to depth, and with greater radial hydraulic conductivity at depth would have higher yields in rainfed systems where crops rely on deep water for grain fill. Developing selection systems for mature root system traits is challenging as there are limited high-throughput phenotyping methods for roots in the field, and there is a risk that traits selected in the lab on young plants will not translate into mature root system traits in the field. We give an example of a breeding programme that combines laboratory and field phenotyping with proof of concept evaluation of the trait at the beginning of the selection programme. This would greatly enhance confidence in a high-throughput laboratory or field screen, and avoid investment in screens without yield value. This approach requires careful selection of field sites and years that allow expression of deep roots and increased yield. It also requires careful selection and crossing of germplasm to allow comparison of root expression among genotypes that are similar for other traits, especially flowering time and disease and toxicity

Frequency selective non-linear blending to improve image quality in liver CT

International Nuclear Information System (INIS)

Bongers, M.N.; Bier, G.; Kloth, C.; Schabel, C.; Nikolaou, K.; Horger, M.; Fritz, J.

2016-01-01

To evaluate the effects of a new frequency selective non-linear blending (NLB) algorithm on the contrast resolution of liver CT with low intravascular concentration of iodine contrast. Our local ethics committee approved this retrospective study. The informed consent requirement was waived. CT exams of 25 patients (60% female, mean age: 65±16 years of age) with late phase CT scans of the liver were included as a model for poor intrahepatic vascular contrast enhancement. Optimal post-processing settings to enhance the contrast of hepatic vessels were determined. Outcome variables included signal-to-noise (SNR) and contrast-to-noise ratios (CNR) of hepatic vessels and SNR of liver parenchyma of standard and post-processed images. Image quality was quantified by two independent readers using Likert scales. The post-processing settings for the visualization of hepatic vasculature were optimal at a center of 115HU, delta of 25HU, and slope of 5. Image noise was statistically indifferent between standard and post-processed images. The CNR between the hepatic vasculature (HV) and liver parenchyma could be significantly increased for liver veins (CNR Standard 1.62±1.10, CNR NLB 3.6±2.94, p=0.0002) and portal veins (CNR Standard 1.31±0.85, CNR NLB 2.42±3.03, p=0.046). The SNR of liver parenchyma was significantly higher on post-processed images (SNR NLB 11.26±3.16, SNR Standard 8.85± 2.27, p=0.008). The overall image quality and depiction of HV were significantly higher on post-processed images (NLB DHV : 4 [3-4.75], S tandardDHV : 2 [1.3-2.5], p=<0.0001; NLBIQ : 4 [4-4], StandardIQ : 2 [2-3], p=<0.0001). The use of a frequency selective non-linear blending algorithm increases the contrast resolution of liver CT and can improve the visibility of the hepatic vasculature in the setting of a low contrast ratio between vessels and the parenchyma.

Frequency selective non-linear blending to improve image quality in liver CT

Energy Technology Data Exchange (ETDEWEB)

Bongers, M.N.; Bier, G.; Kloth, C.; Schabel, C.; Nikolaou, K.; Horger, M. [University Hospital of Tuebingen (Germany). Dept. of Diagnostic and Interventional Radiology; Fritz, J. [Johns Hopkins University School of Medicine, Baltimore, MD (United States). Russell H. Morgan Dept. of Radiology and Radiological Science

2016-12-15

To evaluate the effects of a new frequency selective non-linear blending (NLB) algorithm on the contrast resolution of liver CT with low intravascular concentration of iodine contrast. Our local ethics committee approved this retrospective study. The informed consent requirement was waived. CT exams of 25 patients (60% female, mean age: 65±16 years of age) with late phase CT scans of the liver were included as a model for poor intrahepatic vascular contrast enhancement. Optimal post-processing settings to enhance the contrast of hepatic vessels were determined. Outcome variables included signal-to-noise (SNR) and contrast-to-noise ratios (CNR) of hepatic vessels and SNR of liver parenchyma of standard and post-processed images. Image quality was quantified by two independent readers using Likert scales. The post-processing settings for the visualization of hepatic vasculature were optimal at a center of 115HU, delta of 25HU, and slope of 5. Image noise was statistically indifferent between standard and post-processed images. The CNR between the hepatic vasculature (HV) and liver parenchyma could be significantly increased for liver veins (CNR{sub Standard} 1.62±1.10, CNR{sub NLB} 3.6±2.94, p=0.0002) and portal veins (CNR{sub Standard} 1.31±0.85, CNR{sub NLB} 2.42±3.03, p=0.046). The SNR of liver parenchyma was significantly higher on post-processed images (SNR{sub NLB} 11.26±3.16, SNR{sub Standard} 8.85± 2.27, p=0.008). The overall image quality and depiction of HV were significantly higher on post-processed images (NLB{sub DHV}: 4 [3-4.75], S{sub tandardDHV}: 2 [1.3-2.5], p=<0.0001; {sub NLBIQ}: 4 [4-4], {sub StandardIQ}: 2 [2-3], p=<0.0001). The use of a frequency selective non-linear blending algorithm increases the contrast resolution of liver CT and can improve the visibility of the hepatic vasculature in the setting of a low contrast ratio between vessels and the parenchyma.

Improving sperm banking efficiency in endangered species through the use of a sperm selection method in brown bear (Ursus arctos) thawed sperm.

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Anel-Lopez, L; Ortega-Ferrusola, C; Álvarez, M; Borragán, S; Chamorro, C; Peña, F J; Morrell, J; Anel, L; de Paz, P

2017-06-26

Sperm selection methods such as Single Layer Centrifugation (SLC) have been demonstrated to be a useful tool to improve the quality of sperm samples and therefore to increase the efficiency of other artificial reproductive techniques in several species. This procedure could help to improve the quality of genetic resource banks, which is essential for endangered species. In contrast, these sperm selection methods are optimized and focused on farm animals, where the recovery task is not as important as in endangered species because of their higher sperm availability. The aim of this study was to evaluate two centrifugation methods (300 x g/20 min and 600 x g/10 min) and three concentrations of SLC media (Androcoll-Bear -80, 65 and 50%) to optimise the procedure in order to recover as many sperm with the highest quality as possible. Sperm morphology could be important in the hydrodynamic relationship between the cell and centrifugation medium and thus the effect of sperm head morphometry on sperm yield and its hydrodynamic relationship were studied. The samples selected with Androcoll-Bear 65% showed a very good yield (53.1 ± 2.9) although the yield from Androcoll-Bear 80% was lower (19.3 ± 3.3). The latter showed higher values of motility than the control immediately after post-thawing selection. However, both concentrations of colloid (65 and 80%) showed higher values of viable sperm and viable sperm with intact acrosome than the control. After an incubation of 2 h at 37 °C, the samples from Androcoll-Bear 80% had higher kinematics and proportion of viable sperm with intact acrosome. In the morphometric analysis, the sperm selected by the Androcoll-Bear 80% showed a head with a bigger area which was more elongated than the sperm from other treatments. We conclude that sperm selection with Androcoll-Bear at either 65% or 80% is a suitable technique that allows a sperm population with better quality than the initial sample to be obtained. We recommend the

Improvement in abdominal and flank contouring by a novel adipocyte-selective non-contact radiofrequency device.

Science.gov (United States)

Choi, Sun Young; Kim, Young Jae; Kim, So Yeon; Lee, Woo Jin; Chang, Sung Eun; Lee, Mi Woo; Choi, Jee Ho; Won, Chonghyun

2018-05-07

The demand for undergoing subcutaneous fat reduction has been gradually increasing, and there are many methods and devices for performing non-surgical and non-invasive fat reduction, such as high-intensity focused ultrasound, cryolipolysis, radiofrequency (RF) devices, and lasers. This study evaluated the efficacy and safety of a novel adipocyte-selective non-contact RF device for improving abdominal contouring in Asian subjects. Twenty-four Asian subjects with abundant subcutaneous abdominal and love handle fat tissues were enrolled in this prospective clinical study. They received six 45-min weekly treatments with an RF field device over the abdominal and love handle regions. The body mass index and abdominal circumference were measured at baseline and at 4 and 8 weeks post the last treatment. The thickness of the abdomen and depth of subcutaneous abdominal fat tissue were respectively assessed using calipers and abdominal ultrasonography. A subset of 15 subjects was selected by randomization for fat volume measurement via abdominal CT. For safety evaluation, serum lipid, and liver-related blood tests were performed at baseline and at the sixth treatment session. Subjects rated their heat perception level using a four point scale and their pain score using an 11-point visual analog scale during RF treatment. Twenty-four subjects (21 females and 3 males) completed this study with an 8-week follow-up. The average decreases in abdominal circumference at 4 and 8 weeks post treatment were 3.48 ± 2.11 cm (P < 0.001) and 5.12 ± 0.47 cm (P < 0.001), respectively. The average decreases in abdominal fat thickness at 4 and 8 weeks treatment were 0.27 ± 0.61 cm (P = 0.041) and 0.47 ± 0.60 cm (P = 0.001), respectively. The average decreases in subcutaneous fat tissue depth at 4 and 8 weeks post treatment were 0.16 ± 0.43 cm (P = 0.091) and 0.34 ± 0.39 cm (P < 0.001), respectively. However, there was no

Transporter-Guided Delivery of Nanoparticles to Improve Drug Permeation across Cellular Barriers and Drug Exposure to Selective Cell Types

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Longfa Kou

2018-01-01

Full Text Available Targeted nano-drug delivery systems conjugated with specific ligands to target selective cell-surface receptors or transporters could enhance the efficacy of drug delivery and therapy. Transporters are expressed differentially on the cell-surface of different cell types, and also specific transporters are expressed at higher than normal levels in selective cell types under pathological conditions. They also play a key role in intestinal absorption, delivery via non-oral routes (e.g., pulmonary route and nasal route, and transfer across biological barriers (e.g., blood–brain barrier and blood–retinal barrier. As such, the cell-surface transporters represent ideal targets for nano-drug delivery systems to facilitate drug delivery to selective cell types under normal or pathological conditions and also to avoid off-target adverse side effects of the drugs. There is increasing evidence in recent years supporting the utility of cell-surface transporters in the field of nano-drug delivery to increase oral bioavailability, to improve transfer across the blood–brain barrier, and to enhance delivery of therapeutics in a cell-type selective manner in disease states. Here we provide a comprehensive review of recent advancements in this interesting and important area. We also highlight certain key aspects that need to be taken into account for optimal development of transporter-assisted nano-drug delivery systems.

Optimization of dipeptidic inhibitors of cathepsin L for improved Toxoplasma gondii selectivity and CNS permeability.

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Zwicker, Jeffery D; Diaz, Nicolas A; Guerra, Alfredo J; Kirchhoff, Paul D; Wen, Bo; Sun, Duxin; Carruthers, Vern B; Larsen, Scott D

2018-06-01

The neurotropic protozoan Toxoplasma gondii is the second leading cause of death due to foodborne illness in the US, and has been designated as one of five neglected parasitic infections by the Center for Disease Control and Prevention. Currently, no treatment options exist for the chronic dormant-phase Toxoplasma infection in the central nervous system (CNS). T. gondii cathepsin L (TgCPL) has recently been implicated as a novel viable target for the treatment of chronic toxoplasmosis. In this study, we report the first body of SAR work aimed at developing potent inhibitors of TgCPL with selectivity vs the human cathepsin L. Starting from a known inhibitor of human cathepsin L, and guided by structure-based design, we were able to modulate the selectivity for Toxoplasma vs human CPL by nearly 50-fold while modifying physiochemical properties to be more favorable for metabolic stability and CNS penetrance. The overall potency of our inhibitors towards TgCPL was improved from 2 μM to as low as 110 nM and we successfully demonstrated that an optimized analog 18b is capable of crossing the BBB (0.5 brain/plasma). This work is an important first step toward development of a CNS-penetrant probe to validate TgCPL as a feasible target for the treatment of chronic toxoplasmosis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Site selection process for new nuclear power plants - a method to support decision making and improving public participation

International Nuclear Information System (INIS)

Martins, Vivian B.; Cunha, Tatiana S. da; Simoes Filho, Francisco Fernando Lamego; Lapa, Celso Marcelo F.

2011-01-01

The Brazilian Energy Plan (PNE 2030) that guides the Government in formulating its strategy for expanding energy supply by 2030 highlights the need for the Brazilian electrical system have more than 4,000 MW from nuclear sources by 2025. Therefore, the Government presented a proposal to build four more nuclear power plants with capacity of 1,000 MW each, at first, two in the Northeast and two in Southeast. The selection and site assessment are key parts of the installation process of a nuclear plant and may significantly affect the cost, public acceptance and safety of the facility during its entire life cycle. The result of this initial stage, it can even seriously affect program success. Wrong decisions in the process of site selection may also require a financial commitment to higher planned in a later phase of the project, besides causing extensive and expensive downtime. Select the location where these units will be built is not a trivial process, because involves the consideration of multiple criteria and judgments in addition to obtaining, organizing and managing a diverse range of data, both qualitative and quantitative, to assist in decision making and ensure that the site selected is the most appropriate in relation to safety and technical, economic and environmental feasibility. This paper presents an overview of the site selection process and its stages, the criteria involved in each step, the tools to support decision making that can be used and the difficulties in applying a formal process of decision making. Also discussed are ways to make the process more transparent and democratic, increasing public involvement as a way to improve acceptance and reduce opposition from various sectors of society, trying to minimize the expense and time involved in the implementation of undertakings of this kind. (author)

Selection decisions among reindeer herders in Finland

Directory of Open Access Journals (Sweden)

Kirsi Muuttoranta

2011-04-01

Full Text Available Selection of breeding animals is a tool to improve the revenues in animal production. Information about selection practices and criteria are essential in assessing the possibilities for systematic selection schemes. Attitudes of reindeer herders towards use of selection in improving production were investigated by means of interviews. We interviewed the managers of reindeer herding cooperatives concerning their selection decisions. Fortyfive out of 56 managers answered to the semi-structured questionnaire. Among herding operations, selection of breeding animals was regarded by managers as critical for calf’s autumn weight and survival. The main selection criteria were calf’s health, vigour, body size and muscularity, dam or dam line, and maternal care. Hair quality and hair length were important as well, while such often quoted traits as antler characteristics, e.g. early shedding of antler velvet and thick antler bases, were unimportant. The results show that reindeer herders i acknowledge the importance and effects of selective breeding, and ii have empirical knowledge to list the most important selection criteria.

Validation of candidate gene markers for marker-assisted selection of potato cultivars with improved tuber quality.

Science.gov (United States)

Li, Li; Tacke, Eckhard; Hofferbert, Hans-Reinhardt; Lübeck, Jens; Strahwald, Josef; Draffehn, Astrid M; Walkemeier, Birgit; Gebhardt, Christiane

2013-04-01

Tuber yield, starch content, starch yield and chip color are complex traits that are important for industrial uses and food processing of potato. Chip color depends on the quantity of reducing sugars glucose and fructose in the tubers, which are generated by starch degradation. Reducing sugars accumulate when tubers are stored at low temperatures. Early and efficient selection of cultivars with superior yield, starch yield and chip color is hampered by the fact that reliable phenotypic selection requires multiple year and location trials. Application of DNA-based markers early in the breeding cycle, which are diagnostic for superior alleles of genes that control natural variation of tuber quality, will reduce the number of clones to be evaluated in field trials. Association mapping using genes functional in carbohydrate metabolism as markers has discovered alleles of invertases and starch phosphorylases that are associated with tuber quality traits. Here, we report on new DNA variants at loci encoding ADP-glucose pyrophosphorylase and the invertase Pain-1, which are associated with positive or negative effect with chip color, tuber starch content and starch yield. Marker-assisted selection (MAS) and marker validation were performed in tetraploid breeding populations, using various combinations of 11 allele-specific markers associated with tuber quality traits. To facilitate MAS, user-friendly PCR assays were developed for specific candidate gene alleles. In a multi-parental population of advanced breeding clones, genotypes were selected for having different combinations of five positive and the corresponding negative marker alleles. Genotypes combining five positive marker alleles performed on average better than genotypes with four negative alleles and one positive allele. When tested individually, seven of eight markers showed an effect on at least one quality trait. The direction of effect was as expected. Combinations of two to three marker alleles were

Improvements in recall and food choices using a graphical method to deliver information of select nutrients.

Science.gov (United States)

Pratt, Nathan S; Ellison, Brenna D; Benjamin, Aaron S; Nakamura, Manabu T

2016-01-01

Consumers have difficulty using nutrition information. We hypothesized that graphically delivering information of select nutrients relative to a target would allow individuals to process information in time-constrained settings more effectively than numerical information. Objectives of the study were to determine the efficacy of the graphical method in (1) improving memory of nutrient information and (2) improving consumer purchasing behavior in a restaurant. Values of fiber and protein per calorie were 2-dimensionally plotted alongside a target box. First, a randomized cued recall experiment was conducted (n=63). Recall accuracy of nutrition information improved by up to 43% when shown graphically instead of numerically. Second, the impact of graphical nutrition signposting on diner choices was tested in a cafeteria. Saturated fat and sodium information was also presented using color coding. Nutrient content of meals (n=362) was compared between 3 signposting phases: graphical, nutrition facts panels (NFP), or no nutrition label. Graphical signposting improved nutrient content of purchases in the intended direction, whereas NFP had no effect compared with the baseline. Calories ordered from total meals, entrées, and sides were significantly less during graphical signposting than no-label and NFP periods. For total meal and entrées, protein per calorie purchased was significantly higher and saturated fat significantly lower during graphical signposting than the other phases. Graphical signposting remained a predictor of calories and protein per calorie purchased in regression modeling. These findings demonstrate that graphically presenting nutrition information makes that information more available for decision making and influences behavior change in a realistic setting. Copyright © 2016 Elsevier Inc. All rights reserved.

Space Projects: Improvements Needed in Selecting Future Projects for Private Financing

Science.gov (United States)

1990-01-01

The Office of Management and Budget (OMB) and NASA jointly selected seven projects for commercialization to reduce NASA's fiscal year 1990 budget request and to help achieve the goal of increasing private sector involvement in space. However, the efforts to privately finance these seven projects did not increase the commercial sector's involvement in space to the extent desired. The General Accounting Office (GAO) determined that the projects selected were not a fair test of the potential of increasing commercial investment in space at an acceptable cost to the government, primarily because the projects were not properly screened. That is, neither their suitability for commercialization nor the economic consequences of seeking private financing for them were adequately evaluated before selection. Evaluations and market tests done after selection showed that most of the projects were not viable candidates for private financing. GAO concluded that projects should not be removed from NASA's budget for commercial development until after careful screening has been done to determine whether adequate commercial demand exists, development risks are commercially acceptable and private financing is found or judged to be highly likely, and the cost effectiveness of such a decision is acceptable. Premature removal of projects from NASA's budget ultimately can cause project delays and increased costs when unsuccessful commercialization candidates must be returned to the budget. NASA also needs to ensure appropriate comparisons of government and private financing options for future commercialization projects.

Acute personalized habitual caffeine doses improve attention and have selective effects when considering the fractionation of executive functions.

Science.gov (United States)

Lanini, Juliana; Galduróz, José Carlos Fernandes; Pompéia, Sabine

2016-01-01

Caffeine is widely used, often consumed with food, and improves simple and complex/executive attention under fasting conditions. We investigated whether these cognitive effects are observed when personalized habitual doses of caffeine are ingested by caffeine consumers, whether they are influenced by nutriments and if various executive domains are susceptible to improvement. This was a double-blind, placebo-controlled study including 60 young, healthy, rested males randomly assigned to one of four treatments: placebo fasting, caffeine fasting, placebo meal and caffeine meal. Caffeine doses were individualized for each participant based on their self-reported caffeine consumption at the time of testing (morning). The test battery included measures of simple and sustained attention, executive domains (inhibiting, updating, shifting, dual tasking, planning and accessing long-term memory), control measures of subjective alterations, glucose and insulin levels, skin conductance, heart rate and pupil dilation. Regardless of meal intake, acute habitual doses of caffeine decreased fatigue, and improved simple and sustained attention and executive updating. This executive effect was not secondary to the habitual weekly dose consumed, changes in simple and sustained attention, mood, meal ingestion and increases in cognitive effort. We conclude that the morning caffeine "fix" has positive attentional effects and selectively improved executive updating whether or not caffeine is consumed with food. Copyright © 2015 John Wiley & Sons, Ltd.

Visible-light-driven N-(BiO)2CO3/Graphene oxide composites with improved photocatalytic activity and selectivity for NOx removal

Science.gov (United States)

Chen, Meijuan; Huang, Yu; Yao, Jie; Cao, Jun-ji; Liu, Yuan

2018-02-01

N-doped (BiO)2CO3 (NBOC)/graphene oxide (GO) composite obtained from three-dimensional hierarchical microspheres is successfully synthesized by one-pot hydrothermal method for the first time. In this synthesis, citrate ion plays a critical role in N doping. The obtained samples are used to degrade gaseous nitrogen oxides (NOx) at parts-per-billion (ppb) level under visible-light irradiation. NBOC-GO composite with 1.0 wt% graphene oxide (GO) displays the highest photocatalytic NO removal efficiency, which is 4.3 times higher than that of pristine (BiO)2CO3. Moreover, NBOC-GO composite significantly inhibits toxic NO2 intermediate production, indicating its high selectivity for NO conversion. Compared with regular GO, N doping considerably improves the catalytic performance of NBOC-GO composite, which increases NO removal by 74.6% and fully inhibits NO2 generation. The improved photocatalytic activity is mainly ascribed to extended optical absorption ability and enhanced separation efficiency of photogenerated charge carriers over NBOC-GO composite. Both results of electron spin resonance and theoretical analysis of band structure indicate that NO removal is dominated by oxidation with rad OH and rad O2- radicals. The photocatalytic activity improvement mechanism over the NBOC-GO composite is proposed accordingly based on systematic characterizations. This study demonstrates a feasible route to fabricating Bi-containing composites with high selectivity and stability for air pollution control and provides a new insight into the associated photocatalytic mechanisms.

Vast Portfolio Selection with Gross-exposure Constraints().

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Fan, Jianqing; Zhang, Jingjin; Yu, Ke

2012-01-01

We introduce the large portfolio selection using gross-exposure constraints. We show that with gross-exposure constraint the empirically selected optimal portfolios based on estimated covariance matrices have similar performance to the theoretical optimal ones and there is no error accumulation effect from estimation of vast covariance matrices. This gives theoretical justification to the empirical results in Jagannathan and Ma (2003). We also show that the no-short-sale portfolio can be improved by allowing some short positions. The applications to portfolio selection, tracking, and improvements are also addressed. The utility of our new approach is illustrated by simulation and empirical studies on the 100 Fama-French industrial portfolios and the 600 stocks randomly selected from Russell 3000.

Improving probe set selection for microbial community analysis by leveraging taxonomic information of training sequences

Directory of Open Access Journals (Sweden)

Jiang Tao

2011-10-01

Full Text Available Abstract Background Population levels of microbial phylotypes can be examined using a hybridization-based method that utilizes a small set of computationally-designed DNA probes targeted to a gene common to all. Our previous algorithm attempts to select a set of probes such that each training sequence manifests a unique theoretical hybridization pattern (a binary fingerprint to a probe set. It does so without taking into account similarity between training gene sequences or their putative taxonomic classifications, however. We present an improved algorithm for probe set selection that utilizes the available taxonomic information of training gene sequences and attempts to choose probes such that the resultant binary fingerprints cluster into real taxonomic groups. Results Gene sequences manifesting identical fingerprints with probes chosen by the new algorithm are more likely to be from the same taxonomic group than probes chosen by the previous algorithm. In cases where they are from different taxonomic groups, underlying DNA sequences of identical fingerprints are more similar to each other in probe sets made with the new versus the previous algorithm. Complete removal of large taxonomic groups from training data does not greatly decrease the ability of probe sets to distinguish those groups. Conclusions Probe sets made from the new algorithm create fingerprints that more reliably cluster into biologically meaningful groups. The method can readily distinguish microbial phylotypes that were excluded from the training sequences, suggesting novel microbes can also be detected.

Improving probe set selection for microbial community analysis by leveraging taxonomic information of training sequences.

Science.gov (United States)

Ruegger, Paul M; Della Vedova, Gianluca; Jiang, Tao; Borneman, James

2011-10-10

Population levels of microbial phylotypes can be examined using a hybridization-based method that utilizes a small set of computationally-designed DNA probes targeted to a gene common to all. Our previous algorithm attempts to select a set of probes such that each training sequence manifests a unique theoretical hybridization pattern (a binary fingerprint) to a probe set. It does so without taking into account similarity between training gene sequences or their putative taxonomic classifications, however. We present an improved algorithm for probe set selection that utilizes the available taxonomic information of training gene sequences and attempts to choose probes such that the resultant binary fingerprints cluster into real taxonomic groups. Gene sequences manifesting identical fingerprints with probes chosen by the new algorithm are more likely to be from the same taxonomic group than probes chosen by the previous algorithm. In cases where they are from different taxonomic groups, underlying DNA sequences of identical fingerprints are more similar to each other in probe sets made with the new versus the previous algorithm. Complete removal of large taxonomic groups from training data does not greatly decrease the ability of probe sets to distinguish those groups. Probe sets made from the new algorithm create fingerprints that more reliably cluster into biologically meaningful groups. The method can readily distinguish microbial phylotypes that were excluded from the training sequences, suggesting novel microbes can also be detected.

Addressing catch mechanisms in gillnets improves modeling of selectivity and estimates of mortality rates: a case study using survey data on an endangered stock of Arctic char

DEFF Research Database (Denmark)

Jonsson, T.; Setzer, M.; Pope, John George

2013-01-01

Estimation of fish stock size distributions from survey data requires knowledge about gear selectivity. However, selectivity models rest on assumptions that seldom are analyzed. Departures from these can lead to misinterpretations and biased management recommendations. Here, we use survey data...... and asymmetric, with poor model fits. Removing potentially nonmeshed fish had the greatest positive effect on model fit, resulting in much narrower and less asymmetric selection curves, while attempting to take nonisometric growth into account, by using girth rather than length, improved model fit...

Genetic Gains in Yield and Yield Related Traits under Drought Stress and Favorable Environments in a Maize Population Improved Using Marker Assisted Recurrent Selection

Directory of Open Access Journals (Sweden)

Folusho Bankole

2017-05-01

Full Text Available The objective of marker assisted recurrent selection (MARS is to increase the frequency of favorable marker alleles in a population before inbred line extraction. This approach was used to improve drought tolerance and grain yield (GY in a biparental cross of two elite drought tolerant lines. The testcrosses of randomly selected 50 S1 lines from each of the three selection cycles (C0, C1, C2 of the MARS population, parental testcrosses and the cross between the two parents (F1 were evaluated under drought stress (DS and well watered (WW well as under rainfed conditions to determine genetic gains in GY and other agronomic traits. Also, the S1 lines derived from each selection types were genotyped with single nucleotide polymorphism (SNP markers. Testcrosses derived from C2 produced significantly higher grain field under DS than those derived from C0 with a relative genetic gain of 7% per cycle. Also, the testcrosses of S1 lines from C2 showed an average genetic gain of 1% per cycle under WW condition and 3% per cycle under rainfed condition. Molecular analysis revealed that the frequency of favorable marker alleles increased from 0.510 at C0 to 0.515 at C2, while the effective number of alleles (Ne per locus decreased from C0 (1.93 to C2 (1.87. Our results underscore the effectiveness of MARS for improvement of GY under DS condition.

Improving the selection and development of influenza vaccine viruses - Report of a WHO informal consultation on improving influenza vaccine virus selection, Hong Kong SAR, China, 18-20 November 2015.

Science.gov (United States)

Hampson, Alan; Barr, Ian; Cox, Nancy; Donis, Ruben O; Siddhivinayak, Hirve; Jernigan, Daniel; Katz, Jacqueline; McCauley, John; Motta, Fernando; Odagiri, Takato; Tam, John S; Waddell, Anthony; Webby, Richard; Ziegler, Thedi; Zhang, Wenqing

2017-02-22

Since 2010 the WHO has held a series of informal consultations to explore ways of improving the currently highly complex and time-pressured influenza vaccine virus selection and development process. In November 2015 experts from around the world met to review the current status of efforts in this field. Discussion topics included strengthening influenza surveillance activities to increase the availability of candidate vaccine viruses and improve the extent, timeliness and quality of surveillance data. Consideration was also given to the development and potential application of newer laboratory assays to better characterize candidate vaccine viruses, the potential importance of antibodies directed against influenza virus neuraminidase, and the role of vaccine effectiveness studies. Advances in next generation sequencing and whole genome sequencing of influenza viruses were also discussed, along with associated developments in synthetic genomics technologies, evolutionary analysis and predictive mathematical modelling. Discussions were also held on the late emergence of an antigenic variant influenza A(H3N2) virus in mid-2014 that could not be incorporated in time into the 2014-15 northern hemisphere vaccine. There was broad recognition that given the current highly constrained influenza vaccine development and production timeline it would remain impossible to incorporate any variant virus which emerged significantly long after the relevant WHO biannual influenza vaccine composition meetings. Discussions were also held on the development of pandemic and broadly protective vaccines, and on associated regulatory and manufacturing requirements and constraints. With increasing awareness of the health and economic burdens caused by seasonal influenza, the ever-present threat posed by zoonotic influenza viruses, and the significant impact of the 2014-15 northern hemisphere seasonal influenza vaccine mismatch, this consultation provided a very timely opportunity to share

Selection on resilience improves disease resistance and tolerance to infections

NARCIS (Netherlands)

Mulder, H.A.; Rashidi, H.

2017-01-01

Response to infection in animals has 2 main mechanisms: resistance (ability to control pathogen burden) and tolerance (ability to maintain performance given the pathogen burden). Selection on disease resistance and tolerance to infections seems a promising avenue to increase productivity of animals

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach.

Science.gov (United States)

Nasir, Muhammad; Attique Khan, Muhammad; Sharif, Muhammad; Lali, Ikram Ullah; Saba, Tanzila; Iqbal, Tassawar

2018-02-21

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F-score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods. © 2018 Wiley Periodicals, Inc.

Dynamic, continuous multitasking training leads to task-specific improvements but does not transfer across action selection tasks

Science.gov (United States)

Bender, Angela D.; Filmer, Hannah L.; Naughtin, Claire K.; Dux, Paul E.

2017-12-01

The ability to perform multiple tasks concurrently is an ever-increasing requirement in our information-rich world. Despite this, multitasking typically compromises performance due to the processing limitations associated with cognitive control and decision-making. While intensive dual-task training is known to improve multitasking performance, only limited evidence suggests that training-related performance benefits can transfer to untrained tasks that share overlapping processes. In the real world, however, coordinating and selecting several responses within close temporal proximity will often occur in high-interference environments. Over the last decade, there have been notable reports that training on video action games that require dynamic multitasking in a demanding environment can lead to transfer effects on aspects of cognition such as attention and working memory. Here, we asked whether continuous and dynamic multitasking training extends benefits to tasks that are theoretically related to the trained tasks. To examine this issue, we asked a group of participants to train on a combined continuous visuomotor tracking task and a perceptual discrimination task for six sessions, while an active control group practiced the component tasks in isolation. A battery of tests measuring response selection, response inhibition, and spatial attention was administered before and immediately after training to investigate transfer. Multitasking training resulted in substantial, task-specific gains in dual-task ability, but there was no evidence that these benefits generalized to other action control tasks. The findings suggest that training on a combined visuomotor tracking and discrimination task results in task-specific benefits but provides no additional value for untrained action selection tasks.

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction.

Science.gov (United States)

Akhter, Nasrin; Shehu, Amarda

2018-01-19

Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction

Directory of Open Access Journals (Sweden)

Nasrin Akhter

2018-01-01

Full Text Available Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

Science.gov (United States)

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

Vast Portfolio Selection with Gross-exposure Constraints*

Science.gov (United States)

Fan, Jianqing; Zhang, Jingjin; Yu, Ke

2012-01-01

We introduce the large portfolio selection using gross-exposure constraints. We show that with gross-exposure constraint the empirically selected optimal portfolios based on estimated covariance matrices have similar performance to the theoretical optimal ones and there is no error accumulation effect from estimation of vast covariance matrices. This gives theoretical justification to the empirical results in Jagannathan and Ma (2003). We also show that the no-short-sale portfolio can be improved by allowing some short positions. The applications to portfolio selection, tracking, and improvements are also addressed. The utility of our new approach is illustrated by simulation and empirical studies on the 100 Fama-French industrial portfolios and the 600 stocks randomly selected from Russell 3000. PMID:23293404

Integration trumps selection in object recognition

Science.gov (United States)

Saarela, Toni P.; Landy, Michael S.

2015-01-01

Summary Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several “cues” (color, luminance, texture etc.), and humans can integrate sensory cues to improve detection and recognition [1–3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue-invariance by responding to a given shape independent of the visual cue defining it [5–8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10,11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11,12], imaging [13–16], and single-cell and neural population recordings [17,18]. Besides single features, attention can select whole objects [19–21]. Objects are among the suggested “units” of attention because attention to a single feature of an object causes the selection of all of its features [19–21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near-optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

Integration trumps selection in object recognition.

Science.gov (United States)

Saarela, Toni P; Landy, Michael S

2015-03-30

Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Selective hedging strategies for oil stockpiling

International Nuclear Information System (INIS)

Yun, Won-Cheol

2006-01-01

As a feasible option for improving the economics and operational efficiency of stockpiling by public agency, this study suggests simple selective hedging strategies using forward contracts. The main advantage of these selective hedging strategies over the previous ones is not to predict future spot prices, but to utilize the sign and magnitude of basis easily available to the public. Using the weekly spot and forward prices of West Texas Intermediate for the period of October 1997-August 2002, this study adopts an ex ante out-of-sample analysis to examine selective hedging performances compared to no-hedge and minimum-variance routine hedging strategies. To some extent, selective hedging strategies dominate the traditional routine hedging strategy, but do not improve upon the expected returns of no-hedge case, which is mainly due to the data characteristics of out-of-sample period used in this analysis

Highly improved sensibility and selectivity ethanol sensor of mesoporous Fe-doped NiO nanowires

Science.gov (United States)

Li, X. Q.; Wei, J. Q.; Xu, J. C.; Jin, H. X.; Jin, D. F.; Peng, X. L.; Hong, B.; Li, J.; Yang, Y. T.; Ge, H. L.; Wang, Xinqing

2017-12-01

In this paper, nickel oxides (NiO) and iron (Fe)-doped NiO nanowires (NWs) with the various doping content (from 1 to 9 at%) were synthesized by using SBA-15 templates with the nanocasting method. All samples were synthesized in the same conditions and exhibited the same mesoporous-structures, uniform diameter, and defects. Mesoporous-structures with high surface area created more active sites for the adsorption of oxygen on the surface of all samples, resulting in the smaller surface resistance in air. The impurity energy levels from the donor Fe-doping provided electrons to neutralize the holes of p-type Fe-doped NiO NWs, which greatly enhanced the total resistance. The comparative gas-sensing study between NiO NWs and Fe-doped NiO NWs indicated that the high-valence donor Fe-doping obviously improved the ethanol sensitivity and selectivity for Fe-doped NiO NWs. And Ni0.94Fe0.06O1.03 NWs sensor presented the highest sensitivity of 14.30 toward ethanol gas at 320 °C for the high-valence metal-doping.

The Lean Reference Collection: Improving Functionality through Selection and Weeding.

Science.gov (United States)

Nolan, Christopher W.

1991-01-01

Discusses references collections in academic libraries and offers guidelines for placing materials in a reference collection that focus on their suitability for true reference functions and the expected frequency of use. Problems with poorly managed collections are discussed, and the importance of selection policies and weeding are emphasized. (37…

Selection Method for COTS Systems

DEFF Research Database (Denmark)

Hedman, Jonas; Andersson, Bo

2014-01-01

feature behind the method is that improved understanding of organizational ‘ends’ or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends’ (e.g. improved organizational effectiveness) and ‘means’ (e.g. implementing COTS systems). This way...

Direct and indirect selection responses for seed yield and its components in

Directory of Open Access Journals (Sweden)

rasoul dehghan

2017-06-01

Full Text Available Breeding based on selection indices is an effective method for improving complex traits such as yield. To assess the efficiency of different selection method, 83 exotic along with 17 Iranian safflower genotypes were evaluated at the research farm of Isfahan University of Technology using 10×10 simple lattice design with three replications in 2011. In this study, the selection indices of Smith-Hazel and Pesek-Baker were determined based on the number of capitulum per plant, number of seeds per capitulum and 1000-seed weight. Also response to selection and relative selection efficiency were estimated for traits under study and seed yield. The highest estimated selection efficiency for genetic improvement of seed yield was obtained via selection for number of capitulum per plant. Therefore, this trait can be used as an appropriate selection criterion for improvement of seed yield. The results showed that seed yield was highly correlated with each of these indices and the estimated efficiency of indirect selection via these indices was relatively high. Thus, it seems that these selection indices can be effectively used for seed yield improvement. Results of present study showed that the efficiency of Smith-Hazel indices for simultaneous improvement of number of capitulum per plant, number of seeds per capitulum and 1000-seed weight was higher than that of Pesek-Baker index.

Selection and Participation in Higher Education: University Selection in Support of Student Success and Diversity of Participation

Science.gov (United States)

Palmer, Nigel; Bexley, Emmaline; James, Richard

2011-01-01

A range of imperatives underpin university selection practices. These include demonstrating merit based on prior academic achievement and supporting successful graduate outcomes in the professions and in broader fields of endeavour. They also include improving diversity of participation and equality of educational opportunity. Selection for…

Genomic selection improves response to selection in resilience by exploiting genotype by environment interactions

NARCIS (Netherlands)

Mulder, Herman

2016-01-01

Genotype by environment interactions (GxE) are very common in livestock and hamper genetic improvement. On the other hand, GxE is a source of genetic variation: genetic variation in response to environment, e.g., environmental perturbations such as heat stress or disease. In livestock breeding,

Natural selection. VII. History and interpretation of kin selection theory.

Science.gov (United States)

Frank, S A

2013-06-01

Kin selection theory is a kind of causal analysis. The initial form of kin selection ascribed cause to costs, benefits and genetic relatedness. The theory then slowly developed a deeper and more sophisticated approach to partitioning the causes of social evolution. Controversy followed because causal analysis inevitably attracts opposing views. It is always possible to separate total effects into different component causes. Alternative causal schemes emphasize different aspects of a problem, reflecting the distinct goals, interests and biases of different perspectives. For example, group selection is a particular causal scheme with certain advantages and significant limitations. Ultimately, to use kin selection theory to analyse natural patterns and to understand the history of debates over different approaches, one must follow the underlying history of causal analysis. This article describes the history of kin selection theory, with emphasis on how the causal perspective improved through the study of key patterns of natural history, such as dispersal and sex ratio, and through a unified approach to demographic and social processes. Independent historical developments in the multivariate analysis of quantitative traits merged with the causal analysis of social evolution by kin selection. © 2013 The Author. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

A moving story: Whole-body motor training selectively improves the appraisal of action meanings in naturalistic narratives.

Science.gov (United States)

Trevisan, Piergiorgio; Sedeño, Lucas; Birba, Agustina; Ibáñez, Agustín; García, Adolfo M

2017-10-02

This study examined whether systematic whole-body stimulation and increased attention to visuospatial motion patterns can enhance the appraisal of action meanings evoked by naturalistic texts. Participants listened to action and neutral (non-action) narratives before and after videogame-based bodily training, and responded to questions on information realized by verbs (denoting abstract and action processes) and circumstances (conveying locative or temporal details, for example). Strategically, we worked with dyslexic children, whose potential comprehension deficits could give room to post-training improvements. Results showed a selective boost in understanding of action information, even when controlling for baseline performance. Also, this effect proved uninfluenced by short-term memory skills, and it was absent when training relied on non-action videogames requiring minimal bodily engagement. Of note, the movements described in the texts did not match those performed by participants, suggesting that well-established effector- and direction-specific language embodiment effects may be accompanied by more coarse-grained sensorimotor resonance, driven by activation of motor and visuospatial sensory systems. In sum, the stimulation of movement-related mechanisms seems to selectively boost the appraisal of actions evoked by naturalistic texts. By demonstrating such links between two real-life activities, our study offers an empirical tie between embodied and situated accounts of cognition.

Rate of improvement during and across three treatments for panic disorder with or without agoraphobia : Cognitive behavioral therapy, selective serotonin reuptake inhibitor or both combined

NARCIS (Netherlands)

Van Apeldoorn, Franske J.; Van Hout, Wiljo J. P. J.; Timmerman, Marieke E.; Mersch, Peter Paul A.; den Boer, Johan A.

2013-01-01

Background: Existing literature on panic disorder (PD) yields no data regarding the differential rates of improvement during Cognitive Behavioral Therapy (CBT), Selective Serotonin Reuptake Inhibitor (SSRI) or both combined (CBT+SSRI). Method: Patients were randomized to CBT, SSRI or CBT+SSRI which

Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat.

Science.gov (United States)

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2018-01-01

To evaluate the potential of genomic selection (GS), a selection experiment with GS and phenotypic selection (PS) was performed in an allogamous crop, common buckwheat ( Fagopyrum esculentum Moench). To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598-50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding.

Multivariate analysis and determination of the best indirect selection criteria to genetic improvement the biological nitrogen fixation ability in common bean genotypes (Phaseolus vulgaris L.

Directory of Open Access Journals (Sweden)

Golparvar Reza Ahmad

2012-01-01

Full Text Available In order to determine the best indirect selection criteria for genetic improvement of biological nitrogen fixation, sixty four common bean genotypes were cultivated in two randomized complete block design. Genotypes were inoculated with bacteria Rhizobium legominosarum biovar Phaseoli isolate L-109 only in one of the experiments. The second experiment was considered as check for the first. Correlation analysis showed positive and highly significant correlation of majority of the traits with percent of nitrogen fixation. Step-wise regression designated that traits percent of total nitrogen of shoot, number of nodule per plant and biological yield accounted for 92.3 percent of variation exist in percent of nitrogen fixation. Path analysis indicated that these traits have direct and positive effect on percent of nitrogen fixation. Hence, these traits are promising indirect selection criteria for genetic improvement of nitrogen fixation capability in common bean genotypes especially in early generations.

An improved method of crafting a multi-electrode spiral cuff for the selective.

Science.gov (United States)

Rozman, Janez; Pečlin, Polona; Ribarič, Samo; Godec, Matjaž; Burja, Jaka

2018-01-17

This article reviews an improved methodology and technology for crafting a multi-electrode spiral cuff for the selective activation of nerve fibres in particular superficial regions of a peripheral nerve. The analysis, structural and mechanical properties of the spot welds used for the interconnections between the stimulating electrodes and stainless-steel lead wires are presented. The cuff consisted of 33 platinum electrodes embedded within a self-curling 17-mm-long silicone spiral sheet with a nominal internal diameter of 2.5 mm. The weld was analyzed using scanning electron microscopy and nanohardness tests, while the interconnection was investigated using destructive load tests. The functionality of the cuff was tested in an isolated porcine vagus nerve. The results of the scanning electron microscopy show good alloying and none of the typical welding defects that occur between the wire and the platinum foil. The results of the destructive load tests show that the breaking loads were between 3.22 and 5 N. The results of the nanohardness testing show that the hardness of the weld was different for the particular sites on the weld sample. Finally, the results of the functional testing show that for different stimulation intensities both the compound action potential deflection and the shape are modulated.

Hydrazinonicotinic acid derivatization for selective ionization and improved glycan structure characterization by MALDI-MS.

Science.gov (United States)

Jiao, Jing; Yang, Lijun; Zhang, Ying; Lu, Haojie

2015-08-21

The analysis of glycan is important for understanding cell biology and disease processes because the glycans play a key role in many important biological behaviors, such as cell division, cellular localization, tumor immunology and inflammation. Nevertheless, it is still hard work to analyze glycans by MALDI-MS, which generally stems from the inherent low abundance and the low ionization efficiency of glycans. Moreover, the difficulty in generating informative fragmentations further hinders glycans structure characterization. In this work, hydrazinonicotinic acid (HYNIC) was used as a novel derivatized reagent for improved and selective detection of glycans. Through tagging the reducing terminus of glycans with the diazanyl group of HYNIC, significant enhancement of the ionization efficiency of glycans was achieved. After derivatization, the signal to noise ratio (S/N) of the maltoheptaose was improved by more than one order of magnitude in positive mode. HYNIC derivatization also allowed the sensitive detection of sialylated glycan in negative mode, with a 15 fold enhancement of S/N. Interestingly, it is noteworthy that the HYNIC reagent not only effectively labeled the reducing end of glycans in the presence of tryptic peptides, but also suppressed the ionization of peptides, enabling the direct detection of glycans from glycoprotein without separation. Therefore, analysis of glycans became easier due to the omission of a pre-separation step. Importantly, by using different acid reagents as the catalyst, derivatized product signals corresponding to [M + Na](+) or [M + H](+) were obtained respectively, which yield complementary fragmentation patterns for the structure elucidation of glycans. Finally, more than 40 N-glycans were successfully detected in 10 μL human serum using this method.

Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat

Directory of Open Access Journals (Sweden)

Shiori Yabe

2018-03-01

Full Text Available To evaluate the potential of genomic selection (GS, a selection experiment with GS and phenotypic selection (PS was performed in an allogamous crop, common buckwheat (Fagopyrum esculentum Moench. To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598–50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding.

Collaborative Improvement

DEFF Research Database (Denmark)

Kaltoft, Rasmus

The thesis data have been collected in the EU-sponsored project: Collaborative Improvement Tool for the Extended Manufacturing Enterprise, CO-IMPROVE. In this project four universities (Denmark, Ireland, Italy, and The Netherlands), two software vendors (Greece and Sweden) and three companies...... (Denmark, Italy and The Netherlands) each with three to five suppliers were involved. The CO-IMPROVE project and the thesis is based on “action research” and “action learning”. The main aim of the whole project is through actual involvement and actions make the researchers, companies and selected suppliers...... learn how to improve operations in (hopefully) a win-win like manner through collaboration....

Exploration of the Hypothalamic-Pituitary-Adrenal Axis to Improve Animal Welfare by Means of Genetic Selection: Lessons from the South African Merino

Directory of Open Access Journals (Sweden)

Schalk Cloete

2013-05-01

Full Text Available It is a difficult task to improve animal production by means of genetic selection, if the environment does not allow full expression of the animal’s genetic potential. This concept may well be the future for animal welfare, because it highlights the need to incorporate traits related to production and robustness, simultaneously, to reach sustainable breeding goals. This review explores the identification of potential genetic markers for robustness within the hypothalamic-pituitary-adrenal axis (HPAA, since this axis plays a vital role in the stress response. If genetic selection for superior HPAA responses to stress is possible, then it ought to be possible to breed robust and easily managed genotypes that might be able to adapt to a wide range of environmental conditions whilst expressing a high production potential. This approach is explored in this review by means of lessons learnt from research on Merino sheep, which were divergently selected for their multiple rearing ability. These two selection lines have shown marked differences in reproduction, production and welfare, which makes this breeding programme ideal to investigate potential genetic markers of robustness. The HPAA function is explored in detail to elucidate where such genetic markers are likely to be found.

High-throughput selection for cellulase catalysts using chemical complementation.

Science.gov (United States)

Peralta-Yahya, Pamela; Carter, Brian T; Lin, Hening; Tao, Haiyan; Cornish, Virginia W

2008-12-24

Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases, however, is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Because of the large number of enzyme variants that selections can now test as compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity.

Training-induced improvement of response selection and error detection in aging assessed by task switching: Effects of cognitive, physical and relaxation training

Directory of Open Access Journals (Sweden)

Patrick Darius Gajewski

2012-05-01

Full Text Available Cognitive control functions decline with increasing age. One of them is response selection that forms the link between the goals and the motor system and is therefore crucial for performance outcomes in cognitive tasks. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in electrophysiological brain activity, as measured in event-related potentials (ERPs. 141 healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength-training, cognitive training (paper-pencil and computer-aided, relaxation and wellness (social control group and a no-contact control group that did not receive any intervention. Training sessions took place twice a week for 90 minutes for a period of 4 months.The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task-sets in working memory and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials (ERP which showed higher amplitudes in a number of potentials associated with response selection (N2, allocation of cognitive resources (P3b and error detection (Ne.Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods.

Technology-enabled employee selection: Tweaking the system for better person-environment fit

DEFF Research Database (Denmark)

Holm, Anna B.

Organizations increasingly use information and communication technologies to facilitate their employee selection process. The practice is commonly referred to as e-selection. Recent research has shown that e-selection can significantly improve the efficiency of assessment and selection. However......, organizations also strive to hire the best possible candidates and seek to improve effectiveness of their selection process and achieve better person–environment (PE) fit. The presented research reviews existing literature on PE fit and e-selection and puts forward a heuristic model of technology...

High Selectivity Oxygen Delignification

Energy Technology Data Exchange (ETDEWEB)

Lucian A. Lucia

2005-11-15

Project Objective: The objectives of this project are as follows: (1) Examine the physical and chemical characteristics of a partner mill pre- and post-oxygen delignified pulp and compare them to lab generated oxygen delignified pulps; (2) Apply the chemical selectivity enhancement system to the partner pre-oxygen delignified pulps under mill conditions (with and without any predetermined amounts of carryover) to determine how efficiently viscosity is preserved, how well selectivity is enhanced, if strength is improved, measure any yield differences and/or bleachability differences; and (3) Initiate a mill scale oxygen delignification run using the selectivity enhancement agent, collect the mill data, analyze it, and propose any future plans for implementation.

Antecedent Selection for Sluicing

DEFF Research Database (Denmark)

Anand, Pranav; Hardt, Daniel

2016-01-01

Sluicing is an elliptical process where the majority of a question can go unpronounced as long as there is a salient antecedent in previous discourse. This paper considers the task of antecedent selection: finding the correct antecedent for a given case of sluicing. We argue that both syntactic...... and discourse relationships are important in antecedent selection, and we construct linguistically sophisticated features that describe the relevant relationships. We also define features that describe the relation of the content of the antecedent and the sluice type. We develop a linear model which achieves...... accuracy of 72.4%, a substantial improvement over a strong manually constructed baseline. Feature analysis confirms that both syntactic and discourse features are important in antecedent selection....

A Reinforcement Learning Approach to Improve the Argument Selection Effectiveness in Argumentation-based Negotiation

OpenAIRE

Amandi, Analia Adriana; Monteserin, Ariel José

2016-01-01

Argument selection is considered the essence of the strategy in argumentation-based negotiation. An agent, which is arguing during a negotiation, must decide what arguments are the best to persuade the opponent. In fact, in each negotiation step, the agent must select an argument from a set of candidate arguments by applying some selection policy. Following this policy, the agent observes some factors of the negotiation context, for instance: trust in the opponent and expected utility of the...

Selection criteria for the improvement of seed yield and its components in advances generations of lentil (lens culinaris medik)

International Nuclear Information System (INIS)

Ashraf, S.; Hanif, M.; Sadiq, S.; Abbas, G.; Asghar, M.J.

2008-01-01

Present study was conducted at Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad during the years 2006 and 2007 with the objectives; to study the inheritance of seed yield and related traits in both hybridized (F6) and mutated (M6) populations of lentil and to determine the best selection criterion for the improvement of seed yield. Different genetic parameters (variances, heritabilities, genetic gains and correlations) were computed to study the inheritance pattern and interrelationships of different traits. High heritability was observed for days to flower (97.40%), plant height (90.80%), pods per plant (86.20%), hundred seed weight (83.50%) and seed yield per plant (91.80%) in F6 and for days to flower (96.9%), days to mature (91.8%), hundred seed weight (89.0%) and seed yield per plant (94.0%) in M6 generation. High heritability coupled with moderate to high genetic advance was noted for plant height (90.8%, 16.29) pods per plant (86.20%, 25.53) hundred seed weight (83.50%, 35.67) and seed yield per plant (91.80%, 35.84) in F6 generation and for days to flower (96.9%, 25.08), hundred seed weight (89.0%, 25.56) and seed yield per plant (94.0%, 37.01) in M6 generation. The traits mentioned were found to be under the control of additive genes. Seed yield had positive and significant correlation with pods per plant in M6 and with seed weight in both generations. It was concluded that seed weight and pods per plant may be used as selection criterion in both hybridized and mutated populations for the improvement of seed yield. (author)

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Process signal selection method to improve the impact mitigation of sensor broken for diagnosis using machine learning

International Nuclear Information System (INIS)

Minowa, Hirotsugu; Gofuku, Akio

2014-01-01

Accidents of industrial plants cause large loss on human, economic, social credibility. In recent, studies of diagnostic methods using techniques of machine learning are expected to detect early and correctly abnormality occurred in a plant. However, the general diagnostic machines are generated generally to require all process signals (hereafter, signals) for plant diagnosis. Thus if trouble occurs such as process sensor is broken, the diagnostic machine cannot diagnose or may decrease diagnostic performance. Therefore, we propose an important process signal selection method to improve impact mitigation without reducing the diagnostic performance by reducing the adverse effect of noises on multi-agent diagnostic system. The advantage of our method is the general-purpose property that allows to be applied to various supervised machine learning and to set the various parameters to decide termination of search. The experiment evaluation revealed that diagnostic machines generated by our method using SVM improved the impact mitigation and did not reduce performance about the diagnostic accuracy, the velocity of diagnosis, predictions of plant state near accident occurrence, in comparison with the basic diagnostic machine which diagnoses by using all signals. This paper reports our proposed method and the results evaluated which our method was applied to the simulated abnormal of the fast-breeder reactor Monju. (author)

Improving the seed germination of little bluestem with selection

Science.gov (United States)

Rapid seed germination is an important characteristic when it comes to plant stand establishment under variable environmental conditions. This research was designed to improve the seed germination of six experimental Syn-0 lines of little bluestem [Schizachyrium scoparium (Michx.) Nash]. Two cycle...

THE USE OF SELECTED ANAESTHETIC DRUGS IN SEARCH OF A METHOD FOR IMPROVING EARTHWORMS’ WELFARE

Directory of Open Access Journals (Sweden)

Agnieszka Podolak-Machowska

2013-07-01

Full Text Available This paper describes selected effects of body contact of earthworms Dendrobaena veneta Rosa with local anaesthetic (LA drugs used for human anesthesia (lidocaine and prilocaine and anaesthetics for aquatic animals (MS-222. The findings showed safe and effective immobilization of earthworms with prilocaine at a concentration of 0.25-1%. At the applied concentrations lidocaine was safe, but less effective. On the other hand, MS-222, at the applied concentrations had a strongly irritating effect for earthworms and induced convulsive body movements connected with a discharge of coelomic fluid. The results may be relevant both for improving the welfare of earthworms during experiments and for the organization of research involving testing drugs on invertebrates. In this case, by using earthworms as an experimental model and by applying the method for measuring their mobility after contact with anaesthetics, which has been described in this article, it might be possible to replace experiments on guinea pigs, rabbits, rats and mice, which are expensive and require an approval of an ethics committee, with laboratory tests on earthworms.

International trends in patient selection for elective endovascular aneurysm repair: sicker patients with safer anatomy leading to improved 1-year survival.

Science.gov (United States)

Fitridge, Robert A; Boult, Margaret; Mackillop, Clare; De Loryn, Tania; Barnes, Mary; Cowled, Prue; Thompson, Matthew M; Holt, Peter J; Karthikesalingam, Alan; Sayers, Robert D; Choke, Edward; Boyle, Jonathan R; Forbes, Thomas L; Novick, Teresa V

2015-02-01

To review the trends in patient selection and early death rate for patients undergoing elective endovascular repair of infrarenal abdominal aortic aneurysms (EVAR) in 3 countries. For this study, audit data from 4,163 patients who had undergone elective infrarenal EVAR were amalgamated. The data originated from Australia, Canada (Ontario), and England (London, Cambridge, and Leicester). Statistical analyses were undertaken to determine whether patient characteristics and early death rate varied between and within study groups and over time. The study design was retrospective analysis of data collected prospectively between 1999 and 2012. One-year survival improved over time (P = 0.0013). Canadian patients were sicker than those in Australia or England (P international comparison, several trends were noted including improved 1-year survival despite declining patient health (as measured by increasing ASA status). This may reflect greater knowledge regarding EVAR that centers from different countries have gained over the last decade and improved medical management of patients with aneurysmal disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls

NARCIS (Netherlands)

Roos, de A.P.W.; Schrooten, C.; Veerkamp, R.F.; Arendonk, van J.A.M.

2011-01-01

Genomic selection has the potential to revolutionize dairy cattle breeding because young animals can be accurately selected as parents, leading to a much shorter generation interval and higher rates of genetic gain. The aims of this study were to assess the effects of genomic selection and reduction

Genetic improvement of Pacific white shrimp (Penaeus (Litopenaeus vannamei: perspectives for genomic selection

Directory of Open Access Journals (Sweden)

Héctor eCastillo-Juárez

2015-03-01

Full Text Available The use of breeding programs for the Pacific white shrimp (Penaeus (Litopenaeus vannamei based on mixed linear models with pedigreed data are described. The application of these classic breeding methods yielded continuous progress of great value to increase the profitability of the shrimp industry in several countries. Recent advances in such areas as genomics in shrimp will allow for the development of new breeding programs in the near future that will increase genetic progress. In particular, these novel techniques may help increase disease resistance to specific emerging diseases, which is today a very important component of shrimp breeding programs. Thanks to increased selection accuracy, simulated genetic advance using genomic selection for survival to a disease challenge was up to 2.6 times that of phenotypic sib selection.

Strengthening the influenza vaccine virus selection and development process: Report of the 3rd WHO Informal Consultation for Improving Influenza Vaccine Virus Selection held at WHO headquarters, Geneva, Switzerland, 1-3 April 2014.

Science.gov (United States)

Ampofo, William K; Azziz-Baumgartner, Eduardo; Bashir, Uzma; Cox, Nancy J; Fasce, Rodrigo; Giovanni, Maria; Grohmann, Gary; Huang, Sue; Katz, Jackie; Mironenko, Alla; Mokhtari-Azad, Talat; Sasono, Pretty Multihartina; Rahman, Mahmudur; Sawanpanyalert, Pathom; Siqueira, Marilda; Waddell, Anthony L; Waiboci, Lillian; Wood, John; Zhang, Wenqing; Ziegler, Thedi

2015-08-26

Despite long-recognized challenges and constraints associated with their updating and manufacture, influenza vaccines remain at the heart of public health preparedness and response efforts against both seasonal and potentially pandemic influenza viruses. Globally coordinated virological and epidemiological surveillance is the foundation of the influenza vaccine virus selection and development process. Although national influenza surveillance and reporting capabilities are being strengthened and expanded, sustaining and building upon recent gains has become a major challenge. Strengthening the vaccine virus selection process additionally requires the continuation of initiatives to improve the timeliness and representativeness of influenza viruses shared by countries for detailed analysis by the WHO Global Influenza Surveillance and Response System (GISRS). Efforts are also continuing at the national, regional, and global levels to better understand the dynamics of influenza transmission in both temperate and tropical regions. Improved understanding of the degree of influenza seasonality in tropical countries of the world should allow for the strengthening of national vaccination policies and use of the most appropriate available vaccines. There remain a number of limitations and difficulties associated with the use of HAI assays for the antigenic characterization and selection of influenza vaccine viruses by WHOCCs. Current approaches to improving the situation include the more-optimal use of HAI and other assays; improved understanding of the data produced by neutralization assays; and increased standardization of serological testing methods. A number of new technologies and associated tools have the potential to revolutionize influenza surveillance and response activities. These include the increasingly routine use of whole genome next-generation sequencing and other high-throughput approaches. Such approaches could not only become key elements in outbreak

AID SELECTIVITY PRACTICE AND AID EFFECTIVENESS IN SUB-SAHARAN AFRICA

Directory of Open Access Journals (Sweden)

Adeniyi Jimmy Adedokun

2017-09-01

Full Text Available Foreign aid strategies have undergone restructuring as donors adopt aid selectivity practice to improve aid effectiveness. This study investigates the impact of aid selectivity practice on aid effectiveness (aid-growth relationship in Sub-Saharan Africa (SSA and several groups of countries within SSA from 1980 to 2012. Employing system generalized methods of moments (system GMM technique; the study produces strong evidence that there is significant improvement in aid effectiveness due to aid selectivity practice.

Supplier selection in manufacturing innovation chain-oriented public procurement based on improved PSO method

Directory of Open Access Journals (Sweden)

Xin Xu

2014-01-01

Full Text Available Purpose: At the dynamic innovation market, it is very difficult for an enterprise to accomplish innovation individually; technology innovation is shifting towards collaborative R&D chain mode. Thus, supplier selection based on individually innovation efficiency of enterprise is inapplicable to construct collaborative R&D innovation chain. This study is seeking to address how to select R&D innovation chain supplier in manufacturing industry. Design/methodology/approach: Firstly, Delphi method and AHP method are applied to establish an index system evaluating the suppliers of innovation chain, and then each index is weighted by experts with AHP method. Thirdly, optimized PSO algorithm is put forwarded based on the optimal efficiency of innovation chain to discriminate ideal suppliers meeting realistic conditions. Fourthly, innovation chain construction at generator manufacturing industry was taken as empirical case study to testify the improved PSO model. Findings: The innovation chain is comprised up by several enterprises, innovation performance of a single enterprise is not always positively correlated to that of one innovation chain, and the proposed model is capable to find out the best combination to construct an innovation chain. Research limitations/implications: The relations between these constructs with other variables of interest to the academicals fields were analyzed by a precise and credible data with a clear and concise description of the supply chain integration measurement scales. Practical implications: providing scales that are valid as a diagnostic tool for best practices, as well as providing a benchmark with which to compare the score for each individual plant against a chain of industrial innovation from machinery. Originality/value: Innovation chain integration is an important factor in explaining the innovation performance of companies. The vast range of results obtained is due to the fact that there is no exactness to

Improving influenza vaccine virus selection: report of a WHO informal consultation held at WHO headquarters, Geneva, Switzerland, 14-16 June 2010.

Science.gov (United States)

Ampofo, William K; Baylor, Norman; Cobey, Sarah; Cox, Nancy J; Daves, Sharon; Edwards, Steven; Ferguson, Neil; Grohmann, Gary; Hay, Alan; Katz, Jacqueline; Kullabutr, Kornnika; Lambert, Linda; Levandowski, Roland; Mishra, A C; Monto, Arnold; Siqueira, Marilda; Tashiro, Masato; Waddell, Anthony L; Wairagkar, Niteen; Wood, John; Zambon, Maria; Zhang, Wenqing

2012-03-01

• For almost 60 years, the WHO Global Influenza Surveillance and Response System (GISRS) has been the key player in monitoring the evolution and spread of influenza viruses and recommending the strains to be used in human influenza vaccines. The GISRS has also worked to continually monitor and assess the risk posed by potential pandemic viruses and to guide appropriate public health responses. • The expanded and enhanced role of the GISRS following the adoption of the International Health Regulations (2005), recognition of the continuing threat posed by avian H5N1 and the aftermath of the 2009 H1N1 pandemic provide an opportune time to critically review the process by which influenza vaccine viruses are selected. In addition to identifying potential areas for improvement, such a review will also help to promote greater appreciation by the wider influenza and policy-making community of the complexity of influenza vaccine virus selection. • The selection process is highly coordinated and involves continual year-round integration of virological data and epidemiological information by National Influenza Centres (NICs), thorough antigenic and genetic characterization of viruses by WHO Collaborating Centres (WHOCCs) as part of selecting suitable candidate vaccine viruses, and the preparation of suitable reassortants and corresponding reagents for vaccine standardization by WHO Essential Regulatory Laboratories (ERLs). • Ensuring the optimal effectiveness of vaccines has been assisted in recent years by advances in molecular diagnosis and the availability of more extensive genetic sequence data. However, there remain a number of challenging constraints including variations in the assays used, the possibility of complications resulting from non-antigenic changes, the limited availability of suitable vaccine viruses and the requirement for recommendations to be made up to a year in advance of the peak of influenza season because of production constraints. �

Selection for Surgical Training: An Evidence-Based Review.

Science.gov (United States)

Schaverien, Mark V

2016-01-01

The predictive relationship between candidate selection criteria for surgical training programs and future performance during and at the completion of training has been investigated for several surgical specialties, however there is no interspecialty agreement regarding which selection criteria should be used. Better understanding the predictive reliability between factors at selection and future performance may help to optimize the process and lead to greater standardization of the surgical selection process. PubMed and Ovid MEDLINE databases were searched. Over 560 potentially relevant publications were identified using the search strategy and screened using the Cochrane Collaboration Data Extraction and Assessment Template. 57 studies met the inclusion criteria. Several selection criteria used in the traditional selection demonstrated inconsistent correlation with subsequent performance during and at the end of surgical training. The following selection criteria, however, demonstrated good predictive relationships with subsequent resident performance: USMLE examination scores, Letters of Recommendation (LOR) including the Medical Student Performance Evaluation (MSPE), academic performance during clinical clerkships, the interview process, displaying excellence in extracurricular activities, and the use of unadjusted rank lists. This systematic review supports that the current selection process needs to be further evaluated and improved. Multicenter studies using standardized outcome measures of success are now required to improve the reliability of the selection process to select the best trainees. Published by Elsevier Inc.

Solid-State NMR on bacterial cells: selective cell wall signal enhancement and resolution improvement using dynamic nuclear polarization

International Nuclear Information System (INIS)

Takahashi, Hiroki; Bardet, Michel; De Paepe, Gael; Hediger, Sabine; Ayala, Isabel; Simorre, Jean-Pierre

2013-01-01

Dynamic nuclear polarization (DNP) enhanced solid-state nuclear magnetic resonance (NMR) has recently emerged as a powerful technique for the study of material surfaces. In this study, we demonstrate its potential to investigate cell surface in intact cells. Using Bacillus subtilis bacterial cells as an example, it is shown that the polarizing agent 1-(TEMPO-4-oxy)-3-(TEMPO-4-amino)propan-2-ol (TOTAPOL) has a strong binding affinity to cell wall polymers (peptidoglycan). This particular interaction is thoroughly investigated with a systematic study on extracted cell wall materials, disrupted cells, and entire cells, which proved that TOTAPOL is mainly accumulating in the cell wall. This property is used on one hand to selectively enhance or suppress cell wall signals by controlling radical concentrations and on the other hand to improve spectral resolution by means of a difference spectrum. Comparing DNP-enhanced and conventional solid-state NMR, an absolute sensitivity ratio of 24 was obtained on the entire cell sample. This important increase in sensitivity together with the possibility of enhancing specifically cell wall signals and improving resolution really opens new avenues for the use of DNP-enhanced solid-state NMR as an on-cell investigation tool. (authors)

Solid-state NMR on bacterial cells: selective cell wall signal enhancement and resolution improvement using dynamic nuclear polarization.

Science.gov (United States)

Takahashi, Hiroki; Ayala, Isabel; Bardet, Michel; De Paëpe, Gaël; Simorre, Jean-Pierre; Hediger, Sabine

2013-04-03

Dynamic nuclear polarization (DNP) enhanced solid-state nuclear magnetic resonance (NMR) has recently emerged as a powerful technique for the study of material surfaces. In this study, we demonstrate its potential to investigate cell surface in intact cells. Using Bacillus subtilis bacterial cells as an example, it is shown that the polarizing agent 1-(TEMPO-4-oxy)-3-(TEMPO-4-amino)propan-2-ol (TOTAPOL) has a strong binding affinity to cell wall polymers (peptidoglycan). This particular interaction is thoroughly investigated with a systematic study on extracted cell wall materials, disrupted cells, and entire cells, which proved that TOTAPOL is mainly accumulating in the cell wall. This property is used on one hand to selectively enhance or suppress cell wall signals by controlling radical concentrations and on the other hand to improve spectral resolution by means of a difference spectrum. Comparing DNP-enhanced and conventional solid-state NMR, an absolute sensitivity ratio of 24 was obtained on the entire cell sample. This important increase in sensitivity together with the possibility of enhancing specifically cell wall signals and improving resolution really opens new avenues for the use of DNP-enhanced solid-state NMR as an on-cell investigation tool.

Benchmarking Variable Selection in QSAR.

Science.gov (United States)

Eklund, Martin; Norinder, Ulf; Boyer, Scott; Carlsson, Lars

2012-02-01

Variable selection is important in QSAR modeling since it can improve model performance and transparency, as well as reduce the computational cost of model fitting and predictions. Which variable selection methods that perform well in QSAR settings is largely unknown. To address this question we, in a total of 1728 benchmarking experiments, rigorously investigated how eight variable selection methods affect the predictive performance and transparency of random forest models fitted to seven QSAR datasets covering different endpoints, descriptors sets, types of response variables, and number of chemical compounds. The results show that univariate variable selection methods are suboptimal and that the number of variables in the benchmarked datasets can be reduced with about 60 % without significant loss in model performance when using multivariate adaptive regression splines MARS and forward selection. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application

Science.gov (United States)

Gibbs, Matthew S.; McInerney, David; Humphrey, Greer; Thyer, Mark A.; Maier, Holger R.; Dandy, Graeme C.; Kavetski, Dmitri

2018-02-01

Monthly to seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work focuses on improving such forecasts by considering the following two aspects: (1) state updating to force the models to match observations from the start of the forecast period, and (2) selection of a shorter calibration period that is more representative of the forecast period, compared to a longer calibration period traditionally used. The analysis is undertaken in the context of using streamflow forecasts for environmental flow water management of an open channel drainage network in southern Australia. Forecasts of monthly streamflow are obtained using a conceptual rainfall-runoff model combined with a post-processor error model for uncertainty analysis. This model set-up is applied to two catchments, one with stronger evidence of non-stationarity than the other. A range of metrics are used to assess different aspects of predictive performance, including reliability, sharpness, bias and accuracy. The results indicate that, for most scenarios and metrics, state updating improves predictive performance for both observed rainfall and forecast rainfall sources. Using the shorter calibration period also improves predictive performance, particularly for the catchment with stronger evidence of non-stationarity. The results highlight that a traditional approach of using a long calibration period can degrade predictive performance when there is evidence of non-stationarity. The techniques presented can form the basis for operational monthly streamflow forecasting systems and provide support for environmental decision-making.

Improving the selectivity and sensitivity for quantifying 8-α-hydroxy-mutilin in rabbit tissues by using basic mobile phases and negative ionization.

Science.gov (United States)

Tan, Aimin; Gu, Guifen; Gui, Xuan; Wu, Yanxin; Bolger, Gordon; Licollari, Albert; Fanaras, John C

2018-01-01

Previously reported LC-MS methods for quantifying 8-α-hydroxy-mutilin (a marker residue of tiamulin) in tissues all used a pseudo MRM transition (from protonated molecular ion to protonated molecular ion, m/z 337→337) due to difficulties in finding a product ion, leading to suboptimal selectivity and sensitivity for detection. By using electrospray negative ionization in a basic medium, we, for the first time, found a highly selective and sensitive true MRM transition for 8-α-hydroxy-mutilin, m/z 335→179. With this newly found MRM transition and the use of pleuromutilin as the internal standard, a very sensitive, selective, and robust LC-MS/MS method has been developed and validated for quantifying 8-α-hydroxy-mutilin in rabbit tissues (muscle, liver, kidney, and fat). In comparison with the previously published methods, the selectivity and sensitivity were significantly improved. For the concentration range validated (0.2-10ppm or 0.2-10μg/g), the within-run and between-run accuracies (% bias) ranged from -5.0 to 3.1 and -4.9 to 3.0, respectively. The% CV ranged from 2.2 to 6.6 and 4.7 to 8.3 for within-run and between-run precisions, respectively. The validated method was successfully used to support two GLP tissue residue depletion studies in rabbits. Copyright © 2017 Elsevier B.V. All rights reserved.

EVP-6124, a novel and selective α7 nicotinic acetylcholine receptor partial agonist, improves memory performance by potentiating the acetylcholine response of α7 nicotinic acetylcholine receptors.

Science.gov (United States)

Prickaerts, Jos; van Goethem, Nick P; Chesworth, Richard; Shapiro, Gideon; Boess, Frank G; Methfessel, Christoph; Reneerkens, Olga A H; Flood, Dorothy G; Hilt, Dana; Gawryl, Maria; Bertrand, Sonia; Bertrand, Daniel; König, Gerhard

2012-02-01

EVP-6124, (R)-7-chloro-N-quinuclidin-3-yl)benzo[b]thiophene-2-carboxamide, is a novel partial agonist of α7 neuronal nicotinic acetylcholine receptors (nAChRs) that was evaluated here in vitro and in vivo. In binding and functional experiments, EVP-6124 showed selectivity for α7 nAChRs and did not activate or inhibit heteromeric α4β2 nAChRs. EVP-6124 had good brain penetration and an adequate exposure time. EVP-6124 (0.3 mg/kg, p.o.) significantly restored memory function in scopolamine-treated rats (0.1 mg/kg, i.p.) in an object recognition task (ORT). Although donepezil at 0.1 mg/kg, p.o. or EVP-6124 at 0.03 mg/kg, p.o. did not improve memory in this task, co-administration of these sub-efficacious doses fully restored memory. In a natural forgetting test, an ORT with a 24 h retention time, EVP-6124 improved memory at 0.3 mg/kg, p.o. This improvement was blocked by the selective α7 nAChR antagonist methyllycaconitine (0.3 mg/kg, i.p. or 10 μg, i.c.v.). In co-application experiments of EVP-6124 with acetylcholine, sustained exposure to EVP-6124 in functional investigations in oocytes caused desensitization at concentrations greater than 3 nM, while lower concentrations (0.3-1 nM) caused an increase in the acetylcholine-evoked response. These actions were interpreted as representing a co-agonist activity of EVP-6124 with acetylcholine on α7 nAChRs. The concentrations of EVP-6124 that resulted in physiological potentiation were consistent with the free drug concentrations in brain that improved memory performance in the ORT. These data suggest that the selective partial agonist EVP-6124 improves memory performance by potentiating the acetylcholine response of α7 nAChRs and support new therapeutic strategies for the treatment of cognitive impairment. This article is part of a Special Issue entitled 'Post-Traumatic Stress Disorder'. Copyright © 2011 Elsevier Ltd. All rights reserved.

Dietary selection by steers grazing kikuyu

African Journals Online (AJOL)

being grazeA for a period of 3,5 days in a four-week rotation, at ... Cattle improve the quality of their diet by actively seeking ... of stem in their diet. This would explain why the stem fraction mad~ no significant contribution to the equation predicting diet~ry selection. A:1unusual fact which emerged is that the animals selected.

Selection for production and reproduction traits in pigs

NARCIS (Netherlands)

Vries, de A.G.

1989-01-01

Introduction

Reproduction traits are important for piglet production, whereas production traits are important for fattening. Pig breeding organizations improve both groups of traits by selection in nucleus populations. Optimization of selection in these nucleus populations

Consideraciones y criterios para la selección de procesos para la mejora: Procesos Diana/Considerations and criteria for the selection of processes for the improvement: Diana processes

Directory of Open Access Journals (Sweden)

Alberto Medina-León

2012-09-01

Full Text Available Para implementar un procedimiento de Gestión y Mejora de Procesos, la literatura muestra una amplia revisión de procedimientos o metodologías, todas coincidentes con la necesidad de seleccionar los procesos a mejorar. La presente investigación hace énfasis en los criterios más comúnmente utilizados en la valoración para la selección del orden en que se realizará la mejora, lo que resultó en la recomendación de los criterios: impacto en los objetivos estratégicos y la repercusión en el cliente en cualquier condición existente; además del impacto a corto plazo, la variabilidad y la repetitividad, en dependencia de las necesidades de la organización. Este proceso de selección se sustenta en la utilización de herramientas como el análisis multivariado, el método Kendall para la selección de los procesos relevantes y la Matriz para la selección de los procesos Diana./There is a wealth of literature on procedures and methodologies for the implementation of a procedure of Process Management and Improvement, and all of them coincide with the need for selecting the processes that are going to be improved. This paper stresses the most commonly used criteria in the appraisal for the selection of the order in which the improvement will be made. As a result, there were recommended the following criteria: impact on the strategic objectives and the repercussion on the customer under any existing condition; as well as the short-term impact, the variability and the repetition, depending on the organization needs. This selection process is based on the utilization of instruments such as the multivariate analysis, the Kendall method for the selection of the relevant processes and the Matrix for the selection of the Diana processes.

A High-throughput Selection for Cellulase Catalysts Using Chemical Complementation

Science.gov (United States)

Peralta-Yahya, Pamela; Carter, Brian T.; Lin, Hening; Tao, Haiyan; Cornish, Virginia W.

2010-01-01

Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases however is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Due to the large number of enzyme variants selections can test compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity. PMID:19053460

Improving the selectivity of beam trawls in The Netherlands: the effect of large mesh top panels on the catch rates of sole, plaice, cod and whiting

NARCIS (Netherlands)

Marlen, van B.

2003-01-01

This paper presents the results of experiments aimed to improve the selectivity of beam trawls in the North Sea for roundfish whilst minimizing losses on target flatfish. Large-meshed top panels were designed for the tickler chain type of beam trawls used in this fishery. The design process involved

Spectrally-Selective Photonic Structures for PV Applications

Directory of Open Access Journals (Sweden)

Benedikt Bläsi

2010-01-01

Full Text Available We review several examples of how spectrally-selective photonic structures may be used to improve solar cell systems. Firstly, we introduce different spectrally-selective structures that are based on interference effects. Examples shown include Rugate filter, edge filter and 3D photonic crystals such as artificial opals. In the second part, we discuss several examples of photovoltaic (PV concepts that utilize spectral selectivity such as fluorescence collectors, upconversion systems, spectrum splitting concepts and the intermediate reflector concept. The potential of spectrally selective filters in the context of solar cells is discussed.

Reference satellite selection method for GNSS high-precision relative positioning

Directory of Open Access Journals (Sweden)

Xiao Gao

2017-03-01

Full Text Available Selecting the optimal reference satellite is an important component of high-precision relative positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision (PDOP value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.

Towards Integrated Health Technology Assessment for Improving Decision Making in Selected Countries.

Science.gov (United States)

Oortwijn, Wija; Determann, Domino; Schiffers, Krijn; Tan, Siok Swan; van der Tuin, Jeroen

2017-09-01

To assess the level of comprehensiveness of health technology assessment (HTA) practices around the globe and to formulate recommendations for enhancing legitimacy and fairness of related decision-making processes. To identify best practices, we developed an evaluation framework consisting of 13 criteria on the basis of the INTEGRATE-HTA model (integrative perspective on assessing health technologies) and the Accountability for Reasonableness framework (deliberative appraisal process). We examined different HTA systems in middle-income countries (Argentina, Brazil, and Thailand) and high-income countries (Australia, Canada, England, France, Germany, Scotland, and South Korea). For this purpose, desk research and structured interviews with relevant key stakeholders (N = 32) in the selected countries were conducted. HTA systems in Canada, England, and Scotland appear relatively well aligned with our framework, followed by Australia, Germany, and France. Argentina and South Korea are at an early stage, whereas Brazil and Thailand are at an intermediate level. Both desk research and interviews revealed that scoping is often not part of the HTA process. In contrast, providing evidence reports for assessment is well established. Indirect and unintended outcomes are increasingly considered, but there is room for improvement. Monitoring and evaluation of the HTA process is not well established across countries. Finally, adopting transparent and robust processes, including stakeholder consultation, takes time. This study presents a framework for assessing the level of comprehensiveness of the HTA process in a country. On the basis of applying the framework, we formulate recommendations on how the HTA community can move toward a more integrated decision-making process using HTA. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Slim by design: serving healthy foods first in buffet lines improves overall meal selection.

Directory of Open Access Journals (Sweden)

Brian Wansink

Full Text Available OBJECTIVE: Each day, tens of millions of restaurant goers, conference attendees, college students, military personnel, and school children serve themselves at buffets--many being all-you-can-eat buffets. Knowing how the food order at a buffet triggers what a person selects could be useful in guiding diners to make healthier selections. METHOD: The breakfast food selections of 124 health conference attendees were tallied at two separate seven-item buffet lines (which included cheesy eggs, potatoes, bacon, cinnamon rolls, low-fat granola, low-fat yogurt, and fruit. The food order between the two lines was reversed (least healthy to most healthy, and vise-versa. Participants were randomly assigned to choose their meal from one line or the other, and researchers recorded what participants selected. RESULTS: With buffet foods, the first ones seen are the ones most selected. Over 75% of diners selected the first food they saw, and the first three foods a person encountered in the buffet comprised 66% of all the foods they took. Serving the less healthy foods first led diners to take 31% more total food items (p<0.001. Indeed, diners in this line more frequently chose less healthy foods in combinations, such as cheesy eggs and bacon (r = 0.47; p<0.001 or cheesy eggs and fried potatoes (r= 0.37; p<0.001. This co-selection of healthier foods was less common. CONCLUSIONS: Three words summarize these results: First foods most. What ends up on a buffet diner's plate is dramatically determined by the presentation order of food. Rearranging food order from healthiest to least healthy can nudge unknowing or even resistant diners toward a healthier meal, helping make them slim by design. Health-conscious diners, can proactively start at the healthier end of the line, and this same basic principle of "first foods most" may be relevant in other contexts - such as when serving or passing food at family dinners.

An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications.

Science.gov (United States)

Ye, Fei; Lou, Xin Yuan; Sun, Lin Fu

2017-01-01

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find the food source. However, the proposed mutation strategy uses two distinct generative mechanisms for new food sources at the osphresis phase, allowing the algorithm procedure to search for the optimal solution in both the whole solution space and within the local solution space containing the fruit fly swarm location. In an evaluation based on a group of ten benchmark problems, the proposed algorithm's performance is compared with that of other well-known algorithms, and the results support the superiority of the proposed algorithm. Moreover, this algorithm is successfully applied in a SVM to perform both parameter setting turning for the SVM and feature selection to solve real-world classification problems. This method is called chaotic fruit fly optimization algorithm (CIFOA)-SVM and has been shown to be a more robust and effective optimization method than other well-known methods, particularly in terms of solving the medical diagnosis problem and the credit card problem.

Selection to improve spring fertility in a crossbred sheep population

OpenAIRE

Al-Shorepy, Salih Abdu

1995-01-01

Reproductive and productive performance of a composite sheep population, containing 50% Dorset, 25% Rambouillet and 25% Finnsheep breeding and under selection for ability to lamb in the fall, was evaluated. Traits considered were spring fertility, faIl litter size, live weights at birth, weaning, and at about 90 and 120 d of age, and scrotal circumference at weaning and at about 90 and 120 d of age. Fertility was defined as 1 or 0 depending upon whether a ewe lambed or failed t...

Slim by design: serving healthy foods first in buffet lines improves overall meal selection.

Science.gov (United States)

Wansink, Brian; Hanks, Andrew S

2013-01-01

Each day, tens of millions of restaurant goers, conference attendees, college students, military personnel, and school children serve themselves at buffets--many being all-you-can-eat buffets. Knowing how the food order at a buffet triggers what a person selects could be useful in guiding diners to make healthier selections. The breakfast food selections of 124 health conference attendees were tallied at two separate seven-item buffet lines (which included cheesy eggs, potatoes, bacon, cinnamon rolls, low-fat granola, low-fat yogurt, and fruit). The food order between the two lines was reversed (least healthy to most healthy, and vise-versa). Participants were randomly assigned to choose their meal from one line or the other, and researchers recorded what participants selected. With buffet foods, the first ones seen are the ones most selected. Over 75% of diners selected the first food they saw, and the first three foods a person encountered in the buffet comprised 66% of all the foods they took. Serving the less healthy foods first led diners to take 31% more total food items (pselection of healthier foods was less common. Three words summarize these results: First foods most. What ends up on a buffet diner's plate is dramatically determined by the presentation order of food. Rearranging food order from healthiest to least healthy can nudge unknowing or even resistant diners toward a healthier meal, helping make them slim by design. Health-conscious diners, can proactively start at the healthier end of the line, and this same basic principle of "first foods most" may be relevant in other contexts - such as when serving or passing food at family dinners.

Selfing for the design of genomic selection experiments in biparental plant populations.

Science.gov (United States)

McClosky, Benjamin; LaCombe, Jason; Tanksley, Steven D

2013-11-01

Self-fertilization (selfing) is commonly used for population development in plant breeding, and it is well established that selfing increases genetic variance between lines, thus increasing response to phenotypic selection. Furthermore, numerous studies have explored how selfing can be deployed to maximal benefit in the context of traditional plant breeding programs (Cornish in Heredity 65:201-211,1990a, Heredity 65:213-220,1990b; Liu et al. in Theor Appl Genet 109:370-376, 2004; Pooni and Jinks in Heredity 54:255-260, 1985). However, the impact of selfing on response to genomic selection has not been explored. In the current study we examined how selfing impacts the two key aspects of genomic selection-GEBV prediction (training) and selection response. We reach the following conclusions: (1) On average, selfing increases genomic selection gains by more than 70 %. (2) The gains in genomic selection response attributable to selfing hold over a wide range population sizes (100-500), heritabilities (0.2-0.8), and selection intensities (0.01-0.1). However, the benefits of selfing are dramatically reduced as the number of QTLs drops below 20. (3) The major cause of the improved response to genomic selection with selfing is through an increase in the occurrence of superior genotypes and not through improved GEBV predictions. While performance of the training population improves with selfing (especially with low heritability and small population sizes), the magnitude of these improvements is relatively small compared with improvements observed in the selection population. To illustrate the value of these insights, we propose a practical genomic selection scheme that substantially shortens the number of generations required to fully capture the benefits of selfing. Specifically, we provide simulation evidence that indicates the proposed scheme matches or exceeds the selection gains observed in advanced populations (i.e. F 8 and doubled haploid) across a broad range of

Improving the sun drying of apricots (Prunus armeniaca) with photo-selective dryer cabinet materials

Science.gov (United States)

Photo-selective materials have been studied for their effects on the pre-harvest quality of horticultural crops, but little work has been done on potential post-harvest effects. The aim of this work was to characterize the effects of 5 different photo-selective acrylic materials (used as the lid to...

Component Selection, Accelerated Testing, and Improved Modeling of AMTEC Systems for Space Power (abstract)

Science.gov (United States)

Williams, R. M.; Jeffries-Nakamura, B.; Ryan, M. A.; Underwood, M. L.; Suitor, J.; O'Connor, D.

1993-01-01

Alkali metal thermal to electric converter (AMTEC) designs for space power are numerous, but selection of materials for construction of long-lived AMTEC devices has been limited to electrodes, current collectors, and the solid electrolyte. AMTEC devices with lifetimes greater than 5 years require careful selection and life testing of all hot-side components. The likely selection of a remote condensed design for initial flight test and probable use with a GPHS in AMTEC powered outer planet probes requires the device to be constructed to tolerate T greater than 1150K, as well as exposure to Na(sub (g)), and Na(sub (liq)) on the high pressure side. The temperatures involved make critical high strength and chemical resistance to Na containing Na(sub 2)O. Selection among materials which can be worked should not be driven by ease of fabricability, as high temperature stability is the critical issue. These concepts drive the selection of Mo alloys for Na(sub (liq)) containment in AMTEC cells for T to 1150K operation, as they are significantly stronger than comparable NB or Ta alloys, are less soluble in Na(sub (liq)) containing dissolved Na(sub 2)O, are workable compared to W alloys (which might be used for certain components), and are ductile at the T greater than 500K of proposed AMTEC modules in space applications.

When natural selection gives gene function the cold shoulder.

Science.gov (United States)

Cutter, Asher D; Jovelin, Richard

2015-11-01

It is tempting to invoke organismal selection as perpetually optimizing the function of any given gene. However, natural selection can drive genic functional change without improvement of biochemical activity, even to the extinction of gene activity. Detrimental mutations can creep in owing to linkage with other selectively favored loci. Selection can promote functional degradation, irrespective of genetic drift, when adaptation occurs by loss of gene function. Even stabilizing selection on a trait can lead to divergence of the underlying molecular constituents. Selfish genetic elements can also proliferate independent of any functional benefits to the host genome. Here we review the logic and evidence for these diverse processes acting in genome evolution. This collection of distinct evolutionary phenomena - while operating through easily understandable mechanisms - all contribute to the seemingly counterintuitive notion that maintenance or improvement of a gene's biochemical function sometimes do not determine its evolutionary fate. © 2015 WILEY Periodicals, Inc.

Tagging of blast resistance gene(s) to DNA markers and marker-assisted selection (MAS) in rice improvement

International Nuclear Information System (INIS)

Zhuang, J.Y.; Lu, J.; Qian, H.R.; Lin, H.X.; Zheng, K.L.

1998-01-01

This paper reports progress made on the tagging of blast resistance gene(s) to DNA markers and on the initiation of marker-assisted selection (MAS) for blast resistance in rice improvement. A pair of near isogenic lines, K8OR and K79S, were developed using a Chinese landrace Hong-jiao-zhan as the resistance donor. Ten putatively positive markers were identified by screening 177 mapped DNA markers. Using the F 2 population of 143 plants and the derived F 3 lines, three Restriction Fragment Length Polymorphism (RFLP) markers (RG81, RG869 and RZ397) on chromosome 12 of rice were identified to be closely linked to the blast resistance gene Pi-12(t). The genetic distance between Pi-12(t) and the closest marker RG869 was 5.1 cM. By employing the bulk segregant analysis (BSA) procedure, six of 199 arbitrary primers were found to produce positive Randomly Amplified Polymorphic DNA (RAPD) bands. Tight linkage between Pi-12(t) and three RAPD bands, each from a different primer, was confirmed after amplification of DNA of all F 2 individuals. Two fragments were cloned and sequenced, and two sequence characterised amplified re-ion (SCAR) markers were established. In two other F 3 populations, Xian-feng I/Tetep and Xian-feng, 1/Hong-jiao-zhan, the blast resistance was found to be controlled by interactions of two or more genes. One resistance gene was located in the vicinity of RG81 in both populations. Work to identify other gene(s) is currently under way. Marker assisted selection for blast resistance was initiated. Crosses were made between elite varieties and blast resistance donors to develop populations for DNA marker-assisted selection of blast resistance. In addition, 48 varieties widely used in current rice breeding programs were provided by rice breeders. DNA marker-based polymorphism among, these varieties and resistance donors were analysed to produce a database for future MAS program. (author)

An improved wavelength selection scheme for Monte Carlo solvers applied to hypersonic plasmas

International Nuclear Information System (INIS)

Feldick, Andrew; Modest, Michael F.

2011-01-01

A new databasing scheme is developed for Monte Carlo Ray Tracing methods applied to hypersonic planetary entry. In this scheme, the complex relationships for the emission wavelength selection of atomic and molecular species in nonequilibrium flows are simplified by developing random number relationships for individual transitions, as opposed to using relationships for the spectral emission coefficient of a given species. These new techniques speed up wavelength selection by about 2 orders of magnitude, and offer flexibility for use in weighted or part-spectrum Monte Carlo solvers.

Strategies, limitations and opportunities for marker-assisted selection in livestock

International Nuclear Information System (INIS)

Dekkers, J.C.M.; Werf, H.J. van der

2007-01-01

This chapter reviews the principles, opportunities and limitations for detection of quantitative trait loci (QTL) in livestock and for their use in genetic improvement programmes. Alternate strategies for QTL detection are discussed, as are methods for inclusion of marker and QTL information in genetic evaluation. Practical issues regarding implementation of marker-assisted selection (MAS) for selection in breed crosses and for selection within breeds are described, along with likely routes towards achieving that goal. Opportunities and challenges are also discussed for the use of molecular information for genetic improvement of livestock in developing countries. (author)

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection.

Science.gov (United States)

Daetwyler, Hans D; Hayden, Matthew J; Spangenberg, German C; Hayes, Ben J

2015-08-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selection, optimal haploid value (OHV) selection, which predicts the best doubled haploid that can be produced from a segregating plant. This method focuses selection on the haplotype and optimizes the breeding program toward its end goal of generating an elite fixed line. We rigorously tested OHV selection breeding programs, using computer simulation, and show that it results in up to 0.6 standard deviations more genetic gain than genomic selection. At the same time, OHV selection preserved a substantially greater amount of genetic diversity in the population than genomic selection, which is important to achieve long-term genetic gain in breeding populations. Copyright © 2015 by the Genetics Society of America.

A practical alternative to single tree selection?

Science.gov (United States)

Gary W. Miller; H. Clay Smith

1993-01-01

When landowners want to develop and maintain an uneven-aged tree structure in eastern hardwood stands, single-tree selection often is suggested as the only advisable, long-term partial regeneration harvest method. Single-tree selection is preferred because it provides a means for improving quality and controlling stocking of the residual stand necessary for sustained...

Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

Science.gov (United States)

Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

2014-08-01

Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature

Supplier selection or collaboration? Determining factors of performance improvement when outsourcing manufacturing

OpenAIRE

Dabhilkar, Mandar; Bengtsson, Lars; Haartman, Robin von; Åhlström, Pär

2009-01-01

An empirical study was designed to determine factors of performance improvement when outsourcing manufacturing. Findings from a survey of 136 manufacturing plants in Sweden show that most of them achieve their outsourcing motives, but not without trade-offs. Factors of performance improvements such as economies of scale or operations in low-cost countries can improve one performance dimension, such as product cost, yet negatively impact volume flexibility, speed or product innovation. The res...

Comparing interventions for selective mutism: a pilot study.

Science.gov (United States)

Manassis, Katharina; Tannock, Rosemary

2008-10-01

To examine the outcome within 6 to 8 months of medical and nonmedical intervention for children with severe selective mutism (SM). Children with SM (n = 17) and their mothers, seen in a previous study, attended follow-up appointments with a clinician. Obtained by maternal report were: treatment received, current diagnosis (based on semi-structured interview), speech in various environments, and global improvement. An independent clinician also rated global functioning. The diagnosis of SM persisted in 16 children, but significant symptomatic improvement was evident in the sample. All children had received school consultations. Children who had been treated with selective serotonin reuptake inhibitors (SSRI) (n = 10) showed greater global improvement, improvement in functioning, and improvement in speech outside the family than children who were unmedicated (n = 7). No differences were evident for children receiving and not receiving additional nonmedical intervention. The findings suggest the potential benefit of SSRI treatment in severe SM, but randomized comparative treatment studies are indicated.

NCCDS configuration management process improvement

Science.gov (United States)

Shay, Kathy

1993-01-01

By concentrating on defining and improving specific Configuration Management (CM) functions, processes, procedures, personnel selection/development, and tools, internal and external customers received improved CM services. Job performance within the section increased in both satisfaction and output. Participation in achieving major improvements has led to the delivery of consistent quality CM products as well as significant decreases in every measured CM metrics category.

Improvement of Toluene Selectivity via the Application of an Ethanol Oxidizing Catalytic Cell Upstream of a YSZ-Based Sensor for Air Monitoring Applications

Science.gov (United States)

Sato, Tomoaki; Breedon, Michael; Miura, Norio

2012-01-01

The sensing characteristics of a yttria-stabilized zirconia (YSZ)-based sensor utilizing a NiO sensing-electrode (SE) towards toluene (C7H8) and interfering gases (C3H6, H2, CO, NO2 and C2H5OH) were evaluated with a view to selective C7H8 monitoring in indoor atmospheres. The fabricated YSZ-based sensor showed preferential responses toward 480 ppb C2H5OH, rather than the target 50 ppb C7H8 at an operational temperature of 450 °C under humid conditions (RH ≃ 32%). To overcome this limitation, the catalytic activity of Cr2O3, SnO2, Fe2O3 and NiO powders were evaluated for their selective ethanol oxidation ability. Among these oxides, SnO2 was found to selectively oxidize C2H5OH, thus improving C7H8 selectivity. An inline pre-catalytic cell loaded with SnO2 powder was installed upstream of the YSZ-based sensor utilizing NiO-SE, which enabled the following excellent abilities by selectively catalyzing common interfering gases; sensitive ppb level detection of C7H8 lower than the established Japanese Guideline value; low interferences from 50 ppb C3H6, 500 ppb H2, 100 ppb CO, 40 ppb NO2, as well as 480 ppb C2H5OH. These operational characteristics are all indicative that the developed sensor may be suitable for real-time C7H8 concentration monitoring in indoor environments. PMID:22666053

Evaluation of an Improved Branch-Site Likelihood Method for Detecting Positive Selection at the Molecular Level

DEFF Research Database (Denmark)

Zhang, Jianzhi; Nielsen, Rasmus; Yang, Ziheng

2005-01-01

of interest, while test 2 had acceptable false-positive rates and appeared robust against violations of model assumptions. As test 2 is a direct test of positive selection on the lineages of interest, it is referred to as the branch-site test of positive selection and is recommended for use in real data......Detecting positive Darwinian selection at the DNA sequence level has been a subject of considerable interest. However, positive selection is difficult to detect because it often operates episodically on a few amino acid sites, and the signal may be masked by negative selection. Several methods have...... been developed to test positive selection that acts on given branches (branch methods) or on a subset of sites (site methods). Recently, Yang, Z., and R. Nielsen (2002. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol. 19...

Improvement of selective removal of heavy metals in cyanobacteria by NaOH treatment.

Science.gov (United States)

Nagase, Hiroyasu; Inthorn, Duangrat; Oda, Aiko; Nishimura, Jun; Kajiwara, Yumiko; Park, Myong-Oku; Hirata, Kazumasa; Miyamoto, Kazuhisa

2005-04-01

In the freshwater cyanobacterium, Tolypothrix tenuis, treatment with 0.1 M NaOH increased its Cd-selective adsorption ability in the presence of Ca(2+) or Mg(2+). The selective adsorption was also achieved by other alkaline treatments. Energy-distributed spectroscopy analysis revealed that Cd(2+) was found mainly on the surface of non-treated cells, whereas it was distributed throughout the cell after NaOH treatment. The alkaline treatment was effective in increasing the selective adsorption ability of the cyanobacterium for other bivalent heavy metals such as Cu(2+), Pb(2+) and Zn(2+). The treatment was also applicable to Anabaena variabilis and Microcystis aeruginosa, which are typical cyanobacteria causing algal blooms. The main binding site of Cd(2+) in NaOH-treated cells is assumed to be the carboxyl groups because the binding ability of the cells was diminished by the esterification of carboxyl groups. These results suggest that alkaline treatment of cyanobacteria is a useful technique for producing biosorbents having highly specific binding abilities for heavy metals.

Response to selection under controlled environment versus natural selection in diverse regions across Canada

Science.gov (United States)

Red clover is a widely adaptable and productive forage legume species found in most temperate regions of the world. To date, specific selection techniques for identifying genotypes with superior persistence have not been successful in improving the general adaptation and the long-term persistence o...

Response to selection and genetic parameters of body and carcass weights in Japanese quail selected for 4-week body weight

DEFF Research Database (Denmark)

Khaldari, M; Pakdel, A; Yegane, H Mehrabani

2010-01-01

, respectively. There was a significant effect of sex, generation, and line (P difference for BW and carcass weights but not for carcass percentage components between sexes (P ... to improve carcass traits. Also, intense selection resulting in high rates of inbreeding might result in decreased response to selection due to inbreeding depression....

Subset Selection by Local Convex Approximation

DEFF Research Database (Denmark)

Øjelund, Henrik; Sadegh, Payman; Madsen, Henrik

1999-01-01

This paper concerns selection of the optimal subset of variables in a lenear regression setting. The posed problem is combinatiorial and the globally best subset can only be found in exponential time. We define a cost function for the subset selection problem by adding the penalty term to the usual...... of the subset selection problem so as to guarantee positive definiteness of the Hessian term, hence avoiding numerical instability. The backward Elemination type algorithm attempts to improve the results upon termination of the modified Newton-Raphson search by sing the current solution as an initial guess...

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection

OpenAIRE

Daetwyler, Hans D.; Hayden, Matthew J.; Spangenberg, German C.; Hayes, Ben J.

2015-01-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selec...

The effects of selective and divided attention on sensory precision and integration.

Science.gov (United States)

Odegaard, Brian; Wozny, David R; Shams, Ladan

2016-02-12

In our daily lives, our capacity to selectively attend to stimuli within or across sensory modalities enables enhanced perception of the surrounding world. While previous research on selective attention has studied this phenomenon extensively, two important questions still remain unanswered: (1) how selective attention to a single modality impacts sensory integration processes, and (2) the mechanism by which selective attention improves perception. We explored how selective attention impacts performance in both a spatial task and a temporal numerosity judgment task, and employed a Bayesian Causal Inference model to investigate the computational mechanism(s) impacted by selective attention. We report three findings: (1) in the spatial domain, selective attention improves precision of the visual sensory representations (which were relatively precise), but not the auditory sensory representations (which were fairly noisy); (2) in the temporal domain, selective attention improves the sensory precision in both modalities (both of which were fairly reliable to begin with); (3) in both tasks, selective attention did not exert a significant influence over the tendency to integrate sensory stimuli. Therefore, it may be postulated that a sensory modality must possess a certain inherent degree of encoding precision in order to benefit from selective attention. It also appears that in certain basic perceptual tasks, the tendency to integrate crossmodal signals does not depend significantly on selective attention. We conclude with a discussion of how these results relate to recent theoretical considerations of selective attention. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Supervisory selection and development yields payback

International Nuclear Information System (INIS)

Rubino, E.A.

1991-01-01

The selection and development of first line supervisors is a critical factor in a strategic effort to bring about organizational change, to improve performance and productivity and to enhance professionalism in the work force. Candidates for first line supervisory positions at Philadelphia Electric Company are no longer promoted purely on the basis of seniority. A Supervisory Selection Assessment Center permits candidates to demonstrate leadership potential. Successful candidates then attend an eight week Supervisory Development Academy, away from the work place. On successful completion of the Academy, the supervisor assembles his or her work team and, with training and leadership, shapes a performance based work team ready to plan, execute and assess its own work. Since this radically different program was initiated in September, 1989, results have been highly acclaimed by management. Contractor support has been sharply reduced, budgets have been met and reduced more work has been accomplished and fewer overtime hours have been needed. Workers attend training with no loss of team productivity. Each SDA graduate and his team sets goals to improve quality, increase productivity, increase efficiency, maintain ALARA, improve safety and effect cultural change while improving job satisfaction and morale

Response to family selection and genetic parameters in Japanese quail selected for four week breast weight

DEFF Research Database (Denmark)

Khaldari, Majid; Yeganeh, Hassan Mehrabani; Pakdel, Abbas

2011-01-01

An experiment was conducted to investigate the effect of short-term selection for 4 week breast weight (4wk BRW), and to estimate genetic parameters of body weight, and carcass traits. A selection (S) line and control (C) line was randomly selected from a base population. Data were collected over...... was 0.35±0.06. There were a significant difference for BW, and carcass weights but not for carcass percent components between lines (Pcarcass and leg weights were 0.46, 0.41 and 0.47, and 13.2, 16.2, 4.4 %, respectively....... The genetic correlations of BRW with BW, carcass, leg, and back weights were 0.85, 0.88 and 0.72, respectively. Selection for 4 wk BRW improved feed conversion ratio (FCR) about 0.19 units over the selection period. Inbreeding caused an insignificant decline of the mean of some traits. Results from...

Genomic Selection in Multi-environment Crop Trials.

Science.gov (United States)

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications

Science.gov (United States)

Lou, Xin Yuan; Sun, Lin Fu

2017-01-01

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find the food source. However, the proposed mutation strategy uses two distinct generative mechanisms for new food sources at the osphresis phase, allowing the algorithm procedure to search for the optimal solution in both the whole solution space and within the local solution space containing the fruit fly swarm location. In an evaluation based on a group of ten benchmark problems, the proposed algorithm’s performance is compared with that of other well-known algorithms, and the results support the superiority of the proposed algorithm. Moreover, this algorithm is successfully applied in a SVM to perform both parameter setting turning for the SVM and feature selection to solve real-world classification problems. This method is called chaotic fruit fly optimization algorithm (CIFOA)-SVM and has been shown to be a more robust and effective optimization method than other well-known methods, particularly in terms of solving the medical diagnosis problem and the credit card problem. PMID:28369096

Survival prediction algorithms miss significant opportunities for improvement if used for case selection in trauma quality improvement programs.

Science.gov (United States)

Heim, Catherine; Cole, Elaine; West, Anita; Tai, Nigel; Brohi, Karim

2016-09-01

Quality improvement (QI) programs have shown to reduce preventable mortality in trauma care. Detailed review of all trauma deaths is a time and resource consuming process and calculated probability of survival (Ps) has been proposed as audit filter. Review is limited on deaths that were 'expected to survive'. However no Ps-based algorithm has been validated and no study has examined elements of preventability associated with deaths classified as 'expected'. The objective of this study was to examine whether trauma performance review can be streamlined using existing mortality prediction tools without missing important areas for improvement. We conducted a retrospective study of all trauma deaths reviewed by our trauma QI program. Deaths were classified into non-preventable, possibly preventable, probably preventable or preventable. Opportunities for improvement (OPIs) involve failure in the process of care and were classified into clinical and system deviations from standards of care. TRISS and PS were used for calculation of probability of survival. Peer-review charts were reviewed by a single investigator. Over 8 years, 626 patients were included. One third showed elements of preventability and 4% were preventable. Preventability occurred across the entire range of the calculated Ps band. Limiting review to unexpected deaths would have missed over 50% of all preventability issues and a third of preventable deaths. 37% of patients showed opportunities for improvement (OPIs). Neither TRISS nor PS allowed for reliable identification of OPIs and limiting peer-review to patients with unexpected deaths would have missed close to 60% of all issues in care. TRISS and PS fail to identify a significant proportion of avoidable deaths and miss important opportunities for process and system improvement. Based on this, all trauma deaths should be subjected to expert panel review in order to aim at a maximal output of performance improvement programs. Copyright © 2016 Elsevier

IDENTIFICATION AND SELECTION OF SIX SIGMA PROJECTS

Directory of Open Access Journals (Sweden)

Abdalhkeim FA. Flifel

2017-04-01

Full Text Available Six Sigma is a well-structured and proven methodology for improving organizational performance. It helps achieving the goals of the organization through the use of project-driven approach. The implementation of Six sigma approach depends on proper identification and selection of projects, moreover, the selection of right Six sigma projects is one of the critical success factors of six sigma efforts. The paper provides the sources for the identification of potential projects, top down and bottom up approaches, the process of selection of projects, guidelines that assist the selection of appropriate projects, selection criteria which must be precisely chosen in accordance with the objectives, needs and capabilities of the organization as well as sophisticated techniques and tools recommended in the literature for the selection of projects.

Genomic consequences of selection and genome-wide association mapping in soybean.

Science.gov (United States)

Wen, Zixiang; Boyse, John F; Song, Qijian; Cregan, Perry B; Wang, Dechun

2015-09-03

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

Genetic search feature selection for affective modeling

DEFF Research Database (Denmark)

Martínez, Héctor P.; Yannakakis, Georgios N.

2010-01-01

Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

Bare eye detection of Hg(II) ions based on enzyme inhibition and using mercaptoethanol as a reagent to improve selectivity.

Science.gov (United States)

He, Liuying; Lu, Yuexiang; Wang, Feiyang; Gao, Xinxin; Chen, Ying; Liu, Yueying

2018-02-13

The authors describe a colorimetric method for the determination of Hg 2+ ions based on the inhibition of the activity of the enzyme urease. The pH value of solution increases when urease hydrolyzes urea, which can be visualized by adding a pH indicator such as Phenol Red (PhR). Mercaptoethanol as a typical thiol is added to the system to improve selectivity because it binds metal ions and then - unlike the Hg 2+ mercaptoethanol complex - does not inhibit urease. Hence, the color of the pH indicator PhR turns from yellow to pink as the solution becomes alkaline. The Hg 2+ mercaptoethanol complex, in contrast, strongly inhibits urease and the color of the solution remains yellow. The findings were used to design a photometric assay based on the measurement of the ratio of absorptions of PhR at 558 nm and 430 nm. It has a linear response over the 25 to 40 nM Hg 2+ concentration range and a 5 nM detection limit. This is well below the guideline values of Hg 2+ specified by the US Environmental Protection Agency and the World Health Organization for drinking water (10 nM and 30 nM, respectively). The method was employed to the determination of Hg 2+ in water samples spiked with 10 nM levels of Hg 2+ where color changes still can be observed visually. Graphical Abstract Schematic presentation of a colorimetric method for the ultrasensitive detection of Hg 2+ based on the inhibition of urease activity. Mercaptoethanol is used to improve the selectivity. Even at Hg 2+ concentrations as low as 5 nM, the color change still can be easily observed by bare eyes.

Improving the phenotypic expression of rice genotypes: Rethinking “intensification” for production systems and selection practices for rice breeding

Directory of Open Access Journals (Sweden)

Norman Uphoff

2015-06-01

Full Text Available Intensification in rice crop production is generally understood as requiring increased use of material inputs: water, inorganic fertilizers, and agrochemicals. However, this is not the only kind of intensification available. More productive crop phenotypes, with traits such as more resistance to biotic and abiotic stresses and shorter crop cycles, are possible through modifications in the management of rice plants, soil, water, and nutrients, reducing rather than increasing material inputs. Greater factor productivity can be achieved through the application of new knowledge and more skill, and (initially more labor, as seen from the System of Rice Intensification (SRI, whose practices are used in various combinations by as many as 10 million farmers on about 4 million hectares in over 50 countries. The highest yields achieved with these management methods have come from hybrids and improved rice varieties, confirming the importance of making genetic improvements. However, unimproved varieties are also responsive to these changes, which induce better growth and functioning of rice root systems and more abundance, diversity, and activity of beneficial soil organisms. Some of these organisms as symbiotic endophytes can affect and enhance the expression of rice plants' genetic potential as well as their phenotypic resilience to multiple stresses, including those of climate change. SRI experience and data suggest that decades of plant breeding have been selecting for the best crop genetic endowments under suboptimal growing conditions, with crowding of plants that impedes their photosynthesis and growth, flooding of rice paddies that causes roots to degenerate and forgoes benefits derived from aerobic soil organisms, and overuse of agrochemicals that adversely affect these organisms as well as soil and human health. This review paper reports evidence from research in India and Indonesia that changes in crop and water management can improve the

Autonomous component carrier selection

DEFF Research Database (Denmark)

Garcia, Luis Guilherme Uzeda; Pedersen, Klaus; Mogensen, Preben

2009-01-01

management and efficient system operation. Due to the expected large number of user-deployed cells, centralized network planning becomes unpractical and new scalable alternatives must be sought. In this article, we propose a fully distributed and scalable solution to the interference management problem...... in local areas, basing our study case on LTE-Advanced. We present extensive network simulation results to demonstrate that a simple and robust interference management scheme, called autonomous component carrier selection allows each cell to select the most attractive frequency configuration; improving...... the experience of all users and not just the few best ones; while overall cell capacity is not compromised....

The effects of predictor method factors on selection outcomes: A modular approach to personnel selection procedures.

Science.gov (United States)

Lievens, Filip; Sackett, Paul R

2017-01-01

Past reviews and meta-analyses typically conceptualized and examined selection procedures as holistic entities. We draw on the product design literature to propose a modular approach as a complementary perspective to conceptualizing selection procedures. A modular approach means that a product is broken down into its key underlying components. Therefore, we start by presenting a modular framework that identifies the important measurement components of selection procedures. Next, we adopt this modular lens for reviewing the available evidence regarding each of these components in terms of affecting validity, subgroup differences, and applicant perceptions, as well as for identifying new research directions. As a complement to the historical focus on holistic selection procedures, we posit that the theoretical contributions of a modular approach include improved insight into the isolated workings of the different components underlying selection procedures and greater theoretical connectivity among different selection procedures and their literatures. We also outline how organizations can put a modular approach into operation to increase the variety in selection procedures and to enhance the flexibility in designing them. Overall, we believe that a modular perspective on selection procedures will provide the impetus for programmatic and theory-driven research on the different measurement components of selection procedures. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Feature selection for portfolio optimization

DEFF Research Database (Denmark)

Bjerring, Thomas Trier; Ross, Omri; Weissensteiner, Alex

2016-01-01

Most portfolio selection rules based on the sample mean and covariance matrix perform poorly out-of-sample. Moreover, there is a growing body of evidence that such optimization rules are not able to beat simple rules of thumb, such as 1/N. Parameter uncertainty has been identified as one major....... While most of the diversification benefits are preserved, the parameter estimation problem is alleviated. We conduct out-of-sample back-tests to show that in most cases different well-established portfolio selection rules applied on the reduced asset universe are able to improve alpha relative...

New technologies and animal improvement

International Nuclear Information System (INIS)

Land, R.B.

1988-01-01

The simplification of genetic selection to the pragmatic choice of an appropriate base population, together with the adoption of such techniques as multiple ovulation and embryo transfer to accelerate the rate of response within the chosen population, would increase the contribution of genetic methods to the improvement of the performance of domestic animals. This is particularly relevant to developing countries where limited funds may constrain the opportunities for husbandry improvement, where it is important to select animals under the local conditions and where the infrastructure might limit the use of extensive programmes such as those based on progeny testing. (author). 5 refs, 1 tab

Improving digital image watermarking by means of optimal channel selection

NARCIS (Netherlands)

Huynh-The, Thien; Banos Legran, Oresti; Lee, Sungyoung; Yoon, Yongik; Le-Tien, Thuong

2016-01-01

Supporting safe and resilient authentication and integrity of digital images is of critical importance in a time of enormous creation and sharing of these contents. This paper presents an improved digital image watermarking model based on a coefficient quantization technique that intelligently

Comment ameliorer la selection et le traitement des messages verbaux? (How to Improve the Selection and Processing of Verbal Messages)

National Research Council Canada - National Science Library

Rivenez, Marie; Darwin, Chris; Guillaume, Anne

2005-01-01

L'objectif de cette recherche est d'ameliorer la selection des messages verbaux. Nous cherchons a determiner les facteurs influencant le traitement d'un message verbal lorsque l'attention est portee sur un autre message...

Improved intact soil-core carbon determination applying regression shrinkage and variable selection techniques to complete spectrum laser-induced breakdown spectroscopy (LIBS).

Science.gov (United States)

Bricklemyer, Ross S; Brown, David J; Turk, Philip J; Clegg, Sam M

2013-10-01

Laser-induced breakdown spectroscopy (LIBS) provides a potential method for rapid, in situ soil C measurement. In previous research on the application of LIBS to intact soil cores, we hypothesized that ultraviolet (UV) spectrum LIBS (200-300 nm) might not provide sufficient elemental information to reliably discriminate between soil organic C (SOC) and inorganic C (IC). In this study, using a custom complete spectrum (245-925 nm) core-scanning LIBS instrument, we analyzed 60 intact soil cores from six wheat fields. Predictive multi-response partial least squares (PLS2) models using full and reduced spectrum LIBS were compared for directly determining soil total C (TC), IC, and SOC. Two regression shrinkage and variable selection approaches, the least absolute shrinkage and selection operator (LASSO) and sparse multivariate regression with covariance estimation (MRCE), were tested for soil C predictions and the identification of wavelengths important for soil C prediction. Using complete spectrum LIBS for PLS2 modeling reduced the calibration standard error of prediction (SEP) 15 and 19% for TC and IC, respectively, compared to UV spectrum LIBS. The LASSO and MRCE approaches provided significantly improved calibration accuracy and reduced SEP 32-55% over UV spectrum PLS2 models. We conclude that (1) complete spectrum LIBS is superior to UV spectrum LIBS for predicting soil C for intact soil cores without pretreatment; (2) LASSO and MRCE approaches provide improved calibration prediction accuracy over PLS2 but require additional testing with increased soil and target analyte diversity; and (3) measurement errors associated with analyzing intact cores (e.g., sample density and surface roughness) require further study and quantification.

Classification Using Markov Blanket for Feature Selection

DEFF Research Database (Denmark)

Zeng, Yifeng; Luo, Jian

2009-01-01

Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

Eco-Material Selection for Auto Bodies

Energy Technology Data Exchange (ETDEWEB)

Mayyas, Ahmad T [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Omar, Mohammed [Masdar Institute of Science & Technology; Hayajneh, Mohammed T. [Jordan University of Science and Technology

2017-09-25

In the last decades, majority of automakers started to include lightweight materials in their vehicles to meet hard environmental regulations and to improve fuel efficiency of their vehicles. As a result, eco-material selection for vehicles emerged as a new discipline under design for environment. This chapter will summarize methods of eco-material selections for automotive applications with more emphasis into auto-bodies. A set of metrics for eco-material selection that takes into account all economic, environmental and social factors will be developed using numerical and qualitative methods. These metrics cover products' environmental impact, functionality and manufacturability, in addition to the economic and societal factors.

SIP-FS: a novel feature selection for data representation

Directory of Open Access Journals (Sweden)

Yiyou Guo

2018-02-01

Full Text Available Abstract Multiple features are widely used to characterize real-world datasets. It is desirable to select leading features with stability and interpretability from a set of distinct features for a comprehensive data description. However, most of existing feature selection methods focus on the predictability (e.g., prediction accuracy of selected results yet neglect stability. To obtain compact data representation, a novel feature selection method is proposed to improve stability, and interpretability without sacrificing predictability (SIP-FS. Instead of mutual information, generalized correlation is adopted in minimal redundancy maximal relevance to measure the relation between different feature types. Several feature types (each contains a certain number of features can then be selected and evaluated quantitatively to determine what types contribute to a specific class, thereby enhancing the so-called interpretability of features. Moreover, stability is introduced in the criterion of SIP-FS to obtain consistent results of ranking. We conduct experiments on three publicly available datasets using one-versus-all strategy to select class-specific features. The experiments illustrate that SIP-FS achieves significant performance improvements in terms of stability and interpretability with desirable prediction accuracy and indicates advantages over several state-of-the-art approaches.

AID SELECTIVITY PRACTICE AND AID EFFECTIVENESS IN SUB-SAHARAN AFRICA

OpenAIRE

Adedokun, Adeniyi Jimmy; Abiodun O. Folawewo, Abiodun O.

2017-01-01

Foreign aid strategies have undergone restructuring as donors adopt aid selectivity practice to improve aid effectiveness. This study investigates the impact of aid selectivity practice on aid effectiveness (aid-growth relationship) in Sub-Saharan Africa (SSA) and several groups of countries within SSA from 1980 to 2012. Employing system generalized methods of moments (system GMM) technique; the study produces strong evidence that there is significant improvement in aid effectiveness due to a...

BSL-3 laboratory practices in the United States: comparison of select agent and non-select agent facilities.

Science.gov (United States)

Richards, Stephanie L; Pompei, Victoria C; Anderson, Alice

2014-01-01

New construction of biosafety level 3 (BSL-3) laboratories in the United States has increased in the past decade to facilitate research on potential bioterrorism agents. The Centers for Disease Control and Prevention inspect BSL-3 facilities and review commissioning documentation, but no single agency has oversight over all BSL-3 facilities. This article explores the extent to which standard operating procedures in US BSL-3 facilities vary between laboratories with select agent or non-select agent status. Comparisons are made for the following variables: personnel training, decontamination, personal protective equipment (PPE), medical surveillance, security access, laboratory structure and maintenance, funding, and pest management. Facilities working with select agents had more complex training programs and decontamination procedures than non-select agent facilities. Personnel working in select agent laboratories were likely to use powered air purifying respirators, while non-select agent laboratories primarily used N95 respirators. More rigorous medical surveillance was carried out in select agent workers (although not required by the select agent program) and a higher level of restrictive access to laboratories was found. Most select agent and non-select agent laboratories reported adequate structural integrity in facilities; however, differences were observed in personnel perception of funding for repairs. Pest management was carried out by select agent personnel more frequently than non-select agent personnel. Our findings support the need to promote high quality biosafety training and standard operating procedures in both select agent and non-select agent laboratories to improve occupational health and safety.

CF6 jet engine performance improvement program. Task 1: Feasibility analysis

Science.gov (United States)

Fasching, W. A.

1979-01-01

Technical and economic engine improvement concepts selected for subsequent development include: (1) fan improvement; (2) short core exhaust; (3) HP turbine aerodynamic improvement; (4) HP turbine roundness control; (5) HP turbine active clearance control; and (6) cabin air recirculation. The fuel savings for the selected engine modification concepts for the CF6 fleet are estimated.

System-Wide and Group-Specific Health Service Improvements: Cross-Sectional Survey of Outpatient Improvement Preferences and Associations with Demographic Characteristics

Directory of Open Access Journals (Sweden)

Elizabeth A. Fradgley

2018-01-01

Full Text Available Efficient patient-centred quality improvement requires an understanding of the system-wide areas of dissatisfaction along with evidence to identify the programs which can be strategically targeted according to specific patient characteristics and preferences. This cross-sectional study reports the proportion of chronic disease outpatients selecting 23 patient-centred improvement initiatives. Using univariate tests and multivariable logistic regressions, this multi-site study also identifies initiatives differentially selected by outpatients according to clinical and demographic characteristics. A total of 475 outpatients participated (49% response. Commonly selected initiatives included: reducing wait-times (22.3%; convenient appointment scheduling (16.0%; and receiving up-to-date treatment information (16.0%. Within univariate tests, preferences for information and service accessibility initiatives were not significantly associated with specific subgroups. However, seven initiatives were preferred according to age, gender, diagnosis status, and chronic disease type within multivariate models. For example, neurology outpatients were more likely to select assistance to manage psychological symptoms when compared to oncology outpatients (OR: 2.89. Study findings suggest that system-wide programs to enhance information provision are strategic approaches to improve experiences across patient characteristics. Furthermore, a few initiatives can be targeted to specific groups and emphasized the importance of detailed scoping analyses and tailored implementation plans when designing patient-centred quality improvement programs.

Automatic LOD selection

OpenAIRE

Forsman, Isabelle

2017-01-01

In this paper a method to automatically generate transition distances for LOD, improving image stability and performance is presented. Three different methods were tested all measuring the change between two level of details using the spatial frequency. The methods were implemented as an optional pre-processing step in order to determine the transition distances from multiple view directions. During run-time both view direction based selection and the furthest distance for each direction was ...

Teaching Animal Habitat Selection Using Wildlife Tracking Equipment

Science.gov (United States)

Laskowski, Jessica; Gillespie, Caitlyn; Corral, Lucia; Oden, Amy; Fricke, Kent; Fontaine, Joseph J.

2016-01-01

We present a hands-on outdoor activity coupled with classroom discussion to teach students about wildlife habitat selection, the process by which animals choose where to live. By selecting locations or habitats with many benefits (e.g., food, shelter, mates) and few costs (e.g., predators), animals improve their ability to survive and reproduce.…

An improved method for fast and selective separation of carotenoids by LC-MS.

Science.gov (United States)

Abate-Pella, Daniel; Freund, Dana M; Slovin, Janet P; Hegeman, Adrian D; Cohen, Jerry D

2017-11-01

Carotenoids are a large class of compounds that are biosynthesized by condensation of isoprene units in plants, fungi, bacteria, and some animals. They are characteristically highly conjugated through double bonds, which lead to many isomers as well susceptibility to oxidation and other chemical modifications. Carotenoids are important because of their potent antioxidant activity and are the pigments responsible for color in a wide variety of foods. Human consumption is correlated to many health benefits including prevention of cancer, cardiovascular disease, and age-related disease. Extreme hydrophobicity, poor stability, and low concentration in biological samples make these compounds difficult to analyze and difficult to develop analytical methods for aimed towards identification and quantification. Examples in the literature frequently report the use of exotic stationary phases, solvents, and additives, such as ethyl acetate, dichloromethane, and methyl tert-butyl ether that are incompatible with liquid chromatography mass spectrometry (LC-MS). In order to address these issues, we implemented the use of LC-MS friendly conditions using a low-hydrophobicity cyano-propyl column (Agilent Zorbax SB-CN). We successfully differentiated between isomeric carotenoids by optimizing two gradient methods and using a mixture of 11 standards and LC-MS in positive ionization mode. Three complex biological samples from strawberry leaf, chicken feed supplement, and the photosynthetic bacterium Chloroflexus aurantiacus were analyzed and several carotenoids were resolved in these diverse backgrounds. Our results show this methodology is a significant improvement over other alternatives for analyzing carotenoids because of its ease of use, rapid analysis time, high selectivity, and, most importantly, its compatibility with typical LC-MS conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Real-world scenarios help improve selection of radiology employees.

Science.gov (United States)

Kline, C L; Groff, K; Phillips, M

1998-01-01

Choosing the right candidate through the interview process is critical, particularly in light of rapidly changing skills in various technologies. The authors have changed the interviewing process at Jeanes Hospital in Philadelphia in order to examine and evaluate multiple objectives simultaneously. To do this, they created an instrument that elicits impromptu responses to real-world radiology situations. Such responses help assess a potential candidate's training, emotional strength, technical experience and growth potential. They also determine how much additional training the potential candidate will need to be effective in the department. Using the instrument helps sharpen the assessment of candidate traits such as face-to-face communication skills and response time. The impact on hiring is positive. Quality staff, improved patient care and improved patient safety are only some of the results. Many of the questions included on the instrument come from past problem situations and help the interviewers to determine whether a candidate understands underlying issues and the seriousness of situations. The goal is to ensure that patient care and productivity are not hampered by unusual situations. When a concrete difference is detected between a candidate's response and the department's needs, it is possible to assess the cost-effectiveness of training for the discrepancy. For entry-level candidates, the question is whether the person is trainable. Consistently using this interview document forces hiring managers to identify specific abilities, traits and experience desirable in the workplace.

A Fast Algorithm of Cartographic Sounding Selection

Institute of Scientific and Technical Information of China (English)

SUI Haigang; HUA Li; ZHAO Haitao; ZHANG Yongli

2005-01-01

An effective strategy and framework that adequately integrate the automated and manual processes for fast cartographic sounding selection is presented. The important submarine topographic features are extracted for important soundings selection, and an improved "influence circle" algorithm is introduced for sounding selection. For automatic configuration of soundings distribution pattern, a special algorithm considering multi-factors is employed. A semi-automatic method for solving the ambiguous conflicts is described. On the basis of the algorithms and strategies a system named HGIS for fast cartographic sounding selection is developed and applied in Chinese Marine Safety Administration Bureau (CMSAB). The application experiments show that the system is effective and reliable. At last some conclusions and the future work are given.

Efficient selection against categorically scored hip dysplasia in dogs is possible using best linear unbiased prediction and optimum contribution selection: a simulation study

DEFF Research Database (Denmark)

Malm, S; Sørensen, Anders Christian; Fikse, W F

2013-01-01

Breeding to reduce the prevalence of categorically scored hip dysplasia (HD), based on phenotypic assessment of radiographic hip status, has had limited success. The aim of this study was to evaluate two selection strategies for improved hip status: truncation selection based on phenotypic record...

Improved selection criteria for H II regions, based on IRAS sources

Science.gov (United States)

Yan, Qing-Zeng; Xu, Ye; Walsh, A. J.; Macquart, J. P.; MacLeod, G. C.; Zhang, Bo; Hancock, P. J.; Chen, Xi; Tang, Zheng-Hong

2018-05-01

We present new criteria for selecting H II regions from the Infrared Astronomical Satellite (IRAS) Point Source Catalogue (PSC), based on an H II region catalogue derived manually from the all-sky Wide-field Infrared Survey Explorer (WISE). The criteria are used to augment the number of H II region candidates in the Milky Way. The criteria are defined by the linear decision boundary of two samples: IRAS point sources associated with known H II regions, which serve as the H II region sample, and IRAS point sources at high Galactic latitudes, which serve as the non-H II region sample. A machine learning classifier, specifically a support vector machine, is used to determine the decision boundary. We investigate all combinations of four IRAS bands and suggest that the optimal criterion is log(F_{60}/F_{12})≥ ( -0.19 × log(F_{100}/F_{25})+ 1.52), with detections at 60 and 100 {μ}m. This selects 3041 H II region candidates from the IRAS PSC. We find that IRAS H II region candidates show evidence of evolution on the two-colour diagram. Merging the WISE H II catalogue with IRAS H II region candidates, we estimate a lower limit of approximately 10 200 for the number of H II regions in the Milky Way.

Variable selection in multiple linear regression: The influence of ...

African Journals Online (AJOL)

provide an indication of whether the fit of the selected model improves or ... and calculate M(−i); quantify the influence of case i in terms of a function, f(•), of M and ..... [21] Venter JH & Snyman JLJ, 1997, Linear model selection based on risk ...

Selective cyclooxygenase-1 inhibition improves collateral vascular reactivity in biliary cirrhotic rats

Directory of Open Access Journals (Sweden)

Ching-Chih Chang

2013-10-01

Conclusion: There was no significant hemodynamic change and renal toxicity after acute administration of COX inhibitor in the FBDL-induced cirrhotic rats. Preincubation of selective COX-1, but not COX-2, inhibitor could enhance collateral vascular response to AVP, indicating that COX-1 plays a major role in the collateral vascular reactivity.

Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptor.

Science.gov (United States)

Lenselink, Eelke B; Beuming, Thijs; Sherman, Woody; van Vlijmen, Herman W T; IJzerman, Adriaan P

2014-06-23

A major challenge in structure-based virtual screening (VS) involves the treatment of explicit water molecules during docking in order to improve the enrichment of active compounds over decoys. Here we have investigated this in the context of the adenosine A2A receptor, where water molecules have previously been shown to be important for achieving high enrichment rates with docking, and where the positions of some binding site waters are known from a high-resolution crystal structure. The effect of these waters (both their presence and orientations) on VS enrichment was assessed using a carefully curated set of 299 high affinity A2A antagonists and 17,337 decoys. We show that including certain crystal waters greatly improves VS enrichment and that optimization of water hydrogen positions is needed in order to achieve the best results. We also show that waters derived from a molecular dynamics simulation - without any knowledge of crystallographic waters - can improve enrichments to a similar degree as the crystallographic waters, which makes this strategy applicable to structures without experimental knowledge of water positions. Finally, we used decision trees to select an ensemble of structures with different water molecule positions and orientations that outperforms any single structure with water molecules. The approach presented here is validated against independent test sets of A2A receptor antagonists and decoys from the literature. In general, this water optimization strategy could be applied to any target with waters-mediated protein-ligand interactions.

Grain weight improvement in wheat through irradiation

International Nuclear Information System (INIS)

Rasal, P.N.; Gadekar, D.A.; Gavhane, V.N.; Bhoite, K.D.

2006-01-01

T. aestivum wheat variety NIAW 34 was developed by Agricultural Research Station, Niphad, and was released by Central Varietal Release Committee, for cultivation under irrigated late sown conditions of Peninsular Zone. The grains of NIAW 34 are medium sized with 40g 1000 grain weight. However, in market the bold sized grains (above 40g 1000 grain weight) are preferred by the traders and consumers. To overcome this lacuna, grains of wheat variety NIAW 34 were irradiated to exploit the possibilities of improvement in test weight. The material was irradiated with 15 and 20 kr dose of gamma rays. In M2 generation, mutants for various morphological characters were observed. The plants showing vigorous growth habit and desirable morphological characters were selected. These selected plants were studied for grain characters after harvest. On the basis of improved test weight as compared to parental line, selections were effected. The material was advanced to M6 generation and found stable for character of interest. The material selected comprised of total 10 lines showing improved test weight having range of 42-46 g i.e. increase of 4-6 g over the parental line NIAW 34. The lines selected are being evaluated in yield evaluation trials during Rabi 2006-07. Amongst the doses used, frequency of desired mutants was higher in treatment, of 15 kr

Selecting information technology for physicians' practices: a cross-sectional study

Directory of Open Access Journals (Sweden)

Eden Karen

2002-04-01

Full Text Available Abstract Background Many physicians are transitioning from paper to electronic formats for billing, scheduling, medical charts, communications, etc. The primary objective of this research was to identify the relationship (if any between the software selection process and the office staff's perceptions of the software's impact on practice activities. Methods A telephone survey was conducted with office representatives of 407 physician practices in Oregon who had purchased information technology. The respondents, usually office managers, answered scripted questions about their selection process and their perceptions of the software after implementation. Results Multiple logistic regression revealed that software type, selection steps, and certain factors influencing the purchase were related to whether the respondents felt the software improved the scheduling and financial analysis practice activities. Specifically, practices that selected electronic medical record or practice management software, that made software comparisons, or that considered prior user testimony as important were more likely to have perceived improvements in the scheduling process than were other practices. Practices that considered value important, that did not consider compatibility important, that selected managed care software, that spent less than $10,000, or that provided learning time (most dramatic increase in odds ratio, 8.2 during implementation were more likely to perceive that the software had improved the financial analysis process than were other practices. Conclusion Perhaps one of the most important predictors of improvement was providing learning time during implementation, particularly when the software involves several practice activities. Despite this importance, less than half of the practices reported performing this step.

An Improved 6LoWPAN Hierarchical Routing Protocol

Directory of Open Access Journals (Sweden)

Xue Li

2015-10-01

Full Text Available IETF 6LoWPAN working group is engaged in the IPv6 protocol stack research work based on IEEE802.15.4 standard. In this working group, the routing protocol is one of the important research contents. In the 6LoWPAN, HiLow is a well-known layered routing protocol. This paper puts forward an improved hierarchical routing protocol GHiLow by improving HiLow parent node selection and path restoration strategy. GHiLow improves the parent node selection by increasing the choice of parameters. Simutaneously, it also improves path recovery by analysing different situations to recovery path. Therefore, GHiLow contributes to the ehancement of network performance and the decrease of network energy consumption.

Induction and selection of mutants from in vitro cultured plant cells

Energy Technology Data Exchange (ETDEWEB)

Lee, Yung Il; Kim, Jae Sung; Shin, In Chul; Lee, Sang Jae [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1994-07-01

Mutant cell lines are useful for biochemical, physiological and genetical material for marker in various genetic manipulation experiments and for the direct use in crop plant improvement. Mutant selection may lead to the production of plants showing resistance or tolerance to specific environmental stress, such as solinity, drought, toxed metals, herbicides, pathogens and low temperature. In this review, these included the production of the somatic variation, the selection process itself and stability of the selected characters in cell culture and regenerated plant. Which would seem to be useful for improving plants and securring genetic resources. 45 refs. (Author).

Induction and selection of mutants from in vitro cultured plant cells

International Nuclear Information System (INIS)

Lee, Yung Il; Kim, Jae Sung; Shin, In Chul; Lee, Sang Jae

1994-07-01

Mutant cell lines are useful for biochemical, physiological and genetical material for marker in various genetic manipulation experiments and for the direct use in crop plant improvement. Mutant selection may lead to the production of plants showing resistance or tolerance to specific environmental stress, such as solinity, drought, toxed metals, herbicides, pathogens and low temperature. In this review, these included the production of the somatic variation, the selection process itself and stability of the selected characters in cell culture and regenerated plant. Which would seem to be useful for improving plants and securring genetic resources. 45 refs. (Author)

Energy-Aware Sensor Networks via Sensor Selection and Power Allocation

KAUST Repository

Niyazi, Lama B.; Chaaban, Anas; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2018-01-01

sensor selection and power allocation algorithms of low complexity. Simulation results show an appreciable improvement in their performance over a system in which no selection strategy is applied, with a slight gap from derived lower bounds. The results

Interim Results on Improvement of Melia volkensii

International Nuclear Information System (INIS)

Kariuki, J.G.; Kimondo, J.M; Muchri, D.K

2007-01-01

Melia volkensii is important in some dry lands of Kenya as a high quality timber, for fodder, shade and construction. It is both drought resistant and fast growing and is termite resistant. Demand for the species has led to dysgenic selection, resulting in the selection of superior trees, progressively leading to a pool of poor parent trees remaining in most populations. A genetic improvement strategy and implementation plan was initiated in the year 2005. The main objective was genetic improvement of melia volkensii through selection, breeding and propagation. Specific objectives was to develop new plantations that are superior to their predecessors in one or several key economic traits and to maximize value of logs produced by farmers. The basic material for selection of plus trees were the natural and on farm populations across most of the species' natural range. Selection was carried out in nine transects located in various areas from Isiolo to Voi, through assessment of candidate trees and subsequent comparison with nearest 5 check trees. Site characterization and passport data collection was also carried out. Various selection criteria were used including diameter at breast height (dbh), height, form (straightness and branching habit), resistance to diseases, pests and spiral grain tendency. For establishment of hedges , stressing of root through severing part of the root to produce scions was done, followed by scion selection and grafting. Initial results showed the existence of two main forms in M. volkensii i.e crop and tree ideotypes. Crop ideotypes are shorter, have shorter clear boles with deep large and spreading crowns, mainly found in Mwingi, Nuu, Tseikuru and some parts of Kitui. Tree ideotypes are taller with long clear boles, light branching and sparce crowns mainly found in Voi, Mbeere,Mutha and Embu. Intermediate forms also exist. Because the breeding objective was timber production, the tree ideotypes were favoured in selection. In all nine

Accuracy of marker-assisted selection with auxiliary traits

Indian Academy of Sciences (India)

Unknown

Genetic information on molecular markers is increasingly being used in plant and animal improvement programmes particularly as indirect means to improve a metric trait by selection either on an individual basis or on the basis of an index incorporating such information. This paper examines the utility of an index of ...

Selection of remedial alternatives for mine sites: a multicriteria decision analysis approach.

Science.gov (United States)

Betrie, Getnet D; Sadiq, Rehan; Morin, Kevin A; Tesfamariam, Solomon

2013-04-15

The selection of remedial alternatives for mine sites is a complex task because it involves multiple criteria and often with conflicting objectives. However, an existing framework used to select remedial alternatives lacks multicriteria decision analysis (MCDA) aids and does not consider uncertainty in the selection of alternatives. The objective of this paper is to improve the existing framework by introducing deterministic and probabilistic MCDA methods. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods have been implemented in this study. The MCDA analysis involves processing inputs to the PROMETHEE methods that are identifying the alternatives, defining the criteria, defining the criteria weights using analytical hierarchical process (AHP), defining the probability distribution of criteria weights, and conducting Monte Carlo Simulation (MCS); running the PROMETHEE methods using these inputs; and conducting a sensitivity analysis. A case study was presented to demonstrate the improved framework at a mine site. The results showed that the improved framework provides a reliable way of selecting remedial alternatives as well as quantifying the impact of different criteria on selecting alternatives. Copyright © 2013 Elsevier Ltd. All rights reserved.

Direct and correlated responses to selection for total weight of lamb ...

African Journals Online (AJOL)

The estimated selection responses indicate that direct selection for TWW would be the most suitable selection criterion for improving reproductive performance in flocks with a high reproduction rate where an increase in the number of lambs would be undesirable. (South African Journal of Animal Science, 2001, 31(2): ...

Channel selection for automatic seizure detection

DEFF Research Database (Denmark)

Duun-Henriksen, Jonas; Kjaer, Troels Wesenberg; Madsen, Rasmus Elsborg

2012-01-01

Objective: To investigate the performance of epileptic seizure detection using only a few of the recorded EEG channels and the ability of software to select these channels compared with a neurophysiologist. Methods: Fifty-nine seizures and 1419 h of interictal EEG are used for training and testing...... of an automatic channel selection method. The characteristics of the seizures are extracted by the use of a wavelet analysis and classified by a support vector machine. The best channel selection method is based upon maximum variance during the seizure. Results: Using only three channels, a seizure detection...... sensitivity of 96% and a false detection rate of 0.14/h were obtained. This corresponds to the performance obtained when channels are selected through visual inspection by a clinical neurophysiologist, and constitutes a 4% improvement in sensitivity compared to seizure detection using channels recorded...

Advances in Improving Ukiriguru Composite B Maize ( Zea mays L ...

African Journals Online (AJOL)

S1 recurrent selection was carried out to improve grain yield, plant height, ear placement, resistance to lodging and other desirable agronomic traits in Ukiriguru composite B (UCB) maize variety. This paper presents the genetic gain and progress made in improving these traits through two cycles of selection. Three hundred ...

Sexual selection protects against extinction.

Science.gov (United States)

Lumley, Alyson J; Michalczyk, Łukasz; Kitson, James J N; Spurgin, Lewis G; Morrison, Catriona A; Godwin, Joanne L; Dickinson, Matthew E; Martin, Oliver Y; Emerson, Brent C; Chapman, Tracey; Gage, Matthew J G

2015-06-25

Reproduction through sex carries substantial costs, mainly because only half of sexual adults produce offspring. It has been theorized that these costs could be countered if sex allows sexual selection to clear the universal fitness constraint of mutation load. Under sexual selection, competition between (usually) males and mate choice by (usually) females create important intraspecific filters for reproductive success, so that only a subset of males gains paternity. If reproductive success under sexual selection is dependent on individual condition, which is contingent to mutation load, then sexually selected filtering through 'genic capture' could offset the costs of sex because it provides genetic benefits to populations. Here we test this theory experimentally by comparing whether populations with histories of strong versus weak sexual selection purge mutation load and resist extinction differently. After evolving replicate populations of the flour beetle Tribolium castaneum for 6 to 7 years under conditions that differed solely in the strengths of sexual selection, we revealed mutation load using inbreeding. Lineages from populations that had previously experienced strong sexual selection were resilient to extinction and maintained fitness under inbreeding, with some families continuing to survive after 20 generations of sib × sib mating. By contrast, lineages derived from populations that experienced weak or non-existent sexual selection showed rapid fitness declines under inbreeding, and all were extinct after generation 10. Multiple mutations across the genome with individually small effects can be difficult to clear, yet sum to a significant fitness load; our findings reveal that sexual selection reduces this load, improving population viability in the face of genetic stress.

Learning from Past Classification Errors: Exploring Methods for Improving the Performance of a Deep Learning-based Building Extraction Model through Quantitative Analysis of Commission Errors for Optimal Sample Selection

Science.gov (United States)

Swan, B.; Laverdiere, M.; Yang, L.

2017-12-01

In the past five years, deep Convolutional Neural Networks (CNN) have been increasingly favored for computer vision applications due to their high accuracy and ability to generalize well in very complex problems; however, details of how they function and in turn how they may be optimized are still imperfectly understood. In particular, their complex and highly nonlinear network architecture, including many hidden layers and self-learned parameters, as well as their mathematical implications, presents open questions about how to effectively select training data. Without knowledge of the exact ways the model processes and transforms its inputs, intuition alone may fail as a guide to selecting highly relevant training samples. Working in the context of improving a CNN-based building extraction model used for the LandScan USA gridded population dataset, we have approached this problem by developing a semi-supervised, highly-scalable approach to select training samples from a dataset of identified commission errors. Due to the large scope this project, tens of thousands of potential samples could be derived from identified commission errors. To efficiently trim those samples down to a manageable and effective set for creating additional training sample, we statistically summarized the spectral characteristics of areas with rates of commission errors at the image tile level and grouped these tiles using affinity propagation. Highly representative members of each commission error cluster were then used to select sites for training sample creation. The model will be incrementally re-trained with the new training data to allow for an assessment of how the addition of different types of samples affects the model performance, such as precision and recall rates. By using quantitative analysis and data clustering techniques to select highly relevant training samples, we hope to improve model performance in a manner that is resource efficient, both in terms of training process

Auditory Stream Segregation Improves Infants' Selective Attention to Target Tones Amid Distracters

Science.gov (United States)

Smith, Nicholas A.; Trainor, Laurel J.

2011-01-01

This study examined the role of auditory stream segregation in the selective attention to target tones in infancy. Using a task adapted from Bregman and Rudnicky's 1975 study and implemented in a conditioned head-turn procedure, infant and adult listeners had to discriminate the temporal order of 2,200 and 2,400 Hz target tones presented alone,…

Assessing Predictive Properties of Genome-Wide Selection in Soybeans

Directory of Open Access Journals (Sweden)

Alencar Xavier

2016-08-01

Full Text Available Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr. We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set.

Assessing Predictive Properties of Genome-Wide Selection in Soybeans.

Science.gov (United States)

Xavier, Alencar; Muir, William M; Rainey, Katy Martin

2016-08-09

Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr). We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set. Copyright © 2016 Xavie et al.

Improving the Selectivity of the ISOLDE Resonance Ionization Laser Ion Source and In-Source Laser Spectroscopy of Polonium

CERN Document Server

Fink, Daniel Andreas; Jochim, Selim

Exotic atomic nuclei far away from stability are fascinating objects to be studied in many scientic elds such as atomic-, nuclear-, and astrophysics. Since these are often short-lived isotopes, it is necessary to couple their production with immediate extraction and delivery to an experiment. This is the purpose of the on-line isotope separator facility, ISOLDE, at CERN. An essential aspect of this laboratory is the Resonance Ionization Laser Ion Source (RILIS) because it provides a fast and highly selective means of ionizing the reaction products. This technique is also a sensitive laser-spectroscopy tool for the development and improvement of electron excitation schemes for the resonant laser photoionization and the study of the nuclear structure or fundamental atomic physics. Each of these aspects of the RILIS applications are subjects of this thesis work: a new device for the suppression of unwanted surface ionized contaminants in RILIS ion beams, known as the Laser Ion Source and Trap (LIST), was impleme...

Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

Science.gov (United States)

Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

2015-01-01

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

Material Selection for Cable Gland to Improved Reliability of the High-hazard Industries

Science.gov (United States)

Vashchuk, S. P.; Slobodyan, S. M.; Deeva, V. S.; Vashchuk, D. S.

2018-01-01

The sealed cable glands (SCG) are available to ensure safest connection sheathed single wire for the hazard production facility (nuclear power plant and others) the same as pilot cable, control cables, radio-frequency cables et al. In this paper, we investigate the specifics of the material selection of SCG with the express aim of hazardous man-made facility. We discuss the safe working conditions for cable glands. The research indicates the sintering powdered metals cables provide the reliability growth due to their properties. A number of studies have demonstrated the verification of material selection. On the face of it, we make findings indicating that double glazed sealed units could enhance reliability. We had evaluated sample reliability under fire conditions, seismic load, and pressure containment failure. We used the samples mineral insulated thermocouple cable.

Textbook Development and Selection in Japan and the United States.

Science.gov (United States)

Tani, Masaru; And Others

1993-01-01

Reports on a study trip by 13 U.S. social studies educators and publishers to Japan. Compares development, marketing, and selection of textbooks in the United States and Japan. Concludes that both nations should improve textbooks and textbook selection processes. (CFR)

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition.

Science.gov (United States)

Tsai, Richard Tzong-Han; Sung, Cheng-Lung; Dai, Hong-Jie; Hung, Hsieh-Chuan; Sung, Ting-Yi; Hsu, Wen-Lian

2006-12-18

random fields, which have performed effectively in several well-known tasks, as our underlying ML model. Adding selected conjunction features, applying numerical normalization, and employing pattern-based post-processing improve the F-scores by 1.67%, 1.04%, and 0.57%, respectively. The combined increase of 3.28% yields a total score of 72.98%, which is better than the baseline system that only uses singleton features. We demonstrate the benefits of using the sequential forward search algorithm to select effective conjunction feature groups. In addition, we show that numerical normalization can effectively reduce the number of redundant and unseen features. Furthermore, the Smith-Waterman local alignment algorithm can help ML-based Bio-NER deal with difficult cases that need longer context windows.

Performance Improvements of Selective Emitters by Laser Openings on Large-Area Multicrystalline Si Solar Cells

Directory of Open Access Journals (Sweden)

Sheng-Shih Wang

2014-01-01

Full Text Available This study focuses on the laser opening technique used to form a selective emitter (SE structure on multicrystalline silicon (mc-Si. This technique can be used in the large-area (156 × 156 mm2 solar cells. SE process of this investigation was performed using 3 samples SE1–SE3. Laser fluences can vary in range of 2–5 J/cm2. The optimal conversion efficiency of 15.95% is obtained with the SE3 (2 J/cm2 fluence after laser opening with optimization of heavy and light dopant, which yields a gain of 0.48%abs compared with that of a reference cell (without fluence. In addition, this optimal SE3 cell displays improved characteristics compared with other cells with a higher average value of external quantum efficiency (EQEavg = 68.6% and a lower average value of power loss (Ploss = 2.33 mW/cm2. For the fabrication of solar cells, the laser opening process comprises fewer steps than traditional photolithography does. Furthermore, the laser opening process decreases consumption of chemical materials; therefore, the laser opening process decreases both time and cost. Therefore, SE process is simple, cheap, and suitable for commercialization. Moreover, the prominent features of the process render it effective means to promote overall performance in the photovoltaic industry.

Rational Density Functional Selection Using Game Theory.

Science.gov (United States)

McAnanama-Brereton, Suzanne; Waller, Mark P

2018-01-22

Theoretical chemistry has a paradox of choice due to the availability of a myriad of density functionals and basis sets. Traditionally, a particular density functional is chosen on the basis of the level of user expertise (i.e., subjective experiences). Herein we circumvent the user-centric selection procedure by describing a novel approach for objectively selecting a particular functional for a given application. We achieve this by employing game theory to identify optimal functional/basis set combinations. A three-player (accuracy, complexity, and similarity) game is devised, through which Nash equilibrium solutions can be obtained. This approach has the advantage that results can be systematically improved by enlarging the underlying knowledge base, and the deterministic selection procedure mathematically justifies the density functional and basis set selections.

Efficiency-improving fossil fuel technologies for electricity generation: Data selection and trends

Energy Technology Data Exchange (ETDEWEB)

Lanzi, Elisa [Fondazione Eni Enrico Mattei (Italy); Verdolini, Elena, E-mail: elena.verdolini@feem.it [Fondazione Eni Enrico Mattei (Italy); Universita Cattolica, del Sacro Cuore di Milano (Italy); Hascic, Ivan [OECD Environment Directorate (France)

2011-11-15

This paper studies patenting dynamics in efficiency improving electricity generation technologies as an important indicator of innovation activity. We build a novel database of worldwide patent applications in efficiency-improving fossil fuel technologies for electricity generation and then analyse patenting trends over time and across countries. We find that patenting has mostly been stable over time, with a recent decreasing trend. OECD countries represent the top innovators and the top markets for technology. Some non-OECD countries, and particularly China, are also very active in terms of patenting activity in this sector. The majority of patents are first filed in OECD countries and only then in BRIC and other non-OECD countries. BRIC and other non-OECD countries apply for patents that are mostly marketed domestically, but BRIC countries represent important markets for patent duplication of OECD inventions. These results are indicative of significant technology transfer in the field of efficiency-improving technologies for electricity production. - Highlights: > We study innovation in efficiency-improving electricity generation technologies. > Relevant patents are identified and used as an indicator of innovation. > We show that there is significant technology transfer in this field. > Most patents are first filed in OECD countries and then in non-OECD countries. > Patents in non-OECD countries are mostly marketed domestically.

Oxytocin administration selectively improves olfactory detection thresholds for lyral in patients with schizophrenia.

Science.gov (United States)

Woolley, J D; Lam, O; Chuang, B; Ford, J M; Mathalon, D H; Vinogradov, S

2015-03-01

Olfaction plays an important role in mammalian social behavior. Olfactory deficits are common in schizophrenia and correlate with negative symptoms and low social drive. Despite their prominence and possible clinical relevance, little is understood about the pathological mechanisms underlying olfactory deficits in schizophrenia and there are currently no effective treatments for these deficits. The prosocial neuropeptide oxytocin may affect the olfactory system when administered intranasally to humans and there is growing interest in its therapeutic potential in schizophrenia. To examine this model, we administered 40IU of oxytocin and placebo intranasally to 31 patients with a schizophrenia spectrum illness and 34 age-matched healthy control participants in a randomized, double-blind, placebo-controlled, cross-over study. On each test day, participants completed an olfactory detection threshold test for two different odors: (1) lyral, a synthetic fragrance compound for which patients with schizophrenia have specific olfactory detection threshold deficits, possibly related to decreased cyclic adenosine 3',5'-monophosphate (cAMP) signaling; and (2) anise, a compound for which olfactory detection thresholds change with menstrual cycle phase in women. On the placebo test day, patients with schizophrenia did not significantly differ from healthy controls in detection of either odor. We found that oxytocin administration significantly and selectively improved olfactory detection thresholds for lyral but not for anise in patients with schizophrenia. In contrast, oxytocin had no effect on detection of either odor in healthy controls. Our data indicate that oxytocin administration may ameliorate olfactory deficits in schizophrenia and suggest the effects of intranasal oxytocin may extend to influencing the olfactory system. Given that oxytocin has been found to increase cAMP signaling in vitro a possible mechanism for these effects is discussed. Published by Elsevier Ltd.

Improved production of membrane proteins in Escherichia coli by selective codon substitutions

DEFF Research Database (Denmark)

Nørholm, Morten H.H.; Toddo, Stephen; Virkki, Minttu T.I.

2013-01-01

Membrane proteins are extremely challenging to produce in sufficient quantities for biochemical and structural analysis and there is a growing demand for solutions to this problem. In this study we attempted to improve expression of two difficult-to-express coding sequences (araH and narK) for me......Membrane proteins are extremely challenging to produce in sufficient quantities for biochemical and structural analysis and there is a growing demand for solutions to this problem. In this study we attempted to improve expression of two difficult-to-express coding sequences (araH and nar......K) for membrane transporters. For both coding sequences, synonymous codon substitutions in the region adjacent to the AUG start led to significant improvements in expression, whereas multi-parameter sequence optimization of codons throughout the coding sequence failed. We conclude that coding sequences can be re...

Risk selection and risk adjustment: improving insurance in the individual and small group markets.

Science.gov (United States)

Baicker, Katherine; Dow, William H

2009-01-01

Insurance market reforms face the key challenge of addressing the threat that risk selection poses to the availability, of stable, high-value insurance policies that provide long-term risk protection. Many of the strategies in use today fail to address this breakdown in risk pooling, and some even exacerbate it. Flexible risk adjustment schemes are a promising avenue for promoting market stability and limiting insurer cream-skimming, potentially providing greater benefits at lower cost. Reforms intended to increase insurance coverage and the value of care delivered will be much more effective if implemented in conjunction with policies that address these fundamental selection issues.

Developing evidence-based maternity care in Iran: a quality improvement study

Directory of Open Access Journals (Sweden)

Mohammad Kazem

2008-06-01

Full Text Available Abstract Background Current Iranian perinatal statistics indicate that maternity care continues to need improvement. In response, we implemented a multi-faceted intervention to improve the quality of maternity care at an Iranian Social Security Hospital. Using a before-and-after design our aim was to improve the uptake of selected evidence based practices and more closely attend to identified women's needs and preferences. Methods The major steps of the study were to (1 identify women's needs, values and preferences via interviews, (2 select through a process of professional consensus the top evidence-based clinical recommendations requiring local implementation (3 redesign care based on the selected evidence-based recommendations and women's views, and (4 implement the new care model. We measured the impact of the new care model on maternal satisfaction and caesarean birth rates utilising maternal surveys and medical record audit before and after implementation of the new care model. Results Twenty women's needs and requirements as well as ten evidence-based clinical recommendations were selected as a basis for improving care. Following the introduction of the new model of care, women's satisfaction levels improved significantly on 16 of 20 items (p Conclusion The introduction of a quality improvement care model improved compliance with evidence-based guidelines and was associated with an improvement in women's satisfaction levels and a reduction in rates of caesarean birth.

An Ensemble Method with Integration of Feature Selection and Classifier Selection to Detect the Landslides

Science.gov (United States)

Zhongqin, G.; Chen, Y.

2017-12-01

Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.

Joint beam design and user selection over non-binary coded MIMO interference channel

Science.gov (United States)

Li, Haitao; Yuan, Haiying

2013-03-01

In this paper, we discuss the problem of sum rate improvement for coded MIMO interference system, and propose joint beam design and user selection over interference channel. Firstly, we have formulated non-binary LDPC coded MIMO interference networks model. Then, the least square beam design for MIMO interference system is derived, and the low complexity user selection is presented. Simulation results confirm that the sum rate can be improved by the joint user selection and beam design comparing with single interference aligning beamformer.

Collaborative quality improvement.

Science.gov (United States)

Luckenbaugh, Amy N; Miller, David C; Ghani, Khurshid R

2017-07-01

Quality improvement collaboratives were developed in many medical and surgical disciplines with the goal of measuring and improving the quality of care provided to patients. The aim of this review is to provide an overview of surgical quality improvement collaboratives, and in particular those aimed at improving urological care. Quality improvement collaboratives collect high-quality data using standardized methodologies, and use the data to provide feedback to physicians and practices, and then implement processes to improve patient outcomes. The largest regional collaborative in urology is the Michigan Urological Surgery Improvement Collaborative (MUSIC). Recent efforts by this group have been focused at understanding variation in care, improving patient selection for treatment, reducing treatment morbidity and measuring and optimizing technical skill. The American Urological Association has also recently launched a national quality registry (AQUA), with an initial focus on prostate cancer care. By understanding factors that result in exemplary performance, quality improvement collaboratives are able to develop best practices around areas of care with high variation that have the potential to improve outcomes and reduce costs. These developments have been made possible by the unique model offered by the collaborative structure with the goal of improving patient care at a population level.

Small prizes increased healthful school lunch selection in a Midwestern school district.

Science.gov (United States)

Siegel, Robert; Lockhart, Mary Kate; Barnes, Allison S; Hiller, Elizabeth; Kipp, Roger; Robison, Debora L; Ellsworth, Samantha C; Hudgens, Michelle E

2016-04-01

As obesity has become a pressing health issue for American children, greater attention has been focused on how schools can be used to improve how students eat. Previously, we piloted the use of small prizes in an elementary school cafeteria to improve healthful food selection. We hoped to increase healthful food selection in all the elementary schools of a small school district participating in the United States Department of Agriculture Lunch Program by offering prizes to children who selected a Power Plate (PP), which consisted of an entrée with whole grains, a fruit, a vegetable, and plain low-fat milk. In this study, the PP program was introduced to 3 schools sequentially over an academic year. During the kickoff week, green, smiley-faced emoticons were placed by preferred foods, and children were given a prize daily if they chose a PP on that day. After the first week, students were given a sticker or temporary tattoo 2 days a week if they selected a PP. Combining data from the 3 schools in the program, students increased PP selection from 4.5% at baseline to 49.4% (p small prizes as rewards dramatically improves short-term healthful food selection in elementary school children.

Leveraging Python to improve ebook metadata selection, ingest, and management

Directory of Open Access Journals (Sweden)

Kelly Thompson

2017-10-01

Full Text Available Libraries face many challenges in managing descriptive metadata for ebooks, including quality control, completeness of coverage, and ongoing management. The recent emergence of library management systems that automatically provide descriptive metadata for e-resources activated in system knowledge bases means that ebook management models are moving toward both greater efficiency and more complex implementation and maintenance choices. Automated and data-driven processes for ebook management have always been desirable, but in the current environment, they become necessary. In addition to initial selection of a record source, automation can be applied to quality control processes and ongoing maintenance in order to keep manual, eyes-on work to a minimum while providing the best possible discovery and access. In this article, we describe how we are using Python scripts to address these challenges.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

Science.gov (United States)

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

selection is a useful first step, especially when there is a need to model a large number of species or expert knowledge of the species is limited. Expert input can then be used to refine models that seem unrealistic or for species that experts believe are particularly sensitive to change. It also emphasizes the importance of using multiple models to reduce uncertainty and improve map outputs for conservation planning. Where outputs overlap or show the same direction of change there is greater certainty in the predictions. Areas of disagreement can be used for learning by asking why the models do not agree, and may highlight areas where additional on-the-ground data collection could improve the models.

Multiclass gene selection using Pareto-fronts.

Science.gov (United States)

Rajapakse, Jagath C; Mundra, Piyushkumar A

2013-01-01

Filter methods are often used for selection of genes in multiclass sample classification by using microarray data. Such techniques usually tend to bias toward a few classes that are easily distinguishable from other classes due to imbalances of strong features and sample sizes of different classes. It could therefore lead to selection of redundant genes while missing the relevant genes, leading to poor classification of tissue samples. In this manuscript, we propose to decompose multiclass ranking statistics into class-specific statistics and then use Pareto-front analysis for selection of genes. This alleviates the bias induced by class intrinsic characteristics of dominating classes. The use of Pareto-front analysis is demonstrated on two filter criteria commonly used for gene selection: F-score and KW-score. A significant improvement in classification performance and reduction in redundancy among top-ranked genes were achieved in experiments with both synthetic and real-benchmark data sets.

Code-specific learning rules improve action selection by populations of spiking neurons.

Science.gov (United States)

Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

2014-08-01

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

Six Sigma Project Selection Using Fuzzy TOPSIS Decision Making Approach

Directory of Open Access Journals (Sweden)

Rajeev Rathi

2015-05-01

Full Text Available Six Sigma is considered as a logical business strategy that attempts to identify and eliminate the defects or failures for improving the quality of product and processes. A decision on project selection in Six Sigma is always very critical; it plays a key role in successful implementation of Six Sigma. Selection of a right Six Sigma project is essentially important for an automotive company because it greatly influences the manufacturing costs. This paper discusses an approach for right Six Sigma project selection at an automotive industry using fuzzy logic based TOPSIS method. The fuzzy TOPSIS is a well recognized tool to undertake the fuzziness of the data involved in choosing the right preferences. In this context, evaluation criteria have been designed for selection of best alternative. The weights of evaluation criteria are calculated by using the MDL (modified digital logic method and final ranking is calculated through priority index obtained by using fuzzy TOPSIS method. In the selected case study, this approach has rightly helped to identify the right project for implementing Six Sigma for achieving improvement in productivity.

Online feature selection with streaming features.

Science.gov (United States)

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

Efficiency-improving fossil fuel technologies for electricity generation: Data selection and trends

International Nuclear Information System (INIS)

Lanzi, Elisa; Verdolini, Elena; Hascic, Ivan

2011-01-01

This paper studies patenting dynamics in efficiency improving electricity generation technologies as an important indicator of innovation activity. We build a novel database of worldwide patent applications in efficiency-improving fossil fuel technologies for electricity generation and then analyse patenting trends over time and across countries. We find that patenting has mostly been stable over time, with a recent decreasing trend. OECD countries represent the top innovators and the top markets for technology. Some non-OECD countries, and particularly China, are also very active in terms of patenting activity in this sector. The majority of patents are first filed in OECD countries and only then in BRIC and other non-OECD countries. BRIC and other non-OECD countries apply for patents that are mostly marketed domestically, but BRIC countries represent important markets for patent duplication of OECD inventions. These results are indicative of significant technology transfer in the field of efficiency-improving technologies for electricity production. - Highlights: → We study innovation in efficiency-improving electricity generation technologies. → Relevant patents are identified and used as an indicator of innovation. → We show that there is significant technology transfer in this field. → Most patents are first filed in OECD countries and then in non-OECD countries. → Patents in non-OECD countries are mostly marketed domestically.

Assisted selection in the improvement of soy for human consumption in the State of Tocantins

Directory of Open Access Journals (Sweden)

Aristoteles Capone

2017-07-01

Full Text Available Soy in human food has several health benefits, but finds resistance to its consumption by the western ones due to the flavor caused by the lipoxygenases enzymes. The objective of this study was to select soybean TN (Triple Null hybrids in a population of the fourth self-fertilization cycle (F4 using techniques that use molecular markers. The experiment was conducted in the experimental area of the Federal University of Tocantins Campus Gurupi - TO. Hybridizations between soybean progenitors adapted to Tocantins and TN were performed. Obtained the F1 population in the greenhouse, F2, F3 and F4 were planted in the field, in the F4 generation was selection of superior hybrid for DNA analysis in order to identify hybrids with the trait complete absence of Lox2 and 3. We selected one hundred seventy-one hybrid, made up of DNA extraction and PCR of all. It was concluded that the highest percentage of TN hybrids was obtained at the intersection BRSMG 790A (TN X GB874. Lox2 and Lox3 amplification primers confirmed as an essential tool in a soybean breeding program for human consumption. We selected 34 TN hybrids with the desired agronomic characteristics.

Real-time flavor tagging selection in ATLAS

CERN Document Server

Madaffari, D

2016-01-01

In high-energy physics experiments the online selection is crucial to reject the overwhelming uninteresting collisions. In particular the ATLAS experiment includes b-jet selections in its trigger, in order to select final states with significant heavy-flavor content. Dedicated selections are developed to timely identifying fully hadronic final states containing b-jets and maintaining affordable trigger rates. ATLAS successfully operated b-jet trigger selections during both 2011 and 2012 Large Hadron Collider data-taking campaigns. Work is on-going now to improve the performance of online tagging algorithms to be deployed in Run 2 in 2015. An overview of the Run 1 ATLAS b-jet trigger strategy along with future prospects is presented in this paper. Data-driven techniques to extract the online b-tagging performance, a key ingredient for all analysis relying on such triggers, are also discussed and preliminary results presented.

Empirical Selection of Informative Microsatellite Markers within Co-ancestry Pig Populations Is Required for Improving the Individual Assignment Efficiency

Directory of Open Access Journals (Sweden)

Y. H. Li

2014-05-01

Full Text Available The Lanyu is a miniature pig breed indigenous to Lanyu Island, Taiwan. It is distantly related to Asian and European pig breeds. It has been inbred to generate two breeds and crossed with Landrace and Duroc to produce two hybrids for laboratory use. Selecting sets of informative genetic markers to track the genetic qualities of laboratory animals and stud stock is an important function of genetic databases. For more than two decades, Lanyu derived breeds of common ancestry and crossbreeds have been used to examine the effectiveness of genetic marker selection and optimal approaches for individual assignment. In this paper, these pigs and the following breeds: Berkshire, Duroc, Landrace and Yorkshire, Meishan and Taoyuan, TLRI Black Pig No. 1, and Kaohsiung Animal Propagation Station Black pig are studied to build a genetic reference database. Nineteen microsatellite markers (loci provide information on genetic variation and differentiation among studied breeds. High differentiation index (FST and Cavalli-Sforza chord distances give genetic differentiation among breeds, including Lanyu’s inbred populations. Inbreeding values (FIS show that Lanyu and its derived inbred breeds have significant loss of heterozygosity. Individual assignment testing of 352 animals was done with different numbers of microsatellite markers in this study. The testing assigned 99% of the animals successfully into their correct reference populations based on 9 to 14 markers ranking D-scores, allelic number, expected heterozygosity (HE or FST, respectively. All miss-assigned individuals came from close lineage Lanyu breeds. To improve individual assignment among close lineage breeds, microsatellite markers selected from Lanyu populations with high polymorphic, heterozygosity, FST and D-scores were used. Only 6 to 8 markers ranking HE, FST or allelic number were required to obtain 99% assignment accuracy. This result suggests empirical examination of assignment-error rates

Improved selectivity towards NO₂ of phthalocyanine-based chemosensors by means of original indigo/nanocarbons hybrid material.

Science.gov (United States)

Brunet, J; Pauly, A; Dubois, M; Rodriguez-Mendez, M L; Ndiaye, A L; Varenne, C; Guérin, K

2014-09-01

A new and original gas sensor-system dedicated to the selective monitoring of nitrogen dioxide in air and in the presence of ozone, has been successfully achieved. Because of its high sensitivity and its partial selectivity towards oxidizing pollutants (nitrogen dioxide and ozone), copper phthalocyanine-based chemoresistors are relevant. The selectivity towards nitrogen dioxide results from the implementation of a high efficient and selective ozone filter upstream the sensing device. Thus, a powdered indigo/nanocarbons hybrid material has been developed and investigated for such an application. If nanocarbonaceous material acts as a highly permeable matrix with a high specific surface area, immobilized indigo nanoparticles are involved into an ozonolysis reaction with ozone leading to the selective removal of this analytes from air sample. The filtering yields towards each gas have been experimentally quantified and establish the complete removal of ozone while having the concentration of nitrogen dioxide unchanged. Long-term gas exposures reveal the higher durability of hybrid material as compared to nanocarbons and indigo separately. Synthesis, characterizations by many complementary techniques and tests of hybrid filters are detailed. Results on sensor-system including CuPc-based chemoresistors and indigo/carbon nanotubes hybrid material as in-line filter are illustrated. Sensing performances will be especially discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel gene: sawD related to the differentiation of streptomyces ansochromogenes.

Science.gov (United States)

Gang, L; Wei, C; Yuqing, T; Huarong, T; Chater, K F; Buttner, M J

1999-01-01

A 1.3 kb DNA fragment was cloned from a total DNA library of Streptomyces ansochromogenes using Southern hybridization. Nucleotide sequencing analysis indicated that the 1320 bp DNA fragment contained a complete open reading frame (ORF). In search of databases, the deduced product of ORF containing 213 amino acids is homologous to the serine protease of Caulobacter cresceatus, and a conserved serine-catalytic active site (GPSAG) exists. The gene was designated as sawD. The function of this gene was studied with the strategy of gene disruption, and the result showed that the sawD may be related to sporulation and especially to the spore septation in Streptomyces ansochromogenes. The preliminary result indicated that sawD mutant could produce abundant pigment in contrast with the wild type, it seems that sawD gene may be involved in pigment biosynthesis, and this gene is also dispensable for biosynthesis of nikkomycin in Streptomyces ansochromogenes.

The system of employees motivation in a selected company

OpenAIRE

BEEROVÁ, Petra

2014-01-01

The system of employees motivation in a selected company is the title of this thesis that closely analyzes the system of employees motivation in a selected company and outlines some suggestions that could improve the management and performance in this area. Moreover, the focus is placed towards the motivation of employees in the workplace.

Marker-assisted selection as a tool for genetic improvement of crops, livestock, forestry and fish in developing countries: an overview of the issues

International Nuclear Information System (INIS)

Ruane, R.; Sonnino, A.

2007-01-01

This chapter provides an overview of the techniques, current status and issues involved in using marker-assisted selection (MAS) for genetic improvement in developing countries. Molecular marker maps, the necessary framework for any MAS programme, have been constructed for the majority of agriculturally important species, although the density of the maps varies considerably among species. Despite the considerable resources that have been invested in this field and despite the enormous potential it still represents, with few exceptions, MAS has not yet delivered its expected benefits in commercial breeding programmes for crops, livestock, forest trees or farmed fish in the developed world. When evaluating the potential merits of applying MAS as a tool for genetic improvement in developing countries, some of the issues that should be considered are its economic costs and benefits, its potential benefits compared with conventional breeding or with application of other biotechnologies, and the potential impact of intellectual property rights (IPRs) on the development and application of MAS. (author)

Improved detection limits for phthalates by selective solid-phase micro-extraction

KAUST Repository

Zia, Asif I.; Afsarimanesh, Nasrin; Xie, Li; Nag, Anindya; Al-Bahadly, I. H.; Yu, P. L.; Kosel, Jü rgen

2016-01-01

Presented research reports on an improved method and enhanced limits of detection for phthalates; a hazardous additive used in the production of plastics by solid-phase micro-extraction (SPME) polymer in comparison to molecularly imprinted solid

Tracking and flavour tagging selection in the ATLAS High Level Trigger

CERN Document Server

Calvetti, Milene; The ATLAS collaboration

2017-01-01

In high-energy physics experiments, track based selection in the online environment is crucial for the efficient real time selection of the rare physics process of interest. This is of particular importance at the Large Hadron Collider (LHC), where the increasingly harsh collision environment is challenging the experiments to improve the performance of their online selection. Principal among these challenges is the increasing number of interactions per bunch crossing, known as pileup. In the ATLAS experiment the challenge has been addressed with multiple strategies. Firstly, specific trigger objects have been improved by building algorithms using detailed tracking and vertexing in specific detector regions to improve background rejection without loosing signal efficiency. Secondly, since 2015 all trigger areas have benefited from a new high performance Inner Detector (ID) software tracking system implemented in the High Level Trigger. Finally, performance will be further enhanced in future by the installation...

The rational design of a novel potent analogue of the 5’-AMP-activated protein kinase inhibitor compound C with improved selectivity and cellular activity

Science.gov (United States)

Machrouhi, Fouzia; Ouhamou, Nouara; Laderoute, Keith; Calaoagan, Joy; Bukhtiyarova, Marina; Ehrlich, Paula J.; Klon, Anthony E.

2010-01-01

We have designed and synthesized analogues of compound C, a non-specific inhibitor of 5’-AMP-activated protein kinase (AMPK), using a computational fragment-based drug design (FBDD) approach. Synthesizing only twenty-seven analogues yielded a compound that was equipotent to compound C in the inhibition of the human AMPK (hAMPK) α2 subunit in the heterotrimeric complex in vitro, exhibited significantly improved selectivity against a subset of relevant kinases, and demonstrated enhanced cellular inhibition of AMPK. PMID:20932747

Zn-Ni sulfide selective precipitation: The role of supersaturation

NARCIS (Netherlands)

Sampaio, R.M.M.; Timmers, R.A.; Kocks, N.; Andre, V.; Duarte, M.T.; Hullebusch, van E.D.; Farges, F.; Lens, P.N.L.

2010-01-01

The selective removal of Zn with Na2S from a mixture of Zn and Ni was studied in a continuously stirred tank reactor. At pH 5 and pS 18 the selectivity was improved from 61% to 99% by reducing the supersaturation at the dosing points by means of the reduction of the influent concentrations. The

Path Diversity Improved Opportunistic Routing for Underwater Sensor Networks.

Science.gov (United States)

Bai, Weigang; Wang, Haiyan; He, Ke; Zhao, Ruiqin

2018-04-23

The packets carried along a pre-defined route in underwater sensor networks are very vulnerble. Node mobility or intermittent channel availability easily leads to unreachable routing. Opportunistic routing has been proven to be a promising paradigm to design routing protocols for underwater sensor networks. It takes advantage of the broadcast nature of the wireless medium to combat packet losses and selects potential paths on the fly. Finding an appropriate forwarding candidate set is a key issue in opportunistic routing. Many existing solutions ignore the impact of candidates location distribution on packet forwarding. In this paper, a path diversity improved candidate selection strategy is applied in opportunistic routing to improve packet forwarding efficiency. It not only maximizes the packet forwarding advancements but also takes the candidate’s location distribution into account. Based on this strategy, we propose two effective routing protocols: position improved candidates selection (PICS) and position random candidates selection (PRCS). PICS employs two-hop neighbor information to make routing decisions. PRCS only uses one-hop neighbor information. Simulation results show that both PICS and PRCS can significantly improve network performance when compared with the previous solutions, in terms of packet delivery ratio, average energy consumption and end-to-end delay.

Path Diversity Improved Opportunistic Routing for Underwater Sensor Networks

Directory of Open Access Journals (Sweden)

Weigang Bai

2018-04-01

Full Text Available The packets carried along a pre-defined route in underwater sensor networks are very vulnerble. Node mobility or intermittent channel availability easily leads to unreachable routing. Opportunistic routing has been proven to be a promising paradigm to design routing protocols for underwater sensor networks. It takes advantage of the broadcast nature of the wireless medium to combat packet losses and selects potential paths on the fly. Finding an appropriate forwarding candidate set is a key issue in opportunistic routing. Many existing solutions ignore the impact of candidates location distribution on packet forwarding. In this paper, a path diversity improved candidate selection strategy is applied in opportunistic routing to improve packet forwarding efficiency. It not only maximizes the packet forwarding advancements but also takes the candidate’s location distribution into account. Based on this strategy, we propose two effective routing protocols: position improved candidates selection (PICS and position random candidates selection (PRCS. PICS employs two-hop neighbor information to make routing decisions. PRCS only uses one-hop neighbor information. Simulation results show that both PICS and PRCS can significantly improve network performance when compared with the previous solutions, in terms of packet delivery ratio, average energy consumption and end-to-end delay.

Platelet-rich preparations to improve healing. Part II: platelet activation and enrichment, leukocyte inclusion, and other selection criteria.

Science.gov (United States)

Davis, Vicki L; Abukabda, Alaeddin B; Radio, Nicholas M; Witt-Enderby, Paula A; Clafshenkel, William P; Cairone, J Vito; Rutkowski, James L

2014-08-01

Multiple platelet-rich preparations have been reported to improve wound and bone healing, such as platelet-rich plasma (PRP) and platelet rich fibrin (PRF). The different methods employed during their preparation are important, as they influence the quality of the product applied to a wound or surgical site. Besides the general protocol for preparing the platelet-rich product (discussed in Part 1 of this review), multiple choices need to be considered during its preparation. For example, activation of the platelets is required for the release and enmeshment of growth factors, but the method of activation may influence the resulting matrix, growth factor availability, and healing. Additionally, some methods enrich leukocytes as well as platelets, but others are designed to be leukocyte-poor. Leukocytes have many important roles in healing and their inclusion in PRP results in increased platelet concentrations. Platelet and growth factor enrichment reported for the different types of platelet-rich preparations are also compared. Generally, TGF-β1 and PDGF levels were higher in preparations that contain leukocytes compared to leukocyte-poor PRP. However, platelet concentration may be the most reliable criterion for comparing different preparations. These and other criteria are described to help guide dental and medical professionals, in large and small practices, in selecting the best procedures for their patients. The healing benefits of platelet-rich preparations along with the low risk and availability of simple preparation procedures should encourage more clinicians to incorporate platelet-rich products in their practice to accelerate healing, reduce adverse events, and improve patient outcomes.

Titanium-based spectrally selective surfaces for solar thermal systems

Energy Technology Data Exchange (ETDEWEB)

Wilson, A D; Holmes, J P

1983-10-01

A study of spectrally selective surfaces based on anodic oxide films on titanium is presented. These surfaces have low values of solar absorptance, 0.77, due to the nonideal optical properties of the anodic TiO2 for antireflection of titanium. A simple chemical etching process is described which gives a textured surface with dimensions similar to the wavelengths of solar radiation, leading to spectral selectivity. The performance of this dark-etched surface can be further improved by anodising, and optimum absorbers have been produced with alpha(s) 0.935 and hemispherical emittances (400 K) 0.23. The surface texturing effects a significant improvement in alpha(s) at oblique incidence.

An ant colony optimization based feature selection for web page classification.

Science.gov (United States)

Saraç, Esra; Özel, Selma Ayşe

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

Real-time flavor tagging selection in ATLAS

CERN Document Server

Madaffari, D; The ATLAS collaboration

2014-01-01

In high-energy physics experiments on hadron colliders, online selection is crucial to reject most uninteresting collisions. In particular, the ATLAS experiment includes b-jet selections in its trigger strategy, in order to select final states with heavy-flavor content and enlarge its physics potentials. Dedicated selections are developed to quickly identify fully hadronic final states containing b-jets, while rejecting light QCD jets, and maintain affordable trigger rates without raising jet energy thresholds. ATLAS successfully operated b-jet trigger selections during both 2011 and 2012 data-taking campaigns and hard work is on-going now to improve the performance of tagging algorithms for coming Run2 in 2015. An overview of the ATLAS b-jet trigger strategy and its performance on real data is presented in this contribution, along with future prospects. Data-driven techniques to extract the online b-tagging performance, a key ingredient for all analyses relying on such triggers, are also discussed and result...

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition

Directory of Open Access Journals (Sweden)

Hung Hsieh-Chuan

2006-12-01

-based Bio-NER system, we employ conditional random fields, which have performed effectively in several well-known tasks, as our underlying ML model. Adding selected conjunction features, applying numerical normalization, and employing pattern-based post-processing improve the F-scores by 1.67%, 1.04%, and 0.57%, respectively. The combined increase of 3.28% yields a total score of 72.98%, which is better than the baseline system that only uses singleton features. Conclusion We demonstrate the benefits of using the sequential forward search algorithm to select effective conjunction feature groups. In addition, we show that numerical normalization can effectively reduce the number of redundant and unseen features. Furthermore, the Smith-Waterman local alignment algorithm can help ML-based Bio-NER deal with difficult cases that need longer context windows.

Molecular genetics and livestock selection. Approaches, opportunities and risks

International Nuclear Information System (INIS)

Williams, J.L.

2005-01-01

Following domestication, livestock were selected both naturally through adaptation to their environments and by man so that they would fulfil a particular use. As selection methods have become more sophisticated, rapid progress has been made in improving those traits that are easily measured. However, selection has also resulted in decreased diversity. In some cases, improved breeds have replaced local breeds, risking the loss of important survival traits. The advent of molecular genetics provides the opportunity to identify the genes that control particular traits by a gene mapping approach. However, as with selection, the early mapping studies focused on traits that are easy to measure. Where molecular genetics can play a valuable role in livestock production is by providing the means to select effectively for traits that are difficult to measure. Identifying the genes underpinning particular traits requires a population in which these traits are segregating. Fortunately, several experimental populations have been created that have allowed a wide range of traits to be studied. Gene mapping work in these populations has shown that the role of particular genes in controlling variation in a given trait can depend on the genetic background. A second finding is that the most favourable alleles for a trait may in fact. be present in animals that perform poorly for the trait. In the long term, knowledge of -the genes controlling particular traits, and the way they interact with the genetic background, will allow introgression between breeds and the assembly of genotypes that are best suited to particular environments, producing animals with the desired characteristics. If used wisely, this approach will maintain genetic diversity while improving performance over a wide range of desired traits. (author)

Surface passivation of mixed-halide perovskite CsPb(BrxI1-x)3 nanocrystals by selective etching for improved stability.

Science.gov (United States)

Jing, Qiang; Zhang, Mian; Huang, Xiang; Ren, Xiaoming; Wang, Peng; Lu, Zhenda

2017-06-08

In recent years, there has been an unprecedented rise in the research of halide perovskites because of their important optoelectronic applications, including photovoltaic cells, light-emitting diodes, photodetectors and lasers. The most pressing question concerns the stability of these materials. Here faster degradation and PL quenching are observed at higher iodine content for mixed-halide perovskite CsPb(Br x I 1-x ) 3 nanocrystals, and a simple yet effective method is reported to significantly enhance their stability. After selective etching with acetone, surface iodine is partially etched away to form a bromine-rich surface passivation layer on mixed-halide perovskite nanocrystals. This passivation layer remarkably stabilizes the nanocrystals, making their PL intensity improved by almost three orders of magnitude. It is expected that a similar passivation layer can also be applied to various other kinds of perovskite materials with poor stability issues.

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

Science.gov (United States)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Chloroform-assisted phenol extraction improving proteome profiling of maize embryos through selective depletion of high-abundance storage proteins.

Directory of Open Access Journals (Sweden)

Erhui Xiong

Full Text Available The presence of abundant storage proteins in plant embryos greatly impedes seed proteomics analysis. Vicilin (or globulin-1 is the most abundant storage protein in maize embryo. There is a need to deplete the vicilins from maize embryo extracts for enhanced proteomics analysis. We here reported a chloroform-assisted phenol extraction (CAPE method for vicilin depletion. By CAPE, maize embryo proteins were first extracted in an aqueous buffer, denatured by chloroform and then subjected to phenol extraction. We found that CAPE can effectively deplete the vicilins from maize embryo extract, allowing the detection of low-abundance proteins that were masked by vicilins in 2-DE gel. The novelty of CAPE is that it selectively depletes abundant storage proteins from embryo extracts of both monocot (maize and dicot (soybean and pea seeds, whereas other embryo proteins were not depleted. CAPE can significantly improve proteome profiling of embryos and extends the application of chloroform and phenol extraction in plant proteomics. In addition, the rationale behind CAPE depletion of abundant storage proteins was explored.

Indicators for Monitoring Water, Sanitation, and Hygiene: A Systematic Review of Indicator Selection Methods

Directory of Open Access Journals (Sweden)

Stefanie Schwemlein

2016-03-01

Full Text Available Monitoring water, sanitation, and hygiene (WaSH is important to track progress, improve accountability, and demonstrate impacts of efforts to improve conditions and services, especially in low- and middle-income countries. Indicator selection methods enable robust monitoring of WaSH projects and conditions. However, selection methods are not always used and there are no commonly-used methods for selecting WaSH indicators. To address this gap, we conducted a systematic review of indicator selection methods used in WaSH-related fields. We present a summary of indicator selection methods for environment, international development, and water. We identified six methodological stages for selecting indicators for WaSH: define the purpose and scope; select a conceptual framework; search for candidate indicators; determine selection criteria; score indicators against criteria; and select a final suite of indicators. This summary of indicator selection methods provides a foundation for the critical assessment of existing methods. It can be used to inform future efforts to construct indicator sets in WaSH and related fields.

Construct ability Improvement for Nuclear Power Plants

Energy Technology Data Exchange (ETDEWEB)

Lee, Dae Soo; Lee, Jong Rim; Kim, Jong Ku [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

1997-12-31

The purpose of this study was to identify methods for improving the construct ability of nuclear power plants. This study reviewed several references of current construction practices of domestic and overseas nuclear plants in order to identify potential methods for improving construct ability. The identified methods for improving construct ability were then evaluated based on the applicability to domestic nuclear plant construction. The selected methods are expected to reduce the construction period, improve the quality of construction, cost, safety, and productivity. Selection of which methods should be implemented will require further evaluation of construction modifications, design changes, contract revisions. Among construction methods studied, platform construction methods can be applied through construction sequence modification without significant design changes, and Over the Top construction method of the NSSS, automatic welding of RCL pipes, CLP modularization, etc., are considered to be applied after design modification and adjustment of material lead time. (author). 49 refs., figs., tabs.

Reserve selection with land market feedbacks.

Science.gov (United States)

Butsic, Van; Lewis, David J; Radeloff, Volker C

2013-01-15

How to best site reserves is a leading question for conservation biologists. Recently, reserve selection has emphasized efficient conservation: maximizing conservation goals given the reality of limited conservation budgets, and this work indicates that land market can potentially undermine the conservation benefits of reserves by increasing property values and development probabilities near reserves. Here we propose a reserve selection methodology which optimizes conservation given both a budget constraint and land market feedbacks by using a combination of econometric models along with stochastic dynamic programming. We show that amenity based feedbacks can be accounted for in optimal reserve selection by choosing property price and land development models which exogenously estimate the effects of reserve establishment. In our empirical example, we use previously estimated models of land development and property prices to select parcels to maximize coarse woody debris along 16 lakes in Vilas County, WI, USA. Using each lake as an independent experiment, we find that including land market feedbacks in the reserve selection algorithm has only small effects on conservation efficacy. Likewise, we find that in our setting heuristic (minloss and maxgain) algorithms perform nearly as well as the optimal selection strategy. We emphasize that land market feedbacks can be included in optimal reserve selection; the extent to which this improves reserve placement will likely vary across landscapes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Early Growth of Improved Acacia mangium at Different Planting Densities

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Arif Nirsatmanto

2016-08-01

Full Text Available Integrating tree improvement into silvicultural practices is essential in forest plantation. Concerning this fact, Acacia mangium spacing trial planted using genetically improved seed was established in West Java. This study was aimed to evaluate the impact of ages and planting density on early growth of improved seed A. mangium in the spacing trial. Improved seed from 2 seed orchards (SSO-5 and SSO-20 and a control of unimproved seed from seed stand (SS-7 were tested together in spacing 3 × 3 m and 2 × 2 m. Height, diameter, stem volume, and stand volume were observed at 3 ages. The results showed that improved seed consistently outperformed to unimproved seed. Ages were highly significant for all traits, but the significant difference varied among traits and seed sources for planting density and the interactions. High density performed better growth than low density at first year, and they were varied in subsequent ages depending on traits and seed sources. Improved seed from less intensity selection orchard was less tolerance to high density than that from high intensity selection orchard, but the tolerance was reversed in low density. Improved seed A. mangium from different level of genetic selection has responded differently in behavior to the changes of planting density.

Chemical tailoring of teicoplanin with site-selective reactions.

Science.gov (United States)

Pathak, Tejas P; Miller, Scott J

2013-06-05

Semisynthesis of natural product derivatives combines the power of fermentation with orthogonal chemical reactions. Yet, chemical modification of complex structures represents an unmet challenge, as poor selectivity often undermines efficiency. The complex antibiotic teicoplanin eradicates bacterial infections. However, as resistance emerges, the demand for improved analogues grows. We have discovered chemical reactions that achieve site-selective alteration of teicoplanin. Utilizing peptide-based additives that alter reaction selectivities, certain bromo-teicoplanins are accessible. These new compounds are also scaffolds for selective cross-coupling reactions, enabling further molecular diversification. These studies enable two-step access to glycopeptide analogues not available through either biosynthesis or rapid total chemical synthesis alone. The new compounds exhibit a spectrum of activities, revealing that selective chemical alteration of teicoplanin may lead to analogues with attenuated or enhanced antibacterial properties, in particular against vancomycin- and teicoplanin-resistant strains.

Structure-Based Prediction of Subtype Selectivity of Histamine H3 Receptor Selective Antagonists in Clinical Trials

DEFF Research Database (Denmark)

Kim, Soo-Kyung; Fristrup, Peter; Abrol, Ravinder

2011-01-01

applications, including treatment of Alzheimer’s disease, attention deficit hyperactivity disorder (ADHD), epilepsy, and obesity.(1) However, many of these drug candidates cause undesired side effects through the cross-reactivity with other histamine receptor subtypes. In order to develop improved selectivity...... and antagonists. We find that E2065.46 contributes most in binding H3 selective agonists (5, 6, 7) in agreement with experimental mutation studies. We also find that conserved E5.46/S5.43 in both of hH3HR and hH4HR are involved in H3/ H4 subtype selectivity. In addition, we find that M3786.55 in hH3HR provides...... additional hydrophobic interactions different from hH4HR (the corresponding amino acid of T3236.55 in hH4HR) to provide additional subtype bias. From these studies, we developed a pharmacophore model based on our predictions for known hH3HR selective antagonists in clinical study [ABT-239 1, GSK-189,254 2...

Exercise training improves selected aspects of daytime functioning in adults with obstructive sleep apnea.

Science.gov (United States)

Kline, Christopher E; Ewing, Gary B; Burch, James B; Blair, Steven N; Durstine, J Larry; Davis, J Mark; Youngstedt, Shawn D

2012-08-15

To explore the utility of exercise training for improving daytime functioning in adults with obstructive sleep apnea (OSA). Forty-three sedentary and overweight/obese adults aged 18-55 years with at least moderate-severity untreated OSA (apnea-hypopnea index ≥ 15) were randomized to 12 weeks of moderate-intensity aerobic and resistance exercise training (n = 27) or low-intensity stretching control treatment (n = 16). As part of a trial investigating the efficacy of exercise training on OSA severity, daytime functioning was assessed before and following the intervention. Sleepiness, functional impairment due to sleepiness, depressive symptoms, mood, and quality of life (QOL) were evaluated with validated questionnaires, and cognitive function was assessed with a neurobehavioral performance battery. OSA severity was measured with one night of laboratory polysomnography before and following the intervention. Compared with stretching control, exercise training resulted in significant improvements in depressive symptoms, fatigue and vigor, and aspects of QOL (p improved following exercise versus control to a similar degree in terms of effect sizes (d > 0.5), though these changes were not statistically significant. No neurobehavioral performance improvements were found. Reduced fatigue following exercise training was mediated by a reduction in OSA severity, but changes in OSA severity did not significantly mediate improvement in any other measure of daytime functioning. These data provide preliminary evidence that exercise training may be helpful for improving aspects of daytime functioning of adults with OSA. Larger trials are needed to further verify the observed improvements.

Dealing with selection bias in educational transition models

DEFF Research Database (Denmark)

Holm, Anders; Jæger, Mads Meier

2011-01-01

This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational tr...... account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models.......This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational...... transitions to be correlated across transitions. We use simulated and real data to illustrate how the BPSM improves on the traditional Mare model in terms of correcting for selection bias and providing credible estimates of the effect of family background on educational success. We conclude that models which...

A Triply Selective MIMO Channel Simulator Using GPUs

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R. Carrasco-Alvarez

2018-01-01

Full Text Available A methodology for implementing a triply selective multiple-input multiple-output (MIMO simulator based on graphics processing units (GPUs is presented. The resulting simulator is based on the implementation of multiple double-selective single-input single-output (SISO channel generators, where the multiple inputs and the multiple received signals have been transformed in order to supply the corresponding space correlation of the channel under consideration. A direct consequence of this approach is the flexibility provided, which allows different propagation statistics to each SISO channel to be specified and thus more complex environments to be replicated. It is shown that under some specific constraints, the statistics of the triply selective MIMO simulator are the same as those reported in the state of art. Simulation results show the computational time improvement achieved, up to 650-fold for an 8 × 8 MIMO channel simulator when compared with sequential implementations. In addition to the computational improvement, the proposed simulator offers flexibility for testing a variety of scenarios in vehicle-to-vehicle (V2V and vehicle-to-infrastructure (V2I systems.

Software Process Improvement Using Force Field Analysis ...

African Journals Online (AJOL)

An improvement plan is then drawn and implemented. This paper studied the state of Nigerian software development organizations based on selected attributes. Force field analysis is used to partition the factors obtained into driving and restraining forces. An attempt was made to improve the software development process ...

The recruitment, selection, hiring and adaptation of employees

OpenAIRE

Rajdlová, Jana

2010-01-01

This master's thesis examines and assesses the process of recruitment, selection, hiring and adaptation of employees in the holding ROSS. The thesis is divided into two main parts - the theoretical part and the practical part. The theoretical part describes in general perspective the process of recruitment, selection, hiring and adaptation of employees. The practical part analyses these processes in the holding ROSS and based on the identified findings suggests appropriate changes to improve ...

Sexual selection predicts species richness across the animal kingdom.

Science.gov (United States)

Janicke, Tim; Ritchie, Michael G; Morrow, Edward H; Marie-Orleach, Lucas

2018-05-16

Our improving knowledge of the animal tree of life consistently demonstrates that some taxa diversify more rapidly than others, but what contributes to this variation remains poorly understood. An influential hypothesis proposes that selection arising from competition for mating partners plays a key role in promoting speciation. However, empirical evidence showing a link between proxies of this sexual selection and species richness is equivocal. Here, we collected standardized metrics of sexual selection for a broad range of animal taxa, and found that taxonomic families characterized by stronger sexual selection on males show relatively higher species richness. Thus, our data support the hypothesis that sexual selection elevates species richness. This could occur either by promoting speciation and/or by protecting species against extinction. © 2018 The Author(s).

Optimizing Stem Length To Improve Ligand Selectivity in a Structure-Switching Cocaine-Binding Aptamer.

Science.gov (United States)

Neves, Miguel A D; Shoara, Aron A; Reinstein, Oren; Abbasi Borhani, Okty; Martin, Taylor R; Johnson, Philip E

2017-10-27

Understanding how aptamer structure and function are related is crucial in the design and development of aptamer-based biosensors. We have analyzed a series of cocaine-binding aptamers with different lengths of their stem 1 in order to understand the role that this stem plays in the ligand-induced structure-switching binding mechanism utilized in many of the sensor applications of this aptamer. In the cocaine-binding aptamer, the length of stem 1 controls whether the structure-switching binding mechanism for this aptamer occurs or not. We varied the length of stem 1 from being one to seven base pairs long and found that the structural transition from unfolded to folded in the unbound aptamer is when the aptamer elongates from 3 to 4 base pairs in stem 1. We then used this knowledge to achieve new binding selectivity of this aptamer for quinine over cocaine by using an aptamer with a stem 1 two base pairs long. This selectivity is achieved by means of the greater affinity quinine has for the aptamer compared with cocaine. Quinine provides enough free energy to both fold and bind the 2-base pair-long aptamer while cocaine does not. This tuning of binding selectivity of an aptamer by reducing its stability is likely a general mechanism that could be used to tune aptamer specificity for tighter binding ligands.

Genomic selection for the improvement of antibody response to Newcastle disease and avian influenza virus in chickens.

Directory of Open Access Journals (Sweden)

Tianfei Liu

Full Text Available Newcastle disease (ND and avian influenza (AI are the most feared diseases in the poultry industry worldwide. They can cause flock mortality up to 100%, resulting in a catastrophic economic loss. This is the first study to investigate the feasibility of genomic selection for antibody response to Newcastle disease virus (Ab-NDV and antibody response to Avian Influenza virus (Ab-AIV in chickens. The data were collected from a crossbred population. Breeding values for Ab-NDV and Ab-AIV were estimated using a pedigree-based best linear unbiased prediction model (BLUP and a genomic best linear unbiased prediction model (GBLUP. Single-trait and multiple-trait analyses were implemented. According to the analysis using the pedigree-based model, the heritability for Ab-NDV estimated from the single-trait and multiple-trait models was 0.478 and 0.487, respectively. The heritability for Ab-AIV estimated from the two models was 0.301 and 0.291, respectively. The estimated genetic correlation between the two traits was 0.438. A four-fold cross-validation was used to assess the accuracy of the estimated breeding values (EBV in the two validation scenarios. In the family sample scenario each half-sib family is randomly allocated to one of four subsets and in the random sample scenario the individuals are randomly divided into four subsets. In the family sample scenario, compared with the pedigree-based model, the accuracy of the genomic prediction increased from 0.086 to 0.237 for Ab-NDV and from 0.080 to 0.347 for Ab-AIV. In the random sample scenario, the accuracy was improved from 0.389 to 0.427 for Ab-NDV and from 0.281 to 0.367 for Ab-AIV. The multiple-trait GBLUP model led to a slightly higher accuracy of genomic prediction for both traits. These results indicate that genomic selection for antibody response to ND and AI in chickens is promising.

A “genetics first” approach to selection

Science.gov (United States)

A different approach for using genomic information in genetic improvement is proposed. Past research in population genetics and animal breeding combined with information on sequence variants suggest the possibility that selection might be able to capture a portion of inbreeding and heterosis effect...

One improved LSB steganography algorithm

Science.gov (United States)

Song, Bing; Zhang, Zhi-hong

2013-03-01

It is easy to be detected by X2 and RS steganalysis with high accuracy that using LSB algorithm to hide information in digital image. We started by selecting information embedded location and modifying the information embedded method, combined with sub-affine transformation and matrix coding method, improved the LSB algorithm and a new LSB algorithm was proposed. Experimental results show that the improved one can resist the X2 and RS steganalysis effectively.

Seed improvement by selection and invigoration Seleção e envigoramento como técnicas para o aprimoramento do desempenho de sementes

Directory of Open Access Journals (Sweden)

A.A. Powell

1998-01-01

Full Text Available The basis of differences in seed quality are described for two groups of crops, grain legumes and vegetables and approaches to the improvement of quality are proposed. In grain legumes the major factors affecting seed quality are imbibition damage, seed ageing and their interaction. It is proposed that use of seed vigour tests, specifically the electrical conductivity test, to identify the incidence of imbibition damage and ageing allows the selection of seed lots for sale and for use under different field conditions. Alternatively in grain legume species in which there is a genotypic influence on predisposition to imbibition damage the approach to seed improvement may lie through selection in breeding programmes. Thus identification of testa characteristics that favour slow imbibition would enable selection for these characteristics. Seed ageing is also the major cause of reduced seed quality in vegetable species, leading to slow and asynchronous germination. An approach to their seed improvement has been the development of seed invigoration treatments based on seed hydration. The principle of these treatments is described and several treatments outlined, with emphasis being given to aerated hydration, a treatment completed within 36h. The physiological basis of improvement by invigoration is discussed.Neste trabalho, são descritas diferenças básicas na qualidade de sementes de leguminosas e hortaliças, e propostos procedimentos para a melhoria de seu desempenho. Os principais fatores que afetam a qualidade de sementes de leguminosas são as injurias durante a embebição, o envelhecimento e a interação entre esses fatores. Considera-se que a utilização de testes de vigor, principalmente o de condutividade elétrica, para a identificação de injurias durante a embebição e o grau de envelhecimento, permite a seleção de lotes para a comercialização e uso sob diferentes condições de campo. A alternativa, em leguminosas, onde h

Whipple procedure: patient selection and special considerations

Directory of Open Access Journals (Sweden)

Tan-Tam C

2016-07-01

Full Text Available Clara Tan-Tam,1 Maja Segedi,2 Stephen W Chung2 1Department of Surgery, Bassett Healthcare, Columbia University, Cooperstown, New York, NY, USA; 2Department of Hepatobiliary and Pancreatic Surgery and Liver Transplant, Vancouver General Hospital, University of British Columbia, Vancouver, BC, Canada Abstract: At the inception of pancreatic surgery by Dr Whipple in 1930s, the mortality and morbidity risk was more than 20%. With further understanding of disease processes and improvements in pancreas resection techniques, the mortality risk has decreased to less than 5%. Age and chronic illnesses are no longer a contraindication to surgical treatment. Life expectancy and quality of life at a later age have improved, making older patients more likely to receive pancreatic surgery , thereby also putting emphasis on operative patient selection to minimize complications. This review summarizes the benign and malignant illnesses that are treated with pancreas operations, and innovations and improvements in pancreatic surgery and perioperative care, and describes the careful selection process for patients who would benefit from an operation. These indications are not reserved only to Whipple operation, but to pancreatectomies as well.Keywords: pancreaticoduodenectomy, mortality, morbidity, cancer, trauma, pancreatitis

A CONCEPTUAL MODEL FOR IMPROVED PROJECT SELECTION AND PRIORITISATION

Directory of Open Access Journals (Sweden)

P. J. Viljoen

2012-01-01

Full Text Available

ENGLISH ABSTRACT: Project portfolio management processes are often designed and operated as a series of stages (or project phases and gates. However, the flow of such a process is often slow, characterised by queues waiting for a gate decision and by repeated work from previous stages waiting for additional information or for re-processing. In this paper the authors propose a conceptual model that applies supply chain and constraint management principles to the project portfolio management process. An advantage of the proposed model is that it provides the ability to select and prioritise projects without undue changes to project schedules. This should result in faster flow through the system.

AFRIKAANSE OPSOMMING: Prosesse om portefeuljes van projekte te bestuur word normaalweg ontwerp en bedryf as ’n reeks fases en hekke. Die vloei deur so ’n proses is dikwels stadig en word gekenmerk deur toue wat wag vir besluite by die hekke en ook deur herwerk van vorige fases wat wag vir verdere inligting of vir herprosessering. In hierdie artikel word ‘n konseptuele model voorgestel. Die model berus op die beginsels van voorsieningskettings sowel as van beperkingsbestuur, en bied die voordeel dat projekte geselekteer en geprioritiseer kan word sonder onnodige veranderinge aan projekskedules. Dit behoort te lei tot versnelde vloei deur die stelsel.

Promoting Continuous Quality Improvement in the Alabama Child Health Improvement Alliance Through Q-Sort Methodology and Learning Collaboratives.

Science.gov (United States)

Fifolt, Matthew; Preskitt, Julie; Rucks, Andrew; Corvey, Kathryn; Benton, Elizabeth Cason

Q-sort methodology is an underutilized tool for differentiating among multiple priority measures. The authors describe steps to identify, delimit, and sort potential health measures and use selected priority measures to establish an overall agenda for continuous quality improvement (CQI) activities within learning collaboratives. Through an iterative process, the authors vetted a list of potential child and adolescent health measures. Multiple stakeholders, including payers, direct care providers, and organizational representatives sorted and prioritized measures, using Q-methodology. Q-methodology provided the Alabama Child Health Improvement Alliance (ACHIA) an objective and rigorous approach to system improvement. Selected priority measures were used to design learning collaboratives. An open dialogue among stakeholders about state health priorities spurred greater organizational buy-in for ACHIA and increased its credibility as a statewide provider of learning collaboratives. The integrated processes of Q-sort methodology, learning collaboratives, and CQI offer a practical yet innovative way to identify and prioritize state measures for child and adolescent health and establish a learning agenda for targeted quality improvement activities.

Real-time flavor tagging selection in ATLAS

CERN Document Server

Sahinsoy, M; The ATLAS collaboration

2014-01-01

In high-energy physics experiments, online selection is crucial to reject most uninteresting collisions; in particular, b-jet selections, part of the ATLAS trigger strategy, are meant to select final states with heavy-flavor content. This is the only option to select fully hadronic final states containing b-jets, and is important to reject QCD light jets and maintain affordable trigger rates without raising jet energy thresholds. ATLAS operated b-jet triggers in both 2011 and 2012 data-taking campaigns and is now working to improve the performance of tagging algorithms for Run2. An overview of the ATLAS b-jet trigger strategy and its performance on real data is presented in this contribution, along with future prospects. Data-driven techniques to extract the online b-tagging performance, a key ingredient for all analyses relying on such triggers, are also discussed and results presented.

Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data

International Nuclear Information System (INIS)

Balabin, Roman M.; Smirnov, Sergey V.

2011-01-01

techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice.

Improvements of the Vis-NIRS Model in the Prediction of Soil Organic Matter Content Using Spectral Pretreatments, Sample Selection, and Wavelength Optimization

Science.gov (United States)

Lin, Z. D.; Wang, Y. B.; Wang, R. J.; Wang, L. S.; Lu, C. P.; Zhang, Z. Y.; Song, L. T.; Liu, Y.

2017-07-01

A total of 130 topsoil samples collected from Guoyang County, Anhui Province, China, were used to establish a Vis-NIR model for the prediction of organic matter content (OMC) in lime concretion black soils. Different spectral pretreatments were applied for minimizing the irrelevant and useless information of the spectra and increasing the spectra correlation with the measured values. Subsequently, the Kennard-Stone (KS) method and sample set partitioning based on joint x-y distances (SPXY) were used to select the training set. Successive projection algorithm (SPA) and genetic algorithm (GA) were then applied for wavelength optimization. Finally, the principal component regression (PCR) model was constructed, in which the optimal number of principal components was determined using the leave-one-out cross validation technique. The results show that the combination of the Savitzky-Golay (SG) filter for smoothing and multiplicative scatter correction (MSC) can eliminate the effect of noise and baseline drift; the SPXY method is preferable to KS in the sample selection; both the SPA and the GA can significantly reduce the number of wavelength variables and favorably increase the accuracy, especially GA, which greatly improved the prediction accuracy of soil OMC with Rcc, RMSEP, and RPD up to 0.9316, 0.2142, and 2.3195, respectively.

Selection of catalysts and reactors for hydroprocessing

Energy Technology Data Exchange (ETDEWEB)

Furimsky, E. [Imaf Group, Ottawa, ON (Canada)

1998-07-13

The performance of hydroprocessing units can be influenced by the selection of the catalysts and the type of reactor to suit a particular feed. The catalysts and reactors selected for light feeds differ markedly from those selected for heavy feeds. Fixed-bed reactors have been traditionally used for light feeds. High asphaltene and high metal content feeds are successfully processed using moving-bed and/or ebullated bed reactors. Multi-reactor systems consisting of moving-bed and/or ebullated bed reactors in series with fixed-bed reactors can be used to process difficult feeds. For heavy feeds, the physical properties (e.g. porosity), shape and size of the catalyst particles become crucial parameters. Pretreatment of catalysts by presulfiding improves the performance of the units.

Optimizing drilling performance using a selected drilling fluid

Science.gov (United States)

Judzis, Arnis [Salt Lake City, UT; Black, Alan D [Coral Springs, FL; Green, Sidney J [Salt Lake City, UT; Robertson, Homer A [West Jordan, UT; Bland, Ronald G [Houston, TX; Curry, David Alexander [The Woodlands, TX; Ledgerwood, III, Leroy W.

2011-04-19

To improve drilling performance, a drilling fluid is selected based on one or more criteria and to have at least one target characteristic. Drilling equipment is used to drill a wellbore, and the selected drilling fluid is provided into the wellbore during drilling with the drilling equipment. The at least one target characteristic of the drilling fluid includes an ability of the drilling fluid to penetrate into formation cuttings during drilling to weaken the formation cuttings.

Enhancement of Selection, Bubble and Insertion Sorting Algorithm

OpenAIRE

Muhammad Farooq Umar; Ehsan Ullah Munir; Shafqat Ali Shad; Muhammad Wasif Nisar

2014-01-01

In everyday life there is a large amount of data to arrange because sorting removes any ambiguities and make the data analysis and data processing very easy, efficient and provides with cost less effort. In this study a set of improved sorting algorithms are proposed which gives better performance and design idea. In this study five new sorting algorithms (Bi-directional Selection Sort, Bi-directional bubble sort, MIDBiDirectional Selection Sort, MIDBidirectional bubble sort and linear insert...

A Holistic Quality Evaluation, Selection and Improvement Approach driven by Multilevel Goals and Strategies

Directory of Open Access Journals (Sweden)

Belen Rivera

2016-12-01

Full Text Available Organizations should establish business goals and check for their achievement in a systematic and disciplined way. In order to know if a business goal is achieved, it should be necessary to consider information need goals that also can require satisfying measurement and evaluation goals at operational level. Furthermore, if measurement and evaluation goals are not aligned with top-level business goals such as tactical or strategic level goals, the organization could waste its effort and resources. Usually, the different goals established in an organization are operationalized through projects. For a given project, strategies should be used in order to help in the goal achievement. A strategy defines a set of activities and methods to be followed for a specific goal purpose. Ultimately, to engineering all these issues in a systematic way, organizations should adopt a holistic evaluation approach supported by a set of integrated strategies. By means of a systematic literature review as research method, we have observed that very few approaches support integrated strategies and multilevel goals. To bridge this gap, we have developed a holistic quality multilevel and multipurpose evaluation approach that ties together multilevel goals, projects and integrated strategies. As contributions, this paper discusses an enhanced conceptual base (specified by ontologies for linking business and information need goal concepts with project, strategy and nonfunctional requirements concepts. Then, it defines the step by step of our holistic quality evaluation approach, by listing the necessary activities to establish goals and projects at different organizational levels. Lastly, it specifies and illustrates evaluation scenarios for business/information need goal purposes such as understanding, improving, monitoring and controlling, comparing and selecting entities, which are supported by strategies and strategy patterns.

Recurrent selection as breeding strategy for heat tolerance in wheat

Directory of Open Access Journals (Sweden)

Juarez Campolina Machado

2010-01-01

Full Text Available The development of heat-tolerant varieties is an important goal of wheat breeding programs, requiringefficient selection methods. In the present study the use of recurrent selection was evaluated as a strategy to improve heatstress tolerance in wheat. Two cycles of recurrent selection were performed in experiments conducted in research areas of theUniversidade Federal de Viçosa, located in Coimbra-MG and Viçosa-MG, in 2004 and 2007, in two growing seasons (summerand winter. The genetic gain and the existence of variability show the possibility of successful recurrent selection for heattolerancein wheat.

Training-induced improvement of response selection and error detection in aging assessed by task switching: effects of cognitive, physical, and relaxation training.

Science.gov (United States)

Gajewski, Patrick D; Falkenstein, Michael

2012-01-01

Cognitive control functions decline with increasing age. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in changes of cognitive functions, as measured in electrophysiological brain activity (event-related potentials). One hundred forty-one healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength training), cognitive training (paper-pencil and computer-aided), relaxation and wellness (social control group), and a control group that did not receive any intervention. Training sessions took place twice a week for 90 min for a period of 4 months. The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task sets in working memory, and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials which showed higher amplitudes in a number of potentials associated with response selection (N2), allocation of cognitive resources (P3b), and error detection (Ne). Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods.

Sex selection: the systematic elimination of girls.

Science.gov (United States)

Oomman, Nandini; Ganatra, Bela R

2002-05-01

In strongly patriarchal societies, where the cultural and economic value of sons is at a premium, son preference manifests itself in many ways, ranging from differential allocation of household resources, medical care and neglect of girl children to female infanticide. With the increasing availability of ultrasound in the mid-1980s sex determination followed by sex-selective abortion began to become widespread as well. The following paper introduces this Roundtable and discusses the following questions: Is sex selection a part of women's right to free choice and control over their reproduction? What is the role of the medical profession? Are all manifestations of sex selection equally unethical? Are there solutions? Do the solutions themselves pose new ethical dilemmas? Following this paper, four respondents put different points of view on sex selection as a gender-based preference for a pregnancy; progress in getting the Supreme Court of India to implement a 1994 law regulating the use of antenatal diagnostic technology; why sex selection should be available as a form of reproductive choice; and why sex selection may be empowering for women and justify their actions in the short run, given the demands on them. All agree that only improved status for women and girls will reduce the demand for sex selection.

A modified Janus cassette (Sweet Janus to improve allelic replacement efficiency by high-stringency negative selection in Streptococcus pneumoniae.

Directory of Open Access Journals (Sweden)

Yuan Li

Full Text Available The Janus cassette permits marker-free allelic replacement or knockout in streptomycin-resistant Streptococcus pneumoniae (pneumococcus through sequential positive and negative selection. Spontaneous revertants of Janus can lead to high level of false-positives during negative selection, which necessitate a time-consuming post-selection screening process. We hypothesized that an additional counter-selectable marker in Janus would decrease the revertant frequency and reduce false-positives, since simultaneous reversion of both counter-selectable makers is much less likely. Here we report a modified cassette, Sweet Janus (SJ, in which the sacB gene from Bacillus subtilis conferring sucrose sensitivity is added to Janus. By using streptomycin and sucrose simultaneously as selective agents, the frequency of SJ double revertants was about 105-fold lower than the frequency of Janus revertants. Accordingly, the frequency of false-positives in the SJ-mediated negative selection was about 100-fold lower than what was seen for Janus. Thus, SJ enhances negative selection stringency and can accelerate allelic replacement in pneumococcus, especially when transformation frequency is low due to strain background or suboptimal transformation conditions. Results also suggested the sacB gene alone can function as a counter-selectable marker in the Gram-positive pneumococcus, which will have the advantage of not requiring a streptomycin-resistant strain for allelic replacement.

Adaptive transmission based on multi-relay selection and rate-compatible LDPC codes

Science.gov (United States)

Su, Hualing; He, Yucheng; Zhou, Lin

2017-08-01

In order to adapt to the dynamical changeable channel condition and improve the transmissive reliability of the system, a cooperation system of rate-compatible low density parity check (RC-LDPC) codes combining with multi-relay selection protocol is proposed. In traditional relay selection protocol, only the channel state information (CSI) of source-relay and the CSI of relay-destination has been considered. The multi-relay selection protocol proposed by this paper takes the CSI between relays into extra account in order to obtain more chances of collabration. Additionally, the idea of hybrid automatic request retransmission (HARQ) and rate-compatible are introduced. Simulation results show that the transmissive reliability of the system can be significantly improved by the proposed protocol.

Selective Attention to Auditory Memory Neurally Enhances Perceptual Precision.

Science.gov (United States)

Lim, Sung-Joo; Wöstmann, Malte; Obleser, Jonas

2015-12-09

Selective attention to a task-relevant stimulus facilitates encoding of that stimulus into a working memory representation. It is less clear whether selective attention also improves the precision of a stimulus already represented in memory. Here, we investigate the behavioral and neural dynamics of selective attention to representations in auditory working memory (i.e., auditory objects) using psychophysical modeling and model-based analysis of electroencephalographic signals. Human listeners performed a syllable pitch discrimination task where two syllables served as to-be-encoded auditory objects. Valid (vs neutral) retroactive cues were presented during retention to allow listeners to selectively attend to the to-be-probed auditory object in memory. Behaviorally, listeners represented auditory objects in memory more precisely (expressed by steeper slopes of a psychometric curve) and made faster perceptual decisions when valid compared to neutral retrocues were presented. Neurally, valid compared to neutral retrocues elicited a larger frontocentral sustained negativity in the evoked potential as well as enhanced parietal alpha/low-beta oscillatory power (9-18 Hz) during memory retention. Critically, individual magnitudes of alpha oscillatory power (7-11 Hz) modulation predicted the degree to which valid retrocues benefitted individuals' behavior. Our results indicate that selective attention to a specific object in auditory memory does benefit human performance not by simply reducing memory load, but by actively engaging complementary neural resources to sharpen the precision of the task-relevant object in memory. Can selective attention improve the representational precision with which objects are held in memory? And if so, what are the neural mechanisms that support such improvement? These issues have been rarely examined within the auditory modality, in which acoustic signals change and vanish on a milliseconds time scale. Introducing a new auditory memory

Teaching animal habitat selection using wildlife tracking equipment

Science.gov (United States)

Laskowski, Jessica; Gillespie, Caitlyn R.; Corral, Lucia; Oden, Amy; Fricke, Kent A.; Fontaine, Joseph J.

2016-01-01

We present a hands-on outdoor activity coupled with classroom discussion to teach students about wildlife habitat selection, the process by which animals choose where to live. By selecting locations or habitats with many benefits (e.g., food, shelter, mates) and few costs (e.g., predators), animals improve their ability to survive and reproduce. Biologists track animal movement using radio telemetry technology to study habitat selection so they can better provide species with habitats that promote population growth. We present a curriculum in which students locate “animals” (transmitters) using radio telemetry equipment and apply math skills (use of fractions and percentages) to assess their “animal's” habitat selection by comparing the availability of habitat types with the proportion of “animals” they find in each habitat type.

Genomic selection to improve livestock production in developing countries with a focus on India

DEFF Research Database (Denmark)

Kadarmideen, Haja; Do, Duy Ngoc

2015-01-01

growth will increase the demand for food as well as animal products, particularly in emerging economic giants like India. Moreover, the urbanization has considerable impact on patterns of food consumption in general and on demand for livestock products, in particular and the increased income growth led......Global livestock production has increased substantially during the last decades, in both number of animals and productivity. Meanwhile, the human population is projected to reach 9.6 billions by 2050 and most of the increase in the projection takes place in developing countries. Rapid population...... production (OPU-IVP) of embryos will have a considerable impact in the future. This paper attempts to provide basic concepts of using genomic tools for livestock production with the focus on genomic prediction and selection methods and discuss about the potential application of genomic selection to increase...

Recurrent selection as breeding strategy for heat tolerance in wheat

OpenAIRE

Juarez Campolina Machado; Moacil Alves de Souza; Davi Melo de Oliveira; Adeliano Cargnin; Aderico Júnior Badaró Pimentel; Josiane Cristina de Assis

2010-01-01

The development of heat-tolerant varieties is an important goal of wheat breeding programs, requiringefficient selection methods. In the present study the use of recurrent selection was evaluated as a strategy to improve heatstress tolerance in wheat. Two cycles of recurrent selection were performed in experiments conducted in research areas of theUniversidade Federal de Viçosa, located in Coimbra-MG and Viçosa-MG, in 2004 and 2007, in two growing seasons (summerand winter). The genetic gain ...

Selection of candidate plus phenotypes of Jatropha curcas L. using method of paired comparisons

Energy Technology Data Exchange (ETDEWEB)

Mishra, D.K. [Silviculture Division, Arid Forest Research Institute, P.O. Krishi Mandi, New Pali Road, Jodhpur 342005, Rajasthan (India)

2009-03-15

Jatropha curcas L. (Euphorbiaceae) is an oil bearing species with multiple uses and considerable potential as a biodiesel crop. The present communication deals with the method of selecting plus phenotypes of J. curcas for exploiting genetic variability for further improvement. Candidate plus tree selection is the first and most important stage in any tree improvement programme. The selection of candidate plus plants (CPPs) is based upon various important attributes associated with the species and their relative ranking. Relative preference between various traits and scoring for each trait has been worked out by using the method of paired comparisons for the selection of CPP in J. curcas L. The most important ones are seed and oil yields. (author)

Investigation of selection methods im mutation breeding of barley for protein quantity and quality

International Nuclear Information System (INIS)

Ulonska, E.; Gaul, H.; Baumer, M.; Gesellschaft fuer Strahlen- und Umweltforschung m.b.H., Gruenbach

1975-01-01

This mutation breeding programme is investigating the qualification of micro-mutations for the selection of improved protein quality and quantity. Normally, improvement of protein content in micro-mutations is rather small. Therefore, it is important to develop methods and conditions of selection being (a) capable of measuring these small deviations in protein content and quality, and (b) simple to use. In two experiments carried out in 1971 and 1972 nitrogen fertilization was found to be the most important factor in the improvement of selection conditions. There is a highly significant negative correlation between crude protein content and the standard deviation; i.e. the higher the content of crude protein, the lower the variation coefficient. This in turn leads to an increase of genetic variation necessary for better selection progress. Nitrogen fertilization, especially during ear emergence, covers environmental influences - e.g., planting space, sowing rate, growing in different plots (6, 3, 2, 1 rows or in half-ear hills) - to a great extent. Thus, by applying high doses of nitrogen dressings comparable results can be achieved. In an overall selection experiment (testing the entire crossing and mutation material available at Weihenstephan in a stepwise selection from 1971 to 1973) and two selection experiments conducted in 1971 to 1973 with micro-mutants - variety Nota, 4 times X-rayed and the naked barley strain 1606 treated once with EMS - significant selection results were found. (author)

Explaining the apparent paradox of persistent selection for early flowering.

Science.gov (United States)

Austen, Emily J; Rowe, Locke; Stinchcombe, John R; Forrest, Jessica R K

2017-08-01

Decades of observation in natural plant populations have revealed pervasive phenotypic selection for early flowering onset. This consistent pattern seems at odds with life-history theory, which predicts stabilizing selection on age and size at reproduction. Why is selection for later flowering rare? Moreover, extensive evidence demonstrates that flowering time can and does evolve. What maintains ongoing directional selection for early flowering? Several non-mutually exclusive processes can help to reconcile the apparent paradox of selection for early flowering. We outline four: selection through other fitness components may counter observed fecundity selection for early flowering; asymmetry in the flowering-time-fitness function may make selection for later flowering hard to detect; flowering time and fitness may be condition-dependent; and selection on flowering duration is largely unaccounted for. In this Viewpoint, we develop these four mechanisms, and highlight areas where further study will improve our understanding of flowering-time evolution. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Genetic gain for body weight, feed conversion and carcass traits in selected broiler strains

Directory of Open Access Journals (Sweden)

GS Schmidt

2006-03-01

Full Text Available The Brazilian Swine and Poultry Research Center (Embrapa Suínos e Aves maintains a chicken breeding program for meat production since 1985. Two control lines (LLc and PPc are maintained, whereas two male lines (TT and ZZ and three female lines (PP, VV and KK have been selected. This paper reports the genetic gain after 15 generations of combined selection (mass and independent culling levels in order to develop the commercial broiler stocks Embrapa 021 and Embrapa 022. Selection pressure has been exerted on weight gain, carcass traits and fertility. In addition, female lines have also been selected for egg production, whereas males have been selected for feed efficiency since 1992. All lines have been selected for breast area instead of carcass traits since 1999. The genetic gain was estimated as the deviation between selected lines and the respective unselected lines at 42 days of age. In female lines, body weight improved 504, 548 and 587 g; average breast area increased 27.60; 16.99 and 26.43 cm²; adjusted feed conversion (42-49 d improved -1.46; -0.97 and 1.76 units, and egg production varied 6.99; 7.12 and -3.43% units for PP, VV and KK, respectively. In male lines, body weight improved 758 and 408 g; average breast area increased 31.95 and 19.38 cm², and adjusted feed conversion improved (42-49 d -0.99 and 1.26 for TT and ZZ, respectively. This breeding program has been effective to generate genetic gain and to develop two commercial products, Embrapa 021 (standard and Embrapa 022 (high yield. Nevertheless, feed efficiency is still not satisfactory.

Energy use in selected metal casting facilities - 2003

Energy Technology Data Exchange (ETDEWEB)

Eppich, Robert E. [Eppich Technologies, Syracuse, IN (United States)

2004-05-01

This report represents an energy benchmark for various metal casting processes. It describes process flows and energy use by fuel type and processes for selected casting operations. It also provides recommendations for improving energy efficiency in casting.

Information Gain Based Dimensionality Selection for Classifying Text Documents

Energy Technology Data Exchange (ETDEWEB)

Dumidu Wijayasekara; Milos Manic; Miles McQueen

2013-06-01

Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexity is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.

Improved Extension Neural Network and Its Applications

Directory of Open Access Journals (Sweden)

Yu Zhou

2014-01-01

Full Text Available Extension neural network (ENN is a new neural network that is a combination of extension theory and artificial neural network (ANN. The learning algorithm of ENN is based on supervised learning algorithm. One of important issues in the field of classification and recognition of ENN is how to achieve the best possible classifier with a small number of labeled training data. Training data selection is an effective approach to solve this issue. In this work, in order to improve the supervised learning performance and expand the engineering application range of ENN, we use a novel data selection method based on shadowed sets to refine the training data set of ENN. Firstly, we use clustering algorithm to label the data and induce shadowed sets. Then, in the framework of shadowed sets, the samples located around each cluster centers (core data and the borders between clusters (boundary data are selected as training data. Lastly, we use selected data to train ENN. Compared with traditional ENN, the proposed improved ENN (IENN has a better performance. Moreover, IENN is independent of the supervised learning algorithms and initial labeled data. Experimental results verify the effectiveness and applicability of our proposed work.

Publicly provided private goods: education and selective vouchers

OpenAIRE

Piolatto, Amedeo

2008-01-01

The literature on vouchers often concludes that a vouchers-based system cannot be the outcome of a majority vote. This paper shows that, when the value of vouchers and who is entitled to receive them are fixed exogenously, the majority of voters are in favour of selective vouchers. On top of that, as long as the introduction of vouchers does not undermine the existence of the public school system, introducing selective vouchers induces a Pareto improvement. Middle class agents are the only on...

Pearl millet transformation system using the positive selectable marker gene phosphomannose isomerase

CSIR Research Space (South Africa)

O'Kennedy, MM

2004-04-01

Full Text Available of the transgene. Similar to results obtained from previous studies with maize and wheat, the manA gene was shown to be a superior selectable marker gene for improving transformation efficiencies when compared to antibiotic or herbicide selectable marker genes....

Relay selection from an effective capacity perspective

KAUST Repository

Yang, Yuli

2013-09-01

In this work, we consider a cooperative network where multiple relay nodes having different modulation capabilities assist the end-to-end communication between a source and its destination. Firstly, we evaluate the effective capacity (EC) performance of the network under study. According to the analysis, an EC-based relay selection criterion is proposed. Based on the proposed selection rule and half-duplex decode-and-forward protocol, the activated relays cooperatively help with the packet transmission from the source. At the destination, packet combining is taken into account to improve the quality of service. Compared to the popular scheme, opportunistic relay selection, numerical results are provided to prove the validity and advantages of our proposed scheme in certain scenarios. Moreover, the analysis presented herein offers a convenient tool to the relaying transmission design, specifically on which relay selection scheme should be used as well as how to choose the receiving strategy between with and without packet combining at the destination. © 2013 IEEE.

Optimistic Selection Rule Better Than Majority Voting System

Science.gov (United States)

Sugiyama, Takuya; Obata, Takuya; Hoki, Kunihito; Ito, Takeshi

A recently proposed ensemble approach to game-tree search has attracted a great deal of attention. The ensemble system consists of M computer players, where each player uses a different series of pseudo-random numbers. A combination of multiple players under the majority voting system would improve the performance of a Shogi-playing computer. We present a new strategy of move selection based on the search values of a number of players. The move decision is made by selecting one player from all M players. Each move is selected by referring to the evaluation value of the tree search of each player. The performance and mechanism of the strategy are examined. We show that the optimistic selection rule, which selects the player that yields the highest evaluation value, outperforms the majority voting system. By grouping 16 or more computer players straightforwardly, the winning rates of the strongest Shogi programs increase from 50 to 60% or even higher.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Directory of Open Access Journals (Sweden)

Ahmed Majid Taha

2013-01-01

Full Text Available When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets.

Selective separation of pyrite and chalcopyrite by biomodulation.

Science.gov (United States)

Chandraprabha, M N; Natarajan, K A; Modak, Jayant M

2004-09-01

Selective separation of pyrite from other associated ferrous sulphides at acidic and neutral pH has been a challenging problem. This paper discusses the utility of Acidithiobacillus ferrooxidans for the selective flotation of chalcopyrite from pyrite. Consequent to interaction with bacterial cells, pyrite remained depressed even in the presence of potassium isopropyl xanthate collector while chalcopyrite exhibited significant flotability. However, when the minerals were conditioned together, the selectivity achieved was poor due to the activation of pyrite surface by the copper ions in solution. The selectivity was improved when the sequence of conditioning with bacterial cells and collector was reversed, since the bacterial cells were able to depress collector interacted pyrite effectively, while having negligible effect on chalcopyrite. The observed behaviour is analysed and discussed in detail. The separation obtained was significant both at acidic and alkaline pH. This selectivity achieved was retained when the minerals were interacted with both bacterial cells and collector simultaneously.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Science.gov (United States)

Taha, Ahmed Majid; Mustapha, Aida; Chen, Soong-Der

2013-01-01

When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets. PMID:24396295

Targeting of phage particles towards endothelial cells by antibodies selected through a multi-parameter selection strategy.

Science.gov (United States)

Mandrup, Ole A; Lykkemark, Simon; Kristensen, Peter

2017-02-10

One of the hallmarks of cancer is sustained angiogenesis. Here, normal endothelial cells are activated, and their formation of new blood vessels leads to continued tumour growth. An improved patient condition is often observed when angiogenesis is prevented or normalized through targeting of these genomically stable endothelial cells. However, intracellular targets constitute a challenge in therapy, as the agents modulating these targets have to be delivered and internalized specifically to the endothelial cells. Selection of antibodies binding specifically to certain cell types is well established. It is nonetheless a challenge to ensure that the binding of antibodies to the target cell will mediate internalization. Previously selection of such antibodies has been performed targeting cancer cell lines; most often using either monovalent display or polyvalent display. In this article, we describe selections that isolate internalizing antibodies by sequential combining monovalent and polyvalent display using two types of helper phages, one which increases display valence and one which reduces background. One of the selected antibodies was found to mediate internalization into human endothelial cells, although our results confirms that the single stranded nature of the DNA packaged into phage particles may limit applications aimed at targeting nucleic acids in mammalian cells.

Org 214007-0: a novel non-steroidal selective glucocorticoid receptor modulator with full anti-inflammatory properties and improved therapeutic index.

Science.gov (United States)

van Lierop, Marie-José C; Alkema, Wynand; Laskewitz, Anke J; Dijkema, Rein; van der Maaden, Hans M; Smit, Martin J; Plate, Ralf; Conti, Paolo G M; Jans, Christan G J M; Timmers, C Marco; van Boeckel, Constant A A; Lusher, Scott J; McGuire, Ross; van Schaik, Rene C; de Vlieg, Jacob; Smeets, Ruben L; Hofstra, Claudia L; Boots, Annemieke M H; van Duin, Marcel; Ingelse, Benno A; Schoonen, Willem G E J; Grefhorst, Aldo; van Dijk, Theo H; Kuipers, Folkert; Dokter, Wim H A

2012-01-01

Glucocorticoids (GCs) such as prednisolone are potent immunosuppressive drugs but suffer from severe adverse effects, including the induction of insulin resistance. Therefore, development of so-called Selective Glucocorticoid Receptor Modulators (SGRM) is highly desirable. Here we describe a non-steroidal Glucocorticoid Receptor (GR)-selective compound (Org 214007-0) with a binding affinity to GR similar to that of prednisolone. Structural modelling of the GR-Org 214007-0 binding site shows disturbance of the loop between helix 11 and helix 12 of GR, confirmed by partial recruitment of the TIF2-3 peptide. Using various cell lines and primary human cells, we show here that Org 214007-0 acts as a partial GC agonist, since it repressed inflammatory genes and was less effective in induction of metabolic genes. More importantly, in vivo studies in mice indicated that Org 214007-0 retained full efficacy in acute inflammation models as well as in a chronic collagen-induced arthritis (CIA) model. Gene expression profiling of muscle tissue derived from arthritic mice showed a partial activity of Org 214007-0 at an equi-efficacious dosage of prednisolone, with an increased ratio in repression versus induction of genes. Finally, in mice Org 214007-0 did not induce elevated fasting glucose nor the shift in glucose/glycogen balance in the liver seen with an equi-efficacious dose of prednisolone. All together, our data demonstrate that Org 214007-0 is a novel SGRMs with an improved therapeutic index compared to prednisolone. This class of SGRMs can contribute to effective anti-inflammatory therapy with a lower risk for metabolic side effects.

Selection and characterization of single stranded DNA aptamers recognizing fumonisin B1

International Nuclear Information System (INIS)

Chen, Xiujuan; Huang, Yukun; Duan, Nuo; Wu, Shijia; Xia, Yu; Ma, Xiaoyuan; Ding, Zhansheng; Wang, Zhouping; Zhu, Changqing; Jiang, Yuan

2014-01-01

We present an improved method for the selection of single-stranded DNA aptamers that can recognize fumonisin B 1 (FB 1 ). FB 1 is a carcinogenic mycotoxin mainly found in corn and corn-based food products worldwide, posing a global threat to feed and food safety. Selection was based on the mag-SELEX (magnetic bead systematic evolution of ligands by exponential enrichment) technology modified by adopting free analogs of targets rather than immobilized targets for counter selections. Firstly, aptamer candidates for FB 1 were selected from an 80 nt random DNA library after 13 rounds of selection. Next, binding assays were performed for affinity evaluation, and circular dichroism spectroscopy was used to investigate their conformation. A high-affinity aptamer designated as F10 (with a dissociation constant of 62 ± 5 nM) was identified and tested for its specificity by competitive binding assays. The results demonstrate that this improved mag-SELEX technology facilitates aptamer screening because it avoids the tedious immobilization of counter-selection molecules on magnetic beads. The aptamers obtained by this technique open new possibilities for the detection of FB 1 via aptasensors. (author)

Selecting and Improving Quasi-Experimental Designs in Effectiveness and Implementation Research.

Science.gov (United States)

Handley, Margaret A; Lyles, Courtney R; McCulloch, Charles; Cattamanchi, Adithya

2018-04-01

Interventional researchers face many design challenges when assessing intervention implementation in real-world settings. Intervention implementation requires holding fast on internal validity needs while incorporating external validity considerations (such as uptake by diverse subpopulations, acceptability, cost, and sustainability). Quasi-experimental designs (QEDs) are increasingly employed to achieve a balance between internal and external validity. Although these designs are often referred to and summarized in terms of logistical benefits, there is still uncertainty about (a) selecting from among various QEDs and (b) developing strategies to strengthen the internal and external validity of QEDs. We focus here on commonly used QEDs (prepost designs with nonequivalent control groups, interrupted time series, and stepped-wedge designs) and discuss several variants that maximize internal and external validity at the design, execution and implementation, and analysis stages.

Improved methods for the mathematically controlled comparison of biochemical systems

Directory of Open Access Journals (Sweden)

Schwacke John H

2004-06-01

Full Text Available Abstract The method of mathematically controlled comparison provides a structured approach for the comparison of alternative biochemical pathways with respect to selected functional effectiveness measures. Under this approach, alternative implementations of a biochemical pathway are modeled mathematically, forced to be equivalent through the application of selected constraints, and compared with respect to selected functional effectiveness measures. While the method has been applied successfully in a variety of studies, we offer recommendations for improvements to the method that (1 relax requirements for definition of constraints sufficient to remove all degrees of freedom in forming the equivalent alternative, (2 facilitate generalization of the results thus avoiding the need to condition those findings on the selected constraints, and (3 provide additional insights into the effect of selected constraints on the functional effectiveness measures. We present improvements to the method and related statistical models, apply the method to a previously conducted comparison of network regulation in the immune system, and compare our results to those previously reported.

Improved photovoltaic cells and electrodes

Science.gov (United States)

Skotheim, T.A.

1983-06-29

Improved photovoltaic cells and electrodes for use therein, particularly electrodes employing amorphous silicon or polyacetylene coating are produced by a process which includes filling pinholes or porous openings in the coatings by electrochemical oxidation of selected monomers to deposit insulating polymer in the openings.

Visuospatial selective attention in chickens.

Science.gov (United States)

Sridharan, Devarajan; Ramamurthy, Deepa L; Schwarz, Jason S; Knudsen, Eric I

2014-05-13

Voluntary control of attention promotes intelligent, adaptive behaviors by enabling the selective processing of information that is most relevant for making decisions. Despite extensive research on attention in primates, the capacity for selective attention in nonprimate species has never been quantified. Here we demonstrate selective attention in chickens by applying protocols that have been used to characterize visual spatial attention in primates. Chickens were trained to localize and report the vertical position of a target in the presence of task-relevant distracters. A spatial cue, the location of which varied across individual trials, indicated the horizontal, but not vertical, position of the upcoming target. Spatial cueing improved localization performance: accuracy (d') increased and reaction times decreased in a space-specific manner. Distracters severely impaired perceptual performance, and this impairment was greatly reduced by spatial cueing. Signal detection analysis with an "indecision" model demonstrated that spatial cueing significantly increased choice certainty in localizing targets. By contrast, error-aversion certainty (certainty of not making an error) remained essentially constant across cueing protocols, target contrasts, and individuals. The results show that chickens shift spatial attention rapidly and dynamically, following principles of stimulus selection that closely parallel those documented in primates. The findings suggest that the mechanisms that control attention have been conserved through evolution, and establish chickens--a highly visual species that is easily trained and amenable to cutting-edge experimental technologies--as an attractive model for linking behavior to neural mechanisms of selective attention.

Engineering and Design. Guidelines on Ground Improvement for Structures and Facilities

National Research Council Canada - National Science Library

Enson, Carl

1999-01-01

.... It addresses general evaluation of site and soil conditions, selection of improvement methods, preliminary cost estimating, design, construction, and performance evaluation for ground improvement...

Automated sample plan selection for OPC modeling

Science.gov (United States)

Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

2014-03-01

It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

Improvement of fragment and primer selection for mutation detection by denaturing gradient gel electrophoresis

NARCIS (Netherlands)

Wu, Y; Hayes, VM; Osinga, J; Mulder, IM; Looman, MWG; Buys, CHCM; Hofstra, RMW

1998-01-01

Denaturing gradient gel electrophoresis (DGGE) is one of the most powerful methods for mutation detection currently available. For successful application the appropriate selection of PCR fragments and PCR primers is crucial. The sequence of interest should always be within the domain with the lowest

Features Selection for Skin Micro-Image Symptomatic Recognition

Institute of Scientific and Technical Information of China (English)

HUYue-li; CAOJia-lin; ZHAOQian; FENGXu

2004-01-01

Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92% using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

Features Selection for Skin Micro-Image Symptomatic Recognition

Institute of Scientific and Technical Information of China (English)

HU Yue-li; CAO Jia-lin; ZHAO Qian; FENG Xu

2004-01-01

Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92 % using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

Aluminium supplier selection for the automotive parts manufacturer

Directory of Open Access Journals (Sweden)

M. Cieśla

2016-04-01

Full Text Available This paper presents a methodology for selection of the optimal sources of supply, which is also known as the problem of supplier selection. Theoretical considerations are expanded with research related to aluminium supplier selection for a hypothetical manufacturer of aluminium parts for transportation equipment located in Poland. Evaluation of five suppliers of aluminium from Poland, Germany and Slovenia has been conducted using a weighted scoring method, a strengths and weaknesses method and a graphical method. Choosing the best offer and prioritizing suppliers allows not only the most rational decision in the field of supply logistics to be taken but also the quality of service in the metallurgical industry to be improved.

EDITORIAL: Nanotechnological selection Nanotechnological selection

Science.gov (United States)

Demming, Anna

2013-01-01

across the channel. The aim of achieving selectivity encompasses a huge range of fields in nanotechnology research, from sensing and medicine to nanoelectronics and self-assembly. As our understanding of how nanosystems behave deepens, so too does the hunger to improve our capabilities, allowing greater precision and control in manipulating these systems. Selectivity is far from trivial when shrinking to systems of nanoscale dimensions, but the range of opportunities it brings just keeps on growing. References [1] Gong X, Li J, Guo C, Xu K and Hui Y 2012 Molecular switch for tuning ions across nanopores by an external electric field Nanotechnology 24 025502 [2] Brannon-Peppas L and Blanchette J O 2004 Nanoparticle and targeted systems for cancer therapy Adv. Drug Deliv. Rev 56 1649-59 [3] Lukianova-Hleb E Y, Hanna E Y, Hafner J H and Lapotko D O 2010 Tunable plasmonic nanobubbles for cell theranostics Nanotechnology 21 085102 [4] Zhang T, Mubeen S, Myung N V and Deshusses M A 2008 Recent progress in carbon nanotube-based gas sensors Nanotechnology 19 332001 [5] Mangu R, Rajaputra S and Singh V P 2011 MWCNT-polymer composites as highly sensitive and selective room temperature gas sensors Nanotechnology 22 215502 [6]Meller A, Nivon L, Brandin E, Golovchenko J and Branton D 2000 Rapid nanopore discrimination between single polynucleotide molecules Proc. Natl Acad. Sci. 97 1079-84 [7] Asghar W, Ilyas A, Deshmukh R R, Sumitsawan S, Timmons R B and Iqbal S M 2011 Pulsed plasma polymerization for controlling shrinkage and surface composition of nanopores Nanotechnology 22 285304

Public sector scale-up of zinc and ORS improves coverage in selected districts in Bihar, India.

Science.gov (United States)

Walker, Christa L Fischer; Taneja, Sunita; Lamberti, Laura M; Black, Robert E; Mazumder, Sarmila

2015-12-01

In Bihar, India, a new initiative to enhance diarrhea treatment with zinc and ORS in the public sector was rolled out in selected districts. We conducted an external evaluation to measure changes in diarrhea careseeking and treatment in intervention districts. We conducted baseline and endline household surveys among caregivers of children 2-59 months of age. We calculated summary statistics for household characteristics, knowledge, careseeking and treatments given to children with a diarrhea episode in the last 14 days and built logistic regression models to compare baseline and endline values. Caregivers named a public health center as an appropriate source of care for childhood diarrhea more often at endline (71.3%) compared to baseline (38.4%) but did not report increased careseeking to public sector providers for the current diarrhea episode. In logistic regression analyses, the odds of receiving zinc, with or without oral rehydration salts (ORS), increased at endline by more than 2.7 as compared to baseline. Children who were taken to the public sector for care were more likely to receive zinc (odds ratio, OR = 3.93) and zinc in addition to ORS (OR = 6.10) compared to children who were not taken to the public sector. Coverage of zinc and ORS can improve with public sector programs targeted at training and increasing product availability, but demand creation may be needed to increase public sector careseeking in areas where the private sector has historically provided much of the care.

Characteristic gene selection via weighting principal components by singular values.

Directory of Open Access Journals (Sweden)

Jin-Xing Liu

Full Text Available Conventional gene selection methods based on principal component analysis (PCA use only the first principal component (PC of PCA or sparse PCA to select characteristic genes. These methods indeed assume that the first PC plays a dominant role in gene selection. However, in a number of cases this assumption is not satisfied, so the conventional PCA-based methods usually provide poor selection results. In order to improve the performance of the PCA-based gene selection method, we put forward the gene selection method via weighting PCs by singular values (WPCS. Because different PCs have different importance, the singular values are exploited as the weights to represent the influence on gene selection of different PCs. The ROC curves and AUC statistics on artificial data show that our method outperforms the state-of-the-art methods. Moreover, experimental results on real gene expression data sets show that our method can extract more characteristic genes in response to abiotic stresses than conventional gene selection methods.

The past, present and future genetic improvement of indigenous chicken of Kenya

DEFF Research Database (Denmark)

Khobondo, J O; Okeno, Tobias O; Lihare, G O

2014-01-01

Genetic improvement of farm animals encompasses both mating and selection for desired traits and indigenous chicken genetic resources are no exception. In Kenya, previous attempts to genetically improve indigenous chicken involved cross-breeding scheme by utilizing cockerels and pullets of exotic...... on production traits, determined heritability estimate on growth. Current and ongoing research is focused on molecular characterization, selection for improved immune response, carcass quality, eggs production, growth and adaptation traits. The research is also concerned with conservation of these genetic...

Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance

NARCIS (Netherlands)

Mulder, H.A.; Veerkamp, R.F.; Vereijken, A.; Bijma, P.; Hill, W.G.

2008-01-01

some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters,

A multi-site study on medical school selection, performance, motivation and engagement

NARCIS (Netherlands)

Wouters, A.; Croiset, G.; Schripsema, N. R.; Cohen-Schotanus, J.; Spaai, G. W. G.; Hulsman, R. L.; Kusurkar, R. A.

Medical schools seek ways to improve their admissions strategies, since the available methods prove to be suboptimal for selecting the best and most motivated students. In this multi-site cross-sectional questionnaire study, we examined the value of (different) selection procedures compared to a

A Novel Fault Line Selection Method Based on Improved Oscillator System of Power Distribution Network

Directory of Open Access Journals (Sweden)

Xiaowei Wang

2014-01-01

Full Text Available A novel method of fault line selection based on IOS is presented. Firstly, the IOS is established by using math model, which adopted TZSC signal to replace built-in signal of duffing chaotic oscillator by selecting appropriate parameters. Then, each line’s TZSC decomposed by db10 wavelet packet to get CFB with the maximum energy principle, and CFB was solved by IOS. Finally, maximum chaotic distance and average chaotic distance on the phase trajectory are used to judge fault line. Simulation results show that the proposed method can accurately judge fault line and healthy line in strong noisy background. Besides, the nondetection zones of proposed method are elaborated.

Asymptotic analysis for Nakagami-m fading channels with relay selection

KAUST Repository