Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

PubMed

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

An efficient strategy for cell-based antibody library selection using an integrated vector system.

PubMed

Yoon, Hyerim; Song, Jin Myung; Ryu, Chun Jeih; Kim, Yeon-Gu; Lee, Eun Kyo; Kang, Sunghyun; Kim, Sang Jick

2012-09-18

Cell panning of phage-displayed antibody library is a powerful tool for the development of therapeutic and imaging agents since disease-related cell surface proteins in native complex conformation can be directly targeted. Here, we employed a strategy taking advantage of an integrated vector system which allows rapid conversion of scFv-displaying phage into scFv-Fc format for efficient cell-based scFv library selection on a tetraspanin protein, CD9. A mouse scFv library constructed by using a phagemid vector, pDR-D1 was subjected to cell panning against stable CD9 transfectant, and the scFv repertoire from the enriched phage pool was directly transferred to a mammalian cassette vector, pDR-OriP-Fc1. The resulting constructs enabled transient expression of enough amounts of scFv-Fcs in HEK293E cells, and flow cytometric screening of binders for CD9 transfectant could be performed simply by using the culture supernatants. All three clones selected from the screening showed correct CD9-specificity. They could immunoprecipitate CD9 molecules out of the transfectant cell lysate and correctly stain endogenous CD9 expression on cancer cell membrane. Furthermore, competition assay with a known anti-CD9 monoclonal antibody (mAb) suggested that the binding epitopes of some of them overlap with that of the mAb which resides within the large extracellular loop of CD9. This study demonstrates that scFv-Fc from mammalian transient expression can be chosen as a reliable format for rapid screening and validation in cell-based scFv library selection, and the strategy described here will be applicable to efficient discovery of antibodies to diverse cell-surface targets.

Systematic Sensor Selection Strategy (S4) User Guide

NASA Technical Reports Server (NTRS)

Sowers, T. Shane

2012-01-01

This paper describes a User Guide for the Systematic Sensor Selection Strategy (S4). S4 was developed to optimally select a sensor suite from a larger pool of candidate sensors based on their performance in a diagnostic system. For aerospace systems, selecting the proper sensors is important for ensuring adequate measurement coverage to satisfy operational, maintenance, performance, and system diagnostic criteria. S4 optimizes the selection of sensors based on the system fault diagnostic approach while taking conflicting objectives such as cost, weight and reliability into consideration. S4 can be described as a general architecture structured to accommodate application-specific components and requirements. It performs combinational optimization with a user defined merit or cost function to identify optimum or near-optimum sensor suite solutions. The S4 User Guide describes the sensor selection procedure and presents an example problem using an open source turbofan engine simulation to demonstrate its application.

Selection Strategies for Social Influence in the Threshold Model

NASA Astrophysics Data System (ADS)

Karampourniotis, Panagiotis; Szymanski, Boleslaw; Korniss, Gyorgy

The ubiquity of online social networks makes the study of social influence extremely significant for its applications to marketing, politics and security. Maximizing the spread of influence by strategically selecting nodes as initiators of a new opinion or trend is a challenging problem. We study the performance of various strategies for selection of large fractions of initiators on a classical social influence model, the Threshold model (TM). Under the TM, a node adopts a new opinion only when the fraction of its first neighbors possessing that opinion exceeds a pre-assigned threshold. The strategies we study are of two kinds: strategies based solely on the initial network structure (Degree-rank, Dominating Sets, PageRank etc.) and strategies that take into account the change of the states of the nodes during the evolution of the cascade, e.g. the greedy algorithm. We find that the performance of these strategies depends largely on both the network structure properties, e.g. the assortativity, and the distribution of the thresholds assigned to the nodes. We conclude that the optimal strategy needs to combine the network specifics and the model specific parameters to identify the most influential spreaders. Supported in part by ARL NS-CTA, ARO, and ONR.

Effects of strategy sequences and response-stimulus intervals on children's strategy selection and strategy execution: a study in computational estimation.

PubMed

Lemaire, Patrick; Brun, Fleur

2014-07-01

The present study investigates how children's better strategy selection and strategy execution on a given problem are influenced by which strategy was used on the immediately preceding problem and by the duration between their answer to the previous problem and current problem display. These goals are pursued in the context of an arithmetic problem solving task. Third and fifth graders were asked to select the better strategy to find estimates to two-digit addition problems like 36 + 78. On each problem, children could choose rounding-down (i.e., rounding both operands down to the closest smaller decades, like doing 40 + 60 to solve 42 + 67) or rounding-up strategies (i.e., rounding both operands up to the closest larger decades, like doing 50 + 70 to solve 42 + 67). Children were tested under a short RSI condition (i.e., the next problem was displayed 900 ms after participants' answer) or under a long RSI condition (i.e., the next problem was displayed 1,900 ms after participants' answer). Results showed that both strategy selection (e.g., children selected the better strategy more often under long RSI condition and after selecting the poorer strategy on the immediately preceding problem) and strategy execution (e.g., children executed strategy more efficiently under long RSI condition and were slower when switching strategy over two consecutive problems) were influenced by RSI and which strategy was used on the immediately preceding problem. Moreover, data showed age-related changes in effects of RSI and strategy sequence on mean percent better strategy selection and on strategy performance. The present findings have important theoretical and empirical implications for our understanding of general and specific processes involved in strategy selection, strategy execution, and strategic development.

Natural selection of memory-one strategies for the iterated prisoner's dilemma.

PubMed

Kraines, D P; Kraines, V Y

2000-04-21

In the iterated Prisoner's Dilemma, mutually cooperative behavior can become established through Darwinian natural selection. In simulated interactions of stochastic memory-one strategies for the Iterated Prisoner's Dilemma, Nowak and Sigmund discovered that cooperative agents using a Pavlov (Win-Stay Lose-Switch) type strategy eventually dominate a random population. This emergence follows more directly from a deterministic dynamical system based on differential reproductive success or natural selection. When restricted to an environment of memory-one agents interacting in iterated Prisoner's Dilemma games with a 1% noise level, the Pavlov agent is the only cooperative strategy and one of very few others that cannot be invaded by a similar strategy. Pavlov agents are trusting but no suckers. They will exploit weakness but repent if punished for cheating. Copyright 2000 Academic Press.

Processes in arithmetic strategy selection: a fMRI study.

PubMed

Taillan, Julien; Ardiale, Eléonore; Anton, Jean-Luc; Nazarian, Bruno; Félician, Olivier; Lemaire, Patrick

2015-01-01

This neuroimaging (functional magnetic resonance imaging) study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 × 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up (RU) strategy (i.e., doing 60 × 80 = 4,800) or rounding-down (RD) strategy (i.e., doing 50 × 70 = 3,500 to estimate product of 54 × 78). In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40 × 50). Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC), dorso-lateral prefrontal cortex (DLPFC), and angular gyrus (ANG), when selecting (relative to executing) the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modeling cognitive processes underlying strategy selection.

Processes in arithmetic strategy selection: a fMRI study

PubMed Central

Taillan, Julien; Ardiale, Eléonore; Anton, Jean-Luc; Nazarian, Bruno; Félician, Olivier; Lemaire, Patrick

2015-01-01

This neuroimaging (functional magnetic resonance imaging) study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 × 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up (RU) strategy (i.e., doing 60 × 80 = 4,800) or rounding-down (RD) strategy (i.e., doing 50 × 70 = 3,500 to estimate product of 54 × 78). In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40 × 50). Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC), dorso-lateral prefrontal cortex (DLPFC), and angular gyrus (ANG), when selecting (relative to executing) the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modeling cognitive processes underlying strategy selection. PMID:25698995

SSL: A Theory of How People Learn to Select Strategies

ERIC Educational Resources Information Center

Rieskamp, Jorg; Otto, Philipp E.

2006-01-01

The assumption that people possess a repertoire of strategies to solve the inference problems they face has been raised repeatedly. However, a computational model specifying how people select strategies from their repertoire is still lacking. The proposed strategy selection learning (SSL) theory predicts a strategy selection process on the basis…

Resource efficiency potential of selected technologies, products and strategies.

PubMed

Rohn, Holger; Pastewski, Nico; Lettenmeier, Michael; Wiesen, Klaus; Bienge, Katrin

2014-03-01

Despite rising prices for natural resources during the past 30 years, global consumption of natural resources is still growing. This leads to ecological, economical and social problems. So far, however, limited effort has been made to decrease the natural resource use of goods and services. While resource efficiency is already on the political agenda (EU and national resource strategies), there are still substantial knowledge gaps on the effectiveness of resource efficiency improvement strategies in different fields. In this context and within the project "Material Efficiency and Resource Conservation", the natural resource use of 22 technologies, products and strategies was calculated and their resource efficiency potential analysed. In a preliminary literature- and expert-based identification process, over 250 technologies, strategies, and products, which are regarded as resource efficient, were identified. Out of these, 22 subjects with high resource efficiency potential were selected. They cover a wide range of relevant technologies, products and strategies, such as energy supply and storage, Green IT, transportation, foodstuffs, agricultural engineering, design strategies, lightweight construction, as well as the concept "Using Instead of Owning". To assess the life-cycle-wide resource use of the selected subjects, the material footprint has been applied as a reliable indicator. In addition, sustainability criteria on a qualitative basis were considered. The results presented in this paper show significant resource efficiency potential for many technologies, products and strategies. Copyright © 2013. Published by Elsevier B.V.

Selecting habitat management strategies on refuges

USGS Publications Warehouse

Schroeder, Richard L.; King, Wayne J.; Cornely, John E.

1998-01-01

This report is a joint effort of the Biological Resources Division, U.S. Geological Survey and the U.S. Fish and Wildlife Service (FWS) to provide National Wildlife Refuge (NWR) managers guidance on the selection and evaluation of habitat management strategies to meet stated objectives. The FWS recently completed a handbook on writing refuge management goals and objectives (U.S. Fish and Wildlife Service 1996a). the National Wildlife Refuge System Improvement Act of 1997 requires that National Wildlife Refuge System (NWRS) lands be managed according to approved Comprehensive Conservation Plans to guide management decisions and devise strategies for achieving refuge unit purposes and meeting the NWRS mission. It is expected that over the next several years most refuges will develop new or revised refuge goals and objectives for directing their habitat management strategies. This paper outlines the steps we recommend in selecting and evaluating habitat management strategies to meet specific refuge habitat objectives. We selected two examples to illustrate the process. Although each refuge is unique and will require specific information and solutions, these two examples can be used as guidance when selecting and evaluating habitat management strategies for other refuge resources: Example 1. Management of floodplain woods habitat for forest interior birds. The biological recourse of concern is the quality and quantity of floodplain woods habitat for eastern forest interior birds in the Cypress Creek NWR (U.S. Fish and Wildlife Service 1996b). Example 2. Management of habitat for biodiversity: Historical landscape proportions. The biological resource of concern is the change in diversity associated with man-induced changes in the distribution and abundance of habitat types at the Minnesota Valley NWR (U.S. Fish and Wildlife Service 1996c).

Mutation-selection equilibrium in games with mixed strategies.

PubMed

Tarnita, Corina E; Antal, Tibor; Nowak, Martin A

2009-11-07

We develop a new method for studying stochastic evolutionary game dynamics of mixed strategies. We consider the general situation: there are n pure strategies whose interactions are described by an nxn payoff matrix. Players can use mixed strategies, which are given by the vector (p(1),...,p(n)). Each entry specifies the probability to use the corresponding pure strategy. The sum over all entries is one. Therefore, a mixed strategy is a point in the simplex S(n). We study evolutionary dynamics in a well-mixed population of finite size. Individuals reproduce proportional to payoff. We consider the case of weak selection, which means the payoff from the game is only a small contribution to overall fitness. Reproduction can be subject to mutation; a mutant adopts a randomly chosen mixed strategy. We calculate the average abundance of every mixed strategy in the stationary distribution of the mutation-selection process. We find the crucial conditions that specify if a strategy is favored or opposed by selection. One condition holds for low mutation rate, another for high mutation rate. The result for any mutation rate is a linear combination of those two. As a specific example we study the Hawk-Dove game. We prove general statements about the relationship between games with pure and with mixed strategies.

Plan selection strategy for rectum cancer patients: An interobserver study to assess clinical feasibility.

PubMed

de Jong, Rianne; Lutkenhaus, Lotte; van Wieringen, Niek; Visser, Jorrit; Wiersma, Jan; Crama, Koen; Geijsen, Debby; Bel, Arjan

2016-08-01

In radiotherapy for rectum cancer, the target volume is highly deformable. An adaptive plan selection strategy can mitigate the effect of these variations. The purpose of this study was to evaluate the feasibility of an adaptive strategy by assessing the interobserver variation in CBCT-based plan selection. Eleven patients with rectum cancer, treated with a non-adaptive strategy, were selected. Five CBCT scans were available per patient. To simulate the plan selection strategy, per patient three PTVs were created by varying the anterior upper mesorectum margin. For each CBCT scan, twenty observers selected the smallest PTV that encompassed the target volume. After this initial baseline measurement, the gold standard was determined during a consensus meeting, followed by a second measurement one month later. Differences between both measurements were assessed using the Wilcoxon signed-rank test. In the baseline measurement, the concordance with the gold standard was 69% (range: 60-82%), which improved to 75% (range: 60-87%) in the second measurement (p=0.01). For the second measurement, 10% of plan selections were smaller than the gold standard. With a plan selection consistency between observers of 75%, a plan selection strategy for rectum cancer patients is feasible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Therapists' causal attributions of clients' problems and selection of intervention strategies.

PubMed

Royce, W S; Muehlke, C V

1991-04-01

Therapists' choices of intervention strategies are influenced by many factors, including judgments about the bases of clients' problems. To assess the relationships between such causal attributions and the selection of intervention strategies, 196 counselors, psychologists, and social workers responded to the written transcript of a client's interview by answering two questionnaires, a 1982 scale (Causal Dimension Scale by Russell) which measured causal attribution of the client's problem, and another which measured preference for emotional, rational, and active intervention strategies in dealing with the client, based on the 1979 E-R-A taxonomy of Frey and Raming. A significant relationship was found between the two sets of variables, with internal attributions linked to rational intervention strategies and stable attributions linked to active strategies. The results support Halleck's 1978 hypothesis that theories of psychotherapy tie interventions to etiological considerations.

Application of selection index calculations to determine selection strategies in genomic breeding programs.

PubMed

König, S; Swalve, H H

2009-10-01

The availability of genomic estimated breeding values (GEBV) allows for possible modifications to existing dairy cattle breeding programs. Selection index calculations including genomic and phenotypic observations as index sources were used to determine the optimal number of offspring per genotyped sire with a focus on functional traits and the design of cooperator herds, and to evaluate the importance of a central station test for genotyped bull dams. Evaluation criteria to compare different breeding strategies were correlations between index and aggregate genotype (r(TI)), and the relative selection response percentage (RSR) of an index without single nucleotide polymorphism information in relation to a single nucleotide polymorphism-based index. The number of required daughter records per sire to achieve a predefined r(TI) strongly depends on the accuracy of GEBV (r(mg)) and the heritability of the trait. For a desired r(TI) of 0.8, h(2) = 0.10, and r(mg) = 0.5, at least 57 additional daughters have to be included in the genetic evaluation. Daughter records of genotyped sires are not necessary for optimal scenarios where r(mg) is greater than or equal to r(TI). There still is a substantial need for phenotypic daughter records, especially for low-heritability functional traits and r(mg) < 0.7. Phenotypic records from genotyped potential bull dams have no relevance for increasing r(TI), even with a low value for r(mg) of 0.5. Hence, genomic breeding programs should focus on recording functional traits within progeny groups, preferably in cooperator herds. For low-heritability traits and with r(mg) > 0.7, the RSR of conventional breeding programs was only 10% of RSR from genomic breeding strategies. As shown in scenarios including 2 traits in the index as well as in the aggregate genotype, the availability of highly accurate GEBV for production traits and low-accuracy GEBV for functional traits increased the risk of widening the gap between selection responses in

Affect-Aware Adaptive Tutoring Based on Human-Automation Etiquette Strategies.

PubMed

Yang, Euijung; Dorneich, Michael C

2018-06-01

We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human-automation etiquette strategies. Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students' motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn.

Selective robust optimization: A new intensity-modulated proton therapy optimization strategy

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

Li, Yupeng; Niemela, Perttu; Siljamaki, Sami

2015-08-15

Purpose: To develop a new robust optimization strategy for intensity-modulated proton therapy as an important step in translating robust proton treatment planning from research to clinical applications. Methods: In selective robust optimization, a worst-case-based robust optimization algorithm is extended, and terms of the objective function are selectively computed from either the worst-case dose or the nominal dose. Two lung cancer cases and one head and neck cancer case were used to demonstrate the practical significance of the proposed robust planning strategy. The lung cancer cases had minimal tumor motion less than 5 mm, and, for the demonstration of the methodology,more » are assumed to be static. Results: Selective robust optimization achieved robust clinical target volume (CTV) coverage and at the same time increased nominal planning target volume coverage to 95.8%, compared to the 84.6% coverage achieved with CTV-based robust optimization in one of the lung cases. In the other lung case, the maximum dose in selective robust optimization was lowered from a dose of 131.3% in the CTV-based robust optimization to 113.6%. Selective robust optimization provided robust CTV coverage in the head and neck case, and at the same time improved controls over isodose distribution so that clinical requirements may be readily met. Conclusions: Selective robust optimization may provide the flexibility and capability necessary for meeting various clinical requirements in addition to achieving the required plan robustness in practical proton treatment planning settings.« less

Mutation-selection equilibrium in games with multiple strategies.

PubMed

Antal, Tibor; Traulsen, Arne; Ohtsuki, Hisashi; Tarnita, Corina E; Nowak, Martin A

2009-06-21

In evolutionary games the fitness of individuals is not constant but depends on the relative abundance of the various strategies in the population. Here we study general games among n strategies in populations of large but finite size. We explore stochastic evolutionary dynamics under weak selection, but for any mutation rate. We analyze the frequency dependent Moran process in well-mixed populations, but almost identical results are found for the Wright-Fisher and Pairwise Comparison processes. Surprisingly simple conditions specify whether a strategy is more abundant on average than 1/n, or than another strategy, in the mutation-selection equilibrium. We find one condition that holds for low mutation rate and another condition that holds for high mutation rate. A linear combination of these two conditions holds for any mutation rate. Our results allow a complete characterization of nxn games in the limit of weak selection.

Reference field specification and preliminary beam selection strategy for accelerator-based GCR simulation

NASA Astrophysics Data System (ADS)

Slaba, Tony C.; Blattnig, Steve R.; Norbury, John W.; Rusek, Adam; La Tessa, Chiara

2016-02-01

The galactic cosmic ray (GCR) simulator at the NASA Space Radiation Laboratory (NSRL) is intended to deliver the broad spectrum of particles and energies encountered in deep space to biological targets in a controlled laboratory setting. In this work, certain aspects of simulating the GCR environment in the laboratory are discussed. Reference field specification and beam selection strategies at NSRL are the main focus, but the analysis presented herein may be modified for other facilities and possible biological considerations. First, comparisons are made between direct simulation of the external, free space GCR field and simulation of the induced tissue field behind shielding. It is found that upper energy constraints at NSRL limit the ability to simulate the external, free space field directly (i.e. shielding placed in the beam line in front of a biological target and exposed to a free space spectrum). Second, variation in the induced tissue field associated with shielding configuration and solar activity is addressed. It is found that the observed variation is likely within the uncertainty associated with representing any GCR reference field with discrete ion beams in the laboratory, given current facility constraints. A single reference field for deep space missions is subsequently identified. Third, a preliminary approach for selecting beams at NSRL to simulate the designated reference field is presented. This approach is not a final design for the GCR simulator, but rather a single step within a broader design strategy. It is shown that the beam selection methodology is tied directly to the reference environment, allows facility constraints to be incorporated, and may be adjusted to account for additional constraints imposed by biological or animal care considerations. The major biology questions are not addressed herein but are discussed in a companion paper published in the present issue of this journal. Drawbacks of the proposed methodology are discussed

Assessment strategies for municipal selective waste collection schemes.

PubMed

Ferreira, Fátima; Avelino, Catarina; Bentes, Isabel; Matos, Cristina; Teixeira, Carlos Afonso

2017-01-01

An important strategy to promote a strong sustainable growth relies on an efficient municipal waste management, and phasing out waste landfilling through waste prevention and recycling emerges as a major target. For this purpose, effective collection schemes are required, in particular those regarding selective waste collection, pursuing a more efficient and high quality recycling of reusable materials. This paper addresses the assessment and benchmarking of selective collection schemes, relevant to guide future operational improvements. In particular, the assessment is based on the monitoring and statistical analysis of a core-set of performance indicators that highlights collection trends, complemented with a performance index that gathers a weighted linear combination of these indicators. This combined analysis underlines a potential tool to support decision makers involved in the process of selecting the collection scheme with best overall performance. The presented approach was applied to a case study conducted in Oporto Municipality, with data gathered from two distinct selective collection schemes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heuristic Strategies for Persuader Selection in Contagions on Complex Networks.

PubMed

Wang, Peng; Zhang, Li-Jie; Xu, Xin-Jian; Xiao, Gaoxi

2017-01-01

Individual decision to accept a new idea or product is often driven by both self-adoption and others' persuasion, which has been simulated using a double threshold model [Huang et al., Scientific Reports 6, 23766 (2016)]. We extend the study to consider the case with limited persuasion. That is, a set of individuals is chosen from the population to be equipped with persuasion capabilities, who may succeed in persuading their friends to take the new entity when certain conditions are satisfied. Network node centrality is adopted to characterize each node's influence, based on which three heuristic strategies are applied to pick out persuaders. We compare these strategies for persuader selection on both homogeneous and heterogeneous networks. Two regimes of the underline networks are identified in which the system exhibits distinct behaviors: when networks are sufficiently sparse, selecting persuader nodes in descending order of node centrality achieves the best performance; when networks are sufficiently dense, however, selecting nodes with medium centralities to serve as the persuaders performs the best. Under respective optimal strategies for different types of networks, we further probe which centrality measure is most suitable for persuader selection. It turns out that for the first regime, degree centrality offers the best measure for picking out persuaders from homogeneous networks; while in heterogeneous networks, betweenness centrality takes its place. In the second regime, there is no significant difference caused by centrality measures in persuader selection for homogeneous network; while for heterogeneous networks, closeness centrality offers the best measure.

Feature extraction and selection strategies for automated target recognition

NASA Astrophysics Data System (ADS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-04-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory regionof- interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Selecting decision strategies: the differential role of affect.

PubMed

Scheibehenne, Benjamin; von Helversen, Bettina

2015-01-01

Many theories on cognition assume that people adapt their decision strategies depending on the situation they face. To test if and how affect guides the selection of decision strategies, we conducted an online study (N = 166), where different mood states were induced through video clips. Results indicate that mood influenced the use of decision strategies. Negative mood, in particular anger, facilitated the use of non-compensatory strategies, whereas positive mood promoted compensatory decision rules. These results are in line with the idea that positive mood broadens the focus of attention and thus increases the use of compensatory decision strategies that take many pieces of information into account, whereas negative mood narrows the focus of attention and thus fosters non-compensatory strategies that rely on a selective use of information. The results further indicate that gaining a deeper theoretical understanding of the cognitive mechanisms that govern decision processes requires taking emotions into account.

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate

Neural and behavioral correlates of selective stopping: Evidence for a different strategy adoption.

PubMed

Sánchez-Carmona, Alberto J; Albert, Jacobo; Hinojosa, José A

2016-10-01

The present study examined the neural and behavioral correlates of selective stopping, a form of inhibition that has scarcely been investigated. The selectivity of the inhibitory process is needed when individuals have to deal with an environment filled with multiple stimuli, some of which require inhibition and some of which do not. The stimulus-selective stop-signal task has been used to explore this issue assuming that all participants interrupt their ongoing responses selectively to stop but not to ignore signals. However, recent behavioral evidence suggests that some individuals do not carry out the task as experimenters expect, since they seemed to interrupt their response non-selectively to both signals. In the present study, we detected and controlled the cognitive strategy adopted by participants (n=57) when they performed a stimulus-selective stop-signal task before comparing brain activation between conditions. In order to determine both the onset and the end of the response cancellation process underlying each strategy and to fully take advantage of the precise temporal resolution of event-related potentials, we used a mass univariate approach. Source localization techniques were also employed to estimate the neural underpinnings of the effects observed at the scalp level. Our results from scalp and source level analysis support the behavioral-based strategy classification. Specific effects were observed depending on the strategy adopted by participants. Thus, when contrasting successful stop versus ignore conditions, increased activation was only evident for subjects who were classified as using a strategy whereby the response interruption process was selective to stop trials. This increased activity was observed during the P3 time window in several left-lateralized brain regions, including middle and inferior frontal gyri, as well as parietal and insular cortices. By contrast, in those participants who used a strategy characterized by stopping non-selectively

Learning to choose: Cognitive aging and strategy selection learning in decision making.

PubMed

Mata, Rui; von Helversen, Bettina; Rieskamp, Jörg

2010-06-01

Decision makers often have to learn from experience. In these situations, people must use the available feedback to select the appropriate decision strategy. How does the ability to select decision strategies on the basis of experience change with age? We examined younger and older adults' strategy selection learning in a probabilistic inference task using a computational model of strategy selection learning. Older adults showed poorer decision performance compared with younger adults. In particular, older adults performed poorly in an environment favoring the use of a more cognitively demanding strategy. The results suggest that the impact of cognitive aging on strategy selection learning depends on the structure of the decision environment. (c) 2010 APA, all rights reserved

The Effects of Selection Strategies for Bivariate Loglinear Smoothing Models on NEAT Equating Functions

ERIC Educational Resources Information Center

Moses, Tim; Holland, Paul W.

2010-01-01

In this study, eight statistical strategies were evaluated for selecting the parameterizations of loglinear models for smoothing the bivariate test score distributions used in nonequivalent groups with anchor test (NEAT) equating. Four of the strategies were based on significance tests of chi-square statistics (Likelihood Ratio, Pearson,…

A strategy for position-selective epoxidation of polyprenols.

PubMed

Gnanadesikan, Vijay; Corey, E J

2008-06-25

An effective strategy has been developed for the efficient site-selective epoxidation of poylolefinic isoprenoid alcohols, based on the use of an internal control element for intramolecular reaction. The approach is illustrated by application to a series of polyisoprenoid alcohols (polyprenols) at substrate concentration of 0.5 mM. With polyprenol substrates having the hydroxyl function at one terminus, the internal epoxidation can be directed at the double bond of the polyprenol, which is either four or five away from the terminal hydroxyprenyl subunit.

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Bet hedging based cooperation can limit kin selection and form a basis for mutualism.

PubMed

Uitdehaag, Joost C M

2011-07-07

Mutualism is a mechanism of cooperation in which partners that differ help each other. As such, mutualism opposes mechanisms of kin selection and tag-based selection (for example the green beard mechanism), which are based on giving exclusive help to partners that are related or carry the same tag. In contrast to kin selection, which is a basis for parochialism and intergroup warfare, mutualism can therefore be regarded as a mechanism that drives peaceful coexistence between different groups and individuals. Here the competition between mutualism and kin (tag) selection is studied. In a model where kin selection and tag-based selection are dominant, mutualism is promoted by introducing environmental fluctuations. These fluctuations cause reduction in reproductive success by the mechanism of variance discount. The best strategy to counter variance discount is to share with agents who experience the most anticorrelated fluctuations, a strategy called bet hedging. In this way, bet hedging stimulates cooperation with the most unrelated partners, which is a basis for mutualism. Analytic results and simulations reveal that, if this effect is large enough, mutualistic strategies can dominate kin selective strategies. In addition, mutants of these mutualistic strategies that experience fluctuations that are more anticorrelated to their partner, can outcompete wild type, which can lead to the evolution of specialization. In this way, the evolutionary success of mutualistic strategies can be explained by bet hedging-based cooperation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Methods to Improve the Selection and Tailoring of Implementation Strategies

PubMed Central

Powell, Byron J.; Beidas, Rinad S.; Lewis, Cara C.; Aarons, Gregory A.; McMillen, J. Curtis; Proctor, Enola K.; Khinduka, Shanti K.; Mandell, David S.

2015-01-01

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research. PMID:26289563

Hippocampal SSTR4 somatostatin receptors control the selection of memory strategies.

PubMed

Gastambide, François; Viollet, Cécile; Lepousez, Gabriel; Epelbaum, Jacques; Guillou, Jean-Louis

2009-01-01

Somatostatin (SS14) has been implicated in various cognitive disorders, and converging evidence from animal studies suggests that SS14 neurons differentially regulate hippocampal- and striatal-dependent memory formation. Four SS14 receptor subtypes (SSTR1-4) are expressed in the hippocampus, but their respective roles in memory processes remain to be determined. In the present study, effects of selective SSTR1-4 agonists on memory formation were assessed in a water-maze task which can engage either hippocampus-dependent "place" and/or striatum-dependent "cue" memory formation. Mice received an intrahippocampal injection of one of each of the selective agonists and were then trained to locate an escape platform based on either distal cues (place memory) or a visible proximal cue (cue memory). Retention was tested 24 h later on probe trials aimed at identifying which memory strategy was preferentially retained. Both SS14 and the SSTR4 agonist (L-803,087) dramatically impaired place memory formation in a dose-dependent manner, whereas SSTR1 (L-797,591), SSTR2 (L-779,976), or SSTR3 (L-796,778) agonists did not yield any behavioral effects. However, unlike SS14, the SSTR4 agonist also dose-dependently enhanced cue-based memory formation. This effect was confirmed in another striatal-dependent memory task, the bar-pressing task, where L-803,087 improved memory of the instrumental response, whereas SS14 was once again ineffective. These data suggest that hippocampal SSTR4 are selectively involved in the selection of memory strategies by switching from the use of hippocampus-based multiple associations to the use of simple dorsal striatum-based behavioral responses. Possible neural mechanisms and functional implications are discussed.

Dosimetric advantages of a clinical daily adaptive plan selection strategy compared with a non-adaptive strategy in cervical cancer radiation therapy.

PubMed

van de Schoot, Agustinus J A J; de Boer, Peter; Visser, Jorrit; Stalpers, Lukas J A; Rasch, Coen R N; Bel, Arjan

2017-05-01

Radiation therapy (RT) using a daily plan selection adaptive strategy can be applied to account for interfraction organ motion while limiting organ at risk dose. The aim of this study was to quantify the dosimetric consequences of daily plan selection compared with non-adaptive RT in cervical cancer. Ten consecutive patients who received pelvic irradiation, planning CTs (full and empty bladder), weekly post-fraction CTs and pre-fraction CBCTs were included. Non-adaptive plans were generated based on the PTV defined using the full bladder planning CT. For the adaptive strategy, multiple PTVs were created based on both planning CTs by ITVs of the primary CTVs (i.e., GTV, cervix, corpus-uterus and upper part of the vagina) and corresponding library plans were generated. Daily CBCTs were rigidly aligned to the full bladder planning CT for plan selection. For daily plan recalculation, selected CTs based on initial similarity were deformably registered to CBCTs. Differences in daily target coverage (D 98%  > 95%) and in V 0.5Gy , V 1.5Gy , V 2Gy , D 50% and D 2% for rectum, bladder and bowel were assessed. Non-adaptive RT showed inadequate primary CTV coverage in 17% of the daily fractions. Plan selection compensated for anatomical changes and improved primary CTV coverage significantly (p < 0.01) to 98%. Compared with non-adaptive RT, plan selection decreased the fraction dose to rectum and bowel indicated by significant (p < 0.01) improvements for daily V 0.5Gy , V 1.5Gy , V 2Gy , D 50% and D 2% . However, daily plan selection significantly increased the bladder V 1.5Gy , V 2Gy , D 50% and D 2% . In cervical cancer RT, a non-adaptive strategy led to inadequate target coverage for individual patients. Daily plan selection corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions. The dose to bowel and rectum was decreased significantly when applying adaptive RT.

An efficient sampling strategy for selection of biobank samples using risk scores.

PubMed

Björk, Jonas; Malmqvist, Ebba; Rylander, Lars; Rignell-Hydbom, Anna

2017-07-01

The aim of this study was to suggest a new sample-selection strategy based on risk scores in case-control studies with biobank data. An ongoing Swedish case-control study on fetal exposure to endocrine disruptors and overweight in early childhood was used as the empirical example. Cases were defined as children with a body mass index (BMI) ⩾18 kg/m 2 ( n=545) at four years of age, and controls as children with a BMI of ⩽17 kg/m 2 ( n=4472 available). The risk of being overweight was modelled using logistic regression based on available covariates from the health examination and prior to selecting samples from the biobank. A risk score was estimated for each child and categorised as low (0-5%), medium (6-13%) or high (⩾14%) risk of being overweight. The final risk-score model, with smoking during pregnancy ( p=0.001), birth weight ( p<0.001), BMI of both parents ( p<0.001 for both), type of residence ( p=0.04) and economic situation ( p=0.12), yielded an area under the receiver operating characteristic curve of 67% ( n=3945 with complete data). The case group ( n=416) had the following risk-score profile: low (12%), medium (46%) and high risk (43%). Twice as many controls were selected from each risk group, with further matching on sex. Computer simulations showed that the proposed selection strategy with stratification on risk scores yielded consistent improvements in statistical precision. Using risk scores based on available survey or register data as a basis for sample selection may improve possibilities to study heterogeneity of exposure effects in biobank-based studies.

Oligonucleotide-based strategies to combat polyglutamine diseases

PubMed Central

Fiszer, Agnieszka; Krzyzosiak, Wlodzimierz J.

2014-01-01

Considerable advances have been recently made in understanding the molecular aspects of pathogenesis and in developing therapeutic approaches for polyglutamine (polyQ) diseases. Studies on pathogenic mechanisms have extended our knowledge of mutant protein toxicity, confirmed the toxicity of mutant transcript and identified other toxic RNA and protein entities. One very promising therapeutic strategy is targeting the causative gene expression with oligonucleotide (ON) based tools. This straightforward approach aimed at halting the early steps in the cascade of pathogenic events has been widely tested for Huntington's disease and spinocerebellar ataxia type 3. In this review, we gather information on the use of antisense oligonucleotides and RNA interference triggers for the experimental treatment of polyQ diseases in cellular and animal models. We present studies testing non-allele-selective and allele-selective gene silencing strategies. The latter include targeting SNP variants associated with mutations or targeting the pathologically expanded CAG repeat directly. We compare gene silencing effectors of various types in a number of aspects, including their design, efficiency in cell culture experiments and pre-clinical testing. We discuss advantages, current limitations and perspectives of various ON-based strategies used to treat polyQ diseases. PMID:24848018

Contract Source Selection: An Analysis of Lowest Price Technically Acceptable and Tradeoff Strategies

DTIC Science & Technology

2016-06-01

thorough market research, acquisition professionals must decide at an early stage which source selection strategy (lowest price technically...minimizing risk and ensuring best value for all stakeholders. On the basis of thorough market research, acquisition professionals must decide at an early...price-based, market -driven environment from requirements development through properly disposal. Source selection must be 8 made on a ‘best value

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

PubMed

Zhang, Jianhai; Chen, Ming; Zhao, Shaokai; Hu, Sanqing; Shi, Zhiguo; Cao, Yu

2016-09-22

Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels' weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the

Strategies for nest-site selection by king eiders

USGS Publications Warehouse

Bentzen, R.L.; Powell, A.N.; Suydam, R.S.

2009-01-01

Nest site selection is a critical component of reproduction and has presumably evolved in relation to predation, local resources, and microclimate. We investigated nest-site choice by king eiders (Somateria spectabilis) on the coastal plain of northern Alaska, USA, 2003-2005. We hypothesized that nest-site selection is driven by predator avoidance and that a variety of strategies including concealment, seclusion, and conspecific or inter-specific nest defense might lead to improved nesting success. We systematically searched wetland basins for king eider nests and measured habitat and social variables at nests (n = 212) and random locations (n = 493). King eiders made use of both secluded and concealed breeding strategies; logistic regression models revealed that females selected nests close to water, on islands, and in areas with high willow (Salix spp.) cover but did not select sites near conspecific or glaucous gull (Larus hyperboreus) nests. The most effective nest-placement strategy may vary depending on density and types of nest predators; seclusion is likely a mammalian-predator avoidance tactic whereas concealment may provide protection from avian predators. We recommend that managers in northern Alaska attempt to maintain wetland basins with islands and complex shorelines to provide potential nest sites in the vicinity of water. ?? The Wildlife Society.

On Voxel based Iso-Tumor Control Probabilty and Iso-Complication Maps for Selective Boosting and Selective Avoidance Intensity Modulated Radiotherapy.

PubMed

Kim, Yusung; Tomé, Wolfgang A

2008-01-01

Voxel based iso-Tumor Control Probability (TCP) maps and iso-Complication maps are proposed as a plan-review tool especially for functional image-guided intensity-modulated radiotherapy (IMRT) strategies such as selective boosting (dose painting) and conformal avoidance IMRT. The maps employ voxel-based phenomenological biological dose-response models for target volumes and normal organs. Two IMRT strategies for prostate cancer, namely conventional uniform IMRT delivering an EUD = 84 Gy (equivalent uniform dose) to the entire PTV and selective boosting delivering an EUD = 82 Gy to the entire PTV, are investigated, to illustrate the advantages of this approach over iso-dose maps. Conventional uniform IMRT did yield a more uniform isodose map to the entire PTV while selective boosting did result in a nonuniform isodose map. However, when employing voxel based iso-TCP maps selective boosting exhibited a more uniform tumor control probability map compared to what could be achieved using conventional uniform IMRT, which showed TCP cold spots in high-risk tumor subvolumes despite delivering a higher EUD to the entire PTV. Voxel based iso-Complication maps are presented for rectum and bladder, and their utilization for selective avoidance IMRT strategies are discussed. We believe as the need for functional image guided treatment planning grows, voxel based iso-TCP and iso-Complication maps will become an important tool to assess the integrity of such treatment plans.

On Voxel based Iso-Tumor Control Probabilty and Iso-Complication Maps for Selective Boosting and Selective Avoidance Intensity Modulated Radiotherapy

PubMed Central

Kim, Yusung; Tomé, Wolfgang A.

2010-01-01

Summary Voxel based iso-Tumor Control Probability (TCP) maps and iso-Complication maps are proposed as a plan-review tool especially for functional image-guided intensity-modulated radiotherapy (IMRT) strategies such as selective boosting (dose painting) and conformal avoidance IMRT. The maps employ voxel-based phenomenological biological dose-response models for target volumes and normal organs. Two IMRT strategies for prostate cancer, namely conventional uniform IMRT delivering an EUD = 84 Gy (equivalent uniform dose) to the entire PTV and selective boosting delivering an EUD = 82 Gy to the entire PTV, are investigated, to illustrate the advantages of this approach over iso-dose maps. Conventional uniform IMRT did yield a more uniform isodose map to the entire PTV while selective boosting did result in a nonuniform isodose map. However, when employing voxel based iso-TCP maps selective boosting exhibited a more uniform tumor control probability map compared to what could be achieved using conventional uniform IMRT, which showed TCP cold spots in high-risk tumor subvolumes despite delivering a higher EUD to the entire PTV. Voxel based iso-Complication maps are presented for rectum and bladder, and their utilization for selective avoidance IMRT strategies are discussed. We believe as the need for functional image guided treatment planning grows, voxel based iso-TCP and iso-Complication maps will become an important tool to assess the integrity of such treatment plans. PMID:21151734

Research on regularized mean-variance portfolio selection strategy with modified Roy safety-first principle.

PubMed

Atta Mills, Ebenezer Fiifi Emire; Yan, Dawen; Yu, Bo; Wei, Xinyuan

2016-01-01

We propose a consolidated risk measure based on variance and the safety-first principle in a mean-risk portfolio optimization framework. The safety-first principle to financial portfolio selection strategy is modified and improved. Our proposed models are subjected to norm regularization to seek near-optimal stable and sparse portfolios. We compare the cumulative wealth of our preferred proposed model to a benchmark, S&P 500 index for the same period. Our proposed portfolio strategies have better out-of-sample performance than the selected alternative portfolio rules in literature and control the downside risk of the portfolio returns.

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

PubMed Central

Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

PubMed

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

[Academic burnout and selection-optimization-compensation strategy in medical students].

PubMed

Chun, Kyung Hee; Park, Young Soon; Lee, Young Hwan; Kim, Seong Yong

2014-12-01

This study was conducted to examine the relationship between academic demand, academic burnout, and the selection-optimization-compensation (SOC) strategy in medical students. A total of 317 students at Yeungnam University, comprising 90 premedical course students, 114 medical course students, and 113 graduate course students, completed a survey that addressed the factors of academic burnout and the selection-optimization-compensation strategy. We analyzed variances of burnout and SOC strategy use by group, and stepwise multiple regression analysis was conducted. There were significant differences in emotional exhaustion and cynicism between groups and year in school. In the SOC strategy, there were no significant differences between groups except for elective selection. The second-year medical and graduate students experienced significantly greater exhaustion (p<0.001), and first-year premedical students experienced significantly higher cynicism (p<0.001). By multiple regression analysis, subfactors of academic burnout and emotional exhaustion were significantly affected by academic demand (p<0.001), and 46% of the variance was explained. Cynicism was significantly affected by elective selection (p<0.05), and inefficacy was significantly influenced by optimization (p<0.001). To improve adaptation, prescriptive strategies and preventive support should be implemented with regard to academic burnout in medical school. Longitudinal and qualitative studies on burnout must be conducted.

Neural substrates of similarity and rule-based strategies in judgment

PubMed Central

von Helversen, Bettina; Karlsson, Linnea; Rasch, Björn; Rieskamp, Jörg

2014-01-01

Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI), we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved. PMID:25360099

Coevolution of strategy-selection time scale and cooperation in spatial prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Rong, Zhihai; Wu, Zhi-Xi; Chen, Guanrong

2013-06-01

In this paper, we investigate a networked prisoner's dilemma game where individuals' strategy-selection time scale evolves based on their historical learning information. We show that the more times the current strategy of an individual is learnt by his neighbors, the longer time he will stick on the successful behavior by adaptively adjusting the lifetime of the adopted strategy. Through characterizing the extent of success of the individuals with normalized payoffs, we show that properly using the learned information can form a positive feedback mechanism between cooperative behavior and its lifetime, which can boost cooperation on square lattices and scale-free networks.

Situation selection is a particularly effective emotion regulation strategy for people who need help regulating their emotions.

PubMed

Webb, Thomas L; Lindquist, Kristen A; Jones, Katelyn; Avishai, Aya; Sheeran, Paschal

2018-03-01

Situation selection involves choosing situations based on their likely emotional impact and may be less cognitively taxing or challenging to implement compared to other strategies for regulating emotion, which require people to regulate their emotions "in the moment"; we thus predicted that individuals who chronically experience intense emotions or who are not particularly competent at employing other emotion regulation strategies would be especially likely to benefit from situation selection. Consistent with this idea, we found that the use of situation selection interacted with individual differences in emotional reactivity and competence at emotion regulation to predict emotional outcomes in both a correlational (Study 1; N = 301) and an experimental field study (Study 2; N = 125). Taken together, the findings suggest that situation selection is an effective strategy for regulating emotions, especially for individuals who otherwise struggle to do so.

Health information technology vendor selection strategies and total factor productivity.

PubMed

Ford, Eric W; Huerta, Timothy R; Menachemi, Nir; Thompson, Mark A; Yu, Feliciano

2013-01-01

The aim of this study was to compare health information technology (HIT) adoption strategies' relative performance on hospital-level productivity measures. The American Hospital Association's Annual Survey and Healthcare Information and Management Systems Society Analytics for fiscal years 2002 through 2007 were used for this study. A two-stage approach is employed. First, a Malmquist model is specified to calculate hospital-level productivity measures. A logistic regression model is then estimated to compare the three HIT adoption strategies' relative performance on the newly constructed productivity measures. The HIT vendor selection strategy impacts the amount of technological change required of an organization but does not appear to have either a positive or adverse impact on technical efficiency or total factor productivity. The higher levels in technological change experienced by hospitals using the best of breed and best of suite HIT vendor selection strategies may have a more direct impact on the organization early on in the process. However, these gains did not appear to translate into either increased technical efficiency or total factor productivity during the period studied. Over a longer period, one HIT vendor selection strategy may yet prove to be more effective at improving efficiency and productivity.

Gender, Strategy Selection, and Discussion Satisfaction in Interpersonal Conflict.

ERIC Educational Resources Information Center

Papa, Michael J.; Natalle, Elizabeth J.

1989-01-01

Examines gender-related similarities and differences regarding conflict strategies and satisfaction with conflict interaction in a corporate setting. Reports that gender significantly affected the selection of influence strategies: male-male dyads used assertiveness and reason consistently, while female-female dyads shifted from high levels of…

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum

PubMed Central

Ito, Makoto; Doya, Kenji

2015-01-01

Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the “win-stay, lose-switch” strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum. PMID:26529522

Contract Source Selection: An Analysis of Lowest Price Technically Acceptable and Tradeoff Strategies

DTIC Science & Technology

2016-06-15

selection strategy is key to minimizing risk and ensuring best value for all stakeholders. On the basis of thorough market research , acquisition...administrative lead-time, Contractor Performance Assessment Reporting System ratings, and earned value management assessments) and source selection strategy ...Postgraduate School A. PURPOSE This research analyzes LPTA and tradeoff source selection strategies and contract outcomes to determine if a relationship

Prevention of surgical resident attrition by a novel selection strategy.

PubMed

Kelz, Rachel R; Mullen, James L; Kaiser, Larry R; Pray, Lori A; Shea, Gregory P; Drebin, Jeff A; Wirtalla, Chris J; Morris, Jon B

2010-09-01

We modified the resident selection strategy in an attempt to reduce resident attrition (RA). Despite implementation of the Accreditation Council for Graduate Medical Education work rules, lifestyle and generational priorities have fostered a persistent and relatively high attrition rate for surgical trainees. An independent external review of residents who left the training program and a detailed analysis of the resident selection strategy were performed by an organizational management expert. Modifications implemented in 2005 (the intervention) included standardization of the screening and interview format. Applicants were required to submit a 500 words essay related to stress management, organizational skills, future aspirations, and prioritization abilities. Their responses formed the basis of an extended, personalized, and structured interview script. Candidate characteristics and RA were compared for the 5 years before and after the intervention, using Fisher exact test or chi2. Age, sex, birthplace, medical school ranking, step 1 score, and American Board of Surgey In-Training Examination performance were not significantly different between the selection strategy groups. Risk factors for RA included ABSITE performance and gender. Resident performance and subsequent RA were significantly affected by the resident selection strategy. RA was dramatically reduced following the intervention. A custom designed process to identify candidates most likely to succeed substantially improved resident retention in a demanding academic training program.

Selection strategies for newly registered blood donors in European countries

PubMed Central

Lieshout-Krikke, Ryanne W.; Domanovic, Dragoslav; de Kort, Wim; Mayr, Wolfgang; Liumbruno, Giancarlo M.; Pupella, Simonetta; Kurz, Johann; Knutson, Folke; MacLennan, Sheila; Folléa, Gilles

2017-01-01

Background Two selection strategies for newly-registered blood donors are available: a single-visit selection called the standard selection procedure (SSP), and a two-stage selection named predonation and donation screening (PDS). This study reviews the selection strategies for newly-registered donors currently applied in European countries. Material and methods We collected data on donor selection procedures, blood donation, laboratory screening and HIV, HCV and HBV positive donors/donations from 2010 to 2013 in 30 European countries by using questionnaires. We grouped the countries according to the applied selection strategy, and for each country, we calculated the 4-year prevalence of confirmed positive results indicating the presence of overall and recent HIV, HCV and HBV infections among first-time and repeat donations and among newly-registered donors. Results Most of the 24 countries (80%) apply the SSP strategy for selection of newly-registered donors. Twenty-two countries (73.3%) employ a nucleic acid amplification testing in addition to the mandatory serological screening. The survey confirms a higher overall prevalence of HIV, HCV and HBV infections among first-time donations and newly-registered donors than among repeat donations. In contrast, the prevalence of recently acquired HIV and HCV infections was lower among first-time donations and newly-registered donors than among repeat donations, but higher for recent HBV infections (6.7/105 vs 2.6/105 in the SSP setting and 4.3/105 vs 0.5/105 in one country using PDS). The relatively low numbers of infected donors selected by PDS impeded accurate assessment of the prevalence of recent infections in first-time donations. Discussion The data from European countries provide inconclusive evidence that applying PDS reduces the risk of donations being made in the diagnostic window of first-time donors. The impact of PDS on the risk of window-period donations and blood donor management needs further

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

NASA Technical Reports Server (NTRS)

Sowers, T. Shane; Kopasakis, George; Simon, Donald L.

2008-01-01

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

NASA Technical Reports Server (NTRS)

Sowers, T. Shane; Kopasakis, George; Simon, Donald L.

2008-01-01

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

The Selective Attention Strategy as a Time-Dependent Phenomenon.

ERIC Educational Resources Information Center

Lapan, Richard; Reynolds, Ralph E.

1994-01-01

Differences in how more and less successful readers use selective attention, and whether these differences influence what is learned and recalled were studied with 45 college students. Results reveal different reading patterns for the two groups. The discussion focuses on aspects of the selective attention strategy. (SLD)

Metacognition for strategy selection during arithmetic problem-solving in young and older adults.

PubMed

Geurten, Marie; Lemaire, Patrick

2018-04-19

We examined participants' strategy choices and metacognitive judgments during arithmetic problem-solving. Metacognitive judgments were collected either prospectively or retrospectively. We tested whether metacognitive judgments are related to strategy choices on the current problems and on the immediately following problems, and age-related differences in relations between metacognition and strategy choices. Data showed that both young and older adults were able to make accurate retrospective, but not prospective, judgments. Moreover, the accuracy of retrospective judgments was comparable in young and older adults when participants had to select and execute the better strategy. Metacognitive accuracy was even higher in older adults when participants had to only select the better strategy. Finally, low-confidence judgments on current items were more frequently followed by better strategy selection on immediately succeeding items than high-confidence judgments in both young and older adults. Implications of these findings to further our understanding of age-related differences and similarities in adults' metacognitive monitoring and metacognitive regulation for strategy selection in the context of arithmetic problem solving are discussed.

Impact of selection strategies on representation of underserved populations and intention to practise: international findings.

PubMed

Larkins, Sarah; Michielsen, Kristien; Iputo, Jehu; Elsanousi, Salwa; Mammen, Marykutty; Graves, Lisa; Willems, Sara; Cristobal, Fortunato L; Samson, Rex; Ellaway, Rachel; Ross, Simone; Johnston, Karen; Derese, Anselme; Neusy, André-Jacques

2015-01-01

Socially accountable medical schools aim to reduce health inequalities by training workforces responsive to the priority health needs of underserved communities. One key strategy involves recruiting students from underserved and unequally represented communities on the basis that they may be more likely to return and address local health priorities. This study describes the impacts of different selection strategies of medical schools that aspire to social accountability on the presence of students from underserved communities in their medical education programmes and on student practice intentions. A cross-sectional questionnaire was administered to students starting medical education in five institutions with a social accountability mandate in five different countries. The questionnaire assessed students' background characteristics, rurality of background, and practice intentions (location, discipline of practice and population to be served). The results were compared with the characteristics of students entering medical education in schools with standard selection procedures, and with publicly available socio-economic data. The selection processes of all five schools included strategies that extended beyond the assessment of academic achievement. Four distinct strategies were identified: the quota system; selection based on personal attributes; community involvement, and school marketing strategies. Questionnaire data from 944 students showed that students at the five schools were more likely to be of non-urban origin, of lower socio-economic status and to come from underserved groups. A total of 407 of 810 (50.2%) students indicated an intention to practise in a non-urban area after graduation and the likelihood of this increased with increasing rurality of primary schooling (p = 0.000). Those of rural origin were statistically less likely to express an intention to work abroad (p = 0.003). Selection strategies to ensure that members of underserved communities

Adaptive Strategy Selection in Decision Making.

DTIC Science & Technology

1986-07-31

information processing capabilities of a decision maker, given any " reasonable " time limit for making the decision. If use of a more normative rule...DECISION MAKING JOHN W. PAYNE DTIC DUKE UNIVERSITY L.CT E AUG 13 JAMES R. BETTMAN DUKE. UNIVERSITY ERIC J. JOHNSON CARNEGIE-MELLON UNIVERSITY...REPORT & PERIOD COVERED ADAPTIVE STRATEGY SELECTION IN DECISION MAKING Research 6. PERFORMING ORO. REPORT NUMSER 7. AUTNORfe) e. CONTRACT ON GRANT

Space Operations Center orbit altitude selection strategy

NASA Technical Reports Server (NTRS)

Indrikis, J.; Myers, H. L.

1982-01-01

The strategy for the operational altitude selection has to respond to the Space Operation Center's (SOC) maintenance requirements and the logistics demands of the missions to be supported by the SOC. Three orbit strategies are developed: two are constant altitude, and one variable altitude. In order to minimize the effect of atmospheric uncertainty the dynamic altitude method is recommended. In this approach the SOC will operate at the optimum altitude for the prevailing atmospheric conditions and logistics model, provided that mission safety constraints are not violated. Over a typical solar activity cycle this method produces significant savings in the overall logistics cost.

A strategy for selecting data mining techniques in metabolomics.

PubMed

Banimustafa, Ahmed Hmaidan; Hardy, Nigel W

2012-01-01

There is a general agreement that the development of metabolomics depends not only on advances in chemical analysis techniques but also on advances in computing and data analysis methods. Metabolomics data usually requires intensive pre-processing, analysis, and mining procedures. Selecting and applying such procedures requires attention to issues including justification, traceability, and reproducibility. We describe a strategy for selecting data mining techniques which takes into consideration the goals of data mining techniques on the one hand, and the goals of metabolomics investigations and the nature of the data on the other. The strategy aims to ensure the validity and soundness of results and promote the achievement of the investigation goals.

Tools for Identifying and Prioritizing Evidence-Based Obesity Prevention Strategies, Colorado

PubMed Central

Juhl, Ashley L.; Gujral, Indira B.; Hoaglin-Wagner, Andrea L.; Gabella, Barbara A.; McDermott, Kristin M.

2013-01-01

Colorado’s adult obesity rate has more than doubled since 1995, prompting its Department of Public Health and Environment to list obesity as its top prevention priority. To initiate comprehensive and effective action, the department used a well-known evidence-based public health framework developed by Brownson and others. This article describes the tools and process developed to conduct 2 of the 7 stages in this framework that challenge public health organizations: reviewing the literature and prioritizing effective strategies from that literature. Forty-five department staff participated in an intensive literature review training to identify physical activity and nutrition strategies that effectively address obesity and worked with external stakeholders to prioritize strategies for the state. Divided into 8 multidisciplinary teams organized by the setting where public health could exert leverage, they scanned the scientific literature to identify potential strategies to implement. These teams were trained to use standardized tools to critique findings, systematically abstract key information, and classify the evidence level for each of 58 identified strategies. Next, departmental subject matter experts and representatives from local public health and nonprofit health agencies selected and applied prioritization criteria to rank the 58 strategies. A team charter, group facilitation tools, and 2 web-based surveys were used in the prioritization stage. This process offered the staff a shared experience to gain hands-on practice completing literature reviews and selecting evidence-based strategies, thereby enhancing Colorado’s obesity prevention efforts and improving public health capacity. Practitioners can use these tools and methodology to replicate this process for other health priorities. PMID:23806801

Rethinking volitional control over task choice in multitask environments: use of a stimulus set selection strategy in voluntary task switching.

PubMed

Arrington, Catherine M; Weaver, Starla M

2015-01-01

Under conditions of volitional control in multitask environments, subjects may engage in a variety of strategies to guide task selection. The current research examines whether subjects may sometimes use a top-down control strategy of selecting a task-irrelevant stimulus dimension, such as location, to guide task selection. We term this approach a stimulus set selection strategy. Using a voluntary task switching procedure, subjects voluntarily switched between categorizing letter and number stimuli that appeared in two, four, or eight possible target locations. Effects of stimulus availability, manipulated by varying the stimulus onset asynchrony between the two target stimuli, and location repetition were analysed to assess the use of a stimulus set selection strategy. Considered across position condition, Experiment 1 showed effects of both stimulus availability and location repetition on task choice suggesting that only in the 2-position condition, where selection based on location always results in a target at the selected location, subjects may have been using a stimulus set selection strategy on some trials. Experiment 2 replicated and extended these findings in a visually more cluttered environment. These results indicate that, contrary to current models of task selection in voluntary task switching, the top-down control of task selection may occur in the absence of the formation of an intention to perform a particular task.

Green supplier selection: a new genetic/immune strategy with industrial application

NASA Astrophysics Data System (ADS)

Kumar, Amit; Jain, Vipul; Kumar, Sameer; Chandra, Charu

2016-10-01

With the onset of the 'climate change movement', organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers' preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.

A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection

PubMed Central

Sale, Mark; Sherer, Eric A

2015-01-01

The current algorithm for selecting a population pharmacokinetic/pharmacodynamic model is based on the well-established forward addition/backward elimination method. A central strength of this approach is the opportunity for a modeller to continuously examine the data and postulate new hypotheses to explain observed biases. This algorithm has served the modelling community well, but the model selection process has essentially remained unchanged for the last 30 years. During this time, more robust approaches to model selection have been made feasible by new technology and dramatic increases in computation speed. We review these methods, with emphasis on genetic algorithm approaches and discuss the role these methods may play in population pharmacokinetic/pharmacodynamic model selection. PMID:23772792

The Effect of Vocabulary Self-Selection Strategy and Input Enhancement Strategy on the Vocabulary Knowledge of Iranian EFL Learners

ERIC Educational Resources Information Center

Masoudi, Golfam

2017-01-01

The present study was designed to investigate empirically the effect of Vocabulary Self-Selection strategy and Input Enhancement strategy on the vocabulary knowledge of Iranian EFL Learners. After taking a diagnostic pretest, both experimental groups enrolled in two classes. Learners who practiced Vocabulary Self-Selection were allowed to…

Strategies for crew selection for long duration missions

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.; Holland, Albert W.; Santy, Patricia A.; Rose, Robert M.; Mcfadden, Terry J.

1990-01-01

Issues surrounding psychological reactions to long duration spaceflight are discussed with respect to the definition of criteria for selecting crewmembers for such expeditions. Two broad dimensions of personality and behavior are defined - Instrumentality including achievement orientation, leadership, and ability to perform under pressure and Expressivity encompassing interpersonal sensitivity and competence. A strategy for validating techniques to select in candidates with the optimum psychological profile to perform successfully on long duration missions is described.

Task-selective memory effects for successfully implemented encoding strategies.

PubMed

Leshikar, Eric D; Duarte, Audrey; Hertzog, Christopher

2012-01-01

Previous behavioral evidence suggests that instructed strategy use benefits associative memory formation in paired associate tasks. Two such effective encoding strategies--visual imagery and sentence generation--facilitate memory through the production of different types of mediators (e.g., mental images and sentences). Neuroimaging evidence suggests that regions of the brain support memory reflecting the mental operations engaged at the time of study. That work, however, has not taken into account self-reported encoding task success (i.e., whether participants successfully generated a mediator). It is unknown, therefore, whether task-selective memory effects specific to each strategy might be found when encoding strategies are successfully implemented. In this experiment, participants studied pairs of abstract nouns under either visual imagery or sentence generation encoding instructions. At the time of study, participants reported their success at generating a mediator. Outside of the scanner, participants further reported the quality of the generated mediator (e.g., images, sentences) for each word pair. We observed task-selective memory effects for visual imagery in the left middle occipital gyrus, the left precuneus, and the lingual gyrus. No such task-selective effects were observed for sentence generation. Intriguingly, activity at the time of study in the left precuneus was modulated by the self-reported quality (vividness) of the generated mental images with greater activity for trials given higher ratings of quality. These data suggest that regions of the brain support memory in accord with the encoding operations engaged at the time of study.

Strategy Selection for Cognitive Skill Acquisition Depends on Task Demands and Working Memory Capacity

ERIC Educational Resources Information Center

Hinze, Scott R.; Bunting, Michael F; Pellegrino, James W.

2009-01-01

The involvement of working memory capacity (WMC) in ruled-based cognitive skill acquisition is well-established, but the duration of its involvement and its role in learning strategy selection are less certain. Participants (N=610) learned four logic rules, their corresponding symbols, or logic gates, and the appropriate input-output combinations…

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes.

PubMed

Marzaro, Giovanni; Ferrarese, Alessandro; Chilin, Adriana

2014-08-01

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.

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

PubMed

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.

Secure relay selection based on learning with negative externality in wireless networks

NASA Astrophysics Data System (ADS)

Zhao, Caidan; Xiao, Liang; Kang, Shan; Chen, Guiquan; Li, Yunzhou; Huang, Lianfen

2013-12-01

In this paper, we formulate relay selection into a Chinese restaurant game. A secure relay selection strategy is proposed for a wireless network, where multiple source nodes send messages to their destination nodes via several relay nodes, which have different processing and transmission capabilities as well as security properties. The relay selection utilizes a learning-based algorithm for the source nodes to reach their best responses in the Chinese restaurant game. In particular, the relay selection takes into account the negative externality of relay sharing among the source nodes, which learn the capabilities and security properties of relay nodes according to the current signals and the signal history. Simulation results show that this strategy improves the user utility and the overall security performance in wireless networks. In addition, the relay strategy is robust against the signal errors and deviations of some user from the desired actions.

Selective catalyst reduction light-off strategy

DOEpatents

Gonze, Eugene V [Pinckney, MI

2011-10-18

An emissions control system includes a temperature determination module and an emissions control module. The temperature determination module determines a first temperature of a heater element of a diesel particulate filter (DPF) assembly in an exhaust system and determines a second temperature of a catalyst of the DPF assembly. The emissions control module selectively activates the heater element, selectively initiates a predefined combustion process in an engine based upon the first temperature, and selectively starts a reductant injection process based upon the second temperature.

Empirical study of the dependence of the results of multivariable flexible survival analyses on model selection strategy.

PubMed

Binquet, C; Abrahamowicz, M; Mahboubi, A; Jooste, V; Faivre, J; Bonithon-Kopp, C; Quantin, C

2008-12-30

Flexible survival models, which avoid assumptions about hazards proportionality (PH) or linearity of continuous covariates effects, bring the issues of model selection to a new level of complexity. Each 'candidate covariate' requires inter-dependent decisions regarding (i) its inclusion in the model, and representation of its effects on the log hazard as (ii) either constant over time or time-dependent (TD) and, for continuous covariates, (iii) either loglinear or non-loglinear (NL). Moreover, 'optimal' decisions for one covariate depend on the decisions regarding others. Thus, some efficient model-building strategy is necessary.We carried out an empirical study of the impact of the model selection strategy on the estimates obtained in flexible multivariable survival analyses of prognostic factors for mortality in 273 gastric cancer patients. We used 10 different strategies to select alternative multivariable parametric as well as spline-based models, allowing flexible modeling of non-parametric (TD and/or NL) effects. We employed 5-fold cross-validation to compare the predictive ability of alternative models.All flexible models indicated significant non-linearity and changes over time in the effect of age at diagnosis. Conventional 'parametric' models suggested the lack of period effect, whereas more flexible strategies indicated a significant NL effect. Cross-validation confirmed that flexible models predicted better mortality. The resulting differences in the 'final model' selected by various strategies had also impact on the risk prediction for individual subjects.Overall, our analyses underline (a) the importance of accounting for significant non-parametric effects of covariates and (b) the need for developing accurate model selection strategies for flexible survival analyses. Copyright 2008 John Wiley & Sons, Ltd.

Competitive seeds-selection in complex networks

NASA Astrophysics Data System (ADS)

Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan

2017-02-01

This paper investigates a competitive diffusion model where two competitors simultaneously select a set of nodes (seeds) in the network to influence. We focus on the problem of how to select these seeds such that, when the diffusion process terminates, a competitor can obtain more supports than its opponent. Instead of studying this problem in the game-theoretic framework as in the existing work, in this paper we design several heuristic seed-selection strategies inspired by commonly used centrality measures-Betweenness Centrality (BC), Closeness Centrality (CC), Degree Centrality (DC), Eigenvector Centrality (EC), and K-shell Centrality (KS). We mainly compare three centrality-based strategies, which have better performances in competing with the random selection strategy, through simulations on both real and artificial networks. Even though network structure varies across different networks, we find certain common trend appearing in all of these networks. Roughly speaking, BC-based strategy and DC-based strategy are better than CC-based strategy. Moreover, if a competitor adopts CC-based strategy, then BC-based strategy is a better strategy than DC-based strategy for his opponent, and the superiority of BC-based strategy decreases as the heterogeneity of the network decreases.

Selective testing strategies for diagnosing group A streptococcal infection in children with pharyngitis: a systematic review and prospective multicentre external validation study

PubMed Central

Cohen, Jérémie F.; Cohen, Robert; Levy, Corinne; Thollot, Franck; Benani, Mohamed; Bidet, Philippe; Chalumeau, Martin

2015-01-01

Background: Several clinical prediction rules for diagnosing group A streptococcal infection in children with pharyngitis are available. We aimed to compare the diagnostic accuracy of rules-based selective testing strategies in a prospective cohort of children with pharyngitis. Methods: We identified clinical prediction rules through a systematic search of MEDLINE and Embase (1975–2014), which we then validated in a prospective cohort involving French children who presented with pharyngitis during a 1-year period (2010–2011). We diagnosed infection with group A streptococcus using two throat swabs: one obtained for a rapid antigen detection test (StreptAtest, Dectrapharm) and one obtained for culture (reference standard). We validated rules-based selective testing strategies as follows: low risk of group A streptococcal infection, no further testing or antibiotic therapy needed; intermediate risk of infection, rapid antigen detection for all patients and antibiotic therapy for those with a positive test result; and high risk of infection, empiric antibiotic treatment. Results: We identified 8 clinical prediction rules, 6 of which could be prospectively validated. Sensitivity and specificity of rules-based selective testing strategies ranged from 66% (95% confidence interval [CI] 61–72) to 94% (95% CI 92–97) and from 40% (95% CI 35–45) to 88% (95% CI 85–91), respectively. Use of rapid antigen detection testing following the clinical prediction rule ranged from 24% (95% CI 21–27) to 86% (95% CI 84–89). None of the rules-based selective testing strategies achieved our diagnostic accuracy target (sensitivity and specificity > 85%). Interpretation: Rules-based selective testing strategies did not show sufficient diagnostic accuracy in this study population. The relevance of clinical prediction rules for determining which children with pharyngitis should undergo a rapid antigen detection test remains questionable. PMID:25487666

An Optimization Model For Strategy Decision Support to Select Kind of CPO’s Ship

NASA Astrophysics Data System (ADS)

Suaibah Nst, Siti; Nababan, Esther; Mawengkang, Herman

2018-01-01

The selection of marine transport for the distribution of crude palm oil (CPO) is one of strategy that can be considered in reducing cost of transport. The cost of CPO’s transport from one area to CPO’s factory located at the port of destination may affect the level of CPO’s prices and the number of demands. In order to maintain the availability of CPO a strategy is required to minimize the cost of transporting. In this study, the strategy used to select kind of charter ships as barge or chemical tanker. This study aims to determine an optimization model for strategy decision support in selecting kind of CPO’s ship by minimizing costs of transport. The select of ship was done randomly, so that two-stage stochastic programming model was used to select the kind of ship. Model can help decision makers to select either barge or chemical tanker to distribute CPO.

Mechanical effort predicts the selection of ankle over hip strategies in nonstepping postural responses

PubMed Central

Jonkers, Ilse; De Schutter, Joris; De Groote, Friedl

2016-01-01

Experimental studies have shown that a continuum of ankle and hip strategies is used to restore posture following an external perturbation. Postural responses can be modeled by feedback control with feedback gains that optimize a specific objective. On the one hand, feedback gains that minimize effort have been used to predict muscle activity during perturbed standing. On the other hand, hip and ankle strategies have been predicted by minimizing postural instability and deviation from upright posture. It remains unclear, however, whether and how effort minimization influences the selection of a specific postural response. We hypothesize that the relative importance of minimizing mechanical work vs. postural instability influences the strategy used to restore upright posture. This hypothesis was investigated based on experiments and predictive simulations of the postural response following a backward support surface translation. Peak hip flexion angle was significantly correlated with three experimentally determined measures of effort, i.e., mechanical work, mean muscle activity and metabolic energy. Furthermore, a continuum of ankle and hip strategies was predicted in simulation when changing the relative importance of minimizing mechanical work and postural instability, with increased weighting of mechanical work resulting in an ankle strategy. In conclusion, the combination of experimental measurements and predictive simulations of the postural response to a backward support surface translation showed that the trade-off between effort and postural instability minimization can explain the selection of a specific postural response in the continuum of potential ankle and hip strategies. PMID:27489362

How to select the correct education strategy: when not to go online.

PubMed

Klingbeil, Carol G; Johnson, Norah L; Totka, Joan P; Doyle, Lynn

2009-01-01

Screening for intimate partner violence is an important injury prevention strategy. Nurses who develop staff education, to promote screening, need to select a method that is sensitive to learners. Online learning, although convenient, is not well suited to sensitive topics such as screening for intimate partner violence. The purpose of this article is to describe a curriculum for intimate partner violence screening based on self-efficacy theory, which includes a hospital-produced video, a role play, and a discussion.

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

PubMed Central

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

A Generalization Strategy for Discrete Area Feature by Using Stroke Grouping and Polarization Transportation Selection

NASA Astrophysics Data System (ADS)

Wang, Xiao; Burghardt, Dirk

2018-05-01

This paper presents a new strategy for the generalization of discrete area features by using stroke grouping method and polarization transportation selection. The mentioned stroke is constructed on derive of the refined proximity graph of area features, and the refinement is under the control of four constraints to meet different grouping requirements. The area features which belong to the same stroke are detected into the same group. The stroke-based strategy decomposes the generalization process into two sub-processes by judging whether the area features related to strokes or not. For the area features which belong to the same one stroke, they normally present a linear like pat-tern, and in order to preserve this kind of pattern, typification is chosen as the operator to implement the generalization work. For the remaining area features which are not related by strokes, they are still distributed randomly and discretely, and the selection is chosen to conduct the generalization operation. For the purpose of retaining their original distribution characteristic, a Polarization Transportation (PT) method is introduced to implement the selection operation. Buildings and lakes are selected as the representatives of artificial area feature and natural area feature respectively to take the experiments. The generalized results indicate that by adopting this proposed strategy, the original distribution characteristics of building and lake data can be preserved, and the visual perception is pre-served as before.

Monitoring injury reporting in selected Australian media: a potential advocacy strategy?

PubMed

Stoneham, Melissa; Boss, Andrea; Daube, Mike

2013-04-01

This review of injury articles describes how selected primary print media sources in Australia report injury events and explores how this may impact on public perception of the injury risk and the opportunities it may present to health professionals. Media articles specific to injury, compiled by the Public Health Advocacy Institute of Western Australia (PHAIWA) through their MediaWatch service during 2011, were collated and analysed. Articles were gathered from The West Australian, The Australian and The Sunday Times newspapers and ABC Online. Each article was categorised into injury topics and target groups, and preventive strategies were identified. Of the 546 articles that contained injury as a key word, 424 articles were used for the present study. The majority of articles related to community-based injuries (65%) and the most frequent reported injury was violence and assault. The results also indicate that although there is regular media reporting on injury issues, only one-fifth of reports discuss possible preventive measures. Selected Australian newspapers and the ABC Online are important and low-cost sources of injury-related information for the general public and can impact how the public perceives injury. It is important for public health professionals to embrace media advocacy strategies to assist in influencing and setting local public policy. So what? Public attitudes and understanding of issues are influenced by media coverage. Media monitoring is one tool to track what media sources are reporting about public health issues, the industry and stakeholders. Influencing the quantity and quality of media coverage is critical to advancing healthy public policy, particularly when advocating for prevention strategies to be reported and acted upon. Advocacy is an important health promotion strategy; it is therefore important for health professionals to understand media advocacy and position public health issues as societal issues with policy solutions.

Model For Marketing Strategy Decision Based On Multicriteria Decicion Making: A Case Study In Batik Madura Industry

NASA Astrophysics Data System (ADS)

Anna, I. D.; Cahyadi, I.; Yakin, A.

2018-01-01

Selection of marketing strategy is a prominent competitive advantage for small and medium enterprises business development. The selection process is is a multiple criteria decision-making problem, which includes evaluation of various attributes or criteria in a process of strategy formulation. The objective of this paper is to develop a model for the selection of a marketing strategy in Batik Madura industry. The current study proposes an integrated approach based on analytic network process (ANP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine the best strategy for Batik Madura marketing problems. Based on the results of group decision-making technique, this study selected fourteen criteria, including consistency, cost, trend following, customer loyalty, business volume, uniqueness manpower, customer numbers, promotion, branding, bussiness network, outlet location, credibility and the inovation as Batik Madura marketing strategy evaluation criteria. A survey questionnaire developed from literature review was distributed to a sample frame of Batik Madura SMEs in Pamekasan. In the decision procedure step, expert evaluators were asked to establish the decision matrix by comparing the marketing strategy alternatives under each of the individual criteria. Then, considerations obtained from ANP and TOPSIS methods were applied to build the specific criteria constraints and range of the launch strategy in the model. The model in this study demonstrates that, under current business situation, Straight-focus marketing strategy is the best marketing strategy for Batik Madura SMEs in Pamekasan.

Task-Selective Memory Effects for Successfully Implemented Encoding Strategies

PubMed Central

Leshikar, Eric D.; Duarte, Audrey; Hertzog, Christopher

2012-01-01

Previous behavioral evidence suggests that instructed strategy use benefits associative memory formation in paired associate tasks. Two such effective encoding strategies–visual imagery and sentence generation–facilitate memory through the production of different types of mediators (e.g., mental images and sentences). Neuroimaging evidence suggests that regions of the brain support memory reflecting the mental operations engaged at the time of study. That work, however, has not taken into account self-reported encoding task success (i.e., whether participants successfully generated a mediator). It is unknown, therefore, whether task-selective memory effects specific to each strategy might be found when encoding strategies are successfully implemented. In this experiment, participants studied pairs of abstract nouns under either visual imagery or sentence generation encoding instructions. At the time of study, participants reported their success at generating a mediator. Outside of the scanner, participants further reported the quality of the generated mediator (e.g., images, sentences) for each word pair. We observed task-selective memory effects for visual imagery in the left middle occipital gyrus, the left precuneus, and the lingual gyrus. No such task-selective effects were observed for sentence generation. Intriguingly, activity at the time of study in the left precuneus was modulated by the self-reported quality (vividness) of the generated mental images with greater activity for trials given higher ratings of quality. These data suggest that regions of the brain support memory in accord with the encoding operations engaged at the time of study. PMID:22693593

A novel strategy for selection of allosteric ribozymes yields RiboReporter™ sensors for caffeine and aspartame

PubMed Central

Ferguson, Alicia; Boomer, Ryan M.; Kurz, Markus; Keene, Sara C.; Diener, John L.; Keefe, Anthony D.; Wilson, Charles; Cload, Sharon T.

2004-01-01

We have utilized in vitro selection technology to develop allosteric ribozyme sensors that are specific for the small molecule analytes caffeine or aspartame. Caffeine- or aspartame-responsive ribozymes were converted into fluorescence-based RiboReporter™ sensor systems that were able to detect caffeine or aspartame in solution over a concentration range from 0.5 to 5 mM. With read-times as short as 5 min, these caffeine- or aspartame-dependent ribozymes function as highly specific and facile molecular sensors. Interestingly, successful isolation of allosteric ribozymes for the analytes described here was enabled by a novel selection strategy that incorporated elements of both modular design and activity-based selection methods typically used for generation of catalytic nucleic acids. PMID:15026535

Identification of a Novel and Selective Series of Itk Inhibitors via a Template-Hopping Strategy

PubMed Central

2013-01-01

Inhibition of Itk potentially constitutes a novel, nonsteroidal treatment for asthma and other T-cell mediated diseases. In-house kinase cross-screening resulted in the identification of an aminopyrazole-based series of Itk inhibitors. Initial work on this series highlighted selectivity issues with several other kinases, particularly AurA and AurB. A template-hopping strategy was used to identify a series of aminobenzothiazole Itk inhibitors, which utilized an inherently more selective hinge binding motif. Crystallography and modeling were used to rationalize the observed selectivity. Initial exploration of the SAR around this series identified potent Itk inhibitors in both enzyme and cellular assays. PMID:24900590

Comparison of Coping Strategies of Student Teachers Based on Their Subject of Specialisation

ERIC Educational Resources Information Center

P. M., Majitha; Sajan, K. S.

2015-01-01

The purpose of the study was to find out the difference in the mean scores of coping strategies of student teachers based on their subject of specialisation. A total of 558 student teachers were selected for the study. Results indicate that there exists a significant difference in the mean scores of Coping Strategies of student teachers of Arts…

Strategy for selecting Mars Pathfinder landing sites

NASA Technical Reports Server (NTRS)

Greeley, Ronald; Kuzmin, Ruslin O.

1994-01-01

A strategy for Pathfinder site selection must be developed that is fundamentally different from most previous considerations. At least two approaches can be identified. In one approach, the objective is to select a site representing a key geologic unit on Mars, i.e., a unit that is widespread, easily recognized, and used frequently as a datum in various investigations. The second approach is to select a site that potentially affords access to a wide variety of rock types. Because rover range is limited, rocks from a variety of sources must be assembled in a small area for sampling. Regardless of the approach taken in site selection, the Pathfinder site should include eolian deposits and provisions should be made to obtain measurements on soils. A recommended approach for selecting the Mars Pathfinder landing site is to identify a deltaic deposit, composed of sediments derived from sources of various ages and geologic units that shows evidence of eolian activity. The site should be located as close as possible to the part of the outwash where rapid deposition occurred because the likelihood of 'sorting' by size and composition increases with distance, decreasing the probability of heterogeneity. In addition, it is recommended that field operation tests be conducted to gain experience and insight into conducting science with Pathfinder.

Strategies to address participant misrepresentation for eligibility in Web-based research.

PubMed

Kramer, Jessica; Rubin, Amy; Coster, Wendy; Helmuth, Eric; Hermos, John; Rosenbloom, David; Moed, Rich; Dooley, Meghan; Kao, Ying-Chia; Liljenquist, Kendra; Brief, Deborah; Enggasser, Justin; Keane, Terence; Roy, Monica; Lachowicz, Mark

2014-03-01

Emerging methodological research suggests that the World Wide Web ("Web") is an appropriate venue for survey data collection, and a promising area for delivering behavioral intervention. However, the use of the Web for research raises concerns regarding sample validity, particularly when the Web is used for recruitment and enrollment. The purpose of this paper is to describe the challenges experienced in two different Web-based studies in which participant misrepresentation threatened sample validity: a survey study and an online intervention study. The lessons learned from these experiences generated three types of strategies researchers can use to reduce the likelihood of participant misrepresentation for eligibility in Web-based research. Examples of procedural/design strategies, technical/software strategies and data analytic strategies are provided along with the methodological strengths and limitations of specific strategies. The discussion includes a series of considerations to guide researchers in the selection of strategies that may be most appropriate given the aims, resources and target population of their studies. Copyright © 2014 John Wiley & Sons, Ltd.

Understanding Your Local Economy: Economic Base Analysis and Local Development Strategies. Community Economics.

ERIC Educational Resources Information Center

Weber, Bruce A.; And Others

Community decision makers selecting an economic development strategy most appropriate for their local community must begin with an understanding of how their local economy functions, what its economic base is, and how changes in that base may affect local economic structure and performance. The economic base approach emphasizes the roles of…

Construction and applications of exon-trapping gene-targeting vectors with a novel strategy for negative selection.

PubMed

Saito, Shinta; Ura, Kiyoe; Kodama, Miho; Adachi, Noritaka

2015-06-30

Targeted gene modification by homologous recombination provides a powerful tool for studying gene function in cells and animals. In higher eukaryotes, non-homologous integration of targeting vectors occurs several orders of magnitude more frequently than does targeted integration, making the gene-targeting technology highly inefficient. For this reason, negative-selection strategies have been employed to reduce the number of drug-resistant clones associated with non-homologous vector integration, particularly when artificial nucleases to introduce a DNA break at the target site are unavailable or undesirable. As such, an exon-trap strategy using a promoterless drug-resistance marker gene provides an effective way to counterselect non-homologous integrants. However, constructing exon-trapping targeting vectors has been a time-consuming and complicated process. By virtue of highly efficient att-mediated recombination, we successfully developed a simple and rapid method to construct plasmid-based vectors that allow for exon-trapping gene targeting. These exon-trap vectors were useful in obtaining correctly targeted clones in mouse embryonic stem cells and human HT1080 cells. Most importantly, with the use of a conditionally cytotoxic gene, we further developed a novel strategy for negative selection, thereby enhancing the efficiency of counterselection for non-homologous integration of exon-trap vectors. Our methods will greatly facilitate exon-trapping gene-targeting technologies in mammalian cells, particularly when combined with the novel negative selection strategy.

Selection of examples in case-based computer-aided decision systems

PubMed Central

Mazurowski, Maciej A.; Zurada, Jacek M.; Tourassi, Georgia D.

2013-01-01

Case-based computer-aided decision (CB-CAD) systems rely on a database of previously stored, known examples when classifying new, incoming queries. Such systems can be particularly useful since they do not need retraining every time a new example is deposited in the case base. The adaptive nature of case-based systems is well suited to the current trend of continuously expanding digital databases in the medical domain. To maintain efficiency, however, such systems need sophisticated strategies to effectively manage the available evidence database. In this paper, we discuss the general problem of building an evidence database by selecting the most useful examples to store while satisfying existing storage requirements. We evaluate three intelligent techniques for this purpose: genetic algorithm-based selection, greedy selection and random mutation hill climbing. These techniques are compared to a random selection strategy used as the baseline. The study is performed with a previously presented CB-CAD system applied for false positive reduction in screening mammograms. The experimental evaluation shows that when the development goal is to maximize the system’s diagnostic performance, the intelligent techniques are able to reduce the size of the evidence database to 37% of the original database by eliminating superfluous and/or detrimental examples while at the same time significantly improving the CAD system’s performance. Furthermore, if the case-base size is a main concern, the total number of examples stored in the system can be reduced to only 2–4% of the original database without a decrease in the diagnostic performance. Comparison of the techniques shows that random mutation hill climbing provides the best balance between the diagnostic performance and computational efficiency when building the evidence database of the CB-CAD system. PMID:18854606

Cow genotyping strategies for genomic selection in a small dairy cattle population.

PubMed

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by

Strategies to intervene on causal systems are adaptively selected.

PubMed

Coenen, Anna; Rehder, Bob; Gureckis, Todd M

2015-06-01

How do people choose interventions to learn about causal systems? Here, we considered two possibilities. First, we test an information sampling model, information gain, which values interventions that can discriminate between a learner's hypotheses (i.e. possible causal structures). We compare this discriminatory model to a positive testing strategy that instead aims to confirm individual hypotheses. Experiment 1 shows that individual behavior is described best by a mixture of these two alternatives. In Experiment 2 we find that people are able to adaptively alter their behavior and adopt the discriminatory model more often after experiencing that the confirmatory strategy leads to a subjective performance decrement. In Experiment 3, time pressure leads to the opposite effect of inducing a change towards the simpler positive testing strategy. These findings suggest that there is no single strategy that describes how intervention decisions are made. Instead, people select strategies in an adaptive fashion that trades off their expected performance and cognitive effort. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

Warped document image correction method based on heterogeneous registration strategies

NASA Astrophysics Data System (ADS)

Tong, Lijing; Zhan, Guoliang; Peng, Quanyao; Li, Yang; Li, Yifan

2013-03-01

With the popularity of digital camera and the application requirement of digitalized document images, using digital cameras to digitalize document images has become an irresistible trend. However, the warping of the document surface impacts on the quality of the Optical Character Recognition (OCR) system seriously. To improve the warped document image's vision quality and the OCR rate, this paper proposed a warped document image correction method based on heterogeneous registration strategies. This method mosaics two warped images of the same document from different viewpoints. Firstly, two feature points are selected from one image. Then the two feature points are registered in the other image base on heterogeneous registration strategies. At last, image mosaics are done for the two images, and the best mosaiced image is selected by OCR recognition results. As a result, for the best mosaiced image, the distortions are mostly removed and the OCR results are improved markedly. Experimental results show that the proposed method can resolve the issue of warped document image correction more effectively.

Investigation of some selected strategies for multi-GNSS instantaneous RTK positioning

NASA Astrophysics Data System (ADS)

Paziewski, Jacek; Wielgosz, Pawel

2017-01-01

It is clear that we can benefit from multi-constellation GNSS in precise relative positioning. On the other hand, it is still an open problem how to combine multi-GNSS signals in a single functional model. This study presents methodology and quality assessment of selected methods allowing for multi-GNSS observations combining in relative kinematic positioning using baselines up to tens of kilometers. In specific, this paper characterizes loose and tight integration strategies applied to the ionosphere and troposphere weighted model. Performance assessment of the established strategies was based on the analyses of the integer ambiguity resolution and rover coordinates' repeatability obtained in the medium range instantaneous RTK positioning with the use of full constellation dual frequency GPS and Galileo signals. Since full constellation of Galileo satellites is not yet available, the observational data were obtained from a hardware GNSS signal simulator using regular geodetic GNSS receivers. The results indicate on similar and high performance of the loose, and tight integration with calibrated receiver ISBs strategies. These approaches have undeniable advantage over single system positioning in terms of reliability of the integer ambiguity resolution as well as rover coordinate repeatability.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

PubMed Central

Xiong, Lian; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-01

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. PMID:29342897

The Strategic Teacher: Selecting the Right Research-Based Strategy for Every Lesson

ERIC Educational Resources Information Center

Silver, Harvey F.; Strong, Richard W.; Perini, Matthew J.

2007-01-01

This ultimate guide to teaching strategies gives you 20 of the most reliable teaching strategies for every grade and subject, with dozens of variations and clear steps and examples for how to implement them. To help you choose the right strategy, the authors include a Strategic Dashboard that makes it easy for you to match your strategy to your…

Office-based surgery: embracing patient safety strategies.

PubMed

Shapiro, Fred E; Punwani, Nathan; Urman, Richard D

2013-01-01

Office-based surgery continues to grow as more procedures are being performed in the outpatient setting. With this exponential growth, there is an increasing emphasis on safe and effective patient care. Current research shows both gaps in safety and opportunities for improvement. Practice managers, clinicians, and other personnel should be cognizant that office procedures are coming under intense regulatory scrutiny. Effective strategies to maintain quality and patient safety include the use of checklists, obtaining office accreditation, encouraging board-certification and proper credentialing of proceduralists, and appropriate patient and procedure selection. There is increasing regulation of ambulatory surgery on state and national levels that will likely affect the financial and care quality aspects of office-based practice. Socioeconomic and political forces will continue to shape the future of office-based surgery.

Shaping Attention with Reward: Effects of Reward on Space- and Object-Based Selection

PubMed Central

Shomstein, Sarah; Johnson, Jacoba

2014-01-01

The contribution of rewarded actions to automatic attentional selection remains obscure. We hypothesized that some forms of automatic orienting, such as object-based selection, can be completely abandoned in lieu of reward maximizing strategy. While presenting identical visual stimuli to the observer, in a set of two experiments, we manipulate what is being rewarded (different object targets or random object locations) and the type of reward received (money or points). It was observed that reward alone guides attentional selection, entirely predicting behavior. These results suggest that guidance of selective attention, while automatic, is flexible and can be adjusted in accordance with external non-sensory reward-based factors. PMID:24121412

Genetic grouping strategies in selection efficiency of composite beef cattle ( × ).

PubMed

Petrini, J; Pertile, S F N; Eler, J P; Ferraz, J B S; Mattos, E C; Figueiredo, L G G; Mourão, G B

2015-02-01

The inclusion of genetic groups in sire evaluation has been widely used to represent genetic differences among animals not accounted for by the absence of parentage data. However, the definition of these groups is still arbitrary, and studies assessing the effects of genetic grouping strategies on the selection efficiency are rare. Therefore, the aim in this study was to compare genetic grouping strategies for animals with unknown parentage in prediction of breeding values (EBV). The total of 179,302 records of weaning weight (WW), 29,825 records of scrotal circumference (SC), and 70,302 records of muscling score (MUSC) from Montana Tropical animals, a Brazilian composite beef cattle population, were used. Genetic grouping strategies involving year of birth, sex of the unknown parent, birth farm, breed composition, and their combinations were evaluated. Estimated breeding values were predicted for each approach simulating a loss of genealogy data. Thereafter, these EBV were compared to those obtained in an analysis involving a real relationship matrix to estimate selection efficiency and correlations between EBV and animal rankings. The analysis model included the fixed effects of contemporary groups and class of the dam age at calving, the covariates of additive and nonadditive genetic effects, and age, and the additive genetic effect of animal as random effects. A second model also included the fixed effects of genetic group. The use of genetic groups resulted in means of selection efficiency and correlation of 70.4 to 97.1% and 0.51 to 0.94 for WW, 85.8 to 98.8% and 0.82 to 0.98 for SC, and 85.1 to 98.6% and 0.74 to 0.97 for MUSC, respectively. High selection efficiencies were observed for year of birth and breed composition strategies. The maximum absolute difference in annual genetic gain estimated through the use of complete genealogy and genetic groups were 0.38 kg for WW, 0.02 cm for SC, and 0.01 for MUSC, with lower differences obtained when year of birth

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

PubMed

Bian, Yuemin; Xie, Xiang-Qun Sean

2018-04-09

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

Effects of Activity Based Blended Learning Strategy on Prospective of Teachers' Achievement and Motivation

ERIC Educational Resources Information Center

Abdelraheem, Ahmed Yousif; Ahmed, Abdelrahman Mohammed

2015-01-01

The study investigates the effect of Activity based Blended Learning strategy and Conventional Blended Learning strategy on students' achievement and motivation. Two groups namely, experimental and control group from Sultan Qaboos University were selected randomly for the study. To assess students' achievement in the different groups, pre- and…

Perceptions Regarding Selected Educational Strategies Used by Extension Educators

ERIC Educational Resources Information Center

Kwaw-Mensah, David; Martin, Robert A.

2013-01-01

Purpose: The purpose of this study was to identify the perceptions that extension educators in the North Central region of the United States hold regarding selected educational strategies pertaining to livestock waste management education. Livestock waste management education has been recognized as one of extension's major initiatives in the…

Computer-aided diagnostic strategy selection.

PubMed

Greenes, R A

1986-03-01

Determination of the optimal diagnostic work-up strategy for the patient is becoming a major concern for the practicing physician. Overlap of the indications for various diagnostic procedures, differences in their invasiveness or risk, and high costs have made physicians aware of the need to consider the choice of procedure carefully, as well as its relation to management actions available. In this article, the author discusses research approaches that aim toward development of formal decision analytic methods to allow the physician to determine optimal strategy; clinical algorithms or rules as guides to physician decisions; improved measures for characterizing the performance of diagnostic tests; educational tools for increasing the familiarity of physicians with the concepts underlying these measures and analytic procedures; and computer-based aids for facilitating the employment of these resources in actual clinical practice.

The Development of Children's Strategies for Selective Attention: Evidence for a Transitional Period.

ERIC Educational Resources Information Center

DeMarie-Dreblow, Darlene; Miller, Patricia H.

1988-01-01

This study of 114 children between seven and nine years used a procedure for directly observing child-produced and experimenter-produced strategies to examine the transitional period of strategy development. Findings revealed gradual changes in children's ability to produce, and to benefit from, a strategy of selective attention. (RH)

The Effects of Relationship Type, Partner Intent, and Gender on the Selection of Relationship Maintenance Strategies.

ERIC Educational Resources Information Center

Shea, B. Christine; Pearson, Judy C.

1986-01-01

Indicates that relationship type did not affect the maintenance strategies that partners chose; however, the partners' relationship intent and the sex-composition of the dyad had a significant impact on the selection of directness strategies. Suggests that individuals are not necessarily more likely to select directness strategies than balance or…

Integrative review of implementation strategies for translation of research-based evidence by nurses.

PubMed

Wuchner, Staci S

2014-01-01

The purpose of this review was to synthesize and critique experimental and/or quasi-experimental research that has evaluated implementation strategies for translation of research-based evidence into nursing practice. Successfully implementing evidence-based research can improve patient outcomes. Identifying successful implementation strategies is imperative to move research-based evidence into practice. As implementation science gains popularity, it is imperative to understand the strategies that most effectively translate research-based evidence into practice. The review used the CINAHL and MEDLINE (Ovid) databases. Articles were included if they were experimental and/or quasi-experimental research designs, were written in English, and measured nursing compliance to translation of research-based evidence. An independent review was performed to select and critique the included articles. A wide array of interventions were completed, including visual cues, audit and feedback, educational meetings and materials, reminders, outreach, and leadership involvement. Because of the complex multimodal nature of the interventions and the variety of research topics, comparison across interventions was difficult. Many difficulties exist in determining what implementation strategies are most effective for translation of research-based evidence into practice by nurses. With these limited findings, further research is warranted to determine which implementation strategies most successfully translate research-based evidence into practice.

Compromise-based Robust Prioritization of Climate Change Adaptation Strategies for Watershed Management

NASA Astrophysics Data System (ADS)

Kim, Y.; Chung, E. S.

2014-12-01

This study suggests a robust prioritization framework for climate change adaptation strategies under multiple climate change scenarios with a case study of selecting sites for reusing treated wastewater (TWW) in a Korean urban watershed. The framework utilizes various multi-criteria decision making techniques, including the VIKOR method and the Shannon entropy-based weights. In this case study, the sustainability of TWW use is quantified with indicator-based approaches with the DPSIR framework, which considers both hydro-environmental and socio-economic aspects of the watershed management. Under the various climate change scenarios, the hydro-environmental responses to reusing TWW in potential alternative sub-watersheds are determined using the Hydrologic Simulation Program in Fortran (HSPF). The socio-economic indicators are obtained from the statistical databases. Sustainability scores for multiple scenarios are estimated individually and then integrated with the proposed approach. At last, the suggested framework allows us to prioritize adaptation strategies in a robust manner with varying levels of compromise between utility-based and regret-based strategies.

Goal selection versus process control in a brain-computer interface based on sensorimotor rhythms.

PubMed

Royer, Audrey S; He, Bin

2009-02-01

In a brain-computer interface (BCI) utilizing a process control strategy, the signal from the cortex is used to control the fine motor details normally handled by other parts of the brain. In a BCI utilizing a goal selection strategy, the signal from the cortex is used to determine the overall end goal of the user, and the BCI controls the fine motor details. A BCI based on goal selection may be an easier and more natural system than one based on process control. Although goal selection in theory may surpass process control, the two have never been directly compared, as we are reporting here. Eight young healthy human subjects participated in the present study, three trained and five naïve in BCI usage. Scalp-recorded electroencephalograms (EEG) were used to control a computer cursor during five different paradigms. The paradigms were similar in their underlying signal processing and used the same control signal. However, three were based on goal selection, and two on process control. For both the trained and naïve populations, goal selection had more hits per run, was faster, more accurate (for seven out of eight subjects) and had a higher information transfer rate than process control. Goal selection outperformed process control in every measure studied in the present investigation.

Strategies for Selecting Routes through Real-World Environments: Relative Topography, Initial Route Straightness, and Cardinal Direction

PubMed Central

Brunyé, Tad T.; Collier, Zachary A.; Cantelon, Julie; Holmes, Amanda; Wood, Matthew D.; Linkov, Igor; Taylor, Holly A.

2015-01-01

Previous research has demonstrated that route planners use several reliable strategies for selecting between alternate routes. Strategies include selecting straight rather than winding routes leaving an origin, selecting generally south- rather than north-going routes, and selecting routes that avoid traversal of complex topography. The contribution of this paper is characterizing the relative influence and potential interactions of these strategies. We also examine whether individual differences would predict any strategy reliance. Results showed evidence for independent and additive influences of all three strategies, with a strong influence of topography and initial segment straightness, and relatively weak influence of cardinal direction. Additively, routes were also disproportionately selected when they traversed relatively flat regions, had relatively straight initial segments, and went generally south rather than north. Two individual differences, extraversion and sense of direction, predicted the extent of some effects. Under real-world conditions navigators indeed consider a route’s initial straightness, cardinal direction, and topography, but these cues differ in relative influence and vary in their application across individuals. PMID:25992685

Selective remediation of contaminated sites using a two-level multiphase strategy and geostatistics.

PubMed

Saito, Hirotaka; Goovaerts, Pierre

2003-05-01

Selective soil remediation aims to reduce costs by cleaning only the fraction of an exposure unit (EU) necessary to lower the average concentration below the regulatory threshold. This approach requires a prior stratification of each EU into smaller remediation units (RU) which are then selected according to various criteria. This paper presents a geostatistical framework to account for uncertainties attached to both RU and EU average concentrations in selective remediation. The selection of RUs is based on their impact on the postremediation probability for the EU average concentration to exceed the regulatory threshold, which is assessed using geostatistical stochastic simulation. Application of the technique to a set of 600 dioxin concentrations collected at Piazza Road EPA Superfund site in Missouri shows a substantial decrease in the number of RU remediated compared with single phase remediation. The lower remediation costs achieved by the new strategy are obtained to the detriment of a higher risk of false negatives, yet for this data set this risk remains below the 5% rate set by EPA region 7.

A model-based 'varimax' sampling strategy for a heterogeneous population.

PubMed

Akram, Nuzhat A; Farooqi, Shakeel R

2014-01-01

Sampling strategies are planned to enhance the homogeneity of a sample, hence to minimize confounding errors. A sampling strategy was developed to minimize the variation within population groups. Karachi, the largest urban agglomeration in Pakistan, was used as a model population. Blood groups ABO and Rh factor were determined for 3000 unrelated individuals selected through simple random sampling. Among them five population groups, namely Balochi, Muhajir, Pathan, Punjabi and Sindhi, based on paternal ethnicity were identified. An index was designed to measure the proportion of admixture at parental and grandparental levels. Population models based on index score were proposed. For validation, 175 individuals selected through stratified random sampling were genotyped for the three STR loci CSF1PO, TPOX and TH01. ANOVA showed significant differences across the population groups for blood groups and STR loci distribution. Gene diversity was higher across the sub-population model than in the agglomerated population. At parental level gene diversities are significantly higher across No admixture models than Admixture models. At grandparental level the difference was not significant. A sub-population model with no admixture at parental level was justified for sampling the heterogeneous population of Karachi.

Strategy for selecting disposable bags for cell culture media applications based on a root-cause investigation.

PubMed

Wood, Joseph; Mahajan, Ekta; Shiratori, Masaru

2013-01-01

The use of disposable bags for cell culture media storage has grown significantly in the past decade. Some of the key advantages of using disposable bags relative to non-disposable containers include increased product throughput, decreased cleaning validation costs, reduced risk of cross contamination and lower facility costs. As the scope of use of disposable bags for cell culture applications increases, problematic bags and scenarios should be identified and addressed to continue improving disposables technologies and meet the biotech industry's needs. In this article, we examine a cell culture application wherein media stored in disposable bags is warmed at 37°C before use for cell culture operations. A problematic bag film was identified through a prospective and retrospective cell culture investigation. The investigation provided information on the scope and variation of the issue with respect to different Chinese hamster ovary (CHO) cell lines, cell culture media, and application-specific parameters. It also led to the development of application-specific test methods and enabled a strategy for disposable bag film testing. The strategy was implemented for qualifying an alternative bag film for use in our processes. In this test strategy, multiple lots of 13 bag film types, encompassing eight vendors were evaluated using a three round, cell culture-based test strategy. The test strategy resulted in the determination of four viable bag film options based on the technical data. The results of this evaluation were used to conclude that a volatile or air-quenched compound, likely generated by gamma irradiation of the problematic bag film, negatively impacted cell culture performance. © 2013 American Institute of Chemical Engineers.

Genomic Selection For Bacterial Cold Water Disease Resistance In Rainbow Trout Reveals Large Within-Family Variation That Cannot Be Exploited In Traditional Family-based Selective Breeding

USDA-ARS?s Scientific Manuscript database

Selective breeding is an effective strategy to improve resistance to specific pathogens, and thus has the potential to mitigate antibiotic use in aquaculture. Large family sizes of aquaculture species permits family-based selective breeding programs, but the need for specific-pathogen-free nucleus p...

Selective BET bromodomain inhibition as an antifungal therapeutic strategy

PubMed Central

Mietton, Flore; Ferri, Elena; Champleboux, Morgane; Zala, Ninon; Maubon, Danièle; Zhou, Yingsheng; Harbut, Mike; Spittler, Didier; Garnaud, Cécile; Courçon, Marie; Chauvel, Murielle; d'Enfert, Christophe; Kashemirov, Boris A.; Hull, Mitchell; Cornet, Muriel; McKenna, Charles E.; Govin, Jérôme; Petosa, Carlo

2017-01-01

Invasive fungal infections cause significant morbidity and mortality among immunocompromised individuals, posing an urgent need for new antifungal therapeutic strategies. Here we investigate a chromatin-interacting module, the bromodomain (BD) from the BET family of proteins, as a potential antifungal target in Candida albicans, a major human fungal pathogen. We show that the BET protein Bdf1 is essential in C. albicans and that mutations inactivating its two BDs result in a loss of viability in vitro and decreased virulence in mice. We report small-molecule compounds that inhibit C. albicans Bdf1 with high selectivity over human BDs. Crystal structures of the Bdf1 BDs reveal binding modes for these inhibitors that are sterically incompatible with the human BET-binding pockets. Furthermore, we report a dibenzothiazepinone compound that phenocopies the effects of a Bdf1 BD-inactivating mutation on C. albicans viability. These findings establish BET inhibition as a promising antifungal therapeutic strategy and identify Bdf1 as an antifungal drug target that can be selectively inhibited without antagonizing human BET function. PMID:28516956

Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

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

Sukumar, Sreenivas R; Nutaro, James J

This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

Public Speaking Apprehension, Decision-Making Errors in the Selection of Speech Introduction Strategies and Adherence to Strategy.

ERIC Educational Resources Information Center

Beatty, Michael J.

1988-01-01

Examines the choice-making processes of students engaged in the selection of speech introduction strategies. Finds that the frequency of students making decision-making errors was a positive function of public speaking apprehension. (MS)

Age-Related Changes in Children's Executive Functions and Strategy Selection: A Study in Computational Estimation

ERIC Educational Resources Information Center

Lemaire, Patrick; Lecacheur, Mireille

2011-01-01

Third, fifth, and seventh graders selected the best strategy (rounding up or rounding down) for estimating answers to two-digit addition problems. Executive function measures were collected for each individual. Data showed that (a) children's skill at both strategy selection and execution improved with age and (b) increased efficiency in executive…

Decision method for optimal selection of warehouse material handling strategies by production companies

NASA Astrophysics Data System (ADS)

Dobos, P.; Tamás, P.; Illés, B.

2016-11-01

Adequate establishment and operation of warehouse logistics determines the companies’ competitiveness significantly because it effects greatly the quality and the selling price of the goods that the production companies produce. In order to implement and manage an adequate warehouse system, adequate warehouse position, stock management model, warehouse technology, motivated work force committed to process improvement and material handling strategy are necessary. In practical life, companies have paid small attantion to select the warehouse strategy properly. Although it has a major influence on the production in the case of material warehouse and on smooth costumer service in the case of finished goods warehouse because this can happen with a huge loss in material handling. Due to the dynamically changing production structure, frequent reorganization of warehouse activities is needed, on what the majority of the companies react basically with no reactions. This work presents a simulation test system frames for eligible warehouse material handling strategy selection and also the decision method for selection.

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

NASA Astrophysics Data System (ADS)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

Stress, Time Pressure, Strategy Selection and Math Anxiety in Mathematics: A Review of the Literature.

PubMed

Caviola, Sara; Carey, Emma; Mammarella, Irene C; Szucs, Denes

2017-01-01

We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth "strategy selection") in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations), with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research.

Reference View Selection in DIBR-Based Multiview Coding.

PubMed

Maugey, Thomas; Petrazzuoli, Giovanni; Frossard, Pascal; Cagnazzo, Marco; Pesquet-Popescu, Beatrice

2016-04-01

Augmented reality, interactive navigation in 3D scenes, multiview video, and other emerging multimedia applications require large sets of images, hence larger data volumes and increased resources compared with traditional video services. The significant increase in the number of images in multiview systems leads to new challenging problems in data representation and data transmission to provide high quality of experience on resource-constrained environments. In order to reduce the size of the data, different multiview video compression strategies have been proposed recently. Most of them use the concept of reference or key views that are used to estimate other images when there is high correlation in the data set. In such coding schemes, the two following questions become fundamental: 1) how many reference views have to be chosen for keeping a good reconstruction quality under coding cost constraints? And 2) where to place these key views in the multiview data set? As these questions are largely overlooked in the literature, we study the reference view selection problem and propose an algorithm for the optimal selection of reference views in multiview coding systems. Based on a novel metric that measures the similarity between the views, we formulate an optimization problem for the positioning of the reference views, such that both the distortion of the view reconstruction and the coding rate cost are minimized. We solve this new problem with a shortest path algorithm that determines both the optimal number of reference views and their positions in the image set. We experimentally validate our solution in a practical multiview distributed coding system and in the standardized 3D-HEVC multiview coding scheme. We show that considering the 3D scene geometry in the reference view, positioning problem brings significant rate-distortion improvements and outperforms the traditional coding strategy that simply selects key frames based on the distance between cameras.

Variable Selection in the Presence of Missing Data: Imputation-based Methods.

PubMed

Zhao, Yize; Long, Qi

2017-01-01

Variable selection plays an essential role in regression analysis as it identifies important variables that associated with outcomes and is known to improve predictive accuracy of resulting models. Variable selection methods have been widely investigated for fully observed data. However, in the presence of missing data, methods for variable selection need to be carefully designed to account for missing data mechanisms and statistical techniques used for handling missing data. Since imputation is arguably the most popular method for handling missing data due to its ease of use, statistical methods for variable selection that are combined with imputation are of particular interest. These methods, valid used under the assumptions of missing at random (MAR) and missing completely at random (MCAR), largely fall into three general strategies. The first strategy applies existing variable selection methods to each imputed dataset and then combine variable selection results across all imputed datasets. The second strategy applies existing variable selection methods to stacked imputed datasets. The third variable selection strategy combines resampling techniques such as bootstrap with imputation. Despite recent advances, this area remains under-developed and offers fertile ground for further research.

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

PubMed

Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study

PubMed Central

Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206

Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

PubMed

Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

2015-01-01

Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.

Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

PubMed

Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

2014-01-01

The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Portable, universal, and visual ion sensing platform based on the light emitting diode-based self-referencing-ion selective field-effect transistor.

PubMed

Zhang, Xiaowei; Han, Yanchao; Li, Jing; Zhang, Libing; Jia, Xiaofang; Wang, Erkang

2014-02-04

In this work, a novel and universal ion sensing platform was presented, which enables the visual detection of various ions with high sensitivity and selectivity. Coaxial potential signals (millivolt-scale) of the sample from the self-referencing (SR) ion selective chip can be transferred into the ad620-based amplifier with an output of volt-scale potentials. The amplified voltage is high enough to drive a light emitting diode (LED), which can be used as an amplifier and indicator to report the sample information. With this double amplification device (light emitting diode-based self-referencing-ion selective field-effect transistor, LED-SR-ISFET), a tiny change of the sample concentration can be observed with a distinguishable variation of LED brightness by visual inspection. This LED-based luminescent platform provided a facile, low-cost, and rapid sensing strategy without the need of additional expensive chemiluminescence reagent and instruments. Moreover, the SR mode also endows this device excellent stability and reliability. With this innovative design, sensitive determination of K(+), H(+), and Cl(-) by the naked eye was achieved. It should also be noticed that this sensing strategy can easily be extended to other ions (or molecules) by simply integrating the corresponding ion (or molecule) selective electrode.

A global logrank test for adaptive treatment strategies based on observational studies.

PubMed

Li, Zhiguo; Valenstein, Marcia; Pfeiffer, Paul; Ganoczy, Dara

2014-02-28

In studying adaptive treatment strategies, a natural question that is of paramount interest is whether there is any significant difference among all possible treatment strategies. When the outcome variable of interest is time-to-event, we propose an inverse probability weighted logrank test for testing the equivalence of a fixed set of pre-specified adaptive treatment strategies based on data from an observational study. The weights take into account both the possible selection bias in an observational study and the fact that the same subject may be consistent with more than one treatment strategy. The asymptotic distribution of the weighted logrank statistic under the null hypothesis is obtained. We show that, in an observational study where the treatment selection probabilities need to be estimated, the estimation of these probabilities does not have an effect on the asymptotic distribution of the weighted logrank statistic, as long as the estimation of the parameters in the models for these probabilities is n-consistent. Finite sample performance of the test is assessed via a simulation study. We also show in the simulation that the test can be pretty robust to misspecification of the models for the probabilities of treatment selection. The method is applied to analyze data on antidepressant adherence time from an observational database maintained at the Department of Veterans Affairs' Serious Mental Illness Treatment Research and Evaluation Center. Copyright © 2013 John Wiley & Sons, Ltd.

Age-related Associative Memory Deficits in Value-based Remembering: The Contribution of Agenda-based Regulation and Strategy Use

PubMed Central

Ariel, Robert; Price, Jodi; Hertzog, Christopher

2015-01-01

Value-based remembering in free recall tasks may be spared from the typical age-related cognitive decline observed for episodic memory. However, it is unclear whether value-based remembering for associative information is also spared from age-related cognitive decline. The current experiments evaluated the contribution of agenda-based based regulation and strategy use during study to age differences and similarities in value-based remembering of associative information. Participants studied word pairs (Experiments 1-2) or single words (Experiment 2) slated with different point values by moving a mouse controlled cursor to different spatial locations to reveal either items for study or the point value associated with remembering each item. Some participants also provided strategy reports for each item. Younger and older adults allocated greater time to studying high than low valued information, reported using normatively effective encoding strategies to learn high-valued pairs, and avoided study of low-valued pairs. As a consequence, both age groups selectively remembered more high than low-valued items. Despite nearly identical regulatory behavior, an associative memory deficit for older adults was present for high valued pairs. Age differences in value-based remembering did not occur when the materials were word lists. Fluid intelligence also moderated the effectiveness of older adults’ strategy use for high valued pairs (Experiment 2). These results suggest that age differences in associative value-based remembering may be due to some older adults’ gleaning less benefit from using normatively effective encoding strategies rather than age differences in metacognitive self-regulation per se. PMID:26523692

Strategies for efficiently selecting PHA producing mixed microbial cultures using complex feedstocks: Feast and famine regime and uncoupled carbon and nitrogen availabilities.

PubMed

Oliveira, Catarina S S; Silva, Carlos E; Carvalho, Gilda; Reis, Maria A

2017-07-25

Production of polyhydroxyalkanoates (PHAs) by open mixed microbial cultures (MMCs) has been attracting increasing interest as an alternative technology to PHA production by pure cultures, due to the potential for lower costs associated with the use of open systems (eliminating the requirement for sterile conditions) and the utilisation of cheap feedstock (industrial and agricultural wastes). Such technology relies on the efficient selection of an MMC enriched in PHA-accumulating organisms. Fermented cheese whey, a protein-rich complex feedstock, has been used previously to produce PHA using the feast and famine regime for selection of PHA accumulating cultures. While this selection strategy was found efficient when operated at relatively low organic loading rate (OLR, 2g-CODL -1 d -1 ), great instability and low selection efficiency of PHA accumulating organisms were observed when higher OLR (ca. 6g-CODL -1 d -1 ) was applied. High organic loading is desirable as a means to enhance PHA productivity. In the present study, a new selection strategy was tested with the aim of improving selection for high OLR. It was based on uncoupling carbon and nitrogen supply and was implemented and compared with the conventional feast and famine strategy. For this, two selection reactors were fed with fermented cheese whey applying an OLR of ca. 8.5g-CODL -1 (with 3.8g-CODL -1 resulting from organic acids and ethanol), and operated in parallel under similar conditions, except for the timing of nitrogen supplementation. Whereas in the conventional strategy nitrogen and carbon substrates were added simultaneously at the beginning of the cycle, in the uncoupled substrates strategy, nitrogen addition was delayed to the end of the feast phase (i.e. after exogenous carbon was exhausted). The two different strategies selected different PHA-storing microbial communities, dominated by Corynebacterium and a Xantomonadaceae, respectively with the conventional and the new approaches. The new

Multiple-input multiple-output causal strategies for gene selection.

PubMed

Bontempi, Gianluca; Haibe-Kains, Benjamin; Desmedt, Christine; Sotiriou, Christos; Quackenbush, John

2011-11-25

Traditional strategies for selecting variables in high dimensional classification problems aim to find sets of maximally relevant variables able to explain the target variations. If these techniques may be effective in generalization accuracy they often do not reveal direct causes. The latter is essentially related to the fact that high correlation (or relevance) does not imply causation. In this study, we show how to efficiently incorporate causal information into gene selection by moving from a single-input single-output to a multiple-input multiple-output setting. We show in synthetic case study that a better prioritization of causal variables can be obtained by considering a relevance score which incorporates a causal term. In addition we show, in a meta-analysis study of six publicly available breast cancer microarray datasets, that the improvement occurs also in terms of accuracy. The biological interpretation of the results confirms the potential of a causal approach to gene selection. Integrating causal information into gene selection algorithms is effective both in terms of prediction accuracy and biological interpretation.

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors

PubMed Central

Nefti-Meziani, Samia; Carbonaro, Nicola

2017-01-01

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively. PMID:28858252

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors.

PubMed

Russo, Stefania; Nefti-Meziani, Samia; Carbonaro, Nicola; Tognetti, Alessandro

2017-08-31

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively.

Selective and Sensitive Detection of Cyanide Based on the Displacement Strategy Using a Water-Soluble Fluorescent Probe.

PubMed

La, Ming; Hao, Yuanqiang; Wang, Zhaoyang; Han, Guo-Cheng; Qu, Lingbo

2016-01-01

A water-soluble fluorescent probe (C-GGH) was used for the highly sensitive and selective detection of cyanide (CN(-)) in aqueous media based on the displacement strategy. Due to the presence of the recognition unit GGH (Gly-Gly-His), the probe C-GGH can coordinate with Cu(2+) and consequently display ON-OFF type fluorescence response. Furthermore, the in situ formed nonfluorescent C-GGH-Cu(2+) complex can act as an effective OFF-ON type fluorescent probe for sensing CN(-) anion. Due to the strong binding affinity of CN(-) to Cu(2+), CN(-) can extract Cu(2+) from C-GGH-Cu(2+) complex, leading to the release of C-GGH and the recovery of fluorescent emission of the system. The probe C-GGH-Cu(2+) allowed detection of CN(-) in aqueous solution with a LOD (limit of detection) of 0.017 μmol/L which is much lower than the maximum contaminant level (1.9 μmol/L) for CN(-) in drinking water set by the WHO (World Health Organization). The probe also displayed excellent specificity for CN(-) towards other anions, including F(-), Cl(-), Br(-), I(-), SCN(-), PO4 (3-), N3 (-), NO3 (-), AcO(-), SO4 (2-), and CO3 (2-).

Selective and Sensitive Detection of Cyanide Based on the Displacement Strategy Using a Water-Soluble Fluorescent Probe

PubMed Central

La, Ming; Hao, Yuanqiang; Wang, Zhaoyang; Han, Guo-Cheng; Qu, Lingbo

2016-01-01

A water-soluble fluorescent probe (C-GGH) was used for the highly sensitive and selective detection of cyanide (CN−) in aqueous media based on the displacement strategy. Due to the presence of the recognition unit GGH (Gly-Gly-His), the probe C-GGH can coordinate with Cu2+ and consequently display ON-OFF type fluorescence response. Furthermore, the in situ formed nonfluorescent C-GGH-Cu2+ complex can act as an effective OFF-ON type fluorescent probe for sensing CN− anion. Due to the strong binding affinity of CN− to Cu2+, CN− can extract Cu2+ from C-GGH-Cu2+ complex, leading to the release of C-GGH and the recovery of fluorescent emission of the system. The probe C-GGH-Cu2+ allowed detection of CN− in aqueous solution with a LOD (limit of detection) of 0.017 μmol/L which is much lower than the maximum contaminant level (1.9 μmol/L) for CN− in drinking water set by the WHO (World Health Organization). The probe also displayed excellent specificity for CN− towards other anions, including F−, Cl−, Br−, I−, SCN−, PO4 3−, N3 −, NO3 −, AcO−, SO4 2−, and CO3 2−. PMID:26881185

Genotype-by-environment interactions leads to variable selection on life-history strategy in Common Evening Primrose (Oenothera biennis).

PubMed

Johnson, M T J

2007-01-01

Monocarpic plant species, where reproduction is fatal, frequently exhibit variation in the length of their prereproductive period prior to flowering. If this life-history variation in flowering strategy has a genetic basis, genotype-by-environment interactions (G x E) may maintain phenotypic diversity in flowering strategy. The native monocarpic plant Common Evening Primrose (Oenothera biennis L., Onagraceae) exhibits phenotypic variation for annual vs. biennial flowering strategies. I tested whether there was a genetic basis to variation in flowering strategy in O. biennis, and whether environmental variation causes G x E that imposes variable selection on flowering strategy. In a field experiment, I randomized more than 900 plants from 14 clonal families (genotypes) into five distinct habitats that represented a natural productivity gradient. G x E strongly affected the lifetime fruit production of O. biennis, with the rank-order in relative fitness of genotypes changing substantially between habitats. I detected genetic variation in annual vs. biennial strategies in most habitats, as well as a G x E effect on flowering strategy. This variation in flowering strategy was correlated with genetic variation in relative fitness, and phenotypic and genotypic selection analyses revealed that environmental variation resulted in variable directional selection on annual vs. biennial strategies. Specifically, a biennial strategy was favoured in moderately productive environments, whereas an annual strategy was favoured in low-productivity environments. These results highlight the importance of variable selection for the maintenance of genetic variation in the life-history strategy of a monocarpic plant.

The Node Acquisition and Integration Technique: A Node-Link Based Teaching/Learning Strategy.

ERIC Educational Resources Information Center

Diekhoff, George M.

This paper presents the results of three experiments conducted in connection with development of a node-link based teaching/learning strategy. In experiment 1, subjects were instructed to either define concepts selected from a unit of introductory psychology or to describe the relationships existing between pairs of concepts. The cognitive…

Long-term selection strategies for complex traits using high-density genetic markers.

PubMed

Kemper, K E; Bowman, P J; Pryce, J E; Hayes, B J; Goddard, M E

2012-08-01

Selection of animals for breeding ranked on estimated breeding value maximizes genetic gain in the next generation but does not necessarily maximize long-term response. An alternative method, as practiced by plant breeders, is to build a desired genotype by selection on specific loci. Maximal long-term response in animal breeding requires selection on estimated breeding values with constraints on coancestry. In this paper, we compared long-term genetic response using either a genotype building or a genomic estimated breeding value (GEBV) strategy for the Australian Selection Index (ASI), a measure of profit. First, we used real marker effects from the Australian Dairy Herd Improvement Scheme to estimate breeding values for chromosome segments (approximately 25 cM long) for 2,650 Holstein bulls. Second, we selected 16 animals to be founders for a simulated breeding program where, between them, founders contain the best possible combination of 2 segments from 2 animals at each position in the genome. Third, we mated founder animals and their descendants over 30 generations with 2 breeding objectives: (1) to create a population with the "ideal genotype," where the best 2 segments from the founders segregate at each position, or (2) obtain the highest possible response in ASI with coancestry lower than that achieved under breeding objective 1. Results show that genotype building achieved the ideal genotype for breeding objective 1 and obtained a large gain in ASI over the current population (+A$864.99). However, selection on overall GEBV had greater short-term response and almost as much long-term gain (+A$820.42). When coancestry was lowered under breeding objective 2, selection on overall GEBV achieved a higher response in ASI than the genotype building strategy. Selection on overall GEBV seems more flexible in its selection decisions and was therefore better able to precisely control coancestry while maximizing ASI. We conclude that selection on overall GEBV while

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

MOF-Based Membrane Encapsulated ZnO Nanowires for Enhanced Gas Sensor Selectivity.

PubMed

Drobek, Martin; Kim, Jae-Hun; Bechelany, Mikhael; Vallicari, Cyril; Julbe, Anne; Kim, Sang Sub

2016-04-06

Gas sensors are of a great interest for applications including toxic or explosive gases detection in both in-house and industrial environments, air quality monitoring, medical diagnostics, or control of food/cosmetic properties. In the area of semiconductor metal oxides (SMOs)-based sensors, a lot of effort has been devoted to improve the sensing characteristics. In this work, we report on a general methodology for improving the selectivity of SMOx nanowires sensors, based on the coverage of ZnO nanowires with a thin ZIF-8 molecular sieve membrane. The optimized ZnO@ZIF-8-based nanocomposite sensor shows markedly selective response to H2 in comparison with the pristine ZnO nanowires sensor, while showing the negligible sensing response to C7H8 and C6H6. This original MOF-membrane encapsulation strategy applied to nanowires sensor architecture pave the way for other complex 3D architectures and various types of applications requiring either gas or ion selectivity, such as biosensors, photo(catalysts), and electrodes.

Threshold-selecting strategy for best possible ground state detection with genetic algorithms

NASA Astrophysics Data System (ADS)

Lässig, Jörg; Hoffmann, Karl Heinz

2009-04-01

Genetic algorithms are a standard heuristic to find states of low energy in complex state spaces as given by physical systems such as spin glasses but also in combinatorial optimization. The paper considers the problem of selecting individuals in the current population in genetic algorithms for crossover. Many schemes have been considered in literature as possible crossover selection strategies. We show for a large class of quality measures that the best possible probability distribution for selecting individuals in each generation of the algorithm execution is a rectangular distribution over the individuals sorted by their energy values. This means uniform probabilities have to be assigned to a group of the individuals with lowest energy in the population but probabilities equal to zero to individuals which are corresponding to energy values higher than a fixed cutoff, which is equal to a certain rank in the vector sorted by the energy of the states in the current population. The considered strategy is dubbed threshold selecting. The proof applies basic arguments of Markov chains and linear optimization and makes only a few assumptions on the underlying principles and hence applies to a large class of algorithms.

Automatic parameter selection for feature-based multi-sensor image registration

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Tom, Victor; Webb, Helen; Chao, Alan

2006-05-01

Accurate image registration is critical for applications such as precision targeting, geo-location, change-detection, surveillance, and remote sensing. However, the increasing volume of image data is exceeding the current capacity of human analysts to perform manual registration. This image data glut necessitates the development of automated approaches to image registration, including algorithm parameter value selection. Proper parameter value selection is crucial to the success of registration techniques. The appropriate algorithm parameters can be highly scene and sensor dependent. Therefore, robust algorithm parameter value selection approaches are a critical component of an end-to-end image registration algorithm. In previous work, we developed a general framework for multisensor image registration which includes feature-based registration approaches. In this work we examine the problem of automated parameter selection. We apply the automated parameter selection approach of Yitzhaky and Peli to select parameters for feature-based registration of multisensor image data. The approach consists of generating multiple feature-detected images by sweeping over parameter combinations and using these images to generate estimated ground truth. The feature-detected images are compared to the estimated ground truth images to generate ROC points associated with each parameter combination. We develop a strategy for selecting the optimal parameter set by choosing the parameter combination corresponding to the optimal ROC point. We present numerical results showing the effectiveness of the approach using registration of collected SAR data to reference EO data.

An Optical Biosensing Strategy Based on Selective Light Absorption and Wavelength Filtering from Chromogenic Reaction

PubMed Central

Chun, Hyeong Jin; Han, Yong Duk; Park, Yoo Min; Kim, Ka Ram; Lee, Seok Jae

2018-01-01

To overcome the time and space constraints in disease diagnosis via the biosensing approach, we developed a new signal-transducing strategy that can be applied to colorimetric optical biosensors. Our study is focused on implementation of a signal transduction technology that can directly translate the color intensity signals—that require complicated optical equipment for the analysis—into signals that can be easily counted with the naked eye. Based on the selective light absorption and wavelength-filtering principles, our new optical signaling transducer was built from a common computer monitor and a smartphone. In this signal transducer, the liquid crystal display (LCD) panel of the computer monitor served as a light source and a signal guide generator. In addition, the smartphone was used as an optical receiver and signal display. As a biorecognition layer, a transparent and soft material-based biosensing channel was employed generating blue output via a target-specific bienzymatic chromogenic reaction. Using graphics editor software, we displayed the optical signal guide patterns containing multiple polygons (a triangle, circle, pentagon, heptagon, and 3/4 circle, each associated with a specified color ratio) on the LCD monitor panel. During observation of signal guide patterns displayed on the LCD monitor panel using a smartphone camera via the target analyte-loaded biosensing channel as a color-filtering layer, the number of observed polygons changed according to the concentration of the target analyte via the spectral correlation between absorbance changes in a solution of the biosensing channel and color emission properties of each type of polygon. By simple counting of the changes in the number of polygons registered by the smartphone camera, we could efficiently measure the concentration of a target analyte in a sample without complicated and expensive optical instruments. In a demonstration test on glucose as a model analyte, we could easily measure

An Optical Biosensing Strategy Based on Selective Light Absorption and Wavelength Filtering from Chromogenic Reaction.

PubMed

Chun, Hyeong Jin; Han, Yong Duk; Park, Yoo Min; Kim, Ka Ram; Lee, Seok Jae; Yoon, Hyun C

2018-03-06

To overcome the time and space constraints in disease diagnosis via the biosensing approach, we developed a new signal-transducing strategy that can be applied to colorimetric optical biosensors. Our study is focused on implementation of a signal transduction technology that can directly translate the color intensity signals-that require complicated optical equipment for the analysis-into signals that can be easily counted with the naked eye. Based on the selective light absorption and wavelength-filtering principles, our new optical signaling transducer was built from a common computer monitor and a smartphone. In this signal transducer, the liquid crystal display (LCD) panel of the computer monitor served as a light source and a signal guide generator. In addition, the smartphone was used as an optical receiver and signal display. As a biorecognition layer, a transparent and soft material-based biosensing channel was employed generating blue output via a target-specific bienzymatic chromogenic reaction. Using graphics editor software, we displayed the optical signal guide patterns containing multiple polygons (a triangle, circle, pentagon, heptagon, and 3/4 circle, each associated with a specified color ratio) on the LCD monitor panel. During observation of signal guide patterns displayed on the LCD monitor panel using a smartphone camera via the target analyte-loaded biosensing channel as a color-filtering layer, the number of observed polygons changed according to the concentration of the target analyte via the spectral correlation between absorbance changes in a solution of the biosensing channel and color emission properties of each type of polygon. By simple counting of the changes in the number of polygons registered by the smartphone camera, we could efficiently measure the concentration of a target analyte in a sample without complicated and expensive optical instruments. In a demonstration test on glucose as a model analyte, we could easily measure the

Role of the neostriatal dopaminergic activity in sequencing and selecting behavioural strategies: facilitation of processes involved in selecting the best strategy in a stressful situation.

PubMed

Cools, A R

1980-10-01

The purpose of this study was to detect the behavioural effect of drug-induced changes in the neostriatal dopaminergic activity upon the degree of intrinsic (self-generated) and extrinsic (externally produced) constraints on the selection of behavioural patterns in rats. Both systemic and neostriatal injections of extremely low doses of apomorphine and haloperidol were used to change the neostriatal dopaminergic activity. Behavioural changes were observed in (a) an open-field test, (b) a so-called 'swimming without escape' test, (c) a so-called 'swimming with escape' test, and (d) a test to detect deficiencies in sensory, motor and sensorimotor capacities required to perform both swimming tests. Evidence is found that the neostriatum, especially the neostriatal, dopaminergic activity determines the animal's ability to select the best strategy in a stressful situation by modifying the process of switching strategies under pressure of factors intrinsic to the organism: neither sensory neglect nor inability to initiate voluntary movements underlay the observed phenomena. It is suggested that the neostriatum determines the individual flexibility to cope with available sensory information.

Transformation from gold nanoclusters to plasmonic nanoparticles: A general strategy towards selective detection of organophosphorothioate pesticides.

PubMed

Lu, Qian; Zhou, Tingyao; Wang, Yaping; Gong, Lingshan; Liu, Jinbin

2018-01-15

Luminescent gold nanoclusters (AuNCs) synthesized using non-thiolate DNA ligands were reported to show both optical and structure responses toward diethyposphorthioate (DEP) derived from the hydrolysis of chlorpyrifos (CP). After incubation of AuNCs with DEP, the non-thiolate DNA ligands were immediately replaced and the tiny AuNCs with ultrasmall size transformed gradually to plasmonic nanoparticles, which resulted in significant luminescence quenching of the AuNCs, offering a new possibility to selectively detect organophosphorothioate pesticides that could be easily hydrolyzed to form the special structures such as DEP containing two binding sites (e.g. S and O atoms). Therefore, selecting CP as a model analyte, we here developed a general strategy for the construction of a novel chemosensor for the determination of CP using the non-thiolate DNA coated AuNCs as an optical probe. Based on aggregation-induced luminescence quenching, this strategy exhibited highly sensitive and selective responses towards CP with a limit of detection (LOD) of 0.50μM, and was applied successfully to the analysis of CP in real sample. More interestingly, this facile strategy could easily distinguish CP from other thiol reagents through solution color change in spite of the existence of the coordination between Au and S atom for both of them, and the response mechanisms for them were studied in detail. In additional, it could be extended to detect the other organophosphorothioate pesticides with the similar structure as CP, which exploits a new platform for the construction of chemosensor and application. Copyright © 2017 Elsevier B.V. All rights reserved.

Enrichment assessment of multiple virtual screening strategies for Toll-like receptor 8 agonists based on a maximal unbiased benchmarking data set.

PubMed

Pei, Fen; Jin, Hongwei; Zhou, Xin; Xia, Jie; Sun, Lidan; Liu, Zhenming; Zhang, Liangren

2015-11-01

Toll-like receptor 8 agonists, which activate adaptive immune responses by inducing robust production of T-helper 1-polarizing cytokines, are promising candidates for vaccine adjuvants. As the binding site of toll-like receptor 8 is large and highly flexible, virtual screening by individual method has inevitable limitations; thus, a comprehensive comparison of different methods may provide insights into seeking effective strategy for the discovery of novel toll-like receptor 8 agonists. In this study, the performance of knowledge-based pharmacophore, shape-based 3D screening, and combined strategies was assessed against a maximum unbiased benchmarking data set containing 13 actives and 1302 decoys specialized for toll-like receptor 8 agonists. Prior structure-activity relationship knowledge was involved in knowledge-based pharmacophore generation, and a set of antagonists was innovatively used to verify the selectivity of the selected knowledge-based pharmacophore. The benchmarking data set was generated from our recently developed 'mubd-decoymaker' protocol. The enrichment assessment demonstrated a considerable performance through our selected three-layer virtual screening strategy: knowledge-based pharmacophore (Phar1) screening, shape-based 3D similarity search (Q4_combo), and then a Gold docking screening. This virtual screening strategy could be further employed to perform large-scale database screening and to discover novel toll-like receptor 8 agonists. © 2015 John Wiley & Sons A/S.

Development of risk-based air quality management strategies under impacts of climate change.

PubMed

Liao, Kuo-Jen; Amar, Praveen; Tagaris, Efthimios; Russell, Armistead G

2012-05-01

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of

A ratiometric strategy -based electrochemical sensing interface for the sensitive and reliable detection of imidacloprid.

PubMed

Li, Xueyan; Kan, Xianwen

2018-04-30

In this study, a ratiometric strategy-based electrochemical sensor was developed by electropolymerization of thionine (THI) and β-cyclodextrin (β-CD) composite films on a glassy carbon electrode surface for imidacloprid (IMI) detection. THI played the role of an inner reference element to provide a built-in correction. In addition, the modified β-CD showed good selective enrichment for IMI to improve the sensitivity and anti-interference ability of the sensor. The current ratio between IMI and THI was calculated as the detected signal for IMI sensing. Compared with common single-signal sensing, the proposed ratiometric strategy showed a higher linear range and a lower limit of detection of 4.0 × 10-8-1.0 × 10-5 mol L-1 and 1.7 × 10-8 mol L-1, respectively, for IMI detection. On the other hand, the ratiometric strategy endowed the sensor with good accuracy, reproducibility, and stability. The sensor was also used for IMI determination in real samples with satisfactory results. The simple, effective, and reliable way reported in this study can be further used to prepare ratiometric strategy-based electrochemical sensors for the selective and sensitive detection of other compounds with good accuracy and stability.

Disclosing Mental Illness Information to a Friend: Exploring How the Disclosure Decision-Making Model Informs Strategy Selection.

PubMed

Venetis, Maria K; Chernichky-Karcher, Skye; Gettings, Patricia E

2018-06-01

Within the context of mental illness disclosure between friends, this study tested the disclosure decision-making model (DD-MM; Greene, 2009) to comprehensively investigate factors that predict disclosure enactment strategies. The DD-MM describes how individuals determine whether they will reveal or conceal non-visible health information. Processes of revealing, called disclosures, take various forms including preparation and rehearsal, directness, third-party disclosure, incremental disclosures, entrapment, and indirect mediums (Afifi & Steuber, 2009). We explore the disclosure decision-making process to understand how college students select to disclose their mental illness information with a friend. Participants were 144 students at a Midwestern university who had disclosed their mental illness information to a friend. Structural equation modeling analyses revealed that college students choose strategies based on their evaluation of information assessment and closeness, and that for some strategies, efficacy mediates the relationship between information assessment and strategy. This manuscript discusses implications of findings and suggests direction for future research.

Evaluation of Contrail Reduction Strategies Based on Environmental and Operational Costs

NASA Technical Reports Server (NTRS)

Chen, Neil Y.; Sridhar, Banavar; Ng, Hok K.; Li, Jinhua

2013-01-01

This paper evaluates a set of contrail reduction strategies based on environmental and operational costs. A linear climate model was first used to convert climate effects of carbon dioxide emissions and aircraft contrails to changes in Absolute Global Temperature Potential, a metric that measures the mean surface temperature change due to aircraft emissions and persistent contrail formations. The concept of social cost of carbon and the carbon auction price from recent California's cap-and-trade system were then used to relate the carbon dioxide emissions and contrail formations to an environmental cost index. The strategy for contrail reduction is based on minimizing contrail formations by altering the aircraft's cruising altitude. The strategy uses a user-defined factor to trade off between contrail reduction and additional fuel burn and carbon dioxide emissions. A higher value of tradeoff factor results in more contrail reduction but also more fuel burn and carbon emissions. The strategy is considered favorable when the net environmental cost benefit exceeds the operational cost. The results show how the net environmental benefit varies with different decision-making time-horizon and different carbon cost. The cost models provide a guidance to select the trade-off factor that will result in the most net environmental benefit.

Microbiome Selection Could Spur Next-Generation Plant Breeding Strategies.

PubMed

Gopal, Murali; Gupta, Alka

2016-01-01

" No plant is an island too …" Plants, though sessile, have developed a unique strategy to counter biotic and abiotic stresses by symbiotically co-evolving with microorganisms and tapping into their genome for this purpose. Soil is the bank of microbial diversity from which a plant selectively sources its microbiome to suit its needs. Besides soil, seeds, which carry the genetic blueprint of plants during trans-generational propagation, are home to diverse microbiota that acts as the principal source of microbial inoculum in crop cultivation. Overall, a plant is ensconced both on the outside and inside with a diverse assemblage of microbiota. Together, the plant genome and the genes of the microbiota that the plant harbors in different plant tissues, i.e., the 'plant microbiome,' form the holobiome which is now considered as unit of selection: 'the holobiont.' The 'plant microbiome' not only helps plants to remain fit but also offers critical genetic variability, hitherto, not employed in the breeding strategy by plant breeders, who traditionally have exploited the genetic variability of the host for developing high yielding or disease tolerant or drought resistant varieties. This fresh knowledge of the microbiome, particularly of the rhizosphere, offering genetic variability to plants, opens up new horizons for breeding that could usher in cultivation of next-generation crops depending less on inorganic inputs, resistant to insect pest and diseases and resilient to climatic perturbations. We surmise, from ever increasing evidences, that plants and their microbial symbionts need to be co-propagated as life-long partners in future strategies for plant breeding. In this perspective, we propose bottom-up approach to co-propagate the co-evolved, the plant along with the target microbiome, through - (i) reciprocal soil transplantation method, or (ii) artificial ecosystem selection method of synthetic microbiome inocula, or (iii) by exploration of microRNA transfer

A soft computing based approach using modified selection strategy for feature reduction of medical systems.

PubMed

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.

A Soft Computing Based Approach Using Modified Selection Strategy for Feature Reduction of Medical Systems

PubMed Central

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data. PMID:23573172

Engineering A-kinase Anchoring Protein (AKAP)-selective Regulatory Subunits of Protein Kinase A (PKA) through Structure-based Phage Selection*

PubMed Central

Gold, Matthew G.; Fowler, Douglas M.; Means, Christopher K.; Pawson, Catherine T.; Stephany, Jason J.; Langeberg, Lorene K.; Fields, Stanley; Scott, John D.

2013-01-01

PKA is retained within distinct subcellular environments by the association of its regulatory type II (RII) subunits with A-kinase anchoring proteins (AKAPs). Conventional reagents that universally disrupt PKA anchoring are patterned after a conserved AKAP motif. We introduce a phage selection procedure that exploits high-resolution structural information to engineer RII mutants that are selective for a particular AKAP. Selective RII (RSelect) sequences were obtained for eight AKAPs following competitive selection screening. Biochemical and cell-based experiments validated the efficacy of RSelect proteins for AKAP2 and AKAP18. These engineered proteins represent a new class of reagents that can be used to dissect the contributions of different AKAP-targeted pools of PKA. Molecular modeling and high-throughput sequencing analyses revealed the molecular basis of AKAP-selective interactions and shed new light on native RII-AKAP interactions. We propose that this structure-directed evolution strategy might be generally applicable for the investigation of other protein interaction surfaces. PMID:23625929

The role of selective attention and action selection in the development of multiple action capabilities

NASA Astrophysics Data System (ADS)

Simione, Luca; Nolfi, Stefano

2014-10-01

In this paper we illustrate how the capacity to select the most appropriate actions when handling contexts affording multiple conflicting actions can be solved either through a selective attention strategy (in which the stimuli affording alternative actions are filtered out at the perceptual level through top-down regulation) or at later processing stages through an action selection strategy (through the suppression of the premotor information eliciting alternative actions). By carrying out a series of experiments in which a neuro-robot develops an ability to choose between conflicting actions, we were able to identify the conditions that lead to the development of solutions based on one strategy or another. Overall, the results indicate that the selective attention strategy constitutes the most simple and straightforward mechanism enabling the acquisition of such capacities. Moreover, the characteristics of the adaptive/learning process influence whether the adaptive robot converges towards a selective attention and/or action selection strategy.

System-based strategies for p53 recovery.

PubMed

Azam, Muhammad Rizwan; Fazal, Sahar; Ullah, Mukhtar; Bhatti, Aamer I

2018-06-01

The authors have proposed a systems theory-based novel drug design approach for the p53 pathway. The pathway is taken as a dynamic system represented by ordinary differential equations-based mathematical model. Using control engineering practices, the system analysis and subsequent controller design is performed for the re-activation of wild-type p53. p53 revival is discussed for both modes of operation, i.e. the sustained and oscillatory. To define the problem in control system paradigm, modification in the existing mathematical model is performed to incorporate the effect of Nutlin. Attractor point analysis is carried out to select the suitable domain of attraction. A two-loop negative feedback control strategy is devised to drag the system trajectories to the attractor point and to regulate cellular concentration of Nutlin, respectively. An integrated framework is constituted to incorporate the pharmacokinetic effects of Nutlin in the cancerous cells. Bifurcation analysis is also performed on the p53 model to see the conditions for p53 oscillation.

Classifier transfer with data selection strategies for online support vector machine classification with class imbalance

NASA Astrophysics Data System (ADS)

Krell, Mario Michael; Wilshusen, Nils; Seeland, Anett; Kim, Su Kyoung

2017-04-01

Objective. Classifier transfers usually come with dataset shifts. To overcome dataset shifts in practical applications, we consider the limitations in computational resources in this paper for the adaptation of batch learning algorithms, like the support vector machine (SVM). Approach. We focus on data selection strategies which limit the size of the stored training data by different inclusion, exclusion, and further dataset manipulation criteria like handling class imbalance with two new approaches. We provide a comparison of the strategies with linear SVMs on several synthetic datasets with different data shifts as well as on different transfer settings with electroencephalographic (EEG) data. Main results. For the synthetic data, adding only misclassified samples performed astoundingly well. Here, balancing criteria were very important when the other criteria were not well chosen. For the transfer setups, the results show that the best strategy depends on the intensity of the drift during the transfer. Adding all and removing the oldest samples results in the best performance, whereas for smaller drifts, it can be sufficient to only add samples near the decision boundary of the SVM which reduces processing resources. Significance. For brain-computer interfaces based on EEG data, models trained on data from a calibration session, a previous recording session, or even from a recording session with another subject are used. We show, that by using the right combination of data selection criteria, it is possible to adapt the SVM classifier to overcome the performance drop from the transfer.

Nanobiotechnology-based delivery strategies: New frontiers in brain tumor targeted therapies.

PubMed

Mangraviti, Antonella; Gullotti, David; Tyler, Betty; Brem, Henry

2016-10-28

Despite recent technological advancements and promising preclinical experiments, brain tumor patients are still met with limited treatment options. Some of the barriers to clinical improvements include the systemic toxicity of cytotoxic compounds, the impedance of the blood brain barrier (BBB), and the lack of therapeutic agents that can selectively target the intracranial tumor environment. To overcome such barriers, a number of chemotherapeutic agents and nucleic acid-based therapies are rapidly being synthesized and tested as new brain tumor-targeted delivery strategies. Novel carriers include liposomal and polymeric nanoparticles, wafers, microchips, microparticle-based nanoplatforms and cells-based vectors. Strong preclinical results suggest that these nanotechnologies are set to transform the therapeutic paradigm for brain tumor treatment. In addition to new tumoricidal agents, parallel work is also being conducted on the BBB front. Preclinical testing of chemical and physical modulation strategies is yielding improved intracranial concentrations. New diagnostic and therapeutic imaging techniques, such as high-intensity focused ultrasound and MRI-guided focused ultrasound, are being used to modulate the BBB in a more precise and non-invasive manner. This review details some of the tremendous advances that are being explored in current brain tumor targeted therapies, including local implant development, nanobiotechnology-based delivery strategies, and techniques of BBB manipulation. Copyright © 2016 Elsevier B.V. All rights reserved.

Sodium channel selectivity and conduction: Prokaryotes have devised their own molecular strategy

PubMed Central

Finol-Urdaneta, Rocio K.; Wang, Yibo; Al-Sabi, Ahmed; Zhao, Chunfeng

2014-01-01

Striking structural differences between voltage-gated sodium (Nav) channels from prokaryotes (homotetramers) and eukaryotes (asymmetric, four-domain proteins) suggest the likelihood of different molecular mechanisms for common functions. For these two channel families, our data show similar selectivity sequences among alkali cations (relative permeability, Pion/PNa) and asymmetric, bi-ionic reversal potentials when the Na/K gradient is reversed. We performed coordinated experimental and computational studies, respectively, on the prokaryotic Nav channels NaChBac and NavAb. NaChBac shows an “anomalous,” nonmonotonic mole-fraction dependence in the presence of certain sodium–potassium mixtures; to our knowledge, no comparable observation has been reported for eukaryotic Nav channels. NaChBac’s preferential selectivity for sodium is reduced either by partial titration of its highly charged selectivity filter, when extracellular pH is lowered from 7.4 to 5.8, or by perturbation—likely steric—associated with a nominally electro-neutral substitution in the selectivity filter (E191D). Although no single molecular feature or energetic parameter appears to dominate, our atomistic simulations, based on the published NavAb crystal structure, revealed factors that may contribute to the normally observed selectivity for Na over K. These include: (a) a thermodynamic penalty to exchange one K+ for one Na+ in the wild-type (WT) channel, increasing the relative likelihood of Na+ occupying the binding site; (b) a small tendency toward weaker ion binding to the selectivity filter in Na–K mixtures, consistent with the higher conductance observed with both sodium and potassium present; and (c) integrated 1-D potentials of mean force for sodium or potassium movement that show less separation for the less selective E/D mutant than for WT. Overall, tight binding of a single favored ion to the selectivity filter, together with crucial inter-ion interactions within the pore

Strategies for integrating computer-based activities into your educational environment: a practical guide.

PubMed Central

Miller, J G; Wolf, F M

1996-01-01

Strategies for implementing instructional technology are based on recent experiences at the University of Michigan Medical Center. The issues covered include 1) addressing facilities, hardware, and staffing needs, 2) determining learners' skill requirements and appropriate training activities, and 3) selecting and customizing educational software. Many examples are provided, and nine key points for success are emphasized. PMID:8653447

Stress, Time Pressure, Strategy Selection and Math Anxiety in Mathematics: A Review of the Literature

PubMed Central

Caviola, Sara; Carey, Emma; Mammarella, Irene C.; Szucs, Denes

2017-01-01

We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth “strategy selection”) in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations), with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research. PMID:28919870

The Relationship between Preschoolers' Selective Attention and Memory for Location Strategies

ERIC Educational Resources Information Center

Blumberg, F.C.; Torenberg, M.; Randall, J.D.

2005-01-01

Late and early preschoolers' attention and spatial strategies were examined in response to instructions to recall relevant objects [Blumberg, F. C. & Torenberg, M. (2003). The impact of spatial cues on preschoolers' selective attention. Journal of Genetic Psychology, 164, 42-53] and irrelevant objects [Blumberg, F. C. & Torenberg, M. (in press).…

Do biological-based strategies hold promise to biofouling control in MBRs?

PubMed

Malaeb, Lilian; Le-Clech, Pierre; Vrouwenvelder, Johannes S; Ayoub, George M; Saikaly, Pascal E

2013-10-01

Biofouling in membrane bioreactors (MBRs) remains a primary challenge for their wider application, despite the growing acceptance of MBRs worldwide. Research studies on membrane fouling are extensive in the literature, with more than 200 publications on MBR fouling in the last 3 years; yet, improvements in practice on biofouling control and management have been remarkably slow. Commonly applied cleaning methods are only partially effective and membrane replacement often becomes frequent. The reason for the slow advancement in successful control of biofouling is largely attributed to the complex interactions of involved biological compounds and the lack of representative-for-practice experimental approaches to evaluate potential effective control strategies. Biofouling is driven by microorganisms and their associated extra-cellular polymeric substances (EPS) and microbial products. Microorganisms and their products convene together to form matrices that are commonly treated as a black box in conventional control approaches. Biological-based antifouling strategies seem to be a promising constituent of an effective integrated control approach since they target the essence of biofouling problems. However, biological-based strategies are in their developmental phase and several questions should be addressed to set a roadmap for translating existing and new information into sustainable and effective control techniques. This paper investigates membrane biofouling in MBRs from the microbiological perspective to evaluate the potential of biological-based strategies in offering viable control alternatives. Limitations of available control methods highlight the importance of an integrated anti-fouling approach including biological strategies. Successful development of these strategies requires detailed characterization of microorganisms and EPS through the proper selection of analytical tools and assembly of results. Existing microbiological/EPS studies reveal a number of

A novel 9 × 9 map-based solvent selection strategy for targeted counter-current chromatography isolation of natural products.

PubMed

Liang, Junling; Meng, Jie; Wu, Dingfang; Guo, Mengzhe; Wu, Shihua

2015-06-26

Counter-current chromatography (CCC) is an efficient liquid-liquid chromatography technique for separation and purification of complex mixtures like natural products extracts and synthetic chemicals. However, CCC is still a challenging process requiring some special technical knowledge especially in the selection of appropriated solvent systems. In this work, we introduced a new 9 × 9 map-based solvent selection strategy for CCC isolation of targets, which permit more than 60 hexane-ethyl acetate-methanol-water (HEMWat) solvent systems as the start candidates for the selection of solvent systems. Among these solvent systems, there are clear linear correlations between partition coefficient (K) and the system numbers. Thus, an appropriate CCC solvent system (i.e., sweet spot for K = 1) may be hit by measurement of k values of the target only in two random solvent systems. Besides this, surprisingly, we found that through two sweet spots, we could get a line ("Sweet line") where there are infinite sweet solvent systems being suitable for CCC separation. In these sweet solvent systems, the target has the same partition coefficient (K) but different solubilities. Thus, the better sweet solvent system with higher sample solubility can be obtained for high capacity CCC preparation. Furthermore, we found that there is a zone ("Sweet zone") where all solvent systems have their own sweet partition coefficients values for the target in range of 0.4 < K< 2.5 or extended range of 0.25 < K < 16. All results were validated by using 14 pure GUESSmix mimic natural products as standards and further confirmed by isolation of several targets including honokiol and magnolol from the extracts of Magnolia officinalis Rehd. Et Wils and tanshinone IIA from Salvia miltiorrhiza Bunge. In practice, it is much easier to get a suitable solvent system only by making a simple screening two to four HEMWat two-phase solvent systems to obtain the sweet line or sweet zone without special knowledge

An Evaluation of Statistical Strategies for Making Equating Function Selections. Research Report. ETS RR-08-60

ERIC Educational Resources Information Center

Moses, Tim

2008-01-01

Nine statistical strategies for selecting equating functions in an equivalent groups design were evaluated. The strategies of interest were likelihood ratio chi-square tests, regression tests, Kolmogorov-Smirnov tests, and significance tests for equated score differences. The most accurate strategies in the study were the likelihood ratio tests…

Design strategies of fluorescent probes for selective detection among biothiols.

PubMed

Niu, Li-Ya; Chen, Yu-Zhe; Zheng, Hai-Rong; Wu, Li-Zhu; Tung, Chen-Ho; Yang, Qing-Zheng

2015-10-07

Simple thiol derivatives, such as cysteine (Cys), homocysteine (Hcy), and glutathione (GSH), play key roles in biological processes, and the fluorescent probes to detect such thiols in vivo selectively with high sensitivity and fast response times are critical for understanding their numerous functions. However, the similar structures and reactivities of these thiols pose considerable challenges to the development of such probes. This review focuses on various strategies for the design of fluorescent probes for the selective detection of biothiols. We classify the fluorescent probes for discrimination among biothiols according to reaction types between the probes and thiols such as cyclization with aldehydes, conjugate addition-cyclization with acrylates, native chemical ligation, and aromatic substitution-rearrangement.

The Influence of Computer-Based Text Editors on the Revision Strategies of Inexperienced Writers.

ERIC Educational Resources Information Center

Collier, Richard M.

A study sought to determine the effect of computer-based text editing on the revision strategies of inexperienced writers. Four subjects, none of whom had experience with computers or word processors, were selected from an introductory college composition course and required to master the basic terminal functions that would be necessary for…

Building synthetic gene circuits from combinatorial libraries: screening and selection strategies.

PubMed

Schaerli, Yolanda; Isalan, Mark

2013-07-01

The promise of wide-ranging biotechnology applications inspires synthetic biologists to design novel genetic circuits. However, building such circuits rationally is still not straightforward and often involves painstaking trial-and-error. Mimicking the process of natural selection can help us to bridge the gap between our incomplete understanding of nature's design rules and our desire to build functional networks. By adopting the powerful method of directed evolution, which is usually applied to protein engineering, functional networks can be obtained through screening or selecting from randomised combinatorial libraries. This review first highlights the practical options to introduce combinatorial diversity into gene circuits and then examines strategies for identifying the potentially rare library members with desired functions, either by screening or selection.

The design strategy of selective PTP1B inhibitors over TCPTP.

PubMed

Li, XiangQian; Wang, LiJun; Shi, DaYong

2016-08-15

Protein tyrosine phosphatase 1B (PTP1B) has already been well studied as a highly validated therapeutic target for diabetes and obesity. However, the lack of selectivity limited further studies and clinical applications of PTP1B inhibitors, especially over T-cell protein tyrosine phosphatase (TCPTP). In this review, we enumerate the published specific inhibitors of PTP1B, discuss the structure-activity relationships by analysis of their X-ray structures or docking results, and summarize the characteristic of selectivity related residues and groups. Furthermore, the design strategy of selective PTP1B inhibitors over TCPTP is also proposed. We hope our work could provide an effective way to gain specific PTP1B inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Strategy for Developing Expert-System-Based Internet Protocols (TCP/IP)

NASA Technical Reports Server (NTRS)

Ivancic, William D.

1997-01-01

The Satellite Networks and Architectures Branch of NASA's Lewis Research is addressing the issue of seamless interoperability of satellite networks with terrestrial networks. One of the major issues is improving reliable transmission protocols such as TCP over long latency and error-prone links. Many tuning parameters are available to enhance the performance of TCP including segment size, timers and window sizes. There are also numerous congestion avoidance algorithms such as slow start, selective retransmission and selective acknowledgment that are utilized to improve performance. This paper provides a strategy to characterize the performance of TCP relative to various parameter settings in a variety of network environments (i.e. LAN, WAN, wireless, satellite, and IP over ATM). This information can then be utilized to develop expert-system-based Internet protocols.

Evaluation of delivered dose for a clinical daily adaptive plan selection strategy for bladder cancer radiotherapy.

PubMed

Lutkenhaus, Lotte J; Visser, Jorrit; de Jong, Rianne; Hulshof, Maarten C C M; Bel, Arjan

2015-07-01

To account for variable bladder size during bladder cancer radiotherapy, a daily plan selection strategy was implemented. The aim of this study was to calculate the actually delivered dose using an adaptive strategy, compared to a non-adaptive approach. Ten patients were treated to the bladder and lymph nodes with an adaptive full bladder strategy. Interpolated delineations of bladder and tumor on a full and empty bladder CT scan resulted in five PTVs for which VMAT plans were created. Daily cone beam CT (CBCT) scans were used for plan selection. Bowel, rectum and target volumes were delineated on these CBCTs, and delivered dose for these was calculated using both the adaptive plan, and a non-adaptive plan. Target coverage for lymph nodes improved using an adaptive strategy. The full bladder strategy spared the healthy part of the bladder from a high dose. Average bowel cavity V30Gy and V40Gy significantly reduced with 60 and 69ml, respectively (p<0.01). Other parameters for bowel and rectum remained unchanged. Daily plan selection compared to a non-adaptive strategy yielded similar bladder coverage and improved coverage for lymph nodes, with a significant reduction in bowel cavity V30Gy and V40Gy only, while other sparing was limited. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

GWASinlps: Nonlocal prior based iterative SNP selection tool for genome-wide association studies.

PubMed

Sanyal, Nilotpal; Lo, Min-Tzu; Kauppi, Karolina; Djurovic, Srdjan; Andreassen, Ole A; Johnson, Valen E; Chen, Chi-Hua

2018-06-19

Multiple marker analysis of the genome-wide association study (GWAS) data has gained ample attention in recent years. However, because of the ultra high-dimensionality of GWAS data, such analysis is challenging. Frequently used penalized regression methods often lead to large number of false positives, whereas Bayesian methods are computationally very expensive. Motivated to ameliorate these issues simultaneously, we consider the novel approach of using nonlocal priors in an iterative variable selection framework. We develop a variable selection method, named, iterative nonlocal prior based selection for GWAS, or GWASinlps, that combines, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on some association learning and the parsimonious uncertainty quantification provided by the use of nonlocal priors. The hallmark of our method is the introduction of 'structured screen-and-select' strategy, that considers hierarchical screening, which is not only based on response-predictor associations, but also based on response-response associations, and concatenates variable selection within that hierarchy. Extensive simulation studies with SNPs having realistic linkage disequilibrium structures demonstrate the advantages of our computationally efficient method compared to several frequentist and Bayesian variable selection methods, in terms of true positive rate, false discovery rate, mean squared error, and effect size estimation error. Further, we provide empirical power analysis useful for study design. Finally, a real GWAS data application was considered with human height as phenotype. An R-package for implementing the GWASinlps method is available at https://cran.r-project.org/web/packages/GWASinlps/index.html. Supplementary data are available at Bioinformatics online.

How Metastrategic Considerations Influence the Selection of Frequency Estimation Strategies

ERIC Educational Resources Information Center

Brown, Norman R.

2008-01-01

Prior research indicates that enumeration-based frequency estimation strategies become increasingly common as memory for relevant event instances improves and that moderate levels of context memory are associated with moderate rates of enumeration [Brown, N. R. (1995). Estimation strategies and the judgment of event frequency. Journal of…

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

PubMed

Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

Strategies in Development and Delivery of Nanotechnology Based Cosmetic Products.

PubMed

Ahmad, Usama; Ahmad, Zeeshan; Khan, Ahmed Abdullah; Akhtar, Juber; Singh, Satya Prakash; Ahmad, Farhan Jalees

2018-03-26

The science of formulation involving cosmetic ingredients has always been a challenge since the release of active components greatly depends upon the carrier system involved and the selectivity of skin barrier. The principle obstacle of the skin resides in the epidermis and it's hard for many active components to cross it. The formulation related factors like size of particles, viscosity and lipophilicity of the components also play an important role in permeation of the dermal composition. Though widely used; conventional creams and gels still struggle in terms of success. This work focuses on nano based formulation strategies for successful delivery of cosmetic agents. Novel strategies like nanoemulsion, nanogels, liposomes, aquasomes, niosomes, dendrimers and fullerenes have paved way for successful delivery of dermal formulations to desire depths in the skin. © Georg Thieme Verlag KG Stuttgart · New York.

Early Invasive Versus Selective Strategy for Non-ST-Segment Elevation Acute Coronary Syndrome: The ICTUS Trial.

PubMed

Hoedemaker, Niels P G; Damman, Peter; Woudstra, Pier; Hirsch, Alexander; Windhausen, Fons; Tijssen, Jan G P; de Winter, Robbert J

2017-04-18

The ICTUS (Invasive Versus Conservative Treatment in Unstable Coronary Syndromes) trial compared early invasive strategy with a selective invasive strategy in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and an elevated cardiac troponin T. No long-term benefit of an early invasive strategy was found at 1 and 5 years. The aim of this study was to determine the 10-year clinical outcomes of an early invasive strategy versus a selective invasive strategy in patients with NSTE-ACS and an elevated cardiac troponin T. The ICTUS trial was a multicenter, randomized controlled clinical trial that included 1,200 patients with NSTE-ACS and an elevated cardiac troponin T. Enrollment was from July 2001 to August 2003. We collected 10-year follow-up of death, myocardial infarction (MI), and revascularization through the Dutch population registry, patient phone calls, general practitioners, and hospital records. The primary outcome was the 10-year composite of death or spontaneous MI. Additional outcomes included the composite of death or MI, death, MI (spontaneous and procedure-related), and revascularization. Ten-year death or spontaneous MI was not statistically different between the 2 groups (33.8% vs. 29.0%, hazard ratio [HR]: 1.12; 95% confidence interval [CI]: 0.97 to 1.46; p = 0.11). Revascularization occurred in 82.6% of the early invasive group and 60.5% in the selective invasive group. There were no differences in additional outcomes, except for a higher rate of death or MI in the early invasive group compared with the rates for the selective invasive group (37.6% vs. 30.5%; HR: 1.30; 95% CI: 1.07 to 1.58; p = 0.009), driven by a higher rate of procedure-related MI in the early invasive group (6.5% vs. 2.4%; HR: 2.82; 95% CI: 1.53 to 5.20; p = 0.001). In patients with NSTE-ACS and elevated cardiac troponin T levels, an early invasive strategy has no benefit over a selective invasive strategy in reducing the 10-year composite outcome of

Cell-Based Strategies for Meniscus Tissue Engineering

PubMed Central

Niu, Wei; Guo, Weimin; Han, Shufeng; Zhu, Yun; Liu, Shuyun; Guo, Quanyi

2016-01-01

Meniscus injuries remain a significant challenge due to the poor healing potential of the inner avascular zone. Following a series of studies and clinical trials, tissue engineering is considered a promising prospect for meniscus repair and regeneration. As one of the key factors in tissue engineering, cells are believed to be highly beneficial in generating bionic meniscus structures to replace injured ones in patients. Therefore, cell-based strategies for meniscus tissue engineering play a fundamental role in meniscal regeneration. According to current studies, the main cell-based strategies for meniscus tissue engineering are single cell type strategies; cell coculture strategies also were applied to meniscus tissue engineering. Likewise, on the one side, the zonal recapitulation strategies based on mimicking meniscal differing cells and internal architectures have received wide attentions. On the other side, cell self-assembling strategies without any scaffolds may be a better way to build a bionic meniscus. In this review, we primarily discuss cell seeds for meniscus tissue engineering and their application strategies. We also discuss recent advances and achievements in meniscus repair experiments that further improve our understanding of meniscus tissue engineering. PMID:27274735

Selection of head and whisker coordination strategies during goal-oriented active touch.

PubMed

Schroeder, Joseph B; Ritt, Jason T

2016-04-01

In the rodent whisker system, a key model for neural processing and behavioral choices during active sensing, whisker motion is increasingly recognized as only part of a broader motor repertoire employed by rodents during active touch. In particular, recent studies suggest whisker and head motions are tightly coordinated. However, conditions governing the selection and temporal organization of such coordinated sensing strategies remain poorly understood. We videographically reconstructed head and whisker motions of freely moving mice searching for a randomly located rewarded aperture, focusing on trials in which animals appeared to rapidly "correct" their trajectory under tactile guidance. Mice orienting after unilateral contact repositioned their whiskers similarly to previously reported head-turning asymmetry. However, whisker repositioning preceded head turn onsets and was not bilaterally symmetric. Moreover, mice selectively employed a strategy we term contact maintenance, with whisking modulated to counteract head motion and facilitate repeated contacts on subsequent whisks. Significantly, contact maintenance was not observed following initial contact with an aperture boundary, when the mouse needed to make a large corrective head motion to the front of the aperture, but only following contact by the same whisker field with the opposite aperture boundary, when the mouse needed to precisely align its head with the reward spout. Together these results suggest that mice can select from a diverse range of sensing strategies incorporating both knowledge of the task and whisk-by-whisk sensory information and, moreover, suggest the existence of high level control (not solely reflexive) of sensing motions coordinated between multiple body parts. Copyright © 2016 the American Physiological Society.

Selection of head and whisker coordination strategies during goal-oriented active touch

PubMed Central

2016-01-01

In the rodent whisker system, a key model for neural processing and behavioral choices during active sensing, whisker motion is increasingly recognized as only part of a broader motor repertoire employed by rodents during active touch. In particular, recent studies suggest whisker and head motions are tightly coordinated. However, conditions governing the selection and temporal organization of such coordinated sensing strategies remain poorly understood. We videographically reconstructed head and whisker motions of freely moving mice searching for a randomly located rewarded aperture, focusing on trials in which animals appeared to rapidly “correct” their trajectory under tactile guidance. Mice orienting after unilateral contact repositioned their whiskers similarly to previously reported head-turning asymmetry. However, whisker repositioning preceded head turn onsets and was not bilaterally symmetric. Moreover, mice selectively employed a strategy we term contact maintenance, with whisking modulated to counteract head motion and facilitate repeated contacts on subsequent whisks. Significantly, contact maintenance was not observed following initial contact with an aperture boundary, when the mouse needed to make a large corrective head motion to the front of the aperture, but only following contact by the same whisker field with the opposite aperture boundary, when the mouse needed to precisely align its head with the reward spout. Together these results suggest that mice can select from a diverse range of sensing strategies incorporating both knowledge of the task and whisk-by-whisk sensory information and, moreover, suggest the existence of high level control (not solely reflexive) of sensing motions coordinated between multiple body parts. PMID:26792880

Cost-Effectiveness Analysis of Hepatitis B Vaccination Strategies to Prevent Perinatal Transmission in North Korea: Selective Vaccination vs. Universal Vaccination.

PubMed

Lee, Donghoon; Park, Sang Min

2016-01-01

To tackle the high prevalence of Hepatitis B virus (HBV) infection in North Korea, it is essential that birth doses of HBV vaccines should be administered within 24 hours of birth. As the country fails to provide a Timely Birth Dose (TBD) of HBV vaccine, the efforts of reducing the high prevalence of HBV have been significantly hampered. To examine the cost-effectiveness of vaccination strategies to prevent perinatal transmission of HBV in North Korea, we established a decision tree with a Markov model consisting of selective, universal, and the country's current vaccination program against HBV. The cost-effectiveness analysis was performed from societal and payer's perspectives and evaluated by Disability Adjusted Life Year (DALY). The results suggest that introducing the universal vaccination would prevent 1,866 cases of perinatal infections per 100,000 of the birth cohort of 2013. Furthermore, 900 cases of perinatal infections per 100,000 could be additionally averted if switching to the selective vaccination. The current vaccination is a dominated strategy both from the societal and payer's perspective. The Incremental Cost-Effectiveness Ratio (ICER) between universal and selective vaccination is $267 from the societal perspective and is reported as $273 from the payer's perspective. Based on the assumption that the 2012 Gross Domestic Product (GDP) per capita in North Korea, $582.6 was set for cost-effectiveness criteria, the result of this study indicates that selective vaccination may be a highly cost-effective strategy compared to universal vaccination.

SHAPE Selection (SHAPES) enrich for RNA structure signal in SHAPE sequencing-based probing data

PubMed Central

Poulsen, Line Dahl; Kielpinski, Lukasz Jan; Salama, Sofie R.; Krogh, Anders; Vinther, Jeppe

2015-01-01

Selective 2′ Hydroxyl Acylation analyzed by Primer Extension (SHAPE) is an accurate method for probing of RNA secondary structure. In existing SHAPE methods, the SHAPE probing signal is normalized to a no-reagent control to correct for the background caused by premature termination of the reverse transcriptase. Here, we introduce a SHAPE Selection (SHAPES) reagent, N-propanone isatoic anhydride (NPIA), which retains the ability of SHAPE reagents to accurately probe RNA structure, but also allows covalent coupling between the SHAPES reagent and a biotin molecule. We demonstrate that SHAPES-based selection of cDNA–RNA hybrids on streptavidin beads effectively removes the large majority of background signal present in SHAPE probing data and that sequencing-based SHAPES data contain the same amount of RNA structure data as regular sequencing-based SHAPE data obtained through normalization to a no-reagent control. Moreover, the selection efficiently enriches for probed RNAs, suggesting that the SHAPES strategy will be useful for applications with high-background and low-probing signal such as in vivo RNA structure probing. PMID:25805860

Dynamic Portfolio Strategy Using Clustering Approach

PubMed Central

Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market. PMID:28129333

Dynamic Portfolio Strategy Using Clustering Approach.

PubMed

Ren, Fei; Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

The key role of extinction learning in anxiety disorders: behavioral strategies to enhance exposure-based treatments.

PubMed

Pittig, Andre; van den Berg, Linda; Vervliet, Bram

2016-01-01

Extinction learning is a major mechanism for fear reduction by means of exposure. Current research targets innovative strategies to enhance fear extinction and thereby optimize exposure-based treatments for anxiety disorders. This selective review updates novel behavioral strategies that may provide cutting-edge clinical implications. Recent studies provide further support for two types of enhancement strategies. Procedural enhancement strategies implemented during extinction training translate to how exposure exercises may be conducted to optimize fear extinction. These strategies mostly focus on a maximized violation of dysfunctional threat expectancies and on reducing context and stimulus specificity of extinction learning. Flanking enhancement strategies target periods before and after extinction training and inform optimal preparation and post-processing of exposure exercises. These flanking strategies focus on the enhancement of learning in general, memory (re-)consolidation, and memory retrieval. Behavioral strategies to enhance fear extinction may provide powerful clinical applications to further maximize the efficacy of exposure-based interventions. However, future replications, mechanistic examinations, and translational studies are warranted to verify long-term effects and naturalistic utility. Future directions also comprise the interplay of optimized fear extinction with (avoidance) behavior and motivational antecedents of exposure.

Selectivity as an Emotion Regulation Strategy: Lessons from Older Adults

PubMed Central

Sims, Tamara; Hogan, Candice; Carstensen, Laura

2015-01-01

Findings based on studies of daily life consistently associate older ages with relatively positive emotional experience, suggesting that older adults may regulate emotions more effectively than younger adults. Findings from laboratory studies are equivocal, however, with mixed evidence for age-related improvements in use of emotion regulatory strategies. In the current paper, we propose that findings may reflect a failure of laboratory-based experiments to capture the regulatory strategies that older people use in their everyday lives. We argue that the advantages older people have are likely due to antecedent emotion regulation as opposed to response-focused strategies. Understanding the regulatory approaches that older people actually use may inform developmental models of emotion regulation throughout adulthood as well as interventions for improving emotional experience across the life span. PMID:25914897

Genetic gain and economic values of selection strategies including semen traits in three- and four-way crossbreeding systems for swine production.

PubMed

González-Peña, D; Knox, R V; MacNeil, M D; Rodriguez-Zas, S L

2015-03-01

Four semen traits: volume (VOL), concentration (CON), progressive motility of spermatozoa (MOT), and abnormal spermatozoa (ABN) provide complementary information on boar fertility. Assessment of the impact of selection for semen traits is hindered by limited information on economic parameters. Objectives of this study were to estimate economic values for semen traits and to evaluate the genetic gain when these traits are incorporated into traditional selection strategies in a 3-tier system of swine production. Three-way (maternal nucleus lines A and B and paternal nucleus line C) and 4-way (additional paternal nucleus line D) crossbreeding schemes were compared. A novel population structure that accommodated selection for semen traits was developed. Three selection strategies were simulated. Selection Strategy I (baseline) encompassed selection for maternal traits: number of pigs born alive (NBA), litter birth weight (LBW), adjusted 21-d litter weight (A21), and number of pigs at 21 d (N21); and paternal traits: number of days to 113.5 kg (D113), backfat (BF), ADG, feed efficiency (FE), and carcass lean % (LEAN). Selection Strategy II included Strategy I and the number of usable semen doses per collection (DOSES), a function of the 4 semen traits. Selection Strategy III included Strategy I and the 4 semen traits individually. The estimated economic values of VOL, CON, MOT, ABN, and DOSES for 7 to 1 collections/wk ranged from $0.21 to $1.44/mL, $0.12 to $0.83/10 spermatozoa/mm, $0.61 to $12.66/%, -$0.53 to -$10.88/%, and $2.01 to $41.43/%, respectively. The decrease in the relative economic values of semen traits and DOSES with higher number of collections per wk was sharper between 1 and 2.33 collections/wk than between 2.33 and 7 collections/wk. The higher economic value of MOT and ABN relative to VOL and CON could be linked to the genetic variances and covariances of these traits. Average genetic gains for the maternal traits were comparable across strategies

Fundamental Vocabulary Selection Based on Word Familiarity

NASA Astrophysics Data System (ADS)

Sato, Hiroshi; Kasahara, Kaname; Kanasugi, Tomoko; Amano, Shigeaki

This paper proposes a new method for selecting fundamental vocabulary. We are presently constructing the Fundamental Vocabulary Knowledge-base of Japanese that contains integrated information on syntax, semantics and pragmatics, for the purposes of advanced natural language processing. This database mainly consists of a lexicon and a treebank: Lexeed (a Japanese Semantic Lexicon) and the Hinoki Treebank. Fundamental vocabulary selection is the first step in the construction of Lexeed. The vocabulary should include sufficient words to describe general concepts for self-expandability, and should not be prohibitively large to construct and maintain. There are two conventional methods for selecting fundamental vocabulary. The first is intuition-based selection by experts. This is the traditional method for making dictionaries. A weak point of this method is that the selection strongly depends on personal intuition. The second is corpus-based selection. This method is superior in objectivity to intuition-based selection, however, it is difficult to compile a sufficiently balanced corpora. We propose a psychologically-motivated selection method that adopts word familiarity as the selection criterion. Word familiarity is a rating that represents the familiarity of a word as a real number ranging from 1 (least familiar) to 7 (most familiar). We determined the word familiarity ratings statistically based on psychological experiments over 32 subjects. We selected about 30,000 words as the fundamental vocabulary, based on a minimum word familiarity threshold of 5. We also evaluated the vocabulary by comparing its word coverage with conventional intuition-based and corpus-based selection over dictionary definition sentences and novels, and demonstrated the superior coverage of our lexicon. Based on this, we conclude that the proposed method is superior to conventional methods for fundamental vocabulary selection.

Platinum-based anticancer agents: innovative design strategies and biological perspectives.

PubMed

Ho, Yee-Ping; Au-Yeung, Steve C F; To, Kenneth K W

2003-09-01

The impact of cisplatin on cancer chemotherapy cannot be denied. Over the past 20 years, much effort has been dedicated to discover new platinum-based anticancer agents that are superior to cisplatin or its analogue, carboplatin. Most structural modifications are based on changing one or both of the ligand types coordinated to platinum. Altering the leaving group can influence tissue and intracellular distribution of the drug, whereas the carrier ligand usually determines the structure of adducts formed with DNA. DNA-Pt adducts produced by cisplatin and many of its classical analogues are almost identical, and would explain their similar patterns of tumor sensitivity and susceptibility to resistance. Recently some highly innovative design strategies have emerged, aimed at overcoming platinum resistance and/or to introduce novel mechanisms of antitumor action. Platinum compounds bearing the 1,2-diaminocyclohexane carrier ligand; and those of multinuclear Pt complexes giving rise to radically different DNA-Pt adducts, have resulted in novel anticancer agents capable of circumventing cisplatin resistance. Other strategies have focused on integrating biologically active ligands with platinum moieties intended to selectively localizing the anticancer properties. With the rapid advance in molecular biology, combined with innovation, it is possible new Pt-based anticancer agents will materialize in the near future. Copyright 2003 Wiley Periodicals, Inc.

Quantitative learning strategies based on word networks

NASA Astrophysics Data System (ADS)

Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

2018-02-01

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

Detecting selection effects in community implementations of family-based substance abuse prevention programs.

PubMed

Hill, Laura G; Goates, Scott G; Rosenman, Robert

2010-04-01

To calculate valid estimates of the costs and benefits of substance abuse prevention programs, selection effects must be identified and corrected. A supplemental comparison sample is typically used for this purpose, but in community-based program implementations, such a sample is often not available. We present an evaluation design and analytic approach that can be used in program evaluations of real-world implementations to identify selection effects, which in turn can help inform recruitment strategies, pinpoint possible selection influences on measured program outcomes, and refine estimates of program costs and benefits. We illustrate our approach with data from a multisite implementation of a popular substance abuse prevention program. Our results indicate that the program's participants differed significantly from the population at large.

Neural Architecture of Selective Stopping Strategies: Distinct Brain Activity Patterns Are Associated with Attentional Capture But Not with Outright Stopping.

PubMed

Sebastian, Alexandra; Rössler, Kora; Wibral, Michael; Mobascher, Arian; Lieb, Klaus; Jung, Patrick; Tüscher, Oliver

2017-10-04

In stimulus-selective stop-signal tasks, the salient stop signal needs attentional processing before genuine response inhibition is completed. Differential prefrontal involvement in attentional capture and response inhibition has been linked to the right inferior frontal junction (IFJ) and ventrolateral prefrontal cortex (VLPFC), respectively. Recently, it has been suggested that stimulus-selective stopping may be accomplished by the following different strategies: individuals may selectively inhibit their response only upon detecting a stop signal (independent discriminate then stop strategy) or unselectively whenever detecting a stop or attentional capture signal (stop then discriminate strategy). Alternatively, the discrimination process of the critical signal (stop vs attentional capture signal) may interact with the go process (dependent discriminate then stop strategy). Those different strategies might differentially involve attention- and stopping-related processes that might be implemented by divergent neural networks. This should lead to divergent activation patterns and, if disregarded, interfere with analyses in neuroimaging studies. To clarify this crucial issue, we studied 87 human participants of both sexes during a stimulus-selective stop-signal task and performed strategy-dependent functional magnetic resonance imaging analyses. We found that, regardless of the strategy applied, outright stopping displayed indistinguishable brain activation patterns. However, during attentional capture different strategies resulted in divergent neural activation patterns with variable activation of right IFJ and bilateral VLPFC. In conclusion, the neural network involved in outright stopping is ubiquitous and independent of strategy, while different strategies impact on attention-related processes and underlying neural network usage. Strategic differences should therefore be taken into account particularly when studying attention-related processes in stimulus-selective

Cost-Effectiveness Analysis of Hepatitis B Vaccination Strategies to Prevent Perinatal Transmission in North Korea: Selective Vaccination vs. Universal Vaccination

PubMed Central

Lee, Donghoon; Park, Sang Min

2016-01-01

Background To tackle the high prevalence of Hepatitis B virus (HBV) infection in North Korea, it is essential that birth doses of HBV vaccines should be administered within 24 hours of birth. As the country fails to provide a Timely Birth Dose (TBD) of HBV vaccine, the efforts of reducing the high prevalence of HBV have been significantly hampered. Methods To examine the cost-effectiveness of vaccination strategies to prevent perinatal transmission of HBV in North Korea, we established a decision tree with a Markov model consisting of selective, universal, and the country’s current vaccination program against HBV. The cost-effectiveness analysis was performed from societal and payer’s perspectives and evaluated by Disability Adjusted Life Year (DALY). Results The results suggest that introducing the universal vaccination would prevent 1,866 cases of perinatal infections per 100,000 of the birth cohort of 2013. Furthermore, 900 cases of perinatal infections per 100,000 could be additionally averted if switching to the selective vaccination. The current vaccination is a dominated strategy both from the societal and payer’s perspective. The Incremental Cost-Effectiveness Ratio (ICER) between universal and selective vaccination is $267 from the societal perspective and is reported as $273 from the payer’s perspective. Conclusion Based on the assumption that the 2012 Gross Domestic Product (GDP) per capita in North Korea, $582.6 was set for cost-effectiveness criteria, the result of this study indicates that selective vaccination may be a highly cost-effective strategy compared to universal vaccination. PMID:27802340

Feature selection method based on multi-fractal dimension and harmony search algorithm and its application

NASA Astrophysics Data System (ADS)

Zhang, Chen; Ni, Zhiwei; Ni, Liping; Tang, Na

2016-10-01

Feature selection is an important method of data preprocessing in data mining. In this paper, a novel feature selection method based on multi-fractal dimension and harmony search algorithm is proposed. Multi-fractal dimension is adopted as the evaluation criterion of feature subset, which can determine the number of selected features. An improved harmony search algorithm is used as the search strategy to improve the efficiency of feature selection. The performance of the proposed method is compared with that of other feature selection algorithms on UCI data-sets. Besides, the proposed method is also used to predict the daily average concentration of PM2.5 in China. Experimental results show that the proposed method can obtain competitive results in terms of both prediction accuracy and the number of selected features.

In silico strategies for the selection of chelating compounds with potential application in metal-promoted neurodegenerative diseases

NASA Astrophysics Data System (ADS)

Rodríguez-Rodríguez, Cristina; Rimola, Albert; Alí-Torres, Jorge; Sodupe, Mariona; González-Duarte, Pilar

2011-01-01

The development of new strategies to find commercial molecules with promising biochemical features is a main target in the field of biomedicine chemistry. In this work we present an in silico-based protocol that allows identifying commercial compounds with suitable metal coordinating and pharmacokinetic properties to act as metal-ion chelators in metal-promoted neurodegenerative diseases (MpND). Selection of the chelating ligands is done by combining quantum chemical calculations with the search of commercial compounds on different databases via virtual screening. Starting from different designed molecular frameworks, which mainly constitute the binding site, the virtual screening on databases facilitates the identification of different commercial molecules that enclose such scaffolds and, by imposing a set of chemical and pharmacokinetic filters, obey some drug-like requirements mandatory to deal with MpND. The quantum mechanical calculations are useful to gauge the chelating properties of the selected candidate molecules by determining the structure of metal complexes and evaluating their stability constants. With the proposed strategy, commercial compounds containing N and S donor atoms in the binding sites and capable to cross the BBB have been identified and their chelating properties analyzed.

Metasurface-based angle-selective multichannel acoustic refractor

NASA Astrophysics Data System (ADS)

Liu, Bingyi; Jiang, Yongyuan

2018-05-01

We theoretically study the angle-selective refractions of an impedance-matched acoustic gradient-index metasurface, which is integrated with a rigid bar array of a deep subwavelength period. An interesting refraction order appears under the all-angle incidence despite the existence of a critical angle, and notably, the odevity of the phase-discretization level apparently selects the transmitted diffraction orders. We utilize the strategy of multilayered media design to realize a three-channel acoustic refractor, which shows good promise for constructing multifunctional diffractive acoustic elements for acoustic communication.

A Novel Harmony Search Algorithm Based on Teaching-Learning Strategies for 0-1 Knapsack Problems

PubMed Central

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an

2014-01-01

To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems. In the HSTL algorithm, firstly, a method is presented to adjust dimension dynamically for selected harmony vector in optimization procedure. In addition, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation) are employed to improve the performance of HS algorithm. Another improvement in HSTL method is that the dynamic strategies are adopted to change the parameters, which maintains the proper balance effectively between global exploration power and local exploitation power. Finally, simulation experiments with 13 knapsack problems show that the HSTL algorithm can be an efficient alternative for solving 0-1 knapsack problems. PMID:24574905

A novel harmony search algorithm based on teaching-learning strategies for 0-1 knapsack problems.

PubMed

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an

2014-01-01

To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems. In the HSTL algorithm, firstly, a method is presented to adjust dimension dynamically for selected harmony vector in optimization procedure. In addition, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation) are employed to improve the performance of HS algorithm. Another improvement in HSTL method is that the dynamic strategies are adopted to change the parameters, which maintains the proper balance effectively between global exploration power and local exploitation power. Finally, simulation experiments with 13 knapsack problems show that the HSTL algorithm can be an efficient alternative for solving 0-1 knapsack problems.

Model building strategy for logistic regression: purposeful selection.

PubMed

Zhang, Zhongheng

2016-03-01

Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

Testing Strategies for Model-Based Development

NASA Technical Reports Server (NTRS)

Heimdahl, Mats P. E.; Whalen, Mike; Rajan, Ajitha; Miller, Steven P.

2006-01-01

This report presents an approach for testing artifacts generated in a model-based development process. This approach divides the traditional testing process into two parts: requirements-based testing (validation testing) which determines whether the model implements the high-level requirements and model-based testing (conformance testing) which determines whether the code generated from a model is behaviorally equivalent to the model. The goals of the two processes differ significantly and this report explores suitable testing metrics and automation strategies for each. To support requirements-based testing, we define novel objective requirements coverage metrics similar to existing specification and code coverage metrics. For model-based testing, we briefly describe automation strategies and examine the fault-finding capability of different structural coverage metrics using tests automatically generated from the model.

Evidence-Based Classroom Behaviour Management Strategies

ERIC Educational Resources Information Center

Parsonson, Barry S.

2012-01-01

This paper reviews a range of evidence-based strategies for application by teachers to reduce disruptive and challenging behaviours in their classrooms. These include a number of antecedent strategies intended to help minimise the emergence of problematic behaviours and a range of those which provide positive consequences for appropriate student…

Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.

Selective harmonic elimination strategy in eleven level inverter for PV system with unbalanced DC sources

NASA Astrophysics Data System (ADS)

Ghoudelbourk, Sihem.; Dib, D.; Meghni, B.; Zouli, M.

2017-02-01

The paper deals with the multilevel converters control strategy for photovoltaic system integrated in distribution grids. The objective of the proposed work is to design multilevel inverters for solar energy applications so as to reduce the Total Harmonic Distortion (THD) and to improve the power quality. The multilevel inverter power structure plays a vital role in every aspect of the power system. It is easier to produce a high-power, high-voltage inverter with the multilevel structure. The topologies of multilevel inverter have several advantages such as high output voltage, lower total harmonic distortion (THD) and reduction of voltage ratings of the power semiconductor switching devices. The proposed control strategy ensures an implementation of selective harmonic elimination (SHE) modulation for eleven levels. SHE is a very important and efficient strategy of eliminating selected harmonics by judicious selection of the firing angles of the inverter. Harmonics elimination technique eliminates the need of the expensive low pass filters in the system. Previous research considered that constant and equal DC sources with invariant behavior; however, this research extends earlier work to include variant DC sources, which are typical of lead-acid batteries when used in system PV. This Study also investigates methods to minimize the total harmonic distortion of the synthesized multilevel waveform and to help balance the battery voltage. The harmonic elimination method was used to eliminate selected lower dominant harmonics resulting from the inverter switching action.

Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries †

PubMed Central

Gutiérrez-López-Franca, Carlos; Hervás, Ramón; Johnson, Esperanza

2018-01-01

This paper aims to improve activity recognition systems based on skeletal tracking through the study of two different strategies (and its combination): (a) specialized body parts analysis and (b) stricter restrictions for the most easily detectable activities. The study was performed using the Extended Body-Angles Algorithm, which is able to analyze activities using only a single key sample. This system allows to select, for each considered activity, which are its relevant joints, which makes it possible to monitor the body of the user selecting only a subset of the same. But this feature of the system has both advantages and disadvantages. As a consequence, in the past we had some difficulties with the recognition of activities that only have a small subset of the joints of the body as relevant. The goal of this work, therefore, is to analyze the effect produced by the application of several strategies on the results of an activity recognition system based on skeletal tracking joint oriented devices. Strategies that we applied with the purpose of improve the recognition rates of the activities with a small subset of relevant joints. Through the results of this work, we aim to give the scientific community some first indications about which considered strategy is better. PMID:29789478

On the Application of Different Event-Based Sampling Strategies to the Control of a Simple Industrial Process

PubMed Central

Sánchez, José; Guarnes, Miguel Ángel; Dormido, Sebastián

2009-01-01

This paper is an experimental study of the utilization of different event-based strategies for the automatic control of a simple but very representative industrial process: the level control of a tank. In an event-based control approach it is the triggering of a specific event, and not the time, that instructs the sensor to send the current state of the process to the controller, and the controller to compute a new control action and send it to the actuator. In the document, five control strategies based on different event-based sampling techniques are described, compared, and contrasted with a classical time-based control approach and a hybrid one. The common denominator in the time, the hybrid, and the event-based control approaches is the controller: a proportional-integral algorithm with adaptations depending on the selected control approach. To compare and contrast each one of the hybrid and the pure event-based control algorithms with the time-based counterpart, the two tasks that a control strategy must achieve (set-point following and disturbance rejection) are independently analyzed. The experimental study provides new proof concerning the ability of event-based control strategies to minimize the data exchange among the control agents (sensors, controllers, actuators) when an error-free control of the process is not a hard requirement. PMID:22399975

A quantitative model of optimal data selection in Wason's selection task.

PubMed

Hattori, Masasi

2002-10-01

The optimal data selection model proposed by Oaksford and Chater (1994) successfully formalized Wason's selection task (Wason, 1966). The model, however, involved some questionable assumptions and was also not sufficient as a model of the task because it could not provide quantitative predictions of the card selection frequencies. In this paper, the model was revised to provide quantitative fits to the data. The model can predict the selection frequencies of cards based on a selection tendency function (STF), or conversely, it enables the estimation of subjective probabilities from data. Past experimental data were first re-analysed based on the model. In Experiment 1, the superiority of the revised model was shown. However, when the relationship between antecedent and consequent was forced to deviate from the biconditional form, the model was not supported. In Experiment 2, it was shown that sufficient emphasis on probabilistic information can affect participants' performance. A detailed experimental method to sort participants by probabilistic strategies was introduced. Here, the model was supported by a subgroup of participants who used the probabilistic strategy. Finally, the results were discussed from the viewpoint of adaptive rationality.

LPTA Versus Tradeoff: Analysis of Contract Source Selection Strategies and Performance Outcomes

DTIC Science & Technology

2016-06-01

methodologies contracting professionals employ to acquire what the DOD needs. Contracting professionals may use lowest price technically acceptable (LPTA) and...contract management process, source selection, lowest price technically acceptable, tradeoff 15. NUMBER OF PAGES 69 16. PRICE CODE 17. SECURITY...use lowest price technically acceptable (LPTA) and tradeoff strategies to procure requirements to maximize the overall best value to the government

RNA interference-based therapeutics: new strategies to fight infectious disease.

PubMed

López-Fraga, M; Wright, N; Jiménez, A

2008-12-01

For many years, there has been an ongoing search for new compounds that can selectively alter gene expression as a new way to treat human disease by addressing targets that are otherwise "undruggable" with traditional pharmaceutical approaches involving small molecules or proteins. RNA interference (RNAi) strategies have raised a lot of attention and several compounds are currently being tested in clinical trials. Viruses are the obvious target for RNAi-therapy, as most are difficult to treat with conventional drugs, they become rapidly resistant to drug treatment and their genes differ substantially from human genes, minimizing side effects. Antisense strategy offers very high target specificity, i.e., any viral sequence could potentially be targeted using the complementary oligonucleotide sequence. Consequently, new antisense-based therapeutics have the potential to lead a revolution in the anti-infective drug development field. Additionally, the relatively short turnaround for efficacy testing of potential RNAi molecules and that any pathogen is theoretically amenable to rapid targeting, make them invaluable tools for treating a wide range of diseases. This review will focus on some of the current efforts to treat infectious disease with RNAi-based therapies and some of the obstacles that have appeared on the road to successful clinical intervention.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

NASA Astrophysics Data System (ADS)

Xiang, Lin

incomplete and many relationships among the model ideas had not been well established by the end of the study. Most of them did not treat the natural selection model as a whole but only focused on some ideas within the model. Very few of them could scientifically apply the natural selection model to interpret other evolutionary phenomena. The findings about participating students' programming processes revealed these processes were composed of consecutive programming cycles. The cycle typically included posing a task, constructing and running program codes, and examining the resulting simulation. Students held multiple ideas and applied various programming strategies in these cycles. Students were involved in MBI at each step of a cycle. Three types of ideas, six programming strategies and ten MBI actions were identified out of the processes. The relationships among these ideas, strategies and actions were also identified and described. Findings suggested that ABPM activities could support MBI by (1) exposing students' personal models and understandings, (2) provoking and supporting a series of model-based inquiry activities, such as elaborating target phenomena, abstracting patterns, and revising conceptual models, and (3) provoking and supporting tangible and productive conversations among students, as well as between the instructor and students. Findings also revealed three programming behaviors that appeared to impede productive MBI, including (1) solely phenomenon-orientated programming, (2) transplanting program codes, and (3) blindly running procedures. Based on the findings, I propose a general modeling process in ABPM activities, summarize the ways in which MBI can be supported in ABPM activities and constrained by multiple factors, and suggest the implications of this study in the future ABPM-assisted science instructional design and research.

Investigating the Effectiveness of Teaching Methods Based on a Four-Step Constructivist Strategy

NASA Astrophysics Data System (ADS)

Çalik, Muammer; Ayas, Alipaşa; Coll, Richard K.

2010-02-01

This paper reports on an investigation of the effectiveness an intervention using several different methods for teaching solution chemistry. The teaching strategy comprised a four-step approach derived from a constructivist view of learning. A sample consisting of 44 students (18 boys and 26 girls) was selected purposively from two different Grade 9 classes in the city of Trabzon, Turkey. Data collection employed a purpose-designed `solution chemistry concept test', consisting of 17 items, with the quantitative data from the survey supported by qualitative interview data. The findings suggest that using different methods embedded within the four-step constructivist-based teaching strategy enables students to refute some alternative conceptions, but does not completely eliminate student alternative conceptions for solution chemistry.

Selective detection of hypertoxic organophosphates pesticides via PDMS composite based acetylcholinesterase-inhibition biosensor.

PubMed

Zhao, Wei; Ge, Pei-Yu; Xu, Jing-Juan; Chen, Hong-Yuan

2009-09-01

We report on a pair of highly sensitive amperometric biosensors for organophosphate pesticides (OPs) based on assembling acetylcholinesterase (AChE) on poly(dimethylsiloxane) (PDMS)-poly(diallydimethylemmonium) (PDDA)/gold nanoparticles (AuNPs) composite film. Two AChE immobilization strategies are proposed based on the composite film with hydrophobic and hydrophilic surface tailored by oxygen plasma. The twin biosensors show interesting different electrochemical performances. The hydrophobic surface based PDMS-PDDAN AuNPs/choline oxidase (ChO)/AChE biosensor (biosensor-1) shows excellent stability and unique selectivity to hypertoxic organophosphate. At optimal conditions, this biosensor-1 could measure 5.0 x 10(-10) g/L paraoxon and 1.0 x 10(-9) g/L parathion. As for the hydrophilic surface based biosensor (biosensor-2), it shows no selectivity but can be commonly used for the detection of most OPs. Based on the structure of AChE, it is assumed that via the hydrophobic interaction between enzyme molecules and hydrophobic surface, the enzyme active sites surrounded by hydrophobic amino acids face toward the surface and get better protection from OPs. This assumption may explain the different performances of the twin biosensors and especially the unique selectivity of biosensor-1 to hypertoxic OPs. Real sample detection was performed and the omethoate residue on Cottomrose Hibiscus leaves was detected with biosensor-1.

Strategy-aligned fuzzy approach for market segment evaluation and selection: a modular decision support system by dynamic network process (DNP)

NASA Astrophysics Data System (ADS)

Mohammadi Nasrabadi, Ali; Hosseinpour, Mohammad Hossein; Ebrahimnejad, Sadoullah

2013-05-01

In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment evaluation and selection. A modular decision support system (DSS) is developed to select an optimum segment with its appropriate strategies. The suggested DSS has two main modules. The first one is SPACE matrix which indicates the risk of each segment. Also, it determines the long-term strategies. The second module finds the most preferred segment-strategies over time. Dynamic network process is applied to prioritize segment-strategies according to five competitive force factors. There is vagueness in pairwise comparisons, and this vagueness has been modeled using fuzzy concepts. To clarify, an example is illustrated by a case study in Iran's coffee market. The results show that success possibility of segments could be different, and choosing the best ones could help companies to be sure in developing their business. Moreover, changing the priority of strategies over time indicates the importance of long-term planning. This fact has been supported by a case study on strategic priority difference in short- and long-term consideration.

Domain selection combined with improved cloning strategy for high throughput expression of higher eukaryotic proteins

PubMed Central

Chen, Yunjia; Qiu, Shihong; Luan, Chi-Hao; Luo, Ming

2007-01-01

Background Expression of higher eukaryotic genes as soluble, stable recombinant proteins is still a bottleneck step in biochemical and structural studies of novel proteins today. Correct identification of stable domains/fragments within the open reading frame (ORF), combined with proper cloning strategies, can greatly enhance the success rate when higher eukaryotic proteins are expressed as these domains/fragments. Furthermore, a HTP cloning pipeline incorporated with bioinformatics domain/fragment selection methods will be beneficial to studies of structure and function genomics/proteomics. Results With bioinformatics tools, we developed a domain/domain boundary prediction (DDBP) method, which was trained by available experimental data. Combined with an improved cloning strategy, DDBP had been applied to 57 proteins from C. elegans. Expression and purification results showed there was a 10-fold increase in terms of obtaining purified proteins. Based on the DDBP method, the improved GATEWAY cloning strategy and a robotic platform, we constructed a high throughput (HTP) cloning pipeline, including PCR primer design, PCR, BP reaction, transformation, plating, colony picking and entry clones extraction, which have been successfully applied to 90 C. elegans genes, 88 Brucella genes, and 188 human genes. More than 97% of the targeted genes were obtained as entry clones. This pipeline has a modular design and can adopt different operations for a variety of cloning/expression strategies. Conclusion The DDBP method and improved cloning strategy were satisfactory. The cloning pipeline, combined with our recombinant protein HTP expression pipeline and the crystal screening robots, constitutes a complete platform for structure genomics/proteomics. This platform will increase the success rate of purification and crystallization dramatically and promote the further advancement of structure genomics/proteomics. PMID:17663785

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

PubMed

Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

2016-05-01

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Endoscopic endonasal approaches for the management of skull base meningiomas. Selection criteria and clinical outcomes.

PubMed

Todeschini, Alexandre B; Otto, Bradley A; Carrau, Ricardo L; Prevedello, Daniel M

2018-05-28

Meningiomas are the most common primary intracranial tumor, arising from different locations, including the skull base. Despite advances in adjuvant treatments, surgical resection remains the main and best treatment for meningiomas. New surgical strategies, such as the endoscopic endonasal approach, have greatly contributed in achieving maximum and total safe resection, preserving the patient's neurological function. Based on the senior authors large experience and a review of the current literature, we have compiled this chapter. We review the surgical technique used at our institution and the most relevant aspects of patient selection when considering resecting a skull base meningioma using the the EEA. Further consideration is given to some skull base meningiomas arising from specific locations with some case examples. The EEA is not an ideal approach for every skull base meningioma. Careful evaluation of the surrounding neurovascular structures surrounding the tumor is imperative to select the appropriate surgical corridor for a safe resection. Nevertheless, for appropriately selected cases, the endoscopic technique is a very valuable tool with some evidences of being superior to the microscopic transcranial approach. A dual-trained surgeon, in both endoscopic and transcranial approaches, is the best alternative to achieve the best patient outcome.

G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies

PubMed Central

Wang, Miaoyan; Jakobsdottir, Johanna; Smith, Albert V.; McPeek, Mary Sara

2017-01-01

In a large-scale genetic association study, the number of phenotyped individuals available for sequencing may, in some cases, be greater than the study’s sequencing budget will allow. In that case, it can be important to prioritize individuals for sequencing in a way that optimizes power for association with the trait. Suppose a cohort of phenotyped individuals is available, with some subset of them possibly already sequenced, and one wants to choose an additional fixed-size subset of individuals to sequence in such a way that the power to detect association is maximized. When the phenotyped sample includes related individuals, power for association can be gained by including partial information, such as phenotype data of ungenotyped relatives, in the analysis, and this should be taken into account when assessing whom to sequence. We propose G-STRATEGY, which uses simulated annealing to choose a subset of individuals for sequencing that maximizes the expected power for association. In simulations, G-STRATEGY performs extremely well for a range of complex disease models and outperforms other strategies with, in many cases, relative power increases of 20–40% over the next best strategy, while maintaining correct type 1 error. G-STRATEGY is computationally feasible even for large datasets and complex pedigrees. We apply G-STRATEGY to data on HDL and LDL from the AGES-Reykjavik and REFINE-Reykjavik studies, in which G-STRATEGY is able to closely-approximate the power of sequencing the full sample by selecting for sequencing a only small subset of the individuals. PMID:27256766

Tissue-engineering-based Strategies for Regenerative Endodontics

PubMed Central

Albuquerque, M.T.P.; Valera, M.C.; Nakashima, M.; Nör, J.E.; Bottino, M.C.

2014-01-01

Stemming from in vitro and in vivo pre-clinical and human models, tissue-engineering-based strategies continue to demonstrate great potential for the regeneration of the pulp-dentin complex, particularly in necrotic, immature permanent teeth. Nanofibrous scaffolds, which closely resemble the native extracellular matrix, have been successfully synthesized by various techniques, including but not limited to electrospinning. A common goal in scaffold synthesis has been the notion of promoting cell guidance through the careful design and use of a collection of biochemical and physical cues capable of governing and stimulating specific events at the cellular and tissue levels. The latest advances in processing technologies allow for the fabrication of scaffolds where selected bioactive molecules can be delivered locally, thus increasing the possibilities for clinical success. Though electrospun scaffolds have not yet been tested in vivo in either human or animal pulpless models in immature permanent teeth, recent studies have highlighted their regenerative potential both from an in vitro and in vivo (i.e., subcutaneous model) standpoint. Possible applications for these bioactive scaffolds continue to evolve, with significant prospects related to the regeneration of both dentin and pulp tissue and, more recently, to root canal disinfection. Nonetheless, no single implantable scaffold can consistently guide the coordinated growth and development of the multiple tissue types involved in the functional regeneration of the pulp-dentin complex. The purpose of this review is to provide a comprehensive perspective on the latest discoveries related to the use of scaffolds and/or stem cells in regenerative endodontics. The authors focused this review on bioactive nanofibrous scaffolds, injectable scaffolds and stem cells, and pre-clinical findings using stem-cell-based strategies. These topics are discussed in detail in an attempt to provide future direction and to shed light on

Online selective kernel-based temporal difference learning.

PubMed

Chen, Xingguo; Gao, Yang; Wang, Ruili

2013-12-01

In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation.

PubMed

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

2015-12-23

The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP

Efficient community-based control strategies in adaptive networks

NASA Astrophysics Data System (ADS)

Yang, Hui; Tang, Ming; Zhang, Hai-Feng

2012-12-01

Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible-infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible-infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans.

Sustaining the edge: factors influencing strategy selection in academic health centers.

PubMed

Walsh, Anne M; Szabat, Kathryn

2002-01-01

Competition within the acute care sector as well as increased penetration by managed care organizations has influenced the structure and role of academic health centers during the past decade. The market factors confronting academic health centers are not dissimilar from conditions that confront other organizations competing in mature industries characterized by declining profitability and intense rivalry for market share. When confronted with intense competition or adverse external events, organizations in other industries have responded to potential threats by forming alliances, developing joint ventures, or merging with another firm to maintain their competitive advantage. Although mergers and acquisitions dominated the strategic landscape in the healthcare industry during the past decade, recent evidence suggests that other types of strategic ventures may offer similar economic and contracting benefits to member organizations. Academic health centers have traditionally been involved in network relationships with multiple partners via their shared technology, collaborative research, and joint educational endeavors. These quasi-organizational relationships appear to have provided a framework for strategic decisions and allowed executives of academic health centers to select strategies that were competitive yet closely aligned with their organizational mission. The analysis of factors that influenced strategy selection by executives of academic health centers suggests a deliberate and methodical approach to achieving market share objectives, expanding managed care contracts, and developing physician networks.

Cloning strategy for producing brush-forming protein-based polymers.

PubMed

Henderson, Douglas B; Davis, Richey M; Ducker, William A; Van Cott, Kevin E

2005-01-01

Brush-forming polymers are being used in a variety of applications, and by using recombinant DNA technology, there exists the potential to produce protein-based polymers that incorporate unique structures and functions in these brush layers. Despite this potential, production of protein-based brush-forming polymers is not routinely performed. For the design and production of new protein-based polymers with optimal brush-forming properties, it would be desirable to have a cloning strategy that allows an iterative approach wherein the protein based-polymer product can be produced and evaluated, and then if necessary, it can be sequentially modified in a controlled manner to obtain optimal surface density and brush extension. In this work, we report on the development of a cloning strategy intended for the production of protein-based brush-forming polymers. This strategy is based on the assembly of modules of DNA that encode for blocks of protein-based polymers into a commercially available expression vector; there is no need for custom-modified vectors and no need for intermediate cloning vectors. Additionally, because the design of new protein-based biopolymers can be an iterative process, our method enables sequential modification of a protein-based polymer product. With at least 21 bacterial expression vectors and 11 yeast expression vectors compatible with this strategy, there are a number of options available for production of protein-based polymers. It is our intent that this strategy will aid in advancing the production of protein-based brush-forming polymers.

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Voluntary strategy suppresses the positive impact of preferential selection in prisoner’s dilemma

NASA Astrophysics Data System (ADS)

Sun, Lei; Lin, Pei-jie; Chen, Ya-shan

2014-11-01

Impact of aspiration is ubiquitous in social and biological disciplines. In this work, we try to explore the impact of such a trait on voluntary prisoners’ dilemma game via a selection parameter w. w=0 returns the traditional version of random selection. For positive w, the opponent of high payoff will be selected; while negative w means that the partner of low payoff will be chosen. We find that for positive w, cooperation will be greatly promoted in the interval of small b, at variance cooperation is inhibited with large b. For negative w, cooperation is fully restrained, irrespective of b value. It is found that the positive impact of preferential selection is suppressed by the voluntary strategy in prisoner’s dilemma. These observations can be supported by the spatial patterns. Our work may shed light on the emergence and persistence of cooperation with voluntary participation in social dilemma.

Oligo/Polynucleotide-Based Gene Modification: Strategies and Therapeutic Potential

PubMed Central

Sargent, R. Geoffrey; Kim, Soya

2011-01-01

Oligonucleotide- and polynucleotide-based gene modification strategies were developed as an alternative to transgene-based and classical gene targeting-based gene therapy approaches for treatment of genetic disorders. Unlike the transgene-based strategies, oligo/polynucleotide gene targeting approaches maintain gene integrity and the relationship between the protein coding and gene-specific regulatory sequences. Oligo/polynucleotide-based gene modification also has several advantages over classical vector-based homologous recombination approaches. These include essentially complete homology to the target sequence and the potential to rapidly engineer patient-specific oligo/polynucleotide gene modification reagents. Several oligo/polynucleotide-based approaches have been shown to successfully mediate sequence-specific modification of genomic DNA in mammalian cells. The strategies involve the use of polynucleotide small DNA fragments, triplex-forming oligonucleotides, and single-stranded oligodeoxynucleotides to mediate homologous exchange. The primary focus of this review will be on the mechanistic aspects of the small fragment homologous replacement, triplex-forming oligonucleotide-mediated, and single-stranded oligodeoxynucleotide-mediated gene modification strategies as it relates to their therapeutic potential. PMID:21417933

Glucose Injections into the Dorsal Hippocampus or Dorsolateral Striatum of Rats Prior to T-Maze Training: Modulation of Learning Rates and Strategy Selection

ERIC Educational Resources Information Center

Canal, Clinton E.; Stutz, Sonja J.; Gold, Paul E.

2005-01-01

The present experiments examined the effects of injecting glucose into the dorsal hippocampus or dorsolateral striatum on learning rates and on strategy selection in rats trained on a T-maze that can be solved by using either a hippocampus-sensitive place or striatum-sensitive response strategy. Percentage strategy selection on a probe trial…

Effect of Instructional Strategy on Critical Thinking and Content Knowledge: Using Problem-Based Learning in the Secondary Classroom

ERIC Educational Resources Information Center

Burris, Scott; Garton, Bryan L.

2007-01-01

The purpose of the study was to determine the effect of problem-based learning (PBL) on critical thinking ability and content knowledge among selected secondary agriculture students in Missouri. The study employed a quasi-experimental, non-equivalent comparison group design. The treatment consisted of two instructional strategies: problem-based…

Strategies of molecular imprinting-based fluorescence sensors for chemical and biological analysis.

PubMed

Yang, Qian; Li, Jinhua; Wang, Xiaoyan; Peng, Hailong; Xiong, Hua; Chen, Lingxin

2018-07-30

One pressing concern today is to construct sensors that can withstand various disturbances for highly selective and sensitive detecting trace analytes in complicated samples. Molecularly imprinted polymers (MIPs) with tailor-made binding sites are preferred to be recognition elements in sensors for effective targets detection, and fluorescence measurement assists in highly sensitive detection and user-friendly control. Accordingly, molecular imprinting-based fluorescence sensors (MI-FL sensors) have attracted great research interest in many fields such as chemical and biological analysis. Herein, we comprehensively review the recent advances in MI-FL sensors construction and applications, giving insights on sensing principles and signal transduction mechanisms, focusing on general construction strategies for intrinsically fluorescent or nonfluorescent analytes and improvement strategies in sensing performance, particularly in sensitivity. Construction strategies are well overviewed, mainly including the traditional indirect methods of competitive binding against pre-bound fluorescent indicators, employment of fluorescent functional monomers and embedding of fluorescence substances, and novel rational designs of hierarchical architecture (core-shell/hollow and mesoporous structures), post-imprinting modification, and ratiometric fluorescence detection. Furthermore, MI-FL sensor based microdevices are discussed, involving micromotors, test strips and microfluidics, which are more portable for rapid point-of-care detection and in-field diagnosing. Finally, the current challenges and future perspectives of MI-FL sensors are proposed. Copyright © 2018 Elsevier B.V. All rights reserved.

PROTECTED POLYMORPHISMS AND EVOLUTIONARY STABILITY OF PATCH-SELECTION STRATEGIES IN STOCHASTIC ENVIRONMENTS

PubMed Central

EVANS, STEVEN N.; HENING, ALEXANDRU; SCHREIBER, SEBASTIAN J.

2015-01-01

We consider a population living in a patchy environment that varies stochastically in space and time. The population is composed of two morphs (that is, individuals of the same species with different genotypes). In terms of survival and reproductive success, the associated phenotypes differ only in their habitat selection strategies. We compute invasion rates corresponding to the rates at which the abundance of an initially rare morph increases in the presence of the other morph established at equilibrium. If both morphs have positive invasion rates when rare, then there is an equilibrium distribution such that the two morphs coexist; that is, there is a protected polymorphism for habitat selection. Alternatively, if one morph has a negative invasion rate when rare, then it is asymptotically displaced by the other morph under all initial conditions where both morphs are present. We refine the characterization of an evolutionary stable strategy for habitat selection from [Schreiber, 2012] in a mathematically rigorous manner. We provide a necessary and sufficient condition for the existence of an ESS that uses all patches and determine when using a single patch is an ESS. We also provide an explicit formula for the ESS when there are two habitat types. We show that adding environmental stochasticity results in an ESS that, when compared to the ESS for the corresponding model without stochasticity, spends less time in patches with larger carrying capacities and possibly makes use of sink patches, thereby practicing a spatial form of bet hedging. PMID:25151369

Multicomponent Pt-Based Zigzag Nanowires as Selectivity Controllers for Selective Hydrogenation Reactions.

PubMed

Bai, Shuxing; Bu, Lingzheng; Shao, Qi; Zhu, Xing; Huang, Xiaoqing

2018-06-22

The selective hydrogenation of α, β-unsaturated aldehyde is an extremely important transformation, while developing efficient catalysts with desirable selectivity to highly value-added products is challenging, mainly due to the coexistence of two conjugated unsaturated functional groups. Herein, we report that a series of Pt-based zigzag nanowires (ZNWs) can be adopted as selectivity controllers for α, β-unsaturated aldehyde hydrogenation, where the excellent unsaturated alcohol (UOL) selectivity (>95%) and high saturated aldehyde (SA) selectivity (>94%) are achieved on PtFe ZNWs and PtFeNi ZNWs+AlCl 3 , respectively. The excellent UOL selectivity of PtFe ZNWs is attributed to the lower electron density of the surface Pt atoms, while the high SA selectivity of PtFeNi ZNWs+AlCl 3 is due to synergy between PtFeNi ZNWs and AlCl 3 , highlighting the importance of Pt-based NWs with precisely controlled surface and composition for catalysis and beyond.

Range Sensor-Based Efficient Obstacle Avoidance through Selective Decision-Making.

PubMed

Shim, Youngbo; Kim, Gon-Woo

2018-03-29

In this paper, we address a collision avoidance method for mobile robots. Many conventional obstacle avoidance methods have been focused solely on avoiding obstacles. However, this can cause instability when passing through a narrow passage, and can also generate zig-zag motions. We define two strategies for obstacle avoidance, known as Entry mode and Bypass mode. Entry mode is a pattern for passing through the gap between obstacles, while Bypass mode is a pattern for making a detour around obstacles safely. With these two modes, we propose an efficient obstacle avoidance method based on the Expanded Guide Circle (EGC) method with selective decision-making. The simulation and experiment results show the validity of the proposed method.

Bis-reaction-trigger as a strategy to improve the selectivity of fluorescent probes.

PubMed

Li, Dan; Cheng, Juan; Wang, Cheng-Kun; Ying, Huazhou; Hu, Yongzhou; Han, Feng; Li, Xin

2018-06-01

By the strategy of equipping a fluorophore with two reaction triggers that are tailored to the specific chemistry of peroxynitrite, we have developed a highly selective probe for detecting peroxynitrite in live cells. Sequential response by the two triggers enabled the probe to reveal various degrees of nitrosative stress in live cells via a sensitive emission colour change.

Instruction of Research-Based Comprehension Strategies in Basal Reading Programs

ERIC Educational Resources Information Center

Pilonieta, Paola

2010-01-01

Research supports using research-based comprehension strategies; however, comprehension strategy instruction is not highly visible in basal reading programs or classroom instruction, resulting in many students who struggle with comprehension. A content analysis examined which research-based comprehension strategies were presented in five…

Comparison between Exclusive and Selective Drug-Eluting Stent Strategies in Treating Patients with Multivessel Coronary Artery Disease.

PubMed

Tung, Ying-Chang; Hsiao, Ping-Gune; Hsu, Lung-An; Kuo, Chi-Tai; Chang, Chi-Jen

2014-05-01

The expanded usage of drug-eluting stents (DES) in treating patients with multivessel coronary artery disease (CAD) may sometimes be limited in real-world practice due to cost concerns. We compared the clinical outcomes of exclusive and selective DES use in treating patients with multivessel CAD. From November 2004 to December 2011, 110 patients with multivessel CAD who received four or more stents were enrolled into this study, and divided into two groups according to the DES strategy employed: exclusive DES (n = 52), or selective DES (n = 58). In the selective DES group, DES was reserved for complex lesions only, such that the incidence and predictors of clinical events were assessed. At a mean follow-up of 41.4 ± 26.5 months, there were no significant differences between the two strategies in terms of baseline characteristics, all-cause mortality (exclusive vs. selective: 1.9% vs. 6.9%, p = 0.21), cardiac death (1.9% vs. 1.7%, p = 0.94) and nonfatal myocardial infarction (3.8% vs. 5.2%, p = 0.74). Despite the presence of more ostial lesions in the exclusive DES group, there was a trend such that major adverse cardiac events (MACE) and target lesion revascularization (TLR) rates were higher in the selective DES group (MACE: 17.3% vs. 31%, p = 0.16; TLR: 11.5% vs. 24.1%, p = 0.08). The higher MACE rate in the selective DES group was mainly driven by a higher target vessel revascularization (TVR) rate (15.4% vs. 29.3%, p = 0.08). In the exclusive DES group, SYNTAX score was an independent predictor of MACE [Haxard ratio (HR): 1.09, 95% confidence internal (CI): 1.02-1.16, p = 0.01] and TVR (HR 1.08, 95% CI 1.01-1.15, p = 0.04). Compared to the exclusive DES strategy, the selective DES strategy with reservation of DES for complex lesions is associated with numerically higher, but not statistically significant, rates of MACE and all-cause mortality in this small group of patients with multivessel CAD receiving four or more stents. Bare metal stent; Drug

Comparison between Exclusive and Selective Drug-Eluting Stent Strategies in Treating Patients with Multivessel Coronary Artery Disease

PubMed Central

Tung, Ying-Chang; Hsiao, Ping-Gune; Hsu, Lung-An; Kuo, Chi-Tai; Chang, Chi-Jen

2014-01-01

Background The expanded usage of drug-eluting stents (DES) in treating patients with multivessel coronary artery disease (CAD) may sometimes be limited in real-world practice due to cost concerns. We compared the clinical outcomes of exclusive and selective DES use in treating patients with multivessel CAD. Methods From November 2004 to December 2011, 110 patients with multivessel CAD who received four or more stents were enrolled into this study, and divided into two groups according to the DES strategy employed: exclusive DES (n = 52), or selective DES (n = 58). In the selective DES group, DES was reserved for complex lesions only, such that the incidence and predictors of clinical events were assessed. Results At a mean follow-up of 41.4 ± 26.5 months, there were no significant differences between the two strategies in terms of baseline characteristics, all-cause mortality (exclusive vs. selective: 1.9% vs. 6.9%, p = 0.21), cardiac death (1.9% vs. 1.7%, p = 0.94) and nonfatal myocardial infarction (3.8% vs. 5.2%, p = 0.74). Despite the presence of more ostial lesions in the exclusive DES group, there was a trend such that major adverse cardiac events (MACE) and target lesion revascularization (TLR) rates were higher in the selective DES group (MACE: 17.3% vs. 31%, p = 0.16; TLR: 11.5% vs. 24.1%, p = 0.08). The higher MACE rate in the selective DES group was mainly driven by a higher target vessel revascularization (TVR) rate (15.4% vs. 29.3%, p = 0.08). In the exclusive DES group, SYNTAX score was an independent predictor of MACE [Haxard ratio (HR): 1.09, 95% confidence internal (CI): 1.02-1.16, p = 0.01] and TVR (HR 1.08, 95% CI 1.01-1.15, p = 0.04). Conclusions Compared to the exclusive DES strategy, the selective DES strategy with reservation of DES for complex lesions is associated with numerically higher, but not statistically significant, rates of MACE and all-cause mortality in this small group of patients with multivessel CAD receiving four or more

Reviewing Clinical Effectiveness of Active Training Strategies of Platform-Based Ankle Rehabilitation Robots.

PubMed

Zeng, Xiangfeng; Zhu, Guoli; Zhang, Mingming; Xie, Sheng Q

2018-01-01

This review aims to provide a systematical investigation of clinical effectiveness of active training strategies applied in platform-based ankle robots. English-language studies published from Jan 1980 to Aug 2017 were searched from four databases using key words of "Ankle ∗ " AND "Robot ∗ " AND "Effect ∗ OR Improv ∗ OR Increas ∗ ." Following an initial screening, three rounds of discrimination were successively conducted based on the title, the abstract, and the full paper. A total of 21 studies were selected with 311 patients involved; of them, 13 studies applied a single group while another eight studies used different groups for comparison to verify the therapeutic effect. Virtual-reality (VR) game training was applied in 19 studies, while two studies used proprioceptive neuromuscular facilitation (PNF) training. Active training techniques delivered by platform ankle rehabilitation robots have been demonstrated with great potential for clinical applications. Training strategies are mostly combined with one another by considering rehabilitation schemes and motion ability of ankle joints. VR game environment has been commonly used with active ankle training. Bioelectrical signals integrated with VR game training can implement intelligent identification of movement intention and assessment. These further provide the foundation for advanced interactive training strategies that can lead to enhanced training safety and confidence for patients and better treatment efficacy.

Strategies to select yeast starters cultures for production of flavor compounds in cachaça fermentations.

PubMed

de Souza, Anderson Proust Gonçalves; Vicente, Maristela de Araújo; Klein, Raphael Contelli; Fietto, Luciano Gomes; Coutrim, Maurício Xavier; de Cássia Franco Afonso, Robson José; Araújo, Leandro Dias; da Silva, Paulo Henrique Alves; Bouillet, Leoneide Erica Maduro; Castro, Ieso Miranda; Brandão, Rogelio Lopes

2012-02-01

In this work, we have used classical genetics techniques to find improved starter strains to produce cachaça with superior sensorial quality. Our strategy included the selection of yeast strains resistant to 5,5',5″-trifluor-D: ,L: -leucine (TLF) and cerulenin, since these strains produce higher levels of higher alcohols and esters than parental strains. However, no clear relationship was observed when levels of flavoring compounds were compared with the levels expression of the genes (BAT1, BAT2, ATF2, EEB1 genes) involved with the biosynthesis of flavoring compounds. Furthermore, we determined the stability of phenotypes considered as the best indicators of the quality of the cachaça for a parental strain and its segregants. By applying the principal component analysis, a cluster of segregants, showing a high number of characteristics similar to the parental strain, was recognized. One segregant, that was resistant to TLF and cerulenin, also showed growth stability after six consecutive replications on plates containing high concentrations of sugar and ethanol. "Cachaça" produced at laboratory scale using a parental strain and this segregant showed a higher level of flavoring compounds. Both strains predominated in an open fermentative process through seven cycles, as was shown by mitochondrial restriction fragment length polymorphisms analysis. Based on the physical chemical composition of the obtained products, the results demonstrate the usefulness of the developed strategies for the selection of yeast strains to be used as starters in "cachaça" production.

A semiparametric graphical modelling approach for large-scale equity selection

PubMed Central

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption. PMID:28316507

A semiparametric graphical modelling approach for large-scale equity selection.

PubMed

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

PubMed

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the

Comparison of Different Strategies for Selection/Adaptation of Mixed Microbial Cultures Able to Ferment Crude Glycerol Derived from Second-Generation Biodiesel.

PubMed

Varrone, C; Heggeset, T M B; Le, S B; Haugen, T; Markussen, S; Skiadas, I V; Gavala, H N

2015-01-01

Objective of this study was the selection and adaptation of mixed microbial cultures (MMCs), able to ferment crude glycerol generated from animal fat-based biodiesel and produce building-blocks and green chemicals. Various adaptation strategies have been investigated for the enrichment of suitable and stable MMC, trying to overcome inhibition problems and enhance substrate degradation efficiency, as well as generation of soluble fermentation products. Repeated transfers in small batches and fed-batch conditions have been applied, comparing the use of different inoculum, growth media, and Kinetic Control. The adaptation of activated sludge inoculum was performed successfully and continued unhindered for several months. The best results showed a substrate degradation efficiency of almost 100% (about 10 g/L glycerol in 21 h) and different dominant metabolic products were obtained, depending on the selection strategy (mainly 1,3-propanediol, ethanol, or butyrate). On the other hand, anaerobic sludge exhibited inactivation after a few transfers. To circumvent this problem, fed-batch mode was used as an alternative adaptation strategy, which led to effective substrate degradation and high 1,3-propanediol and butyrate production. Changes in microbial composition were monitored by means of Next Generation Sequencing, revealing a dominance of glycerol consuming species, such as Clostridium, Klebsiella, and Escherichia.

A strategy for clone selection under different production conditions.

PubMed

Legmann, Rachel; Benoit, Brian; Fedechko, Ronald W; Deppeler, Cynthia L; Srinivasan, Sriram; Robins, Russell H; McCormick, Ellen L; Ferrick, David A; Rodgers, Seth T; Russo, A Peter

2011-01-01

Top performing clones have failed at the manufacturing scale while the true best performer may have been rejected early in the screening process. Therefore, the ability to screen multiple clones in complex fed-batch processes using multiple process variations can be used to assess robustness and to identify critical factors. This dynamic ranking of clones' strategy requires the execution of many parallel experiments than traditional approaches. Therefore, this approach is best suited for micro-bioreactor models which can perform hundreds of experiments quickly and efficiently. In this study, a fully monitored and controlled small scale platform was used to screen eight CHO clones producing a recombinant monoclonal antibody across several process variations, including different feeding strategies, temperature shifts and pH control profiles. The first screen utilized 240 micro-bioreactors were run for two weeks for this assessment of the scale-down model as a high-throughput tool for clone evaluation. The richness of the outcome data enable to clearly identify the best and worst clone as well as process in term of maximum monoclonal antibody titer. The follow-up comparison study utilized 180 micro-bioreactors in a full factorial design and a subset of 12 clone/process combinations was selected to be run parallel in duplicate shake flasks. Good correlation between the micro-bioreactor predictions and those made in shake flasks with a Pearson correlation value of 0.94. The results also demonstrate that this micro-scale system can perform clone screening and process optimization for gaining significant titer improvements simultaneously. This dynamic ranking strategy can support better choices of production clones. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

Teachers' Perceptions of Strategy Based Reading Instruction for Reading Comprehension

ERIC Educational Resources Information Center

Gibson, Katherine D.

2009-01-01

Strategy based reading instruction helps teachers differentiate the teaching of reading. It also supports many types of readers by explicitly teaching and modeling reading comprehension strategies. The purpose of this study is to explore the effectiveness of strategy based reading instruction for improving student reading comprehension. …

Two-dimensional solid-phase extraction strategy for the selective enrichment of aminoglycosides in milk.

PubMed

Shen, Aijin; Wei, Jie; Yan, Jingyu; Jin, Gaowa; Ding, Junjie; Yang, Bingcheng; Guo, Zhimou; Zhang, Feifang; Liang, Xinmiao

2017-03-01

An orthogonal two-dimensional solid-phase extraction strategy was established for the selective enrichment of three aminoglycosides including spectinomycin, streptomycin, and dihydrostreptomycin in milk. A reversed-phase liquid chromatography material (C 18 ) and a weak cation-exchange material (TGA) were integrated in a single solid-phase extraction cartridge. The feasibility of two-dimensional clean-up procedure that experienced two-step adsorption, two-step rinsing, and two-step elution was systematically investigated. Based on the orthogonality of reversed-phase and weak cation-exchange procedures, the two-dimensional solid-phase extraction strategy could minimize the interference from the hydrophobic matrix existing in traditional reversed-phase solid-phase extraction. In addition, high ionic strength in the extracts could be effectively removed before the second dimension of weak cation-exchange solid-phase extraction. Combined with liquid chromatography and tandem mass spectrometry, the optimized procedure was validated according to the European Union Commission directive 2002/657/EC. A good performance was achieved in terms of linearity, recovery, precision, decision limit, and detection capability in milk. Finally, the optimized two-dimensional clean-up procedure incorporated with liquid chromatography and tandem mass spectrometry was successfully applied to the rapid monitoring of aminoglycoside residues in milk. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The dilemma of female mate selection in the brown bear, a species with sexually selected infanticide

PubMed Central

Bellemain, Eva; Zedrosser, Andreas; Manel, Stéphanie; Waits, Lisette P; Taberlet, Pierre; Swenson, Jon E

2005-01-01

Because of differential investment in gametes between sexes, females tend to be the more selective sex. Based on this concept, we investigate mate selection in a large carnivore: the brown bear (Ursus arctos). We hypothesize that, in this species with sexually selected infanticide (SSI), females may be faced with a dilemma: either select a high-quality partner based on phenotypic criteria, as suggested by theories of mate choice, or rather mate with future potentially infanticidal males as a counter-strategy to SSI. We evaluated which male characteristics were important in paternity assignment. Among males available in the vicinity of the females, the largest, most heterozygous and less inbred and also the geographically closest males were more often the fathers of the female's next litter. We suggest that female brown bears may select the closest males as a counter-strategy to infanticide and exercise a post-copulatory cryptic choice, based on physical attributes, such as a large body size, reflecting male genetic quality. However, male–male competition either in the form of fighting before copulation or during the post-copulatory phase, in the form of sperm competition, cannot entirely be ruled out. PMID:16543170

Self-Regulatory Strategies in Daily Life: Selection, Optimization, and Compensation and Everyday Memory Problems

ERIC Educational Resources Information Center

Robinson, Stephanie A.; Rickenbach, Elizabeth H.; Lachman, Margie E.

2016-01-01

The effective use of self-regulatory strategies, such as selection, optimization, and compensation (SOC) requires resources. However, it is theorized that SOC use is most advantageous for those experiencing losses and diminishing resources. The present study explored this seeming paradox within the context of limitations or constraints due to…

Brain Based Instruction in Correctional Settings: Strategies for Teachers.

ERIC Educational Resources Information Center

Becktold, Toni Hill

2001-01-01

Brain-based learning strategies (learner choice, movement, small groups) may be inappropriate in corrections for security reasons. Problems encountered in correctional education (attention deficit disorder, learned helplessness) complicate the use of these strategies. Incorporating brain-based instruction in these settings requires creativity and…

Selection for Surgical Training: An Evidence-Based Review.

PubMed

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.

Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility.

PubMed

Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun

2014-10-27

In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.

Preferential selection based on degree difference in the spatial prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Huang, Changwei; Dai, Qionglin; Cheng, Hongyan; Li, Haihong

2017-10-01

Strategy evolution in spatial evolutionary games is generally implemented through imitation processes between individuals. In most previous studies, it is assumed that individuals pick up one of their neighbors randomly to learn from. However, by considering the heterogeneity of individuals' influence in the real society, preferential selection is more realistic. Here, we introduce a preferential selection mechanism based on degree difference into spatial prisoner's dilemma games on Erdös-Rényi networks and Barabási-Albert scale-free networks and investigate the effects of the preferential selection on cooperation. The results show that, when the individuals prefer to choose the neighbors who have small degree difference with themselves to imitate, cooperation is hurt by the preferential selection. In contrast, when the individuals prefer to choose those large degree difference neighbors to learn from, there exists optimal preference strength resulting in the maximal cooperation level no matter what the network structure is. In addition, we investigate the robustness of the results against variations of the noise, the average degree and the size of network in the model, and find that the qualitative features of the results are unchanged.

Projects, Training, and Strategies for Generating Income: A Selected Annotated Bibliography. Annotated Bibliography #4.

ERIC Educational Resources Information Center

Michigan State Univ., East Lansing. Non-Formal Education Information Center.

A selected annotated bibliography on projects, training, and strategies for generating income, intended for persons actively engaged in non-formal education for development, reflects a growing number of projects on income generation by and for women's groups, and a reliance upon indigenous associations and group action. Documents dating from 1969…

A tool for selecting SNPs for association studies based on observed linkage disequilibrium patterns.

PubMed

De La Vega, Francisco M; Isaac, Hadar I; Scafe, Charles R

2006-01-01

The design of genetic association studies using single-nucleotide polymorphisms (SNPs) requires the selection of subsets of the variants providing high statistical power at a reasonable cost. SNPs must be selected to maximize the probability that a causative mutation is in linkage disequilibrium (LD) with at least one marker genotyped in the study. The HapMap project performed a genome-wide survey of genetic variation with about a million SNPs typed in four populations, providing a rich resource to inform the design of association studies. A number of strategies have been proposed for the selection of SNPs based on observed LD, including construction of metric LD maps and the selection of haplotype tagging SNPs. Power calculations are important at the study design stage to ensure successful results. Integrating these methods and annotations can be challenging: the algorithms required to implement these methods are complex to deploy, and all the necessary data and annotations are deposited in disparate databases. Here, we present the SNPbrowser Software, a freely available tool to assist in the LD-based selection of markers for association studies. This stand-alone application provides fast query capabilities and swift visualization of SNPs, gene annotations, power, haplotype blocks, and LD map coordinates. Wizards implement several common SNP selection workflows including the selection of optimal subsets of SNPs (e.g. tagging SNPs). Selected SNPs are screened for their conversion potential to either TaqMan SNP Genotyping Assays or the SNPlex Genotyping System, two commercially available genotyping platforms, expediting the set-up of genetic studies with an increased probability of success.

Properties of different selection signature statistics and a new strategy for combining them.

PubMed

Ma, Y; Ding, X; Qanbari, S; Weigend, S; Zhang, Q; Simianer, H

2015-11-01

Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait.

Implementation of Technology-based Patient Engagement Strategies within Practice-based Research Networks.

PubMed

Careyva, Beth; Shaak, Kyle; Mills, Geoffrey; Johnson, Melanie; Goodrich, Samantha; Stello, Brian; Wallace, Lorraine S

2016-01-01

Technology-based patient engagement strategies (such as patient portals) are increasingly available, yet little is known about current use and barriers within practice-based research networks (PBRNs). PBRN directors have unique opportunities to inform the implementation of patient-facing technology and to translate these findings into practice. PBRN directors were queried regarding technology-based patient engagement strategies as part of the 2015 CAFM Educational Research Alliance (CERA) survey of PBRN directors. A total of 102 PBRN directors were identified via the Agency for Healthcare Research and Quality's registry; 54 of 96 eligible PBRN directors completed the survey, for a response rate of 56%. Use of technology-based patient engagement strategies within PBRNs was limited, with less than half of respondents reporting experience with the most frequently named tools (risk assessments/decision aids). Information technology (IT) support was the top barrier, followed by low rates of portal enrollment. For engaging participant practices, workload and practice leadership were cited as most important, with fewer respondents noting concerns about patient privacy. Given limited use of patient-facing technologies, PBRNs have an opportunity to clarify the optimal use of these strategies. Providing IT support and addressing clinician concerns regarding workload may facilitate the inclusion of innovative technologies in PBRNs. © Copyright 2016 by the American Board of Family Medicine.

Search strategy selection in the Morris water maze indicates allocentric map formation during learning that underpins spatial memory formation.

PubMed

Rogers, Jake; Churilov, Leonid; Hannan, Anthony J; Renoir, Thibault

2017-03-01

Using a Matlab classification algorithm, we demonstrate that a highly salient distal cue array is required for significantly increased likelihoods of spatial search strategy selection during Morris water maze spatial learning. We hypothesized that increased spatial search strategy selection during spatial learning would be the key measure demonstrating the formation of an allocentric map to the escape location. Spatial memory, as indicated by quadrant preference for the area of the pool formally containing the hidden platform, was assessed as the main measure that this allocentric map had formed during spatial learning. Our C57BL/6J wild-type (WT) mice exhibit quadrant preference in the highly salient cue paradigm but not the low, corresponding with a 120% increase in the odds of a spatial search strategy selection during learning. In contrast, quadrant preference remains absent in serotonin 1A receptor (5-HT 1A R) knockout (KO) mice, who exhibit impaired search strategy selection during spatial learning. Additionally, we also aimed to assess the impact of the quality of the distal cue array on the spatial learning curves of both latency to platform and path length using mixed-effect regression models and found no significant associations or interactions. In contrast, we demonstrated that the spatial learning curve for search strategy selection was absent during training in the low saliency paradigm. Therefore, we propose that allocentric search strategy selection during spatial learning is the learning parameter in mice that robustly indicates the formation of a cognitive map for the escape goal location. These results also suggest that both latency to platform and path length spatial learning curves do not discriminate between allocentric and egocentric spatial learning and do not reliably predict spatial memory formation. We also show that spatial memory, as indicated by the absolute time in the quadrant formerly containing the hidden platform alone (without

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

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

Choudhury, Sutanay; Holder, Larry; Chin, George

2015-05-27

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving networks spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with prominent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphs in amore » continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a ``Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named ``Relative Selectivity" that is used to select between different query processing strategies. Our experiments performed on real online news, network traffic stream and a synthetic social network benchmark demonstrate 10-100x speedups over non-incremental, selectivity agnostic approaches.« less

A universal mini-vector and an annealing of PCR products (APP)-based cloning strategy for convenient molecular biological manipulations.

PubMed

Liu, Xia; Li, Tuoping; Hart, Darren J; Gao, Song; Wang, Hongling; Gao, Herui; Xu, Shumin; Zhang, Yifeng; Liu, Yifei; An, Yingfeng

2018-03-18

Currently, the most widely used strategies for molecular cloning are sticky-end ligation-based cloning, TA cloning, blunt-end ligation-based cloning and ligase-independent cloning. In this study we have developed a novel mini-vector pANY1 which can simultaneously meet the requirements of all these cloning strategies. In addition, the selection of appropriate restriction digestion sites is difficult in some cases because of the presence of internal sites. In this study, an annealing of PCR products (APP)-based sticky-end cloning strategy was introduced to avoid this issue. Additionally, false positives occur during molecular cloning, which increases the workload of isolating positive clones. The plasmid pANY1 contains a ccdB cassette between multiple cloning sites, which efficiently avoids these false positives. Therefore, this mini-vector should serve as a useful tool with wide applications in biosciences, agriculture, food technologies, etc. Copyright © 2018 Elsevier Inc. All rights reserved.

A RSSI-based parameter tracking strategy for constrained position localization

NASA Astrophysics Data System (ADS)

Du, Jinze; Diouris, Jean-François; Wang, Yide

2017-12-01

In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.

Determining the appropriate strategies for emergency planning through AHP-SWOT.

PubMed

Kalatpour, Omid

2017-01-01

During an unexpected incident, companies should demonstrate appropriate behaviour based on predetermined and rehearsed emergency strategies. This paper describes how to select the proper strategies for emergency situations via means of the AHP-SWOT tool, where the initial SWOT analysis is conducted for the emergency management system, and the final strategies are selected via the analytic hierarchy process (AHP). Alternative response strategies comprise internal, shared and external responses. Most of the scenarios investigated for this study demanded a shared response. These findings highlight the importance of mutual aid agreements, cooperative exercises and the improvement of communication systems. Organisations can take advantage of integrated approaches to select the best strategies and tactics for normal situations in general and emergency situations in particular.

Antibody-Based Preventive and Therapeutic Strategies Against HIV.

PubMed

Fabra-Garcia, Amanda; Beltran, Carolina; Sanchez-Merino, Victor; Yuste, Eloisa

2016-01-01

Over the years, numerous studies have been carried out demonstrating the role of antibodies in HIV control leading to the development of antibody-based therapeutic and prophylactic strategies. The objective of this review is to provide updated information on the role of antibodies in the prevention and control of HIV infection and the strategies against HIV that have been designed based on this information. Passive transfer of anti-HIV antibodies in animal models has proven the efficacy of certain antibodies in the prevention and treatment of infection. The capacity of antibodies to control the virus was first attributed to their neutralizing capacity. However, we now know that there are other Fc-mediated antibody activities associated with virus protection. When it comes to better understanding protection against HIV, we ought to pay particular attention to mucosal immune responses. The evidence accumulated so far indicates that an effective vaccine against HIV should generate both mucosal IgAs and systemic IgGs. Due to the problematic induction of protective anti-HIV antibodies, several groups have developed alternative approaches based on antibody delivery via gene therapy vectors. Experiments in animal models with these vectors have shown impressive protection levels and this strategy is now being clinically trialed. Taking into account all the information included in this review, it seems evident that anti-HIV-1 antibodies play an important role in virus control and prevention. This review aims to give an overview of the strategies used and the advances in antibody-based preventive and therapeutic strategies against HIV-1.

Reviewing Clinical Effectiveness of Active Training Strategies of Platform-Based Ankle Rehabilitation Robots

PubMed Central

2018-01-01

Objective This review aims to provide a systematical investigation of clinical effectiveness of active training strategies applied in platform-based ankle robots. Method English-language studies published from Jan 1980 to Aug 2017 were searched from four databases using key words of “Ankle∗” AND “Robot∗” AND “Effect∗ OR Improv∗ OR Increas∗.” Following an initial screening, three rounds of discrimination were successively conducted based on the title, the abstract, and the full paper. Result A total of 21 studies were selected with 311 patients involved; of them, 13 studies applied a single group while another eight studies used different groups for comparison to verify the therapeutic effect. Virtual-reality (VR) game training was applied in 19 studies, while two studies used proprioceptive neuromuscular facilitation (PNF) training. Conclusion Active training techniques delivered by platform ankle rehabilitation robots have been demonstrated with great potential for clinical applications. Training strategies are mostly combined with one another by considering rehabilitation schemes and motion ability of ankle joints. VR game environment has been commonly used with active ankle training. Bioelectrical signals integrated with VR game training can implement intelligent identification of movement intention and assessment. These further provide the foundation for advanced interactive training strategies that can lead to enhanced training safety and confidence for patients and better treatment efficacy. PMID:29675142

A Comparative Evaluation of Computer Based and Non-Computer Based Instructional Strategies.

ERIC Educational Resources Information Center

Emerson, Ian

1988-01-01

Compares the computer assisted instruction (CAI) tutorial with its non-computerized pedagogical roots: the Socratic Dialog with Skinner's Programmed Instruction. Tests the effectiveness of a CAI tutorial on diffusion and osmosis against four other interactive and non-interactive instructional strategies. Notes computer based strategies were…

A high efficiency gene disruption strategy using a positive-negative split selection marker and electroporation for Fusarium oxysporum.

PubMed

Liang, Liqin; Li, Jianqiang; Cheng, Lin; Ling, Jian; Luo, Zhongqin; Bai, Miao; Xie, Bingyan

2014-11-01

The Fusarium oxysporum species complex consists of fungal pathogens that cause serial vascular wilt disease on more than 100 cultivated species throughout the world. Gene function analysis is rapidly becoming more and more important as the whole-genome sequences of various F. oxysporum strains are being completed. Gene-disruption techniques are a common molecular tool for studying gene function, yet are often a limiting step in gene function identification. In this study we have developed a F. oxysporum high-efficiency gene-disruption strategy based on split-marker homologous recombination cassettes with dual selection and electroporation transformation. The method was efficiently used to delete three RNA-dependent RNA polymerase (RdRP) genes. The gene-disruption cassettes of three genes can be constructed simultaneously within a short time using this technique. The optimal condition for electroporation is 10μF capacitance, 300Ω resistance, 4kV/cm field strength, with 1μg of DNA (gene-disruption cassettes). Under these optimal conditions, we were able to obtain 95 transformants per μg DNA. And after positive-negative selection, the transformants were efficiently screened by PCR, screening efficiency averaged 85%: 90% (RdRP1), 85% (RdRP2) and 77% (RdRP3). This gene-disruption strategy should pave the way for high throughout genetic analysis in F. oxysporum. Copyright © 2014 Elsevier GmbH. All rights reserved.

High-efficiency CRISPR/Cas9 multiplex gene editing using the glycine tRNA-processing system-based strategy in maize.

PubMed

Qi, Weiwei; Zhu, Tong; Tian, Zhongrui; Li, Chaobin; Zhang, Wei; Song, Rentao

2016-08-11

CRISPR/Cas9 genome editing strategy has been applied to a variety of species and the tRNA-processing system has been used to compact multiple gRNAs into one synthetic gene for manipulating multiple genes in rice. We optimized and introduced the multiplex gene editing strategy based on the tRNA-processing system into maize. Maize glycine-tRNA was selected to design multiple tRNA-gRNA units for the simultaneous production of numerous gRNAs under the control of one maize U6 promoter. We designed three gRNAs for simplex editing and three multiple tRNA-gRNA units for multiplex editing. The results indicate that this system not only increased the number of targeted sites but also enhanced mutagenesis efficiency in maize. Additionally, we propose an advanced sequence selection of gRNA spacers for relatively more efficient and accurate chromosomal fragment deletion, which is important for complete abolishment of gene function especially long non-coding RNAs (lncRNAs). Our results also indicated that up to four tRNA-gRNA units in one expression cassette design can still work in maize. The examples reported here demonstrate the utility of the tRNA-processing system-based strategy as an efficient multiplex genome editing tool to enhance maize genetic research and breeding.

Age differences in everyday problem-solving effectiveness: older adults select more effective strategies for interpersonal problems.

PubMed

Blanchard-Fields, Fredda; Mienaltowski, Andrew; Seay, Renee Baldi

2007-01-01

Using the Everyday Problem Solving Inventory of Cornelius and Caspi, we examined differences in problem-solving strategy endorsement and effectiveness in two domains of everyday functioning (instrumental or interpersonal, and a mixture of the two domains) and for four strategies (avoidance-denial, passive dependence, planful problem solving, and cognitive analysis). Consistent with past research, our research showed that older adults were more problem focused than young adults in their approach to solving instrumental problems, whereas older adults selected more avoidant-denial strategies than young adults when solving interpersonal problems. Overall, older adults were also more effective than young adults when solving everyday problems, in particular for interpersonal problems.

Strategy community development based on local resources

NASA Astrophysics Data System (ADS)

Meirinawati; Prabawati, I.; Pradana, G. W.

2018-01-01

The problem of progressing regions is not far from economic problems and is often caused by the inability of the regions in response to changes in economic conditions that occur, so the need for community development programs implemented to solve various problems. Improved community effort required with the real conditions and needs of each region. Community development based on local resources process is very important, because it is an increase in human resource capability in the optimal utilization of local resource potential. In this case a strategy is needed in community development based on local resources. The community development strategy are as follows:(1) “Eight Line Equalization Plus” which explains the urgency of rural industrialization, (2) the construction of the village will be more successful when combining strategies are tailored to regional conditions, (3) the escort are positioning themselves as the Planner, supervisor, information giver, motivator, facilitator, connecting at once evaluators.

High-Speed Lateral Flow Strategy for a Fast Biosensing with an Improved Selectivity and Binding Affinity.

PubMed

Cho, Dong Guk; Yoo, Haneul; Lee, Haein; Choi, Yeol Kyo; Lee, Minju; Ahn, Dong June; Hong, Seunghun

2018-05-10

We report a high-speed lateral flow strategy for a fast biosensing with an improved selectivity and binding affinity even under harsh conditions. In this strategy, biosensors were fixed at a location away from the center of a round shape disk, and the disk was rotated to create the lateral flow of a target solution on the biosensors during the sensing measurements. Experimental results using the strategy showed high reaction speeds, high binding affinity, and low nonspecific adsorptions of target molecules to biosensors. Furthermore, binding affinity between target molecules and sensing molecules was enhanced even in harsh conditions such as low pH and low ionic strength conditions. These results show that the strategy can improve the performance of conventional biosensors by generating high-speed lateral flows on a biosensor surface. Therefore, our strategy can be utilized as a simple but powerful tool for versatile bio and medical applications.

Computing border bases using mutant strategies

NASA Astrophysics Data System (ADS)

Ullah, E.; Abbas Khan, S.

2014-01-01

Border bases, a generalization of Gröbner bases, have actively been addressed during recent years due to their applicability to industrial problems. In cryptography and coding theory a useful application of border based is to solve zero-dimensional systems of polynomial equations over finite fields, which motivates us for developing optimizations of the algorithms that compute border bases. In 2006, Kehrein and Kreuzer formulated the Border Basis Algorithm (BBA), an algorithm which allows the computation of border bases that relate to a degree compatible term ordering. In 2007, J. Ding et al. introduced mutant strategies bases on finding special lower degree polynomials in the ideal. The mutant strategies aim to distinguish special lower degree polynomials (mutants) from the other polynomials and give them priority in the process of generating new polynomials in the ideal. In this paper we develop hybrid algorithms that use the ideas of J. Ding et al. involving the concept of mutants to optimize the Border Basis Algorithm for solving systems of polynomial equations over finite fields. In particular, we recall a version of the Border Basis Algorithm which is actually called the Improved Border Basis Algorithm and propose two hybrid algorithms, called MBBA and IMBBA. The new mutants variants provide us space efficiency as well as time efficiency. The efficiency of these newly developed hybrid algorithms is discussed using standard cryptographic examples.

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy

PubMed Central

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system. PMID:27835638

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PubMed

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

A systematic methodology for selecting decontamination strategies following a biocontamination event.

PubMed

Krauter, Paula; Edwards, Donna; Yang, Lynn; Tucker, Mark

2011-09-01

Decontamination and recovery of a facility or outdoor area after a wide-area biological incident involving a highly persistent agent (eg, Bacillus anthracis spores) is a complex process that requires extensive information and significant resources, which are likely to be limited, particularly if multiple facilities or areas are affected. This article proposes a systematic methodology for evaluating information to select the decontamination or alternative treatments that optimize use of resources if decontamination is required for the facility or area. The methodology covers a wide range of approaches, including volumetric and surface decontamination, monitored natural attenuation, and seal and abandon strategies. A proposed trade-off analysis can help decision makers understand the relative appropriateness, efficacy, and labor, skill, and cost requirements of the various decontamination methods for the particular facility or area needing treatment--whether alone or as part of a larger decontamination effort. Because the state of decontamination knowledge and technology continues to evolve rapidly, the methodology presented here is designed to accommodate new strategies and materials and changing information.

Using Nonlinear Stochastic Evolutionary Game Strategy to Model an Evolutionary Biological Network of Organ Carcinogenesis Under a Natural Selection Scheme

PubMed Central

Chen, Bor-Sen; Tsai, Kun-Wei; Li, Cheng-Wei

2015-01-01

Molecular biologists have long recognized carcinogenesis as an evolutionary process that involves natural selection. Cancer is driven by the somatic evolution of cell lineages. In this study, the evolution of somatic cancer cell lineages during carcinogenesis was modeled as an equilibrium point (ie, phenotype of attractor) shifting, the process of a nonlinear stochastic evolutionary biological network. This process is subject to intrinsic random fluctuations because of somatic genetic and epigenetic variations, as well as extrinsic disturbances because of carcinogens and stressors. In order to maintain the normal function (ie, phenotype) of an evolutionary biological network subjected to random intrinsic fluctuations and extrinsic disturbances, a network robustness scheme that incorporates natural selection needs to be developed. This can be accomplished by selecting certain genetic and epigenetic variations to modify the network structure to attenuate intrinsic fluctuations efficiently and to resist extrinsic disturbances in order to maintain the phenotype of the evolutionary biological network at an equilibrium point (attractor). However, during carcinogenesis, the remaining (or neutral) genetic and epigenetic variations accumulate, and the extrinsic disturbances become too large to maintain the normal phenotype at the desired equilibrium point for the nonlinear evolutionary biological network. Thus, the network is shifted to a cancer phenotype at a new equilibrium point that begins a new evolutionary process. In this study, the natural selection scheme of an evolutionary biological network of carcinogenesis was derived from a robust negative feedback scheme based on the nonlinear stochastic Nash game strategy. The evolvability and phenotypic robustness criteria of the evolutionary cancer network were also estimated by solving a Hamilton–Jacobi inequality – constrained optimization problem. The simulation revealed that the phenotypic shift of the lung cancer

Improving the Effectiveness and Efficiency of Textbook Selection Procedures: A Smorgasbord of Suggestions and Strategies.

ERIC Educational Resources Information Center

Schumm, Jeanne Shay; Doucette, Martha

1991-01-01

Integrates strategies and suggestions from professional books and articles to provide educators with an overview of components of the textbook selection process. Organizes the smorgasbord into three sections: the salad bar (initial screening), the main course (examination of textbooks), and the dessert bar (plans for implementation of the textbook…

Web-Based Learning: Cognitive Styles and Instructional Strategies

ERIC Educational Resources Information Center

Alomyan, Hesham Raji

2016-01-01

This paper reports a study, which investigated whether different instructional strategies might interact with individual's cognitive style in learning. A web-based learning package was designed employing three strategies, Interactive Concept Maps, Illustration with Embedded Text and Text-Only. Group Embedded Figure Test was administered to 178…

Genetic and economic benefits of selection based on performance recording and genotyping in lower tiers of multi-tiered sheep breeding schemes.

PubMed

Santos, Bruno F S; van der Werf, Julius H J; Gibson, John P; Byrne, Timothy J; Amer, Peter R

2017-01-17

Performance recording and genotyping in the multiplier tier of multi-tiered sheep breeding schemes could potentially reduce the difference in the average genetic merit between nucleus and commercial flocks, and create additional economic benefits for the breeding structure. The genetic change in a multiple-trait breeding objective was predicted for various selection strategies that included performance recording, parentage testing and genomic selection. A deterministic simulation model was used to predict selection differentials and the flow of genetic superiority through the different tiers. Cumulative discounted economic benefits were calculated based on trait gains achieved in each of the tiers and considering the extra revenue and associated costs of applying recording, genotyping and selection practices in the multiplier tier of the breeding scheme. Performance recording combined with genomic or parentage information in the multiplier tier reduced the genetic lag between the nucleus and commercial flock by 2 to 3 years. The overall economic benefits of improved performance in the commercial tier offset the costs of recording the multiplier. However, it took more than 18 years before the cumulative net present value of benefits offset the costs at current test prices. Strategies in which recorded multiplier ewes were selected as replacements for the nucleus flock did modestly increase profitability when compared to a closed nucleus structure. Applying genomic selection is the most beneficial strategy if testing costs can be reduced or by genotyping only a proportion of the selection candidates. When the cost of genotyping was reduced, scenarios that combine performance recording with genomic selection were more profitable and reached breakeven point about 10 years earlier. Economic benefits can be generated in multiplier flocks by implementing performance recording in conjunction with either DNA pedigree recording or genomic technology. These recording

Electrochemical current rectification-a novel signal amplification strategy for highly sensitive and selective aptamer-based biosensor.

PubMed

Feng, Lingyan; Sivanesan, Arumugam; Lyu, Zhaozi; Offenhäusser, Andreas; Mayer, Dirk

2015-04-15

Electrochemical aptamer-based (E-AB) sensors represent an emerging class of recently developed sensors. However, numerous of these sensors are limited by a low surface density of electrode-bound redox-oligonucleotides which are used as probe. Here we propose to use the concept of electrochemical current rectification (ECR) for the enhancement of the redox signal of E-AB sensors. Commonly, the probe-DNA performs a change in conformation during target binding and enables a nonrecurring charge transfer between redox-tag and electrode. In our system, the redox-tag of the probe-DNA is continuously replenished by solution-phase redox molecules. A unidirectional electron transfer from electrode via surface-linked redox-tag to the solution-phase redox molecules arises that efficiently amplifies the current response. Using this robust and straight-forward strategy, the developed sensor showed a substantial signal amplification and consequently improved sensitivity with a calculated detection limit of 114nM for ATP, which was improved by one order of magnitude compared with the amplification-free detection and superior to other previous detection results using enzymes or nanomaterials-based signal amplification. To the best of our knowledge, this is the first demonstration of an aptamer-based electrochemical biosensor involving electrochemical rectification, which can be presumably transferred to other biomedical sensor systems. Copyright © 2014 Elsevier B.V. All rights reserved.

Control Strategies for the DAB Based PV Interface System

PubMed Central

El-Helw, Hadi M.; Al-Hasheem, Mohamed; Marei, Mostafa I.

2016-01-01

This paper presents an interface system based on the Dual Active Bridge (DAB) converter for Photovoltaic (PV) arrays. Two control strategies are proposed for the DAB converter to harvest the maximum power from the PV array. The first strategy is based on a simple PI controller to regulate the terminal PV voltage through the phase shift angle of the DAB converter. The Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) technique is utilized to set the reference of the PV terminal voltage. The second strategy presented in this paper employs the Artificial Neural Network (ANN) to directly set the phase shift angle of the DAB converter that results in harvesting maximum power. This feed-forward strategy overcomes the stability issues of the feedback strategy. The proposed PV interface systems are modeled and simulated using MATLAB/SIMULINK and the EMTDC/PSCAD software packages. The simulation results reveal accurate and fast response of the proposed systems. The dynamic performance of the proposed feed-forward strategy outdoes that of the feedback strategy in terms of accuracy and response time. Moreover, an experimental prototype is built to test and validate the proposed PV interface system. PMID:27560138

Improving the satellite communication efficiency of the accumulative acknowledgement strategies

NASA Astrophysics Data System (ADS)

Duarte, Otto Carlos M. B.; de Lima, Heliomar Medeiros

The performances of two finite buffer error recovery strategies are analyzed. In both strategies the retransmission request decision between selective repeat and continuous retransmission is based on an imminent buffer overflow condition. These are accumulative acknowledgment schemes, but in the second strategy the selective-repeat control frame is uniquely an individual negative acknowledgment. The two strategies take advantage of the availability of a greater buffer capacity, making the most of the selective repeat, postponing the sending of a continuous retransmission request. Numerical results show a better performance very close to the ideal, but it does not integrally conform to the high-level data link control (HDLC) procedures. It is shown that these strategies are well suited for high-speed data transfer in the high-error-rate satellite environment.

Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies

PubMed Central

Khamassi, Mehdi; Humphries, Mark D.

2012-01-01

Behavior in spatial navigation is often organized into map-based (place-driven) vs. map-free (cue-driven) strategies; behavior in operant conditioning research is often organized into goal-directed vs. habitual strategies. Here we attempt to unify the two. We review one powerful theory for distinct forms of learning during instrumental conditioning, namely model-based (maintaining a representation of the world) and model-free (reacting to immediate stimuli) learning algorithms. We extend these lines of argument to propose an alternative taxonomy for spatial navigation, showing how various previously identified strategies can be distinguished as “model-based” or “model-free” depending on the usage of information and not on the type of information (e.g., cue vs. place). We argue that identifying “model-free” learning with dorsolateral striatum and “model-based” learning with dorsomedial striatum could reconcile numerous conflicting results in the spatial navigation literature. From this perspective, we further propose that the ventral striatum plays key roles in the model-building process. We propose that the core of the ventral striatum is positioned to learn the probability of action selection for every transition between states of the world. We further review suggestions that the ventral striatal core and shell are positioned to act as “critics” contributing to the computation of a reward prediction error for model-free and model-based systems, respectively. PMID:23205006

Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming

NASA Astrophysics Data System (ADS)

Vercher, Enriqueta

2008-08-01

This paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.

A novel safety assessment strategy applied to non-selective extracts.

PubMed

Koster, Sander; Leeman, Winfried; Verheij, Elwin; Dutman, Ellen; van Stee, Leo; Nielsen, Lene Munch; Ronsmans, Stefan; Noteborn, Hub; Krul, Lisette

2015-06-01

A main challenge in food safety research is to demonstrate that processing of foodstuffs does not lead to the formation of substances for which the safety upon consumption might be questioned. This is especially so since food is a complex matrix in which the analytical detection of substances, and consequent risk assessment thereof, is difficult to determine. Here, a pragmatic novel safety assessment strategy is applied to the production of non-selective extracts (NSEs), used for different purposes in food such as for colouring purposes, which are complex food mixtures prepared from reference juices. The Complex Mixture Safety Assessment Strategy (CoMSAS) is an exposure driven approach enabling to efficiently assess the safety of the NSE by focussing on newly formed substances or substances that may increase in exposure during the processing of the NSE. CoMSAS enables to distinguish toxicologically relevant from toxicologically less relevant substances, when related to their respective levels of exposure. This will reduce the amount of work needed for identification, characterisation and safety assessment of unknown substances detected at low concentration, without the need for toxicity testing using animal studies. In this paper, the CoMSAS approach has been applied for elderberry and pumpkin NSEs used for food colouring purposes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bourdieu's Distinction between Rules and Strategies and Secondary Principal Practice: A Review of Selected Literature

ERIC Educational Resources Information Center

Anderson, Karen

2016-01-01

This paper reviews a selection of literature on secondary principal practice from which to propose an approach for further research. The review demonstrates that applications of Bourdieu's theory of practice have contributed to understandings about secondary principal practice, and that the distinction he made between rules and strategies has the…

Selecting and Assessing the Family-Friendly Community: Adaptive Strategies of Middle-Class, Dual-Earner Couples

ERIC Educational Resources Information Center

Sweet, Stephen; Swisher, Raymond; Moen, Phyllis

2005-01-01

Using a life course perspective, this study analyzes the adaptive strategy of community selection utilized by middle-class dual-earner couples, as well as the perceived family friendliness of their communities. Although many common concerns exist (most paramount being safety, jobs, and housing quality), parents are more apt than nonparents to…

A genetic replacement system for selection-based engineering of essential proteins

PubMed Central

2012-01-01

Background Essential genes represent the core of biological functions required for viability. Molecular understanding of essentiality as well as design of synthetic cellular systems includes the engineering of essential proteins. An impediment to this effort is the lack of growth-based selection systems suitable for directed evolution approaches. Results We established a simple strategy for genetic replacement of an essential gene by a (library of) variant(s) during a transformation. The system was validated using three different essential genes and plasmid combinations and it reproducibly shows transformation efficiencies on the order of 107 transformants per microgram of DNA without any identifiable false positives. This allowed for reliable recovery of functional variants out of at least a 105-fold excess of non-functional variants. This outperformed selection in conventional bleach-out strains by at least two orders of magnitude, where recombination between functional and non-functional variants interfered with reliable recovery even in recA negative strains. Conclusions We propose that this selection system is extremely suitable for evaluating large libraries of engineered essential proteins resulting in the reliable isolation of functional variants in a clean strain background which can readily be used for in vivo applications as well as expression and purification for use in in vitro studies. PMID:22898007

Design and Evaluation of Perceptual-based Object Group Selection Techniques

NASA Astrophysics Data System (ADS)

Dehmeshki, Hoda

Selecting groups of objects is a frequent task in graphical user interfaces. It is required prior to many standard operations such as deletion, movement, or modification. Conventional selection techniques are lasso, rectangle selection, and the selection and de-selection of items through the use of modifier keys. These techniques may become time-consuming and error-prone when target objects are densely distributed or when the distances between target objects are large. Perceptual-based selection techniques can considerably improve selection tasks when targets have a perceptual structure, for example when arranged along a line. Current methods to detect such groups use ad hoc grouping algorithms that are not based on results from perception science. Moreover, these techniques do not allow selecting groups with arbitrary arrangements or permit modifying a selection. This dissertation presents two domain-independent perceptual-based systems that address these issues. Based on established group detection models from perception research, the proposed systems detect perceptual groups formed by the Gestalt principles of good continuation and proximity. The new systems provide gesture-based or click-based interaction techniques for selecting groups with curvilinear or arbitrary structures as well as clusters. Moreover, the gesture-based system is adapted for the graph domain to facilitate path selection. This dissertation includes several user studies that show the proposed systems outperform conventional selection techniques when targets form salient perceptual groups and are still competitive when targets are semi-structured.

Oligonucleotide-based pharmaceuticals: Non-clinical and clinical safety signals and non-clinical testing strategies.

PubMed

Mustonen, Enni-Kaisa; Palomäki, Tiina; Pasanen, Markku

2017-11-01

Antisense oligonucleotides, short interfering RNAs (siRNAs) and aptamers are oligonucleotide-based pharmaceuticals with a promising role in targeted therapies. Currently, five oligonucleotide-based pharmaceuticals have achieved marketing authorization in Europe or USA and many more are undergoing clinical testing. However, several safety concerns have been raised in non-clinical and clinical studies. Oligonucleotides share properties with both chemical and biological pharmaceuticals and therefore they pose challenges also from the regulatory point of view. We have analyzed the safety data of oligonucleotides and evaluated the applicability of current non-clinical toxicological guidelines for assessing the safety of oligonucleotide-based pharmaceuticals. Oligonucleotide-based pharmaceuticals display a similar toxicological profile, exerting adverse effects on liver and kidney, evoking hematological alterations, as well as causing immunostimulation and prolonging the coagulation time. It is possible to extrapolate some of these effects from non-clinical studies to humans. However, evaluation strategies for genotoxicity testing of "non-natural" oligonucleotides should be revised. Additionally, the selective use of surrogates and prediction of clinical endpoints for non-clinically observed immunostimulation is complicated by its multiple potential manifestations, demanding improvements in the testing strategies. Utilizing more relevant and mechanistic-based approaches and taking better account of species differences, could possibly improve the prediction of relevant immunological/proinflammatory effects in humans. Copyright © 2017 Elsevier Inc. All rights reserved.

Strategies for a permanent lunar base

NASA Technical Reports Server (NTRS)

Duke, M. B.; Mendell, W. W.; Roberts, B. B.

1985-01-01

One or more of three possible objectives, encompassing scientific research, lunar resource exploitation for space infrastructure construction, and lunar environment self-sufficiency refinement with a view to future planetary habitation, may be the purpose of manned lunar base activities. Attention is presently given to the possibility that the early phases of all three lunar base orientations may be developed in such a way as to share the greatest number of common elements. An evaluation is made of the cost and complexity of the lunar base, and the Space Transportation System used in conjunction with it, as functions of long term base use strategy.

Confirming Preferences or Collecting Data? Information Search Strategies and Romantic Partner Selection

PubMed Central

Hennessy, Michael; Fishbein, Martin; Curtis, Brenda; Barrett, Daniel W.

2010-01-01

This article investigates two kinds of information search strategies in the context of selecting romantic partners. Confirmatory searching occurs when people ask for more information about a romantic partner in order to validate or confirm their assessment. Balanced searches are characterized by a search for risk information for partners rated as attractive and for attractiveness information about partners rated as risky in order to attain a more complete evaluation. A factorial survey computer program randomly constructed 5 types of partner descriptions and college-age respondents evaluated nine descriptions in terms of both health risk and romantic attractiveness outcomes. The results show little evidence of balanced search strategies: for all vignette types the respondents searched for attractiveness information. Regression analysis of the search outcomes showed no difference between males and females in the desire for attractiveness or risk information, the amount of additional information desired, or the proportion of descriptions for which more information was desired. However, an attractive physical appearance did increase the amount of additional information desired and the proportion of vignettes for which more information was desired. The results were generally inconsistent with a balanced search hypothesis; a better characterization of the respondents' strategy might be “confirmatory bias.” PMID:18350465

Confirming preferences or collecting data? Information search strategies and romantic partner selection.

PubMed

Hennessy, Michael H; Fishbein, Marty; Curtis, Brenda; Barrett, Daniel

2008-03-01

This article investigates two kinds of information search strategies in the context of selecting romantic partners. Confirmatory searching occurs when people ask for more information about a romantic partner in order to validate or confirm their assessment. Balanced searches are characterized by a search for risk information for partners rated as attractive and for attractiveness information about partners rated as risky in order to attain a more complete evaluation. A factorial survey computer program randomly constructed five types of partner descriptions and college-age respondents evaluated nine descriptions in terms of both health risk and romantic attractiveness outcomes. The results show little evidence of balanced search strategies: for all vignette types the respondents searched for attractiveness information. Regression analysis of the search outcomes showed no difference between males and females in the desire for attractiveness or risk information, the amount of additional information desired, or the proportion of descriptions for which more information was desired. However, an attractive physical appearance did increase the amount of additional information desired and the proportion of vignettes for which more information was desired. The results were generally inconsistent with a balanced search hypothesis; a better characterization of the respondents' strategy might be "confirmatory bias."

Multiobjective immune algorithm with nondominated neighbor-based selection.

PubMed

Gong, Maoguo; Jiao, Licheng; Du, Haifeng; Bo, Liefeng

2008-01-01

Abstract Nondominated Neighbor Immune Algorithm (NNIA) is proposed for multiobjective optimization by using a novel nondominated neighbor-based selection technique, an immune inspired operator, two heuristic search operators, and elitism. The unique selection technique of NNIA only selects minority isolated nondominated individuals in the population. The selected individuals are then cloned proportionally to their crowding-distance values before heuristic search. By using the nondominated neighbor-based selection and proportional cloning, NNIA pays more attention to the less-crowded regions of the current trade-off front. We compare NNIA with NSGA-II, SPEA2, PESA-II, and MISA in solving five DTLZ problems, five ZDT problems, and three low-dimensional problems. The statistical analysis based on three performance metrics including the coverage of two sets, the convergence metric, and the spacing, show that the unique selection method is effective, and NNIA is an effective algorithm for solving multiobjective optimization problems. The empirical study on NNIA's scalability with respect to the number of objectives shows that the new algorithm scales well along the number of objectives.

Information access in a dual-task context: testing a model of optimal strategy selection.

PubMed

Wickens, C D; Seidler, K S

1997-09-01

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

Information access in a dual-task context: testing a model of optimal strategy selection

NASA Technical Reports Server (NTRS)

Wickens, C. D.; Seidler, K. S.

1997-01-01

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

Breaking the color barrier - a multi-selective antibody reporter offers innovative strategies of fluorescence detection.

PubMed

Gallo, Eugenio; Jarvik, Jonathan W

2017-08-01

A novel bi-partite fluorescence platform exploits the high affinity and selectivity of antibody scaffolds to capture and activate small-molecule fluorogens. In this report, we investigated the property of multi-selectivity activation by a single antibody against diverse cyanine family fluorogens. Our fluorescence screen identified three cell-impermeant fluorogens, each with unique emission spectra (blue, green and red) and nanomolar affinities. Most importantly, as a protein fusion tag to G-protein-coupled receptors, the antibody biosensor retained full activity - displaying bright fluorogen signals with minimal background on live cells. Because fluorogen-activating antibodies interact with their target ligands via non-covalent interactions, we were able to perform advanced multi-color detection strategies on live cells, previously difficult or impossible with conventional reporters. We found that by fine-tuning the concentrations of the different color fluorogen molecules in solution, a user may interchange the fluorescence signal (onset versus offset), execute real-time signal exchange via fluorogen competition, measure multi-channel fluorescence via co-labeling, and assess real-time cell surface receptor traffic via pulse-chase experiments. Thus, here we inform of an innovative reporter technology based on tri-color signal that allows user-defined fluorescence tuning in live-cell applications. © 2017. Published by The Company of Biologists Ltd.

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

A strategy for selecting sexual partners believed to pose little/no risks for HIV: serosorting and its implications for HIV transmission.

PubMed

Eaton, Lisa A; Kalichman, Seth C; O'Connell, Daniel A; Karchner, William D

2009-10-01

A common HIV/AIDS risk reduction strategy among men who have sex with men (MSM) is to limit their unprotected sex partners to those who are of the same HIV status, a practice referred to as serosorting. Decisions to serosort for HIV risk reduction are based on personal impressions and beliefs, and there is limited guidance offered on this community derived strategy from public health services. This paper reviews research on serosorting for HIV risk reduction and offers an evidence-based approach to serosorting guidance. Following a comprehensive electronic and manual literature search, we reviewed 51 studies relating to the implications of serosorting. Studies showed that HIV negative MSM who select partners based on HIV status are inadvertently placing themselves at risk for HIV. Infrequent HIV testing, lack of HIV status disclosure, co-occurring sexually transmitted infections, and acute HIV infection impede the potential protective benefits of serosorting. Public health messages should continue to encourage reductions in numbers of sexual partners and increases in condom use. Risk reduction messages should also highlight the limitations of relying on one's own and partner's HIV status in making sexual risk decisions.

Genome-based nutrition: an intervention strategy for the prevention and treatment of obesity and nonalcoholic steatohepatitis.

PubMed

Roman, Sonia; Ojeda-Granados, Claudia; Ramos-Lopez, Omar; Panduro, Arturo

2015-03-28

Obesity and nonalcoholic steatohepatitis are increasing in westernized countries, regardless of their geographic location. In Latin America, most countries, including Mexico, have a heterogeneous admixture genome with Amerindian, European and African ancestries. However, certain high allelic frequencies of several nutrient-related polymorphisms may have been achieved by past gene-nutrient interactions. Such interactions may have promoted the positive selection of variants adapted to regional food sources. At present, the unbalanced diet composition of the Mexicans has led the country to a 70% prevalence rate of overweightness and obesity due to substantial changes in food habits, among other factors. International guidelines and intervention strategies may not be adequate for all populations worldwide because they do not consider disparities in genetic and environmental factors, and thus there is a need for differential prevention and management strategies. Here, we provide the rationale for an intervention strategy for the prevention and management of obesity-related diseases such as non-alcoholic steatohepatitis based on a regionalized genome-based diet. The components required to design such a diet should focus on the specific ancestry of each population around the world and the convenience of consuming traditional ethnic food.

Genome-based nutrition: An intervention strategy for the prevention and treatment of obesity and nonalcoholic steatohepatitis

PubMed Central

Roman, Sonia; Ojeda-Granados, Claudia; Ramos-Lopez, Omar; Panduro, Arturo

2015-01-01

Obesity and nonalcoholic steatohepatitis are increasing in westernized countries, regardless of their geographic location. In Latin America, most countries, including Mexico, have a heterogeneous admixture genome with Amerindian, European and African ancestries. However, certain high allelic frequencies of several nutrient-related polymorphisms may have been achieved by past gene-nutrient interactions. Such interactions may have promoted the positive selection of variants adapted to regional food sources. At present, the unbalanced diet composition of the Mexicans has led the country to a 70% prevalence rate of overweightness and obesity due to substantial changes in food habits, among other factors. International guidelines and intervention strategies may not be adequate for all populations worldwide because they do not consider disparities in genetic and environmental factors, and thus there is a need for differential prevention and management strategies. Here, we provide the rationale for an intervention strategy for the prevention and management of obesity-related diseases such as non-alcoholic steatohepatitis based on a regionalized genome-based diet. The components required to design such a diet should focus on the specific ancestry of each population around the world and the convenience of consuming traditional ethnic food. PMID:25834309

Selection of nursing teaching strategies in mainland China: A questionnaire survey.

PubMed

Zhou, HouXiu; Liu, MengJie; Zeng, Jing; Zhu, JingCi

2016-04-01

In nursing education, the traditional lecture and direct demonstration teaching method cannot cultivate the various skills that nursing students need. How to choose a more scientific and rational teaching method is a common concern for nursing educators worldwide. To investigate the basis for selecting teaching methods among nursing teachers in mainland China, the factors affecting the selection of different teaching methods, and the application of different teaching methods in theoretical and skill-based nursing courses. Questionnaire survey. Seventy one nursing colleges from 28 provincial-level administrative regions in mainland China. Following the principle of voluntary informed consent, 262 nursing teachers were randomly selected through a nursing education network platform and a conference platform. The questionnaire contents included the basis for and the factors influencing the selection of nursing teaching methods, the participants' common teaching methods, and the teaching experience of the surveyed nursing teachers. The questionnaires were distributed through the network or conference platform, and the data were analyzed by SPSS 17.0 software. The surveyed nursing teachers selected teaching methods mainly based on the characteristics of the teaching content, the characteristics of the students, and their previous teaching experiences. The factors affecting the selection of teaching methods mainly included large class sizes, limited class time, and limited examination formats. The surveyed nursing teachers primarily used lectures to teach theory courses and the direct demonstration method to teach skills courses, and the application frequencies of these two teaching methods were significantly higher than those of other teaching methods (P=0.000). More attention should be paid to the selection of nursing teaching methods. Every teacher should strategically choose teaching methods before each lesson, and nursing education training focused on selecting

Using inquiry-based instructional strategies in third-grade science

NASA Astrophysics Data System (ADS)

Harris, Fanicia D.

The purpose of the study was to determine if the use of inquiry-based instructional strategies as compared to traditional instructional strategies would increase third-grade students' achievement in science, based on the pretest/posttest of the school system and the Georgia Criterion-Referenced Competency Test (CRCT). Inquiry-based instruction, presented students with a question, an observation, a data set, or a hypothesis for problem solving such as scientists use when working in real-world situations. This descriptive research employed a quantitative strategy using a pretest/posttest control group design. The research compared the science academic achievement levels of one Grade 3 class [N=14] exposed to a teacher's inquiry-based instructional strategies as compared to one Grade 3 class [ N=18] exposed to a teacher's traditional instructional strategies. The study compared the science academic performance levels of third-grade students as measured by pretest/posttest mean scores from the school system-based assessment and the Georgia CRCT. Four research hypotheses were examined. Based on the overall findings from this study, both the experimental group and the control group significantly increased their mean scores from the pretests to the posttests. The amount of gain from the pretest to the posttest was significantly greater for the experimental group than the control group for pretest/posttest 1 [t(12) = 8.79, p < .01] and pretest/posttest 2 [t(12) = 9.40, p < .01]. The experimental group significantly outperformed the control group with regard to their mean number of items answered correctly on the life sciences test [t(27) = -1.95, p = .06]. Finally, the control group did not outperform the experimental group on any of the comparisons made throughout this study. The results of this study provide empirical support for the effectiveness of the use of inquiry-based learning strategies, given that the experimental group outperformed the control group on all four

Fault Diagnosis Strategies for SOFC-Based Power Generation Plants

PubMed Central

Costamagna, Paola; De Giorgi, Andrea; Gotelli, Alberto; Magistri, Loredana; Moser, Gabriele; Sciaccaluga, Emanuele; Trucco, Andrea

2016-01-01

The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements. PMID:27556472

Development of an operation strategy for hydrogen production using solar PV energy based on fluid dynamic aspects

NASA Astrophysics Data System (ADS)

Amores, Ernesto; Rodríguez, Jesús; Oviedo, José; de Lucas-Consuegra, Antonio

2017-06-01

Alkaline water electrolysis powered by renewable energy sources is one of the most promising strategies for environmentally friendly hydrogen production. However, wind and solar energy sources are highly dependent on weather conditions. As a result, power fluctuations affect the electrolyzer and cause several negative effects. Considering these limiting effects which reduce the water electrolysis efficiency, a novel operation strategy is proposed in this study. It is based on pumping the electrolyte according to the current density supplied by a solar PV module, in order to achieve the suitable fluid dynamics conditions in an electrolysis cell. To this aim, a mathematical model including the influence of electrode-membrane distance, temperature and electrolyte flow rate has been developed and used as optimization tool. The obtained results confirm the convenience of the selected strategy, especially when the electrolyzer is powered by renewable energies.

Design Strategies for Aptamer-Based Biosensors

PubMed Central

Han, Kun; Liang, Zhiqiang; Zhou, Nandi

2010-01-01

Aptamers have been widely used as recognition elements for biosensor construction, especially in the detection of proteins or small molecule targets, and regarded as promising alternatives for antibodies in bioassay areas. In this review, we present an overview of reported design strategies for the fabrication of biosensors and classify them into four basic modes: target-induced structure switching mode, sandwich or sandwich-like mode, target-induced dissociation/displacement mode and competitive replacement mode. In view of the unprecedented advantages brought about by aptamers and smart design strategies, aptamer-based biosensors are expected to be one of the most promising devices in bioassay related applications. PMID:22399891

Trophic Strategies of Unicellular Plankton.

PubMed

Chakraborty, Subhendu; Nielsen, Lasse Tor; Andersen, Ken H

2017-04-01

Unicellular plankton employ trophic strategies ranging from pure photoautotrophs over mixotrophy to obligate heterotrophs (phagotrophs), with cell sizes from 10 -8 to 1 μg C. A full understanding of how trophic strategy and cell size depend on resource environment and predation is lacking. To this end, we develop and calibrate a trait-based model for unicellular planktonic organisms characterized by four traits: cell size and investments in phototrophy, nutrient uptake, and phagotrophy. We use the model to predict how optimal trophic strategies depend on cell size under various environmental conditions, including seasonal succession. We identify two mixotrophic strategies: generalist mixotrophs investing in all three investment traits and obligate mixotrophs investing only in phototrophy and phagotrophy. We formulate two conjectures: (1) most cells are limited by organic carbon; however, small unicellulars are colimited by organic carbon and nutrients, and only large photoautotrophs and smaller mixotrophs are nutrient limited; (2) trophic strategy is bottom-up selected by the environment, while optimal size is top-down selected by predation. The focus on cell size and trophic strategies facilitates general insights into the strategies of a broad class of organisms in the size range from micrometers to millimeters that dominate the primary and secondary production of the world's oceans.

Morph-X-Select: Morphology-based tissue aptamer selection for ovarian cancer biomarker discovery

PubMed Central

Wang, Hongyu; Li, Xin; Volk, David E.; Lokesh, Ganesh L.-R.; Elizondo-Riojas, Miguel-Angel; Li, Li; Nick, Alpa M.; Sood, Anil K.; Rosenblatt, Kevin P.; Gorenstein, David G.

2016-01-01

High affinity aptamer-based biomarker discovery has the advantage of simultaneously discovering an aptamer affinity reagent and its target biomarker protein. Here, we demonstrate a morphology-based tissue aptamer selection method that enables us to use tissue sections from individual patients and identify high-affinity aptamers and their associated target proteins in a systematic and accurate way. We created a combinatorial DNA aptamer library that has been modified with thiophosphate substitutions of the phosphate ester backbone at selected 5′dA positions for enhanced nuclease resistance and targeting. Based on morphological assessment, we used image-directed laser microdissection (LMD) to dissect regions of interest bound with the thioaptamer (TA) library and further identified target proteins for the selected TAs. We have successfully identified and characterized the lead candidate TA, V5, as a vimentin-specific sequence that has shown specific binding to tumor vasculature of human ovarian tissue and human microvascular endothelial cells. This new Morph-X-Select method allows us to select high-affinity aptamers and their associated target proteins in a specific and accurate way, and could be used for personalized biomarker discovery to improve medical decision-making and to facilitate the development of targeted therapies to achieve more favorable outcomes. PMID:27839510

Task-Specific Response Strategy Selection on the Basis of Recent Training Experience

PubMed Central

Fulvio, Jacqueline M.; Green, C. Shawn; Schrater, Paul R.

2014-01-01

The goal of training is to produce learning for a range of activities that are typically more general than the training task itself. Despite a century of research, predicting the scope of learning from the content of training has proven extremely difficult, with the same task producing narrowly focused learning strategies in some cases and broadly scoped learning strategies in others. Here we test the hypothesis that human subjects will prefer a decision strategy that maximizes performance and reduces uncertainty given the demands of the training task and that the strategy chosen will then predict the extent to which learning is transferable. To test this hypothesis, we trained subjects on a moving dot extrapolation task that makes distinct predictions for two types of learning strategy: a narrow model-free strategy that learns an input-output mapping for training stimuli, and a general model-based strategy that utilizes humans' default predictive model for a class of trajectories. When the number of distinct training trajectories is low, we predict better performance for the mapping strategy, but as the number increases, a predictive model is increasingly favored. Consonant with predictions, subject extrapolations for test trajectories were consistent with using a mapping strategy when trained on a small number of training trajectories and a predictive model when trained on a larger number. The general framework developed here can thus be useful both in interpreting previous patterns of task-specific versus task-general learning, as well as in building future training paradigms with certain desired outcomes. PMID:24391490

Ensemble of surrogates-based optimization for identifying an optimal surfactant-enhanced aquifer remediation strategy at heterogeneous DNAPL-contaminated sites

NASA Astrophysics Data System (ADS)

Jiang, Xue; Lu, Wenxi; Hou, Zeyu; Zhao, Haiqing; Na, Jin

2015-11-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

Ensemble of Surrogates-based Optimization for Identifying an Optimal Surfactant-enhanced Aquifer Remediation Strategy at Heterogeneous DNAPL-contaminated Sites

NASA Astrophysics Data System (ADS)

Lu, W., Sr.; Xin, X.; Luo, J.; Jiang, X.; Zhang, Y.; Zhao, Y.; Chen, M.; Hou, Z.; Ouyang, Q.

2015-12-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

A universal strategy for the creation of machine learning-based atomistic force fields

NASA Astrophysics Data System (ADS)

Huan, Tran Doan; Batra, Rohit; Chapman, James; Krishnan, Sridevi; Chen, Lihua; Ramprasad, Rampi

2017-09-01

Emerging machine learning (ML)-based approaches provide powerful and novel tools to study a variety of physical and chemical problems. In this contribution, we outline a universal strategy to create ML-based atomistic force fields, which can be used to perform high-fidelity molecular dynamics simulations. This scheme involves (1) preparing a big reference dataset of atomic environments and forces with sufficiently low noise, e.g., using density functional theory or higher-level methods, (2) utilizing a generalizable class of structural fingerprints for representing atomic environments, (3) optimally selecting diverse and non-redundant training datasets from the reference data, and (4) proposing various learning approaches to predict atomic forces directly (and rapidly) from atomic configurations. From the atomistic forces, accurate potential energies can then be obtained by appropriate integration along a reaction coordinate or along a molecular dynamics trajectory. Based on this strategy, we have created model ML force fields for six elemental bulk solids, including Al, Cu, Ti, W, Si, and C, and show that all of them can reach chemical accuracy. The proposed procedure is general and universal, in that it can potentially be used to generate ML force fields for any material using the same unified workflow with little human intervention. Moreover, the force fields can be systematically improved by adding new training data progressively to represent atomic environments not encountered previously.

Assessing risk-adjustment approaches under non-random selection.

PubMed

Luft, Harold S; Dudley, R Adams

2004-01-01

Various approaches have been proposed to adjust for differences in enrollee risk in health plans. Because risk-selection strategies may have different effects on enrollment, we simulated three types of selection--dumping, skimming, and stinting. Concurrent diagnosis-based risk adjustment, and a hybrid using concurrent adjustment for about 8% of the cases and prospective adjustment for the rest, perform markedly better than prospective or demographic adjustments, both in terms of R2 and the extent to which plans experience unwarranted gains or losses. The simulation approach offers a valuable tool for analysts in assessing various risk-adjustment strategies under different selection situations.

NetProt: Complex-based Feature Selection.

PubMed

Goh, Wilson Wen Bin; Wong, Limsoon

2017-08-04

Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

Strategy selection in the minority game

NASA Astrophysics Data System (ADS)

D'hulst, R.; Rodgers, G. J.

2000-04-01

We investigate the dynamics of the choice of an active strategy in the minority game. A history distribution is introduced as an analytical tool to study the asymmetry between the two choices offered to the agents. Its properties are studied numerically. It allows us to show that the departure from uniformity in the initial attribution of strategies to the agents is important even in the efficient market. Also, an approximate expression for the variance of the number of agents at one side in the efficient phase is proposed. All the analytical propositions are supported by numerical simulations of the system.

General chemoselective and redox-responsive ligation and release strategy.

PubMed

Park, Sungjin; Westcott, Nathan P; Luo, Wei; Dutta, Debjit; Yousaf, Muhammad N

2014-03-19

We report a switchable redox click and cleave reaction strategy for conjugating and releasing a range of molecules on demand. This chemoselective redox-responsive ligation (CRRL) and release strategy is based on a redox switchable oxime linkage that is controlled by mild chemical or electrochemical redox signals and can be performed at physiological conditions without the use of a catalyst. Both conjugation and release reactions are kinetically well behaved and quantitative. The CRRL strategy is synthetically modular and easily monitored and characterized by routine analytical techniques. We demonstrate how the CRRL strategy can be used for the dynamic generation of cyclic peptides and the ligation of two different peptides that are stable but can be selectively cleaved upon changes in the redox environment. We also demonstrate a new redox based delivery of cargoes to live cells strategy via the CRRL methodology by synthesizing a FRET redox-responsive probe that is selectively activated within a cellular environment. We believe the ease of the CRRL strategy should find wide use in a range of applications in biology, tissue engineering, nanoscience, synthetic chemistry, and material science and will expand the suite of current conjugation and release strategies.

Development of a qPCR Strategy to Select Bean Genes Involved in Plant Defense Response and Regulated by the Trichoderma velutinum - Rhizoctonia solani Interaction.

PubMed

Mayo, Sara; Cominelli, Eleonora; Sparvoli, Francesca; González-López, Oscar; Rodríguez-González, Alvaro; Gutiérrez, Santiago; Casquero, Pedro A

2016-01-01

Bean production is affected by a wide diversity of fungal pathogens, among them Rhizoctonia solani is one of the most important. A strategy to control bean infectious diseases, mainly those caused by fungi, is based on the use of biocontrol agents (BCAs) that can reduce the negative effects of plant pathogens and also can promote positive responses in the plant. Trichoderma is a fungal genus that is able to induce the expression of genes involved in plant defense response and also to promote plant growth, root development and nutrient uptake. In this article, a strategy that combines in silico analysis and real time PCR to detect additional bean defense-related genes, regulated by the presence of Trichoderma velutinum and/or R. solani has been applied. Based in this strategy, from the 48 bean genes initially analyzed, 14 were selected, and only WRKY33, CH5b and hGS showed an up-regulatory response in the presence of T. velutinum. The other genes were or not affected (OSM34) or down-regulated by the presence of this fungus. R. solani infection resulted in a down-regulation of most of the genes analyzed, except PR1, OSM34 and CNGC2 that were not affected, and the presence of both, T. velutinum and R. solani, up-regulates hGS and down-regulates all the other genes analyzed, except CH5b which was not significantly affected. As conclusion, the strategy described in the present work has been shown to be effective to detect genes involved in plant defense, which respond to the presence of a BCA or to a pathogen and also to the presence of both. The selected genes show significant homology with previously described plant defense genes and they are expressed in bean leaves of plants treated with T. velutinum and/or infected with R. solani.

Employers' use of value-based purchasing strategies.

PubMed

Rosenthal, Meredith B; Landon, Bruce E; Normand, Sharon-Lise T; Frank, Richard G; Ahmad, Thaniyyah S; Epstein, Arnold M

2007-11-21

Value-based purchasing by employers has often been portrayed as the lynchpin to quality improvement in a market-based health care system. Although a small group of the largest national employers has been actively engaged in promoting quality measurement, reporting, and pay for performance, it is unknown whether these ideas have significantly permeated employer-sponsored health benefit purchasing. To provide systematic descriptions and analyses of value-based purchasing and related efforts to improve quality of care by health care purchasers. We conducted telephone interviews with executives at 609 of the largest employers across 41 US markets between July 2005 and March 2006. The 41 randomly selected markets have at least 100,000 persons enrolled in health maintenance organizations, include approximately 91% of individuals enrolled in health maintenance organizations nationally, and represent roughly 78% of the US metropolitan population. Using the Dun & Bradstreet database of US employers, we identified the 26 largest firms in each market. Firms ranged in size from 60 to 250,000 employees. The degree to which value-based purchasing and related strategies are reported being used by employers. Percentages were weighted by number of employees. Of 1041 companies contacted, 609 employer representatives completed the survey (response rate, 64%). A large percentage of surveyed executives reported that they examine health plan quality data (269 respondents; 65% [95% confidence interval {CI}, 57%-74%]; P<.001), but few reported using it for performance rewards (49 respondents; 17% [95% CI, 7%-27%]; P=.008) or to influence employees (71 respondents; 23% [95% CI, 13%-33%]). Physician quality information is even less commonly examined (71 respondents; 16% [95% CI, 9%-23%]) or used by employers to reward performance (8 respondents; 2% [95% CI, 0%-3%]) or influence employee choice of providers (34 respondents; 8% [95% CI, 3%-12%]). Surveyed employers as a whole do not appear to

A framework for sustainable nanomaterial selection and design based on performance, hazard, and economic considerations.

PubMed

Falinski, Mark M; Plata, Desiree L; Chopra, Shauhrat S; Theis, Thomas L; Gilbertson, Leanne M; Zimmerman, Julie B

2018-04-30

Engineered nanomaterials (ENMs) and ENM-enabled products have emerged as potentially high-performance replacements to conventional materials and chemicals. As such, there is an urgent need to incorporate environmental and human health objectives into ENM selection and design processes. Here, an adapted framework based on the Ashby material selection strategy is presented as an enhanced selection and design process, which includes functional performance as well as environmental and human health considerations. The utility of this framework is demonstrated through two case studies, the design and selection of antimicrobial substances and conductive polymers, including ENMs, ENM-enabled products and their alternatives. Further, these case studies consider both the comparative efficacy and impacts at two scales: (i) a broad scale, where chemical/material classes are readily compared for primary decision-making, and (ii) within a chemical/material class, where physicochemical properties are manipulated to tailor the desired performance and environmental impact profile. Development and implementation of this framework can inform decision-making for the implementation of ENMs to facilitate promising applications and prevent unintended consequences.

Evolution of cooperative strategies from first principles.

PubMed

Burtsev, Mikhail; Turchin, Peter

2006-04-20

One of the greatest challenges in the modern biological and social sciences is to understand the evolution of cooperative behaviour. General outlines of the answer to this puzzle are currently emerging as a result of developments in the theories of kin selection, reciprocity, multilevel selection and cultural group selection. The main conceptual tool used in probing the logical coherence of proposed explanations has been game theory, including both analytical models and agent-based simulations. The game-theoretic approach yields clear-cut results but assumes, as a rule, a simple structure of payoffs and a small set of possible strategies. Here we propose a more stringent test of the theory by developing a computer model with a considerably extended spectrum of possible strategies. In our model, agents are endowed with a limited set of receptors, a set of elementary actions and a neural net in between. Behavioural strategies are not predetermined; instead, the process of evolution constructs and reconstructs them from elementary actions. Two new strategies of cooperative attack and defence emerge in simulations, as well as the well-known dove, hawk and bourgeois strategies. Our results indicate that cooperative strategies can evolve even under such minimalist assumptions, provided that agents are capable of perceiving heritable external markers of other agents.

Identifying and ranking implicit leadership strategies to promote evidence-based practice implementation in addiction health services.

PubMed

Guerrero, Erick G; Padwa, Howard; Fenwick, Karissa; Harris, Lesley M; Aarons, Gregory A

2016-05-14

Despite a solid research base supporting evidence-based practices (EBPs) for addiction treatment such as contingency management and medication-assisted treatment, these services are rarely implemented and delivered in community-based addiction treatment programs in the USA. As a result, many clients do not benefit from the most current and efficacious treatments, resulting in reduced quality of care and compromised treatment outcomes. Previous research indicates that addiction program leaders play a key role in supporting EBP adoption and use. The present study expanded on this previous work to identify strategies that addiction treatment program leaders report using to implement new practices. We relied on a staged and iterative mixed-methods approach to achieve the following four goals: (a) collect data using focus groups and semistructured interviews and conduct analyses to identify implicit managerial strategies for implementation, (b) use surveys to quantitatively rank strategy effectiveness, (c) determine how strategies fit with existing theories of organizational management and change, and (d) use a consensus group to corroborate and expand on the results of the previous three stages. Each goal corresponded to a methodological phase, which included data collection and analytic approaches to identify and evaluate leadership interventions that facilitate EBP implementation in community-based addiction treatment programs. Findings show that the top-ranked strategies involved the recruitment and selection of staff members receptive to change, offering support and requesting feedback during the implementation process, and offering in vivo and hands-on training. Most strategies corresponded to emergent implementation leadership approaches that also utilize principles of transformational and transactional leadership styles. Leadership behaviors represented orientations such as being proactive to respond to implementation needs, supportive to assist staff members

Multidisciplinary perspectives for Alzheimer's and Parkinson's diseases: hydrogels for protein delivery and cell-based drug delivery as therapeutic strategies.

PubMed

Giordano, Carmen; Albani, Diego; Gloria, Antonio; Tunesi, Marta; Batelli, Sara; Russo, Teresa; Forloni, Gianluigi; Ambrosio, Luigi; Cigada, Alberto

2009-12-01

This review presents two intriguing multidisciplinary strategies that might make the difference in the treatment of neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. The first proposed strategy is based on the controlled delivery of recombinant proteins known to play a key role in these neurodegenerative disorders that are released in situ by optimized polymer-based systems. The second strategy is the use of engineered cells, encapsulated and delivered in situ by suitable polymer-based systems, that act as drug reservoirs and allow the delivery of selected molecules to be used in the treatment of Alzheimer's and Parkinson's diseases. In both these scenarios, the design and development of optimized polymer-based drug delivery and cell housing systems for central nervous system applications represent a key requirement. Materials science provides suitable hydrogel-based tools to be optimized together with suitably designed recombinant proteins or drug delivering-cells that, once in situ, can provide an effective treatment for these neurodegenerative disorders. In this scenario, only interdisciplinary research that fully integrates biology, biochemistry, medicine and materials science can provide a springboard for the development of suitable therapeutic tools, not only for the treatment of Alzheimer's and Parkinson's diseases but also, prospectively, for a wide range of severe neurodegenerative disorders.

Quantifying selective pressures driving bacterial evolution using lineage analysis

PubMed Central

Lambert, Guillaume; Kussell, Edo

2015-01-01

Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population’s rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages –i.e. the life-histories of individuals and their ancestors– to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to E. coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life-history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection, and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems. PMID:26213639

Quantifying Selective Pressures Driving Bacterial Evolution Using Lineage Analysis

NASA Astrophysics Data System (ADS)

Lambert, Guillaume; Kussell, Edo

2015-01-01

Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population's rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages—i.e., the life histories of individuals and their ancestors—to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to Escherichia coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems.

Competency-Based Human Resource Development Strategy

ERIC Educational Resources Information Center

Gangani, Noordeen T.; McLean, Gary N.; Braden, Richard A.

2004-01-01

This paper explores issues in developing and implementing a competency-based human resource development strategy. The paper summarizes a literature review on how competency models can improve HR performance. A case study is presented of American Medical Systems (AMS), a mid-sized health-care and medical device company, where the model is being…

Structure-Based Design of Potent and Selective 3-Phosphoinositide-Dependent Kinase-1 (PDK1) Inhibitors

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

Medina, Jesus R.; Becker, Christopher J.; Blackledge, Charles W.

2014-10-02

Phosphoinositide-dependent protein kinase-1(PDK1) is a master regulator of the AGC family of kinases and an integral component of the PI3K/AKT/mTOR pathway. As this pathway is among the most commonly deregulated across all cancers, a selective inhibitor of PDK1 might have utility as an anticancer agent. Herein we describe our lead optimization of compound 1 toward highly potent and selective PDK1 inhibitors via a structure-based design strategy. The most potent and selective inhibitors demonstrated submicromolar activity as measured by inhibition of phosphorylation of PDK1 substrates as well as antiproliferative activity against a subset of AML cell lines. In addition, reduction ofmore » phosphorylation of PDK1 substrates was demonstrated in vivo in mice bearing OCl-AML2 xenografts. These observations demonstrate the utility of these molecules as tools to further delineate the biology of PDK1 and the potential pharmacological uses of a PDK1 inhibitor.« less

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

PubMed

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.

Cytosine-based nucleoside analogs are selectively lethal to DNA mismatch repair-deficient tumour cells by enhancing levels of intracellular oxidative stress

PubMed Central

Hewish, M; Martin, S A; Elliott, R; Cunningham, D; Lord, C J; Ashworth, A

2013-01-01

Background: DNA mismatch repair deficiency is present in a significant proportion of a number of solid tumours and is associated with distinct clinical behaviour. Methods: To identify the therapeutic agents that might show selectivity for mismatch repair-deficient tumour cells, we screened a pair of isogenic MLH1-deficient and MLH1-proficient tumour cell lines with a library of clinically used drugs. To test the generality of hits in the screen, selective agents were retested in cells deficient in the MSH2 mismatch repair gene. Results: We identified cytarabine and other related cytosine-based nucleoside analogues as being selectively toxic to MLH1 and MSH2-deficient tumour cells. The selective cytotoxicity we observed was likely caused by increased levels of cellular oxidative stress, as it could be abrogated by antioxidants. Conclusion: We propose that cytarabine-based chemotherapy regimens may represent a tumour-selective treatment strategy for mismatch repair-deficient cancers. PMID:23361057

Nursing performance under high workload: a diary study on the moderating role of selection, optimization and compensation strategies.

PubMed

Baethge, Anja; Müller, Andreas; Rigotti, Thomas

2016-03-01

The aim of this study was to investigate whether selective optimization with compensation constitutes an individualized action strategy for nurses wanting to maintain job performance under high workload. High workload is a major threat to healthcare quality and performance. Selective optimization with compensation is considered to enhance the efficient use of intra-individual resources and, therefore, is expected to act as a buffer against the negative effects of high workload. The study applied a diary design. Over five consecutive workday shifts, self-report data on workload was collected at three randomized occasions during each shift. Self-reported job performance was assessed in the evening. Self-reported selective optimization with compensation was assessed prior to the diary reporting. Data were collected in 2010. Overall, 136 nurses from 10 German hospitals participated. Selective optimization with compensation was assessed with a nine-item scale that was specifically developed for nursing. The NASA-TLX scale indicating the pace of task accomplishment was used to measure workload. Job performance was assessed with one item each concerning performance quality and forgetting of intentions. There was a weaker negative association between workload and both indicators of job performance in nurses with a high level of selective optimization with compensation, compared with nurses with a low level. Considering the separate strategies, selection and compensation turned out to be effective. The use of selective optimization with compensation is conducive to nurses' job performance under high workload levels. This finding is in line with calls to empower nurses' individual decision-making. © 2015 John Wiley & Sons Ltd.

Learning Strategies of Successful and Unsuccessful University Students

ERIC Educational Resources Information Center

Simsek, Ali; Balaban, Jale

2010-01-01

The purpose of this study was to assess the most commonly used learning strategies of undergraduate students and how these strategies were related to their academic performance. Toward this purpose, a 60 item Likert scale was administered to a sample of 278 undergraduate students. The students were selected based on their cumulative…

Entropy-based gene ranking without selection bias for the predictive classification of microarray data.

PubMed

Furlanello, Cesare; Serafini, Maria; Merler, Stefano; Jurman, Giuseppe

2003-11-06

We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process). With E-RFE, we speed up the recursive feature elimination (RFE) with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

Strategies for Improving the Performance of Sensors Based on Organic Field-Effect Transistors.

PubMed

Wu, Xiaohan; Mao, Shun; Chen, Junhong; Huang, Jia

2018-04-01

Organic semiconductors (OSCs) have been extensively studied as sensing channel materials in field-effect transistors due to their unique charge transport properties. Stimulation caused by its environmental conditions can readily change the charge-carrier density and mobility of OSCs. Organic field-effect transistors (OFETs) can act as both signal transducers and signal amplifiers, which greatly simplifies the device structure. Over the past decades, various sensors based on OFETs have been developed, including physical sensors, chemical sensors, biosensors, and integrated sensor arrays with advanced functionalities. However, the performance of OFET-based sensors still needs to be improved to meet the requirements from various practical applications, such as high sensitivity, high selectivity, and rapid response speed. Tailoring molecular structures and micro/nanofilm structures of OSCs is a vital strategy for achieving better sensing performance. Modification of the dielectric layer and the semiconductor/dielectric interface is another approach for improving the sensor performance. Moreover, advanced sensory functionalities have been achieved by developing integrated device arrays. Here, a brief review of strategies used for improving the performance of OFET sensors is presented, which is expected to inspire and provide guidance for the design of future OFET sensors for various specific and practical applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Selective Distance-Based K+ Quantification on Paper-Based Microfluidics.

PubMed

Gerold, Chase T; Bakker, Eric; Henry, Charles S

2018-04-03

In this study, paper-based microfluidic devices (μPADs) capable of K + quantification in aqueous samples, as well as in human serum, using both colorimetric and distance-based methods are described. A lipophilic phase containing potassium ionophore I (valinomycin) was utilized to achieve highly selective quantification of K + in the presence of Na + , Li + , and Mg 2+ ions. Successful addition of a suspended lipophilic phase to a wax printed paper-based device is described and offers a solution to current approaches that rely on organic solvents, which damage wax barriers. The approach provides an avenue for future alkali/alkaline quantification utilizing μPADs. Colorimetric spot tests allowed for K + quantification from 0.1-5.0 mM using only 3.00 μL of sample solution. Selective distance-based quantification required small sample volumes (6.00 μL) and gave responses sensitive enough to distinguish between 1.0 and 2.5 mM of sample K + . μPADs using distance-based methods were also capable of differentiating between 4.3 and 6.9 mM K + in human serum samples. Distance-based methods required no digital analysis, electronic hardware, or pumps; any steps required for quantification could be carried out using the naked eye.

Community based rehabilitation: a strategy for peace-building

PubMed Central

Boyce, William; Koros, Michael; Hodgson, Jennifer

2002-01-01

Background Certain features of peace-building distinguish it from peacekeeping, and make it an appropriate strategy in dealing with vertical conflict and low intensity conflict. However, some theorists suggest that attempts, through peace-building, to impose liberal values upon non-democratic cultures are misguided and lack an ethical basis. Discussion We have been investigating the peace-building properties of community based approaches to disability in a number of countries. This paper describes the practice and impact of peace-building through Community Based Rehabilitation (CBR) strategies in the context of armed conflict. The ethical basis for peace-building through practical community initiatives is explored. A number of benefits and challenges to using CBR strategies for peace-building purposes are identified. Summary During post-conflict reconstruction, disability is a powerful emotive lever that can be used to mobilize cooperation between factions. We suggest that civil society, in contrast to state-level intervention, has a valuable role in reducing the risks of conflict through community initiatives. PMID:12417012

A New Strategy to Prepare Polymer-based Shape Memory Elastomers.

PubMed

Song, Shijie; Feng, Jiachun; Wu, Peiyi

2011-10-04

A new strategy that utilizes the microphase separation of block copolymer and phase transition of small molecules for preparing polymer-based shape memory elastomer has been proposed. According to this strategy, a novel kind of shape memory elastomer comprising styrene-b-(ethylene-co-butylene)-b-styrene (SEBS) and paraffin has been prepared. Because paraffins are midblock-selective molecules for SEBS, they will preferentially enter and swell EB blocks supporting paraffins as an excellent switch phase for shape memory effect. Microstructures of SEBS/paraffin composites have been characterized by transmission electron microscopy, polarized light microscopy, and differential scanning calorimetry. The composites demonstrate various phase morphologies with regard to different paraffin loading. It has been found that under low paraffin loading, all the paraffins precisely embed in and swell EB-rich domains. While under higher loading, part of the paraffins become free and a larger-scaled phase separation has been observed. However, within wide paraffin loadings, all composites show good shape fixing, shape recovery performances, and improved tensile properties. Compared to the reported methods for shape memory elastomers preparation, this method not only simplifies the fabrication procedure from raw materials to processing but also offers a controllable approach for the optimization of shape memory properties as well as balancing the rigidity and softness of the material. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Toward a Common Understanding of Research-Based Instructional Strategies

ERIC Educational Resources Information Center

Goodwin, Deborah; Webb, Mary Ann

2014-01-01

A review of available books, articles and on-line resources which deal with "Research-Based Instructional Strategies" will produce a plethora of materials which promote the effectiveness of these strategies on student achievement. Also, a perusal of classroom instruction and teacher evaluation instruments will reveal that many of the…

Nanosphere-based one-step strategy for efficient and nondestructive detection of circulating tumor cells.

PubMed

Wu, Ling-Ling; Wen, Cong-Ying; Hu, Jiao; Tang, Man; Qi, Chu-Bo; Li, Na; Liu, Cui; Chen, Lan; Pang, Dai-Wen; Zhang, Zhi-Ling

2017-08-15

Detecting viable circulating tumor cells (CTCs) without disruption to their functions for in vitro culture and functional study could unravel the biology of metastasis and promote the development of personalized anti-tumor therapies. However, existing CTC detection approaches commonly include CTC isolation and subsequent destructive identification, which damages CTC viability and functions and generates substantial CTC loss. To address the challenge of efficiently detecting viable CTCs for functional study, we develop a nanosphere-based cell-friendly one-step strategy. Immunonanospheres with prominent magnetic/fluorescence properties and extraordinary stability in complex matrices enable simultaneous efficient magnetic capture and specific fluorescence labeling of tumor cells directly in whole blood. The collected cells with fluorescent tags can be reliably identified, free of the tedious and destructive manipulations from conventional CTC identification. Hence, as few as 5 tumor cells in ca. 1mL of whole blood can be efficiently detected via only 20min incubation, and this strategy also shows good reproducibility with the relative standard deviation (RSD) of 8.7%. Moreover, due to the time-saving and gentle processing and the minimum disruption of immunonanospheres to cells, 93.8±0.1% of detected tumor cells retain cell viability and proliferation ability with negligible changes of cell functions, capacitating functional study on cell migration, invasion and glucose uptake. Additionally, this strategy exhibits successful CTC detection in 10/10 peripheral blood samples of cancer patients. Therefore, this nanosphere-based cell-friendly one-step strategy enables viable CTC detection and further functional analyses, which will help to unravel tumor metastasis and guide treatment selection. Copyright © 2017 Elsevier B.V. All rights reserved.

Label fusion based brain MR image segmentation via a latent selective model

NASA Astrophysics Data System (ADS)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

Healthy Aging Promotion through Neuroscientific Information-Based Strategies.

PubMed

Seinfeld, Sofia; Sanchez-Vives, Maria V

2015-09-28

To ensure the well-being of a rapidly growing elderly population, it is fundamental to find strategies to foster healthy brain aging. With this intention, we designed a program of scientific-based lectures aimed at dissemination by established neuroscientists about brain function, brain plasticity and how lifestyle influences the brain. We also carried out a pilot study on the impact of the lectures on attendees. The objective was to provide information to elderly people in order to encourage them to identify unhealthy and healthy daily habits, and more importantly, to promote behavioral changes towards healthy brain aging. Here we report on our experience. In order to determine the impact of the lectures in the daily routine of the attendees, we asked them to fill out questionnaires. Preliminary results indicate that neuroscientific information-based strategies can be a useful method to have a positive impact on the lives of elderly, increase their awareness on how to improve brain function and promote positive lifestyle modifications. Furthermore, based on self-reported data, we also found that through this strategy it is possible to promote behavioral changes related to nutrition, sleep, and realization of physical and cognitively stimulating activities. Finally, based on the results obtained, the importance of promoting self-efficacy and the empowerment of the older populations is highlighted.

Healthy Aging Promotion through Neuroscientific Information-Based Strategies

PubMed Central

Seinfeld, Sofia; Sanchez-Vives, Maria V.

2015-01-01

To ensure the well-being of a rapidly growing elderly population, it is fundamental to find strategies to foster healthy brain aging. With this intention, we designed a program of scientific-based lectures aimed at dissemination by established neuroscientists about brain function, brain plasticity and how lifestyle influences the brain. We also carried out a pilot study on the impact of the lectures on attendees. The objective was to provide information to elderly people in order to encourage them to identify unhealthy and healthy daily habits, and more importantly, to promote behavioral changes towards healthy brain aging. Here we report on our experience. In order to determine the impact of the lectures in the daily routine of the attendees, we asked them to fill out questionnaires. Preliminary results indicate that neuroscientific information-based strategies can be a useful method to have a positive impact on the lives of elderly, increase their awareness on how to improve brain function and promote positive lifestyle modifications. Furthermore, based on self-reported data, we also found that through this strategy it is possible to promote behavioral changes related to nutrition, sleep, and realization of physical and cognitively stimulating activities. Finally, based on the results obtained, the importance of promoting self-efficacy and the empowerment of the older populations is highlighted. PMID:26426029

Comparison of tablet-based strategies for incision planning in laser microsurgery

NASA Astrophysics Data System (ADS)

Schoob, Andreas; Lekon, Stefan; Kundrat, Dennis; Kahrs, Lüder A.; Mattos, Leonardo S.; Ortmaier, Tobias

2015-03-01

Recent research has revealed that incision planning in laser surgery deploying stylus and tablet outperforms state-of-the-art micro-manipulator-based laser control. Providing more detailed quantitation regarding that approach, a comparative study of six tablet-based strategies for laser path planning is presented. Reference strategy is defined by monoscopic visualization and continuous path drawing on a graphics tablet. Further concepts deploying stereoscopic or a synthesized laser view, point-based path definition, real-time teleoperation or a pen display are compared with the reference scenario. Volunteers were asked to redraw and ablate stamped lines on a sample. Performance is assessed by measuring planning accuracy, completion time and ease of use. Results demonstrate that significant differences exist between proposed concepts. The reference strategy provides more accurate incision planning than the stereo or laser view scenario. Real-time teleoperation performs best with respect to completion time without indicating any significant deviation in accuracy and usability. Point-based planning as well as the pen display provide most accurate planning and increased ease of use compared to the reference strategy. As a result, combining the pen display approach with point-based planning has potential to become a powerful strategy because of benefiting from improved hand-eye-coordination on the one hand and from a simple but accurate technique for path definition on the other hand. These findings as well as the overall usability scale indicating high acceptance and consistence of proposed strategies motivate further advanced tablet-based planning in laser microsurgery.

A dynamic replication management strategy in distributed GIS

NASA Astrophysics Data System (ADS)

Pan, Shaoming; Xiong, Lian; Xu, Zhengquan; Chong, Yanwen; Meng, Qingxiang

2018-03-01

Replication strategy is one of effective solutions to meet the requirement of service response time by preparing data in advance to avoid the delay of reading data from disks. This paper presents a brand-new method to create copies considering the selection of replicas set, the number of copies for each replica and the placement strategy of all copies. First, the popularities of all data are computed considering both the historical access records and the timeliness of the records. Then, replica set can be selected based on their recent popularities. Also, an enhanced Q-value scheme is proposed to assign the number of copies for each replica. Finally, a reasonable copies placement strategy is designed to meet the requirement of load balance. In addition, we present several experiments that compare the proposed method with techniques that use other replication management strategies. The results show that the proposed model has better performance than other algorithms in all respects. Moreover, the experiments based on different parameters also demonstrated the effectiveness and adaptability of the proposed algorithm.

Positive versus Negative Communication Strategies in Task-Based Learning

ERIC Educational Resources Information Center

Rohani, Siti

2013-01-01

This study aimed at describing how the implementation of Task-Based Learning (TBL) would shape or change students' use of oral communication strategies. Students' problems and strategies to solve the problems during the implementation of TBL were also explored. The study was a mixed method, employing both quantitative and qualitative analysis…

Discriminative Projection Selection Based Face Image Hashing

NASA Astrophysics Data System (ADS)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

Switch in Site of Inhibition: A Strategy for Structure-Based Discovery of Human Topoisomerase IIα Catalytic Inhibitors

PubMed Central

2015-01-01

A study of structure-based modulation of known ligands of hTopoIIα, an important enzyme involved in DNA processes, coupled with synthesis and in vitro assays led to the establishment of a strategy of rational switch in mode of inhibition of the enzyme’s catalytic cycle. 6-Arylated derivatives of known imidazopyridine ligands were found to be selective inhibitors of hTopoIIα, while not showing TopoI inhibition and DNA binding. Interestingly, while the parent imidazopyridines acted as ATP-competitive inhibitors, arylated derivatives inhibited DNA cleavage similar to merbarone, indicating a switch in mode of inhibition from ATP-hydrolysis to the DNA-cleavage stage of catalytic cycle of the enzyme. The 6-aryl-imidazopyridines were relatively more cytotoxic than etoposide in cancer cells and less toxic to normal cells. Such unprecedented strategy will encourage research on “choice-based change” in target-specific mode of action for rapid drug discovery. PMID:25941559

Specifying Skill-Based Training Strategies and Devices: A Model Description

DTIC Science & Technology

1990-06-01

Technical Report 897 Specifying Skill-Based Training N Strategies and Devices: A Model Description I Paui J. Sticha and Mark Schlager Human Resources...unlimied 90 ’ Technical Report 897 Specifying Skill-Based Training Strategies and Devices: A Model Description Paul J. Sticha and Mark Schlager Human...SECURITY CLASSIFICATION OF THIS PAGE Form Approved REPORT DOCUMENTATION PAGE FMNo o7 ote la. REPORT SECURITY CLASSIFICATION lb. RESTRICTWE MARKINGS

[Progress in the spectral library based protein identification strategy].

PubMed

Yu, Derui; Ma, Jie; Xie, Zengyan; Bai, Mingze; Zhu, Yunping; Shu, Kunxian

2018-04-25

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

What Successful Science Teachers Do: 75 Research-Based Strategies

ERIC Educational Resources Information Center

Glasgow, Neal A.; Cheyne, Michele; Yerrick, Randy K.

2010-01-01

The experience and science expertise of these award-winning authors makes this easy-to-use guide a teacher's treasure trove. This latest edition to the popular What Successful Teachers Do series describes 75 research-based strategies and outlines best practices for inquiry-oriented science. Each strategy includes a brief description of the…

A visual parallel-BCI speller based on the time-frequency coding strategy.

PubMed

Xu, Minpeng; Chen, Long; Zhang, Lixin; Qi, Hongzhi; Ma, Lan; Tang, Jiabei; Wan, Baikun; Ming, Dong

2014-04-01

Spelling is one of the most important issues in brain-computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time-frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time-frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min(-1), with an average of 54.0 bit min(-1) and 43.0 bit min(-1) in the three rounds and five rounds, respectively. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.

Age differences in strategy shift: retrieval avoidance or general shift reluctance?

PubMed

Frank, David J; Touron, Dayna R; Hertzog, Christopher

2013-09-01

Previous studies of metacognitive age differences in skill acquisition strategies have relied exclusively on tasks with a processing shift from an algorithm to retrieval strategy. Older adults' demonstrated reluctance to shift strategies in such tasks could reflect either a specific aversion to a memory retrieval strategy or a general, inertial resistance to strategy change. Haider and Frensch's (1999) alphabet verification task (AVT) affords a non-retrieval-based strategy shift. Participants verify the continuation of alphabet strings such as D E F G [4] L, with the bracketed digit indicating a number of letters to be skipped. When all deviations are restricted to the letter-digit-letter portion, participants can speed their responses by selectively attending to only that part of the stimulus. We adapted the AVT to include conditions that promoted shift to a retrieval strategy, a selective attention strategy, or both strategies. Item-level strategy reports were validated by eye movement data. Older adults shifted more slowly to the retrieval strategy but more quickly to the selective attention strategy than young adults, indicating a retrieval-strategy avoidance. Strategy confidence and perceived strategy difficulty correlated with shift to the two strategies in both age groups. Perceived speed of responses with each strategy specifically correlated with older adults' strategy choices, suggesting that some older adults avoid retrieval because they do not appreciate its efficiency benefits.

Age Differences in Strategy Shift: Retrieval Avoidance or General Shift Reluctance?

PubMed Central

Frank, David J.; Touron, Dayna R.; Hertzog, Christopher

2013-01-01

Previous studies of metacognitive age differences in skill acquisition strategies have relied exclusively on tasks with a processing shift from an algorithm to retrieval strategy. Older adults’ demonstrated reluctance to shift strategies in such tasks could reflect either a specific aversion to a memory retrieval strategy or a general, inertial resistance to strategy change. Haider and Frensch’s (1999) alphabet verification task (AVT) affords a non-retrieval-based strategy shift. Participants verify the continuation of alphabet strings such as D E F G [4] L, with the bracketed digit indicating a number of letters to be skipped. When all deviations are restricted to the letter-digit-letter portion, participants can speed their responses by selectively attend only to that part of the stimulus. We adapted the AVT to include conditions which promoted shift to a retrieval strategy, a selective attention strategy, or both strategies. Item-level strategy reports were validated by eye movement data. Older adults shifted more slowly to the retrieval strategy but more quickly to the selective attention strategy than young adults, indicating a retrieval-strategy avoidance. Strategy confidence and perceived strategy difficulty correlated with shift to the two strategies in both age groups. Perceived speed of responses with each strategy specifically correlated with older adults’ strategy choices, suggesting that some older adults avoid retrieval because they do not appreciate its efficiency benefits. PMID:23088195

Influence of scan strategy and molten pool configuration on microstructures and tensile properties of selective laser melting additive manufactured aluminum based parts

NASA Astrophysics Data System (ADS)

Dai, Donghua; Gu, Dongdong; Zhang, Han; Xiong, Jiapeng; Ma, Chenglong; Hong, Chen; Poprawe, Reinhart

2018-02-01

Selective laser melting additive manufacturing of the AlSi12 material parts through the re-melting of the previously solidified layer using the continuous two layers 90° rotate scan strategy was conducted. The influence of the re-melting behavior and scan strategy on the formation of the ;track-track; and ;layer-layer; molten pool boundaries (MPBs), dimensional accuracy, microstructure feature, tensile properties, microscopic sliding behavior and the fracture mechanism as loaded a tensile force has been studied. It showed that the defects, such as the part distortion, delamination and cracks, were significantly eliminated with the deformation rate less than 1%. The microstructure of a homogeneous distribution of the Si phase, no apparent grain orientation on both sides of the MPBs, was produced in the as-fabricated part, promoting the efficient transition of the load stress. Cracks preferentially initiate at the ;track-track; MPBs when the tensile stress increases to a certain value, resulting in the formation of the cleavage steps along the tensile loading direction. The cracks propagate along the ;layer-layer; MPBs, generating the fine dimples. The mechanical behavior of the SLM-processed AlSi12 parts can be significantly enhanced with the ultimate tensile strength, yield strength and elongation of 476.3 MPa, 315.5 MPa and 6.7%, respectively.

Improved routing strategy based on gravitational field theory

NASA Astrophysics Data System (ADS)

Song, Hai-Quan; Guo, Jin

2015-10-01

Routing and path selection are crucial for many communication and logistic applications. We study the interaction between nodes and packets and establish a simple model for describing the attraction of the node to the packet in transmission process by using the gravitational field theory, considering the real and potential congestion of the nodes. On the basis of this model, we propose a gravitational field routing strategy that considers the attractions of all of the nodes on the travel path to the packet. In order to illustrate the efficiency of proposed routing algorithm, we introduce the order parameter to measure the throughput of the network by the critical value of phase transition from a free flow phase to a congested phase, and study the distribution of betweenness centrality and traffic jam. Simulations show that, compared with the shortest path routing strategy, the gravitational field routing strategy considerably enhances the throughput of the network and balances the traffic load, and nearly all of the nodes are used efficiently. Project supported by the Technology and Development Research Project of China Railway Corporation (Grant No. 2012X007-D) and the Key Program of Technology and Development Research Foundation of China Railway Corporation (Grant No. 2012X003-A).

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

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

Choudhury, Sutanay; Holder, Larry; Chin, George

2015-02-02

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving net- works spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with promi- nent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphsmore » in a continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a “Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named “Relative Selectivity" that is used to se- lect between different query processing strategies. Our experiments performed on real online news, network traffic stream and a syn- thetic social network benchmark demonstrate 10-100x speedups over selectivity agnostic approaches.« less

Synthesis of pyrrole-imidazole polyamide oligomers based on a copper-catalyzed cross-coupling strategy.

PubMed

Shiga, Naoki; Takayanagi, Shihori; Muramoto, Risa; Murakami, Tasuku; Qin, Rui; Suzuki, Yuta; Shinohara, Ken-Ichi; Kaneda, Atsushi; Nemoto, Tetsuhiro

2017-05-15

Pyrrole-imidazole (Py-Im) polyamides are useful tools for chemical biology and medicinal chemistry studies due to their unique binding properties to the minor groove of DNA. We developed a novel method of synthesizing Py-Im polyamide oligomers based on a Cu-catalyzed cross-coupling strategy. All four patterns of dimer fragments could be synthesized using a Cu-catalyzed Ullmann-type cross-coupling with easily prepared monomer units. Moreover, we demonstrated that pyrrole dimer, trimer, and tetramer building blocks for Py-Im polyamide synthesis were accessible by combining site selective iodination of the pyrrole/pyrrole coupling adduct. Copyright © 2017 Elsevier Ltd. All rights reserved.

Selection of broilers for increased innate immune markers: Past strategies and looking ahead

USDA-ARS?s Scientific Manuscript database

Economic efficiency demanded by the poultry industry has pushed selection towards high production with improved feed conversion ratios (FCR) and high yield; however, selection based heavily on growth characteristics and other phenotypic traits has adversely affected immune competence. Despite incre...

Transfer of analytical procedures: a panel of strategies selected for risk management, with emphasis on an integrated equivalence-based comparative testing approach.

PubMed

Agut, C; Caron, A; Giordano, C; Hoffman, D; Ségalini, A

2011-09-10

In 2001, a multidisciplinary team made of analytical scientists and statisticians at Sanofi-aventis has published a methodology which has governed, from that time, the transfers from R&D sites to Manufacturing sites of the release monographs. This article provides an overview of the recent adaptations brought to this original methodology taking advantage of our experience and the new regulatory framework, and, in particular, the risk management perspective introduced by ICH Q9. Although some alternate strategies have been introduced in our practices, the comparative testing one, based equivalence testing as statistical approach, remains the standard for assays lying on very critical quality attributes. This is conducted with the concern to control the most important consumer's risk involved at two levels in analytical decisions in the frame of transfer studies: risk, for the receiving laboratory, to take poor release decisions with the analytical method and risk, for the sending laboratory, to accredit such a receiving laboratory on account of its insufficient performances with the method. Among the enhancements to the comparative studies, the manuscript presents the process settled within our company for a better integration of the transfer study into the method life-cycle, just as proposals of generic acceptance criteria and designs for assay and related substances methods. While maintaining rigor and selectivity of the original approach, these improvements tend towards an increased efficiency in the transfer operations. Copyright © 2011 Elsevier B.V. All rights reserved.

Advances in stable isotope assisted labeling strategies with information science.

PubMed

Kigawa, Takanori

2017-08-15

Stable-isotope (SI) labeling of proteins is an essential technique to investigate their structures, interactions or dynamics by nuclear magnetic resonance (NMR) spectroscopy. The assignment of the main-chain signals, which is the fundamental first step in these analyses, is usually achieved by a sequential assignment method based on triple resonance experiments. Independently of the triple resonance experiment-based sequential assignment, amino acid-selective SI labeling is beneficial for discriminating the amino acid type of each signal; therefore, it is especially useful for the signal assignment of difficult targets. Various combinatorial selective labeling schemes have been developed as more sophisticated labeling strategies. In these strategies, amino acids are represented by combinations of SI labeled samples, rather than simply assigning one amino acid to one SI labeled sample as in the case of conventional amino acid-selective labeling. These strategies have proven to be useful for NMR analyses of difficult proteins, such as those in large complex systems, in living cells, attached or integrated into membranes, or with poor solubility. In this review, recent advances in stable isotope assisted labeling strategies will be discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

The Learning Environment Counts: Longitudinal Qualitative Analysis of Study Strategies Adopted by First-Year Medical Students in a Competency-Based Educational Program.

PubMed

Bierer, S Beth; Dannefer, Elaine F

2016-11-01

The move toward competency-based education will require medical schools and postgraduate training programs to restructure learning environments to motivate trainees to take personal ownership for learning. This qualitative study explores how medical students select and implement study strategies while enrolled in a unique, nontraditional program that emphasizes reflection on performance and competence rather than relying on high-stakes examinations or grades to motivate students to learn and excel. Fourteen first-year medical students volunteered to participate in three, 45-minute interviews (42 overall) scheduled three months apart during 2013-2014. Two medical educators used structured interview guides to solicit students' previous assessment experiences, preferred learning strategies, and performance monitoring processes. Interviews were digitally recorded and transcribed verbatim. Participants confirmed accuracy of transcripts. Researchers independently read transcripts and met regularly to discuss transcripts and judge when themes achieved saturation. Medical students can adopt an assessment for learning mind-set with faculty guidance and implement appropriate study strategies for mastery-learning demands. Though students developed new strategies at different rates during the year, they all eventually identified study and performance monitoring strategies to meet learning needs. Students who had diverse learning experiences in college embraced mastery-based study strategies sooner than peers after recognizing that the learning environment did not reward performance-based strategies. Medical students can take ownership for their learning and implement specific strategies to regulate behavior when learning environments contain building blocks emphasized in self-determination theory. Findings should generalize to educational programs seeking strategies to design learning environments that promote self-regulated learning.

Selection of the open pit mining cut-off grade strategy under price uncertainty using a risk based multi-criteria ranking system / Wybór strategii określania warunku opłacalności wydobycia w kopalniach odkrywkowych w warunkach niepewności cen w oparciu o wielokryterialny system rankingowy z uwzględnieniem czynników ryzyka

NASA Astrophysics Data System (ADS)

Azimi, Yousue; Osanloo, Montza; Esfahanipour, Akbar

2012-12-01

Cut-off Grade Strategy (COGS) is a concept that directly influences the financial, technical, economic, environmental, and legal issues in relation to exploitation of a mineral resource. A decision making system is proposed to select the best technically feasible COGS under price uncertainty. In the proposed system both the conventional discounted cash flow and modern simulation based real option valuations are used to evaluate the alternative strategies. Then the conventional expected value criterion and a multiple criteria ranking system were used to rank the strategies based on the two valuation methods. In the multiple criteria ranking system besides the expected value other stochastic orders expressing abilities of strategies in producing extra profits, minimizing losses and achieving the predefined goals of the exploitation strategy are considered. Finally, the best strategy is selected based on the overall average rank of strategies through all ranking systems. The proposed system was examined using the data of Sungun Copper Mine. To assess the merits of the alternatives better, ranking process was done at both high (prevailing economic condition) and low price conditions. Ranking results revealed that at different price conditions and valuation methods, different results would be obtained. It is concluded that these differences are due to the different behavior of the embedded option to close the mine early, which is more likely to be exercised under low price condition rather than high price condition. The proposed system would enhance the quality of decision making process by providing a more informative and certain platform for project evaluation.

Strategies of marine dinoflagellate survival and some rules of assembly

NASA Astrophysics Data System (ADS)

Smayda, Theodore J.; Reynolds, Colin S.

2003-03-01

Dinoflagellate ecology is based on multiple adaptive strategies and species having diverse habitat preferences. Nine types of mixing-irradiance-nutrient habitats selecting for specific marine dinoflagellate life-form types are recognised, with five rules of assembly proposed to govern bloom-species selection and community organisation within these habitats. Assembly is moulded around an abiotic template of light energy, nutrient supply and physical mixing in permutative combinations. Species selected will have one of three basic ( C-, S-, R-) strategies: colonist species ( C-) which predominate in chemically disturbed habitats; nutrient stress tolerant species ( S-), and species ( R-) tolerant of shear/stress forces in physically disturbed water masses. This organisational plan of three major habitat variables and three major adaptive strategies is termed the 3-3 plan. The bloom behaviour and habitat specialisation of dinoflagellates and diatoms are compared. Dinoflagellates behave as annual species, bloom soloists, are ecophysiologically diverse, and habitat specialists whose blooms tend to be monospecific. Diatoms behave as perennial species, guild members, are habitat cosmopolites, have a relatively uniform bloom strategy based on species-rich pools and exhibit limited habitat specialisation. Dinoflagellate bloom-species selection follows a taxonomic hierarchical pathway which progresses from phylogenetic to generic to species selection, and in that sequence. Each hierarchical taxonomic level has its own adaptive requirements subject to rules of assembly. Dinoflagellates would appear to be well suited to exploit marine habitats and to be competitive with other phylogenetic groups, yet fail to do so.

Facile and Efficient Decontamination of Thorium from Rare Earths Based on Selective Selenite Crystallization.

PubMed

Wang, Yaxing; Lu, Huangjie; Dai, Xing; Duan, Tao; Bai, Xiaojing; Cai, Yawen; Yin, Xuemiao; Chen, Lanhua; Diwu, Juan; Du, Shiyu; Zhou, Ruhong; Chai, Zhifang; Albrecht-Schmitt, Thomas E; Liu, Ning; Wang, Shuao

2018-02-19

The coexistence of radioactive contaminants (e.g., thorium, uranium, and their daughters) in rare earth minerals introduces significant environmental, economic, and technological hurdles in modern rare earth production. Efficient, low cost, and green decontamination strategies are therefore desired to ameliorate this problem. We report here a single-step and quantitative decontamination strategy of thorium from rare earths based on a unique periodic trend in the formation of crystalline selenite compounds across the lanthanide series, where Ce(III) is fully oxidized in situ to Ce(IV). This gives rise to a crystallization system that is highly selective to trap tetravalent f-blocks while all other trivalent lanthanides completely remain in solution when coexist. These results are bolstered by first-principles calculations of lattice energies and an examination of bonding in these compounds. This system is contrasted with typical natural and synthetic systems, where trivalent and tetravalent f-block elements often cocrystallize. The separation factors after one round of crystallization were determined from binary systems of Th(IV)/La(III), Th(IV)/Eu(III), and Th(IV)/Yb(III) to reach 2.1 × 10 5 , 1.2 × 10 5 , and 9 × 10 4 , respectively. Selective crystallization of thorium from a simulated monazite composite yields a separation factor of 1.9 × 10 3 with nearly quantitative removal of thorium.

Teaching Business Strategy for an Emerging Economy: An Internet-Based Simulation.

ERIC Educational Resources Information Center

Miller, Van V.

2003-01-01

Describes an Internet-based simulation used in a course about business strategy in an emerging economy. The simulation, when coupled with today's dominant strategy paradigm, the Resource Based View, appears to yield a course design that attracts students while emphasizing the actual substance which is crucial in such a course. (EV)

Mixed strategy and coevolution dynamics in social networks

NASA Astrophysics Data System (ADS)

Zhong, Weicai; Abbass, Hussein A.; Bender, Axel; Liu, Jing

2011-01-01

We investigate coevolution dynamics of both individual strategies and social ties as they adapt within the snowdrift game with mixed strategies. We propose a partner selection mechanism based on the concept of trust. Here trust is considered an instrument for an individual both selecting the right partners and being selected amongst other potential partners. Based on her local views of the system, the focal individual dismisses the link from the partner with the lowest trust and rewires to the partner’s partner with the highest trust. It is shown that such a trust-based partner switching mechanism favors the emergence of cooperators. Furthermore, when the number of an individual’s partners is restricted (which is a metaphor of limited capacities and capabilities of an individual in real environments), surprising assortative mixing patterns are formed in the emerging network and change the network’s degree distribution from a power-law distribution to an asymmetrically U-shaped distribution. This plays a leading role in preventing global avalanches triggered by perturbations acting on the state of the highly connected individuals.

A Hydrazone-Based exo-Directing-Group Strategy for β C-H Oxidation of Aliphatic Amines.

PubMed

Huang, Zhongxing; Wang, Chengpeng; Dong, Guangbin

2016-04-18

Described is a new hydrazone-based exo-directing group (DG) strategy developed for the functionalization of unactivated primary β C-H bonds of aliphatic amines. Conveniently synthesized from protected primary amines, the hydrazone DGs are shown to site-selectively promote the β-acetoxylation and tosyloxylation via five-membered exo-palladacycles. Amines with a wide scope of skeletons and functional groups are tolerated. Moreover, the hydrazone DG can be readily removed, and a one-pot C-H acetoxylation/DG removal protocol was also discovered. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Selecting supplier combination based on fuzzy multicriteria analysis

NASA Astrophysics Data System (ADS)

Han, Zhi-Qiu; Luo, Xin-Xing; Chen, Xiao-Hong; Yang, Wu-E.

2015-07-01

Existing multicriteria analysis (MCA) methods are probably ineffective in selecting a supplier combination. Thus, an MCA-based fuzzy 0-1 programming method is introduced. The programming relates to a simple MCA matrix that is used to select a single supplier. By solving the programming, the most feasible combination of suppliers is selected. Importantly, this result differs from selecting suppliers one by one according to a single-selection order, which is used to rank sole suppliers in existing MCA methods. An example highlights such difference and illustrates the proposed method.

Social Networks-Based Adaptive Pairing Strategy for Cooperative Learning

ERIC Educational Resources Information Center

Chuang, Po-Jen; Chiang, Ming-Chao; Yang, Chu-Sing; Tsai, Chun-Wei

2012-01-01

In this paper, we propose a grouping strategy to enhance the learning and testing results of students, called Pairing Strategy (PS). The proposed method stems from the need of interactivity and the desire of cooperation in cooperative learning. Based on the social networks of students, PS provides members of the groups to learn from or mimic…

Evidentiary Pluralism as a Strategy for Research and Evidence-Based Practice in Rehabilitation Psychology