Novel nonlinear knowledge-based mean force potentials based on machine learning.

PubMed

Dong, Qiwen; Zhou, Shuigeng

2011-01-01

The prediction of 3D structures of proteins from amino acid sequences is one of the most challenging problems in molecular biology. An essential task for solving this problem with coarse-grained models is to deduce effective interaction potentials. The development and evaluation of new energy functions is critical to accurately modeling the properties of biological macromolecules. Knowledge-based mean force potentials are derived from statistical analysis of proteins of known structures. Current knowledge-based potentials are almost in the form of weighted linear sum of interaction pairs. In this study, a class of novel nonlinear knowledge-based mean force potentials is presented. The potential parameters are obtained by nonlinear classifiers, instead of relative frequencies of interaction pairs against a reference state or linear classifiers. The support vector machine is used to derive the potential parameters on data sets that contain both native structures and decoy structures. Five knowledge-based mean force Boltzmann-based or linear potentials are introduced and their corresponding nonlinear potentials are implemented. They are the DIH potential (single-body residue-level Boltzmann-based potential), the DFIRE-SCM potential (two-body residue-level Boltzmann-based potential), the FS potential (two-body atom-level Boltzmann-based potential), the HR potential (two-body residue-level linear potential), and the T32S3 potential (two-body atom-level linear potential). Experiments are performed on well-established decoy sets, including the LKF data set, the CASP7 data set, and the Decoys “R”Us data set. The evaluation metrics include the energy Z score and the ability of each potential to discriminate native structures from a set of decoy structures. Experimental results show that all nonlinear potentials significantly outperform the corresponding Boltzmann-based or linear potentials, and the proposed discriminative framework is effective in developing knowledge-based mean force potentials. The nonlinear potentials can be widely used for ab initio protein structure prediction, model quality assessment, protein docking, and other challenging problems in computational biology.

Importance of ligand reorganization free energy in protein-ligand binding-affinity prediction.

PubMed

Yang, Chao-Yie; Sun, Haiying; Chen, Jianyong; Nikolovska-Coleska, Zaneta; Wang, Shaomeng

2009-09-30

Accurate prediction of the binding affinities of small-molecule ligands to their biological targets is fundamental for structure-based drug design but remains a very challenging task. In this paper, we have performed computational studies to predict the binding models of 31 small-molecule Smac (the second mitochondria-derived activator of caspase) mimetics to their target, the XIAP (X-linked inhibitor of apoptosis) protein, and their binding affinities. Our results showed that computational docking was able to reliably predict the binding models, as confirmed by experimentally determined crystal structures of some Smac mimetics complexed with XIAP. However, all the computational methods we have tested, including an empirical scoring function, two knowledge-based scoring functions, and MM-GBSA (molecular mechanics and generalized Born surface area), yield poor to modest prediction for binding affinities. The linear correlation coefficient (r(2)) value between the predicted affinities and the experimentally determined affinities was found to be between 0.21 and 0.36. Inclusion of ensemble protein-ligand conformations obtained from molecular dynamic simulations did not significantly improve the prediction. However, major improvement was achieved when the free-energy change for ligands between their free- and bound-states, or "ligand-reorganization free energy", was included in the MM-GBSA calculation, and the r(2) value increased from 0.36 to 0.66. The prediction was validated using 10 additional Smac mimetics designed and evaluated by an independent group. This study demonstrates that ligand reorganization free energy plays an important role in the overall binding free energy between Smac mimetics and XIAP. This term should be evaluated for other ligand-protein systems and included in the development of new scoring functions. To our best knowledge, this is the first computational study to demonstrate the importance of ligand reorganization free energy for the prediction of protein-ligand binding free energy.

Mitochondria in Lung Diseases

PubMed Central

Aravamudan, Bharathi; Thompson, Michael A.; Pabelick, Christina M.; Prakash, Y. S.

2014-01-01

Summary Mitochondria are autonomous cellular organelles that oversee a variety of functions such as metabolism, energy production, calcium buffering, and cell fate determination. Regulation of their morphology and diverse activities beyond energy production are being recognized as playing major roles in cellular health and dysfunction. This review is aimed at summarizing what is known regarding mitochondrial contributions to pathogenesis of lung diseases. Emphasis is given to understanding the importance of structural and functional aspects of mitochondria in both normal cellular function (based on knowledge from other cell types) and in development and modulation of lung diseases such as asthma, COPD, cystic fibrosis and cancer. Emerging techniques that allow examination of mitochondria, and potential strategies to target mitochondria in the treatment of lung diseases are also discussed. PMID:23978003

Constraint methods that accelerate free-energy simulations of biomolecules.

PubMed

Perez, Alberto; MacCallum, Justin L; Coutsias, Evangelos A; Dill, Ken A

2015-12-28

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.

From Process Understanding Via Soil Functions to Sustainable Soil Management - A Systemic Approach

NASA Astrophysics Data System (ADS)

Wollschlaeger, U.; Bartke, S.; Bartkowski, B.; Daedlow, K.; Helming, K.; Kogel-Knabner, I.; Lang, B.; Rabot, E.; Russell, D.; Stößel, B.; Weller, U.; Wiesmeier, M.; Rabot, E.; Vogel, H. J.

2017-12-01

Fertile soils are central resources for the production of biomass and the provision of food and energy. A growing world population and latest climate targets lead to an increasing demand for both, food and bio-energy, which requires preserving and improving the long-term productivity of soils as a bio-economic resource. At the same time, other soil functions and ecosystem services need to be maintained: filter for clean water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these soil functions result from the interaction of a multitude of physical, chemical and biological processes that are not yet sufficiently understood. In addition, we lack understanding about the interplay between the socio-economic system and the soil system and how soil functions benefit human wellbeing. Hence, a solid and integrated assessment of soil quality requires the consideration of the ensemble of soil functions and its relation to soil management to finally be able to develop site-specific options for sustainable soil management. We present an integrated modeling approach that investigates the influence of soil management on the ensemble of soil functions. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. As the evidence base required for feeding the model is for the most part stored in the existing scientific literature, another central component of our work is to set up a public "knowledge-portal" providing the infrastructure for a community effort towards a comprehensive knowledge base on soil processes as a basis for model developments. The connection to the socio-economic system is established using the Drivers-Pressures-Impacts-States-Responses (DPSIR) framework where our improved understanding about soil ecosystem processes is linked to ecosystem services and resource efficiency via the soil functions.

Study of Impact on Undergraduates' Entrepreneurial Failure Based on the Model of Psychological Resilience-Knowledge Acquisition

ERIC Educational Resources Information Center

Jing, Tang; Dancheng, Luo; Ye, Zhao

2016-01-01

Purpose: The entrepreneurship is a course of gaining knowledge from the failure and stimulating positive energy constantly. The entrepreneur's psychological resilience is the key to gain knowledge (positive energy) from failure (negative energy). The education of undergraduate entrepreneurship is one of the priorities these days. Educators shall…

Predicting Multicomponent Adsorption Isotherms in Open-Metal Site Materials Using Force Field Calculations Based on Energy Decomposed Density Functional Theory.

PubMed

Heinen, Jurn; Burtch, Nicholas C; Walton, Krista S; Fonseca Guerra, Célia; Dubbeldam, David

2016-12-12

For the design of adsorptive-separation units, knowledge is required of the multicomponent adsorption behavior. Ideal adsorbed solution theory (IAST) breaks down for olefin adsorption in open-metal site (OMS) materials due to non-ideal donor-acceptor interactions. Using a density-function-theory-based energy decomposition scheme, we develop a physically justifiable classical force field that incorporates the missing orbital interactions using an appropriate functional form. Our first-principles derived force field shows greatly improved quantitative agreement with the inflection points, initial uptake, saturation capacity, and enthalpies of adsorption obtained from our in-house adsorption experiments. While IAST fails to make accurate predictions, our improved force field model is able to correctly predict the multicomponent behavior. Our approach is also transferable to other OMS structures, allowing the accurate study of their separation performances for olefins/paraffins and further mixtures involving complex donor-acceptor interactions. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Comparison of Functional Models for Use in the Function-Failure Design Method

NASA Technical Reports Server (NTRS)

Stock, Michael E.; Stone, Robert B.; Tumer, Irem Y.

2006-01-01

When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized functional and failure mode vocabularies are used. Two separate function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed functional models.

Quantum mechanical energy-based screening of combinatorially generated library of tautomers. TauTGen: a tautomer generator program.

PubMed

Harańczyk, Maciej; Gutowski, Maciej

2007-01-01

We describe a procedure of finding low-energy tautomers of a molecule. The procedure consists of (i) combinatorial generation of a library of tautomers, (ii) screening based on the results of geometry optimization of initial structures performed at the density functional level of theory, and (iii) final refinement of geometry for the top hits at the second-order Möller-Plesset level of theory followed by single-point energy calculations at the coupled cluster level of theory with single, double, and perturbative triple excitations. The library of initial structures of various tautomers is generated with TauTGen, a tautomer generator program. The procedure proved to be successful for these molecular systems for which common chemical knowledge had not been sufficient to predict the most stable structures.

Longitudinal determinants of energy levels in knowledge workers.

PubMed

Arnetz, Bengt B; Broadbridge, Carissa L; Ghosh, Samiran

2014-01-01

Increasingly, workers in the service, welfare, and health care sectors suffer adverse effects (ie, depression, burnout, etc) of "low-energy syndromes." Less is known about energy-based outcomes among knowledge workers. This study aimed to identify determinants of self-rated energy in knowledge workers and examine how these determinants change over time. In collaboration with a large union and employer federation, 317 knowledge workers in Sweden responded to the health and productivity survey three times. At each assessment, worry, satisfaction with eating habits, and work-effectiveness were predictive of energy levels; however, only work-effectiveness covaried with energy over time. This study suggests that perceived work-effectiveness is an important factor in preventing knowledge workers from experiencing "low-energy syndromes." Lifestyle factors also play a role. Therefore, multifaceted interventions for increasing energy are needed.

Locating landmarks on high-dimensional free energy surfaces

PubMed Central

Chen, Ming; Yu, Tang-Qing; Tuckerman, Mark E.

2015-01-01

Coarse graining of complex systems possessing many degrees of freedom can often be a useful approach for analyzing and understanding key features of these systems in terms of just a few variables. The relevant energy landscape in a coarse-grained description is the free energy surface as a function of the coarse-grained variables, which, despite the dimensional reduction, can still be an object of high dimension. Consequently, navigating and exploring this high-dimensional free energy surface is a nontrivial task. In this paper, we use techniques from multiscale modeling, stochastic optimization, and machine learning to devise a strategy for locating minima and saddle points (termed “landmarks”) on a high-dimensional free energy surface “on the fly” and without requiring prior knowledge of or an explicit form for the surface. In addition, we propose a compact graph representation of the landmarks and connections between them, and we show that the graph nodes can be subsequently analyzed and clustered based on key attributes that elucidate important properties of the system. Finally, we show that knowledge of landmark locations allows for the efficient determination of their relative free energies via enhanced sampling techniques. PMID:25737545

Effect of electromagnetic waves on human reproduction.

PubMed

Wdowiak, Artur; Mazurek, Paweł A; Wdowiak, Anita; Bojar, Iwona

2017-03-31

Electromagnetic radiation (EMR) emitting from the natural environment, as well as from the use of industrial and everyday appliances, constantly influence the human body. The effect of this type of energy on living tissues may exert various effects on their functioning, although the mechanisms conditioning this phenomenon have not been fully explained. It may be expected that the interactions between electromagnetic radiation and the living organism would depend on the amount and parameters of the transmitted energy and type of tissue exposed. Electromagnetic waves exert an influence on human reproduction by affecting the male and female reproductive systems, the developing embryo, and subsequently, the foetus. Knowledge concerning this problem is still being expanded; however, all the conditionings of human reproduction still remain unknown. The study presents the current state of knowledge concerning the problem, based on the latest scientific reports.

Adaptive pattern recognition by mini-max neural networks as a part of an intelligent processor

NASA Technical Reports Server (NTRS)

Szu, Harold H.

1990-01-01

In this decade and progressing into 21st Century, NASA will have missions including Space Station and the Earth related Planet Sciences. To support these missions, a high degree of sophistication in machine automation and an increasing amount of data processing throughput rate are necessary. Meeting these challenges requires intelligent machines, designed to support the necessary automations in a remote space and hazardous environment. There are two approaches to designing these intelligent machines. One of these is the knowledge-based expert system approach, namely AI. The other is a non-rule approach based on parallel and distributed computing for adaptive fault-tolerances, namely Neural or Natural Intelligence (NI). The union of AI and NI is the solution to the problem stated above. The NI segment of this unit extracts features automatically by applying Cauchy simulated annealing to a mini-max cost energy function. The feature discovered by NI can then be passed to the AI system for future processing, and vice versa. This passing increases reliability, for AI can follow the NI formulated algorithm exactly, and can provide the context knowledge base as the constraints of neurocomputing. The mini-max cost function that solves the unknown feature can furthermore give us a top-down architectural design of neural networks by means of Taylor series expansion of the cost function. A typical mini-max cost function consists of the sample variance of each class in the numerator, and separation of the center of each class in the denominator. Thus, when the total cost energy is minimized, the conflicting goals of intraclass clustering and interclass segregation are achieved simultaneously.

A Digital Game-Based Learning System for Energy Education: An Energy COnservation PET

ERIC Educational Resources Information Center

Yang, Jie Chi; Chien, Kun Huang; Liu, Tzu Chien

2012-01-01

Energy education has been conducted to equip learners with relevant energy conservation knowledge for many years. However, learners seldom put the knowledge into practice and even have few ideas about how to reduce energy consumption. To this end, there is a need to address this issue to improve the efficiency of energy education. One of the…

Representing energy efficiency diagnosis strategies in cognitive work analysis.

PubMed

Hilliard, Antony; Jamieson, Greg A

2017-03-01

This article describes challenges encountered in applying Jens Rasmussen's Cognitive Work Analysis (CWA) framework to the practice of energy efficiency Monitoring & Targeting (M&T). Eight theoretic issues encountered in the analysis are described with respect to Rasmussen's work and the modeling solutions we adopted. We grappled with how to usefully apply Work Domain Analysis (WDA) to analyze categories of domains with secondary purposes and no ideal grain of decomposition. This difficulty encouraged us to pursue Control Task (ConTA) and Strategies (StrA) analysis, which are under-explored as bases for interface design. In ConTA we found M&T was best represented by two interlinked work functions; one controlling energy, the other maintaining knowledge representations. From StrA, we identified a popular representation-dependent strategy and inferred information required to diagnose faults in system performance and knowledge representation. This article presents and discusses excerpts from our analysis, and outlines their application to diagnosis support tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

Energy literacy of Indiana high school practical arts and vocational teachers

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

Emshousen, F.W. Jr.

The purpose of the study was to develop an energy knowledge examination, investigate the extent high school teachers of home economics, agriculture, and industrial arts differ in their knowledge of energy, and to ascertain the extent their knowledge of energy differs with personal, educational, and geographic characteristics. Based upon literature review, a subject model was structured according to Bloom's (1956) taxonomy category of Knowledge and Hauenstein's (1972) procedure for classifying knowledges. Energy experts critically evaluated this model, which after refinement, was used to develop an Energy Knowledge Examination. The model consisted of six primary elements: sources, uses, costs, conservation, conversion,more » and policy issues. Energy experts reviewed items for accuracy, relevance, reading level, and clarity. The final instrument (65 multiple choice questions), was administered to a stratified random sample of Indiana public high school (IPHS) teachers from selected disciplines. Findings revealed significant biases among energy experts regarding relevance of specific subject content to the needs of teachers and students. Significant differences in the energy knowledge of IPHS teachers existed only in specific areas of the subject.« less

KoBaMIN: a knowledge-based minimization web server for protein structure refinement.

PubMed

Rodrigues, João P G L M; Levitt, Michael; Chopra, Gaurav

2012-07-01

The KoBaMIN web server provides an online interface to a simple, consistent and computationally efficient protein structure refinement protocol based on minimization of a knowledge-based potential of mean force. The server can be used to refine either a single protein structure or an ensemble of proteins starting from their unrefined coordinates in PDB format. The refinement method is particularly fast and accurate due to the underlying knowledge-based potential derived from structures deposited in the PDB; as such, the energy function implicitly includes the effects of solvent and the crystal environment. Our server allows for an optional but recommended step that optimizes stereochemistry using the MESHI software. The KoBaMIN server also allows comparison of the refined structures with a provided reference structure to assess the changes brought about by the refinement protocol. The performance of KoBaMIN has been benchmarked widely on a large set of decoys, all models generated at the seventh worldwide experiments on critical assessment of techniques for protein structure prediction (CASP7) and it was also shown to produce top-ranking predictions in the refinement category at both CASP8 and CASP9, yielding consistently good results across a broad range of model quality values. The web server is fully functional and freely available at http://csb.stanford.edu/kobamin.

On the use of the energy probability distribution zeros in the study of phase transitions

NASA Astrophysics Data System (ADS)

Mól, L. A. S.; Rodrigues, R. G. M.; Stancioli, R. A.; Rocha, J. C. S.; Costa, B. V.

2018-04-01

This contribution is devoted to cover some technical aspects related to the use of the recently proposed energy probability distribution zeros in the study of phase transitions. This method is based on the partial knowledge of the partition function zeros and has been shown to be extremely efficient to precisely locate phase transition temperatures. It is based on an iterative method in such a way that the transition temperature can be approached at will. The iterative method will be detailed and some convergence issues that has been observed in its application to the 2D Ising model and to an artificial spin ice model will be shown, together with ways to circumvent them.

Predicting protein complex geometries with a neural network.

PubMed

Chae, Myong-Ho; Krull, Florian; Lorenzen, Stephan; Knapp, Ernst-Walter

2010-03-01

A major challenge of the protein docking problem is to define scoring functions that can distinguish near-native protein complex geometries from a large number of non-native geometries (decoys) generated with noncomplexed protein structures (unbound docking). In this study, we have constructed a neural network that employs the information from atom-pair distance distributions of a large number of decoys to predict protein complex geometries. We found that docking prediction can be significantly improved using two different types of polar hydrogen atoms. To train the neural network, 2000 near-native decoys of even distance distribution were used for each of the 185 considered protein complexes. The neural network normalizes the information from different protein complexes using an additional protein complex identity input neuron for each complex. The parameters of the neural network were determined such that they mimic a scoring funnel in the neighborhood of the native complex structure. The neural network approach avoids the reference state problem, which occurs in deriving knowledge-based energy functions for scoring. We show that a distance-dependent atom pair potential performs much better than a simple atom-pair contact potential. We have compared the performance of our scoring function with other empirical and knowledge-based scoring functions such as ZDOCK 3.0, ZRANK, ITScore-PP, EMPIRE, and RosettaDock. In spite of the simplicity of the method and its functional form, our neural network-based scoring function achieves a reasonable performance in rigid-body unbound docking of proteins. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Systematic Uncertainties in High-Energy Hadronic Interaction Models

NASA Astrophysics Data System (ADS)

Zha, M.; Knapp, J.; Ostapchenko, S.

2003-07-01

Hadronic interaction models for cosmic ray energies are uncertain since our knowledge of hadronic interactions is extrap olated from accelerator experiments at much lower energies. At present most high-energy models are based on Grib ov-Regge theory of multi-Pomeron exchange, which provides a theoretical framework to evaluate cross-sections and particle production. While experimental data constrain some of the model parameters, others are not well determined and are therefore a source of systematic uncertainties. In this paper we evaluate the variation of results obtained with the QGSJET model, when modifying parameters relating to three ma jor sources of uncertainty: the form of the parton structure function, the role of diffractive interactions, and the string hadronisation. Results on inelastic cross sections, on secondary particle production and on the air shower development are discussed.

Enhancing Conceptual Knowledge of Energy in Biology with Incorrect Representations

ERIC Educational Resources Information Center

Wernecke, Ulrike; Schütte, Kerstin; Schwanewedel, Julia; Harms, Ute

2018-01-01

Energy is an important concept in all natural sciences, and a challenging one for school science education. Students' conceptual knowledge of energy is often low, and they entertain misconceptions. Educational research in science and mathematics suggests that learning through depictive representations and learning from errors, based on the theory…

A STATE-VARIABLE APPROACH FOR PREDICTING THE TIME REQUIRED FOR 50% RECRYSTALLIZATION

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

M. STOUT; ET AL

2000-08-01

It is important to be able to model the recrystallization kinetics in aluminum alloys during hot deformation. The industrial relevant process of hot rolling is an example of where the knowledge of whether or not a material recrystallizes is critical to making a product with the correct properties. Classically, the equations that describe the kinetics of recrystallization predict the time to 50% recrystallization. These equations are largely empirical; they are based on the free energy for recrystallization, a Zener-Holloman parameter, and have several adjustable exponents to fit the equation to engineering data. We have modified this form of classical theorymore » replacing the Zener-Hollomon parameter with a deformation energy increment, a free energy available to drive recrystallization. The advantage of this formulation is that the deformation energy increment is calculated based on the previously determined temperature and strain-rate sensitivity of the constitutive response. We modeled the constitutive response of the AA5182 aluminum using a state variable approach, the value of the state variable is a function of the temperature and strain-rate history of deformation. Thus, the recrystallization kinetics is a function of only the state variable and free energy for recrystallization. There are no adjustable exponents as in classical theory. Using this approach combined with engineering recrystallization data we have been able to predict the kinetics of recrystallization in AA5182 as a function of deformation strain rate and temperature.« less

Energy Content Estimation by Collegians for Portion Standardized Foods Frequently Consumed in Korea

PubMed Central

Kim, Jin; Lee, Hee Jung; Lee, Hyun Jung; Lee, Sun Ha; Yun, Jee-Young; Choi, Mi-Kyeong

2014-01-01

The purpose of this study is to estimate Korean collegians' knowledge of energy content in the standard portion size of foods frequently consumed in Korea and to investigate the differences in knowledge between gender groups. A total of 600 collegians participated in this study. Participants' knowledge was assessed based on their estimation on the energy content of 30 selected food items with their actual-size photo images. Standard portion size of food was based on 2010 Korean Dietary Reference Intakes, and the percentage of participants who accurately estimated (that is, within 20% of the true value) the energy content of the standard portion size was calculated for each food item. The food for which the most participants provided the accurate estimation was ramyun (instant noodles) (67.7%), followed by cooked rice (57.8%). The proportion of students who overestimated the energy content was highest for vegetables (68.8%) and beverages (68.1%). The proportion of students who underestimated the energy content was highest for grains and starches (42.0%) and fruits (37.1%). Female students were more likely to check energy content of foods that they consumed than male students. From these results, it was concluded that the knowledge on food energy content was poor among collegians, with some gender difference. Therefore, in the future, nutrition education programs should give greater attention to improving knowledge on calorie content and to helping them apply this knowledge in order to develop effective dietary plans. PMID:24527417

Energy content estimation by collegians for portion standardized foods frequently consumed in Korea.

PubMed

Kim, Jin; Lee, Hee Jung; Lee, Hyun Jung; Lee, Sun Ha; Yun, Jee-Young; Choi, Mi-Kyeong; Kim, Mi-Hyun

2014-01-01

The purpose of this study is to estimate Korean collegians' knowledge of energy content in the standard portion size of foods frequently consumed in Korea and to investigate the differences in knowledge between gender groups. A total of 600 collegians participated in this study. Participants' knowledge was assessed based on their estimation on the energy content of 30 selected food items with their actual-size photo images. Standard portion size of food was based on 2010 Korean Dietary Reference Intakes, and the percentage of participants who accurately estimated (that is, within 20% of the true value) the energy content of the standard portion size was calculated for each food item. The food for which the most participants provided the accurate estimation was ramyun (instant noodles) (67.7%), followed by cooked rice (57.8%). The proportion of students who overestimated the energy content was highest for vegetables (68.8%) and beverages (68.1%). The proportion of students who underestimated the energy content was highest for grains and starches (42.0%) and fruits (37.1%). Female students were more likely to check energy content of foods that they consumed than male students. From these results, it was concluded that the knowledge on food energy content was poor among collegians, with some gender difference. Therefore, in the future, nutrition education programs should give greater attention to improving knowledge on calorie content and to helping them apply this knowledge in order to develop effective dietary plans.

Density functional theory and chromium: Insights from the dimers

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

Würdemann, Rolf; Kristoffersen, Henrik H.; Moseler, Michael

2015-03-28

The binding in small Cr clusters is re-investigated, where the correct description of the dimer in three charge states is used as criterion to assign the most suitable density functional theory approximation. The difficulty in chromium arises from the subtle interplay between energy gain from hybridization and energetic cost due to exchange between s and d based molecular orbitals. Variations in published bond lengths and binding energies are shown to arise from insufficient numerical representation of electron density and Kohn-Sham wave-functions. The best functional performance is found for gradient corrected (GGA) functionals and meta-GGAs, where we find severe differences betweenmore » functionals from the same family due to the importance of exchange. Only the “best fit” from Bayesian error estimation is able to predict the correct energetics for all three charge states unambiguously. With this knowledge, we predict small bond-lengths to be exclusively present in Cr{sub 2} and Cr{sub 2}{sup −}. Already for the dimer cation, solely long bond-lengths appear, similar to what is found in the trimer and in chromium bulk.« less

Free Energy Perturbation Calculations of the Thermodynamics of Protein Side-Chain Mutations.

PubMed

Steinbrecher, Thomas; Abel, Robert; Clark, Anthony; Friesner, Richard

2017-04-07

Protein side-chain mutation is fundamental both to natural evolutionary processes and to the engineering of protein therapeutics, which constitute an increasing fraction of important medications. Molecular simulation enables the prediction of the effects of mutation on properties such as binding affinity, secondary and tertiary structure, conformational dynamics, and thermal stability. A number of widely differing approaches have been applied to these predictions, including sequence-based algorithms, knowledge-based potential functions, and all-atom molecular mechanics calculations. Free energy perturbation theory, employing all-atom and explicit-solvent molecular dynamics simulations, is a rigorous physics-based approach for calculating thermodynamic effects of, for example, protein side-chain mutations. Over the past several years, we have initiated an investigation of the ability of our most recent free energy perturbation methodology to model the thermodynamics of protein mutation for two specific problems: protein-protein binding affinities and protein thermal stability. We highlight recent advances in the field and outline current and future challenges. Copyright © 2017 Elsevier Ltd. All rights reserved.

A machine learning approach for ranking clusters of docked protein‐protein complexes by pairwise cluster comparison

PubMed Central

Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.

2017-01-01

ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158

Using a biased qubit to probe complex systems

NASA Astrophysics Data System (ADS)

Pollock, Felix A.; Checińska, Agata; Pascazio, Saverio; Modi, Kavan

2016-09-01

Complex mesoscopic systems play increasingly important roles in modern science, from understanding biological functions at the molecular level to designing solid-state information processing devices. The operation of these systems typically depends on their energetic structure, yet probing their energy landscape can be extremely challenging; they have many degrees of freedom, which may be hard to isolate and measure independently. Here, we show that a qubit (a two-level quantum system) with a biased energy splitting can directly probe the spectral properties of a complex system, without knowledge of how they couple. Our work is based on the completely positive and trace-preserving map formalism, which treats any unknown dynamics as a "black-box" process. This black box contains information about the system with which the probe interacts, which we access by measuring the survival probability of the initial state of the probe as function of the energy splitting and the process time. Fourier transforming the results yields the energy spectrum of the complex system. Without making assumptions about the strength or form of its coupling, our probe could determine aspects of a complex molecule's energy landscape as well as, in many cases, test for coherent superposition of its energy eigenstates.

First Extraction of Transversity from a Global Analysis of Electron-Proton and Proton-Proton Data

NASA Astrophysics Data System (ADS)

Radici, Marco; Bacchetta, Alessandro

2018-05-01

We present the first extraction of the transversity distribution in the framework of collinear factorization based on the global analysis of pion-pair production in deep-inelastic scattering and in proton-proton collisions with a transversely polarized proton. The extraction relies on the knowledge of dihadron fragmentation functions, which are taken from the analysis of electron-positron annihilation data. For the first time, the transversity is extracted from a global analysis similar to what is usually done for the spin-averaged and helicity distributions. The knowledge of transversity is important for, among other things, detecting possible signals of new physics in high-precision low-energy experiments.

Accurate wavelengths for X-ray spectroscopy and the NIST hydrogen-like ion database

NASA Astrophysics Data System (ADS)

Kotochigova, S. A.; Kirby, K. P.; Brickhouse, N. S.; Mohr, P. J.; Tupitsyn, I. I.

2005-06-01

We have developed an ab initio multi-configuration Dirac-Fock-Sturm method for the precise calculation of X-ray emission spectra, including energies, transition wavelengths and transition probabilities. The calculations are based on non-orthogonal basis sets, generated by solving the Dirac-Fock and Dirac-Fock-Sturm equations. Inclusion of Sturm functions into the basis set provides an efficient description of correlation effects in highly charged ions and fast convergence of the configuration interaction procedure. A second part of our study is devoted to developing a theoretical procedure and creating an interactive database to generate energies and transition frequencies for hydrogen-like ions. This procedure is highly accurate and based on current knowledge of the relevant theory, which includes relativistic, quantum electrodynamic, recoil, and nuclear size effects.

The integration of quantitative information with an intelligent decision support system for residential energy retrofits

NASA Astrophysics Data System (ADS)

Mo, Yunjeong

The purpose of this research is to support the development of an intelligent Decision Support System (DSS) by integrating quantitative information with expert knowledge in order to facilitate effective retrofit decision-making. To achieve this goal, the Energy Retrofit Decision Process Framework is analyzed. Expert system shell software, a retrofit measure cost database, and energy simulation software are needed for developing the DSS; Exsys Corvid, the NREM database and BEopt were chosen for implementing an integration model. This integration model demonstrates the holistic function of a residential energy retrofit system for existing homes, by providing a prioritized list of retrofit measures with cost information, energy simulation and expert advice. The users, such as homeowners and energy auditors, can acquire all of the necessary retrofit information from this unified system without having to explore several separate systems. The integration model plays the role of a prototype for the finalized intelligent decision support system. It implements all of the necessary functions for the finalized DSS, including integration of the database, energy simulation and expert knowledge.

The role of chemistry in the energy challenge.

PubMed

Schlögl, Robert

2010-02-22

Chemistry with its key targets of providing materials and processes for conversion of matter is at the center stage of the energy challenge. Most energy conversion systems work on (bio)chemical energy carriers and require for their use suitable process and material solutions. The enormous scale of their application demands optimization beyond the incremental improvement of empirical discoveries. Knowledge-based systematic approaches are mandatory to arrive at scalable and sustainable solutions. Chemistry for energy, "ENERCHEM" contributes in many ways already today to the use of fossil energy carriers. Optimization of these processes exemplified by catalysis for fuels and chemicals production or by solid-state lightning can contribute in the near future substantially to the dual challenge of energy use and climate protection being in fact two sides of the same challenge. The paper focuses on the even greater role that ENERCHEM will have to play in the era of renewable energy systems where the storage of solar energy in chemical carries and batteries is a key requirement. A multidisciplinary and diversified approach is suggested to arrive at a stable and sustainable system of energy conversion processes. The timescales for transformation of the present energy scenario will be decades and the resources will be of global economic dimensions. ENERCHEM will have to provide the reliable basis for such technologies based on deep functional understanding.

Microgrid energy dispatching for industrial zones with renewable generations and electric vehicles via stochastic optimization and learning

NASA Astrophysics Data System (ADS)

Zhang, Kai; Li, Jingzhi; He, Zhubin; Yan, Wanfeng

2018-07-01

In this paper, a stochastic optimization framework is proposed to address the microgrid energy dispatching problem with random renewable generation and vehicle activity pattern, which is closer to the practical applications. The patterns of energy generation, consumption and storage availability are all random and unknown at the beginning, and the microgrid controller design (MCD) is formulated as a Markov decision process (MDP). Hence, an online learning-based control algorithm is proposed for the microgrid, which could adapt the control policy with increasing knowledge of the system dynamics and converges to the optimal algorithm. We adopt the linear approximation idea to decompose the original value functions as the summation of each per-battery value function. As a consequence, the computational complexity is significantly reduced from exponential growth to linear growth with respect to the size of battery states. Monte Carlo simulation of different scenarios demonstrates the effectiveness and efficiency of our algorithm.

Developing Learning Progression-Based Teacher Knowledge Measures

ERIC Educational Resources Information Center

Jin, Hui; Shin, HyoJeong; Johnson, Michele E.; Kim, JinHo; Anderson, Charles W.

2015-01-01

This study developed learning progression-based measures of science teachers' content knowledge (CK) and pedagogical content knowledge (PCK). The measures focus on an important topic in secondary science curriculum using scientific reasoning (i.e., tracing matter, tracing energy, and connecting scales) to explain plants gaining weight and…

Fundamental Use of Surgical Energy (FUSE): An Essential Educational Program for Operating Room Safety

PubMed Central

Jones, Stephanie B; Munro, Malcolm G; Feldman, Liane S; Robinson, Thomas N; Brunt, L Michael; Schwaitzberg, Steven D; Jones, Daniel B; Fuchshuber, Pascal R

2017-01-01

Operating room (OR) safety has become a major concern in patient safety since the 1990s. Improvement of team communication and behavior is a popular target for safety programming at the institutional level. Despite these efforts, essential safety gaps remain in the OR and procedure rooms. A prime example is the use of energy-based devices in ORs and procedural areas. The lack of fundamental understanding of energy device function, design, and application contributes to avoidable injury and harm at a rate of approximately 1 to 2 per 1000 patients in the US. Hundreds of OR fires occur each year in the US, some causing severe injury and even death. Most of these fires are associated with the use of energy-based surgical devices. In response to this safety issue, the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) developed the Fundamental Use of Surgical Energy (FUSE) program. This program includes a standardized curriculum targeted to surgeons, other physicians, and allied health care professionals and a psychometrically designed and validated certification test. A successful FUSE certification documents acquisition of the basic knowledge needed to safely use energy-based devices in the OR. By design FUSE fills a void in the curriculum and competency assessment for surgeons and other procedural specialists in the use of energy-based devices in patients. PMID:28241913

Knowledge network model of the energy consumption in discrete manufacturing system

NASA Astrophysics Data System (ADS)

Xu, Binzi; Wang, Yan; Ji, Zhicheng

2017-07-01

Discrete manufacturing system generates a large amount of data and information because of the development of information technology. Hence, a management mechanism is urgently required. In order to incorporate knowledge generated from manufacturing data and production experience, a knowledge network model of the energy consumption in the discrete manufacturing system was put forward based on knowledge network theory and multi-granularity modular ontology technology. This model could provide a standard representation for concepts, terms and their relationships, which could be understood by both human and computer. Besides, the formal description of energy consumption knowledge elements (ECKEs) in the knowledge network was also given. Finally, an application example was used to verify the feasibility of the proposed method.

Investigation of Activation Cross Sections of the Proton Induced Nuclear Reactions on Natural Iron at Medium Energies

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

Ditroi, F.; Tarkanyi, F.; Csikai, J.

2005-05-24

Iron is one of the most important structural materials in every field of science, technology, industry, etc. Its application in a radiating environment requires the knowledge of accurate excitation functions for the possible reactions in question. By using the Thin Layer Activation technique (TLA) the knowledge of such data is also extremely important even in the case of relative measurements to design the irradiation (irradiation energy, beam intensity, duration) and also for radioactive safety estimations. The cross sections are frequently measured at low energies but there are unsatisfactory and unreliable data in the energy range above 40 MeV.

Investigation of Activation Cross Sections of the Proton Induced Nuclear Reactions on Natural Iron at Medium Energies

NASA Astrophysics Data System (ADS)

Ditrói, F.; Tárkányi, F.; Csikai, J.; Uddin, M. S.; Hagiwara, M.; Baba, M.

2005-05-01

Iron is one of the most important structural materials in every field of science, technology, industry, etc. Its application in a radiating environment requires the knowledge of accurate excitation functions for the possible reactions in question. By using the Thin Layer Activation technique (TLA) the knowledge of such data is also extremely important even in the case of relative measurements to design the irradiation (irradiation energy, beam intensity, duration) and also for radioactive safety estimations. The cross sections are frequently measured at low energies but there are unsatisfactory and unreliable data in the energy range above 40 MeV.

Study of the effects of informational and persuasive messages on the attitudes of high school students toward the use of nuclear energy for electrical production

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

Showers, D.E.

1986-01-01

This investigation assessed the relationship between knowledge about and attitudes toward nuclear energy. The study's purpose was accomplished by attempting to manipulate knowledge about and attitude toward nuclear energy independently. Over two thousand high school students participated in the study. A Non-Equivalent Control Group quasi-experimental design was used involving random assignment by intact groups to treatments. A knowledge treatment was designed to increase student knowledge without affecting attitudes. An attitude treatment was designed to change attitudes without changing knowledge, and a control treatment was employed for comparison to the experimental treatments. Each treatment consisted of a videotape with a viewingmore » guide and a homework assignment. The Nuclear Energy Assessment Battery was used as a pretest, post-test, and retention test. Males scored significantly higher in knowledge and positive attitudes, but no interaction between gender and treatment was found. The study concluded that (1) there is a correlation between nuclear knowledge and attitudes, (2) knowledge about nuclear energy can be changed without affecting attitude and attitude can be changed without affecting knowledge, and (3) students show differences and attitude based on gender.« less

State of knowledge about energy development impacts on North American rangelands: An integrative approach.

PubMed

Kreuter, Urs P; Iwaasa, Alan D; Theodori, Gene L; Ansley, R James; Jackson, Robert B; Fraser, Lauchlan H; Naeth, M Anne; McGillivray, Susan; Moya, Edmundo Garcia

2016-09-15

To reduce dependence on foreign oil reserves, there has been a push in North America to develop alternative domestic energy resources. Relatively undeveloped renewable energy resources include biofuels and wind and solar energy, many of which occur predominantly on rangelands. Rangelands are also key areas for natural gas development from shales and tight sand formations. Accordingly, policies aimed at greater energy independence are likely to affect the delivery of crucial ecosystem services provided by rangelands. Assessing and dealing with the biophysical and socio-economic effects of energy development on rangeland ecosystems require an integrative and systematic approach that is predicated on a broad understanding of diverse issues related to energy development. In this article, we present a road map for developing an integrative assessment of energy development on rangelands in North America. We summarize current knowledge of socio-economic and biophysical aspects of rangeland based energy development, and we identify knowledge gaps and monitoring indicators to fill these knowledge gaps. Copyright © 2016 Elsevier Ltd. All rights reserved.

Teaching physics using project-based engineering curriculum with a theme of alternative energy

NASA Astrophysics Data System (ADS)

Tasior, Bryan

The Next Generation Science Standards (NGSS) provide a new set of science standards that, if adopted, shift the focus from content knowledge-based to skill-based education. Students will be expected to use science to investigate the natural world and solve problems using the engineering design process. The world also is facing an impending crisis related to climate, energy supply and use, and alternative energy development. Education has an opportunity to help provide the much needed paradigm shift from our current methods of providing the energy needs of society. The purpose of this research was to measure the effectiveness of a unit that accomplishes the following objectives: uses project-based learning to teach the engineering process and standards of the NGSS, addresses required content expectations of energy and electricity from the HSCE's, and provides students with scientific evidence behind issues (both environmental and social/economic) relating to the energy crisis and current dependence of fossil fuels as our primary energy source. The results of the research indicate that a physics unit can be designed to accomplish these objectives. The unit that was designed, implemented and reported here also shows that it was highly effective at improving students' science content knowledge, implementing the engineering design standards of the NGSS, while raising awareness, knowledge and motivations relating to climate and the energy crisis.

Measuring the Scatter of the Mass–Richness Relation in Galaxy Clusters in Photometric Imaging Surveys by Means of Their Correlation Function

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

Campa, Julia; Estrada, Juan; Flaugher, Brenna

2017-02-03

The knowledge of the scatter in the mass-observable relation is a key ingredient for a cosmological analysis based on galaxy clusters in a photometric survey. We demonstrate here how the linear bias measured in the correlation function for clusters can be used to determine the value of the scatter. The new method is tested in simulations of a 5.000 square degrees optical survey up to z~1, similar to the ongoing Dark Energy Survey. The results indicate that the scatter can be measured with a precision of 5% using this technique.

Structural Variation of Alpha-synuclein with Temperature by a Coarse-grained Approach with Knowledge-based Interactions (Postprint)

DTIC Science & Technology

2015-07-01

the radius of gyration in detail as a function FIG. 5. Variation of the root mean square (RMS) displacement of the center of mass of the protein with...depends on the temperature. The global motion can be examined by analyzing the variation of the root mean square displacement (RMS) of the center of...and global physical quantities during the course of simula- tion, including the energy of each residue, its mobility, mean square displacement of the

The Avian Proghrelin System

USDA-ARS?s Scientific Manuscript database

To understand how the proghrelin system functions in regulating growth hormone release and food intake as well as defining its pleiotropic roles in such diverse physiological processes as energy homeostasis, gastrointestinal tract function and reproduction requires detailed knowledge of the structur...

Development of an expert system prototype for determining software functional requirements for command management activities at NASA Goddard

NASA Technical Reports Server (NTRS)

Liebowitz, J.

1986-01-01

The development of an expert system prototype for software functional requirement determination for NASA Goddard's Command Management System, as part of its process of transforming general requests into specific near-earth satellite commands, is described. The present knowledge base was formulated through interactions with domain experts, and was then linked to the existing Knowledge Engineering Systems (KES) expert system application generator. Steps in the knowledge-base development include problem-oriented attribute hierarchy development, knowledge management approach determination, and knowledge base encoding. The KES Parser and Inspector, in addition to backcasting and analogical mapping, were used to validate the expert system-derived requirements for one of the major functions of a spacecraft, the solar Maximum Mission. Knowledge refinement, evaluation, and implementation procedures of the expert system were then accomplished.

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, Betty M.

1988-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth science. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of US energy and mineral resources.

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, B.M.

1987-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth sciences. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of the Nation's energy and mineral resources.

Alchemical Free Energy Calculations for Nucleotide Mutations in Protein-DNA Complexes.

PubMed

Gapsys, Vytautas; de Groot, Bert L

2017-12-12

Nucleotide-sequence-dependent interactions between proteins and DNA are responsible for a wide range of gene regulatory functions. Accurate and generalizable methods to evaluate the strength of protein-DNA binding have long been sought. While numerous computational approaches have been developed, most of them require fitting parameters to experimental data to a certain degree, e.g., machine learning algorithms or knowledge-based statistical potentials. Molecular-dynamics-based free energy calculations offer a robust, system-independent, first-principles-based method to calculate free energy differences upon nucleotide mutation. We present an automated procedure to set up alchemical MD-based calculations to evaluate free energy changes occurring as the result of a nucleotide mutation in DNA. We used these methods to perform a large-scale mutation scan comprising 397 nucleotide mutation cases in 16 protein-DNA complexes. The obtained prediction accuracy reaches 5.6 kJ/mol average unsigned deviation from experiment with a correlation coefficient of 0.57 with respect to the experimentally measured free energies. Overall, the first-principles-based approach performed on par with the molecular modeling approaches Rosetta and FoldX. Subsequently, we utilized the MD-based free energy calculations to construct protein-DNA binding profiles for the zinc finger protein Zif268. The calculation results compare remarkably well with the experimentally determined binding profiles. The software automating the structure and topology setup for alchemical calculations is a part of the pmx package; the utilities have also been made available online at http://pmx.mpibpc.mpg.de/dna_webserver.html .

Photo nuclear energy loss term for muon-nucleus interactions based on xi scaling model of QCD

NASA Technical Reports Server (NTRS)

Roychoudhury, R.

1985-01-01

Extensive air showers (EMC) experiments discovered a significant deviation of the ratio of structure functions of iron and deuteron from unity. It was established that the quark parton distribution in nuclei are different from the corresponding distribution in the nucleus. It was examined whether these results have an effect on the calculation of photo nucleus energy loss term for muon-nucleus nuclear interaction. Though the EMC and SLAC data were restricted to rather large q sq region it is expected that the derivation would persist even in the low q sq domain. For the ratio of iron and deuteron structure function a rather naive least square fit of the form R(x) = a + bx was taken and it is assumed that the formula is valid for the whole q sq region the absence of any knowledge of R(x) for small q sq.

Simulating protein folding initiation sites using an alpha-carbon-only knowledge-based force field

PubMed Central

Buck, Patrick M.; Bystroff, Christopher

2015-01-01

Protein folding is a hierarchical process where structure forms locally first, then globally. Some short sequence segments initiate folding through strong structural preferences that are independent of their three-dimensional context in proteins. We have constructed a knowledge-based force field in which the energy functions are conditional on local sequence patterns, as expressed in the hidden Markov model for local structure (HMMSTR). Carbon-alpha force field (CALF) builds sequence specific statistical potentials based on database frequencies for α-carbon virtual bond opening and dihedral angles, pairwise contacts and hydrogen bond donor-acceptor pairs, and simulates folding via Brownian dynamics. We introduce hydrogen bond donor and acceptor potentials as α-carbon probability fields that are conditional on the predicted local sequence. Constant temperature simulations were carried out using 27 peptides selected as putative folding initiation sites, each 12 residues in length, representing several different local structure motifs. Each 0.6 μs trajectory was clustered based on structure. Simulation convergence or representativeness was assessed by subdividing trajectories and comparing clusters. For 21 of the 27 sequences, the largest cluster made up more than half of the total trajectory. Of these 21 sequences, 14 had cluster centers that were at most 2.6 Å root mean square deviation (RMSD) from their native structure in the corresponding full-length protein. To assess the adequacy of the energy function on nonlocal interactions, 11 full length native structures were relaxed using Brownian dynamics simulations. Equilibrated structures deviated from their native states but retained their overall topology and compactness. A simple potential that folds proteins locally and stabilizes proteins globally may enable a more realistic understanding of hierarchical folding pathways. PMID:19137613

Thermodynamic Diagrams

NASA Astrophysics Data System (ADS)

Chaston, Scot

1999-02-01

Thermodynamic data such as equilibrium constants, standard cell potentials, molar enthalpies of formation, and standard entropies of substances can be a very useful basis for an organized presentation of knowledge in diverse areas of applied chemistry. Thermodynamic data can become particularly useful when incorporated into thermodynamic diagrams that are designed to be easy to recall, to serve as a basis for reconstructing previous knowledge, and to determine whether reactions can occur exergonically or only with the help of an external energy source. Few students in our chemistry-based courses would want to acquire the depth of knowledge or rigor of professional thermodynamicists. But they should nevertheless learn how to make good use of thermodynamic data in their professional occupations that span the chemical, biological, environmental, and medical laboratory fields. This article discusses examples of three thermodynamic diagrams that have been developed for this purpose. They are the thermodynamic energy account (TEA), the total entropy scale, and the thermodynamic scale diagrams. These diagrams help in the teaching and learning of thermodynamics by bringing the imagination into the process of developing a better understanding of abstract thermodynamic functions, and by allowing the reader to keep track of specialist thermodynamic discourses in the literature.

Towards answering the "so what" question in marine renewables environmental impact assessment.

NASA Astrophysics Data System (ADS)

Degraer, Steven; Birchenough, Silvana N. R.; Braeckman, Ulrike; Coolen, Joop W. P.; Dannheim, Jennifer; De Mesel, Ilse; Grégoire, Marilaure; Kerckhof, Francis; Lacroix, Geneviève; Lindeboom, Han; Moens, Tom; Soetaert, Karline; Vanaverbeke, Jan; Van Hoey, Gert

2016-04-01

Marine renewable energy (MRE) projects are increasingly occupying the European North-Atlantic coasts and this is clearly observed in the North Sea. Given the expected impacts on the marine environment, each individual project is accompanied by a legally mandatory, environmental monitoring programme. These programmes are focused on the resultant effects on ecosystem component structure (e.g. species composition, numbers and densities) of single industrial projects. To date, there is a tendency to further narrow down to only a selection of ecosystem components (e.g. marine mammals and birds). While a wide knowledge-based understanding of structural impacts on (a selection of) ecosystem components exists, this evidence is largely lacking when undertaking impact assessments at the ecosystem functioning level (e.g. trophic interactions, dispersal and nutrient cycling). This critical knowledge gap compromises a scientifically-underpinned answer to the "so what" question of environmental impacts, i.e. whether the observed impacts are considered to be good or bad, or acceptable or unacceptable. The importance of ecosystem functioning is further acknowledged in the descriptors 4 and 6 of the Marine Strategy Framework Directive (EU MSFD) and is at the heart of a sustainable use and management of our marine resources. There hence is a fundamental need to focus on ecosystem functioning at the spatial scales at which marine ecosystems function when assessing MRE impacts. Here, we make a plea for an increased investment in a large (spatial) scale impact assessment of MRE projects focused on ecosystem functioning. This presentation will cover a selection of examples from North Sea MRE monitoring programmes, where the current knowledge has limited conclusions on the "so what" question. We will demonstrate how an ecosystem functioning-focused approach at an appropriate spatial scale could advance our current understanding, whilst assessing these issues. These examples will cover biogeochemical cycling, food webs and connectivity in a cumulative MRE impact assessment context. This presentation will highlight both the available knowledge base and further elaborate on the knowledge gaps. We will offer guidance on how these knowledge gaps could be further investigated, based on examples taken from the recently started projects FaCE-It, Functional biodiversity in a changing sedimentary environment: implications for biogeochemistry and food webs in a managerial setting (financed by the Belgian Science Policy) and UNDINE, Understanding the influence of man-made structures on the ecosystem functions of the North Sea (financed by INSITE). This presentation will set the scene and offer further thinking on the current issues associated to MRE monitoring, particularly beyond the level of ecological structure and individual industrial projects. The overall message will aid advancing and strengthening a collaborative MRE monitoring, helping scientists, managers and regulators to answer the much needed "so what" question to support environmental assessments. Keywords: offshore wind farms, cumulative effects, spatial upscaling, ecosystem functioning, biogeochemical cycling, food webs Contact author: Steven Degraer, steven.degraer@naturalsciences.be

Elucidating Hyperconjugation from Electronegativity to Predict Drug Conformational Energy in a High Throughput Manner.

PubMed

Liu, Zhaomin; Pottel, Joshua; Shahamat, Moeed; Tomberg, Anna; Labute, Paul; Moitessier, Nicolas

2016-04-25

Computational chemists use structure-based drug design and molecular dynamics of drug/protein complexes which require an accurate description of the conformational space of drugs. Organic chemists use qualitative chemical principles such as the effect of electronegativity on hyperconjugation, the impact of steric clashes on stereochemical outcome of reactions, and the consequence of resonance on the shape of molecules to rationalize experimental observations. While computational chemists speak about electron densities and molecular orbitals, organic chemists speak about partial charges and localized molecular orbitals. Attempts to reconcile these two parallel approaches such as programs for natural bond orbitals and intrinsic atomic orbitals computing Lewis structures-like orbitals and reaction mechanism have appeared. In the past, we have shown that encoding and quantifying chemistry knowledge and qualitative principles can lead to predictive methods. In the same vein, we thought to understand the conformational behaviors of molecules and to encode this knowledge back into a molecular mechanics tool computing conformational potential energy and to develop an alternative to atom types and training of force fields on large sets of molecules. Herein, we describe a conceptually new approach to model torsion energies based on fundamental chemistry principles. To demonstrate our approach, torsional energy parameters were derived on-the-fly from atomic properties. When the torsional energy terms implemented in GAFF, Parm@Frosst, and MMFF94 were substituted by our method, the accuracy of these force fields to reproduce MP2-derived torsional energy profiles and their transferability to a variety of functional groups and drug fragments were overall improved. In addition, our method did not rely on atom types and consequently did not suffer from poor automated atom type assignments.

Modeling the energy performance of event-driven wireless sensor network by using static sink and mobile sink.

PubMed

Chen, Jiehui; Salim, Mariam B; Matsumoto, Mitsuji

2010-01-01

Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations.

Modeling the Energy Performance of Event-Driven Wireless Sensor Network by Using Static Sink and Mobile Sink

PubMed Central

Chen, Jiehui; Salim, Mariam B.; Matsumoto, Mitsuji

2010-01-01

Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations. PMID:22163503

Simultaneous Multiparameter Cellular Energy Metabolism Profiling of Small Populations of Cells.

PubMed

Kelbauskas, Laimonas; Ashili, Shashaanka P; Lee, Kristen B; Zhu, Haixin; Tian, Yanqing; Meldrum, Deirdre R

2018-03-12

Functional and genomic heterogeneity of individual cells are central players in a broad spectrum of normal and disease states. Our knowledge about the role of cellular heterogeneity in tissue and organism function remains limited due to analytical challenges one encounters when performing single cell studies in the context of cell-cell interactions. Information based on bulk samples represents ensemble averages over populations of cells, while data generated from isolated single cells do not account for intercellular interactions. We describe a new technology and demonstrate two important advantages over existing technologies: first, it enables multiparameter energy metabolism profiling of small cell populations (<100 cells)-a sample size that is at least an order of magnitude smaller than other, commercially available technologies; second, it can perform simultaneous real-time measurements of oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and mitochondrial membrane potential (MMP)-a capability not offered by any other commercially available technology. Our results revealed substantial diversity in response kinetics of the three analytes in dysplastic human epithelial esophageal cells and suggest the existence of varying cellular energy metabolism profiles and their kinetics among small populations of cells. The technology represents a powerful analytical tool for multiparameter studies of cellular function.

Work function of bulk-insulating topological insulator Bi{sub 2–x}Sb{sub x}Te{sub 3–y}Se{sub y}

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

Takane, Daichi; Souma, Seigo; Center for Spintronics Research Network, Tohoku University, Sendai 980-8577

Recent discovery of bulk insulating topological insulator (TI) Bi{sub 2–x}Sb{sub x}Te{sub 3–y}Se{sub y} paved a pathway toward practical device application of TIs. For realizing TI-based devices, it is necessary to contact TIs with a metal. Since the band-bending at the interface dominates the character of devices, knowledge of TIs' work function is of essential importance. We have determined the compositional dependence of the work function in Bi{sub 2–x}Sb{sub x}Te{sub 3–y}Se{sub y} by high-resolution photoemission spectroscopy. The obtained work-function values (4.95–5.20 eV) track the energy shift of the surface chemical potential seen by angle-resolved photoemission spectroscopy. The present result serves as amore » useful guide for developing TI-based electronic devices.« less

A novel vortex tube-based N2-expander liquefaction process for enhancing the energy efficiency of natural gas liquefaction

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Wei, Feng; Hussain, Arif; Ali, Wahid; Sehee, Oh; Lee, Moonyong

2017-11-01

This research work unfolds a simple, safe, and environment-friendly energy efficient novel vortex tube-based natural gas liquefaction process (LNG). A vortex tube was introduced to the popular N2-expander liquefaction process to enhance the liquefaction efficiency. The process structure and condition were modified and optimized to take a potential advantage of the vortex tube on the natural gas liquefaction cycle. Two commercial simulators ANSYS® and Aspen HYSYS® were used to investigate the application of vortex tube in the refrigeration cycle of LNG process. The Computational fluid dynamics (CFD) model was used to simulate the vortex tube with nitrogen (N2) as a working fluid. Subsequently, the results of the CFD model were embedded in the Aspen HYSYS® to validate the proposed LNG liquefaction process. The proposed natural gas liquefaction process was optimized using the knowledge-based optimization (KBO) approach. The overall energy consumption was chosen as an objective function for optimization. The performance of the proposed liquefaction process was compared with the conventional N2-expander liquefaction process. The vortex tube-based LNG process showed a significant improvement of energy efficiency by 20% in comparison with the conventional N2-expander liquefaction process. This high energy efficiency was mainly due to the isentropic expansion of the vortex tube. It turned out that the high energy efficiency of vortex tube-based process is totally dependent on the refrigerant cold fraction, operating conditions as well as refrigerant cycle configurations.

NRV web knowledge base on low-energy nuclear physics

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

Karpov, V., E-mail: karpov@jinr.ru; Denikin, A. S.; Alekseev, A. P.

Principles underlying the organization and operation of the NRV web knowledge base on low-energy nuclear physics (http://nrv.jinr.ru) are described. This base includes a vast body of digitized experimental data on the properties of nuclei and on cross sections for nuclear reactions that is combined with a wide set of interconnected computer programs for simulating complex nuclear dynamics, which work directly in the browser of a remote user. Also, the current situation in the realms of application of network information technologies in nuclear physics is surveyed. The potential of the NRV knowledge base is illustrated in detail by applying it tomore » the example of an analysis of the fusion of nuclei that is followed by the decay of the excited compound nucleus formed.« less

Renewable energy education and industrial arts: linking knowledge producers with knowledge

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

Foley, R.L.

This study introduces renewable energy technology into the industrial arts programs in the State of New Hampshire by providing the following information for decision making: (1) a broad-based perspective on renewable energy technology; (2) the selection of an educational change model; (3) data from a needs analysis; (4) an initial screening of potential teacher-trainers. The Wolf-Welsh Linkage Model was selected as the knowledge production/utilization model for bridging the knowledge gap between renewable energy experts and industrial arts teachers. Ninety-six renewable energy experts were identified by a three-step peer nomination process (92% response rate). The experts stressed the conceptual foundations, economicmore » justifications, and the scientific and quantitative basics of renewable energy technology. The teachers focused on wood-burning technology, educational strategies, and the more popular alternative energy sources such as windpower, hydropower, photovoltaics, and biomass. The most emphatic contribution of the needs analysis was the experts' and teachers' shared perception that residential/commercial building design, retrofitting, and construction is the single most important practical, technical area for the application of renewable energy technology.« less

Research on Knowledge-Based Optimization Method of Indoor Location Based on Low Energy Bluetooth

NASA Astrophysics Data System (ADS)

Li, C.; Li, G.; Deng, Y.; Wang, T.; Kang, Z.

2017-09-01

With the rapid development of LBS (Location-based Service), the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1) The establishment and application of a priori and posterior knowledge base. 2) Primary selection of signal source. 3) Elimination of positioning gross error. 4) Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.

On the hydrophilicity of electrodes for capacitive energy extraction

NASA Astrophysics Data System (ADS)

Lian, Cheng; Kong, Xian; Liu, Honglai; Wu, Jianzhong

2016-11-01

The so-called Capmix technique for energy extraction is based on the cyclic expansion of electrical double layers to harvest dissipative energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the electrical potentials for the charging and discharging processes, which must be matched with the pore characteristics of the electrode materials. While a number of recent studies have examined the effects of the electrode pore size and geometry on the capacitive energy extraction processes, there is little knowledge on how the surface properties of the electrodes affect the thermodynamic efficiency. In this work, we investigate the Capmix processes using the classical density functional theory for a realistic model of electrolyte solutions. The theoretical predictions allow us to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different surface hydrophobicity. In agreement with recent experiments, we find that the thermodynamic efficiency can be much improved by using most hydrophilic electrodes.

On the hydrophilicity of electrodes for capacitive energy extraction

DOE PAGES

Lian, Cheng; East China Univ. of Science and Technology, Shanghai; Kong, Xian; ...

2016-09-14

The so-called Capmix technique for energy extraction is based on the cyclic expansion of electrical double layers to harvest dissipative energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the electrical potentials for the charging and discharging processes, which must be matched with the pore characteristics of the electrode materials. While a number of recent studies have examined the effects of the electrode pore size and geometry on the capacitive energy extraction processes, there is little knowledge on how the surface properties of the electrodes affect the thermodynamic efficiency. In thismore » paper, we investigate the Capmix processes using the classical density functional theory for a realistic model of electrolyte solutions. The theoretical predictions allow us to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different surface hydrophobicity. Finally, in agreement with recent experiments, we find that the thermodynamic efficiency can be much improved by using most hydrophilic electrodes.« less

Effects of an energy balance educational intervention and the COPE cognitive behavioral therapy intervention for Division I U.S. Air Force Academy female athletes.

PubMed

Buffington, Brenda C; Melnyk, Bernadette M; Morales, Shelly; Lords, Amanda; Zupan, Michael R

2016-04-01

Female athletes struggle harder than male athletes to lose body fat and maintain a leaner physique. The purpose of this study was to determine the effects of an educational and cognitive behavioral therapy (CBT)-based intervention on knowledge, body composition, anxiety, stress, and nutritional intake. A randomized controlled trial was conducted with 153 female athletes from the U.S. Air Force Academy (USAFA). Participants were assigned to one of three groups: (a) a combined energy balance and CBT-based intervention (E1); (b) a CBT-based intervention alone (E2); and (c) a control group (C). Main outcomes included a DXA scan for body composition, a knowledge test, the GAD-7 for anxiety, the brief inventory of perceived stress (BIPS) for stress, and a 24-h food recall. Significant improvement on knowledge of energy balance occurred in all three groups E1 (p < .001), E2, and C (p < .05). Significant reductions in percentage of body fat occurred in E1 (p < .001) and E2 (p < .05). There also were significant reductions in the percent of fat consumed by E1 (p < .05) and saturated fat consumed by both E1 and E2 (p < .05). The control group only demonstrated a significant increase in stress as measured by the BIPS (p < .05). A combined energy balance and CBT-based intervention improves knowledge and body fat. The importance to assess knowledge, anxiety, stress, nutrition intake, and percentage of body fat in female athletes and to deliver evidence-based interventions to improve their health outcomes. ©2016 American Association of Nurse Practitioners.

A Structural Model for a Self-Assembled Nanotube Provides Insight into Its Exciton Dynamics

PubMed Central

2016-01-01

The design and synthesis of functional self-assembled nanostructures is frequently an empirical process fraught with critical knowledge gaps about atomic-level structure in these noncovalent systems. Here, we report a structural model for a semiconductor nanotube formed via the self-assembly of naphthalenediimide-lysine (NDI-Lys) building blocks determined using experimental 13C–13C and 13C–15N distance restraints from solid-state nuclear magnetic resonance supplemented by electron microscopy and X-ray powder diffraction data. The structural model reveals a two-dimensional-crystal-like architecture of stacked monolayer rings each containing ∼50 NDI-Lys molecules, with significant π-stacking interactions occurring both within the confines of the ring and along the long axis of the tube. Excited-state delocalization and energy transfer are simulated for the nanotube based on time-dependent density functional theory and an incoherent hopping model. Remarkably, these calculations reveal efficient energy migration from the excitonic bright state, which is in agreement with the rapid energy transfer within NDI-Lys nanotubes observed previously using fluorescence spectroscopy. PMID:26120375

Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

NASA Technical Reports Server (NTRS)

Genuardi, Michael T.

1993-01-01

One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

Interoperability-oriented Integration of Failure Knowledge into Functional Knowledge and Knowledge Transformation based on Concepts Mapping

NASA Astrophysics Data System (ADS)

Koji, Yusuke; Kitamura, Yoshinobu; Kato, Yoshikiyo; Tsutsui, Yoshio; Mizoguchi, Riichiro

In conceptual design, it is important to develop functional structures which reflect the rich experience in the knowledge from previous design failures. Especially, if a designer learns possible abnormal behaviors from a previous design failure, he or she can add an additional function which prevents such abnormal behaviors and faults. To do this, it is a crucial issue to share such knowledge about possible faulty phenomena and how to cope with them. In fact, a part of such knowledge is described in FMEA (Failure Mode and Effect Analysis) sheets, function structure models for systematic design and fault trees for FTA (Fault Tree Analysis).

BCL::MP-Fold: membrane protein structure prediction guided by EPR restraints

PubMed Central

Fischer, Axel W.; Alexander, Nathan S.; Woetzel, Nils; Karakaş, Mert; Weiner, Brian E.; Meiler, Jens

2016-01-01

For many membrane proteins, the determination of their topology remains a challenge for methods like X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. Electron paramagnetic resonance (EPR) spectroscopy has evolved as an alternative technique to study structure and dynamics of membrane proteins. The present study demonstrates the feasibility of membrane protein topology determination using limited EPR distance and accessibility measurements. The BCL::MP-Fold algorithm assembles secondary structure elements (SSEs) in the membrane using a Monte Carlo Metropolis (MCM) approach. Sampled models are evaluated using knowledge-based potential functions and agreement with the EPR data and a knowledge-based energy function. Twenty-nine membrane proteins of up to 696 residues are used to test the algorithm. The protein-size-normalized root-mean-square-deviation (RMSD100) value of the most accurate model is better than 8 Å for twenty-seven, better than 6 Å for twenty-two, and better than 4 Å for fifteen out of twenty-nine proteins, demonstrating the algorithm’s ability to sample the native topology. The average enrichment could be improved from 1.3 to 2.5, showing the improved discrimination power by using EPR data. PMID:25820805

Predicting RNA 3D structure using a coarse-grain helix-centered model

PubMed Central

Kerpedjiev, Peter; Höner zu Siederdissen, Christian; Hofacker, Ivo L.

2015-01-01

A 3D model of RNA structure can provide information about its function and regulation that is not possible with just the sequence or secondary structure. Current models suffer from low accuracy and long running times and either neglect or presume knowledge of the long-range interactions which stabilize the tertiary structure. Our coarse-grained, helix-based, tertiary structure model operates with only a few degrees of freedom compared with all-atom models while preserving the ability to sample tertiary structures given a secondary structure. It strikes a balance between the precision of an all-atom tertiary structure model and the simplicity and effectiveness of a secondary structure representation. It provides a simplified tool for exploring global arrangements of helices and loops within RNA structures. We provide an example of a novel energy function relying only on the positions of stems and loops. We show that coupling our model to this energy function produces predictions as good as or better than the current state of the art tools. We propose that given the wide range of conformational space that needs to be explored, a coarse-grain approach can explore more conformations in less iterations than an all-atom model coupled to a fine-grain energy function. Finally, we emphasize the overarching theme of providing an ensemble of predicted structures, something which our tool excels at, rather than providing a handful of the lowest energy structures. PMID:25904133

An expert system prototype for aiding in the development of software functional requirements for NASA Goddard's command management system: A case study and lessons learned

NASA Technical Reports Server (NTRS)

Liebowitz, Jay

1986-01-01

At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.

Planning and Teaching Report-Writing. PEN.

ERIC Educational Resources Information Center

Hayes, Julie

Although an Australian educator had taught isolated aspects of functional grammar for a number of years, she felt that she had not put enough energy into building field (topic) knowledge. With the unit featured in this PEN Digest she aims to focus on building a quite extensive knowledge of the topic--snakes. According to the Digest, the educator…

A knowledge-based control system for air-scour optimisation in membrane bioreactors.

PubMed

Ferrero, G; Monclús, H; Sancho, L; Garrido, J M; Comas, J; Rodríguez-Roda, I

2011-01-01

Although membrane bioreactors (MBRs) technology is still a growing sector, its progressive implementation all over the world, together with great technical achievements, has allowed it to reach a mature degree, just comparable to other more conventional wastewater treatment technologies. With current energy requirements around 0.6-1.1 kWh/m3 of treated wastewater and investment costs similar to conventional treatment plants, main market niche for MBRs can be areas with very high restrictive discharge limits, where treatment plants have to be compact or where water reuse is necessary. Operational costs are higher than for conventional treatments; consequently there is still a need and possibilities for energy saving and optimisation. This paper presents the development of a knowledge-based decision support system (DSS) for the integrated operation and remote control of the biological and physical (filtration and backwashing or relaxation) processes in MBRs. The core of the DSS is a knowledge-based control module for air-scour consumption automation and energy consumption minimisation.

Clean energy storage technology in the making: An innovation systems perspective on flywheel energy storage.

PubMed

Wicki, Samuel; Hansen, Erik G

2017-09-20

The emergence and diffusion of green and sustainable technologies is full of obstacles and has therefore become an important area of research. We are interested in further understanding the dynamics between entrepreneurial experimentation, market formation, and institutional contexts, together playing a decisive role for successful diffusion of such technologies. Accordingly, we study these processes by adopting a technological innovation system perspective focusing on actors, networks, and institutions as well as the functions provided by them. Using a qualitative case study research design, we focus on the high-speed flywheel energy storage technology. As flywheels are based on a rotating mass allowing short-term storage of energy in kinetic form, they represent an environmentally-friendly alternative to electrochemical batteries and therefore can play an important role in sustainable energy transitions. Our contribution is threefold: First , regarding the flywheel energy storage technology, our findings reveal two subsystems and related markets in which development took different courses. In the automotive sector, flywheels are developing well as a braking energy recovery technology under the influence of two motors of innovation. In the electricity sector, they are stagnating at the stage of demonstration projects because of two important system weaknesses that counteract demand for storage. Second , we contribute to the theory of technological innovation systems by better understanding the internal dynamics between different functions of an innovation system as well as between the innovation system and its (external) contextual structures. Our third contribution is methodological. According to our best knowledge, we are the first to use system dynamics to (qualitatively) analyze and visualize dynamics between the diverse functions of innovation systems with the aim of enabling a better understanding of complex and iterative system processes. The paper also derives important implications for energy scholars, flywheel practitioners, and policymakers.

Water Resources and Sustainable Agriculture in 21st Century: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Asrar, G.

2008-05-01

Global agriculture faces some unique challenges and opportunities for the rest of this century. The need for food, feed and fiber will continues to grow as the world population continue to increase in the future. Agricultural ecosystems are also expected to be the source of a significant portion of renewable energy and fuels around the world, without further compromising the integrity of the natural resources base. How can agriculture continue to provide these services to meet the growing needs of world population while sustaining the integrity of agricultural ecosystems and natural resources, the very foundation it depends on? In the last century, scientific discoveries and technological innovations in agriculture resulted in significant increase in food, feed and fiber production globally, while the total amount of water, energy, fertilizers and other input used to achieve this growth remained the same or even decreased significantly in some parts of the world. Scientific and technical advances in understanding global and regional water and energy cycles, water resources management, soil and water conservation practices, weather prediction, plant breeding and biotechnology, and information and communication technologies contributed to this tremendous achievement. The projected increase in global population, urbanization, and changing lifestyles will continue the pressure on both agriculture and other managed and natural ecosystems to provide necessary goods and services for the rest of this century. To meet these challenges, we must obtain the requisite scientific and technical advances in the functioning of Earth's water, energy, carbon and biogeochemical cycles. We also need to apply the knowledge we gain and technologies we develop in assessing Earth's ecosystems' conditions, and their management and stewardship. In agricultural ecosystems, management of soil and water quality and quantity together with development of new varieties of plants based on advances in genomic, genetics, breeding and applied biotechnologies are a key to our ability to address these challenges. We must also continue to develop agronomic practices that sustain the integrity of natural resources and conserve energy on one-hand while maximizing agricultural production per unit area of land on the other hand. This will require managing agricultural ecosystems for their multiple functions and services together, instead of looking at each function/service in isolation. In this presentation, we will provide an overview of the scientific and technical knowledge required for sustainable management of agricultural ecosystems and associated natural resources. We will describe the soil, water and energy research needs/priorities in agriculture. We will also provide some examples of recent accomplishments and future directions in developing decision support tools for assessing the impacts of weather and climate variations and change, and their risk to agricultural ecosystems. We will then focus on opportunities and challenges associated with measurement, monitoring and modeling of soil moisture and its use in management and operation of agricultural ecosystems. The overall intent of this presentation is to stimulate some discussion on future directions and priorities for soil, water and energy research in agricultural ecosystems, and how the knowledge we gain from this research can be conveyed to the users for risk assessment, decision making, and multi-service ecosystem management purposes.

Empirical dual energy calibration (EDEC) for cone-beam computed tomography.

PubMed

Stenner, Philip; Berkus, Timo; Kachelriess, Marc

2007-09-01

Material-selective imaging using dual energy CT (DECT) relies heavily on well-calibrated material decomposition functions. These require the precise knowledge of the detected x-ray spectra, and even if they are exactly known the reliability of DECT will suffer from scattered radiation. We propose an empirical method to determine the proper decomposition function. In contrast to other decomposition algorithms our empirical dual energy calibration (EDEC) technique requires neither knowledge of the spectra nor of the attenuation coefficients. The desired material-selective raw data p1 and p2 are obtained as functions of the measured attenuation data q1 and q2 (one DECT scan = two raw data sets) by passing them through a polynomial function. The polynomial's coefficients are determined using a general least squares fit based on thresholded images of a calibration phantom. The calibration phantom's dimension should be of the same order of magnitude as the test object, but other than that no assumptions on its exact size or positioning are made. Once the decomposition coefficients are determined DECT raw data can be decomposed by simply passing them through the polynomial. To demonstrate EDEC simulations of an oval CTDI phantom, a lung phantom, a thorax phantom and a mouse phantom were carried out. The method was further verified by measuring a physical mouse phantom, a half-and-half-cylinder phantom and a Yin-Yang phantom with a dedicated in vivo dual source micro-CT scanner. The raw data were decomposed into their components, reconstructed, and the pixel values obtained were compared to the theoretical values. The determination of the calibration coefficients with EDEC is very robust and depends only slightly on the type of calibration phantom used. The images of the test phantoms (simulations and measurements) show a nearly perfect agreement with the theoretical micro values and density values. Since EDEC is an empirical technique it inherently compensates for scatter components. The empirical dual energy calibration technique is a pragmatic, simple, and reliable calibration approach that produces highly quantitative DECT images.

Assessing Learning Progression of Energy Concepts across Middle School Grades: The Knowledge Integration Perspective

ERIC Educational Resources Information Center

Lee, Hee-Sun; Liu, Ou Lydia

2010-01-01

We use a construct-based assessment approach to measure learning progression of energy concepts across physical, life, and earth science contexts in middle school grades. We model the knowledge integration construct in six levels in terms of the numbers of ideas and links used in student-generated explanations. For this study, we selected 10 items…

Prediction of digestibility and energy concentration of winter pasture forage and herbage of low-input grassland--a comparison of methods.

PubMed

Opitz v Boberfeld, W; Theobald, P C; Laser, H

2003-06-01

Regarding the estimation of the energy concentration or digestibility of herb-dominated forage and plant samples from winter pastures, it could be expected that the estimation is only reliable when in vitro methods with rumen fluid as inoculum (= gas production techniques) are used. For the verification of this thesis based on logical reflections, an in vitro-method with rumen fluid added as inoculum, as well as chemical, and enzymatic methods were applied under consideration of existing estimating functions. As a possible reason for the observed divergence of the methods, effects of fungal infections or, respectively, secondary compounds in herbs are discussed. At the present state of knowledge, it is adequate to estimate the energy concentration in vitro by gas tests, as far as fattening types like suckler cows and beef cattle are concerned, maybe in contrast to the forage evaluation for dairy cows.

A novel method for calculating the energy barriers for carbon diffusion in ferrite under heterogeneous stress

NASA Astrophysics Data System (ADS)

Tchitchekova, Deyana S.; Morthomas, Julien; Ribeiro, Fabienne; Ducher, Roland; Perez, Michel

2014-07-01

A novel method for accurate and efficient evaluation of the change in energy barriers for carbon diffusion in ferrite under heterogeneous stress is introduced. This method, called Linear Combination of Stress States, is based on the knowledge of the effects of simple stresses (uniaxial or shear) on these diffusion barriers. Then, it is assumed that the change in energy barriers under a complex stress can be expressed as a linear combination of these already known simple stress effects. The modifications of energy barriers by either uniaxial traction/compression and shear stress are determined by means of atomistic simulations with the Climbing Image-Nudge Elastic Band method and are stored as a set of functions. The results of this method are compared to the predictions of anisotropic elasticity theory. It is shown that, linear anisotropic elasticity fails to predict the correct energy barrier variation with stress (especially with shear stress) whereas the proposed method provides correct energy barrier variation for stresses up to ˜3 GPa. This study provides a basis for the development of multiscale models of diffusion under non-uniform stress.

A novel method for calculating the energy barriers for carbon diffusion in ferrite under heterogeneous stress.

PubMed

Tchitchekova, Deyana S; Morthomas, Julien; Ribeiro, Fabienne; Ducher, Roland; Perez, Michel

2014-07-21

A novel method for accurate and efficient evaluation of the change in energy barriers for carbon diffusion in ferrite under heterogeneous stress is introduced. This method, called Linear Combination of Stress States, is based on the knowledge of the effects of simple stresses (uniaxial or shear) on these diffusion barriers. Then, it is assumed that the change in energy barriers under a complex stress can be expressed as a linear combination of these already known simple stress effects. The modifications of energy barriers by either uniaxial traction/compression and shear stress are determined by means of atomistic simulations with the Climbing Image-Nudge Elastic Band method and are stored as a set of functions. The results of this method are compared to the predictions of anisotropic elasticity theory. It is shown that, linear anisotropic elasticity fails to predict the correct energy barrier variation with stress (especially with shear stress) whereas the proposed method provides correct energy barrier variation for stresses up to ∼3 GPa. This study provides a basis for the development of multiscale models of diffusion under non-uniform stress.

All-Atom Four-Body Knowledge-Based Statistical Potentials to Distinguish Native Protein Structures from Nonnative Folds

PubMed Central

2017-01-01

Recent advances in understanding protein folding have benefitted from coarse-grained representations of protein structures. Empirical energy functions derived from these techniques occasionally succeed in distinguishing native structures from their corresponding ensembles of nonnative folds or decoys which display varying degrees of structural dissimilarity to the native proteins. Here we utilized atomic coordinates of single protein chains, comprising a large diverse training set, to develop and evaluate twelve all-atom four-body statistical potentials obtained by exploring alternative values for a pair of inherent parameters. Delaunay tessellation was performed on the atomic coordinates of each protein to objectively identify all quadruplets of interacting atoms, and atomic potentials were generated via statistical analysis of the data and implementation of the inverted Boltzmann principle. Our potentials were evaluated using benchmarking datasets from Decoys-‘R'-Us, and comparisons were made with twelve other physics- and knowledge-based potentials. Ranking 3rd, our best potential tied CHARMM19 and surpassed AMBER force field potentials. We illustrate how a generalized version of our potential can be used to empirically calculate binding energies for target-ligand complexes, using HIV-1 protease-inhibitor complexes for a practical application. The combined results suggest an accurate and efficient atomic four-body statistical potential for protein structure prediction and assessment. PMID:29119109

Computational neuroanatomy: ontology-based representation of neural components and connectivity.

PubMed

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-02-05

A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

Editorial: Functional nanomaterials for energy applications

DOE PAGES

Devan, Rupesh S.; Ma, Yuan -Ron; Kim, Jin -Hyeok; ...

2015-02-16

In order to leap forward from the energy crisis issues and improve lifestyle, we all are looking positively toward nanomaterials or nanostructures. Thus, the exploration of new features of both typical and novel materials at the nanoscale level is playing important role in the development of innovative and improved energy technologies that have the capability of conserve/convert energy at large extend. By tailoring the surface morphology of materials in its nanoforms, the functional properties can be significantly adapted and specifically combined to produce highly potent multifunctional materials for conversion, storage, and consumption of energy in various forms. The papers selectedmore » for this special issue represent a good panel for addressing various energy applications including solar cell, fuel cells, nanofluid twisters, and gas sensors. Of course, the selected topic and the papers are not an exhaustive representation of the utilization of functional nanomaterials for energy applications. Nevertheless, they represent the rich and many-facet knowledge, which we have the pleasure of sharing with the readers.« less

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR.

PubMed

Westermaier, Yvonne; Ruiz-Carmona, Sergio; Theret, Isabelle; Perron-Sierra, Françoise; Poissonnet, Guillaume; Dacquet, Catherine; Boutin, Jean A; Ducrot, Pierre; Barril, Xavier

2017-08-01

The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

Approximate Degrees of Similarity between a User's Knowledge and the Tutorial Systems' Knowledge Base

ERIC Educational Resources Information Center

Mogharreban, Namdar

2004-01-01

A typical tutorial system functions by means of interaction between four components: the expert knowledge base component, the inference engine component, the learner's knowledge component and the user interface component. In typical tutorial systems the interaction and the sequence of presentation as well as the mode of evaluation are…

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

Rodríguez-González, R.; Martínez-Orozco, J. C.; Madrigal-Melchor, J.

In this work we use the standard T-matrix method to study the tunneling of Dirac electrons through graphene multilayers. A graphene sheet is deposited on top of slabs of Silicon-Oxide (SiO{sub 2}) and Silicon-Carbide (SiC) substrates, in which we applied the Cantor’s series. We calculate the transmittance as a function of energy for different incident angles and different generations of the Cantor’s series. Comparing the transmittance, we found three types of self-similarity: (a) local - into generations, (b) between incident angles and (c) between generations. We also compute the angular distribution of the transmittance for fixed energies finding a self-similarmore » pattern between generations. To our knowledge is the first time that four different self-similar patterns are presented in Cantor-based multilayers.« less

Light-Nuclei Spectra from Chiral Dynamics

NASA Astrophysics Data System (ADS)

Piarulli, M.; Baroni, A.; Girlanda, L.; Kievsky, A.; Lovato, A.; Lusk, Ewing; Marcucci, L. E.; Pieper, Steven C.; Schiavilla, R.; Viviani, M.; Wiringa, R. B.

2018-02-01

In recent years local chiral interactions have been derived and implemented in quantum Monte Carlo methods in order to test to what extent the chiral effective field theory framework impacts our knowledge of few- and many-body systems. In this Letter, we present Green's function Monte Carlo calculations of light nuclei based on the family of local two-body interactions presented by our group in a previous paper in conjunction with chiral three-body interactions fitted to bound- and scattering-state observables in the three-nucleon sector. These interactions include Δ intermediate states in their two-pion-exchange components. We obtain predictions for the energy levels and level ordering of nuclei in the mass range A =4 - 12 , accurate to ≤2 % of the binding energy, in very satisfactory agreement with experimental data.

Identified research directions for using manufacturing knowledge earlier in the product lifecycle

PubMed Central

Hedberg, Thomas D.; Hartman, Nathan W.; Rosche, Phil; Fischer, Kevin

2016-01-01

Design for Manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within Computer-Aided Design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customization on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities, or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is how can manufacturing knowledge, depending on its definition, be used earlier in the product lifecycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behavior, and context characteristics of product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product lifecycle. PMID:27990027

Identified research directions for using manufacturing knowledge earlier in the product lifecycle.

PubMed

Hedberg, Thomas D; Hartman, Nathan W; Rosche, Phil; Fischer, Kevin

2017-01-01

Design for Manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within Computer-Aided Design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customization on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities, or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is how can manufacturing knowledge, depending on its definition, be used earlier in the product lifecycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behavior, and context characteristics of product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product lifecycle.

Strategies for innovative energy-based nursing practice: the Healing Touch program.

PubMed

Kelley, Mari

2002-01-01

The purpose of this article is to share professional knowledge, practice, and educational opportunities related to energy-based nursing in order to broaden and improve the delivery of health care services. The holistic, theory-based approach places a patient's perceived needs first, and cares for the human body as well as the spirit. Energy medicine is an intricate part of the patient's expectation for health care. Watson's transpersonal-caring-healing model is explored (Watson, 1999). This model expands the view of the person to one that embodies energy that is comprised of spirit, a universal mind, and consciousness. The North American Nurses Diagnosis Association (NANDA) recognizes energy therapy as an intervention representing a specific theory: human energy field theory (HEFT). This therapy is related to the approved nursing diagnosis of energy field disturbance 1.8 (NANDA, 1995/1996). Healing touch (HT) is an energy-based therapeutic approach to healing that emphasizes caring for the whole person based on the HEFT. It is used in the nursing profession to influence changes in the human energy system; HT affects physical, emotional, mental, and spiritual health. The nursing process is evident throughout the curriculum. Nurse researchers report positive patients outcomes. The holistic nursing concept of energetic healing returns nurse professionals to the essence of nursing. Spinal cord injury (SCI) nurses will benefit by increasing their knowledge and awareness of energy therapy to increase patient satisfaction and improve outcomes for persons with SCI.

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

PubMed Central

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate. PMID:25793221

An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

PubMed

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

PubMed

Shim, Jihyun; Mackerell, Alexander D

2011-05-01

A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Distributions of experimental protein structures on coarse-grained free energy landscapes

PubMed Central

Liu, Jie; Jernigan, Robert L.

2015-01-01

Predicting conformational changes of proteins is needed in order to fully comprehend functional mechanisms. With the large number of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component analysis. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. In this work, we use principal component analysis of experimental structures of 50 diverse proteins to extract the most important directions of their motions, sample structures along these directions, and estimate their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca2+ adenosine triphosphatase (SERCA), as examples, we show that such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, we also show that Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes. PMID:26723638

A density functional theory based approach for predicting melting points of ionic liquids

DOE PAGES

Chen, Lihua; Bryantsev, Vyacheslav S.

2017-01-17

Accurate prediction of melting points of ILs is important both from the fundamental point of view and from the practical perspective for screening ILs with low melting points and broadening their utilization in a wider temperature range. In this work, we present an ab initio approach to calculating melting points of ILs with known crystal structures and illustrate its application for a series of 11 ILs containing imidazolium/pyrrolidinium cations and halide/polyatomic fluoro-containing anions. The melting point is determined as a temperature at which the Gibbs free energy of fusion is zero. The Gibbs free energy of fusion can be expressedmore » through the use of the Born-Fajans-Haber cycle via the lattice free energy of forming a solid IL from gaseous phase ions and the sum of the solvation free energies of ions comprising IL. Dispersion-corrected density functional theory (DFT) involving (semi)local (PBE-D3) and hybrid exchange-correlation (HSE06-D3) functionals is applied to estimate the lattice enthalpy, entropy, and free energy. The ions solvation free energies are calculated with the SMD-generic-IL solvation model at the M06-2X/6-31+G(d) level of theory under standard conditions. The melting points of ILs computed with the HSE06-D3 functional are in good agreement with the experimental data, with a mean absolute error of 30.5 K and a mean relative error of 8.5%. The model is capable of accurately reproducing the trends in melting points upon variation of alkyl substituents in organic cations and replacement one anion by another. The results verify that the lattice energies of ILs containing polyatomic fluoro-containing anions can be approximated reasonably well using the volume-based thermodynamic approach. However, there is no correlation of the computed lattice energies with molecular volume for ILs containing halide anions. Moreover, entropies of solid ILs follow two different linear relationships with molecular volume for halides and polyatomic fluoro-containing anions. As a result, continuous progress in predicting crystal structures of organic salts with halide anions will be a key factor for successful prediction of melting points with no prior knowledge of the crystal structure.« less

A density functional theory based approach for predicting melting points of ionic liquids

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

Chen, Lihua; Bryantsev, Vyacheslav S.

Accurate prediction of melting points of ILs is important both from the fundamental point of view and from the practical perspective for screening ILs with low melting points and broadening their utilization in a wider temperature range. In this work, we present an ab initio approach to calculating melting points of ILs with known crystal structures and illustrate its application for a series of 11 ILs containing imidazolium/pyrrolidinium cations and halide/polyatomic fluoro-containing anions. The melting point is determined as a temperature at which the Gibbs free energy of fusion is zero. The Gibbs free energy of fusion can be expressedmore » through the use of the Born-Fajans-Haber cycle via the lattice free energy of forming a solid IL from gaseous phase ions and the sum of the solvation free energies of ions comprising IL. Dispersion-corrected density functional theory (DFT) involving (semi)local (PBE-D3) and hybrid exchange-correlation (HSE06-D3) functionals is applied to estimate the lattice enthalpy, entropy, and free energy. The ions solvation free energies are calculated with the SMD-generic-IL solvation model at the M06-2X/6-31+G(d) level of theory under standard conditions. The melting points of ILs computed with the HSE06-D3 functional are in good agreement with the experimental data, with a mean absolute error of 30.5 K and a mean relative error of 8.5%. The model is capable of accurately reproducing the trends in melting points upon variation of alkyl substituents in organic cations and replacement one anion by another. The results verify that the lattice energies of ILs containing polyatomic fluoro-containing anions can be approximated reasonably well using the volume-based thermodynamic approach. However, there is no correlation of the computed lattice energies with molecular volume for ILs containing halide anions. Moreover, entropies of solid ILs follow two different linear relationships with molecular volume for halides and polyatomic fluoro-containing anions. As a result, continuous progress in predicting crystal structures of organic salts with halide anions will be a key factor for successful prediction of melting points with no prior knowledge of the crystal structure.« less

Energy balance in the core of the Saturn plasma sheet: H2O chemistry

NASA Astrophysics Data System (ADS)

Shemansky, D. E.; Yoshii, J.; Liu, X.

2011-10-01

A model of the weakly ionized plasma at Saturn has been developed to investigate the properties of the system. Energy balance is a critical consideration. The present model is based on two sources of mass, H2O, and HI. H2O is a variable. HI is a significant volume of gas flowing through the plasma imposed by the source at Saturn [1,2,3]. The energy sources are solar radiation and heterogeneous magnetosphere electrons. The model calculations produce energy rates, species partitioning, and relaxation lifetimes. For the first time the state of the ambient plasma sheet electrons is directly connected to the energy forcing functions. Within limits of knowledge, the predicted state of the core region of the plasma sheet in neutral and ionized gas corresponds satisfactorily to observation. The dominant ions in these calculations are H2O+ and H3O+ with lifetimes of several days. The lifetime of H2O is roughly 60 days. In calculations carried out so far the predicted source rate for H2O is lower than the rates quoted from the Enceladus encounters.

Integrating knowledge based functionality in commercial hospital information systems.

PubMed

Müller, M L; Ganslandt, T; Eich, H P; Lang, K; Ohmann, C; Prokosch, H U

2000-01-01

Successful integration of knowledge-based functions in the electronic patient record depends on direct and context-sensitive accessibility and availability to clinicians and must suit their workflow. In this paper we describe an exemplary integration of an existing standalone scoring system for acute abdominal pain into two different commercial hospital information systems using Java/Corba technolgy.

Dual-mode operation of 2D material-base hot electron transistors

PubMed Central

Lan, Yann-Wen; Torres, Jr., Carlos M.; Zhu, Xiaodan; Qasem, Hussam; Adleman, James R.; Lerner, Mitchell B.; Tsai, Shin-Hung; Shi, Yumeng; Li, Lain-Jong; Yeh, Wen-Kuan; Wang, Kang L.

2016-01-01

Vertical hot electron transistors incorporating atomically-thin 2D materials, such as graphene or MoS2, in the base region have been proposed and demonstrated in the development of electronic and optoelectronic applications. To the best of our knowledge, all previous 2D material-base hot electron transistors only considered applying a positive collector-base potential (VCB > 0) as is necessary for the typical unipolar hot-electron transistor behavior. Here we demonstrate a novel functionality, specifically a dual-mode operation, in our 2D material-base hot electron transistors (e.g. with either graphene or MoS2 in the base region) with the application of a negative collector-base potential (VCB < 0). That is, our 2D material-base hot electron transistors can operate in either a hot-electron or a reverse-current dominating mode depending upon the particular polarity of VCB. Furthermore, these devices operate at room temperature and their current gains can be dynamically tuned by varying VCB. We anticipate our multi-functional dual-mode transistors will pave the way towards the realization of novel flexible 2D material-based high-density and low-energy hot-carrier electronic applications. PMID:27581550

Dual-mode operation of 2D material-base hot electron transistors.

PubMed

Lan, Yann-Wen; Torres, Carlos M; Zhu, Xiaodan; Qasem, Hussam; Adleman, James R; Lerner, Mitchell B; Tsai, Shin-Hung; Shi, Yumeng; Li, Lain-Jong; Yeh, Wen-Kuan; Wang, Kang L

2016-09-01

Vertical hot electron transistors incorporating atomically-thin 2D materials, such as graphene or MoS2, in the base region have been proposed and demonstrated in the development of electronic and optoelectronic applications. To the best of our knowledge, all previous 2D material-base hot electron transistors only considered applying a positive collector-base potential (VCB > 0) as is necessary for the typical unipolar hot-electron transistor behavior. Here we demonstrate a novel functionality, specifically a dual-mode operation, in our 2D material-base hot electron transistors (e.g. with either graphene or MoS2 in the base region) with the application of a negative collector-base potential (VCB < 0). That is, our 2D material-base hot electron transistors can operate in either a hot-electron or a reverse-current dominating mode depending upon the particular polarity of VCB. Furthermore, these devices operate at room temperature and their current gains can be dynamically tuned by varying VCB. We anticipate our multi-functional dual-mode transistors will pave the way towards the realization of novel flexible 2D material-based high-density and low-energy hot-carrier electronic applications.

Structure-based multiscale approach for identification of interaction partners of PDZ domains.

PubMed

Tiwari, Garima; Mohanty, Debasisa

2014-04-28

PDZ domains are peptide recognition modules which mediate specific protein-protein interactions and are known to have a complex specificity landscape. We have developed a novel structure-based multiscale approach which identifies crucial specificity determining residues (SDRs) of PDZ domains from explicit solvent molecular dynamics (MD) simulations on PDZ-peptide complexes and uses these SDRs in combination with knowledge-based scoring functions for proteomewide identification of their interaction partners. Multiple explicit solvent simulations ranging from 5 to 50 ns duration have been carried out on 28 PDZ-peptide complexes with known binding affinities. MM/PBSA binding energy values calculated from these simulations show a correlation coefficient of 0.755 with the experimental binding affinities. On the basis of the SDRs of PDZ domains identified by MD simulations, we have developed a simple scoring scheme for evaluating binding energies for PDZ-peptide complexes using residue based statistical pair potentials. This multiscale approach has been benchmarked on a mouse PDZ proteome array data set by calculating the binding energies for 217 different substrate peptides in binding pockets of 64 different mouse PDZ domains. Receiver operating characteristic (ROC) curve analysis indicates that, the area under curve (AUC) values for binder vs nonbinder classification by our structure based method is 0.780. Our structure based method does not require experimental PDZ-peptide binding data for training.

Consequences of tropical land use for multitrophic biodiversity and ecosystem functioning.

PubMed

Barnes, Andrew D; Jochum, Malte; Mumme, Steffen; Haneda, Noor Farikhah; Farajallah, Achmad; Widarto, Tri Heru; Brose, Ulrich

2014-10-28

Our knowledge about land-use impacts on biodiversity and ecosystem functioning is mostly limited to single trophic levels, leaving us uncertain about whole-community biodiversity-ecosystem functioning relationships. We analyse consequences of the globally important land-use transformation from tropical forests to oil palm plantations. Species diversity, density and biomass of invertebrate communities suffer at least 45% decreases from rainforest to oil palm. Combining metabolic and food-web theory, we calculate annual energy fluxes to model impacts of land-use intensification on multitrophic ecosystem functioning. We demonstrate a 51% reduction in energy fluxes from forest to oil palm communities. Species loss clearly explains variation in energy fluxes; however, this relationship depends on land-use systems and functional feeding guilds, whereby predators are the most heavily affected. Biodiversity decline from forest to oil palm is thus accompanied by even stronger reductions in functionality, threatening to severely limit the functional resilience of communities to cope with future global changes.

Use of GIS-based Site-specific Nitrogen Management for Improving Energy Efficiency

USDA-ARS?s Scientific Manuscript database

To our knowledge, geographical information system (GIS)-based site-specific nitrogen management (SSNM) techniques have not been used to assess agricultural energy costs and efficiency. This chapter uses SSNM case studies for corn (Zea mays L.) grown in Missouri and cotton (Gossypium hirsutum L.) gro...

DataHub knowledge based assistance for science visualization and analysis using large distributed databases

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Collins, Donald J.; Doyle, Richard J.; Jacobson, Allan S.

1991-01-01

Viewgraphs on DataHub knowledge based assistance for science visualization and analysis using large distributed databases. Topics covered include: DataHub functional architecture; data representation; logical access methods; preliminary software architecture; LinkWinds; data knowledge issues; expert systems; and data management.

Computational neuroanatomy: ontology-based representation of neural components and connectivity

PubMed Central

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-01-01

Background A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future. PMID:19208191

Multiscale modeling for ferroelectric materials: identification of the phase-field model’s free energy for PZT from atomistic simulations

NASA Astrophysics Data System (ADS)

Völker, Benjamin; Landis, Chad M.; Kamlah, Marc

2012-03-01

Within a knowledge-based multiscale simulation approach for ferroelectric materials, the atomic level can be linked to the mesoscale by transferring results from first-principles calculations into a phase-field model. A recently presented routine (Völker et al 2011 Contin. Mech. Thermodyn. 23 435-51) for adjusting the Helmholtz free energy coefficients to intrinsic and extrinsic ferroelectric material properties obtained by DFT calculations and atomistic simulations was subject to certain limitations: caused by too small available degrees of freedom, an independent adjustment of the spontaneous strains and piezoelectric coefficients was not possible, and the elastic properties could only be considered in cubic instead of tetragonal symmetry. In this work we overcome such restrictions by expanding the formulation of the free energy function, i.e. by motivating and introducing new higher-order terms that have not appeared in the literature before. Subsequently we present an improved version of the adjustment procedure for the free energy coefficients that is solely based on input parameters from first-principles calculations performed by Marton and Elsässer, as documented in Völker et al (2011 Contin. Mech. Thermodyn. 23 435-51). Full sets of adjusted free energy coefficients for PbTiO3 and tetragonal Pb(Zr,Ti)O3 are presented, and the benefits of the newly introduced higher-order free energy terms are discussed.

Effects of Locus of Control on Behavioral Intention and Learning Performance of Energy Knowledge in Game-Based Learning

ERIC Educational Resources Information Center

Yang, Jie Chi; Lin, Yi Lung; Liu, Yi-Chun

2017-01-01

Game-based learning has been gradually adopted in energy education as an effective learning tool because digital games have the potential to increase energy literacy and encourage behavior change. However, not every learner can benefit from this support. There is a need to examine how human factors affect learners' reactions to digital games for…

RETScreen Plus Software Tutorial

NASA Technical Reports Server (NTRS)

Ganoe, Rene D.; Stackhouse, Paul W., Jr.; DeYoung, Russell J.

2014-01-01

Greater emphasis is being placed on reducing both the carbon footprint and energy cost of buildings. A building's energy usage depends upon many factors one of the most important is the local weather and climate conditions to which it's electrical, heating and air conditioning systems must respond. Incorporating renewable energy systems, including solar systems, to supplement energy supplies and increase energy efficiency is important to saving costs and reducing emissions. Also retrofitting technologies to buildings requires knowledge of building performance in its current state, potential future climate state, projection of potential savings with capital investment, and then monitoring the performance once the improvements are made. RETScreen Plus is a performance analysis software module that supplies the needed functions of monitoring current building performance, targeting projected energy efficiency improvements and verifying improvements once completed. This tutorial defines the functions of RETScreen Plus as well as outlines the general procedure for monitoring and reporting building energy performance.

Constructing Knowledge about the Trigonometric Functions and Their Geometric Meaning on the Unit Circle

ERIC Educational Resources Information Center

Altman, Renana; Kidron, Ivy

2016-01-01

Processes of knowledge construction are investigated. A learner is constructing knowledge about the trigonometric functions and their geometric meaning on the unit circle. The analysis is based on the dynamically nested epistemic action model for abstraction in context. Different tasks are offered to the learner. In his effort to perform the…

Measurements and usage of cross sections of various (n,xn) threshold reactions

NASA Astrophysics Data System (ADS)

Chudoba, P.; Vrzalová, J.; Svoboda, O.; Krása, A.; Kugler, A.; Majerle, M.; Suchopár, M.; Wagner, V.

2017-03-01

Current trend in nuclear reactor physics is a transition from technologies using thermal neutrons to technologies utilizing fast neutrons. Unfortunately focus was put mainly on the thermal neutrons for a long time and lead to very good knowledge about this low energy region, but very scarce coverage of the high energy region. This means that there is a gap in the knowledge of excitation functions for higher energies. This gap spreads from 20 MeV up to 1 GeV and higher. This is exactly the energy region needed for description of advanced nuclear systems such as accelerator driven systems (ADS). Our group from Nuclear Physics Institute (NPI) of the CAS is a member of an international collaboration Energy & Transmutation of Radioactive Waste (E&T RAW). This collaboration focuses on ADS for many years. In order to measure neutron field within ADS models it is necessary to know excitation functions of reactions used to monitor the neutron field. In many cases there are almost no experimental data for suitable reactions. Worse and quite common case is that there are no data at all. Therefore we are also focusing on measurements of these data in order to fill the databases as well as to allow further improvements of codes for nuclear data calculations.

Neuronal Lipid Metabolism: Multiple Pathways Driving Functional Outcomes in Health and Disease

PubMed Central

Tracey, Timothy J.; Steyn, Frederik J.; Wolvetang, Ernst J.; Ngo, Shyuan T.

2018-01-01

Lipids are a fundamental class of organic molecules implicated in a wide range of biological processes related to their structural diversity, and based on this can be broadly classified into five categories; fatty acids, triacylglycerols (TAGs), phospholipids, sterol lipids and sphingolipids. Different lipid classes play major roles in neuronal cell populations; they can be used as energy substrates, act as building blocks for cellular structural machinery, serve as bioactive molecules, or a combination of each. In amyotrophic lateral sclerosis (ALS), dysfunctions in lipid metabolism and function have been identified as potential drivers of pathogenesis. In particular, aberrant lipid metabolism is proposed to underlie denervation of neuromuscular junctions, mitochondrial dysfunction, excitotoxicity, impaired neuronal transport, cytoskeletal defects, inflammation and reduced neurotransmitter release. Here we review current knowledge of the roles of lipid metabolism and function in the CNS and discuss how modulating these pathways may offer novel therapeutic options for treating ALS. PMID:29410613

Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging Based on a Riemannian Manifold Approach.

PubMed

Baust, Maximilian; Weinmann, Andreas; Wieczorek, Matthias; Lasser, Tobias; Storath, Martin; Navab, Nassir

2016-08-01

In this paper, we consider combined TV denoising and diffusion tensor fitting in DTI using the affine-invariant Riemannian metric on the space of diffusion tensors. Instead of first fitting the diffusion tensors, and then denoising them, we define a suitable TV type energy functional which incorporates the measured DWIs (using an inverse problem setup) and which measures the nearness of neighboring tensors in the manifold. To approach this functional, we propose generalized forward- backward splitting algorithms which combine an explicit and several implicit steps performed on a decomposition of the functional. We validate the performance of the derived algorithms on synthetic and real DTI data. In particular, we work on real 3D data. To our knowledge, the present paper describes the first approach to TV regularization in a combined manifold and inverse problem setup.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865

ISPE: A knowledge-based system for fluidization studies

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

Reddy, S.

1991-01-01

Chemical engineers use mathematical simulators to design, model, optimize and refine various engineering plants/processes. This procedure requires the following steps: (1) preparation of an input data file according to the format required by the target simulator; (2) excecuting the simulation; and (3) analyzing the results of the simulation to determine if all specified goals'' are satisfied. If the goals are not met, the input data file must be modified and the simulation repeated. This multistep process is continued until satisfactory results are obtained. This research was undertaken to develop a knowledge based system, IPSE (Intelligent Process Simulation Environment), that canmore » enhance the productivity of chemical engineers/modelers by serving as an intelligent assistant to perform a variety tasks related to process simulation. ASPEN, a widely used simulator by the US Department of Energy (DOE) at Morgantown Energy Technology Center (METC) was selected as the target process simulator in the project. IPSE, written in the C language, was developed using a number of knowledge-based programming paradigms: object-oriented knowledge representation that uses inheritance and methods, rulebased inferencing (includes processing and propagation of probabilistic information) and data-driven programming using demons. It was implemented using the knowledge based environment LASER. The relationship of IPSE with the user, ASPEN, LASER and the C language is shown in Figure 1.« less

Incorporating Resilience into Dynamic Social Models

DTIC Science & Technology

2016-07-20

solved by simply using the information provided by the scenario. Instead, additional knowledge is required from relevant fields that study these...resilience function by leveraging Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network framework[5],[6]. BKBs allow for inferencing...reasoning network framework based on Bayesian Knowledge Bases (BKBs). BKBs are central to our social resilience framework as they are used to

Cellular energy metabolism in T-lymphocytes.

PubMed

Gaber, Timo; Strehl, Cindy; Sawitzki, Birgit; Hoff, Paula; Buttgereit, Frank

2015-01-01

Energy homeostasis is a hallmark of cell survival and maintenance of cell function. Here we focus on the impact of cellular energy metabolism on T-lymphocyte differentiation, activation, and function in health and disease. We describe the role of transcriptional and posttranscriptional regulation of lymphocyte metabolism on immune functions of T cells. We also summarize the current knowledge about T-lymphocyte adaptations to inflammation and hypoxia, and the impact on T-cell behavior of pathophysiological hypoxia (as found in tumor tissue, chronically inflamed joints in rheumatoid arthritis and during bone regeneration). A better understanding of the underlying mechanisms that control immune cell metabolism and immune response may provide therapeutic opportunities to alter the immune response under conditions of either immunosuppression or inflammation, potentially targeting infections, vaccine response, tumor surveillance, autoimmunity, and inflammatory disorders.

XML-Based SHINE Knowledge Base Interchange Language

NASA Technical Reports Server (NTRS)

James, Mark; Mackey, Ryan; Tikidjian, Raffi

2008-01-01

The SHINE Knowledge Base Interchange Language software has been designed to more efficiently send new knowledge bases to spacecraft that have been embedded with the Spacecraft Health Inference Engine (SHINE) tool. The intention of the behavioral model is to capture most of the information generally associated with a spacecraft functional model, while specifically addressing the needs of execution within SHINE and Livingstone. As such, it has some constructs that are based on one or the other.

Automation of energy demand forecasting

NASA Astrophysics Data System (ADS)

Siddique, Sanzad

Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

Promoting Students' Problem Solving Skills and Knowledge of STEM Concepts in a Data-Rich Learning Environment: Using Online Data as a Tool for Teaching about Renewable Energy Technologies

ERIC Educational Resources Information Center

Thurmond, Brandi

2011-01-01

This study sought to compare a data-rich learning (DRL) environment that utilized online data as a tool for teaching about renewable energy technologies (RET) to a lecture-based learning environment to determine the impact of the learning environment on students' knowledge of Science, Technology, Engineering, and Math (STEM) concepts related…

The priming of storage glucan synthesis from bacteria to plants: current knowledge and new developments.

PubMed

D'Hulst, Christophe; Mérida, Angel

2010-10-01

Starch is the main polymer in which carbon and energy are stored in land plants, algae and some cyanobacteria. It plays a crucial role in the physiology of these organisms and also represents an important polymer for humans, in terms of both diet and nonfood industry uses. Recent efforts have elucidated most of the steps involved in the synthesis of starch. However, the process that initiates the synthesis of the starch granule remains unclear. Here, we outline the similarities between the synthesis of starch and the synthesis of glycogen, the other widespread and abundant glucose-based polymer in living cells. We place special emphasis on the mechanisms of initiation of the glycogen granule and current knowledge concerning the initiation of the starch granule. We also discuss recent discoveries regarding the function of starch synthases in the priming of the starch granule and possible interactions with other elements of the starch synthesis machinery.

Combined use of computational chemistry and chemoinformatics methods for chemical discovery

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

Sugimoto, Manabu, E-mail: sugimoto@kumamoto-u.ac.jp; Institute for Molecular Science, 38 Nishigo-Naka, Myodaiji, Okazaki 444-8585; CREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012

2015-12-31

Data analysis on numerical data by the computational chemistry calculations is carried out to obtain knowledge information of molecules. A molecular database is developed to systematically store chemical, electronic-structure, and knowledge-based information. The database is used to find molecules related to a keyword of “cancer”. Then the electronic-structure calculations are performed to quantitatively evaluate quantum chemical similarity of the molecules. Among the 377 compounds registered in the database, 24 molecules are found to be “cancer”-related. This set of molecules includes both carcinogens and anticancer drugs. The quantum chemical similarity analysis, which is carried out by using numerical results of themore » density-functional theory calculations, shows that, when some energy spectra are referred to, carcinogens are reasonably distinguished from the anticancer drugs. Therefore these spectral properties are considered of as important measures for classification.« less

Overview of NRC Proactive Management of Materials Degradation (PMMD) Program

NASA Astrophysics Data System (ADS)

Carpenter, C. E. Gene; Hull, Amy; Oberson, Greg

Materials degradation phenomena, if not appropriately managed, have the potential to adversely impact the design functionality and safety margins of nuclear power plant (NPP) systems, structures and components (SSCs). Therefore, the U.S. Nuclear Regulatory Commission (NRC) has initiated an over-the-horizon multi-year research Proactive Management of Materials Degradation (PMMD) Research Program, which is presently evaluating longer time frames (i.e., 80 or more years) and including passive long-lived SSCs beyond the primary piping and core internals, such as concrete containment and cable insulation. This will allow the NRC to (1) identify significant knowledge gaps and new forms of degradation; (2) capture current knowledge base; and, (3) prioritize materials degradation research needs and directions for future efforts. This effort is being accomplished in collaboration with the U.S. Department of Energy's (DOE) LWR Sustainability (LWRS) program. This presentation will discuss the activities to date, including results, and the path forward.

Light-Nuclei Spectra from Chiral Dynamics

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

Piarulli, M.; Baroni, A.; Girlanda, L.

In recent years local chiral interactions have been derived and implemented in quantum Monte Carlo methods in order to test to what extent the chiral effective field theory framework impacts our knowledge of few- and many-body systems. Here in this Letter, we present Green’s function Monte Carlo calculations of light nuclei based on the family of local two-body interactions presented by our group in a previous paper in conjunction with chiral three-body interactions fitted to bound- and scattering-state observables in the three-nucleon sector. These interactions include Δ intermediate states in their two-pion-exchange components. We obtain predictions for the energy levelsmore » and level ordering of nuclei in the mass range A=4–12, accurate to ≤2% of the binding energy, in very satisfactory agreement with experimental data.« less

Light-Nuclei Spectra from Chiral Dynamics

DOE PAGES

Piarulli, M.; Baroni, A.; Girlanda, L.; ...

2018-02-01

In recent years local chiral interactions have been derived and implemented in quantum Monte Carlo methods in order to test to what extent the chiral effective field theory framework impacts our knowledge of few- and many-body systems. Here in this Letter, we present Green’s function Monte Carlo calculations of light nuclei based on the family of local two-body interactions presented by our group in a previous paper in conjunction with chiral three-body interactions fitted to bound- and scattering-state observables in the three-nucleon sector. These interactions include Δ intermediate states in their two-pion-exchange components. We obtain predictions for the energy levelsmore » and level ordering of nuclei in the mass range A=4–12, accurate to ≤2% of the binding energy, in very satisfactory agreement with experimental data.« less

Thermodynamics and the evolution of a city: a tale of how ...

EPA Pesticide Factsheets

Cities are complex organized systems, similar to biological and ecological systems in the way that they are structured and function. These systems are subject to the laws of thermodynamics and the principles of Energy Systems Theory (EST). Like other systems, cities experience larger scale drivers of change in resources. Unlike other ecosystems, cities react through socio-economic responses.Important contributions towards an integrated understanding of urban dynamics can be gained when their structures, functions and developments are interpreted within EST contexts.We have constructed a systems dynamics model that simulates some structural and functional aspects of Chicago in space and over time and we interpret model outcomes using EST. The purposes of the model are twofold, a knowledge base for integrating historical information, and for scenario modeling. Our history of Chicago starts in 1830 as a narrative, on the economic development and human population growth. Illustrated by a series of conceptual Energy Systems Models, it describes changes in trade, land tenure, and transportation as a result of increased access to nonlocal resources. Our simulation model, covers the post-World War II period to the present, and examines changes in population and its distribution on the landscape, material and energy flows, alterations of fresh water flows and management of wastewater. Scenario modeling is performed using a platform that estimates the potential impli

Theory of Covalent Adsorbate Frontier Orbital Energies on Functionalized Light-Absorbing Semiconductor Surfaces.

PubMed

Yu, Min; Doak, Peter; Tamblyn, Isaac; Neaton, Jeffrey B

2013-05-16

Functional hybrid interfaces between organic molecules and semiconductors are central to many emerging information and solar energy conversion technologies. Here we demonstrate a general, empirical parameter-free approach for computing and understanding frontier orbital energies - or redox levels - of a broad class of covalently bonded organic-semiconductor surfaces. We develop this framework in the context of specific density functional theory (DFT) and many-body perturbation theory calculations, within the GW approximation, of an exemplar interface, thiophene-functionalized silicon (111). Through detailed calculations taking into account structural and binding energetics of mixed-monolayers consisting of both covalently attached thiophene and hydrogen, chlorine, methyl, and other passivating groups, we quantify the impact of coverage, nonlocal polarization, and interface dipole effects on the alignment of the thiophene frontier orbital energies with the silicon band edges. For thiophene adsorbate frontier orbital energies, we observe significant corrections to standard DFT (∼1 eV), including large nonlocal electrostatic polarization effects (∼1.6 eV). Importantly, both results can be rationalized from knowledge of the electronic structure of the isolated thiophene molecule and silicon substrate systems. Silicon band edge energies are predicted to vary by more than 2.5 eV, while molecular orbital energies stay similar, with the different functional groups studied, suggesting the prospect of tuning energy alignment over a wide range for photoelectrochemistry and other applications.

Operationalizing Levels of Academic Mastery Based on Vygotsky's Theory: The Study of Mathematical Knowledge

ERIC Educational Resources Information Center

Nezhnov, Peter; Kardanova, Elena; Vasilyeva, Marina; Ludlow, Larry

2015-01-01

The present study tested the possibility of operationalizing levels of knowledge acquisition based on Vygotsky's theory of cognitive growth. An assessment tool (SAM-Math) was developed to capture a hypothesized hierarchical structure of mathematical knowledge consisting of procedural, conceptual, and functional levels. In Study 1, SAM-Math was…

Carbon-Based Functional Materials Derived from Waste for Water Remediation and Energy Storage.

PubMed

Ma, Qinglang; Yu, Yifu; Sindoro, Melinda; Fane, Anthony G; Wang, Rong; Zhang, Hua

2017-04-01

Carbon-based functional materials hold the key for solving global challenges in the areas of water scarcity and the energy crisis. Although carbon nanotubes (CNTs) and graphene have shown promising results in various fields of application, their high preparation cost and low production yield still dramatically hinder their wide practical applications. Therefore, there is an urgent call for preparing carbon-based functional materials from low-cost, abundant, and sustainable sources. Recent innovative strategies have been developed to convert various waste materials into valuable carbon-based functional materials. These waste-derived carbon-based functional materials have shown great potential in many applications, especially as sorbents for water remediation and electrodes for energy storage. Here, the research progress in the preparation of waste-derived carbon-based functional materials is summarized, along with their applications in water remediation and energy storage; challenges and future research directions in this emerging research field are also discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multimedia learning for increasing knowledge on energy efficiency and promotion of proenvironmental behavior: A study of undergraduate students in Costa Rica

NASA Astrophysics Data System (ADS)

Walsh-Zuniga, Yoselyn

Promotion of energy efficiency practices among household has been employed in many interventions with a varying degree of success, mainly on developed countries. The purpose of the study is to promote and measure knowledge of proenvironmental behavior in undergraduate students in the Costa Rica Institute of Technology. The intervention used for this purpose provided personal and altruistic information about the impact of energy consumption activities in household. People's perceptions and attitudes about behaviors that contribute and mitigate climate change were also investigated. Participants were students from undergraduate programs who are also inhabitants of the residence hall provided by the institution. The participation consisted in two surveys and a learning module. Students responded a survey before and after exposure to a learning module. Surveys focused on identifying knowledge, attitudes and intentions. The learning module provided information about three hypothetical scenarios and corresponding energy consumption estimates for each one. Participants did not significantly improve their knowledge on energy efficiency topics and did not change perceptions about the topic of climate change. Yet for both, knowledge and perceptions, participants demonstrated an average knowledge on topics associated to climate change. In addition, participants did not use technical information to explain concepts and perceptions. Another important finding was that participants wrote their responses more third-person than in first person singular or plural, meaning that, excluding themselves from the solution and the problem. Results suggest that there is an average knowledge among participants about 2.5 out of 5 points that represent a start point to design more successful interventions that promote energy efficiency behaviors. A major recommendation to improve energy efficiency behaviors is to place a greater emphasis and awareness in personal consequences of the misuse of energy in household as part of future interventions. More studies based on real consumption data along with more engaging visualizations are highly encouraged.

On the physical interpretation of the nuclear molecular orbital energy.

PubMed

Charry, Jorge; Pedraza-González, Laura; Reyes, Andrés

2017-06-07

Recently, several groups have extended and implemented molecular orbital (MO) schemes to simultaneously obtain wave functions for electrons and selected nuclei. Many of these schemes employ an extended Hartree-Fock approach as a first step to find approximate electron-nuclear wave functions and energies. Numerous studies conducted with these extended MO methodologies have explored various effects of quantum nuclei on physical and chemical properties. However, to the best of our knowledge no physical interpretation has been assigned to the nuclear molecular orbital energy (NMOE) resulting after solving extended Hartree-Fock equations. This study confirms that the NMOE is directly related to the molecular electrostatic potential at the position of the nucleus.

ISYMOD: a knowledge warehouse for the identification, assembly and analysis of bacterial integrated systems.

PubMed

Chabalier, Julie; Capponi, Cécile; Quentin, Yves; Fichant, Gwennaele

2005-04-01

Complex biological functions emerge from interactions between proteins in stable supra-molecular assemblies and/or through transitory contacts. Most of the time protein partners of the assemblies are composed of one or several domains which exhibit different biochemical functions. Thus the study of cellular process requires the identification of different functional units and their integration in an interaction network; such complexes are referred to as integrated systems. In order to exploit with optimum efficiency the increased release of data, automated bioinformatics strategies are needed to identify, reconstruct and model such systems. For that purpose, we have developed a knowledge warehouse dedicated to the representation and acquisition of bacterial integrated systems involved in the exchange of the bacterial cell with its environment. ISYMOD is a knowledge warehouse that consistently integrates in the same environment the data and the methods used for their acquisition. This is achieved through the construction of (1) a domain knowledge base (DKB) devoted to the storage of the knowledge about the systems, their functional specificities, their partners and how they are related and (2) a methodological knowledge base (MKB) which depicts the task layout used to identify and reconstruct functional integrated systems. Instantiation of the DKB is obtained by solving the tasks of the MKB, whereas some tasks need instances of the DKB to be solved. AROM, an object-based knowledge representation system, has been used to design the DKB, and its task manager, AROMTasks, for developing the MKB. In this study two integrated systems, ABC transporters and two component systems, both involved in adaptation processes of a bacterial cell to its biotope, have been used to evaluate the feasibility of the approach.

Summaries of FY 1996 geosciences research

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

NONE

1996-12-01

The Geosciences Research Program is directed by the Department of Energy`s (DOE`s) Office of Energy Research (OER) through its Office of Basic Energy Sciences (OBES). Activities in the Geosciences Research Program are directed toward building the long-term fundamental knowledge base necessary to provide for energy technologies of the future. Future energy technologies and their individual roles in satisfying the nations energy needs cannot be easily predicted. It is clear, however, that these future energy technologies will involve consumption of energy and mineral resources and generation of technological wastes. The earth is a source for energy and mineral resources and ismore » also the host for wastes generated by technological enterprise. Viable energy technologies for the future must contribute to a national energy enterprise that is efficient, economical, and environmentally sound. The Geosciences Research Program emphasizes research leading to fundamental knowledge of the processes that transport, modify, concentrate, and emplace (1) the energy and mineral resources of the earth and (2) the energy by-products of man.« less

Environmental knowledge and attitudes and behaviours towards energy consumption.

PubMed

Paço, Arminda; Lavrador, Tânia

2017-07-15

Numerous investigations have arisen in order to study and characterise environmentally friendly consumer profiles, with some authors applying the relationship between knowledge, attitudes and behaviour to this end. The present research approach, based upon the Theory of Reasoned Action (TRA), seeks to verify the existence of relationships between knowledge and attitudes and between knowledge and environmental behaviour. In this instance, data collection involved a questionnaire aimed at assessing the overall environmental knowledge of respondents as well as their attitudes and behaviours regarding energy issues (savings, consumption, interest, use). The results pointed to the lack of relationship between knowledge and attitudes, and between knowledge and behaviour whilst the relationship between attitudes and behaviour proved to be only weak. The results also found that males, older students and those studying Engineering and the Social and Human Sciences are those reporting higher levels of environmental knowledge. However, when it comes to attitudes and behaviours, females seem to display more awareness around these issues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Insight from first principles into the stability and magnetism of alkali-metal superoxide nanoclusters

NASA Astrophysics Data System (ADS)

Arcelus, Oier; Suaud, Nicolas; Katcho, Nebil A.; Carrasco, Javier

2017-05-01

Alkali-metal superoxides are gaining increasing interest as 2p magnetic materials for information and energy storage. Despite significant research efforts on bulk materials, gaps in our knowledge of the electronic and magnetic properties at the nanoscale still remain. Here, we focused on the role that structural details play in determining stability, electronic structure, and magnetic couplings of (MO2)n (M = Li, Na, and K, with n = 2-8) clusters. Using first-principles density functional theory based on the Perdew-Burke-Ernzerhof and Heyd-Scuseria-Ernzerhof functionals, we examined the effect of atomic structure on the relative stability of different polymorphs within each investigated cluster size. We found that small clusters prefer to form planar-ring structures, whereas non-planar geometries become more stable when increasing the cluster size. However, the crossover point depends on the nature of the alkali metal. Our analysis revealed that electrostatic interactions govern the highly ionic M-O2 bonding and ultimately control the relative stability between 2-D and 3-D geometries. In addition, we analyzed the weak magnetic couplings between superoxide molecules in (NaO2)4 clusters comparing model Hamiltonian methods based on Wannier function projections onto πg states with wave function-based multi-reference calculations.

Probabilistic models for neural populations that naturally capture global coupling and criticality

PubMed Central

2017-01-01

Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality. PMID:28926564

Dissipation of 'dark energy' by cortex in knowledge retrieval.

PubMed

Capolupo, Antonio; Freeman, Walter J; Vitiello, Giuseppe

2013-03-01

We have devised a thermodynamic model of cortical neurodynamics expressed at the classical level by neural networks and at the quantum level by dissipative quantum field theory. Our model is based on features in the spatial images of cortical activity newly revealed by high-density electrode arrays. We have incorporated the mechanism and necessity for so-called dark energy in knowledge retrieval. We have extended the model first using the Carnot cycle to define our measures for energy, entropy and temperature, and then using the Rankine cycle to incorporate criticality and phase transitions. We describe the dynamics of two interactive fields of neural activity that express knowledge, one at high and the other at low energy density, and the two operators that create and annihilate the fields. We postulate that the extremely high density of energy sequestered briefly in cortical activity patterns can account for the vividness, richness of associations, and emotional intensity of memories recalled by stimuli. Copyright © 2013 Elsevier B.V. All rights reserved.

Adoption of Library 2.0 Functionalities by Academic Libraries and Users: A Knowledge Management Perspective

ERIC Educational Resources Information Center

Kim, Yong-Mi; Abbas, June

2010-01-01

This study investigates the adoption of Library 2.0 functionalities by academic libraries and users through a knowledge management perspective. Based on randomly selected 230 academic library Web sites and 184 users, the authors found RSS and blogs are widely adopted by academic libraries while users widely utilized the bookmark function.…

Inelastic scattering of electrons at real metal surfaces

NASA Astrophysics Data System (ADS)

Ding, Z.-J.

1997-04-01

A theory is presented to calculate the electron inelastic scattering cross section for a moving electron near the surface region at an arbitrary takeoff angle. The theory is based on using a bulk plasmon-pole approximation to derive the numerically computable expression of the electron self-energy in the random-phase approximation for a surface system, through the use of experimental optical constants. It is shown that the wave-vector-dependent surface dielectric function satisfies the surface sum rules in this scheme. The theory provides a detailed knowledge of electron self-energy depending on the kinetic energy, distance from surface, and velocity vector of an electron moving in any metal of a known dielectric constant, accommodating the formulation to practical situation in surface electron spectroscopies. Numerical computations of the energy-loss cross section have been made for Si and Au. The contribution to the total differential scattering cross section from each component is analyzed. The depth dependence informs us in detail how the bulk excitation mode changes to a surface excitation mode with an electron approaching the surface from the interior of a medium.

Food and Sustainability Challenges Under Climate Changes.

PubMed

Moustafa, Khaled

2016-12-01

Plants are permanently impacted by their environments, and their abilities to tolerate multiple fluctuating environmental conditions vary as a function of several genetic and natural factors. Over the past decades, scientific innovations and applications of the knowledge derived from biotechnological investigations to agriculture caused a substantial increase of the yields of many crops. However, due to exacerbating effects of climate change and a growing human population, a crisis of malnutrition may arise in the upcoming decades in some places in the world. So, effective, ethical and managerial regulations and fair policies should be set up and applied at the local and global levels so that Earth may fairly provide the food and living accommodation needed by its inhabitants. To save some energy consumption, electric devices (for e.g., smartphones, laptops, street lights, traffic lights, etc.) should be manufactured to work with solar energy, whenever available, particularly in sunny countries where sun is available most of the time. Such characteristic will save energy and make solar energy-based smartphones and laptops less cumbersome in terms of chargers and plugging issues.

c-T phase diagram and Landau free energies of (AgAu)55 nanoalloy via neural-network molecular dynamic simulations.

PubMed

Chiriki, Siva; Jindal, Shweta; Bulusu, Satya S

2017-10-21

For understanding the structure, dynamics, and thermal stability of (AgAu) 55 nanoalloys, knowledge of the composition-temperature (c-T) phase diagram is essential due to the explicit dependence of properties on composition and temperature. Experimentally, generating the phase diagrams is very challenging, and therefore theoretical insight is necessary. We use an artificial neural network potential for (AgAu) 55 nanoalloys. Predicted global minimum structures for pure gold and gold rich compositions are lower in energy compared to previous reports by density functional theory. The present work based on c-T phase diagram, surface area, surface charge, probability of isomers, and Landau free energies supports the enhancement of catalytic property of Ag-Au nanoalloys by incorporation of Ag up to 24% by composition in Au nanoparticles as found experimentally. The phase diagram shows that there is a coexistence temperature range of 70 K for Ag 28 Au 27 compared to all other compositions. We propose the power spectrum coefficients derived from spherical harmonics as an order parameter to calculate Landau free energies.

SAAFEC: Predicting the Effect of Single Point Mutations on Protein Folding Free Energy Using a Knowledge-Modified MM/PBSA Approach.

PubMed

Getov, Ivan; Petukh, Marharyta; Alexov, Emil

2016-04-07

Folding free energy is an important biophysical characteristic of proteins that reflects the overall stability of the 3D structure of macromolecules. Changes in the amino acid sequence, naturally occurring or made in vitro, may affect the stability of the corresponding protein and thus could be associated with disease. Several approaches that predict the changes of the folding free energy caused by mutations have been proposed, but there is no method that is clearly superior to the others. The optimal goal is not only to accurately predict the folding free energy changes, but also to characterize the structural changes induced by mutations and the physical nature of the predicted folding free energy changes. Here we report a new method to predict the Single Amino Acid Folding free Energy Changes (SAAFEC) based on a knowledge-modified Molecular Mechanics Poisson-Boltzmann (MM/PBSA) approach. The method is comprised of two main components: a MM/PBSA component and a set of knowledge based terms delivered from a statistical study of the biophysical characteristics of proteins. The predictor utilizes a multiple linear regression model with weighted coefficients of various terms optimized against a set of experimental data. The aforementioned approach yields a correlation coefficient of 0.65 when benchmarked against 983 cases from 42 proteins in the ProTherm database. the webserver can be accessed via http://compbio.clemson.edu/SAAFEC/.

Promoting Students' Problem Solving Skills and Knowledge of STEM Concepts in a Data-Rich Learning Environment: Using Online Data as a Tool for Teaching about Renewable Energy Technologies

NASA Astrophysics Data System (ADS)

Thurmond, Brandi

This study sought to compare a data-rich learning (DRL) environment that utilized online data as a tool for teaching about renewable energy technologies (RET) to a lecture-based learning environment to determine the impact of the learning environment on students' knowledge of Science, Technology, Engineering, and Math (STEM) concepts related to renewable energy technologies and students' problem solving skills. Two purposefully selected Advanced Placement (AP) Environmental Science teachers were included in the study. Each teacher taught one class about RET in a lecture-based environment (control) and another class in a DRL environment (treatment), for a total of four classes of students (n=128). This study utilized a quasi-experimental, pretest/posttest, control-group design. The initial hypothesis that the treatment group would have a significant gain in knowledge of STEM concepts related to RET and be better able to solve problems when compared to the control group was not supported by the data. Although students in the DRL environment had a significant gain in knowledge after instruction, posttest score comparisons of the control and treatment groups revealed no significant differences between the groups. Further, no significant differences were noted in students' problem solving abilities as measured by scores on a problem-based activity and self-reported abilities on a reflective questionnaire. This suggests that the DRL environment is at least as effective as the lecture-based learning environment in teaching AP Environmental Science students about RET and fostering the development of problem solving skills. As this was a small scale study, further research is needed to provide information about effectiveness of DRL environments in promoting students' knowledge of STEM concepts and problem-solving skills.

Recovering the 3d Pose and Shape of Vehicles from Stereo Images

NASA Astrophysics Data System (ADS)

Coenen, M.; Rottensteiner, F.; Heipke, C.

2018-05-01

The precise reconstruction and pose estimation of vehicles plays an important role, e.g. for autonomous driving. We tackle this problem on the basis of street level stereo images obtained from a moving vehicle. Starting from initial vehicle detections, we use a deformable vehicle shape prior learned from CAD vehicle data to fully reconstruct the vehicles in 3D and to recover their 3D pose and shape. To fit a deformable vehicle model to each detection by inferring the optimal parameters for pose and shape, we define an energy function leveraging reconstructed 3D data, image information, the vehicle model and derived scene knowledge. To minimise the energy function, we apply a robust model fitting procedure based on iterative Monte Carlo model particle sampling. We evaluate our approach using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012). Our approach can deal with very coarse pose initialisations and we achieve encouraging results with up to 82 % correct pose estimations. Moreover, we are able to deliver very precise orientation estimation results with an average absolute error smaller than 4°.

Universal Features of Metastable State Energies in Cellular Matter

NASA Astrophysics Data System (ADS)

Kim, Sangwoo; Wang, Yiliang; Hilgenfeldt, Sascha

2018-06-01

Mechanical equilibrium states of cellular matter are overwhelmingly metastable and separated from each other by topology changes. Using theory and simulations, it is shown that for a wide class of energy functionals in 2D, including those describing tissue cell layers, local energy differences between neighboring metastable states as well as global energy differences between initial states and ground states are governed by simple, universal relations. Knowledge of instantaneous length of an edge undergoing a T 1 transition is sufficient to predict local energy changes, while the initial edge length distribution yields a successful prediction for the global energy difference. An analytical understanding of the model parameters is provided.

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053

The direct and inverse problems of an air-saturated porous cylinder submitted to acoustic radiation.

PubMed

Ogam, Erick; Depollier, Claude; Fellah, Z E A

2010-09-01

Gas-saturated porous skeleton materials such as geomaterials, polymeric and metallic foams, or biomaterials are fundamental in a diverse range of applications, from structural materials to energy technologies. Most polymeric foams are used for noise control applications and knowledge of the manner in which the energy of sound waves is dissipated with respect to the intrinsic acoustic properties is important for the design of sound packages. Foams are often employed in the audible, low frequency range where modeling and measurement techniques for the recovery of physical parameters responsible for energy loss are still few. Accurate acoustic methods of characterization of porous media are based on the measurement of the transmitted and/or reflected acoustic waves by platelike specimens at ultrasonic frequencies. In this study we develop an acoustic method for the recovery of the material parameters of a rigid-frame, air-saturated polymeric foam cylinder. A dispersion relation for sound wave propagation in the porous medium is derived from the propagation equations and a model solution is sought based on plane-wave decomposition using orthogonal cylindrical functions. The explicit analytical solution equation of the scattered field shows that it is also dependent on the intrinsic acoustic parameters of the porous cylinder, namely, porosity, tortuosity, and flow resistivity (permeability). The inverse problem of the recovery of the flow resistivity and porosity is solved by seeking the minima of the objective functions consisting of the sum of squared residuals of the differences between the experimental and theoretical scattered field data.

A Collaborative Knowledge Plane for Autonomic Networks

NASA Astrophysics Data System (ADS)

Mbaye, Maïssa; Krief, Francine

Autonomic networking aims to give network components self-managing capabilities. Several autonomic architectures have been proposed. Each of these architectures includes sort of a knowledge plane which is very important to mimic an autonomic behavior. Knowledge plane has a central role for self-functions by providing suitable knowledge to equipment and needs to learn new strategies for more accuracy.However, defining knowledge plane's architecture is still a challenge for researchers. Specially, defining the way cognitive supports interact each other in knowledge plane and implementing them. Decision making process depends on these interactions between reasoning and learning parts of knowledge plane. In this paper we propose a knowledge plane's architecture based on machine learning (inductive logic programming) paradigm and situated view to deal with distributed environment. This architecture is focused on two self-functions that include all other self-functions: self-adaptation and self-organization. Study cases are given and implemented.

Detector response function of an energy-resolved CdTe single photon counting detector.

PubMed

Liu, Xin; Lee, Hyoung Koo

2014-01-01

While spectral CT using single photon counting detector has shown a number of advantages in diagnostic imaging, knowledge of the detector response function of an energy-resolved detector is needed to correct the signal bias and reconstruct the image more accurately. The objective of this paper is to study the photo counting detector response function using laboratory sources, and investigate the signal bias correction method. Our approach is to model the detector response function over the entire diagnostic energy range (20 keV

GW-BSE approach on S1 vertical transition energy of large charge transfer compounds: A performance assessment.

PubMed

Ziaei, Vafa; Bredow, Thomas

2016-11-07

In this work, we apply many-body perturbation theory (MBPT) on large critical charge transfer (CT) complexes to assess its performance on the S 1 excitation energy. Since the S 1 energy of CT compounds is heavily dependent on the Hartree-Fock (HF) exchange fraction in the reference density functional, MBPT opens a new way for reliable prediction of CT S 1 energy without explicit knowledge of suitable amount of HF-exchange, in contrary to the time-dependent density functional theory (TD-DFT), where depending on various functionals, large errors can arise. Thus, simply by starting from a (semi-)local reference functional and performing update of Kohn-Sham (KS) energies in the Green's function G while keeping dynamical screened interaction (W(ω)) frozen to the mean-field level, we obtain impressingly highly accurate S 1 energy at slightly higher computational cost in comparison to TD-DFT. However, this energy-only updating mechanism in G fails to work if the initial guess contains a fraction or 100% HF-exchange, and hence considerably inaccurate S 1 energy is predicted. Furthermore, eigenvalue updating both in G and W(ω) overshoots the S 1 energy due to enhanced underscreening of W(ω), independent of the (hybrid-)DFT starting orbitals. A full energy-update on top of HF orbitals even further overestimates the S 1 energy. An additional update of KS wave functions within the Quasi-Particle Self-Consistent GW (QSGW) deteriorates results, in stark contrast to the good results obtained from QSGW for periodic systems. For the sake of transferability, we further present data of small critical non-charge transfer systems, confirming the outcomes of the CT-systems.

Functional Knowledge of Pre-Exposure Prophylaxis for HIV Prevention Among Participants in a Web-Based Survey of Sexually Active Gay, Bisexual, and Other Men Who Have Sex With Men: Cross-Sectional Study

PubMed Central

2018-01-01

Background Awareness of pre-exposure prophylaxis (PrEP) for HIV prevention is increasing, but little is known about the functional knowledge of PrEP and its impact on willingness to use PrEP. Objective The objective of this study was to assess the functional knowledge of PrEP among a sample of gay, bisexual, and other men who have sex with men (MSM) participating in a Web-based survey of sexually active MSM. Methods Men at least 18 years old, residing in the United States, and reporting sex with a man in the previous 6 months were recruited through social networking websites. PrEP functional knowledge included the following 4 questions (1) efficacy of consistent PrEP use, (2) inconsistent PrEP use and effectiveness, (3) PrEP and condom use, and (4) effectiveness at reducing sexually transmitted infections (STIs). Ordinal logistic regression was used to identify respondent characteristics associated with PrEP functional knowledge. In a subsample of participants responding to HIV prevention questions, we compared willingness to use PrEP by response to PrEP functional knowledge using logistic regression analysis adjusted for age, race and ethnicity, and education level. Results Among 573 respondents, PrEP knowledge was high regarding adherence (488/573, 85.2%), condom use (532/573, 92.8%), and STIs (480/573, 83.8%), but only 252/573 (44.0%) identified the correct efficacy. Lower functional PrEP knowledge was associated with minority race/ethnicity (P=.005), lower education (P=.01), and not having an HIV test in the past year (P=.02). Higher PrEP knowledge was associated with willingness to use PrEP (P=.009). Younger age was not associated with higher PrEP functional knowledge or willingness to use PrEP. Conclusions PrEP knowledge was generally high in our study, including condom use and consistent use but may be lacking in higher risk MSM. The majority of respondents did not correctly identify PrEP efficacy with consistent use, which could impact motivation to seek out PrEP for HIV prevention. Targeted messaging to increase PrEP knowledge may increase PrEP use. PMID:29362213

ISPE: A knowledge-based system for fluidization studies. 1990 Annual report

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

Reddy, S.

1991-01-01

Chemical engineers use mathematical simulators to design, model, optimize and refine various engineering plants/processes. This procedure requires the following steps: (1) preparation of an input data file according to the format required by the target simulator; (2) excecuting the simulation; and (3) analyzing the results of the simulation to determine if all ``specified goals`` are satisfied. If the goals are not met, the input data file must be modified and the simulation repeated. This multistep process is continued until satisfactory results are obtained. This research was undertaken to develop a knowledge based system, IPSE (Intelligent Process Simulation Environment), that canmore » enhance the productivity of chemical engineers/modelers by serving as an intelligent assistant to perform a variety tasks related to process simulation. ASPEN, a widely used simulator by the US Department of Energy (DOE) at Morgantown Energy Technology Center (METC) was selected as the target process simulator in the project. IPSE, written in the C language, was developed using a number of knowledge-based programming paradigms: object-oriented knowledge representation that uses inheritance and methods, rulebased inferencing (includes processing and propagation of probabilistic information) and data-driven programming using demons. It was implemented using the knowledge based environment LASER. The relationship of IPSE with the user, ASPEN, LASER and the C language is shown in Figure 1.« less

Teaching Energy Using an Integrated Science Approach

ERIC Educational Resources Information Center

Poggi, Valeria; Miceli, Cristina; Testa, Italo

2017-01-01

Despite its relevance to all scientific domains, the debate surrounding the teaching of energy is still open. The main point remains the problems students have in understanding some aspects of the energy concept and in applying their knowledge to the comprehension of natural phenomena. In this paper, we present a research-based interdisciplinary…

Doppler Broadening and its Contribution to Compton Energy-Absorption Cross Sections: An Analysis of the Compton Component in Terms of Mass-Energy Absorption Coefficient

NASA Astrophysics Data System (ADS)

Rao, D. V.; Takeda, T.; Itai, Y.; Akatsuka, T.; Cesareo, R.; Brunetti, A.; Gigante, G. E.

2002-09-01

Compton energy absorption cross sections are calculated using the formulas based on a relativistic impulse approximation to assess the contribution of Doppler broadening and to examine the Compton profile literature and explore what, if any, effect our knowledge of this line broadening has on the Compton component in terms of mass-energy absorption coefficient. Compton energy-absorption cross sections are evaluated for all elements, Z=1-100, and for photon energies 1 keV-100 MeV. Using these cross sections, the Compton component of the mass-energy absorption coefficient is derived in the energy region from 1 keV to 1 MeV for all the elements Z=1-100. The electron momentum prior to the scattering event should cause a Doppler broadening of the Compton line. The momentum resolution function is evaluated in terms of incident and scattered photon energy and scattering angle. The overall momentum resolution of each contribution is estimated for x-ray and γ-ray energies of experimental interest in the angular region 1°-180°. Also estimated is the Compton broadening using nonrelativistic formula in the angular region 1°-180°, for 17.44, 22.1, 58.83, and 60 keV photons for a few elements (H, C, N, O, P, S, K, and Ca) of biological importance.

Managing the data deluge: data-driven GO category assignment improves while complexity of functional annotation increases.

PubMed

Gobeill, Julien; Pasche, Emilie; Vishnyakova, Dina; Ruch, Patrick

2013-01-01

The available curated data lag behind current biological knowledge contained in the literature. Text mining can assist biologists and curators to locate and access this knowledge, for instance by characterizing the functional profile of publications. Gene Ontology (GO) category assignment in free text already supports various applications, such as powering ontology-based search engines, finding curation-relevant articles (triage) or helping the curator to identify and encode functions. Popular text mining tools for GO classification are based on so called thesaurus-based--or dictionary-based--approaches, which exploit similarities between the input text and GO terms themselves. But their effectiveness remains limited owing to the complex nature of GO terms, which rarely occur in text. In contrast, machine learning approaches exploit similarities between the input text and already curated instances contained in a knowledge base to infer a functional profile. GO Annotations (GOA) and MEDLINE make possible to exploit a growing amount of curated abstracts (97 000 in November 2012) for populating this knowledge base. Our study compares a state-of-the-art thesaurus-based system with a machine learning system (based on a k-Nearest Neighbours algorithm) for the task of proposing a functional profile for unseen MEDLINE abstracts, and shows how resources and performances have evolved. Systems are evaluated on their ability to propose for a given abstract the GO terms (2.8 on average) used for curation in GOA. We show that since 2006, although a massive effort was put into adding synonyms in GO (+300%), our thesaurus-based system effectiveness is rather constant, reaching from 0.28 to 0.31 for Recall at 20 (R20). In contrast, thanks to its knowledge base growth, our machine learning system has steadily improved, reaching from 0.38 in 2006 to 0.56 for R20 in 2012. Integrated in semi-automatic workflows or in fully automatic pipelines, such systems are more and more efficient to provide assistance to biologists. DATABASE URL: http://eagl.unige.ch/GOCat/

Knowledge service decision making in business incubators based on the supernetwork model

NASA Astrophysics Data System (ADS)

Zhao, Liming; Zhang, Haihong; Wu, Wenqing

2017-08-01

As valuable resources for incubating firms, knowledge resources have received gradually increasing attention from all types of business incubators, and business incubators use a variety of knowledge services to stimulate rapid growth in incubating firms. Based on previous research, we generalize the knowledge transfer and knowledge networking services of two main forms of knowledge services and further divide knowledge transfer services into knowledge depth services and knowledge breadth services. Then, we construct the business incubators' knowledge supernetwork model, describe the evolution mechanism among heterogeneous agents and utilize a simulation to explore the performance variance of different business incubators' knowledge services. The simulation results show that knowledge stock increases faster when business incubators are able to provide knowledge services to more incubating firms and that the degree of discrepancy in the knowledge stock increases during the process of knowledge growth. Further, knowledge transfer services lead to greater differences in the knowledge structure, while knowledge networking services lead to smaller differences. Regarding the two types of knowledge transfer services, knowledge depth services are more conducive to knowledge growth than knowledge breadth services, but knowledge depth services lead to greater gaps in knowledge stocks and greater differences in knowledge structures. Overall, it is optimal for business incubators to select a single knowledge service or portfolio strategy based on the amount of time and energy expended on the two types of knowledge services.

Integrative pathway knowledge bases as a tool for systems molecular medicine.

PubMed

Liang, Mingyu

2007-08-20

There exists a sense of urgency to begin to generate a cohesive assembly of biomedical knowledge as the pace of knowledge accumulation accelerates. The urgency is in part driven by the emergence of systems molecular medicine that emphasizes the combination of systems analysis and molecular dissection in the future of medical practice and research. A potentially powerful approach is to build integrative pathway knowledge bases that link organ systems function with molecules.

Rule-based simulation models

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Seraphine, Kathleen M.

1991-01-01

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

Computational functional genomics-based approaches in analgesic drug discovery and repurposing.

PubMed

Lippmann, Catharina; Kringel, Dario; Ultsch, Alfred; Lötsch, Jörn

2018-06-01

Persistent pain is a major healthcare problem affecting a fifth of adults worldwide with still limited treatment options. The search for new analgesics increasingly includes the novel research area of functional genomics, which combines data derived from various processes related to DNA sequence, gene expression or protein function and uses advanced methods of data mining and knowledge discovery with the goal of understanding the relationship between the genome and the phenotype. Its use in drug discovery and repurposing for analgesic indications has so far been performed using knowledge discovery in gene function and drug target-related databases; next-generation sequencing; and functional proteomics-based approaches. Here, we discuss recent efforts in functional genomics-based approaches to analgesic drug discovery and repurposing and highlight the potential of computational functional genomics in this field including a demonstration of the workflow using a novel R library 'dbtORA'.

The cross-tissue metabolic response of abalone (Haliotis midae) to functional hypoxia.

PubMed

Venter, Leonie; Loots, Du Toit; Mienie, Lodewyk J; Jansen van Rensburg, Peet J; Mason, Shayne; Vosloo, Andre; Lindeque, Jeremie Z

2018-03-23

Functional hypoxia is a stress condition caused by the abalone itself as a result of increased muscle activity, which generally necessitates the employment of anaerobic metabolism if the activity is sustained for prolonged periods. With that being said, abalone are highly reliant on anaerobic metabolism to provide partial compensation for energy production during oxygen-deprived episodes. However, current knowledge on the holistic metabolic response for energy metabolism during functional hypoxia, and the contribution of different metabolic pathways and various abalone tissues towards the overall accumulation of anaerobic end-products in abalone are scarce. Metabolomics analysis of adductor muscle, foot muscle, left gill, right gill, haemolymph and epipodial tissue samples indicated that South African abalone ( Haliotis midae) subjected to functional hypoxia utilises predominantly anaerobic metabolism, and depends on all of the main metabolite classes (proteins, carbohydrates and lipids) for energy supply. Functional hypoxia caused increased levels of anaerobic end-products: lactate, alanopine, tauropine, succinate and alanine. Also, elevation in arginine levels was detected, confirming that abalone use phosphoarginine to generate energy during functional hypoxia. Different tissues showed varied metabolic responses to hypoxia, with functional hypoxia showing excessive changes in the adductor muscle and gills. From this metabolomics investigation, it becomes evident that abalone are metabolically able to produce sufficient amounts of energy when functional hypoxia is experienced. Also, tissue interplay enables the adjustment of H. midae energy requirements as their metabolism shifts from aerobic to anaerobic respiration during functional hypoxia.This article has an associated First Person interview with the first author of the paper. © 2018. Published by The Company of Biologists Ltd.

The cross-tissue metabolic response of abalone (Haliotis midae) to functional hypoxia

PubMed Central

Venter, Leonie; Loots, Du Toit; Mienie, Lodewyk J.; Jansen van Rensburg, Peet J.; Mason, Shayne; Vosloo, Andre

2018-01-01

ABSTRACT Functional hypoxia is a stress condition caused by the abalone itself as a result of increased muscle activity, which generally necessitates the employment of anaerobic metabolism if the activity is sustained for prolonged periods. With that being said, abalone are highly reliant on anaerobic metabolism to provide partial compensation for energy production during oxygen-deprived episodes. However, current knowledge on the holistic metabolic response for energy metabolism during functional hypoxia, and the contribution of different metabolic pathways and various abalone tissues towards the overall accumulation of anaerobic end-products in abalone are scarce. Metabolomics analysis of adductor muscle, foot muscle, left gill, right gill, haemolymph and epipodial tissue samples indicated that South African abalone (Haliotis midae) subjected to functional hypoxia utilises predominantly anaerobic metabolism, and depends on all of the main metabolite classes (proteins, carbohydrates and lipids) for energy supply. Functional hypoxia caused increased levels of anaerobic end-products: lactate, alanopine, tauropine, succinate and alanine. Also, elevation in arginine levels was detected, confirming that abalone use phosphoarginine to generate energy during functional hypoxia. Different tissues showed varied metabolic responses to hypoxia, with functional hypoxia showing excessive changes in the adductor muscle and gills. From this metabolomics investigation, it becomes evident that abalone are metabolically able to produce sufficient amounts of energy when functional hypoxia is experienced. Also, tissue interplay enables the adjustment of H. midae energy requirements as their metabolism shifts from aerobic to anaerobic respiration during functional hypoxia. This article has an associated First Person interview with the first author of the paper. PMID:29572259

High performance transcription factor-DNA docking with GPU computing

PubMed Central

2012-01-01

Background Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. Methods In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems. Results The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design. Conclusions We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem. PMID:22759575

Rational design of competitive electrocatalysts for the oxygen reduction reaction in hydrogen fuel cells

NASA Astrophysics Data System (ADS)

Stolbov, Sergey; Alcántara Ortigoza, Marisol

2012-02-01

The large-scale application of one of the most promising clean and renewable sources of energy, hydrogen fuel cells, still awaits efficient and cost-effective electrocatalysts for the oxygen reduction reaction (ORR) occurring on the cathode. We demonstrate that truly rational design renders electrocatalysts possessing both qualities. By unifying the knowledge on surface morphology, composition, electronic structure and reactivity, we solve that sandwich-like structures are an excellent choice for optimization. Their constituting species couple synergistically yielding reaction-environment stability, cost-effectiveness and tunable reactivity. This cooperative-action concept enabled us to predict two advantageous ORR electrocatalysts. Density functional theory calculations of the reaction free-energy diagrams confirm that these materials are more active toward ORR than the so far best Pt-based catalysts. Our designing concept advances also a general approach for engineering materials in heterogeneous catalysis.

Biology and pathological implications of brown adipose tissue: promises and caveats for the control of obesity and its associated complications.

PubMed

Tapia, Pablo; Fernández-Galilea, Marta; Robledo, Fermín; Mardones, Pablo; Galgani, José E; Cortés, Víctor A

2018-05-01

The discovery of metabolically active brown adipose tissue (BAT) in adult humans has fuelled the research of diverse aspects of this previously neglected tissue. BAT is solely present in mammals and its clearest physiological role is non-shivering thermogenesis, owing to the capacity of brown adipocytes to dissipate metabolic energy as heat. Recently, a number of other possible functions have been proposed, including direct regulation of glucose and lipid homeostasis and the secretion of a number of factors with diverse regulatory actions. Herein, we review recent advances in general biological knowledge of BAT and discuss the possible implications of this tissue in human metabolic health. In particular, we confront the claimed thermogenic potential of BAT for human energy balance and body mass regulation, mostly based on animal studies, with the most recent quantifications of human BAT. © 2017 Cambridge Philosophical Society.

Equilibrium geometries, electronic and magnetic properties of small AunNi- (n = 1-9) clusters

NASA Astrophysics Data System (ADS)

Tang, Cui-Ming; Chen, Xiao-Xu; Yang, Xiang-Dong

2014-05-01

Geometrical, electronic and magnetic properties of small AunNi- (n = 1-9) clusters have been investigated based on density functional theory (DFT) at PW91P86 level. An extensive structural search shows that the relative stable structures of AunNi- (n = 1-9) clusters adopt 2D structure for n = 1-5, 7 and 3D structure for n = 6, 8-9. And the substitution of a Ni atom for an Au atom in the Au-n+1 cluster obviously changes the structure of the host cluster. Moreover, an odd-even alternation phenomenon has been found for HOMO-LUMO energy gaps, indicating that the relative stable structures of the AunNi- clusters with odd-numbered gold atoms have a higher relative stability. Finally, the natural population analysis (NPA) and the vertical detachment energies (VDE) are studied, respectively. The theoretical values of VDE are reported for the first time to our best knowledge.

Application of Knowledge-Based Techniques to Tracking Function

DTIC Science & Technology

2006-09-01

38394041 42434445 46474849 505152 53545556 57585960 616263 646566 676869 707172 737475 7677 7879 8081 8283 8485 8687 8889 9091 9293 9495 969798 99100...Knowledge-based applications to adaptive space-time processing. Volume I: Summary”, AFRL-SN-TR-2001-146 Vol. I (of Vol. VI ), Final Technical Report, July...2001-146 Vol. IV (of Vol. VI ), Final Technical Report, July 2001. [53] C. Morgan, L. Moyer, “Knowledge-based applications to adaptive space-time

Learning to teach upper primary school algebra: changes to teachers' mathematical knowledge for teaching functional thinking

NASA Astrophysics Data System (ADS)

Wilkie, Karina J.

2016-06-01

A key aspect of learning algebra in the middle years of schooling is exploring the functional relationship between two variables: noticing and generalising the relationship, and expressing it mathematically. This article describes research on the professional learning of upper primary school teachers for developing their students' functional thinking through pattern generalisation. This aspect of algebra learning has been explicitly brought to the attention of upper primary teachers in the recently introduced Australian curriculum. Ten practising teachers participated over 1 year in a design-based research project involving a sequence of geometric pattern generalisation lessons with their classes. Initial and final survey responses and teachers' interactions in regular meetings and lessons were analysed from cognitive and situated perspectives on professional learning, using a theoretical model for the different types of knowledge needed for teaching mathematics. The teachers demonstrated an increase in certain aspects of their mathematical knowledge for teaching algebra as well as some residual issues. Implications for the professional learning of practising and pre-service teachers to develop their mathematics knowledge for teaching functional thinking, and challenges with operationalising knowledge categories for field-based research are presented.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

PubMed Central

Frimurer, Thomas M.; Meiler, Jens

2013-01-01

The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 103 fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes. PMID:23844000

High Penetration of Renewable Energy in the Transportation Sector: Scenarios, Barriers, and Enablers; Preprint

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

Vimmerstedt, L.; Brown, A.; Heath, G.

2012-06-01

Transportation accounts for 71% of U.S. petroleum use and 33% of its greenhouse gases emissions. Pathways toward reduced greenhouse gas emissions and petroleum dependence in the transportation sector have been analyzed in considerable detail, but with some limitations. To add to this knowledge, the U.S. Department of Energy has launched a study focused on underexplored greenhouse-gas-abatement and oil-savings opportunities related to transportation. This Transportation Energy Futures study analyzes specific issues and associated key questions to strengthen the existing knowledge base and help cultivate partnerships among federal agencies, state and local governments, and industry.

Recent developments in the layer-by-layer assembly of polyaniline and carbon nanomaterials for energy storage and sensing applications. From synthetic aspects to structural and functional characterization

NASA Astrophysics Data System (ADS)

Marmisollé, Waldemar A.; Azzaroni, Omar

2016-05-01

The construction of hybrid polymer-inorganic nanoarchitectures for electrochemical purposes based on the layer-by-layer assembly of conducting polymers and carbon nanomaterials has become increasingly popular over the last decade. This explosion of interest is primarily related to the increasing mastery in the design of supramolecular constructs using simple wet chemical approaches. Concomitantly, this continuous research activity paved the way to the rapid development of nanocomposites or ``nanoblends'' readily integrable into energy storage and sensing devices. In this sense, the layer-by-layer (LbL) assembly technique has allowed us to access three-dimensional (3D) multicomponent carbon-based network nanoarchitectures displaying addressable electrical, electrochemical and transport properties in which conducting polymers, such as polyaniline, and carbon nanomaterials, such as carbon nanotubes or nanographene, play unique roles without disrupting their inherent functions - complementary entities coexisting in harmony. Over the last few years the level of functional sophistication reached by LbL-assembled carbon-based 3D network nanoarchitectures, and the level of knowledge related to how to design, fabricate and optimize the properties of these 3D nanoconstructs have advanced enormously. This feature article presents and discusses not only the recent advances but also the emerging challenges in complex hybrid nanoarchitectures that result from the layer-by-layer assembly of polyaniline, a quintessential conducting polymer, and diverse carbon nanomaterials. This is a rapidly developing research area, and this work attempts to provide an overview of the diverse 3D network nanoarchitectures prepared up to now. The importance of materials processing and LbL integration is explored within each section and while the overall emphasis is on energy storage and sensing applications, the most widely-used synthetic strategies and characterization methods for ``nanoblend'' formation and performance evaluation are also presented.

A data management life-cycle

USGS Publications Warehouse

Ferderer, David A.

2001-01-01

Documented, reliable, and accessible data and information are essential building blocks supporting scientific research and applications that enhance society's knowledge base (fig. 1). The U.S. Geological Survey (USGS), a leading provider of science data, information, and knowledge, is uniquely positioned to integrate science and natural resource information to address societal needs. The USGS Central Energy Resources Team (USGS-CERT) provides critical information and knowledge on the quantity, quality, and distribution of the Nation's and the world's oil, gas, and coal resources. By using a life-cycle model, the USGS-CERT Data Management Project is developing an integrated data management system to (1) promote access to energy data and information, (2) increase data documentation, and (3) streamline product delivery to the public, scientists, and decision makers. The project incorporates web-based technology, data cataloging systems, data processing routines, and metadata documentation tools to improve data access, enhance data consistency, and increase office efficiency

Students' Socioscientific Reasoning and Decision-making on Energy-related Issues—Development of a measurement instrument

NASA Astrophysics Data System (ADS)

Sakschewski, Mark; Eggert, Sabina; Schneider, Susanne; Bögeholz, Susanne

2014-09-01

The concept of energy is one key component of science education curricula worldwide. While it is still being taught in many science classrooms from a mainly conceptual knowledge perspective, the need to frame the concept of energy as a socioscientific issue and implement it in the context of citizenship education and education for sustainable development, is getting more and more explicit. As we will be faced with limited fossil fuels and the consequences of global climate change in the future, students have to be supported in becoming literate citizens who are able to reach informed energy-related decisions. In this article, we focus on students' reasoning and decision-making processes about socioscientific energy-related issues. In more detail, we developed a paper-and-pencil measurement instrument to assess secondary school students' competencies in this domain. The functioning of the measurement instrument was analysed with a sample of 850 students from grades 6, 8, 10 and 12 using item response theory. Findings show that the measurement instrument functions in terms of reliability and validity. Concerning student ability, elaborate reasoning and decision-making was characterised by the use of trade-offs and the ability to weigh arguments and to reflect on the structure of reasoning and decision-making processes. The developed measurement instrument provides a complement for existing test instruments on conceptual knowledge about the concept of energy. It aims to contribute to a change in teaching about energy, especially in physics education in the sense of education for sustainable development.

Empirical projection-based basis-component decomposition method

NASA Astrophysics Data System (ADS)

Brendel, Bernhard; Roessl, Ewald; Schlomka, Jens-Peter; Proksa, Roland

2009-02-01

Advances in the development of semiconductor based, photon-counting x-ray detectors stimulate research in the domain of energy-resolving pre-clinical and clinical computed tomography (CT). For counting detectors acquiring x-ray attenuation in at least three different energy windows, an extended basis component decomposition can be performed in which in addition to the conventional approach of Alvarez and Macovski a third basis component is introduced, e.g., a gadolinium based CT contrast material. After the decomposition of the measured projection data into the basis component projections, conventional filtered-backprojection reconstruction is performed to obtain the basis-component images. In recent work, this basis component decomposition was obtained by maximizing the likelihood-function of the measurements. This procedure is time consuming and often unstable for excessively noisy data or low intrinsic energy resolution of the detector. Therefore, alternative procedures are of interest. Here, we introduce a generalization of the idea of empirical dual-energy processing published by Stenner et al. to multi-energy, photon-counting CT raw data. Instead of working in the image-domain, we use prior spectral knowledge about the acquisition system (tube spectra, bin sensitivities) to parameterize the line-integrals of the basis component decomposition directly in the projection domain. We compare this empirical approach with the maximum-likelihood (ML) approach considering image noise and image bias (artifacts) and see that only moderate noise increase is to be expected for small bias in the empirical approach. Given the drastic reduction of pre-processing time, the empirical approach is considered a viable alternative to the ML approach.

The Design and Evaluation of a Front-End User Interface for Energy Researchers.

ERIC Educational Resources Information Center

Borgman, Christine L.; And Others

1989-01-01

Reports on the Online Access to Knowledge (OAK) Project, which developed software to support end user access to a Department of Energy database based on the skill levels and needs of energy researchers. The discussion covers issues in development, evaluation, and the study of user behavior in designing an interface tailored to a special…

Significance of a Recurring Function in Energy Transfer

NASA Astrophysics Data System (ADS)

Mishra, Subodha

2017-05-01

The appearance of a unique function in the energy transfer from one system to the other in different physical situations such as electrical, mechanical, optical, and quantum mechanical processes is established in this work. Though the laws governing the energy transformation and its transfer from system to system are well known, here we notice a unity in diversity; a unique function appears in various cases of energy transfer whether it is a classical or a quantum mechanical process. We consider four examples, well known in elementary physics, from the fields of electricity, mechanics, optics, and quantum mechanics. We find that this unique function is in fact the transfer function corresponding to all these physical situations, and the interesting and intriguing finding is that the inverse Laplace transform of this transfer function, which is the impulse-response function of the systems when multiplied by a factor of -½, is the solution of a linear differential equation for an "instantly forced critically damped harmonic oscillator." It is important to note that though the physical phenomena considered are quite distinct, the underlying process in the language of impulse-response of the system in the time domain is a unique one. To the best of our knowledge we have not seen anywhere the above analysis of determining the unique function or its description as a transfer function in literature.

Free-Energy-Based Protein Design: Re-Engineering Cellular Retinoic Acid Binding Protein II Assisted by the Moveable-Type Approach.

PubMed

Zhong, Haizhen A; Santos, Elizabeth M; Vasileiou, Chrysoula; Zheng, Zheng; Geiger, James H; Borhan, Babak; Merz, Kenneth M

2018-03-14

How to fine-tune the binding free energy of a small-molecule to a receptor site by altering the amino acid residue composition is a key question in protein engineering. Indeed, the ultimate solution to this problem, to chemical accuracy (±1 kcal/mol), will result in profound and wide-ranging applications in protein design. Numerous tools have been developed to address this question using knowledge-based models to more computationally intensive molecular dynamics simulations-based free energy calculations, but while some success has been achieved there remains room for improvement in terms of overall accuracy and in the speed of the methodology. Here we report a fast, knowledge-based movable-type (MT)-based approach to estimate the absolute and relative free energy of binding as influenced by mutations in a small-molecule binding site in a protein. We retrospectively validate our approach using mutagenesis data for retinoic acid binding to the Cellular Retinoic Acid Binding Protein II (CRABPII) system and then make prospective predictions that are borne out experimentally. The overall performance of our approach is supported by its success in identifying mutants that show high or even sub-nano-molar binding affinities of retinoic acid to the CRABPII system.

Test Systems to Study the Structure and Function of Uncoupling Protein 1: A Critical Overview

PubMed Central

Hirschberg, Verena; Fromme, Tobias; Klingenspor, Martin

2011-01-01

The discovery of active brown adipose tissue (BAT) in healthy adult humans has renewed interest in the biology of this organ. BAT is capable of distributing nutrient energy in the form of heat allowing small mammals to efficiently defend their body temperature when acutely exposed to the cold. On the other hand BAT might be a target for the treatment of obesity and related diseases, as its pharmacological activation could allow release of excess energy stored in white adipose tissue depots. Energy dissipation in BAT depends on the activity of uncoupling protein 1 (UCP1), therefore a BAT-based obesity therapy requires a detailed understanding of structure and function of UCP1. Although UCP1 has been in the focus of research since its discovery, central questions concerning its mechanistic function and regulation are not yet resolved. They have been addressed in native mitochondria but also in several test systems, which are generally used to lower inter-experimental variability and to simplify analysis conditions. Different test systems have contributed to our current knowledge about UCP1 but of course all of them have certain limitations. We here provide an overview about research on UCP1 structure and function in test systems. So far, these have nearly exclusively been employed to study rodent and not human UCP1. Considering that the amino acid sequence of mouse and human UCP1 is only 79% identical, it will be essential to test whether the human version has a similarly high catalytic activity, allowing a relevant amount of energy dissipation in human BAT. Besides the issue of comparable mechanistic function a sufficiently high expression level of human UCP1 is a further prerequisite for anti-obesity therapeutic potential. Treatments which induce BAT hyperplasia and UCP1 expression in humans might therefore be equally important to discover as mere activators of the thermogenic process. PMID:22654819

Dissipation of ‘dark energy’ by cortex in knowledge retrieval

NASA Astrophysics Data System (ADS)

Capolupo, Antonio; Freeman, Walter J.; Vitiello, Giuseppe

2013-03-01

We have devised a thermodynamic model of cortical neurodynamics expressed at the classical level by neural networks and at the quantum level by dissipative quantum field theory. Our model is based on features in the spatial images of cortical activity newly revealed by high-density electrode arrays. We have incorporated the mechanism and necessity for so-called dark energy in knowledge retrieval. We have extended the model first using the Carnot cycle to define our measures for energy, entropy and temperature, and then using the Rankine cycle to incorporate criticality and phase transitions. We describe the dynamics of two interactive fields of neural activity that express knowledge, one at high and the other at low energy density, and the two operators that create and annihilate the fields. We postulate that the extremely high density of energy sequestered briefly in cortical activity patterns can account for the vividness, richness of associations, and emotional intensity of memories recalled by stimuli.

Singers' interest and knowledge levels of vocal function and dysfunction: survey findings.

PubMed

Braun-Janzen, Colleen; Zeine, Lina

2009-07-01

A questionnaire investigating the levels of interest in and knowledge of vocal function and dysfunction was completed by 129 singers. Those with professional singing experience indicated significantly greater interest and higher perceived knowledge levels than amateurs in areas of vocal anatomy and physiology, vocal hygiene, and functional vocal pathologies. Greater interest levels, but not higher perceived knowledge levels were reported by professional singers (PSs) in the area of the role of the speech-language pathologist (SLP) and the voice. Professionals answered significantly more knowledge-based questions correctly than amateurs in all areas except the role of the SLP and the voice. However, findings indicated wide variability in knowledge levels of both groups. Singing teachers (STs) within the group significantly outperformed the remainder of the group in areas of vocal anatomy and physiology, vocal hygiene, and functional vocal pathologies. Scores of the choir directors (CDs) within the group were not significantly superior to the remainder of the group except in the area of functional vocal pathologies. Implications for a preventative approach to vocal health are discussed.

Ecology of an Eel Grass Community

ERIC Educational Resources Information Center

Etri, Lawrence

1978-01-01

Analyzing a square meter of a Zostera community on Long Island's South Shore, this article illustrates the relationship between primary energy producer and primary and secondary energy consumer populations within the Zostera community. Specific plant-animal relationships based upon knowledge of estuarine environments are discussed. (JC)

Fission fragment charge and mass distributions in 239Pu(n, f ) in the adiabatic nuclear energy density functional theory

DOE PAGES

Regnier, D.; Dubray, N.; Schunck, N.; ...

2016-05-13

Here, accurate knowledge of fission fragment yields is an essential ingredient of numerous applications ranging from the formation of elements in the r process to fuel cycle optimization for nuclear energy. The need for a predictive theory applicable where no data are available, together with the variety of potential applications, is an incentive to develop a fully microscopic approach to fission dynamics.

The Role of Knowledge in Participatory and Pluralistic Approaches to ESE

ERIC Educational Resources Information Center

Rudsberg, Karin; Öhman, Johan

2015-01-01

The purpose of this article is to investigate "in situ" the functions that knowledge has when used by students in argumentative discussions. The study is based on Dewey's pragmatic perspective of knowledge, which means that knowledge gets its meaning in the activity at hand. The analyses are conducted using Transactional Argumentation…

New Knowledge Derived from Learned Knowledge: Functional-Anatomic Correlates of Stimulus Equivalence

ERIC Educational Resources Information Center

Schlund, Michael W.; Hoehn-Saric, Rudolf; Cataldo, Michael F.

2007-01-01

Forming new knowledge based on knowledge established through prior learning is a central feature of higher cognition that is captured in research on stimulus equivalence (SE). Numerous SE investigations show that reinforcing behavior under control of distinct sets of arbitrary conditional relations gives rise to stimulus control by new, "derived"…

The Nuclear Energy Knowledge and Validation Center Summary of Activities Conducted in FY16

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

Gougar, Hans David

The Nuclear Energy Knowledge and Validation Center (NEKVaC) is a new initiative by the Department of Energy (DOE) and Idaho National Laboratory (INL) to coordinate and focus the resources and expertise that exist with the DOE toward solving issues in modern nuclear code validation and knowledge management. In time, code owners, users, and developers will view the NEKVaC as a partner and essential resource for acquiring the best practices and latest techniques for validating codes, providing guidance in planning and executing experiments, facilitating access to and maximizing the usefulness of existing data, and preserving knowledge for continual use by nuclearmore » professionals and organizations for their own validation needs. The scope of the NEKVaC covers many interrelated activities that will need to be cultivated carefully in the near term and managed properly once the NEKVaC is fully functional. Three areas comprise the principal mission: (1) identify and prioritize projects that extend the field of validation science and its application to modern codes, (2) develop and disseminate best practices and guidelines for high-fidelity multiphysics/multiscale analysis code development and associated experiment design, and (3) define protocols for data acquisition and knowledge preservation and provide a portal for access to databases currently scattered among numerous organizations. These mission areas, while each having a unique focus, are interdependent and complementary. Likewise, all activities supported by the NEKVaC, both near term and long term, must possess elements supporting all three areas. This cross cutting nature is essential to ensuring that activities and supporting personnel do not become “stove piped” (i.e., focused a specific function that the activity itself becomes the objective rather than achieving the larger vision). This report begins with a description of the mission areas; specifically, the role played by each major committee and the types of activities for which they are responsible. It then lists and describes the proposed near term tasks upon which future efforts can build.« less

Diagnosis and sensor validation through knowledge of structure and function

NASA Technical Reports Server (NTRS)

Scarl, Ethan A.; Jamieson, John R.; Delaune, Carl I.

1987-01-01

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

Detecting opportunities for parallel observations on the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Lucks, Michael

1992-01-01

The presence of multiple scientific instruments aboard the Hubble Space Telescope provides opportunities for parallel science, i.e., the simultaneous use of different instruments for different observations. Determining whether candidate observations are suitable for parallel execution depends on numerous criteria (some involving quantitative tradeoffs) that may change frequently. A knowledge based approach is presented for constructing a scoring function to rank candidate pairs of observations for parallel science. In the Parallel Observation Matching System (POMS), spacecraft knowledge and schedulers' preferences are represented using a uniform set of mappings, or knowledge functions. Assessment of parallel science opportunities is achieved via composition of the knowledge functions in a prescribed manner. The knowledge acquisition, and explanation facilities of the system are presented. The methodology is applicable to many other multiple criteria assessment problems.

The analysis of mathematics teachers' learning on algebra function limit material based on teaching experience difference

NASA Astrophysics Data System (ADS)

Ma'rufi, Budayasa, I. Ketut; Juniati, Dwi

2017-08-01

The aim of this study was to describe the analysis of mathematics teachers' learning on algebra function limit material based on teaching experience difference. The purpose of this study is to describe the analysis of mathematics teacher's learning on limit algebraic functions in terms of the differences of teaching experience. Learning analysis focused on Pedagogical Content Knowledge (PCK) of teachers in mathematics on limit algebraic functions related to the knowledge of pedagogy. PCK of teachers on limit algebraic function is a type of specialized knowledge for teachers on how to teach limit algebraic function that can be understood by students. Subjects are two high school mathematics teacher who has difference of teaching experience they are one Novice Teacher (NP) and one Experienced Teacher (ET). Data are collected through observation of learning in the class, videos of learning, and then analyzed using qualitative analysis. Teacher's knowledge of Pedagogic defined as a knowledge and understanding of teacher about planning and organizing of learning, and application of learning strategy. The research results showed that the Knowledge of Pedagogy on subject NT in mathematics learning on the material of limit function algebra showed that the subject NT tended to describe procedurally, without explaining the reasons why such steps were used, asking questions which tended to be monotonous not be guiding and digging deeper, and less varied in the use of learning strategies while subject ET gave limited guidance and opportunities to the students to find their own answers, exploit the potential of students to answer questions, provide an opportunity for students to interact and work in groups, and subject ET tended to combine conceptual and procedural explanation.

Peak reduction for commercial buildings using energy storage

NASA Astrophysics Data System (ADS)

Chua, K. H.; Lim, Y. S.; Morris, S.

2017-11-01

Battery-based energy storage has emerged as a cost-effective solution for peak reduction due to the decrement of battery’s price. In this study, a battery-based energy storage system is developed and implemented to achieve an optimal peak reduction for commercial customers with the limited energy capacity of the energy storage. The energy storage system is formed by three bi-directional power converter rated at 5 kVA and a battery bank with capacity of 64 kWh. Three control algorithms, namely fixed-threshold, adaptive-threshold, and fuzzy-based control algorithms have been developed and implemented into the energy storage system in a campus building. The control algorithms are evaluated and compared under different load conditions. The overall experimental results show that the fuzzy-based controller is the most effective algorithm among the three controllers in peak reduction. The fuzzy-based control algorithm is capable of incorporating a priori qualitative knowledge and expertise about the load characteristic of the buildings as well as the useable energy without over-discharging the batteries.

Whole Protein Native Fitness Potentials

NASA Astrophysics Data System (ADS)

Faraggi, Eshel; Kloczkowski, Andrzej

2013-03-01

Protein structure prediction can be separated into two tasks: sample the configuration space of the protein chain, and assign a fitness between these hypothetical models and the native structure of the protein. One of the more promising developments in this area is that of knowledge based energy functions. However, standard approaches using pair-wise interactions have shown shortcomings demonstrated by the superiority of multi-body-potentials. These shortcomings are due to residue pair-wise interaction being dependent on other residues along the chain. We developed a method that uses whole protein information filtered through machine learners to score protein models based on their likeness to native structures. For all models we calculated parameters associated with the distance to the solvent and with distances between residues. These parameters, in addition to energy estimates obtained by using a four-body-potential, DFIRE, and RWPlus were used as training for machine learners to predict the fitness of the models. Testing on CASP 9 targets showed that our method is superior to DFIRE, RWPlus, and the four-body potential, which are considered standards in the field.

Thermionic Energy Conversion Based on Graphene van der Waals Heterostructures

PubMed Central

Liang, Shi-Jun; Liu, Bo; Hu, Wei; Zhou, Kun; Ang, L. K.

2017-01-01

Seeking for thermoelectric (TE) materials with high figure of merit (or ZT), which can directly converts low-grade wasted heat (400 to 500 K) into electricity, has been a big challenge. Inspired by the concept of multilayer thermionic devices, we propose and design a solid-state thermionic devices (as a power generator or a refrigerator) in using van der Waals (vdW) heterostructure sandwiched between two graphene electrodes, to achieve high energy conversion efficiency in the temperature range of 400 to 500 K. The vdW heterostructure is composed of suitable multiple layers of transition metal dichalcogenides (TMDs), such as MoS2, MoSe2, WS2 and WSe2. From our calculations, WSe2 and MoSe2 are identified as two ideal TMDs (using the reported experimental material’s properties), which can harvest waste heat at 400 K with efficiencies about 7% to 8%. To our best knowledge, this design is the first in combining the advantages of graphene electrodes and TMDs to function as a thermionic-based device. PMID:28387363

Development of a Design Supporting System for Nano-Materials based on a Framework for Integrated Knowledge of Functioning-Manufacturing Process

NASA Astrophysics Data System (ADS)

Tarumi, Shinya; Kozaki, Kouji; Kitamura, Yoshinobu; Mizoguchi, Riichiro

In the recent materials research, much work aims at realization of ``functional materials'' by changing structure and/or manufacturing process with nanotechnology. However, knowledge about the relationship among function, structure and manufacturing process is not well organized. So, material designers have to consider a lot of things at the same time. It would be very helpful for them to support their design process by a computer system. In this article, we discuss a conceptual design supporting system for nano-materials. Firstly, we consider a framework for representing functional structures and manufacturing processes of nano-materials with relationships among them. We expand our former framework for representing functional knowledge based on our investigation through discussion with experts of nano-materials. The extended framework has two features: 1) it represents functional structures and manufacturing processes comprehensively, 2) it expresses parameters of function and ways with their dependencies because they are important for material design. Next, we describe a conceptual design support system we developed based on the framework with its functionalities. Lastly, we evaluate the utility of our system in terms of functionality for design supports. For this purpose, we tried to represent two real examples of material design. And then we did an evaluation experiment on conceptual design of material using our system with the collaboration of domain experts.

Structure prediction of nanoclusters; a direct or a pre-screened search on the DFT energy landscape?

PubMed

Farrow, M R; Chow, Y; Woodley, S M

2014-10-21

The atomic structure of inorganic nanoclusters obtained via a search for low lying minima on energy landscapes, or hypersurfaces, is reported for inorganic binary compounds: zinc oxide (ZnO)n, magnesium oxide (MgO)n, cadmium selenide (CdSe)n, and potassium fluoride (KF)n, where n = 1-12 formula units. The computational cost of each search is dominated by the effort to evaluate each sample point on the energy landscape and the number of required sample points. The effect of changing the balance between these two factors on the success of the search is investigated. The choice of sample points will also affect the number of required data points and therefore the efficiency of the search. Monte Carlo based global optimisation routines (evolutionary and stochastic quenching algorithms) within a new software package, viz. Knowledge Led Master Code (KLMC), are employed to search both directly and after pre-screening on the DFT energy landscape. Pre-screening includes structural relaxation to minimise a cheaper energy function - based on interatomic potentials - and is found to improve significantly the search efficiency, and typically reduces the number of DFT calculations required to locate the local minima by more than an order of magnitude. Although the choice of functional form is important, the approach is robust to small changes to the interatomic potential parameters. The computational cost of initial DFT calculations of each structure is reduced by employing Gaussian smearing to the electronic energy levels. Larger (KF)n nanoclusters are predicted to form cuboid cuts from the rock-salt phase, but also share many structural motifs with (MgO)n for smaller clusters. The transition from 2D rings to 3D (bubble, or fullerene-like) structures occur at a larger cluster size for (ZnO)n and (CdSe)n. Differences between the HOMO and LUMO energies, for all the compounds apart from KF, are in the visible region of the optical spectrum (2-3 eV); KF lies deep in the UV region at 5 eV and shows little variation. Extrapolating the electron affinities found for the clusters with respect to size results in the qualitatively correct work functions for the respective bulk materials.

Simulation based energy-resource efficient manufacturing integrated with in-process virtual management

NASA Astrophysics Data System (ADS)

Katchasuwanmanee, Kanet; Cheng, Kai; Bateman, Richard

2016-09-01

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow (productivity) and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.

Process management using component thermal-hydraulic function classes

DOEpatents

Morman, James A.; Wei, Thomas Y. C.; Reifman, Jaques

1999-01-01

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced.

Process management using component thermal-hydraulic function classes

DOEpatents

Morman, J.A.; Wei, T.Y.C.; Reifman, J.

1999-07-27

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced. 5 figs.

SU-E-T-332: Dosimetric Impact of Photon Energy and Treatment Technique When Knowledge Based Auto-Planning Is Implemented in Radiotherapy of Localized Prostate Cancer

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

Liu, Z; Kennedy, A; Larsen, E

2015-06-15

Purpose: The aim of this study was to investigate the dosimetric impact of the combination of photon energy and treatment technique on radiotherapy of localized prostate cancer when knowledge based planning was used. Methods: A total of 16 patients with localized prostate cancer were retrospectively retrieved from database and used for this study. For each patient, four types of treatment plans with different combinations of photon energy (6X and 10X) and treatment techniques (7-field IMRT and 2-arc VMAT) were created using a prostate DVH estimation model in RapidPlan™ and Eclipse treatment planning system (Varian Medical System). For any beam arrangement,more » DVH objectives and weighting priorities were generated based on the geometric relationship between the OAR and PTV. Photon optimization algorithm was used for plan optimization and AAA algorithm was used for final dose calculation. Plans were evaluated in terms of the pre-defined dosimetric endpoints for PTV, rectum, bladder, penile bulb, and femur heads. A Student’s paired t-test was used for statistical analysis and p > 0.05 was considered statistically significant. Results: For PTV, V95 was statistically similar among all four types of plans, though the mean dose of 10X plans was higher than that of 6X plans. VMAT plans showed higher heterogeneity index than IMRT plans. No statistically significant difference in dosimetry metrics was observed for rectum, bladder, and penile bulb among plan types. For left and right femur, VMAT plans had a higher mean dose than IMRT plans regardless of photon energy, whereas the maximum dose was similar. Conclusion: Overall, the dosimetric endpoints were similar regardless of photon energy and treatment techniques when knowledge based auto planning was used. Given the similarity in dosimetry metrics of rectum, bladder, and penile bulb, the genitourinary and gastrointestinal toxicities should be comparable among the selections of photon energy and treatment techniques.« less

An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

PubMed

Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

2012-01-01

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

PubMed Central

Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

2012-01-01

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions. PMID:23112650

Knowledge-based nursing diagnosis

NASA Astrophysics Data System (ADS)

Roy, Claudette; Hay, D. Robert

1991-03-01

Nursing diagnosis is an integral part of the nursing process and determines the interventions leading to outcomes for which the nurse is accountable. Diagnoses under the time constraints of modern nursing can benefit from a computer assist. A knowledge-based engineering approach was developed to address these problems. A number of problems were addressed during system design to make the system practical extended beyond capture of knowledge. The issues involved in implementing a professional knowledge base in a clinical setting are discussed. System functions, structure, interfaces, health care environment, and terminology and taxonomy are discussed. An integrated system concept from assessment through intervention and evaluation is outlined.

Advanced software development workstation. Knowledge base design: Design of knowledge base for flight planning application

NASA Technical Reports Server (NTRS)

Izygon, Michel E.

1992-01-01

The development process of the knowledge base for the generation of Test Libraries for Mission Operations Computer (MOC) Command Support focused on a series of information gathering interviews. These knowledge capture sessions are supporting the development of a prototype for evaluating the capabilities of INTUIT on such an application. the prototype includes functions related to POCC (Payload Operation Control Center) processing. It prompts the end-users for input through a series of panels and then generates the Meds associated with the initialization and the update of hazardous command tables for a POCC Processing TLIB.

Noncovalent Interactions of DNA Bases with Naphthalene and Graphene.

PubMed

Cho, Yeonchoo; Min, Seung Kyu; Yun, Jeonghun; Kim, Woo Youn; Tkatchenko, Alexandre; Kim, Kwang S

2013-04-09

The complexes of a DNA base bound to graphitic systems are studied. Considering naphthalene as the simplest graphitic system, DNA base-naphthalene complexes are scrutinized at high levels of ab initio theory including coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] at the complete basis set (CBS) limit. The stacked configurations are the most stable, where the CCSD(T)/CBS binding energies of guanine, adenine, thymine, and cytosine are 9.31, 8.48, 8.53, 7.30 kcal/mol, respectively. The energy components are investigated using symmetry-adapted perturbation theory based on density functional theory including the dispersion energy. We compared the CCSD(T)/CBS results with several density functional methods applicable to periodic systems. Considering accuracy and availability, the optB86b nonlocal functional and the Tkatchenko-Scheffler functional are used to study the binding energies of nucleobases on graphene. The predicted values are 18-24 kcal/mol, though many-body effects on screening and energy need to be further considered.

[Supercomputer investigation of the protein-ligand system low-energy minima].

PubMed

Oferkin, I V; Sulimov, A V; Katkova, E V; Kutov, D K; Grigoriev, F V; Kondakova, O A; Sulimov, V B

2015-01-01

The accuracy of the protein-ligand binding energy calculations and ligand positioning is strongly influenced by the choice of the docking target function. This work demonstrates the evaluation of the five different target functions used in docking: functions based on MMFF94 force field and functions based on PM7 quantum-chemical method accounting or without accounting the implicit solvent model (PCM, COSMO or SGB). For these purposes the ligand positions corresponding to the minima of the target function and the experimentally known ligand positions in the protein active site (crystal ligand positions) were compared. Each function was examined on the same test-set of 16 protein-ligand complexes. The new parallelized docking program FLM based on Monte Carlo search algorithm was developed to perform the comprehensive low-energy minima search and to calculate the protein-ligand binding energy. This study demonstrates that the docking target function based on the MMFF94 force field can be used to detect the crystal or near crystal positions of the ligand by the finding the low-energy local minima spectrum of the target function. The importance of solvent accounting in the docking process for the accurate ligand positioning is also shown. The accuracy of the ligand positioning as well as the correlation between the calculated and experimentally determined protein-ligand binding energies are improved when the MMFF94 force field is substituted by the new PM7 method with implicit solvent accounting.

Spectroscopy of reflection-asymmetric nuclei with relativistic energy density functionals

NASA Astrophysics Data System (ADS)

Xia, S. Y.; Tao, H.; Lu, Y.; Li, Z. P.; Nikšić, T.; Vretenar, D.

2017-11-01

Quadrupole and octupole deformation energy surfaces, low-energy excitation spectra, and transition rates in 14 isotopic chains: Xe, Ba, Ce, Nd, Sm, Gd, Rn, Ra, Th, U, Pu, Cm, Cf, and Fm, are systematically analyzed using a theoretical framework based on a quadrupole-octupole collective Hamiltonian (QOCH), with parameters determined by constrained reflection-asymmetric and axially symmetric relativistic mean-field calculations. The microscopic QOCH model based on the PC-PK1 energy density functional and δ -interaction pairing is shown to accurately describe the empirical trend of low-energy quadrupole and octupole collective states, and predicted spectroscopic properties are consistent with recent microscopic calculations based on both relativistic and nonrelativistic energy density functionals. Low-energy negative-parity bands, average octupole deformations, and transition rates show evidence for octupole collectivity in both mass regions, for which a microscopic mechanism is discussed in terms of evolution of single-nucleon orbitals with deformation.

Constraints on the ωπ Form Factor from Analyticity and Unitarity

NASA Astrophysics Data System (ADS)

Ananthanarayan, B.; Caprini, Irinel; Kubis, Bastian

Form factors are important low-energy quantities and an accurate knowledge of these sheds light on the strong interactions. A variety of methods based on general principles have been developed to use information known in different energy regimes to constrain them in regions where experimental information needs to be tested precisely. Here we review our recent work on the electromagnetic ωπ form factor in a model-independent framework known as the method of unitarity bounds, partly motivated by the discre-pancies noted recently between the theoretical calculations of the form factor based on dispersion relations and certain experimental data measured from the decay ω → π0γ*. We have applied a modified dispersive formalism, which uses as input the discontinuity of the ωπ form factor calculated by unitarity below the ωπ threshold and an integral constraint on the square of its modulus above this threshold. The latter constraint was obtained by exploiting unitarity and the positivity of the spectral function of a QCD correlator, computed on the spacelike axis by operator product expansion and perturbative QCD. An alternative constraint is obtained by using data available at higher energies for evaluating an integral of the modulus squared with a suitable weight function. From these conditions we derived upper and lower bounds on the modulus of the ωπ form factor in the region below the ωπ threshold. The results confirm the existence of a disagreement between dispersion theory and experimental data on the ωπ form factor around 0:6 GeV, including those from NA60 published in 2016.

Constraints on the ωπ form factor from analyticity and unitarity

NASA Astrophysics Data System (ADS)

Ananthanarayan, B.; Caprini, Irinel; Kubis, Bastian

2016-05-01

Form factors are important low-energy quantities and an accurate knowledge of these sheds light on the strong interactions. A variety of methods based on general principles have been developed to use information known in different energy regimes to constrain them in regions where experimental information needs to be tested precisely. Here we review our recent work on the electromagnetic ωπ form factor in a model-independent framework known as the method of unitarity bounds, partly motivated by the discrepancies noted recently between the theoretical calculations of the form factor based on dispersion relations and certain experimental data measured from the decay ω → π0γ∗. We have applied a modified dispersive formalism, which uses as input the discontinuity of the ωπ form factor calculated by unitarity below the ωπ threshold and an integral constraint on the square of its modulus above this threshold. The latter constraint was obtained by exploiting unitarity and the positivity of the spectral function of a QCD correlator, computed on the spacelike axis by operator product expansion and perturbative QCD. An alternative constraint is obtained by using data available at higher energies for evaluating an integral of the modulus squared with a suitable weight function. From these conditions we derived upper and lower bounds on the modulus of the ωπ form factor in the region below the ωπ threshold. The results confirm the existence of a disagreement between dispersion theory and experimental data on the ωπ form factor around 0.6 GeV, including those from NA60 published in 2016.

Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

Analysis of Defects in Trouser Manufacturing: Development of a Knowledge-Based Framework. Volume 1. Final Technical Report

DTIC Science & Technology

1992-02-28

the primary goal of instituting remedial measures. Many apparel plants, as they function today in the United States, do not maintain an accu- rate...type of usage is the primary functional mode for FDAS. Alternatively, the user could suggest a defect to FDAS and let it find out if the defect is...Endeavor The primary objective of the research effort is to develop a knowledge-based system to an- alyze the causes of defects in apparel

Methods for understanding microbial community structures and functions in microbial fuel cells: a review.

PubMed

Zhi, Wei; Ge, Zheng; He, Zhen; Zhang, Husen

2014-11-01

Microbial fuel cells (MFCs) employ microorganisms to recover electric energy from organic matter. However, fundamental knowledge of electrochemically active bacteria is still required to maximize MFCs power output for practical applications. This review presents microbiological and electrochemical techniques to help researchers choose the appropriate methods for the MFCs study. Pre-genomic and genomic techniques such as 16S rRNA based phylogeny and metagenomics have provided important information in the structure and genetic potential of electrode-colonizing microbial communities. Post-genomic techniques such as metatranscriptomics allow functional characterizations of electrode biofilm communities by quantifying gene expression levels. Isotope-assisted phylogenetic analysis can further link taxonomic information to microbial metabolisms. A combination of electrochemical, phylogenetic, metagenomic, and post-metagenomic techniques offers opportunities to a better understanding of the extracellular electron transfer process, which in turn can lead to process optimization for power output. Copyright © 2014 Elsevier Ltd. All rights reserved.

The place of practical wisdom in science education: what can be learned from Aristotelian ethics and a virtue-based theory of knowledge

NASA Astrophysics Data System (ADS)

Salloum, Sara

2017-06-01

This conceptual paper aims to characterize science teachers' practical knowledge utilizing a virtue-based theory of knowledge and the Aristotelian notion of phronesis/practical wisdom. The article argues that a greater understanding of the concept of phronesis and its relevance to science education would enrich our understandings of teacher knowledge, its development, and consequently models of teacher education. Views of teacher knowledge presented in this paper are informed by philosophical literature that questions normative views of knowledge and argues for a virtue-based epistemology rather than a belief-based one. The paper first outlines general features of phronesis/practical wisdom. Later, a virtue-based view of knowledge is described. A virtue-based view binds knowledge with moral concepts and suggests that knowledge development is motivated by intellectual virtues such as intellectual sobriety, perseverance, fairness, and humility. A virtue-based theory of knowledge gives prominence to the virtue of phronesis/practical wisdom, whose primary function is to mediate among virtues and theoretical knowledge into a line of action that serves human goods. The role of phronesis and its relevance to teaching science are explained accordingly. I also discuss differences among various characterizations of practical knowledge in science education and a virtue-based characterization. Finally, implications and further questions for teacher education are presented.

Upper Primary School Teachers' Mathematical Knowledge for Teaching Functional Thinking in Algebra

ERIC Educational Resources Information Center

Wilkie, Karina J.

2014-01-01

This article is based on a project that investigated teachers' knowledge in teaching an important aspect of algebra in the middle years of schooling--functions, relations and joint variation. As part of the project, 105 upper primary teachers were surveyed during their participation in Contemporary Teaching and Learning of Mathematics, a research…

A Cognitive Task Analysis, with Implications for Designing a Simulation-Based Performance Assessment.

ERIC Educational Resources Information Center

Mislevy, Robert J.; Steinberg, Linda S.; Breyer, F. Jay; Almond, Russell G.; Johnson, Lynn

To function effectively as a learning environment, a simulation system must present learners with situations in which they use relevant knowledge, skills, and abilities. To function effectively as an assessment, such a system must additionally be able to evoke and interpret observable evidence about targeted knowledge in a manner that is…

Schema Theories as a Base for the Structural Representation of the Knowledge State.

ERIC Educational Resources Information Center

Dochy, F. J. R. C.; Bouwens, M. R. J.

From the view of schema-transfer theory, the use of schemata with their several functions gives an explanation for the facilitative effect of prior knowledge on learning processes. This report gives a theoretical exploration of the concept of schemata, underlying schema theories, and functions of schemata to indicate the importance of schema…

A Web-Based Earth-Systems Knowledge Portal and Collaboration Platform

NASA Astrophysics Data System (ADS)

D'Agnese, F. A.; Turner, A. K.

2010-12-01

In support of complex water-resource sustainability projects in the Great Basin region of the United States, Earth Knowledge, Inc. has developed several web-based data management and analysis platforms that have been used by its scientists, clients, and public to facilitate information exchanges, collaborations, and decision making. These platforms support accurate water-resource decision-making by combining second-generation internet (Web 2.0) technologies with traditional 2D GIS and web-based 2D and 3D mapping systems such as Google Maps, and Google Earth. Most data management and analysis systems use traditional software systems to address the data needs and usage behavior of the scientific community. In contrast, these platforms employ more accessible open-source and “off-the-shelf” consumer-oriented, hosted web-services. They exploit familiar software tools using industry standard protocols, formats, and APIs to discover, process, fuse, and visualize earth, engineering, and social science datasets. Thus, they respond to the information needs and web-interface expectations of both subject-matter experts and the public. Because the platforms continue to gather and store all the contributions of their broad-spectrum of users, each new assessment leverages the data, information, and expertise derived from previous investigations. In the last year, Earth Knowledge completed a conceptual system design and feasibility study for a platform, which has a Knowledge Portal providing access to users wishing to retrieve information or knowledge developed by the science enterprise and a Collaboration Environment Module, a framework that links the user-access functions to a Technical Core supporting technical and scientific analyses including Data Management, Analysis and Modeling, and Decision Management, and to essential system administrative functions within an Administrative Module. The over-riding technical challenge is the design and development of a single technical platform that is accessed through a flexible series of knowledge portal and collaboration environment styles reflecting the information needs and user expectations of a diverse community of users. Recent investigations have defined the information needs and expectations of the major end-users and also have reviewed and assessed a wide variety of modern web-based technologies. Combining these efforts produced design specifications and recommendations for the selection and integration of web- and client-based tools. When fully developed, the resulting platform will: -Support new, advanced information systems and decision environments that take full advantage of multiple data sources and platforms; -Provide a distribution network tailored to the timely delivery of products to a broad range of users that are needed to support applications in disaster management, resource management, energy, and urban sustainability; -Establish new integrated multiple-user requirements and knowledge databases that support researchers and promote infusion of successful technologies into existing processes; and -Develop new decision support strategies and presentation methodologies for applied earth science applications to reduce risk, cost, and time.

Machine learning-based screening of complex molecules for polymer solar cells

NASA Astrophysics Data System (ADS)

Jørgensen, Peter Bjørn; Mesta, Murat; Shil, Suranjan; García Lastra, Juan Maria; Jacobsen, Karsten Wedel; Thygesen, Kristian Sommer; Schmidt, Mikkel N.

2018-06-01

Polymer solar cells admit numerous potential advantages including low energy payback time and scalable high-speed manufacturing, but the power conversion efficiency is currently lower than for their inorganic counterparts. In a Phenyl-C_61-Butyric-Acid-Methyl-Ester (PCBM)-based blended polymer solar cell, the optical gap of the polymer and the energetic alignment of the lowest unoccupied molecular orbital (LUMO) of the polymer and the PCBM are crucial for the device efficiency. Searching for new and better materials for polymer solar cells is a computationally costly affair using density functional theory (DFT) calculations. In this work, we propose a screening procedure using a simple string representation for a promising class of donor-acceptor polymers in conjunction with a grammar variational autoencoder. The model is trained on a dataset of 3989 monomers obtained from DFT calculations and is able to predict LUMO and the lowest optical transition energy for unseen molecules with mean absolute errors of 43 and 74 meV, respectively, without knowledge of the atomic positions. We demonstrate the merit of the model for generating new molecules with the desired LUMO and optical gap energies which increases the chance of finding suitable polymers by more than a factor of five in comparison to the randomised search used in gathering the training set.

Energy: A Cross-Curricular Approach.

ERIC Educational Resources Information Center

Lalonde, Christine

This guide is based on the premise that lives (and lifestyles) revolve around the production, consumption, and conversion of energy. Yet for such an all-encompassing concept little accompanying factual knowledge exists at the grade-school level. The objectives (and the resulting activities and extensions) are focused on the needs of the upper…

Study by molecular dynamics of the influence of temperature and pressure on the optical properties of undoped 3C-SiC structures

NASA Astrophysics Data System (ADS)

Domingues, Gilberto; Monthe, Aubin Mekeze; Guévelou, Simon; Rousseau, Benoit

2018-01-01

Silicon carbide (SiC)-based open-cell foams appear to be promising porous materials for designing high-temperature energy conversion systems such as volumetric solar receivers. In these media, heat transfers and fluid flows occur simultaneously. The numerical models developed for computing the thermal efficiencies of SiC foams must take into account the energy contribution of thermal radiation. In particular, the thermal radiative properties of these foams must be accurately known. This explains why knowledge of the pressure and temperature dependences of the optical properties of the crystalline parts, which compose the foams, is of primary concern for computing the latter properties correctly. However, the data available in the literature provide the evolution laws of the dielectric functions, needed to calculate the optical properties, as dependent on one thermodynamic parameter at a time. To deal with this issue, a study of the temperature/pressure influence on the dielectric functions of a silicon carbide structure by simulation with molecular dynamics (MD) is presented in this paper. The Vashishta interaction potential, based on the sum of two- and three-body terms, is used in this study. The simulations are carried out on undoped 3C-SiC at pressures ranging from 0.2 to 20 GPa and temperatures ranging from 300 K to 1500 K. The dielectric functions are obtained by applying the linear response theory and comparing them with values provided in the literature, using a Lorentz model. The simulated results, in good agreement with the experimental ones, make it possible to establish the evolution laws of the dielectric functions with both parameters, temperature and pressure, applicable to any field requiring the use of undoped silicon carbide.

A threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

Fission fragment charge and mass distributions in 239Pu(n ,f ) in the adiabatic nuclear energy density functional theory

NASA Astrophysics Data System (ADS)

Regnier, D.; Dubray, N.; Schunck, N.; Verrière, M.

2016-05-01

Background: Accurate knowledge of fission fragment yields is an essential ingredient of numerous applications ranging from the formation of elements in the r process to fuel cycle optimization for nuclear energy. The need for a predictive theory applicable where no data are available, together with the variety of potential applications, is an incentive to develop a fully microscopic approach to fission dynamics. Purpose: In this work, we calculate the pre-neutron emission charge and mass distributions of the fission fragments formed in the neutron-induced fission of 239Pu using a microscopic method based on nuclear density functional theory (DFT). Methods: Our theoretical framework is the nuclear energy density functional (EDF) method, where large-amplitude collective motion is treated adiabatically by using the time-dependent generator coordinate method (TDGCM) under the Gaussian overlap approximation (GOA). In practice, the TDGCM is implemented in two steps. First, a series of constrained EDF calculations map the configuration and potential-energy landscape of the fissioning system for a small set of collective variables (in this work, the axial quadrupole and octupole moments of the nucleus). Then, nuclear dynamics is modeled by propagating a collective wave packet on the potential-energy surface. Fission fragment distributions are extracted from the flux of the collective wave packet through the scission line. Results: We find that the main characteristics of the fission charge and mass distributions can be well reproduced by existing energy functionals even in two-dimensional collective spaces. Theory and experiment agree typically within two mass units for the position of the asymmetric peak. As expected, calculations are sensitive to the structure of the initial state and the prescription for the collective inertia. We emphasize that results are also sensitive to the continuity of the collective landscape near scission. Conclusions: Our analysis confirms that the adiabatic approximation provides an effective scheme to compute fission fragment yields. It also suggests that, at least in the framework of nuclear DFT, three-dimensional collective spaces may be a prerequisite to reach 10% accuracy in predicting pre-neutron emission fission fragment yields.

Threats and knowledge gaps for ecosystem services provided by kelp forests: a northeast Atlantic perspective

PubMed Central

Smale, Dan A; Burrows, Michael T; Moore, Pippa; O'Connor, Nessa; Hawkins, Stephen J

2013-01-01

Kelp forests along temperate and polar coastlines represent some of most diverse and productive habitats on the Earth. Here, we synthesize information from >60 years of research on the structure and functioning of kelp forest habitats in European waters, with particular emphasis on the coasts of UK and Ireland, which represents an important biogeographic transition zone that is subjected to multiple threats and stressors. We collated existing data on kelp distribution and abundance and reanalyzed these data to describe the structure of kelp forests along a spatial gradient spanning more than 10° of latitude. We then examined ecological goods and services provided by kelp forests, including elevated secondary production, nutrient cycling, energy capture and flow, coastal defense, direct applications, and biodiversity repositories, before discussing current and future threats posed to kelp forests and identifying key knowledge gaps. Recent evidence unequivocally demonstrates that the structure of kelp forests in the NE Atlantic is changing in response to climate- and non-climate-related stressors, which will have major implications for the structure and functioning of coastal ecosystems. However, kelp-dominated habitats along much of the NE Atlantic coastline have been chronically understudied over recent decades in comparison with other regions such as Australasia and North America. The paucity of field-based research currently impedes our ability to conserve and manage these important ecosystems. Targeted observational and experimental research conducted over large spatial and temporal scales is urgently needed to address these knowledge gaps. PMID:24198956

Threats and knowledge gaps for ecosystem services provided by kelp forests: a northeast Atlantic perspective.

PubMed

Smale, Dan A; Burrows, Michael T; Moore, Pippa; O'Connor, Nessa; Hawkins, Stephen J

2013-10-01

Kelp forests along temperate and polar coastlines represent some of most diverse and productive habitats on the Earth. Here, we synthesize information from >60 years of research on the structure and functioning of kelp forest habitats in European waters, with particular emphasis on the coasts of UK and Ireland, which represents an important biogeographic transition zone that is subjected to multiple threats and stressors. We collated existing data on kelp distribution and abundance and reanalyzed these data to describe the structure of kelp forests along a spatial gradient spanning more than 10° of latitude. We then examined ecological goods and services provided by kelp forests, including elevated secondary production, nutrient cycling, energy capture and flow, coastal defense, direct applications, and biodiversity repositories, before discussing current and future threats posed to kelp forests and identifying key knowledge gaps. Recent evidence unequivocally demonstrates that the structure of kelp forests in the NE Atlantic is changing in response to climate- and non-climate-related stressors, which will have major implications for the structure and functioning of coastal ecosystems. However, kelp-dominated habitats along much of the NE Atlantic coastline have been chronically understudied over recent decades in comparison with other regions such as Australasia and North America. The paucity of field-based research currently impedes our ability to conserve and manage these important ecosystems. Targeted observational and experimental research conducted over large spatial and temporal scales is urgently needed to address these knowledge gaps.

The Design of Individual Knowledge Sharing Platform Based on Blog for Online Information Literacy Education

NASA Astrophysics Data System (ADS)

Qun, Zeng; Xiaocheng, Zhong

Knowledge sharing means that an individual, team and organization share the knowledge with other members of the organization in the course of activities through the various ways. This paper analyzes the obstacle factors in knowledge sharing based on the technical point, and chooses the Blog technology to build a platform for improving knowledge sharing between individuals. The construction of the platform is an important foundation for information literacy education, and it also can be used to achieve online information literacy education. Finally, it gives a detailed analysis of its functions, advantages and disadvantages.

Current level and correlates of traditional cooking energy sources utilization in urban settings in the context of climate change and health, northwest Ethiopia: a case of Debre Markos town.

PubMed

Geremew, Kumlachew; Gedefaw, Molla; Dagnew, Zewdu; Jara, Dube

2014-01-01

Traditional biomass has been the major source of cooking energy for major segment of Ethiopian population for thousands of years. Cognizant of this energy poverty, the Government of Ethiopia has been spending huge sum of money to increase hydroelectric power generating stations. To assess current levels and correlates of traditional cooking energy sources utilization. A community based cross-sectional study was conducted employing both quantitative and qualitative approaches on systematically selected 423 households for quantitative and purposively selected 20 people for qualitative parts. SPSS version 16 for windows was used to analyze the quantitative data. Logistic regression was fitted to assess possible associations and its strength was measured using odds ratio at 95% CI. Qualitative data were analyzed thematically. The study indicated that 95% of households still use traditional biomass for cooking. Those who were less knowledgeable about negative health and environmental effects of traditional cooking energy sources were seven and six times more likely to utilize them compared with those who were knowledgeable (AOR (95% CI) = 7.56 (1.635, 34.926), AOR (95% CI) = 6.68 (1.80, 24.385), resp.). The most outstanding finding of this study was that people use traditional energy for cooking mainly due to lack of the knowledge and their beliefs about food prepared using traditional energy. That means "...people still believe that food cooked with charcoal is believed to taste delicious than cooked with other means."  The majority of households use traditional biomass for cooking due to lack of knowledge and belief. Therefore, mechanisms should be designed to promote electric energy and to teach the public about health effects of traditional cooking energy source.

Operationalizing Levels of Academic Mastery Based on Vygotsky’s Theory

PubMed Central

Nezhnov, Peter; Kardanova, Elena; Ludlow, Larry

2014-01-01

The present study tested the possibility of operationalizing levels of knowledge acquisition based on Vygotsky’s theory of cognitive growth. An assessment tool (SAM-Math) was developed to capture a hypothesized hierarchical structure of mathematical knowledge consisting of procedural, conceptual, and functional levels. In Study 1, SAM-Math was administered to 4th-grade students (N = 2,216). The results of Rasch analysis indicated that the test provided an operational definition for the construct of mathematical competence that included the three levels of mastery corresponding to the theoretically based hierarchy of knowledge. In Study 2, SAM-Math was administered to students in 4th, 6th, 8th, and 10th grades (N = 396) to examine developmental changes in the levels of mathematics knowledge. The results showed that the mastery of mathematical concepts presented in elementary school continued to deepen beyond elementary school, as evidenced by a significant growth in conceptual and functional levels of knowledge. The findings are discussed in terms of their implications for psychological theory, test design, and educational practice. PMID:29795820

A Method for the Calculation of Lattice Energies of Complex Crystals with Application to the Oxides of Molybdenum

NASA Technical Reports Server (NTRS)

Chaney, William S.

1961-01-01

A theoretical study has been made of molybdenum dioxide and molybdenum trioxide in order to extend the knowledge of factors Involved in the oxidation of molybdenum. New methods were developed for calculating the lattice energies based on electrostatic valence theory, and the coulombic, polarization, Van der Waals, and repulsion energie's were calculated. The crystal structure was examined and structure details were correlated with lattice energy.

Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review

PubMed Central

Lv, Zhuowen; Xing, Xianglei; Wang, Kejun; Guan, Donghai

2015-01-01

Gait is a unique perceptible biometric feature at larger distances, and the gait representation approach plays a key role in a video sensor-based gait recognition system. Class Energy Image is one of the most important gait representation methods based on appearance, which has received lots of attentions. In this paper, we reviewed the expressions and meanings of various Class Energy Image approaches, and analyzed the information in the Class Energy Images. Furthermore, the effectiveness and robustness of these approaches were compared on the benchmark gait databases. We outlined the research challenges and provided promising future directions for the field. To the best of our knowledge, this is the first review that focuses on Class Energy Image. It can provide a useful reference in the literature of video sensor-based gait representation approach. PMID:25574935

Exploring the Impact of a Standards-Based Mathematics and Pedagogy Class on Preservice Teachers' Beliefs and Subject Matter Knowledge

ERIC Educational Resources Information Center

Stohlmann, Micah Stephen

2012-01-01

This case study explored the impact of a standards-based mathematics and pedagogy class on preservice elementary teachers' beliefs and conceptual subject matter knowledge of linear functions. The framework for the standards-based mathematics and pedagogy class in this study involved the National Council of Teachers of Mathematics Standards,…

Refinement of protein termini in template-based modeling using conformational space annealing.

PubMed

Park, Hahnbeom; Ko, Junsu; Joo, Keehyoung; Lee, Julian; Seok, Chaok; Lee, Jooyoung

2011-09-01

The rapid increase in the number of experimentally determined protein structures in recent years enables us to obtain more reliable protein tertiary structure models than ever by template-based modeling. However, refinement of template-based models beyond the limit available from the best templates is still needed for understanding protein function in atomic detail. In this work, we develop a new method for protein terminus modeling that can be applied to refinement of models with unreliable terminus structures. The energy function for terminus modeling consists of both physics-based and knowledge-based potential terms with carefully optimized relative weights. Effective sampling of both the framework and terminus is performed using the conformational space annealing technique. This method has been tested on a set of termini derived from a nonredundant structure database and two sets of termini from the CASP8 targets. The performance of the terminus modeling method is significantly improved over our previous method that does not employ terminus refinement. It is also comparable or superior to the best server methods tested in CASP8. The success of the current approach suggests that similar strategy may be applied to other types of refinement problems such as loop modeling or secondary structure rearrangement. Copyright © 2011 Wiley-Liss, Inc.

Effects of functional interactivity on patients' knowledge, empowerment, and health outcomes: an experimental model-driven evaluation of a web-based intervention.

PubMed

Camerini, Luca; Schulz, Peter Johannes

2012-07-18

The effectiveness of eHealth interventions in terms of reach and outcomes is now well documented. However, there is a need to understand not only whether eHealth interventions work, but also what kind of functions and mechanisms enhance their effectiveness. The present investigation contributes to tackling these challenges by investigating the role played by functional interactivity on patients' knowledge, empowerment, and health outcomes. To test whether health knowledge and empowerment mediate a possible relationship between the availability of interactive features on an eHealth application and individuals' health outcomes. We present an empirical, model-driven evaluation of the effects of functional interactivity implemented in an eHealth application, based on a brief theoretical review of the constructs of interactivity, health knowledge, empowerment, and health outcomes. We merged these constructs into a theoretical model of interactivity effects that we tested on an eHealth application for patients with fibromyalgia syndrome (FMS). This study used a pretest-posttest experimental design. We recruited 165 patients and randomly assigned them to three study groups, corresponding to different levels of functional interactivity. Eligibility to participate in the study required that patients (1) be fluent in Italian, (2) have access to the Internet, (3) report confidence in how to use a computer, and (4) have received a diagnosis of FMS from a doctor. We used structural equation modeling techniques to analyze changes between the pretest and the posttest results. The main finding was that functional interactivity had no impact on empowerment dimensions, nor direct observable effects on knowledge. However, knowledge positively affected health outcomes (b = -.12, P = .02), as did the empowerment dimensions of meaning (b = -.49, P < .001) and impact (b = -.25, P < .001). The theoretical model was partially confirmed, but only as far as the effects of knowledge and empowerment were concerned. The differential effect of interactive functions was by far weaker than expected. The strong impact of knowledge and empowerment on health outcomes suggests that these constructs should be targeted and enhanced by eHealth applications.

The safe use of surgical energy devices by surgeons may be overestimated.

PubMed

Ha, Ally; Richards, Carly; Criman, Erik; Piaggione, Jillian; Yheulon, Christopher; Lim, Robert

2018-03-01

Surgical energy injuries are an underappreciated phenomenon. Improper use of surgical energy or poor attention to patient safety can result in operating room fires, tissue injuries, and interferences with other electronic devices, while rare complications can be devastatingly severe. Despite this, there is no current standard requirement for educating surgeons on the safe use of energy-based devices or evaluation of electrosurgery (ES) education in residency training, credentialing, or practice. The study aimed to assess the current baseline knowledge of surgeons and surgical trainees with regards to ES across varying experiences at a tertiary level care center. Surgeons and surgical trainees from seven surgical specialties (General Surgery, Cardiothoracic Surgery, Vascular Surgery, Obstetrics/Gynecology, Orthopedic Surgery, Urology, and Otorhinolaryngology) at a tertiary level care hospital were tested. Testing included an evaluation regarding their background training and experiences with ES-related adverse events and a 15 multiple-choice-question exam testing critical knowledge of ES. A total of 134 surveys were sent out with 72 responses (53.7%). The mean quiz score was 51.5 ± 15.5% (passing score was 80%). Of staff surgeons, 33/65 (50.8%) completed the survey with mean and median scores of 54.9 and 53.3%, respectively (range 33.3-86.7%). Of surgical trainees, 39/69 (56.5%) completed the survey with mean and median scores of 48.6 and 46.7%, respectively (range 13.3-80.0%). There were no statistically significant differences based on training status (p = 0.08), previous training (p = 0.24), number of cases (p = 0.06), or specialty (p = 0.689). Surgeons and surgical trainees both have a significant knowledge gap in the safe and effective use of surgical energy devices, regardless of surgical specialty and despite what they feel was adequate training. The knowledge gap is not improved with experience. A formal surgical energy education program should be a requirement for residency training or credentialing.

Energy Levels of Hydrogen and Deuterium

National Institute of Standards and Technology Data Gateway

SRD 142 NIST Energy Levels of Hydrogen and Deuterium (Web, free access)   This database provides theoretical values of energy levels of hydrogen and deuterium for principle quantum numbers n = 1 to 200 and all allowed orbital angular momenta l and total angular momenta j. The values are based on current knowledge of the revelant theoretical contributions including relativistic, quantum electrodynamic, recoil, and nuclear size effects.

Chapter 8: Estimating net greenhouse gas (GHG) emissions from wood energy use; Issues and the current state of knowledge

Treesearch

Prakash Nepal; Kenneth E. Skog

2014-01-01

Use of woody biomass from sustainably managed sources to produce energy is considered an important strategy to mitigate climate change because the resource is renewable (biomass regrowth on land recaptures emitted carbon dioxide (CO2) due to biomass burning) and can substitute for fossil-fuel-based energy such as coal and natural gas. However,...

The development of a classification schema for arts-based approaches to knowledge translation.

PubMed

Archibald, Mandy M; Caine, Vera; Scott, Shannon D

2014-10-01

Arts-based approaches to knowledge translation are emerging as powerful interprofessional strategies with potential to facilitate evidence uptake, communication, knowledge, attitude, and behavior change across healthcare provider and consumer groups. These strategies are in the early stages of development. To date, no classification system for arts-based knowledge translation exists, which limits development and understandings of effectiveness in evidence syntheses. We developed a classification schema of arts-based knowledge translation strategies based on two mechanisms by which these approaches function: (a) the degree of precision in key message delivery, and (b) the degree of end-user participation. We demonstrate how this classification is necessary to explore how context, time, and location shape arts-based knowledge translation strategies. Classifying arts-based knowledge translation strategies according to their core attributes extends understandings of the appropriateness of these approaches for various healthcare settings and provider groups. The classification schema developed may enhance understanding of how, where, and for whom arts-based knowledge translation approaches are effective, and enable theorizing of essential knowledge translation constructs, such as the influence of context, time, and location on utilization strategies. The classification schema developed may encourage systematic inquiry into the effectiveness of these approaches in diverse interprofessional contexts. © 2014 Sigma Theta Tau International.

Energy management and attitude control for spacecraft

NASA Astrophysics Data System (ADS)

Costic, Bret Thomas

2001-07-01

This PhD dissertation describes the design and implementation of various control strategies centered around spacecraft applications: (i) an attitude control system for spacecraft, (ii) flywheels used for combined attitude and energy tracking, and (iii) an adaptive autobalancing control algorithm. The theory found in each of these sections is demonstrated through simulation or experimental results. An introduction to each of these three primary chapters can be found in chapter one. The main problem addressed in the second chapter is the quaternion-based, attitude tracking control of rigid spacecraft without angular velocity measurements and in the presence of an unknown inertia matrix. As a stepping-stone, an adaptive, full-state feedback controller that compensates for parametric uncertainty while ensuring asymptotic attitude tracking errors is designed. The adaptive, full-state feedback controller is then redesigned such that the need for angular velocity measurements is eliminated. The proposed adaptive, output feedback controller ensures asymptotic attitude tracking. This work uses a four-parameter representation of the spacecraft attitude that does not exhibit singular orientations as in the case of the previous three-parameter representation-based results. To the best of my knowledge, this represents the first solution to the adaptive, output feedback, attitude tracking control problem for the quaternion representation. Simulation results are included to illustrate the performance of the proposed output feedback control strategy. The third chapter is devoted to the use of multiple flywheels that integrate the energy storage and attitude control functions in space vehicles. This concept, which is referred to as an Integrated Energy Management and Attitude Control (IEMAC) system, reduces the space vehicle bus mass, volume, cost, and maintenance requirements while maintaining or improving the space vehicle performance. To this end, two nonlinear IEMAC strategies (model-based and adaptive) that simultaneously track a desired attitude trajectory and desired energy/power profile are presented. Both strategies ensure asymptotic tracking while the adaptive controller compensates for uncertain spacecraft inertia. In the final chapter, a control strategy is designed for a rotating, unbalanced disk. The control strategy, which is composed of a control torque and two control forces, regulates the disk displacement and ensures angular velocity tracking. The controller uses a desired compensation adaptation law and a gain adjusted forgetting factor to achieve exponential stability despite the lack of knowledge of the imbalance-related parameters, provided a mild persistency of excitation condition is satisfied.

Soil as a Sustainable Resource for the Bioeconomy - BonaRes

NASA Astrophysics Data System (ADS)

Wollschläger, Ute; Amelung, Wulf; Brüggemann, Nicolas; Brunotte, Joachim; Gebbers, Robin; Grosch, Rita; Heinrich, Uwe; Helming, Katharina; Kiese, Ralf; Leinweber, Peter; Reinhold-Hurek, Barbara; Veldkamp, Edzo; Vogel, Hans-Jörg; Winkelmann, Traud

2017-04-01

Fertile soils are a fundamental resource for the production of biomass and provision of food and energy. A growing world population and latest climate targets lead to an increasing demand for bio-based products which require preserving and - ideally - improving the long-term productivity of soils as a bio-economic resource. At the same time, other soil functions and ecosystem services need to be maintained: filter for clean water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these soil functions result from the interaction of a multitude of physical, chemical and biological processes which are insufficiently understood. In addition, we lack understanding about the interplay between the socio-economic system and the soil system and how soil functions benefit human wellbeing, including SDGs. However, a solid and integrated assessment of soil quality requires the consideration of the ensemble of soil functions and its relation to soil management. To make soil management sustainable, we need to establish a scientific knowledge base of complex soil system processes that allows for developing models and tools to quantitatively predict the impact of a multitude of management measures on soil functions. This will finally allow for the provision of options for a site-specific, sustainable soil management. To face this challenge, the German Federal Ministry of Education and Research (BMBF) recently launched the funding program "Soil as a Sustainable Resource for the Bioeconomy - BonaRes". In a joint effort, ten collaborative projects and the coordinating BonaRes Centre are engaged to close existing knowledge gaps for a profound and systemic assessment and understanding of soil functions and their sensitivity to soil management. In BonaRes, the complete process chain of sustainable soil use in the context of a sustainable bio-economy is being addressed: from understanding of soil processes using state-of the art and novel measurement and modelling techniques towards soil functions and ecosystem services driving the development of assessment and decision support tools for a sustainable soil management. To this end, soil scientists and researchers from several other disciplines including social sciences are collaborating closely. Besides a better understanding of fundamental soil processes from each of the collaborative projects and the development of novel measurement techniques and models, the outcome of the joint BonaRes programme will be a web-based portal (www.bonares.de) providing information, knowledge, models, a data repository with doi-referenced, internationally available, open soil data from the BonaRes funding initiative and beyond, as well as decision support options for a sustainable soil management. This presentation will provide an overview about the BonaRes funding initiative and the research conducted therein.

Investigating Urban Eighth-Grade Students' Knowledge of Energy Resources

ERIC Educational Resources Information Center

Bodzin, Alec

2012-01-01

This study investigated urban eighth-grade students' knowledge of energy resources and associated issues including energy acquisition, energy generation, storage and transport, and energy consumption and conservation. A 39 multiple-choice-item energy resources knowledge assessment was completed by 1043 eighth-grade students in urban schools in two…

D and D Knowledge Management Information Tool - 2012 - 12106

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

Upadhyay, H.; Lagos, L.; Quintero, W.

2012-07-01

Deactivation and decommissioning (D and D) work is a high priority activity across the Department of Energy (DOE) complex. Subject matter specialists (SMS) associated with the different ALARA (As-Low-As-Reasonably-Achievable) Centers, DOE sites, Energy Facility Contractors Group (EFCOG) and the D and D community have gained extensive knowledge and experience over the years in the cleanup of the legacy waste from the Manhattan Project. To prevent the D and D knowledge and expertise from being lost over time from the evolving and aging workforce, DOE and the Applied Research Center (ARC) at Florida International University (FIU) proposed to capture and maintainmore » this valuable information in a universally available and easily usable system. D and D KM-IT provides single point access to all D and D related activities through its knowledge base. It is a community driven system. D and D KM-IT makes D and D knowledge available to the people who need it at the time they need it and in a readily usable format. It uses the World Wide Web as the primary source for content in addition to information collected from subject matter specialists and the D and D community. It brings information in real time through web based custom search processes and its dynamic knowledge repository. Future developments include developing a document library, providing D and D information access on mobile devices for the Technology module and Hotline, and coordinating multiple subject matter specialists to support the Hotline. The goal is to deploy a high-end sophisticated and secured system to serve as a single large knowledge base for all the D and D activities. The system consolidates a large amount of information available on the web and presents it to users in the simplest way possible. (authors)« less

A prototype system for perinatal knowledge engineering using an artificial intelligence tool.

PubMed

Sokol, R J; Chik, L

1988-01-01

Though several perinatal expert systems are extant, the use of artificial intelligence has, as yet, had minimal impact in medical computing. In this evaluation of the potential of AI techniques in the development of a computer based "Perinatal Consultant," a "top down" approach to the development of a perinatal knowledge base was taken, using as a source for such a knowledge base a 30-page manuscript of a chapter concerning high risk pregnancy. The UNIX utility "style" was used to parse sentences and obtain key words and phrases, both as part of a natural language interface and to identify key perinatal concepts. Compared with the "gold standard" of sentences containing key facts as chosen by the experts, a semiautomated method using a nonmedical speller to identify key words and phrases in context functioned with a sensitivity of 79%, i.e., approximately 8 in 10 key sentences were detected as the basis for PROLOG, rules and facts for the knowledge base. These encouraging results suggest that functional perinatal expert systems may well be expedited by using programming utilities in conjunction with AI tools and published literature.

What Happens to the Food We Eat? Children's Conceptions of the Structure and Function of the Digestive System.

ERIC Educational Resources Information Center

Teixeira, Francimar Martins

2000-01-01

Describes children's conceptions of the structure and function of the human digestive system based on an investigation carried out with children aged 4-10 (n=45). Finds that children possess biological knowledge as an independent knowledge domain from the age of four. Discusses acquisition of and barriers to scientific concepts related to human…

The Fully-Functioning University and Its Contribution to the Advancement of Knowledge

ERIC Educational Resources Information Center

Bourner, Tom; Rospigliosi, Asher; Heath, Linda

2016-01-01

The aim of this paper is to explore the implications of the concept of a "fully-functioning university" for its contribution to the advancement of knowledge. The paper therefore starts by reviewing that concept and the tripartite mission on which it is based. The main question that the paper seeks to answer is, "what kinds of…

How Toddlers Acquire and Transfer Tool Knowledge: Developmental Changes and the Role of Executive Functions

ERIC Educational Resources Information Center

Pauen, Sabina; Bechtel-Kuehne, Sabrina

2016-01-01

This report investigates tool learning and its relations to executive functions (EFs) in toddlers. In Study 1 (N = 93), 18-, 20-, 22-, and 24-month-old children learned equally well to choose a correct tool from observation, whereas performance based on feedback improved with age. Knowledge transfer showed significant progress after 22 months of…

Integration of Component Knowledge in Penalized-Likelihood Reconstruction with Morphological and Spectral Uncertainties.

PubMed

Stayman, J Webster; Tilley, Steven; Siewerdsen, Jeffrey H

2014-01-01

Previous investigations [1-3] have demonstrated that integrating specific knowledge of the structure and composition of components like surgical implants, devices, and tools into a model-based reconstruction framework can improve image quality and allow for potential exposure reductions in CT. Using device knowledge in practice is complicated by uncertainties in the exact shape of components and their particular material composition. Such unknowns in the morphology and attenuation properties lead to errors in the forward model that limit the utility of component integration. In this work, a methodology is presented to accommodate both uncertainties in shape as well as unknown energy-dependent attenuation properties of the surgical devices. This work leverages the so-called known-component reconstruction (KCR) framework [1] with a generalized deformable registration operator and modifications to accommodate a spectral transfer function in the component model. Moreover, since this framework decomposes the object into separate background anatomy and "known" component factors, a mixed fidelity forward model can be adopted so that measurements associated with projections through the surgical devices can be modeled with much greater accuracy. A deformable KCR (dKCR) approach using the mixed fidelity model is introduced and applied to a flexible wire component with unknown structure and composition. Image quality advantages of dKCR over traditional reconstruction methods are illustrated in cone-beam CT (CBCT) data acquired on a testbench emulating a 3D-guided needle biopsy procedure - i.e., a deformable component (needle) with strong energy-dependent attenuation characteristics (steel) within a complex soft-tissue background.

NMRe: a web server for NMR protein structure refinement with high-quality structure validation scores.

PubMed

Ryu, Hyojung; Lim, GyuTae; Sung, Bong Hyun; Lee, Jinhyuk

2016-02-15

Protein structure refinement is a necessary step for the study of protein function. In particular, some nuclear magnetic resonance (NMR) structures are of lower quality than X-ray crystallographic structures. Here, we present NMRe, a web-based server for NMR structure refinement. The previously developed knowledge-based energy function STAP (Statistical Torsion Angle Potential) was used for NMRe refinement. With STAP, NMRe provides two refinement protocols using two types of distance restraints. If a user provides NOE (Nuclear Overhauser Effect) data, the refinement is performed with the NOE distance restraints as a conventional NMR structure refinement. Additionally, NMRe generates NOE-like distance restraints based on the inter-hydrogen distances derived from the input structure. The efficiency of NMRe refinement was validated on 20 NMR structures. Most of the quality assessment scores of the refined NMR structures were better than those of the original structures. The refinement results are provided as a three-dimensional structure view, a secondary structure scheme, and numerical and graphical structure validation scores. NMRe is available at http://psb.kobic.re.kr/nmre/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Functional equivalency inferred from "authoritative sources" in networks of homologous proteins.

PubMed

Natarajan, Shreedhar; Jakobsson, Eric

2009-06-12

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods.

Functional Equivalency Inferred from “Authoritative Sources” in Networks of Homologous Proteins

PubMed Central

Natarajan, Shreedhar; Jakobsson, Eric

2009-01-01

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods. PMID:19521530

Economics of internal and external energy storage in solar power plant operation

NASA Technical Reports Server (NTRS)

Manvi, R.; Fujita, T.

1977-01-01

A simple approach is formulated to investigate the effect of energy storage on the bus-bar electrical energy cost of solar thermal power plants. Economic analysis based on this approach does not require detailed definition of a specific storage system. A wide spectrum of storage system candidates ranging from hot water to superconducting magnets can be studied based on total investment and a rough knowledge of energy in and out efficiencies. Preliminary analysis indicates that internal energy storage (thermal) schemes offer better opportunities for energy cost reduction than external energy storage (nonthermal) schemes for solar applications. Based on data and assumptions used in JPL evaluation studies, differential energy costs due to storage are presented for a 100 MWe solar power plant by varying the energy capacity. The simple approach presented in this paper provides useful insight regarding the operation of energy storage in solar power plant applications, while also indicating a range of design parameters where storage can be cost effective.

Nontrivial thermodynamics in 't Hooft's large-N limit

NASA Astrophysics Data System (ADS)

Cubero, Axel Cortés

2015-05-01

We study the finite volume/temperature correlation functions of the (1 +1 )-dimensional SU (N ) principal chiral sigma model in the planar limit. The exact S-matrix of the sigma model is known to simplify drastically at large N , and this leads to trivial thermodynamic Bethe ansatz (TBA) equations. The partition function, if derived using the TBA, can be shown to be that of free particles. We show that the correlation functions and expectation values of operators at finite volume/temperature are not those of the free theory, and that the TBA does not give enough information to calculate them. Our analysis is done using the Leclair-Mussardo formula for finite-volume correlators, and knowledge of the exact infinite-volume form factors. We present analytical results for the one-point function of the energy-momentum tensor, and the two-point function of the renormalized field operator. The results for the energy-momentum tensor can be used to define a nontrivial partition function.

Standards for hospital libraries 2002

PubMed Central

Gluck, Jeannine Cyr; Hassig, Robin Ackley; Balogh, Leeni; Bandy, Margaret; Doyle, Jacqueline Donaldson; Kronenfeld, Michael R.; Lindner, Katherine Lois; Murray, Kathleen; Petersen, JoAn; Rand, Debra C.

2002-01-01

The Medical Library Association's “Standards for Hospital Libraries 2002” have been developed as a guide for hospital administrators, librarians, and accrediting bodies to ensure that hospitals have the resources and services to effectively meet their needs for knowledge-based information. Specific requirements for knowledge-based information include that the library be a separate department with its own budget. Knowledge-based information in the library should be directed by a qualified librarian who functions as a department head and is a member of the Academy of Health Information Professionals. The standards define the role of the medical librarian and the links between knowledge-based information and other functions such as patient care, patient education, performance improvement, and education. In addition, the standards address the development and implementation of the knowledge-based information needs assessment and plans, the promotion and publicity of the knowledge-based information services, and the physical space and staffing requirements. The role, qualifications, and functions of a hospital library consultant are outlined. The health sciences library is positioned to play a key role in the hospital. The increasing use of the Internet and new information technologies by medical, nursing, and allied health staffs; patients; and the community require new strategies, strategic planning, allocation of adequate resources, and selection and evaluation of appropriate information resources and technologies. The Hospital Library Standards Committee has developed this document as a guideline to be used in facing these challenges. Editor's Note: The “Standards for Hospital Libraries 2002” were approved by the members of the Hospital Library Section during MLA '02 in Dallas, Texas. They were subsequently approved by Section Council and received final approval from the MLA Board of Directors in June 2002. They succeed the Standards for Hospital Libraries published in 1994 and the Minimum Standards for Health Sciences Libraries in Hospitals from 1983. A Frequently Asked Questions document discussing the development of the new standards can be found on the Hospital Library Section Website at http://www.hls.mlanet.org. PMID:12398254

Geant4 Predictions of Energy Spectra in Typical Space Radiation Environment

NASA Technical Reports Server (NTRS)

Sabra, M. S.; Barghouty, A. F.

2014-01-01

Accurate knowledge of energy spectra inside spacecraft is important for protecting astronauts as well as sensitive electronics from the harmful effects of space radiation. Such knowledge allows one to confidently map the radiation environment inside the vehicle. The purpose of this talk is to present preliminary calculations for energy spectra inside a spherical shell shielding and behind a slab in typical space radiation environment using the 3D Monte-Carlo transport code Geant4. We have simulated proton and iron isotropic sources and beams impinging on Aluminum and Gallium arsenide (GaAs) targets at energies of 0.2, 0.6, 1, and 10 GeV/u. If time permits, other radiation sources and beams (_, C, O) and targets (C, Si, Ge, water) will be presented. The results are compared to ground-based measurements where available.

Fuzzy Linguistic Knowledge Based Behavior Extraction for Building Energy Management Systems

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

Dumidu Wijayasekara; Milos Manic

2013-08-01

Significant portion of world energy production is consumed by building Heating, Ventilation and Air Conditioning (HVAC) units. Thus along with occupant comfort, energy efficiency is also an important factor in HVAC control. Modern buildings use advanced Multiple Input Multiple Output (MIMO) control schemes to realize these goals. However, since the performance of HVAC units is dependent on many criteria including uncertainties in weather, number of occupants, and thermal state, the performance of current state of the art systems are sub-optimal. Furthermore, because of the large number of sensors in buildings, and the high frequency of data collection, large amount ofmore » information is available. Therefore, important behavior of buildings that compromise energy efficiency or occupant comfort is difficult to identify. This paper presents an easy to use and understandable framework for identifying such behavior. The presented framework uses human understandable knowledge-base to extract important behavior of buildings and present it to users via a graphical user interface. The presented framework was tested on a building in the Pacific Northwest and was shown to be able to identify important behavior that relates to energy efficiency and occupant comfort.« less

Determination of structure and properties of molecular crystals from first principles.

PubMed

Szalewicz, Krzysztof

2014-11-18

CONSPECTUS: Until recently, it had been impossible to predict structures of molecular crystals just from the knowledge of the chemical formula for the constituent molecule(s). A solution of this problem has been achieved using intermolecular force fields computed from first principles. These fields were developed by calculating interaction energies of molecular dimers and trimers using an ab initio method called symmetry-adapted perturbation theory (SAPT) based on density-functional theory (DFT) description of monomers [SAPT(DFT)]. For clusters containing up to a dozen or so atoms, interaction energies computed using SAPT(DFT) are comparable in accuracy to the results of the best wave function-based methods, whereas the former approach can be applied to systems an order of magnitude larger than the latter. In fact, for monomers with a couple dozen atoms, SAPT(DFT) is about equally time-consuming as the supermolecular DFT approach. To develop a force field, SAPT(DFT) calculations are performed for a large number of dimer and possibly also trimer configurations (grid points in intermolecular coordinates), and the interaction energies are then fitted by analytic functions. The resulting force fields can be used to determine crystal structures and properties by applying them in molecular packing, lattice energy minimization, and molecular dynamics calculations. In this way, some of the first successful determinations of crystal structures were achieved from first principles, with crystal densities and lattice parameters agreeing with experimental values to within about 1%. Crystal properties obtained using similar procedures but empirical force fields fitted to crystal data have typical errors of several percent due to low sensitivity of empirical fits to interactions beyond those of the nearest neighbors. The first-principles approach has additional advantages over the empirical approach for notional crystals and cocrystals since empirical force fields can only be extrapolated to such cases. As an alternative to applying SAPT(DFT) in crystal structure calculations, one can use supermolecular DFT interaction energies combined with scaled dispersion energies computed from simple atom-atom functions, that is, use the so-called DFT+D approach. Whereas the standard DFT methods fail for intermolecular interactions, DFT+D performs reasonably well since the dispersion correction is used not only to provide the missing dispersion contribution but also to fix other deficiencies of DFT. The latter cancellation of errors is unphysical and can be avoided by applying the so-called dispersionless density functional, dlDF. In this case, the dispersion energies are added without any scaling. The dlDF+D method is also one of the best performing DFT+D methods. The SAPT(DFT)-based approach has been applied so far only to crystals with rigid monomers. It can be extended to partly flexible monomers, that is, to monomers with only a few internal coordinates allowed to vary. However, the costs will increase relative to rigid monomer cases since the number of grid points increases exponentially with the number of dimensions. One way around this problem is to construct force fields with approximate couplings between inter- and intramonomer degrees of freedom. Another way is to calculate interaction energies (and possibly forces) "on the fly", i.e., in each step of lattice energy minimization procedure. Such an approach would be prohibitively expensive if it replaced analytic force fields at all stages of the crystal predictions procedure, but it can be used to optimize a few dozen candidate structures determined by other methods.

From free energy to expected energy: Improving energy-based value function approximation in reinforcement learning.

PubMed

Elfwing, Stefan; Uchibe, Eiji; Doya, Kenji

2016-12-01

Free-energy based reinforcement learning (FERL) was proposed for learning in high-dimensional state and action spaces. However, the FERL method does only really work well with binary, or close to binary, state input, where the number of active states is fewer than the number of non-active states. In the FERL method, the value function is approximated by the negative free energy of a restricted Boltzmann machine (RBM). In our earlier study, we demonstrated that the performance and the robustness of the FERL method can be improved by scaling the free energy by a constant that is related to the size of network. In this study, we propose that RBM function approximation can be further improved by approximating the value function by the negative expected energy (EERL), instead of the negative free energy, as well as being able to handle continuous state input. We validate our proposed method by demonstrating that EERL: (1) outperforms FERL, as well as standard neural network and linear function approximation, for three versions of a gridworld task with high-dimensional image state input; (2) achieves new state-of-the-art results in stochastic SZ-Tetris in both model-free and model-based learning settings; and (3) significantly outperforms FERL and standard neural network function approximation for a robot navigation task with raw and noisy RGB images as state input and a large number of actions. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm.

PubMed

Tian, Ye; Huang, Xiaoqiang; Zhu, Yushan

2015-08-01

Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.

Stacked-unstacked equilibrium at the nick site of DNA.

PubMed

Protozanova, Ekaterina; Yakovchuk, Peter; Frank-Kamenetskii, Maxim D

2004-09-17

Stability of duplex DNA with respect to separation of complementary strands is crucial for DNA executing its major functions in the cell and it also plays a central role in major biotechnology applications of DNA: DNA sequencing, polymerase chain reaction, and DNA microarrays. Two types of interaction are well known to contribute to DNA stability: stacking between adjacent base-pairs and pairing between complementary bases. However, their contribution into the duplex stability is yet to be determined. Now we fill this fundamental gap in our knowledge of the DNA double helix. We have prepared a series of 32, 300 bp-long DNA fragments with solitary nicks in the same position differing only in base-pairs flanking the nick. Electrophoretic mobility of these fragments in the gel has been studied. Assuming the equilibrium between stacked and unstacked conformations at the nick site, all 32 stacking free energy parameters have been obtained. Only ten of them are essential and they govern the stacking interactions between adjacent base-pairs in intact DNA double helix. A full set of DNA stacking parameters has been determined for the first time. From these data and from a well-known dependence of DNA melting temperature on G.C content, the contribution of base-pairing into duplex stability has been estimated. The obtained energy parameters of the DNA double helix are of paramount importance for understanding sequence-dependent DNA flexibility and for numerous biotechnology applications.

An expert system shell for inferring vegetation characteristics: Interface for the addition of techniques (Task H)

NASA Technical Reports Server (NTRS)

Harrison, P. Ann

1993-01-01

All the NASA VEGetation Workbench (VEG) goals except the Learning System provide the scientist with several different techniques. When VEG is run, rules assist the scientist in selecting the best of the available techniques to apply to the sample of cover type data being studied. The techniques are stored in the VEG knowledge base. The design and implementation of an interface that allows the scientist to add new techniques to VEG without assistance from the developer were completed. A new interface that enables the scientist to add techniques to VEG without assistance from the developer was designed and implemented. This interface does not require the scientist to have a thorough knowledge of Knowledge Engineering Environment (KEE) by Intellicorp or a detailed knowledge of the structure of VEG. The interface prompts the scientist to enter the required information about the new technique. It prompts the scientist to enter the required Common Lisp functions for executing the technique and the left hand side of the rule that causes the technique to be selected. A template for each function and rule and detailed instructions about the arguments of the functions, the values they should return, and the format of the rule are displayed. Checks are made to ensure that the required data were entered, the functions compiled correctly, and the rule parsed correctly before the new technique is stored. The additional techniques are stored separately from the VEG knowledge base. When the VEG knowledge base is loaded, the additional techniques are not normally loaded. The interface allows the scientist the option of adding all the previously defined new techniques before running VEG. When the techniques are added, the required units to store the additional techniques are created automatically in the correct places in the VEG knowledge base. The methods file containing the functions required by the additional techniques is loaded. New rule units are created to store the new rules. The interface that allow the scientist to select which techniques to use is updated automatically to include the new techniques. Task H was completed. The interface that allows the scientist to add techniques to VEG was implemented and comprehensively tested. The Common Lisp code for the Add Techniques system is listed in Appendix A.

PDA: A coupling of knowledge and memory for case-based reasoning

NASA Technical Reports Server (NTRS)

Bharwani, S.; Walls, J.; Blevins, E.

1988-01-01

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

Turning over a new leaf in lipid droplet biology

USDA-ARS?s Scientific Manuscript database

Lipid droplets (LDs) in plants have long been viewed as storage depots for neutral lipids that serve as energy sources or precursors for membrane biosynthesis. While much of our knowledge of LD function in plants comes from studies of oilseeds, a recent surge in research of LDs in non-seed tissues h...

Orienting the Work-Based Curriculum Towards Work Process Knowledge: A Rationale and a German Case Study

ERIC Educational Resources Information Center

Boreham, Nick

2004-01-01

The term 'work process knowledge' refers to the knowledge needed for working in flexible and innovative business environments, including those in which information and communication technologies have been introduced to integrate previously separated production functions. It involves a systems-level understanding of the work process in the…

PVDaCS - A prototype knowledge-based expert system for certification of spacecraft data

NASA Technical Reports Server (NTRS)

Wharton, Cathleen; Shiroma, Patricia J.; Simmons, Karen E.

1989-01-01

On-line data management techniques to certify spacecraft information are mandated by increasing telemetry rates. Knowledge-based expert systems offer the ability to certify data electronically without the need for time-consuming human interaction. Issues of automatic certification are explored by designing a knowledge-based expert system to certify data from a scientific instrument, the Orbiter Ultraviolet Spectrometer, on an operating NASA planetary spacecraft, Pioneer Venus. The resulting rule-based system, called PVDaCS (Pioneer Venus Data Certification System), is a functional prototype demonstrating the concepts of a larger system design. A key element of the system design is the representation of an expert's knowledge through the usage of well ordered sequences. PVDaCS produces a certification value derived from expert knowledge and an analysis of the instrument's operation. Results of system performance are presented.

Figure-ground segmentation based on class-independent shape priors

NASA Astrophysics Data System (ADS)

Li, Yang; Liu, Yang; Liu, Guojun; Guo, Maozu

2018-01-01

We propose a method to generate figure-ground segmentation by incorporating shape priors into the graph-cuts algorithm. Given an image, we first obtain a linear representation of an image and then apply directional chamfer matching to generate class-independent, nonparametric shape priors, which provide shape clues for the graph-cuts algorithm. We then enforce shape priors in a graph-cuts energy function to produce object segmentation. In contrast to previous segmentation methods, the proposed method shares shape knowledge for different semantic classes and does not require class-specific model training. Therefore, the approach obtains high-quality segmentation for objects. We experimentally validate that the proposed method outperforms previous approaches using the challenging PASCAL VOC 2010/2012 and Berkeley (BSD300) segmentation datasets.

Integrating knowledge and control into hypermedia-based training environments: Experiments with HyperCLIPS

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.

1990-01-01

The issues of knowledge representation and control in hypermedia-based training environments are discussed. The main objective is to integrate the flexible presentation capability of hypermedia with a knowledge-based approach to lesson discourse management. The instructional goals and their associated concepts are represented in a knowledge representation structure called a 'concept network'. Its functional usages are many: it is used to control the navigation through a presentation space, generate tests for student evaluation, and model the student. This architecture was implemented in HyperCLIPS, a hybrid system that creates a bridge between HyperCard, a popular hypertext-like system used for building user interfaces to data bases and other applications, and CLIPS, a highly portable government-owned expert system shell.

European transition to a low carbon electricity system using a mix of variable renewable energies: carbon saving trajectories as functions of production and storage capacity.

NASA Astrophysics Data System (ADS)

Francois, Baptiste; Creutin, Jean-Dominique

2016-04-01

Today, most of the produced energy is generated from fossil energy sources (i.e. coal, petroleum). As a result, the energy sector is still the main source of greenhouse gas in the atmosphere. For limiting greenhouse gas emission, a transition from fossil to renewable energy is required, increasing gradually the fraction energy coming from variable renewable energy (i.e. solar power, wind power and run-of-the river hydropower, hereafter denoted as VRE). VRE penetration, i.e. the percentage of demand satisfied by variable renewables assuming no storage capacity, is hampered by their variable and un-controllable features. Many studies show that combining different VRE over space smoothes their variability and increases their global penetration by a better match of demand fluctuations. When the demand is not fully supplied by the VRE generation, backup generation is required from stored energy (mostly from dams) or fossil sources, the latter being associated with high greenhouse gas emission. Thus the VRE penetration is a direct indicator of carbon savings and basically depends on the VRE installed capacity, its mix features, and on the installed storage capacity. In this study we analyze the European transition to a low carbon electricity system. Over a selection of representative regions we analyze carbon saving trajectories as functions of VRE production and storage capacities for different scenarios mixing one to three VRE with non-renewables. We show substantial differences between trajectories when the mix of sources is far from the local optimums, when the storage capacity evolves. We bring new elements of reflection about the effect of transport grid features from local independent systems to a European "copper plate". This work is part of the FP7 project COMPLEX (Knowledge based climate mitigation systems for a low carbon economy; Project FP7-ENV-2012 number: 308601; http://www.complex.ac.uk/).

Inhomogeneity induced and appropriately parameterized semilocal exchange and correlation energy functionals in two-dimensions.

PubMed

Patra, Abhilash; Jana, Subrata; Samal, Prasanjit

2018-04-07

The construction of meta generalized gradient approximations based on the density matrix expansion (DME) is considered as one of the most accurate techniques to design semilocal exchange energy functionals in two-dimensional density functional formalism. The exchange holes modeled using DME possess unique features that make it a superior entity. Parameterized semilocal exchange energy functionals based on the DME are proposed. The use of different forms of the momentum and flexible parameters is to subsume the non-uniform effects of the density in the newly constructed semilocal functionals. In addition to the exchange functionals, a suitable correlation functional is also constructed by working upon the local correlation functional developed for 2D homogeneous electron gas. The non-local effects are induced into the correlation functional by a parametric form of one of the newly constructed exchange energy functionals. The proposed functionals are applied to the parabolic quantum dots with a varying number of confined electrons and the confinement strength. The results obtained with the aforementioned functionals are quite satisfactory, which indicates why these are suitable for two-dimensional quantum systems.

Inhomogeneity induced and appropriately parameterized semilocal exchange and correlation energy functionals in two-dimensions

NASA Astrophysics Data System (ADS)

Patra, Abhilash; Jana, Subrata; Samal, Prasanjit

2018-04-01

The construction of meta generalized gradient approximations based on the density matrix expansion (DME) is considered as one of the most accurate techniques to design semilocal exchange energy functionals in two-dimensional density functional formalism. The exchange holes modeled using DME possess unique features that make it a superior entity. Parameterized semilocal exchange energy functionals based on the DME are proposed. The use of different forms of the momentum and flexible parameters is to subsume the non-uniform effects of the density in the newly constructed semilocal functionals. In addition to the exchange functionals, a suitable correlation functional is also constructed by working upon the local correlation functional developed for 2D homogeneous electron gas. The non-local effects are induced into the correlation functional by a parametric form of one of the newly constructed exchange energy functionals. The proposed functionals are applied to the parabolic quantum dots with a varying number of confined electrons and the confinement strength. The results obtained with the aforementioned functionals are quite satisfactory, which indicates why these are suitable for two-dimensional quantum systems.

HRM in the Knowledge-based Economy: Is There an Afterlife?

ERIC Educational Resources Information Center

Raich, Mario

2002-01-01

Explains changes in the workplace attributed to the knowledge economy and poses questions for businesses, workers, and the human resources function. Outlines new expectations of and a new framework for human resource management. (SK)

Structure refinement of membrane proteins via molecular dynamics simulations.

PubMed

Dutagaci, Bercem; Heo, Lim; Feig, Michael

2018-07-01

A refinement protocol based on physics-based techniques established for water soluble proteins is tested for membrane protein structures. Initial structures were generated by homology modeling and sampled via molecular dynamics simulations in explicit lipid bilayer and aqueous solvent systems. Snapshots from the simulations were selected based on scoring with either knowledge-based or implicit membrane-based scoring functions and averaged to obtain refined models. The protocol resulted in consistent and significant refinement of the membrane protein structures similar to the performance of refinement methods for soluble proteins. Refinement success was similar between sampling in the presence of lipid bilayers and aqueous solvent but the presence of lipid bilayers may benefit the improvement of lipid-facing residues. Scoring with knowledge-based functions (DFIRE and RWplus) was found to be as good as scoring using implicit membrane-based scoring functions suggesting that differences in internal packing is more important than orientations relative to the membrane during the refinement of membrane protein homology models. © 2018 Wiley Periodicals, Inc.

A density difference based analysis of orbital-dependent exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Grabowski, Ireneusz; Teale, Andrew M.; Fabiano, Eduardo; Śmiga, Szymon; Buksztel, Adam; Della Sala, Fabio

2014-03-01

We present a density difference based analysis for a range of orbital-dependent Kohn-Sham functionals. Results for atoms, some members of the neon isoelectronic series and small molecules are reported and compared with ab initio wave function calculations. Particular attention is paid to the quality of approximations to the exchange-only optimised effective potential (OEP) approach: we consider both the localised Hartree-Fock as well as the Krieger-Li-Iafrate methods. Analysis of density differences at the exchange-only level reveals the impact of the approximations on the resulting electronic densities. These differences are further quantified in terms of the ground state energies, frontier orbital energy differences and highest occupied orbital energies obtained. At the correlated level, an OEP approach based on a perturbative second-order correlation energy expression is shown to deliver results comparable with those from traditional wave function approaches, making it suitable for use as a benchmark against which to compare standard density functional approximations.

An Energy-Based Limit State Function for Estimation of Structural Reliability in Shock Environments

DOE PAGES

Guthrie, Michael A.

2013-01-01

limit state function is developed for the estimation of structural reliability in shock environments. This limit state function uses peak modal strain energies to characterize environmental severity and modal strain energies at failure to characterize the structural capacity. The Hasofer-Lind reliability index is briefly reviewed and its computation for the energy-based limit state function is discussed. Applications to two degree of freedom mass-spring systems and to a simple finite element model are considered. For these examples, computation of the reliability index requires little effort beyond a modal analysis, but still accounts for relevant uncertainties in both the structure and environment.more » For both examples, the reliability index is observed to agree well with the results of Monte Carlo analysis. In situations where fast, qualitative comparison of several candidate designs is required, the reliability index based on the proposed limit state function provides an attractive metric which can be used to compare and control reliability.« less

D and D knowledge management information tool - a web based system developed to share D and D knowledge worldwide

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

Lagos, L.; Upadhyay, H.; Shoffner, P.

2013-07-01

Deactivation and decommissioning (D and D) work is a high risk and technically challenging enterprise within the U.S. Department of Energy complex. During the past three decades, the DOE's Office of Environmental Management has been in charge of carrying out one of the largest environmental restoration efforts in the world: the cleanup of the Manhattan Project legacy. In today's corporate world, worker experiences and knowledge that have developed over time represent a valuable corporate asset. The ever-dynamic workplace, coupled with an aging workforce, presents corporations with the ongoing challenge of preserving work-related experiences and knowledge for cross-generational knowledge transfer tomore » the future workforce [5]. To prevent the D and D knowledge base and expertise from being lost over time, the DOE and the Applied Research Center at Florida International University (FIU) have developed the web-based Knowledge Management Information Tool (KM-IT) to capture and maintain this valuable information in a universally available and easily accessible and usable system. The D and D KM-IT was developed in collaboration with DOE Headquarters (HQ), the Energy Facility Contractors Group (EFCOG), and the ALARA [as low as reasonably achievable] Centers at Savannah River Sites to preserve the D and D information generated and collected by the D and D community. This is an open secured system that can be accessed from https://www.dndkm.org over the web and through mobile devices at https://m.dndkm.org. This knowledge system serves as a centralized repository and provides a common interface for D and D-related activities. It also improves efficiency by reducing the need to rediscover knowledge and promotes the reuse of existing knowledge. It is a community-driven system that facilitates the gathering, analyzing, storing, and sharing of knowledge and information within the D and D community. It assists the DOE D and D community in identifying potential solutions to their problem areas by using the vast resources and knowledge base available throughout the global D and D community. The D and D KM-IT offers a mechanism to the global D and D community for searching relevant D and D information and is focused on providing a single point of access into the collective knowledge base of the D and D community within and outside of the DOE. Collecting information from subject matter specialists, it builds a knowledge repository for future reference archiving Lessons Learned, Best Practices, ALARA reports, and other relevant documents and maintains a secured collaboration platform for the global D and D community to share knowledge. With the dynamic nature and evolution of the D and D knowledge base due to multiple factors such as changes in the workforce, new technologies and methodologies, economics, and regulations, the D and D KM-IT is being developed in a phased and modular fashion. (authors)« less

Nanomaterials derived from metal-organic frameworks

NASA Astrophysics Data System (ADS)

Dang, Song; Zhu, Qi-Long; Xu, Qiang

2018-01-01

The thermal transformation of metal-organic frameworks (MOFs) generates a variety of nanostructured materials, including carbon-based materials, metal oxides, metal chalcogenides, metal phosphides and metal carbides. These derivatives of MOFs have characteristics such as high surface areas, permanent porosities and controllable functionalities that enable their good performance in sensing, gas storage, catalysis and energy-related applications. Although progress has been made to tune the morphologies of MOF-derived structures at the nanometre scale, it remains crucial to further our knowledge of the relationship between morphology and performance. In this Review, we summarize the synthetic strategies and optimized methods that enable control over the size, morphology, composition and structure of the derived nanomaterials. In addition, we compare the performance of materials prepared by the MOF-templated strategy and other synthetic methods. Our aim is to reveal the relationship between the morphology and the physico-chemical properties of MOF-derived nanostructures to optimize their performance for applications such as sensing, catalysis, and energy storage and conversion.

A first-principles study of He, Xe, Kr and O incorporation in thorium carbide

NASA Astrophysics Data System (ADS)

Pérez Daroca, D.; Llois, A. M.; Mosca, H. O.

2015-05-01

Thorium-based materials are currently being investigated in relation with their potential utilization in Generation-IV reactors as nuclear fuels. Understanding the incorporation of fission products and oxygen is very important to predict the behavior of nuclear fuels. A first approach to this goal is the study of the incorporation energies and stability of these elements in the material. By means of first-principles calculations within the framework of density functional theory, we calculate the incorporation energies of He, Xe, Kr and O atoms in Th and C vacancy sites, in tetrahedral interstitials and in Schottky defects along the 〈1 1 1〉 and 〈1 0 0〉 directions. We also analyze atomic displacements, volume modifications and Bader charges. This kind of results for ThC, to the best authors' knowledge, have not been obtained previously, neither experimentally, nor theoretically. This should deal as a starting point towards the study of the complex behavior of fission products in irradiated ThC.

Energy requirements in preschool-age children with cerebral palsy.

PubMed

Walker, Jacqueline L; Bell, Kristie L; Boyd, Roslyn N; Davies, Peter S W

2012-12-01

There is a paucity of data concerning the energy requirements (ERs) of preschool-age children with cerebral palsy (CP), the knowledge of which is essential for early nutritional management. We aimed to determine the ERs for preschool-age children with CP in relation to functional ability, motor type, and distribution and compared with typically developing children (TDC) and published estimation equations. Thirty-two children with CP (63% male) of all functional abilities, motor types, and distributions and 16 TDC (63% male) aged 2.9-4.4 y participated in this study. The doubly labeled water method was used to determine ERs. Statistical analyses were conducted by 1-factor ANOVA and post hoc Tukey honestly significant difference tests, independent and paired t tests, Bland and Altman analyses, correlations, and multivariable regressions. As a population, children with CP had significantly lower ERs than did TDC (P < 0.05). No significant difference in ERs was found between ambulant children and TDC. Marginally ambulant and nonambulant children had ERs that were ∼18% lower than those of ambulant children and 31% lower than those of TDC. A trend toward lower ERs with greater numbers of limbs involved was observed. The influence of motor type could not be determined statistically. Published equations substantially underestimated ERs in the nonambulant children by ∼22%. In preschool-age children with CP, ERs decreased as ambulatory status declined and more limbs were involved. The greatest predictor of ERs was fat-free mass, then ambulatory status. Future research should build on the information presented to expand the knowledge base regarding ERs in children with CP. This trial was registered with the Australian New Zealand Clinical Trials Registry as ACTRN 12612000686808.

Interstellar Communication Channel Based on a Biological Universal

NASA Technical Reports Server (NTRS)

Weber, Arthur L.; DeVincenzi, Donald L. (Technical Monitor)

1999-01-01

Cellular biosynthesis starts with sugar substrates and continues energetically downhill to yield amino acid, rapid, and nucleotide products. To understand the energetics of these processes, we calculated the energy for biosynthesis from sugars of E. cali's amino acids, nucleotides, and lipids. We found that the biosynthesis of amino acids and lipids from sugar substrates proceeds by redox disproportionation. of sugar carbon with a favorable energy of about -11 kcal/mole of carbon. Overall, redox disproportion of sugar carbon accounted for 84% and 96% (ATP only 6% and 1%) of the total biosynthetic energy of amino acids and lipids (the major cellular constituents). Next, we calculated for all 48 possible 3-carbon substrates the energy of maximal disproportionation to carbon dioxide and methane. We found no other carbon substrates than matched sugars in biosynthetic energy, efficiency, and simplicity. From this, we concluded that sugars are the optimal biosynthetic substrate. Since this conclusion is based on universal properties of carbon chemistry, other carbon-based life throughout the Universe would also use optimal sugar substrates. Furthermore, this rather obvious universal role of sugars as the optimal biosubstrate would probably be common knowledge of technological civilizations throughout the Universe. Since the elemental building block of all sugars is formaldehyde, the common knowledge that sugars are the universal optimal biosubstrate could reasonably lead to the selection of a line(s) in the microwave spectrum of formaldehyde as a frequency for interstellar communication.

Knowledge management impact of information technology Web 2.0/3.0. The case study of agent software technology usability in knowledge management system

NASA Astrophysics Data System (ADS)

Sołtysik-Piorunkiewicz, Anna

2015-02-01

How we can measure the impact of internet technology Web 2.0/3.0 for knowledge management? How we can use the Web 2.0/3.0 technologies for generating, evaluating, sharing, organizing knowledge in knowledge-based organization? How we can evaluate it from user-centered perspective? Article aims to provide a method for evaluate the usability of web technologies to support knowledge management in knowledge-based organizations of the various stages of the cycle knowledge management, taking into account: generating knowledge, evaluating knowledge, sharing knowledge, etc. for the modern Internet technologies based on the example of agent technologies. The method focuses on five areas of evaluation: GUI, functional structure, the way of content publication, organizational aspect, technological aspect. The method is based on the proposed indicators relating respectively to assess specific areas of evaluation, taking into account the individual characteristics of the scoring. Each of the features identified in the evaluation is judged first point wise, then this score is subject to verification and clarification by means of appropriate indicators of a given feature. The article proposes appropriate indicators to measure the impact of Web 2.0/3.0 technologies for knowledge management and verification them in an example of agent technology usability in knowledge management system.

Energy-Based Tissue Fusion for Sutureless Closure: Applications, Mechanisms, and Potential for Functional Recovery.

PubMed

Kramer, Eric A; Rentschler, Mark E

2018-06-04

As minimally invasive surgical techniques progress, the demand for efficient, reliable methods for vascular ligation and tissue closure becomes pronounced. The surgical advantages of energy-based vessel sealing exceed those of traditional, compression-based ligatures in procedures sensitive to duration, foreign bodies, and recovery time alike. Although the use of energy-based devices to seal or transect vasculature and connective tissue bundles is widespread, the breadth of heating strategies and energy dosimetry used across devices underscores an uncertainty as to the molecular nature of the sealing mechanism and induced tissue effect. Furthermore, energy-based techniques exhibit promise for the closure and functional repair of soft and connective tissues in the nervous, enteral, and dermal tissue domains. A constitutive theory of molecular bonding forces that arise in response to supraphysiological temperatures is required in order to optimize and progress the use of energy-based tissue fusion. While rapid tissue bonding has been suggested to arise from dehydration, dipole interactions, molecular cross-links, or the coagulation of cellular proteins, long-term functional tissue repair across fusion boundaries requires that the reaction to thermal damage be tailored to catalyze the onset of biological healing and remodeling. In this review, we compile and contrast findings from published thermal fusion research in an effort to encourage a molecular approach to characterization of the prevalent and promising energy-based tissue bond.

A NEW QUANTUM MECHANICAL THEORY OF EVOLUTION OF UNIVERSE AND LIFE

PubMed Central

Nigam, M C

1990-01-01

Based upon the principles of ancient science of Life, which admits both consciousness and matter, a new Quantum Mechanical theory of evolution of universe and life is propounded. The theory advocates: Right from the time, the evolution of universe takes place, life also starts evolving energies and ethereal – consciousness (subtler and real) in anti-electrons, as the complimentary partners. The material body acquires electrons for cordoning of atomic nuclei and displaying its manifestation, in the three spatial dimensions in scale of time. The ethereal consciousness acquires anti electrons for gaining necessary energy for superimposing itself over any of the manifested bodies of equivalent electronic energy and deriving the bliss of materialization. The theory is based upon the solid foundation of the ancient science (ethereal consciousness) laid down by the ancient seekers of knowledge like Kapila and Caraka who interpret many of the riddles of modern science on the frontiers of various disciplines of knowledge. PMID:22556513

Translating the basic knowledge of mitochondrial functions to metabolic therapy: role of L-carnitine.

PubMed

Marcovina, Santica M; Sirtori, Cesare; Peracino, Andrea; Gheorghiade, Mihai; Borum, Peggy; Remuzzi, Giuseppe; Ardehali, Hossein

2013-02-01

Mitochondria play important roles in human physiological processes, and therefore, their dysfunction can lead to a constellation of metabolic and nonmetabolic abnormalities such as a defect in mitochondrial gene expression, imbalance in fuel and energy homeostasis, impairment in oxidative phosphorylation, enhancement of insulin resistance, and abnormalities in fatty acid metabolism. As a consequence, mitochondrial dysfunction contributes to the pathophysiology of insulin resistance, obesity, diabetes, vascular disease, and chronic heart failure. The increased knowledge on mitochondria and their role in cellular metabolism is providing new evidence that these disorders may benefit from mitochondrial-targeted therapies. We review the current knowledge of the contribution of mitochondrial dysfunction to chronic diseases, the outcomes of experimental studies on mitochondrial-targeted therapies, and explore the potential of metabolic modulators in the treatment of selected chronic conditions. As an example of such modulators, we evaluate the efficacy of the administration of L-carnitine and its analogues acetyl and propionyl L-carnitine in several chronic diseases. L-carnitine is intrinsically involved in mitochondrial metabolism and function as it plays a key role in fatty acid oxidation and energy metabolism. In addition to the transportation of free fatty acids across the inner mitochondrial membrane, L-carnitine modulates their oxidation rate and is involved in the regulation of vital cellular functions such as apoptosis. Thus, L-carnitine and its derivatives show promise in the treatment of chronic conditions and diseases associated with mitochondrial dysfunction but further translational studies are needed to fully explore their potential. Copyright © 2013 Mosby, Inc. All rights reserved.

Bile Acid Receptor Agonist GW4064 Regulates PPARγ Coactivator-1α Expression Through Estrogen Receptor-Related Receptor α

PubMed Central

Dwivedi, Shailendra Kumar Dhar; Singh, Nidhi; Kumari, Rashmi; Mishra, Jay Sharan; Tripathi, Sarita; Banerjee, Priyam; Shah, Priyanka; Kukshal, Vandana; Tyagi, Abdul Malik; Gaikwad, Anil Nilkanth; Chaturvedi, Rajnish Kumar; Mishra, Durga Prasad; Trivedi, Arun Kumar; Sanyal, Somali; Chattopadhyay, Naibedya; Ramachandran, Ravishankar; Siddiqi, Mohammad Imran; Bandyopadhyay, Arun; Arora, Ashish; Lundåsen, Thomas; Anakk, Sayee Priyadarshini; Moore, David D.

2011-01-01

Peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) is induced in energy-starved conditions and is a key regulator of energy homeostasis. This makes PGC-1α an attractive therapeutic target for metabolic syndrome and diabetes. In our effort to identify new regulators of PGC-1α expression, we found that GW4064, a widely used synthetic agonist for the nuclear bile acid receptor [farnesoid X receptor (FXR)] strongly enhances PGC-1α promoter reporter activity, mRNA, and protein expression. This induction in PGC-1α concomitantly enhances mitochondrial mass and expression of several PGC-1α target genes involved in mitochondrial function. Using FXR-rich or FXR-nonexpressing cell lines and tissues, we found that this effect of GW4064 is not mediated directly by FXR but occurs via activation of estrogen receptor-related receptor α (ERRα). Cell-based, biochemical and biophysical assays indicate GW4064 as an agonist of ERR proteins. Interestingly, FXR disruption alters GW4064 induction of PGC-1α mRNA in a tissue-dependent manner. Using FXR-null [FXR knockout (FXRKO)] mice, we determined that GW4064 induction of PGC-1α expression is not affected in oxidative soleus muscles of FXRKO mice but is compromised in the FXRKO liver. Mechanistic studies to explain these differences revealed that FXR physically interacts with ERR and protects them from repression by the atypical corepressor, small heterodimer partner in liver. Together, this interplay between ERRα-FXR-PGC-1α and small heterodimer partner offers new insights into the biological functions of ERRα and FXR, thus providing a knowledge base for therapeutics in energy balance-related pathophysiology. PMID:21493670

Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

NASA Technical Reports Server (NTRS)

Lara-Rosano, Felipe

1992-01-01

In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.

Error-associated behaviors and error rates for robotic geology

NASA Technical Reports Server (NTRS)

Anderson, Robert C.; Thomas, Geb; Wagner, Jacob; Glasgow, Justin

2004-01-01

This study explores human error as a function of the decision-making process. One of many models for human decision-making is Rasmussen's decision ladder [9]. The decision ladder identifies the multiple tasks and states of knowledge involved in decision-making. The tasks and states of knowledge can be classified by the level of cognitive effort required to make the decision, leading to the skill, rule, and knowledge taxonomy (Rasmussen, 1987). Skill based decisions require the least cognitive effort and knowledge based decisions require the greatest cognitive effort. Errors can occur at any of the cognitive levels.

Capacitive Energy Extraction by Few-Layer Graphene Electrodes

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

Lian, Cheng; Zhan, Cheng; Jiang, De-en

Capacitive double-layer expansion is a promising technology to harvest energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the operation potentials and electrode materials. While carbonaceous materials such as graphene and various forms of activated carbons are routinely used as the electrodes, there is little knowledge on how the quantum capacitance and the electric double-layer (EDL) capacitance, which are on the same order of magnitude, affect the capacitive performance. Toward understanding that from a theoretical perspective, here we study the capacitive energy extraction with graphene electrodes as a function of themore » number of graphene layers. The classical density functional theory is joined with the electronic density functional theory to obtain the EDL and the quantum capacitance, respectively. The theoretical results show that the quantum capacitance contribution plays a dominant role in extracting energy using the single-layer graphene, but its effect diminishes as the number of graphene layers increases. The overall extracted energy is dominated by the EDL contribution beyond about four graphene layers. Electrodes with more graphene layers are able to extract more energy at low charging potential. Here, because many porous carbons have nanopores with stacked graphene layers, our theoretical predictions are useful to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different wall thickness.« less

Capacitive Energy Extraction by Few-Layer Graphene Electrodes

DOE PAGES

Lian, Cheng; Zhan, Cheng; Jiang, De-en; ...

2017-06-09

Capacitive double-layer expansion is a promising technology to harvest energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the operation potentials and electrode materials. While carbonaceous materials such as graphene and various forms of activated carbons are routinely used as the electrodes, there is little knowledge on how the quantum capacitance and the electric double-layer (EDL) capacitance, which are on the same order of magnitude, affect the capacitive performance. Toward understanding that from a theoretical perspective, here we study the capacitive energy extraction with graphene electrodes as a function of themore » number of graphene layers. The classical density functional theory is joined with the electronic density functional theory to obtain the EDL and the quantum capacitance, respectively. The theoretical results show that the quantum capacitance contribution plays a dominant role in extracting energy using the single-layer graphene, but its effect diminishes as the number of graphene layers increases. The overall extracted energy is dominated by the EDL contribution beyond about four graphene layers. Electrodes with more graphene layers are able to extract more energy at low charging potential. Here, because many porous carbons have nanopores with stacked graphene layers, our theoretical predictions are useful to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different wall thickness.« less

Structural and functional characterization of solute binding proteins for aromatic compounds derived from lignin: p-coumaric acid and related aromatic acids.

PubMed

Tan, Kemin; Chang, Changsoo; Cuff, Marianne; Osipiuk, Jerzy; Landorf, Elizabeth; Mack, Jamey C; Zerbs, Sarah; Joachimiak, Andrzej; Collart, Frank R

2013-10-01

Lignin comprises 15-25% of plant biomass and represents a major environmental carbon source for utilization by soil microorganisms. Access to this energy resource requires the action of fungal and bacterial enzymes to break down the lignin polymer into a complex assortment of aromatic compounds that can be transported into the cells. To improve our understanding of the utilization of lignin by microorganisms, we characterized the molecular properties of solute binding proteins of ATP-binding cassette transporter proteins that interact with these compounds. A combination of functional screens and structural studies characterized the binding specificity of the solute binding proteins for aromatic compounds derived from lignin such as p-coumarate, 3-phenylpropionic acid and compounds with more complex ring substitutions. A ligand screen based on thermal stabilization identified several binding protein clusters that exhibit preferences based on the size or number of aromatic ring substituents. Multiple X-ray crystal structures of protein-ligand complexes for these clusters identified the molecular basis of the binding specificity for the lignin-derived aromatic compounds. The screens and structural data provide new functional assignments for these solute-binding proteins which can be used to infer their transport specificity. This knowledge of the functional roles and molecular binding specificity of these proteins will support the identification of the specific enzymes and regulatory proteins of peripheral pathways that funnel these compounds to central metabolic pathways and will improve the predictive power of sequence-based functional annotation methods for this family of proteins. Copyright © 2013 Wiley Periodicals, Inc.

Structural and functional characterization of solute binding proteins for aromatic compounds derived from lignin: p-coumaric acid and related aromatic acids

PubMed Central

Tan, Kemin; Chang, Changsoo; Cuff, Marianne; Osipiuk, Jerzy; Landorf, Elizabeth; Mack, Jamey C.; Zerbs, Sarah; Joachimiak, Andrzej; Collart, Frank R.

2013-01-01

Lignin comprises 15.25% of plant biomass and represents a major environmental carbon source for utilization by soil microorganisms. Access to this energy resource requires the action of fungal and bacterial enzymes to break down the lignin polymer into a complex assortment of aromatic compounds that can be transported into the cells. To improve our understanding of the utilization of lignin by microorganisms, we characterized the molecular properties of solute binding proteins of ATP.binding cassette transporter proteins that interact with these compounds. A combination of functional screens and structural studies characterized the binding specificity of the solute binding proteins for aromatic compounds derived from lignin such as p-coumarate, 3-phenylpropionic acid and compounds with more complex ring substitutions. A ligand screen based on thermal stabilization identified several binding protein clusters that exhibit preferences based on the size or number of aromatic ring substituents. Multiple X-ray crystal structures of protein-ligand complexes for these clusters identified the molecular basis of the binding specificity for the lignin-derived aromatic compounds. The screens and structural data provide new functional assignments for these solute.binding proteins which can be used to infer their transport specificity. This knowledge of the functional roles and molecular binding specificity of these proteins will support the identification of the specific enzymes and regulatory proteins of peripheral pathways that funnel these compounds to central metabolic pathways and will improve the predictive power of sequence-based functional annotation methods for this family of proteins. PMID:23606130

Optoelectronic properties of type I indium gallium arsenide quantum cascade lasers with applications to optical modulation

NASA Astrophysics Data System (ADS)

Murawski, Robert K.

Quantum Cascade Lasers (QCL) are unique unipolar conduction band devices designed to emit in the mid infrared region (MIR). They have been employed very successfully in spectroscopy and sensing applications. Motivated by predictions of modulation bandwidths above 100 GHz, communication links based on QCLs were recently demonstrated. However, the intrinsic device circuitry of the QCL limits its bandwidth. In this thesis a new All-Optical Modulation of the QCL is presented and investigated both theoretically and experimentally. This method of modulation allows for full access to the bandwidth as well as unique optical control of the MIR laser emission. For this purpose, conduction and valence band wave functions for the complex QCL structure are presented allowing for the first time calculations of their interband energy resonances. Based on this knowledge, a novel optical modulation scheme is developed utilizing interband transition for laser modulation. Using laser rate equations, more accurate predictions for the response function can be derived. Optical modulation is shown to be superior to direct modulation. In addition to this theoretical framework, first experiments are presented on the effects of illuminating a QCL with additional lasers at or above the interband gap. The first demonstration of All-Optical Modulation was achieved using time varying near infrared illumination and the complimentary signature in the MIR QCL emission was observed. In addition to extending the knowledge base of QCL research by a first calculation of its valence band structure, this work opens new possibilities in modulation and control of the QCL's MIR emission by interband transition. Application of this technique range from fundamental physics research (e.g. electron coherence) to ultrafast communication (e.g. free-space links) and high-resolution spectroscopy.

Pore scale Assessment of Heat and Mass transfer in Porous Medium Using Phase Field Method with Application to Soil Borehole Thermal Storage (SBTES) Systems

NASA Astrophysics Data System (ADS)

Moradi, A.

2015-12-01

To properly model soil thermal performance in unsaturated porous media, for applications such as SBTES systems, knowledge of both soil hydraulic and thermal properties and how they change in space and time is needed. Knowledge obtained from pore scale to macroscopic scale studies can help us to better understand these systems and contribute to the state of knowledge which can then be translated to engineering applications in the field (i.e. implementation of SBTES systems at the field scale). One important thermal property that varies with soil water content, effective thermal conductivity, is oftentimes included in numerical models through the use of empirical relationships and simplified mathematical formulations developed based on experimental data obtained at either small laboratory or field scales. These models assume that there is local thermodynamic equilibrium between the air and water phases for a representative elementary volume. However, this assumption may not always be valid at the pore scale, thus questioning the validity of current modeling approaches. The purpose of this work is to evaluate the validity of the local thermodynamic equilibrium assumption as related to the effective thermal conductivity at pore scale. A numerical model based on the coupled Cahn-Hilliard and heat transfer equation was developed to solve for liquid flow and heat transfer through variably saturated porous media. In this model, the evolution of phases and the interfaces between phases are related to a functional form of the total free energy of the system. A unique solution for the system is obtained by solving the Navier-Stokes equation through free energy minimization. Preliminary results demonstrate that there is a correlation between soil temperature / degree of saturation and equivalent thermal conductivity / heat flux. Results also confirm the correlation between pressure differential magnitude and equilibrium time for multiphase flow to reach steady state conditions. Based on these results, the equivalent time for steady-state heat transfer is much larger than the equivalent time for steady-state multiphase flow for a given pressure differential. Moreover, the wetting phase flow and consequently heat transfer appear to be sensitive to contact angle and porosity of the domain.

Using diagnostic experiences in experience-based innovative design

NASA Astrophysics Data System (ADS)

Prabhakar, Sattiraju; Goel, Ashok K.

1992-03-01

Designing a novel class of devices requires innovation. Often, the design knowledge of these devices does not identify and address the constraints that are required for their performance in the real world operating environment. So any new design adapted from these devices tend to be similarly sketchy. In order to address this problem, we propose a case-based reasoning method called performance driven innovation (PDI). We model the design as a dynamic process, arrive at a design by adaptation from the known designs, generate failures for this design for some new constraints, and then use this failure knowledge to generate the required design knowledge for the new constraints. In this paper, we discuss two aspects of PDI: the representation of PDI cases and the translation of the failure knowledge into design knowledge for a constraint. Each case in PDI has two components: design and failure knowledge. Both of them are represented using a substance-behavior-function model. Failure knowledge has internal device failure behaviors and external environmental behaviors. The environmental behavior, for a constraint, interacting with the design behaviors, results in the failure internal behavior. The failure adaptation strategy generates functions, from the failure knowledge, which can be addressed using the routine design methods. These ideas are illustrated using a coffee-maker example.

Conceptual information processing: A robust approach to KBS-DBMS integration

NASA Technical Reports Server (NTRS)

Lazzara, Allen V.; Tepfenhart, William; White, Richard C.; Liuzzi, Raymond

1987-01-01

Integrating the respective functionality and architectural features of knowledge base and data base management systems is a topic of considerable interest. Several aspects of this topic and associated issues are addressed. The significance of integration and the problems associated with accomplishing that integration are discussed. The shortcomings of current approaches to integration and the need to fuse the capabilities of both knowledge base and data base management systems motivates the investigation of information processing paradigms. One such paradigm is concept based processing, i.e., processing based on concepts and conceptual relations. An approach to robust knowledge and data base system integration is discussed by addressing progress made in the development of an experimental model for conceptual information processing.

An Exploration of Leadership in Virtual Communities of Practice

ERIC Educational Resources Information Center

Chrisentary, John

2013-01-01

Virtual community of practice (VCoP) teams are becoming a typical function in many knowledge-based organizations. VCoP teams can consist of team members located in various cities, states, and countries. The main characteristic of the VCoP is team members' sense of community that allows individuals to share knowledge. Knowledge sharing in a VCoP…

Using social media to facilitate knowledge transfer in complex engineering environments: a primer for educators

NASA Astrophysics Data System (ADS)

Murphy, Glen; Salomone, Sonia

2013-03-01

While highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Consequently, an essential challenge for engineering organisations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. This paper acts as a primer for those seeking to gain an understanding of the design, functionality and utility of a suite of software tools generically termed social media technologies in the context of optimising the management of tacit engineering knowledge. Underpinned by knowledge management theory and using detailed case examples, this paper explores how social media technologies achieve such goals, allowing for the transfer of knowledge by tapping into the tacit and explicit knowledge of disparate groups in complex engineering environments.

Electron Thermionic Emission from Graphene and a Thermionic Energy Converter

NASA Astrophysics Data System (ADS)

Liang, Shi-Jun; Ang, L. K.

2015-01-01

In this paper, we propose a model to investigate the electron thermionic emission from single-layer graphene (ignoring the effects of the substrate) and to explore its application as the emitter of a thermionic energy converter (TIC). An analytical formula is derived, which is a function of the temperature, work function, and Fermi energy level. The formula is significantly different from the traditional Richardson-Dushman (RD) law for which it is independent of mass to account for the supply function of the electrons in the graphene behaving like massless fermion quasiparticles. By comparing with a recent experiment [K. Jiang et al., Nano Res. 7, 553 (2014)] measuring electron thermionic emission from suspended single-layer graphene, our model predicts that the intrinsic work function of single-layer graphene is about 4.514 eV with a Fermi energy level of 0.083 eV. For a given work function, a scaling of T3 is predicted, which is different from the traditional RD scaling of T2. If the work function of the graphene is lowered to 2.5-3 eV and the Fermi energy level is increased to 0.8-0.9 eV, it is possible to design a graphene-cathode-based TIC operating at around 900 K or lower, as compared with the metal-based cathode TIC (operating at about 1500 K). With a graphene-based cathode (work function=4.514 eV ) at 900 K and a metallic-based anode (work function=2.5 eV ) like LaB6 at 425 K, the efficiency of our proposed TIC is about 45%.

Large impact of reorganization energy on photovoltaic conversion due to interfacial charge-transfer transitions.

PubMed

Fujisawa, Jun-ichi

2015-05-14

Interfacial charge-transfer (ICT) transitions are expected to be a novel charge-separation mechanism for efficient photovoltaic conversion featuring one-step charge separation without energy loss. Photovoltaic conversion due to ICT transitions has been investigated using several TiO2-organic hybrid materials that show organic-to-inorganic ICT transitions in the visible region. In applications of ICT transitions to photovoltaic conversion, there is a significant problem that rapid carrier recombination is caused by organic-inorganic electronic coupling that is necessary for the ICT transitions. In order to solve this problem, in this work, I have theoretically studied light-to-current conversions due to the ICT transitions on the basis of the Marcus theory with density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations. An apparent correlation between the reported incident photon-to-current conversion efficiencies (IPCE) and calculated reorganization energies was clearly found, in which the IPCE increases with decreasing the reorganization energy consistent with the Marcus theory in the inverted region. This activation-energy dependence was systematically explained by the equation formulated by the Marcus theory based on a simple excited-state kinetic scheme. This result indicates that the reduction of the reorganization energy can suppress the carrier recombination and enhance the IPCE. The reorganization energy is predominantly governed by the structural change in the chemical-adsorption moiety between the ground and ICT excited states. This work provides crucial knowledge for efficient photovoltaic conversion due to ICT transitions.

Wind for Schools Affiliate Programs: Wind and Hydropower Technologies Program (Fact Sheet)

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

Not Available

2009-12-01

The U.S. Department of Energy's (DOE's) Wind for Schools program is designed to raise awareness about the benefits of wind energy while simultaneously developing a wind energy knowledge base in future leaders of our communities, states, and nation. To accommodate the many stakeholders who are interested in the program, a Wind for Schools affiliate program has been implemented. This document describes the affiliate program and how interested schools may participate.

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

ProbOnto: ontology and knowledge base of probability distributions.

PubMed

Swat, Maciej J; Grenon, Pierre; Wimalaratne, Sarala

2016-09-01

Probability distributions play a central role in mathematical and statistical modelling. The encoding, annotation and exchange of such models could be greatly simplified by a resource providing a common reference for the definition of probability distributions. Although some resources exist, no suitably detailed and complex ontology exists nor any database allowing programmatic access. ProbOnto, is an ontology-based knowledge base of probability distributions, featuring more than 80 uni- and multivariate distributions with their defining functions, characteristics, relationships and re-parameterization formulas. It can be used for model annotation and facilitates the encoding of distribution-based models, related functions and quantities. http://probonto.org mjswat@ebi.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Gut-Brain Glucose Signaling in Energy Homeostasis.

PubMed

Soty, Maud; Gautier-Stein, Amandine; Rajas, Fabienne; Mithieux, Gilles

2017-06-06

Intestinal gluconeogenesis is a recently identified function influencing energy homeostasis. Intestinal gluconeogenesis induced by specific nutrients releases glucose, which is sensed by the nervous system surrounding the portal vein. This initiates a signal positively influencing parameters involved in glucose control and energy management controlled by the brain. This knowledge has extended our vision of the gut-brain axis, classically ascribed to gastrointestinal hormones. Our work raises several questions relating to the conditions under which intestinal gluconeogenesis proceeds and may provide its metabolic benefits. It also leads to questions on the advantage conferred by its conservation through a process of natural selection. Copyright © 2017 Elsevier Inc. All rights reserved.

A concept ideation framework for medical device design.

PubMed

Hagedorn, Thomas J; Grosse, Ian R; Krishnamurty, Sundar

2015-06-01

Medical device design is a challenging process, often requiring collaboration between medical and engineering domain experts. This collaboration can be best institutionalized through systematic knowledge transfer between the two domains coupled with effective knowledge management throughout the design innovation process. Toward this goal, we present the development of a semantic framework for medical device design that unifies a large medical ontology with detailed engineering functional models along with the repository of design innovation information contained in the US Patent Database. As part of our development, existing medical, engineering, and patent document ontologies were modified and interlinked to create a comprehensive medical device innovation and design tool with appropriate properties and semantic relations to facilitate knowledge capture, enrich existing knowledge, and enable effective knowledge reuse for different scenarios. The result is a Concept Ideation Framework for Medical Device Design (CIFMeDD). Key features of the resulting framework include function-based searching and automated inter-domain reasoning to uniquely enable identification of functionally similar procedures, tools, and inventions from multiple domains based on simple semantic searches. The significance and usefulness of the resulting framework for aiding in conceptual design and innovation in the medical realm are explored via two case studies examining medical device design problems. Copyright © 2015 Elsevier Inc. All rights reserved.

Online epistemic communities: theoretical and methodological directions for understanding knowledge co-elaboration in new digital spaces.

PubMed

Détienne, Françoise; Barcellini, Flore; Baker, Michael; Burkhardt, Jean-Marie; Fréard, Dominique

2012-01-01

This paper presents, illustrates and discusses a generic framework for studying knowledge co-elaboration in online epistemic communities ("OECs"). Our approach is characterised by: considering knowledge co-elaboration as a design activity; distinguishing discussion and production spaces in OECs; characterising participation via the notion of role; fine-grained analyses of meaning, content and communicative functions in interactions. On this basis, three key issues for ergonomics research on OECs are discussed and illustrated by results from our previous studies on OSS and Wikipedia. One issue concerns the interrelation between design (task) and regulation. Whereas design task-oriented activity is distributed among participants, we illustrate that OCEs function with specialised emerging roles of group regulation. However, the task-oriented activity also functions at an interpersonal level, as an interplay of knowledge-based discussion with negotiation of competencies. Another issue concerns the foci of activity on the (designed) knowledge object. Based on a generic task model, we illustrate asymmetry and distinctiveness in tasks' foci of participants. The last issue concerns how design-use mediation is ensured by specific forms of mediation roles in OECs. Finally we discuss the degree of generality of our framework and draw some perspectives for extending our framework to other OECs.

Construction of a cDNA library for sea cucumber Acaudina leucoprocta and differential expression of ferritin peptide

NASA Astrophysics Data System (ADS)

Zhou, Jun; Hou, Fujing; Li, Ye; Su, Xiurong; Li, Taiwu; Jin, Chunhua

2016-07-01

Acaudina leucoprocta is an edible sea cucumber of economic interest that is widely distributed in China. Little information is available concerning the molecular genetics of this species although such knowledge would contribute to a better understanding of the optimal conditions for its aquaculture and its mechanisms of defense against disease. Therefore, we constructed a cDNA library and, based on bioinformatics analysis of the sequences, the functions of 75% of the cDNAs were identified, including those involved in cell structure, energy metabolism, mitochondrial function, and signal transduction pathways. Approximately 25% of genes in the library were unmatched. The gene for A. leucoprocta ferritin was also cloned. The predicted amino-acid sequence of ferritin displayed significant homology with other sea-cucumber counterparts but indicated that it was a new member of the ferritin family. Semiquantitative real-time RT-PCR indicated the highest levels of ferritin mRNA expression in the intestine. A polyclonal antibody of ferritin was also produced. These data provide a set of molecular tools essential for further studies of the functions of ferritin protein in A. leucoprocta.

Form and function relationships revealed by long-term research in a semiarid mountain catchment

NASA Astrophysics Data System (ADS)

McNamara, J. P.; Benner, S. G.; Chandler, D. G.; Flores, A. N.; Marshall, H. P.; Seyfried, M. S.; Poulos, M. J.; Pierce, J. L.

2017-12-01

Fifteen years of cumulative research in the Dry Creek Experimental Watershed in southwest Idaho, USA has revealed relationships between catchment form and function and contributed to improved fundamental understanding of Critical Zone structure, function, and evolution that would not have been possible through independent short term projects alone. The impacts of aspect and elevation on incident energy and water, coupled with climate seasonality, has produced tightly connected landforms properties and hydrologic processes. North-facing hillslopes have steeper slopes, thicker soil mantles, and finer soil texture than their south-facing counterparts. Finer soils enable higher water holding capacities on north facing slopes, which when coupled with thicker soils produces higher soil water storage capacity. The storage of water first as snow, then as soil moisture determines how upland ecosystems survive the seasonal and persistent water stress that happens each year, and sustains streamflow throughout the year. The cumulative body of local knowledge has improved general understanding of catchment science, serves as a resource for developing, evaluating, and improving conceptual and numerical of process-based models, and for data-driven hydrologic education.

Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi

In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

An architecture for intelligent task interruption

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Narayan, Srini

1990-01-01

In the design of real time systems the capability for task interruption is often considered essential. The problem of task interruption in knowledge-based domains is examined. It is proposed that task interruption can be often avoided by using appropriate functional architectures and knowledge engineering principles. Situations for which task interruption is indispensable, a preliminary architecture based on priority hierarchies is described.

Genre-Based Tasks in Foreign Language Writing: Developing Writers' Genre Awareness, Linguistic Knowledge, and Writing Competence

ERIC Educational Resources Information Center

Yasuda, Sachiko

2011-01-01

This study examines how novice foreign language (FL) writers develop their genre awareness, linguistic knowledge, and writing competence in a genre-based writing course that incorporates email-writing tasks. To define genre, the study draws on systemic functional linguistics (SFL) that sees language as a resource for making meaning in a particular…

[Energy saving and LED lamp lighting and human health].

PubMed

Deĭnego, V N; Kaptsov, V A

2013-01-01

The appearance of new sources of high-intensity with large proportion of blue light in the spectrum revealed new risks of their influence on the function of the eye and human health, especially for children and teenagers. There is an urgent need to reconsider the research methods of vision hygiene in conditions of energy-saving and LED bulbs lighting. On the basis of a systematic approach and knowledge of the newly discovered photosensitive receptors there was built hierarchical model of the interaction of "light environment - the eye - the system of formation of visual images - the hormonal system of the person - his psycho-physiological state." This approach allowed us to develop a range of risk for the negative impact of spectrum on the functions of the eye and human health, as well as to formulate the hygiene requirements for energy-efficient high-intensity light sources.

Energy conservation in the earth's crust and climate change.

PubMed

Mu, Yao; Mu, Xinzhi

2013-02-01

Among various matters which make up the earth's crust, the thermal conductivity of coal, oil, and oil-gas, which are formed over a long period of geological time, is extremely low. This is significant to prevent transferring the internal heat of the earth to the thermal insulation of the surface, cooling the surface of the earth, stimulating biological evolution, and maintaining natural ecological balance as well. Fossil energy is thermal insulating layer in the earth's crust. Just like the function of the thermal isolation of subcutaneous fatty tissue under the dermis of human skin, it keeps the internal heat within the organism so it won't be transferred to the skin's surface and be lost maintaining body temperature at low temperatures. Coal, oil, oil-gas, and fat belong to the same hydrocarbons, and the functions of their thermal insulation are exactly the same. That is to say, coal, oil, and oil-gas are just like the earth's "subcutaneous fatty tissue" and objectively formed the insulation protection on earth's surface. This paper argues that the human large-scale extraction of fossil energy leads to damage of the earth's crust heat-resistant sealing, increasing terrestrial heat flow, or the heat flow as it is called, transferring the internal heat of the earth to Earth's surface excessively, and causing geotemperature and sea temperature to rise, thus giving rise to global warming. The reason for climate warming is not due to the expansion of greenhouse gases but to the wide exploitation of fossil energy, which destroyed the heat insulation of the earth's crust, making more heat from the interior of the earth be released to the atmosphere. Based on the energy conservation principle, the measurement of the increase of the average global temperature that was caused by the increase of terrestrial heat flow since the Industrial Revolution is consistent with practical data. This paper illustrates "pathogenesis" of climate change using medical knowledge. The mathematical verification is based on the principle of energy conservation. The central idea or clou in this paper is that fossil energy is a thermal insulating layer in the earth's crust, the thermal insulating layer was destroyed after human large-scale mining of fossil energy, and the internal heat of the earth was excessively released to the surface so as to cause climate change.

An Energy Model for Viewing Embodied Human Capital Theory

ERIC Educational Resources Information Center

Kaufman, Neil A.; Geroy, Gary D.

2007-01-01

Human capital development is one of the emerging areas of study with regard to social science theory, practice, and research. A relatively new concept, human capital is described in terms of individual knowledge skills and experience. It is currently expressed as a function of education as well as a measure of economic activity. Little theory…

Assessing the impact of modeling limits on intelligent systems

NASA Technical Reports Server (NTRS)

Rouse, William B.; Hammer, John M.

1990-01-01

The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifying limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility.

The Global Experience of Deployment of Energy-Efficient Technologies in High-Rise Construction

NASA Astrophysics Data System (ADS)

Potienko, Natalia D.; Kuznetsova, Anna A.; Solyakova, Darya N.; Klyueva, Yulia E.

2018-03-01

The objective of this research is to examine issues related to the increasing importance of energy-efficient technologies in high-rise construction. The aim of the paper is to investigate modern approaches to building design that involve implementation of various energy-saving technologies in diverse climates and at different structural levels, including the levels of urban development, functionality, planning, construction and engineering. The research methodology is based on the comprehensive analysis of the advanced global expertise in the design and construction of energy-efficient high-rise buildings, with the examination of their positive and negative features. The research also defines the basic principles of energy-efficient architecture. Besides, it draws parallels between the climate characteristics of countries that lead in the field of energy-efficient high-rise construction, on the one hand, and the climate in Russia, on the other, which makes it possible to use the vast experience of many countries, wholly or partially. The paper also gives an analytical review of the results arrived at by implementing energy efficiency principles into high-rise architecture. The study findings determine the impact of energy-efficient technologies on high-rise architecture and planning solutions. In conclusion, the research states that, apart from aesthetic and compositional interpretation of architectural forms, an architect nowadays has to address the task of finding a synthesis between technological and architectural solutions, which requires knowledge of advanced technologies. The study findings reveal that the implementation of modern energy-efficient technologies into high-rise construction is of immediate interest and is sure to bring long-term benefits.

Tools for knowledge acquisition within the NeuroScholar system and their application to anatomical tract-tracing data

PubMed Central

Burns, Gully APC; Cheng, Wei-Cheng

2006-01-01

Background Knowledge bases that summarize the published literature provide useful online references for specific areas of systems-level biology that are not otherwise supported by large-scale databases. In the field of neuroanatomy, groups of small focused teams have constructed medium size knowledge bases to summarize the literature describing tract-tracing experiments in several species. Despite years of collation and curation, these databases only provide partial coverage of the available published literature. Given that the scientists reading these papers must all generate the interpretations that would normally be entered into such a system, we attempt here to provide general-purpose annotation tools to make it easy for members of the community to contribute to the task of data collation. Results In this paper, we describe an open-source, freely available knowledge management system called 'NeuroScholar' that allows straightforward structured markup of the PDF files according to a well-designed schema to capture the essential details of this class of experiment. Although, the example worked through in this paper is quite specific to neuroanatomical connectivity, the design is freely extensible and could conceivably be used to construct local knowledge bases for other experiment types. Knowledge representations of the experiment are also directly linked to the contributing textual fragments from the original research article. Through the use of this system, not only could members of the community contribute to the collation task, but input data can be gathered for automated approaches to permit knowledge acquisition through the use of Natural Language Processing (NLP). Conclusion We present a functional, working tool to permit users to populate knowledge bases for neuroanatomical connectivity data from the literature through the use of structured questionnaires. This system is open-source, fully functional and available for download from [1]. PMID:16895608

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning

PubMed Central

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach. PMID:24616695

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning.

PubMed

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach.

Current Level and Correlates of Traditional Cooking Energy Sources Utilization in Urban Settings in the Context of Climate Change and Health, Northwest Ethiopia: A Case of Debre Markos Town

PubMed Central

Geremew, Kumlachew; Gedefaw, Molla; Dagnew, Zewdu; Jara, Dube

2014-01-01

Background. Traditional biomass has been the major source of cooking energy for major segment of Ethiopian population for thousands of years. Cognizant of this energy poverty, the Government of Ethiopia has been spending huge sum of money to increase hydroelectric power generating stations. Objective. To assess current levels and correlates of traditional cooking energy sources utilization. Methods. A community based cross-sectional study was conducted employing both quantitative and qualitative approaches on systematically selected 423 households for quantitative and purposively selected 20 people for qualitative parts. SPSS version 16 for windows was used to analyze the quantitative data. Logistic regression was fitted to assess possible associations and its strength was measured using odds ratio at 95% CI. Qualitative data were analyzed thematically. Result. The study indicated that 95% of households still use traditional biomass for cooking. Those who were less knowledgeable about negative health and environmental effects of traditional cooking energy sources were seven and six times more likely to utilize them compared with those who were knowledgeable (AOR (95% CI) = 7.56 (1.635, 34.926), AOR (95% CI) = 6.68 (1.80, 24.385), resp.). The most outstanding finding of this study was that people use traditional energy for cooking mainly due to lack of the knowledge and their beliefs about food prepared using traditional energy. That means “…people still believe that food cooked with charcoal is believed to taste delicious than cooked with other means.”  Conclusion. The majority of households use traditional biomass for cooking due to lack of knowledge and belief. Therefore, mechanisms should be designed to promote electric energy and to teach the public about health effects of traditional cooking energy source. PMID:24895591

Principles of light harvesting from single photosynthetic complexes.

PubMed

Schlau-Cohen, G S

2015-06-06

Photosynthetic systems harness sunlight to power most life on Earth. In the initial steps of photosynthetic light harvesting, absorbed energy is converted to chemical energy with near-unity quantum efficiency. This is achieved by an efficient, directional and regulated flow of energy through a network of proteins. Here, we discuss the following three key principles of this flow and of photosynthetic light harvesting: thermal fluctuations of the protein structure; intrinsic conformational switches with defined functional consequences; and environmentally triggered conformational switches. Through these principles, photosynthetic systems balance two types of operational costs: metabolic costs, or the cost of maintaining and running the molecular machinery, and opportunity costs, or the cost of losing any operational time. Understanding how the molecular machinery and dynamics are designed to balance these costs may provide a blueprint for improved artificial light-harvesting devices. With a multi-disciplinary approach combining knowledge of biology, this blueprint could lead to low-cost and more effective solar energy conversion. Photosynthetic systems achieve widespread light harvesting across the Earth's surface; in the face of our growing energy needs, this is functionality we need to replicate, and perhaps emulate.

KBGIS-II: A knowledge-based geographic information system

NASA Technical Reports Server (NTRS)

Smith, Terence; Peuquet, Donna; Menon, Sudhakar; Agarwal, Pankaj

1986-01-01

The architecture and working of a recently implemented Knowledge-Based Geographic Information System (KBGIS-II), designed to satisfy several general criteria for the GIS, is described. The system has four major functions including query-answering, learning and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial object language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is performing all its designated tasks successfully. Future reports will relate performance characteristics of the system.

A Technology-Enhanced Unit of Modeling Static Electricity: Integrating scientific explanations and everyday observations

NASA Astrophysics Data System (ADS)

Shen, Ji; Linn, Marcia C.

2011-08-01

What trajectories do students follow as they connect their observations of electrostatic phenomena to atomic-level visualizations? We designed an electrostatics unit, using the knowledge integration framework to help students link observations and scientific ideas. We analyze how learners integrate ideas about charges, charged particles, energy, and observable events. We compare learning enactments in a typical school and a magnet school in the USA. We use pre-tests, post-tests, embedded notes, and delayed post-tests to capture the trajectories of students' knowledge integration. We analyze how visualizations help students grapple with abstract electrostatics concepts such as induction. We find that overall students gain more sophisticated ideas. They can interpret dynamic, interactive visualizations, and connect charge- and particle-based explanations to interpret observable events. Students continue to have difficulty in applying the energy-based explanation.

Outer Membrane Protein Folding and Topology from a Computational Transfer Free Energy Scale.

PubMed

Lin, Meishan; Gessmann, Dennis; Naveed, Hammad; Liang, Jie

2016-03-02

Knowledge of the transfer free energy of amino acids from aqueous solution to a lipid bilayer is essential for understanding membrane protein folding and for predicting membrane protein structure. Here we report a computational approach that can calculate the folding free energy of the transmembrane region of outer membrane β-barrel proteins (OMPs) by combining an empirical energy function with a reduced discrete state space model. We quantitatively analyzed the transfer free energies of 20 amino acid residues at the center of the lipid bilayer of OmpLA. Our results are in excellent agreement with the experimentally derived hydrophobicity scales. We further exhaustively calculated the transfer free energies of 20 amino acids at all positions in the TM region of OmpLA. We found that the asymmetry of the Gram-negative bacterial outer membrane as well as the TM residues of an OMP determine its functional fold in vivo. Our results suggest that the folding process of an OMP is driven by the lipid-facing residues in its hydrophobic core, and its NC-IN topology is determined by the differential stabilities of OMPs in the asymmetrical outer membrane. The folding free energy is further reduced by lipid A and assisted by general depth-dependent cooperativities that exist between polar and ionizable residues. Moreover, context-dependency of transfer free energies at specific positions in OmpLA predict regions important for protein function as well as structural anomalies. Our computational approach is fast, efficient and applicable to any OMP.

Investigating Knowledge Management Status among Faculty Members of Kerman University of Medical Sciences based on the Nonaka Model in 2015

PubMed Central

Vali, Leila; Izadi, Azar; Jahani, Yunes; Okhovati, Maryam

2016-01-01

Introduction Education and research are two major functions of universities, which require proper and systematic exploitation of available knowledge and information. Therefore, it is necessary to investigate the knowledge management status in an education system by considering the function of faculty members in creation and dissemination of knowledge. This study was conducted to investigate the knowledge management status among faculty members of the Kerman University of Medical Sciences based on the Nonaka and Takeuchi models in 2015. Methods This was a descriptive-analytical and cross-sectional study. It was conducted on 165 faculty members at the Kerman University of Medical Sciences, who were selected from seven faculties as weighted using a random stratified sampling method. The Nonaka and Takeuchi knowledge management questionnaire consists of 26 questions in four dimensions of socialization, externalization, internalization, and combination. Scoring of questions was conducted using the five-point Likert scale. To analyze data, independent t-test, one-way ANOVA, Pearson correlation coefficients, and the Kruskal-Wallis test were employed. Results The four dimensions in the Nonaka and Takeuchi model are based on optimal indicators (3.5), dimensions of combination, and externalization with an average of 3.3 were found in higher ranks and internalization and socialization had averages of 3.1 and 3. According to the findings of this study, the average knowledge management among faculty members of the Kerman University of Medical Sciences was estimated to be 3.1, with a bit difference compared to the average. According to the results of t-tests, there was no significant relationship between gender and various dimensions of knowledge management (p>0.05). The findings of Kruskal-Wallis showed that there is no significant relationship between variables of age, academic rank, and type of faculty with regard to dimensions of knowledge management (p>0.05). In addition, according to the results of Pearson tests, there is no significant relation between employment history and dimensions of knowledge management (p>0.05). Conclusion Considering the function and importance of knowledge management in education and research organizations including universities, it is recommended to pay comprehensive attention to establishment of knowledge management and knowledge sharing in universities and provide the required background to from research teams and communication networks inside and outside universities. PMID:27757183

Investigating Knowledge Management Status among Faculty Members of Kerman University of Medical Sciences based on the Nonaka Model in 2015.

PubMed

Vali, Leila; Izadi, Azar; Jahani, Yunes; Okhovati, Maryam

2016-08-01

Education and research are two major functions of universities, which require proper and systematic exploitation of available knowledge and information. Therefore, it is necessary to investigate the knowledge management status in an education system by considering the function of faculty members in creation and dissemination of knowledge. This study was conducted to investigate the knowledge management status among faculty members of the Kerman University of Medical Sciences based on the Nonaka and Takeuchi models in 2015. This was a descriptive-analytical and cross-sectional study. It was conducted on 165 faculty members at the Kerman University of Medical Sciences, who were selected from seven faculties as weighted using a random stratified sampling method. The Nonaka and Takeuchi knowledge management questionnaire consists of 26 questions in four dimensions of socialization, externalization, internalization, and combination. Scoring of questions was conducted using the five-point Likert scale. To analyze data, independent t-test, one-way ANOVA, Pearson correlation coefficients, and the Kruskal-Wallis test were employed. The four dimensions in the Nonaka and Takeuchi model are based on optimal indicators (3.5), dimensions of combination, and externalization with an average of 3.3 were found in higher ranks and internalization and socialization had averages of 3.1 and 3. According to the findings of this study, the average knowledge management among faculty members of the Kerman University of Medical Sciences was estimated to be 3.1, with a bit difference compared to the average. According to the results of t-tests, there was no significant relationship between gender and various dimensions of knowledge management (p>0.05). The findings of Kruskal-Wallis showed that there is no significant relationship between variables of age, academic rank, and type of faculty with regard to dimensions of knowledge management (p>0.05). In addition, according to the results of Pearson tests, there is no significant relation between employment history and dimensions of knowledge management (p>0.05). Considering the function and importance of knowledge management in education and research organizations including universities, it is recommended to pay comprehensive attention to establishment of knowledge management and knowledge sharing in universities and provide the required background to from research teams and communication networks inside and outside universities.

Relationship Between Energy Drink Consumption and Nutrition Knowledge in Student-Athletes.

PubMed

Hardy, Richard; Kliemann, Nathalie; Evansen, Taylor; Brand, Jefferson

2017-01-01

To identify the relationships between energy drink consumption, nutrition knowledge, and socio-demographic characteristics in a convenience sample of student-athletes. Cross-sectional. Online survey. A total of 194 student-athletes (112 female and 82 male). Socio-demographic characteristics, knowledge of human nutrition, energy drink consumption habits. Chi-square tests of independence, independent t tests, and hierarchical regression analyses were applied. Most student-athletes in the sample (85.5%) did not consume energy drinks, but those who did tended to be male (P = .004), had lower overall knowledge of nutrition (P = .02), and had a lower grade point average (P < .001) than did nonusers. Also, energy drink consumption was associated with the overall nutrition knowledge score when adjusted for socio-demographic characteristics, with nonusers having greater nutrition knowledge (P = .007) than users. Student-athletes tend to refrain from energy drink use but those who use it have a tendency to have lower nutrition knowledge than do nonusers. Therefore, nutrition education targeted toward student-athletes should encompass the consumption of energy drinks because limited evidence shows the benefits of collegiate athletes consuming energy drinks. Copyright © 2016 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Light output function and assembly of the time-of-flight enhanced diagnostics neutron spectrometer plastic scintillators for background reduction by double kinematic selection at EAST

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

Peng, X. Y.; Chen, Z. J.; Zhang, X.

The 2.5 MeV neutron spectrometer TOFED (Time-Of-Flight Enhanced Diagnostics) has been constructed to perform advanced neutron emission spectroscopy diagnosis of deuterium plasmas on EAST. The instrument has a double-ring structure which, in combination with pulse shape digitization, allows for a dual kinematic selection in the time-of-flight/recoil proton energy (tof/E{sub p}) space, thus improving the spectrometer capability to resolve fast ion signatures in the neutron spectrum, in principle up to a factor ≈100. The identification and separation of features from the energetic ions in the neutron spectrum depends on the detailed knowledge of the instrument response function, both in terms ofmore » the light output function of the scintillators and the effect of undesired multiple neutron scatterings in the instrument. This work presents the determination of the light output function of the TOFED plastic scintillator detectors and their geometrical assembly. Results from dedicated experiments with γ-ray sources and quasi-monoenergetic neutron beams are presented. Implications on the instrument capability to perform background suppression based on double kinematic selection are discussed.« less

Material Separation Using Dual-Energy CT: Current and Emerging Applications.

PubMed

Patino, Manuel; Prochowski, Andrea; Agrawal, Mukta D; Simeone, Frank J; Gupta, Rajiv; Hahn, Peter F; Sahani, Dushyant V

2016-01-01

Dual-energy (DE) computed tomography (CT) offers the opportunity to generate material-specific images on the basis of the atomic number Z and the unique mass attenuation coefficient of a particular material at different x-ray energies. Material-specific images provide qualitative and quantitative information about tissue composition and contrast media distribution. The most significant contribution of DE CT-based material characterization comes from the capability to assess iodine distribution through the creation of an image that exclusively shows iodine. These iodine-specific images increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues, improving lesion detection and characterization in the abdomen. In addition, DE CT enables computational removal of iodine influence from a CT image, generating virtual noncontrast images. Several additional materials, including calcium, fat, and uric acid, can be separated, permitting imaging assessment of metabolic imbalances, elemental deficiencies, and abnormal deposition of materials within tissues. The ability to obtain material-specific images from a single, contrast-enhanced CT acquisition can complement the anatomic knowledge with functional information, and may be used to reduce the radiation dose by decreasing the number of phases in a multiphasic CT examination. DE CT also enables generation of energy-specific and virtual monochromatic images. Clinical applications of DE CT leverage both material-specific images and virtual monochromatic images to expand the current role of CT and overcome several limitations of single-energy CT. (©)RSNA, 2016.

Identifying the stored energy of a hyperelastic structure by using an attenuated Landweber method

NASA Astrophysics Data System (ADS)

Seydel, Julia; Schuster, Thomas

2017-12-01

We consider the nonlinear inverse problem of identifying the stored energy function of a hyperelastic material from full knowledge of the displacement field as well as from surface sensor measurements. The displacement field is represented as a solution of Cauchy’s equation of motion, which is a nonlinear elastic wave equation. Hyperelasticity means that the first Piola-Kirchhoff stress tensor is given as the gradient of the stored energy function. We assume that a dictionary of suitable functions is available. The aim is to recover the stored energy with respect to this dictionary. The considered inverse problem is of vital interest for the development of structural health monitoring systems which are constructed to detect defects in elastic materials from boundary measurements of the displacement field, since the stored energy encodes the mechanical properties of the underlying structure. In this article we develop a numerical solver using the attenuated Landweber method. We show that the parameter-to-solution map satisfies the local tangential cone condition. This result can be used to prove local convergence of the attenuated Landweber method in the case that the full displacement field is measured. In our numerical experiments we demonstrate how to construct an appropriate dictionary and show that our method is well suited to localize damages in various situations.

[Web-based support system for medical device maintenance].

PubMed

Zhao, Jinhai; Hou, Wensheng; Chen, Haiyan; Tang, Wei; Wang, Yihui

2015-01-01

A Web-based technology system was put forward aiming at the actual problems of the long maintenance cycle and the difficulties of the maintenance and repairing of medical equipments. Based on analysis of platform system structure and function, using the key technologies such as search engine, BBS, knowledge base and etc, a platform for medical equipment service technician to use by online or offline was designed. The platform provides users with knowledge services and interactive services, enabling users to get a more ideal solution.

Visualizing the dynamic structure of the plant photosynthetic membrane.

PubMed

Ruban, Alexander V; Johnson, Matthew P

2015-11-03

The chloroplast thylakoid membrane is the site for the initial steps of photosynthesis that convert solar energy into chemical energy, ultimately powering almost all life on earth. The heterogeneous distribution of protein complexes within the membrane gives rise to an intricate three-dimensional structure that is nonetheless extremely dynamic on a timescale of seconds to minutes. These dynamics form the basis for the regulation of photosynthesis, and therefore the adaptability of plants to different environments. High-resolution microscopy has in recent years begun to provide new insights into the structural dynamics underlying a number of regulatory processes such as membrane stacking, photosystem II repair, photoprotective energy dissipation, state transitions and alternative electron transfer. Here we provide an overview of the essentials of thylakoid membrane structure in plants, and consider how recent advances, using a range of microscopies, have substantially increased our knowledge of the thylakoid dynamic structure. We discuss both the successes and limitations of the currently available techniques and highlight newly emerging microscopic methods that promise to move the field beyond the current 'static' view of membrane organization based on frozen snapshots to a 'live' view of functional membranes imaged under native aqueous conditions at ambient temperature and responding dynamically to external stimuli.

Ten questions concerning future buildings beyond zero energy and carbon neutrality

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

Wang, Na; Phelan, Patrick E.; Gonzalez, Jorge

2017-07-01

Architects, planners, and building scientists have been at the forefront of envisioning a future built environment for centuries. However, fragmental views that emphasize one facet of the built environment, such as energy, environment, or groundbreaking technologies, often do not achieve expected outcomes. Buildings are responsible for approximately one-third of worldwide carbon emissions and account for over 40% of primary energy consumption in the U.S. In addition to achieving the ambitious goal of reducing building greenhouse gas emissions by 75% by 2050, buildings must improve their functionality and performance to meet current and future human, societal, and environmental needs in amore » changing world. In this article, we introduce a new framework to guide potential evolution of the building stock in the next century, based on greenhouse gas emissions as the common thread to investigate the potential implications of new design paradigms, innovative operational strategies, and disruptive technologies. This framework emphasizes integration of multidisciplinary knowledge, scalability for mainstream buildings, and proactive approaches considering constraints and unknowns. The framework integrates the interrelated aspects of the built environment through a series of quantitative metrics that aim to improve environmental outcomes while optimizing building performance to achieve healthy, adaptive, and productive buildings.« less

E1 and M1 γ-strength functions in 144Nd

DOE PAGES

Voinov, A. V.; Grimes, S. M.

2015-12-14

Both E1 and M1 γ-strength functions below the neutron separation energy were analyzed based on experimental data from 143Nd(n,γ) 144Nd and 143Nd(n,γα) 140Ce reactions. It is confirmed that the commonly adopted E1 model based on the temperature dependence of the width of the giant dipole resonance works well. The popular M1 strength function due to the spin-flip magnetic resonance located near the neutron binding energy is not capable of reproducing experimental data. As a result, the low-energy enhancement of the M1 strength or the energy-independent model of Weisskopf, both leading to the low-energy strength sizable to E1 one, fit experimentalmore » data best.« less

Three good reasons for heart surgeons to understand cardiac metabolism.

PubMed

Doenst, Torsten; Bugger, Heiko; Schwarzer, Michael; Faerber, Gloria; Borger, Michael A; Mohr, Friedrich W

2008-05-01

It is the principal goal of cardiac surgeons to improve or reinstate contractile function with, through or after a surgical procedure on the heart. Uninterrupted contractile function of the heart is irrevocably linked to the uninterrupted supply of energy in the form of ATP. Thus, it would appear natural that clinicians interested in myocardial contractile function are interested in the way the heart generates ATP, i.e. the processes generally referred to as energy metabolism. Yet, it may appear that the relevance of energy metabolism in cardiac surgery is limited to the area of cardioplegia, which is a declining research interest. It is the goal of this review to change this trend and to illustrate the role and the therapeutic potential of metabolism and metabolic interventions for management. We present three compelling reasons why cardiac metabolism is of direct, practical interest to the cardiac surgeon and why a better understanding of energy metabolism might indeed result in improved surgical outcomes: (1) To understand cardioplegic arrest, ischemia and reperfusion, one needs a working knowledge of metabolism; (2) hyperglycemia is an underestimated and modifiable risk factor; (3) acute metabolic interventions can be effective in patients undergoing cardiac surgery.

Islet α cells and glucagon--critical regulators of energy homeostasis.

PubMed

Campbell, Jonathan E; Drucker, Daniel J

2015-06-01

Glucagon is secreted from islet α cells and controls blood levels of glucose in the fasting state. Impaired glucagon secretion predisposes some patients with type 1 diabetes mellitus (T1DM) to hypoglycaemia; whereas hyperglycaemia in patients with T1DM or type 2 diabetes mellitus (T2DM) is often associated with hyperglucagonaemia. Hence, therapeutic strategies to safely achieve euglycaemia in patients with diabetes mellitus now encompass bihormonal approaches to simultaneously deliver insulin and glucagon (in patients with T1DM) or reduce excess glucagon action (in patients with T1DM or T2DM). Glucagon also reduces food intake and increases energy expenditure through central and peripheral mechanisms, which suggests that activation of signalling through the glucagon receptor might be useful for controlling body weight. Here, we review new data that is relevant to understanding α-cell biology and glucagon action in the brain, liver, adipose tissue and heart, with attention to normal physiology, as well as conditions associated with dysregulated glucagon action. The feasibility and safety of current and emerging glucagon-based therapies that encompass both gain-of-function and loss-of-function approaches for the treatment of T1DM, T2DM and obesity is discussed in addition to developments, challenges and critical gaps in our knowledge that require additional investigation.

Recent Progress in Advanced Nanobiological Materials for Energy and Environmental Applications

PubMed Central

Choi, Hyo-Jick; Montemagno, Carlo D.

2013-01-01

In this review, we briefly introduce our efforts to reconstruct cellular life processes by mimicking natural systems and the applications of these systems to energy and environmental problems. Functional units of in vitro cellular life processes are based on the fabrication of artificial organelles using protein-incorporated polymersomes and the creation of bioreactors. This concept of an artificial organelle originates from the first synthesis of poly(siloxane)-poly(alkyloxazoline) block copolymers three decades ago and the first demonstration of protein activity in the polymer membrane a decade ago. The increased value of biomimetic polymers results from many research efforts to find new applications such as functionally active membranes and a biochemical-producing polymersome. At the same time, foam research has advanced to the point that biomolecules can be efficiently produced in the aqueous channels of foam. Ongoing research includes replication of complex biological processes, such as an artificial Calvin cycle for application in biofuel and specialty chemical production, and carbon dioxide sequestration. We believe that the development of optimally designed biomimetic polymers and stable/biocompatible bioreactors would contribute to the realization of the benefits of biomimetic systems. Thus, this paper seeks to review previous research efforts, examine current knowledge/key technical parameters, and identify technical challenges ahead. PMID:28788424

The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research.

PubMed

Cano, Isaac; Tényi, Ákos; Schueller, Christine; Wolff, Martin; Huertas Migueláñez, M Mercedes; Gomez-Cabrero, David; Antczak, Philipp; Roca, Josep; Cascante, Marta; Falciani, Francesco; Maier, Dieter

2014-11-28

Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu.

Pedagogical content knowledge: Knowledge of pedagogy novice teachers in mathematics learning on limit algebraic function

NASA Astrophysics Data System (ADS)

Ma'rufi, Budayasa, I. Ketut; Juniati, Dwi

2017-02-01

Teacher is one of the key aspects of student's achievement. Teachers should master content material taught, how to teach it, and can interpret the students' thinking so that students easily understand the subject matter. This research was a qualitative research that aimed at describing profile of PCK's teachers in mathematics on limit algebraic functions in terms of the differences of teaching experience. Pedagogical Content Knowledge (PCK) and understanding of teachers is defined as involving the relationship between knowledge of teaching materials, how to transfer the subject matter, and the knowledge of students in mathematics on limit algebraic functions that the subject matter may be understood by students. The PCK components in this research were knowledge of subject matter, knowledge of pedagogy, and knowledge of students. Knowledge of pedagogy defines as knowledge and understanding of teachers about the planning and organization of the learning and teaching strategy of limit algebraic function. The subjects were two mathematics high school teachers who teach in class XI IPS. Data were collected through observation of learning during five meetings and interviews before and after the lesson continued with qualitative data analysis. Focus of this article was to describe novice teacher's knowledge of student in mathematics learning on limit algebraic function. Based on the results of the analysis of qualitative data the data concluded that novice teacher's knowledge of pedagogy in mathematics on limit algebraic function showed: 1) in teaching the definitions tend to identify prior knowledge of the student experience with the material to be studied, but not in the form of a problem, 2) in posing the questions tend to be monotonous non lead and dig, 3) in response to student questions preservice teachers do not take advantage of the characteristics or the potential of other students, 4) in addressing the problem of students, tend to use the drill approach and did not give illustrations easily to understand by students, 5) in teaching application concepts, tend to explain procedurally, without explaining the reasons why these steps are carried out, 6) less varied in the use of learning strategies.

Molecular dynamics simulations of fluid cyclopropane with MP2/CBS-fitted intermolecular interaction potentials

NASA Astrophysics Data System (ADS)

Ho, Yen-Ching; Wang, Yi-Siang; Chao, Sheng D.

2017-08-01

Modeling fluid cycloalkanes with molecular dynamics simulations has proven to be a very challenging task partly because of lacking a reliable force field based on quantum chemistry calculations. In this paper, we construct an ab initio force field for fluid cyclopropane using the second-order Møller-Plesset perturbation theory. We consider 15 conformers of the cyclopropane dimer for the orientation sampling. Single-point energies at important geometries are calibrated by the coupled cluster with single, double, and perturbative triple excitation method. Dunning's correlation consistent basis sets (up to aug-cc-pVTZ) are used in extrapolating the interaction energies at the complete basis set limit. The force field parameters in a 9-site Lennard-Jones model are regressed by the calculated interaction energies without using empirical data. With this ab initio force field, we perform molecular dynamics simulations of fluid cyclopropane and calculate both the structural and dynamical properties. We compare the simulation results with those using an empirical force field and obtain a quantitative agreement for the detailed atom-wise radial distribution functions. The experimentally observed gross radial distribution function (extracted from the neutron scattering measurements) is well reproduced in our simulation. Moreover, the calculated self-diffusion coefficients and shear viscosities are in good agreement with the experimental data over a wide range of thermodynamic conditions. To the best of our knowledge, this is the first ab initio force field which is capable of competing with empirical force fields for simulating fluid cyclopropane.

Thermal radiative and thermodynamic properties of solid and liquid uranium and plutonium carbides in the visible-near-infrared range

NASA Astrophysics Data System (ADS)

Fisenko, Anatoliy I.; Lemberg, Vladimir F.

2016-09-01

The knowledge of thermal radiative and thermodynamic properties of uranium and plutonium carbides under extreme conditions is essential for designing a new metallic fuel materials for next generation of a nuclear reactor. The present work is devoted to the study of the thermal radiative and thermodynamic properties of liquid and solid uranium and plutonium carbides at their melting/freezing temperatures. The Stefan-Boltzmann law, total energy density, number density of photons, Helmholtz free energy density, internal energy density, enthalpy density, entropy density, heat capacity at constant volume, pressure, and normal total emissivity are calculated using experimental data for the frequency dependence of the normal spectral emissivity of liquid and solid uranium and plutonium carbides in the visible-near infrared range. It is shown that the thermal radiative and thermodynamic functions of uranium carbide have a slight difference during liquid-to-solid transition. Unlike UC, such a difference between these functions have not been established for plutonium carbide. The calculated values for the normal total emissivity of uranium and plutonium carbides at their melting temperatures is in good agreement with experimental data. The obtained results allow to calculate the thermal radiative and thermodynamic properties of liquid and solid uranium and plutonium carbides for any size of samples. Based on the model of Hagen-Rubens and the Wiedemann-Franz law, a new method to determine the thermal conductivity of metals and carbides at the melting points is proposed.

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

Inquiry-Based Science and Technology Enrichment Program: Green Earth Enhanced with Inquiry and Technology

NASA Astrophysics Data System (ADS)

Kim, Hanna

2011-12-01

This study investigated the effectiveness of a guided inquiry integrated with technology, in terms of female middle-school students' attitudes toward science/scientists and content knowledge regarding selective science concepts (e.g., Greenhouse Effect, Air/Water Quality, Alternative Energy, and Human Health). Thirty-five female students who were entering eighth grade attended an intensive, 1-week Inquiry-Based Science and Technology Enrichment Program which used a main theme, "Green Earth Enhanced with Inquiry and Technology." We used pre- and post-attitude surveys, pre- and post-science content knowledge tests, and selective interviews to collect data and measure changes in students' attitudes and content knowledge. The study results indicated that at the post-intervention measures, participants significantly improved their attitudes toward science and science-related careers and increased their content knowledge of selected science concepts ( p < .05).

Scattering-layer-induced energy storage function in polymer-based quasi-solid-state dye-sensitized solar cells.

PubMed

Zhang, Xi; Jiang, Hongrui

2015-03-09

Photo-self-charging cells (PSCs) are compact devices with dual functions of photoelectric conversion and energy storage. By introducing a scattering layer in polymer-based quasi-solid-state dye-sensitized solar cells, two-electrode PSCs with highly compact structure were obtained. The charge storage function stems from the formed ion channel network in the scattering layer/polymer electrolyte system. Both the photoelectric conversion and the energy storage functions are integrated in only the photoelectrode of such PSCs. This design of PSC could continuously output power as a solar cell with considerable efficiency after being photo-charged. Such PSCs could be applied in highly-compact mini power devices.

Energy.

PubMed

Chambers, David W

2012-01-01

Energy is the capacity to do the things we are capable of and desire to accomplish. Most often this is thought of in terms of PEP--personal energy potential--a reservoir of individual vivacity and zest for work. Like a battery, energy can be conceived of as a resource that is alternatively used and replenished. Transitions between activities, variety of tasks, and choices of what to spend energy on are part of energy management. Energy capacity can be thought of at four levels: (a) so little that harm is caused and extraordinary steps are needed for recovery, (b) a deficit that slightly impairs performance but will recover naturally, (c) the typical range of functioning, and (d) a surplus that may or may not be useful and requires continual investment to maintain. "Flow" is the experience of optimal energy use when challenges balance capacity as a result of imposing order on our environment. There are other energy resources in addition to personal vim. Effective work design reduces demands on energy. Money, office design, and knowledge are excellent substitutes for personal energy.

Evaluation of a school-based diabetes education intervention, an extension of Program ENERGY

NASA Astrophysics Data System (ADS)

Conner, Matthew David

Background: The prevalence of both obesity and type 2 diabetes in the United States has increased over the past two decades and rates remain high. The latest data from the National Center for Health Statistics estimates that 36% of adults and 17% of children and adolescents in the US are obese (CDC Adult Obesity, CDC Childhood Obesity). Being overweight or obese greatly increases one's risk of developing several chronic diseases, such as type 2 diabetes. Approximately 8% of adults in the US have diabetes, type 2 diabetes accounts for 90-95% of these cases. Type 2 diabetes in children and adolescents is still rare, however clinical reports suggest an increase in the frequency of diagnosis (CDC Diabetes Fact Sheet, 2011). Results from the Diabetes Prevention Program show that the incidence of type 2 diabetes can be reduced through the adoption of a healthier lifestyle among high-risk individuals (DPP, 2002). Objectives: This classroom-based intervention included scientific coverage of energy balance, diabetes, diabetes prevention strategies, and diabetes management. Coverage of diabetes management topics were included in lesson content to further the students' understanding of the disease. Measurable short-term goals of the intervention included increases in: general diabetes knowledge, diabetes management knowledge, and awareness of type 2 diabetes prevention strategies. Methods: A total of 66 sixth grade students at Tavelli Elementary School in Fort Collins, CO completed the intervention. The program consisted of nine classroom-based lessons; students participated in one lesson every two weeks. The lessons were delivered from November of 2005 to May of 2006. Each bi-weekly lesson included a presentation and interactive group activities. Participants completed two diabetes knowledge questionnaires at baseline and post intervention. A diabetes survey developed by Program ENERGY measured general diabetes knowledge and awareness of type 2 diabetes prevention strategies. The second questionnaire, adapted from a survey developed for the Starr County Diabetes Education Study (Garcia et al, 2001), measured general diabetes and diabetes management knowledge. A comparison group, a total of 19 students, also completed both surveys during the study period. Results: Significant increases (p<0.05) were seen in the post-intervention study group in general diabetes knowledge, diabetes management knowledge, and awareness of diabetes prevention strategies, when compared to the baseline study group and comparison group.

Intersection of argumentation and the use of multiple representations in the context of socioscientific issues

NASA Astrophysics Data System (ADS)

Namdar, Bahadir; Shen, Ji

2016-05-01

Using multiple representations and argumentation are two fundamental processes in science. With the advancements of information communication technologies, these two processes are blended more so than ever before. However, little is known about how these two processes interact with each other in student learning. Hence, we conducted a design-based study in order to distill the relationship between these two processes. Specifically, we designed a learning unit on nuclear energy and implemented it with a group of preservice middle school teachers. The participants used a web-based knowledge organization platform that incorporated three representational modes: textual, concept map, and pictorial. The participants organized their knowledge on nuclear energy by searching, sorting, clustering information through the use of these representational modes and argued about the nuclear energy issue. We found that the use of multiple representations and argumentation interacted with each other in a complex way. Based on our findings, we argue that the complexity can be unfolded in two aspects: (a) the use of multiple representations mediates argumentation in different forms and for different purposes; (b) the type of argumentation that leads to refinement of the use of multiple representations is often non-mediated and drawn from personal experience.

Improving density functional tight binding predictions of free energy surfaces for peptide condensation reactions in solution

NASA Astrophysics Data System (ADS)

Kroonblawd, Matthew; Goldman, Nir

First principles molecular dynamics using highly accurate density functional theory (DFT) is a common tool for predicting chemistry, but the accessible time and space scales are often orders of magnitude beyond the resolution of experiments. Semi-empirical methods such as density functional tight binding (DFTB) offer up to a thousand-fold reduction in required CPU hours and can approach experimental scales. However, standard DFTB parameter sets lack good transferability and calibration for a particular system is usually necessary. Force matching the pairwise repulsive energy term in DFTB to short DFT trajectories can improve the former's accuracy for chemistry that is fast relative to DFT simulation times (<10 ps), but the effects on slow chemistry and the free energy surface are not well-known. We present a force matching approach to increase the accuracy of DFTB predictions for free energy surfaces. Accelerated sampling techniques are combined with path collective variables to generate the reference DFT data set and validate fitted DFTB potentials without a priori knowledge of transition states. Accuracy of force-matched DFTB free energy surfaces is assessed for slow peptide-forming reactions by direct comparison to DFT results for particular paths. Extensions to model prebiotic chemistry under shock conditions are discussed. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Hybrid Functional Study of Sodium and Potassium Incorporation in Cu2ZnSnS4

NASA Astrophysics Data System (ADS)

Tse, Kin Fai; Wong, Manhoi; Zhang, Yiou; Zhang, Jingzhao; Zhu, Junyi

The thermodynamics of Na and K incorporation and its effects in Cu2ZnSnS4 (CZTS) is studied using density functional theory with hybrid functional. The allowed chemical potential of Na/K in CZTS is established. Formation energy calculations shows that Na can be significantly incorporated as both substitutional defects and interstitial defects, and incorporation of K related defects are generally less favorable. Transition energy calculations is performed showing that both Na and K exhibit benign defect properties and act as a p-type dopant. The qualitative disagreement between GGA with rigid band edge shifting and HSE calculations, formation of defect complexes, and implications in experiment will also be discussed. The understandings on the defect properties of Na and K provides an essential knowledge to further understand the surfactant effects of Na and K observed in experiments. This work is supported by General Research Fund Ref. No: 14319416.

An assessment of research and development leadership in ocean energy technologies

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

Bruch, V.L.

1994-04-01

Japan is clearly the leader in ocean energy technologies. The United Kingdom also has had many ocean energy research projects, but unlike Japan, most of the British projects have not progressed from the feasibility study stage to the demonstration stage. Federally funded ocean energy research in the US was stopped because it was perceived the technologies could not compete with conventional sources of fuel. Despite the probable small market for ocean energy technologies, the short sighted viewpoint of the US government regarding funding of these technologies may be harmful to US economic competitiveness. The technologies may have important uses inmore » other applications, such as offshore construction and oil and gas drilling. Discontinuing the research and development of these technologies may cause the US to lose knowledge and miss market opportunities. If the US wishes to maintain its knowledge base and a market presence for ocean energy technologies, it may wish to consider entering into a cooperative agreement with Japan and/or the United Kingdom. Cooperative agreements are beneficial not only for technology transfer but also for cost-sharing.« less

Design of a Knowledge Driven HIS

PubMed Central

Pryor, T. Allan; Clayton, Paul D.; Haug, Peter J.; Wigertz, Ove

1987-01-01

Design of the software architecture for a knowledge driven HIS is presented. In our design the frame has been used as the basic unit of knowledge representation. The structure of the frame is being designed to be sufficiently universal to contain knowledge required to implement not only expert systems, but almost all traditional HIS functions including ADT, order entry and results review. The design incorporates a two level format for the knowledge. The first level as ASCII records is used to maintain the knowledge base while the second level converted by special knowledge compilers to standard computer languages is used for efficient implementation of the knowledge applications.

Evaluations of Energy Spectra of Neutrons Emitted Promptly in Neutron-induced Fission of 235 U and 239 Pu

DOE PAGES

Neudecker, Denise; Talou, Patrick; Kawano, Toshihiko; ...

2018-02-01

The energy spectra of neutrons emitted promptly in the neutron-induced fission reactions of 235U and 239Pu were re-evaluated for ENDF/B-VIII.0. The evaluations presented here are based on a careful modeling of all relevant physics processes, an extensive analysis of experimental data and a detailed quantification of pertinent uncertainties. Energy spectra of neutrons emitted in up to fourth chance fission are considered and both compound and pre-equilibrium processes are included. Also, important nuclear model parameters, such as the average total kinetic energy of the fission fragments and the multiple chance fission probabilities, and their uncertainties are estimated based on experimental knowledge,more » model information and evaluated data. In addition to experimental information already available for ENDF/B-VII.1, these new evaluations make use of recently published experimental data either of high precision or spanning a broad incident energy range, information on legacy measurements explaining discrepancies and recently measured data of the average total kinetic energy as a function of incident neutron energy. The resulting evaluated data and covariances agree well with the experimental database used for the evaluation. However, the evaluated spectra are softer than the 235U and 239Pu ENDF/B-VII.1, JENDL-4.0 and JEFF-3.2 evaluations for incident neutron energies E inc ≤ 1.5 MeV and E inc ≤ 5 MeV, respectively. For E inc > 5 MeV, the evaluated spectra show structures due to the improved modeling which are not present in ENDF/B-VII.1 and JEFF-3.2 but can be observed in JENDL-4.0 evaluations. Part of these new evaluations were adopted for ENDF/B-VIII.0, while the ENDF/B-VII.1 239Pu PFNS was retained for E inc ≤ 5 MeV awaiting more conclusive experimental evidence.« less

Evaluations of Energy Spectra of Neutrons Emitted Promptly in Neutron-induced Fission of 235U and 239Pu

NASA Astrophysics Data System (ADS)

Neudecker, D.; Talou, P.; Kawano, T.; Kahler, A. C.; White, M. C.; Taddeucci, T. N.; Haight, R. C.; Kiedrowski, B.; O'Donnell, J. M.; Gomez, J. A.; Kelly, K. J.; Devlin, M.; Rising, M. E.

2018-02-01

The energy spectra of neutrons emitted promptly in the neutron-induced fission reactions of 235U and 239Pu were re-evaluated for ENDF/B-VIII.0. These evaluations are based on a careful modeling of all relevant physics processes, an extensive analysis of experimental data and a detailed quantification of pertinent uncertainties. Energy spectra of neutrons emitted in up to fourth chance fission are considered and both compound and pre-equilibrium processes are included. Also, important nuclear model parameters, such as the average total kinetic energy of the fission fragments and the multiple chance fission probabilities, and their uncertainties are estimated based on experimental knowledge, model information and evaluated data. In addition to experimental information already available for ENDF/B-VII.1, these new evaluations make use of recently published experimental data either of high precision or spanning a broad incident energy range, information on legacy measurements explaining discrepancies and recently measured data of the average total kinetic energy as a function of incident neutron energy. The resulting evaluated data and covariances agree well with the experimental database used for the evaluation. However, the evaluated spectra are softer than the 235U and 239Pu ENDF/B-VII.1, JENDL-4.0 and JEFF-3.2 evaluations for incident neutron energies Einc ≤ 1.5 MeV and Einc ≤ 5 MeV, respectively. For Einc > 5 MeV, the evaluated spectra show structures due to the improved modeling which are not present in ENDF/B-VII.1 and JEFF-3.2 but can be observed in JENDL-4.0 evaluations. Part of these new evaluations were adopted for ENDF/B-VIII.0, while the ENDF/B-VII.1 239Pu PFNS was retained for Einc ≤ 5 MeV awaiting more conclusive experimental evidence.

Evaluations of Energy Spectra of Neutrons Emitted Promptly in Neutron-induced Fission of 235 U and 239 Pu

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

Neudecker, Denise; Talou, Patrick; Kawano, Toshihiko

The energy spectra of neutrons emitted promptly in the neutron-induced fission reactions of 235U and 239Pu were re-evaluated for ENDF/B-VIII.0. The evaluations presented here are based on a careful modeling of all relevant physics processes, an extensive analysis of experimental data and a detailed quantification of pertinent uncertainties. Energy spectra of neutrons emitted in up to fourth chance fission are considered and both compound and pre-equilibrium processes are included. Also, important nuclear model parameters, such as the average total kinetic energy of the fission fragments and the multiple chance fission probabilities, and their uncertainties are estimated based on experimental knowledge,more » model information and evaluated data. In addition to experimental information already available for ENDF/B-VII.1, these new evaluations make use of recently published experimental data either of high precision or spanning a broad incident energy range, information on legacy measurements explaining discrepancies and recently measured data of the average total kinetic energy as a function of incident neutron energy. The resulting evaluated data and covariances agree well with the experimental database used for the evaluation. However, the evaluated spectra are softer than the 235U and 239Pu ENDF/B-VII.1, JENDL-4.0 and JEFF-3.2 evaluations for incident neutron energies E inc ≤ 1.5 MeV and E inc ≤ 5 MeV, respectively. For E inc > 5 MeV, the evaluated spectra show structures due to the improved modeling which are not present in ENDF/B-VII.1 and JEFF-3.2 but can be observed in JENDL-4.0 evaluations. Part of these new evaluations were adopted for ENDF/B-VIII.0, while the ENDF/B-VII.1 239Pu PFNS was retained for E inc ≤ 5 MeV awaiting more conclusive experimental evidence.« less

A geometric stochastic approach based on marked point processes for road mark detection from high resolution aerial images

NASA Astrophysics Data System (ADS)

Tournaire, O.; Paparoditis, N.

Road detection has been a topic of great interest in the photogrammetric and remote sensing communities since the end of the 70s. Many approaches dealing with various sensor resolutions, the nature of the scene or the wished accuracy of the extracted objects have been presented. This topic remains challenging today as the need for accurate and up-to-date data is becoming more and more important. Based on this context, we will study in this paper the road network from a particular point of view, focusing on road marks, and in particular dashed lines. Indeed, they are very useful clues, for evidence of a road, but also for tasks of a higher level. For instance, they can be used to enhance quality and to improve road databases. It is also possible to delineate the different circulation lanes, their width and functionality (speed limit, special lanes for buses or bicycles...). In this paper, we propose a new robust and accurate top-down approach for dashed line detection based on stochastic geometry. Our approach is automatic in the sense that no intervention from a human operator is necessary to initialise the algorithm or to track errors during the process. The core of our approach relies on defining geometric, radiometric and relational models for dashed lines objects. The model also has to deal with the interactions between the different objects making up a line, meaning that it introduces external knowledge taken from specifications. Our strategy is based on a stochastic method, and in particular marked point processes. Our goal is to find the objects configuration minimising an energy function made-up of a data attachment term measuring the consistency of the image with respect to the objects and a regularising term managing the relationship between neighbouring objects. To sample the energy function, we use Green algorithm's; coupled with a simulated annealing to find its minimum. Results from aerial images at various resolutions are presented showing that our approach is relevant and accurate as it can handle the most frequent layouts of dashed lines. Some issues, for instance, such as the relative weighting of both terms of the energy are also discussed in the conclusion.

Facilitating Subject Matter Expert (SME)-Built Knowledge Bases (KBS)

DTIC Science & Technology

2004-12-01

exists in the field of economics. Most economics textbooks articulate the desirability of maintaining low inflation, ceteris paribus. However, policy...might say that functional knowledge is what the economic policymakers have and rely on to realize the principles agreed upon in economics textbooks . Note

A domain-specific system for representing knowledge of both man-made objects and human actions. Evidence from a case with an association of deficits.

PubMed

Vannuscorps, Gilles; Pillon, Agnesa

2011-07-01

We report the single-case study of a brain-damaged individual, JJG, presenting with a conceptual deficit and whose knowledge of living things, man-made objects, and actions was assessed. The aim was to seek for empirical evidence pertaining to the issue of how conceptual knowledge of objects, both living things and man-made objects, is related to conceptual knowledge of actions at the functional level. We first found that JJG's conceptual knowledge of both man-made objects and actions was similarly impaired while his conceptual knowledge of living things was spared as well as his knowledge of unique entities. We then examined whether this pattern of association of a conceptual deficit for both man-made objects and actions could be accounted for, first, by the "sensory/functional" and, second, the "manipulability" account for category-specific conceptual impairments advocated within the Feature-Based-Organization theory of conceptual knowledge organization, by assessing, first, patient's knowledge of sensory compared to functional features, second, his knowledge of manipulation compared to functional features and, third, his knowledge of manipulable compared to non-manipulable objects and actions. The later assessment also allowed us to evaluate an account for the deficits in terms of failures of simulating the hand movements implied by manipulable objects and manual actions. The findings showed that, contrary to the predictions made by the "sensory/functional", the "manipulability", and the "failure-of-simulating" accounts for category-specific conceptual impairments, the patient's association of deficits for both man-made objects and actions was not associated with a disproportionate impairment of functional compared to sensory knowledge or of manipulation compared to functional knowledge; manipulable items were not more impaired than non-manipulable items either. In the general discussion, we propose to account for the patient's association of deficits by the hypothesis that concepts whose core property is that of being a mean of achieving a goal - like the concepts of man-made objects and of actions - are learned, represented and processed by a common domain-specific conceptual system, which would have evolved to allow human beings to quickly and efficiently design and understand means to achieve goals and purposes. Copyright © 2011 Elsevier Ltd. All rights reserved.

What determines transitions between energy- and moisture-limited evaporative regimes?

NASA Astrophysics Data System (ADS)

Haghighi, E.; Gianotti, D.; Akbar, R.; Salvucci, G.; Entekhabi, D.

2017-12-01

The relationship between evaporative fraction (EF) and soil moisture (SM) has traditionally been used in atmospheric and land-surface modeling communities to determine the strength of land-atmosphere coupling in the context of the dominant evaporative regime (energy- or moisture-limited). However, recent field observations reveal that EF-SM relationship is not unique and could vary substantially with surface and/or meteorological conditions. This implies that conventional EF-SM relationships (exclusive of surface and meteorological conditions) are embedded in more complex dependencies and that in fact it is a multi-dimensional function. To fill the fundamental knowledge gaps on the important role of varying surface and meteorological conditions not accounted for by the traditional evaporative regime conceptualization, we propose a generalized EF framework using a mechanistic pore-scale model for evaporation and energy partitioning over drying soil surfaces. Nonlinear interactions among the components of the surface energy balance are reflected in a critical SM that marks the onset of transition between energy- and moisture-limited evaporative regimes. The new generalized EF framework enables physically based estimates of the critical SM, and provides new insights into the origin of land surface EF partitioning linked to meteorological input data and the evolution of land surface temperature during surface drying that affect the relative efficiency of surface energy balance components. Our results offer new opportunities to advance predictive capabilities quantifying land-atmosphere coupling for a wide range of present and projected meteorological input data.

An experiment to verify that the weak interactions satisfy the strong equivalence principle. [electron capture and gravitational potential

NASA Technical Reports Server (NTRS)

Eby, P. B.

1978-01-01

The construction of a clock based on the beta decay process is proposed to test for any violations by the weak interaction of the strong equivalence principle bu determining whether the weak interaction coupling constant beta is spatially constant or whether it is a function of gravitational potential (U). The clock can be constructed by simply counting the beta disintegrations of some suitable source. The total number of counts are to be taken a measure of elapsed time. The accuracy of the clock is limited by the statistical fluctuations in the number of counts, N, which is equal to the square root of N. Increasing N gives a corresponding increase in accuracy. A source based on the electron capture process can be used so as to avoid low energy electron discrimination problems. Solid state and gaseous detectors are being considered. While the accuracy of this type of beta decay clock is much less than clocks based on the electromagnetic interaction, there is a corresponding lack of knowledge of the behavior of beta as a function of gravitational potential. No predictions from nonmetric theories as to variations in beta are available as yet, but they may occur at the U/sg C level.

Olfaction Under Metabolic Influences

PubMed Central

2012-01-01

Recently published work and emerging research efforts have suggested that the olfactory system is intimately linked with the endocrine systems that regulate or modify energy balance. Although much attention has been focused on the parallels between taste transduction and neuroendocrine controls of digestion due to the novel discovery of taste receptors and molecular components shared by the tongue and gut, the equivalent body of knowledge that has accumulated for the olfactory system, has largely been overlooked. During regular cycles of food intake or disorders of endocrine function, olfaction is modulated in response to changing levels of various molecules, such as ghrelin, orexins, neuropeptide Y, insulin, leptin, and cholecystokinin. In view of the worldwide health concern regarding the rising incidence of diabetes, obesity, and related metabolic disorders, we present a comprehensive review that addresses the current knowledge of hormonal modulation of olfactory perception and how disruption of hormonal signaling in the olfactory system can affect energy homeostasis. PMID:22832483

Development of user-centered interfaces to search the knowledge resources of the Virginia Henderson International Nursing Library.

PubMed

Jones, Josette; Harris, Marcelline; Bagley-Thompson, Cheryl; Root, Jane

2003-01-01

This poster describes the development of user-centered interfaces in order to extend the functionality of the Virginia Henderson International Nursing Library (VHINL) from library to web based portal to nursing knowledge resources. The existing knowledge structure and computational models are revised and made complementary. Nurses' search behavior is captured and analyzed, and the resulting search models are mapped to the revised knowledge structure and computational model.

Principle, design and validation of a power-generated magnetorheological energy absorber with velocity self-sensing capability

NASA Astrophysics Data System (ADS)

Bai, Xian-Xu; Zhong, Wei-Min; Zou, Qi; Zhu, An-Ding; Sun, Jun

2018-07-01

Based on the structural design concept of ‘functional integration’, this paper proposes the principle of a power-generated magnetorheological energy absorber with velocity self-sensing capability (PGMREA), which realizes the integration of controllable damping mechanism and mechanical energy-electrical energy conversion mechanism in structure profile and multiple functions in function profile, including controllable damping, power generation and velocity self-sensing. The controllable damping mechanism consists of an annular gap and a ball screw. The annular gap fulfilled with MR fluid that operates in pure shear mode under controllable electromagnetic field. The rotational damping torque generated from the controllable damping mechanism is translated to a linear damping force via the ball screw. The mechanical energy-electrical energy conversion mechanism is realized by the ball screw and a generator composed of a permanent magnet rotor and a generator stator. The ball screw based mechanical energy-electrical energy conversion mechanism converts the mechanical energy of excitations to electrical energy for storage or directly to power the controllable damping mechanism of the PGMREA. The velocity self-sensing capability of the PGMREA is achieved via signal processing using the mechanical energy-electrical energy conversion information. Based on the principle of the proposed PGMREA, the mathematical model of the PGMREA is established, including the damping force, generated power and self-sensing velocity. The electromagnetic circuit of the PGMREA is simulated and verified via a finite element analysis software ANSYS. The developed PGMREA prototype is experimentally tested on a servo-hydraulic testing system. The model-based predicted results and the experimental results are compared and analyzed.

The Photoelectric Effect: Experimental Confirmation Concerning a Widespread Misconception in the Theory

ERIC Educational Resources Information Center

Wong, Darren; Lee, Paul; Shenghan, Gao; Xuezhou, Wang; Qi, Huan Yan; Kit, Foong See

2011-01-01

The photoelectric effect is widely taught in schools and institutions. It is common knowledge that in order for photoelectrons to be emitted, the energy of the incoming photons must be greater than the work function of the irradiated metal (i.e. hv greater than [phi][subscript emitter]). However, what may not be as commonly known is that the…

Calculating phase diagrams using PANDAT and panengine

NASA Astrophysics Data System (ADS)

Chen, S.-L.; Zhang, F.; Xie, F.-Y.; Daniel, S.; Yan, X.-Y.; Chang, Y. A.; Schmid-Fetzer, R.; Oates, W. A.

2003-12-01

Knowledge of phase equilibria or phase diagrams and thermodynamic properties is important in alloy design and materials-processing simulation. In principle, stable phase equilibrium is uniquely determined by the thermodynamic properties of the system, such as the Gibbs energy functions of the phases. PANDAT, a new computer software package for multicomponent phase-diagram calculation, was developed under the guidance of this principle.

Determination of the state-of-charge in leadacid batteries by means of a reference cell

NASA Astrophysics Data System (ADS)

Armenta, C.

A knowledge of the state-of-charge of any battery is an essential requirement for system energy management and for battery life extension. In photovoltaic power plants and stand-alone photovoltaic installations, a knowledge of the state-of-charge helps one to predict remaining energy, to determine time remaining before battery turndown, and to avoid failures during operation. A reliable method of predicting the state-of-charge will allow reduced installation costs because less reserve capacity is needed to guarantee a reliable energy supply. We propose an on-line method based on simple electrical measurements combined with a new electrolyte agitation technique which avoids systematic control of the battery state-of-charge. The method is very accurate and reduces the standard error in the state-of-charge prediction.

Growing knowledge of the mTOR signaling network.

PubMed

Huang, Kezhen; Fingar, Diane C

2014-12-01

The kinase mTOR (mechanistic target of rapamycin) integrates diverse environmental signals and translates these cues into appropriate cellular responses. mTOR forms the catalytic core of at least two functionally distinct signaling complexes, mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2). mTORC1 promotes anabolic cellular metabolism in response to growth factors, nutrients, and energy and functions as a master controller of cell growth. While significantly less well understood than mTORC1, mTORC2 responds to growth factors and controls cell metabolism, cell survival, and the organization of the actin cytoskeleton. mTOR plays critical roles in cellular processes related to tumorigenesis, metabolism, immune function, and aging. Consequently, aberrant mTOR signaling contributes to myriad disease states, and physicians employ mTORC1 inhibitors (rapamycin and analogs) for several pathological conditions. The clinical utility of mTOR inhibition underscores the important role of mTOR in organismal physiology. Here we review our growing knowledge of cellular mTOR regulation by diverse upstream signals (e.g. growth factors; amino acids; energy) and how mTORC1 integrates these signals to effect appropriate downstream signaling, with a greater emphasis on mTORC1 over mTORC2. We highlight dynamic subcellular localization of mTORC1 and associated factors as an important mechanism for control of mTORC1 activity and function. We will cover major cellular functions controlled by mTORC1 broadly. While significant advances have been made in the last decade regarding the regulation and function of mTOR within complex cell signaling networks, many important findings remain to be discovered. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adjoint optimization of natural convection problems: differentially heated cavity

NASA Astrophysics Data System (ADS)

Saglietti, Clio; Schlatter, Philipp; Monokrousos, Antonios; Henningson, Dan S.

2017-12-01

Optimization of natural convection-driven flows may provide significant improvements to the performance of cooling devices, but a theoretical investigation of such flows has been rarely done. The present paper illustrates an efficient gradient-based optimization method for analyzing such systems. We consider numerically the natural convection-driven flow in a differentially heated cavity with three Prandtl numbers (Pr=0.15{-}7) at super-critical conditions. All results and implementations were done with the spectral element code Nek5000. The flow is analyzed using linear direct and adjoint computations about a nonlinear base flow, extracting in particular optimal initial conditions using power iteration and the solution of the full adjoint direct eigenproblem. The cost function for both temperature and velocity is based on the kinetic energy and the concept of entransy, which yields a quadratic functional. Results are presented as a function of Prandtl number, time horizons and weights between kinetic energy and entransy. In particular, it is shown that the maximum transient growth is achieved at time horizons on the order of 5 time units for all cases, whereas for larger time horizons the adjoint mode is recovered as optimal initial condition. For smaller time horizons, the influence of the weights leads either to a concentric temperature distribution or to an initial condition pattern that opposes the mean shear and grows according to the Orr mechanism. For specific cases, it could also been shown that the computation of optimal initial conditions leads to a degenerate problem, with a potential loss of symmetry. In these situations, it turns out that any initial condition lying in a specific span of the eigenfunctions will yield exactly the same transient amplification. As a consequence, the power iteration converges very slowly and fails to extract all possible optimal initial conditions. According to the authors' knowledge, this behavior is illustrated here for the first time.

ICME for Crashworthiness of TWIP Steels: From Ab Initio to the Crash Performance

NASA Astrophysics Data System (ADS)

Güvenç, O.; Roters, F.; Hickel, T.; Bambach, M.

2015-01-01

During the last decade, integrated computational materials engineering (ICME) emerged as a field which aims to promote synergetic usage of formerly isolated simulation models, data and knowledge in materials science and engineering, in order to solve complex engineering problems. In our work, we applied the ICME approach to a crash box, a common automobile component crucial to passenger safety. A newly developed high manganese steel was selected as the material of the component and its crashworthiness was assessed by simulated and real drop tower tests. The crashworthiness of twinning-induced plasticity (TWIP) steel is intrinsically related to the strain hardening behavior caused by the combination of dislocation glide and deformation twinning. The relative contributions of those to the overall hardening behavior depend on the stacking fault energy (SFE) of the selected material. Both the deformation twinning mechanism and the stacking fault energy are individually well-researched topics, but especially for high-manganese steels, the determination of the stacking-fault energy and the occurrence of deformation twinning as a function of the SFE are crucial to understand the strain hardening behavior. We applied ab initio methods to calculate the stacking fault energy of the selected steel composition as an input to a recently developed strain hardening model which models deformation twinning based on the SFE-dependent dislocation mechanisms. This physically based material model is then applied to simulate a drop tower test in order to calculate the energy absorption capacity of the designed component. The results are in good agreement with experiments. The model chain links the crash performance to the SFE and hence to the chemical composition, which paves the way for computational materials design for crashworthiness.

Distributed Knowledge-Based Systems

DTIC Science & Technology

1989-03-15

For example, patients with cerebral palsy , a disease affecting motor control, typically have several muscles that function improperly in different...phases of the gait cycle. The malfunctions in the case of cerebral palsy are improper contractions of the muscles - both in terms of the magnitude and...problem, if true, has serious implications for how knowledge acquisition should be done. Because some knowledge representation must be the target of

Analysis of Energy Industry Upgrading in Northeast China

NASA Astrophysics Data System (ADS)

Liu, Xiao-jing; Ji, Yu-liang; Guan, Bai-feng; Jing, Xin

2018-02-01

Promoting regional economic growth and realizing the transformation of the mode of economic growth are in industrial upgrading essence The product is a carrier that represents a series of links of production, management and marketing behind the enterprise, and is a comprehensive reflection of the knowledge and ability of a country or region. Based on the industrial spatial structure, this paper visualizes the industrial space in Northeast China from 2005 to 2015, analyzes the comparative advantages of the energy industry in Northeast China, and examines the status quo of the upgrade of the energy industry according to the industrial upgrading status. Based on the industrial spatial structure, Industry intensity in the industrial space, put forward the future direction of the energy industry upgrade and upgrade path.

Large-energy, narrow-bandwidth laser pulse at 1645 nm in a diode-pumped Er:YAG solid-state laser passively Q-switched by a monolayer graphene saturable absorber.

PubMed

Zhou, Rong; Tang, Pinghua; Chen, Yu; Chen, Shuqing; Zhao, Chujun; Zhang, Han; Wen, Shuangchun

2014-01-10

Nonlinear transmission parameters of monolayer graphene at 1645 nm were obtained. Based on the monolayer graphene saturable absorber, a 1532 nm LD pumped 1645 nm passively Q-switched Er:YAG laser was demonstrated. Under the pump power of 20.8 W, a 1645 nm Q-switched pulse with FWHM of 0.13 nm (without the use of etalon) and energy of 13.5 μJ per pulse can be obtained. To the best of our knowledge, this is the highest pulse energy for graphene-based passively Q-switched Er:YAG laseroperating at 1645 nm, suggesting the potentials of graphene materials for high-energy solid-state laser applications.

Atmospheric Fluorescence Yield

NASA Technical Reports Server (NTRS)

Adams, James H., Jr.; Christl, M. J.; Fountain, W. F.; Gregory, J. C.; Martens, K.; Sokolsky, P.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

Several existing and planned experiments estimate the energies of ultra-high energy cosmic rays from air showers using the atmospheric fluorescence from these showers. Accurate knowledge of the conversion from atmospheric fluorescence to energy loss by ionizing particles in the atmosphere is key to this technique. In this paper we discuss a small balloon-borne instrument to make the first in situ measurements versus altitude of the atmospheric fluorescence yield. The instrument can also be used in the lab to investigate the dependence of the fluorescence yield in air on temperature, pressure and the concentrations of other gases that present in the atmosphere. The results can be used to explore environmental effects on and improve the accuracy of cosmic ray energy measurements for existing ground-based experiments and future space-based experiments.

New Kohn-Sham density functional based on microscopic nuclear and neutron matter equations of state

NASA Astrophysics Data System (ADS)

Baldo, M.; Robledo, L. M.; Schuck, P.; Viñas, X.

2013-06-01

A new version of the Barcelona-Catania-Paris energy functional is applied to a study of nuclear masses and other properties. The functional is largely based on calculated ab initio nuclear and neutron matter equations of state. Compared to typical Skyrme functionals having 10-12 parameters apart from spin-orbit and pairing terms, the new functional has only 2 or 3 adjusted parameters, fine tuning the nuclear matter binding energy and fixing the surface energy of finite nuclei. An energy rms value of 1.58 MeV is obtained from a fit of these three parameters to the 579 measured masses reported in the Audi and Wapstra [Nucl. Phys. ANUPABL0375-947410.1016/j.nuclphysa.2003.11.003 729, 337 (2003)] compilation. This rms value compares favorably with the one obtained using other successful mean field theories, which range from 1.5 to 3.0 MeV for optimized Skyrme functionals and 0.7 to 3.0 for the Gogny functionals. The other properties that have been calculated and compared to experiment are nuclear radii, the giant monopole resonance, and spontaneous fission lifetimes.

Non-equilibrium plasma kinetics of reacting CO: an improved state to state approach

NASA Astrophysics Data System (ADS)

Pietanza, L. D.; Colonna, G.; Capitelli, M.

2017-12-01

Non-equilibrium plasma kinetics of reacting CO for conditions typically met in microwave discharges have been developed based on the coupling of excited state kinetics and the Boltzmann equation for the electron energy distribution function (EEDF). Particular attention is given to the insertion in the vibrational kinetics of a complete set of electron molecule resonant processes linking the whole vibrational ladder of the CO molecule, as well as to the role of Boudouard reaction, i.e. the process of forming CO2 by two vibrationally excited CO molecules, in shaping the vibrational distribution of CO and promoting reaction channels assisted by vibrational excitation (pure vibrational mechanisms, PVM). PVM mechanisms can become competitive with electron impact dissociation processes (DEM) in the activation of CO. A case study reproducing the conditions of a microwave discharge has been considered following the coupled kinetics also in the post discharge conditions. Results include the evolution of EEDF in discharge and post discharge conditions highlighting the role of superelastic vibrational and electronic collisions in shaping the EEDF. Moreover, PVM rate coefficients and DEM ones are studied as a function of gas temperature, showing a non-Arrhenius behavior, i.e. the rate coefficients increase with decreasing gas temperature as a result of a vibrational-vibrational (V-V) pumping up mechanism able to form plateaux in the vibrational distribution function. The accuracy of the results is discussed in particular in connection to the present knowledge of the activation energy of the Boudouard process.

Building Energy Consumption Pattern Analysis of Detached Housing for the Policy Decision Simulator

NASA Astrophysics Data System (ADS)

Lim, Jiyoun; Lee, Seung-Eon

2018-03-01

The Korean government announced its plan to raise the previous reduction goal of greenhouse gas emission from buildings by 26.9% until 2020 on July 2015. Therefore, policies regarding efficiency in the building energy are implemented fast, but the level of building owners and market understanding is low in general, and the government service system which supports decision making for implementing low-energy buildings has not been provided yet. The purpose of this study is to present the design direction for establishing user customized building energy database to perform a role to provide autonomous ecosystem of low-energy buildings. In order to reduce energy consumption in buildings, it is necessary to carry out the energy performance analysis based on the characteristics of target building. By analysing about 20-thousand cases of the amount of housing energy consumption in Korea, this study suggested the real energy consumption pattern by building types. Also, the energy performance of a building could be determined by energy consumption, but previous building energy consumption analysis programs required expert knowledge and experience in program usage, so it was difficult for normal building users to use such programs. Therefore, a measure to provide proper default using the level of data which general users with no expert knowledge regarding building energy could enter easily was suggested in this study.

Building validation tools for knowledge-based systems

NASA Technical Reports Server (NTRS)

Stachowitz, R. A.; Chang, C. L.; Stock, T. S.; Combs, J. B.

1987-01-01

The Expert Systems Validation Associate (EVA), a validation system under development at the Lockheed Artificial Intelligence Center for more than a year, provides a wide range of validation tools to check the correctness, consistency and completeness of a knowledge-based system. A declarative meta-language (higher-order language), is used to create a generic version of EVA to validate applications written in arbitrary expert system shells. The architecture and functionality of EVA are presented. The functionality includes Structure Check, Logic Check, Extended Structure Check (using semantic information), Extended Logic Check, Semantic Check, Omission Check, Rule Refinement, Control Check, Test Case Generation, Error Localization, and Behavior Verification.

Model-driven development of covariances for spatiotemporal environmental health assessment.

PubMed

Kolovos, Alexander; Angulo, José Miguel; Modis, Konstantinos; Papantonopoulos, George; Wang, Jin-Feng; Christakos, George

2013-01-01

Known conceptual and technical limitations of mainstream environmental health data analysis have directed research to new avenues. The goal is to deal more efficiently with the inherent uncertainty and composite space-time heterogeneity of key attributes, account for multi-sourced knowledge bases (health models, survey data, empirical relationships etc.), and generate more accurate predictions across space-time. Based on a versatile, knowledge synthesis methodological framework, we introduce new space-time covariance functions built by integrating epidemic propagation models and we apply them in the analysis of existing flu datasets. Within the knowledge synthesis framework, the Bayesian maximum entropy theory is our method of choice for the spatiotemporal prediction of the ratio of new infectives (RNI) for a case study of flu in France. The space-time analysis is based on observations during a period of 15 weeks in 1998-1999. We present general features of the proposed covariance functions, and use these functions to explore the composite space-time RNI dependency. We then implement the findings to generate sufficiently detailed and informative maps of the RNI patterns across space and time. The predicted distributions of RNI suggest substantive relationships in accordance with the typical physiographic and climatologic features of the country.

The CROPROTECT project and wider opportunities to improve farm productivity through web-based knowledge exchange.

PubMed

Bruce, Toby J A

2016-05-01

A key global 21st century challenge is to maximize agricultural production while minimizing use of resources such as land, water, and energy to meet rising demand for produce. To meet this challenge, while also adapting to climate change, agriculture will have to become more knowledge intensive and deploy smarter farming techniques. The intention of this study was to: (1) Highlight the opportunity for web-based knowledge exchange to increase farm productivity and thus contribute to achieving food and energy security, (2) Give some examples of online farming information services such as the "CROPROTECT" tool I am developing in the UK, the CABI "Plantwise" Knowledge Bank and the IRRI "Rice Doctor," and (3) Consider lessons learnt so far. There are huge opportunities to facilitate knowledge exchange through online systems for farmers and people who advise farmers. CROPROTECT is interacting with users to determine priorities in terms of the pests, weeds, and diseases covered and is providing key information to assist with their management. Knowledge is a critical input for farming systems. Crop protection in particular is becoming more difficult due to evolution of pest resistance and changes in legislation. Up to date information can be made rapidly available and shared online through websites and smartphone Apps. Agricultural extension no longer relies solely on physical meetings and printed documents. The capacity to share information via the Internet is tremendous with its potential to reach a wide audience in the farming community, to provide rapid updates and to interact more with the users. However, in an era of information deluge, accessing relevant information and ensuring reliability are essential considerations. There is also a need to bring science and farming communities together to turn information into relevant farming knowledge.

Quantification of the Water-Energy Nexus in Beijing City Based on Copula Analysis

NASA Astrophysics Data System (ADS)

Cai, J.; Cai, Y.

2017-12-01

Water resource and energy resource are intimately and highly interwoven, called ``water-energy nexus", which poses challenges for the sustainable management of water resource and energy resource. In this research, the Copula analysis method is first proposed to be applied in "water-energy nexus" field to clarify the internal relationship of water resource and energy resource, which is a favorable tool to explore the relevance among random variables. Beijing City, the capital of China, is chosen as a case study. The marginal distribution functions of water resource and energy resource are analyzed first. Then the Binary Copula function is employed to construct the joint distribution function of "water-energy nexus" to quantify the inherent relationship between water resource and energy resource. The results show that it is more appropriate to apply Lognormal distribution to establish the marginal distribution function of water resource. Meanwhile, Weibull distribution is more feasible to describe the marginal distribution function of energy resource. Furthermore, it is more suitable to adopt the Bivariate Normal Copula function to construct the joint distribution function of "water-energy nexus" in Beijing City. The findings can help to identify and quantify the "water-energy nexus". In addition, our findings can provide reasonable policy recommendations on the sustainable management of water resource and energy resource to promote regional coordinated development.

Treatment of Electronic Energy Level Transition and Ionization Following the Particle-Based Chemistry Model

NASA Technical Reports Server (NTRS)

Liechty, Derek S.; Lewis, Mark

2010-01-01

A new method of treating electronic energy level transitions as well as linking ionization to electronic energy levels is proposed following the particle-based chemistry model of Bird. Although the use of electronic energy levels and ionization reactions in DSMC are not new ideas, the current method of selecting what level to transition to, how to reproduce transition rates, and the linking of the electronic energy levels to ionization are, to the author s knowledge, novel concepts. The resulting equilibrium temperatures are shown to remain constant, and the electronic energy level distributions are shown to reproduce the Boltzmann distribution. The electronic energy level transition rates and ionization rates due to electron impacts are shown to reproduce theoretical and measured rates. The rates due to heavy particle impacts, while not as favorable as the electron impact rates, compare favorably to values from the literature. Thus, these new extensions to the particle-based chemistry model of Bird provide an accurate method for predicting electronic energy level transition and ionization rates in gases.

Integration of object-oriented knowledge representation with the CLIPS rule based system

NASA Technical Reports Server (NTRS)

Logie, David S.; Kamil, Hasan

1990-01-01

The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

Influence of spokes on the ionized metal flux fraction in chromium high power impulse magnetron sputtering

NASA Astrophysics Data System (ADS)

Biskup, B.; Maszl, C.; Breilmann, W.; Held, J.; Böke, M.; Benedikt, J.; von Keudell, A.

2018-03-01

High power impulse magnetron sputtering (HiPIMS) discharges are an excellent tool for deposition of thin films with superior properties. By adjusting the plasma parameters, an energetic metal and reactive species growth flux can be controlled. This control requires, however, a quantitative knowledge of the ion-to-neutral ratio in the growth flux and of the ion energy distribution function to optimize the deposited energy per incorporated atom in the film. This quantification is performed by combining two diagnostics, a quartz crystal microbalance (QCM) combined with an ion-repelling grid system (IReGS) to discriminate ions versus neutrals and a HIDEN EQP plasma monitor to measure the ion energy distribution function (IEDF). This approach yields the ionized metal flux fraction (IMFF) as the ionization degree in the growth flux. This is correlated to the plasma performance recorded by time resolved ICCD camera measurements, which allow to identify the formation of pronounced ionization zones, so called spokes, in the HiPIMS plasma. Thereby an automatic technique was developed to identify the spoke mode number. The data indicates two distinct regimes with respect to spoke formation that occur with increasing peak power, a stochastic regime with no spokes at low peak powers followed by a regime with distinct spokes at varying mode numbers at higher peak powers. The IMFF increases with increasing peak power reaching values of almost 80% at very high peak powers. The transition in between the two regimes coincides with a pronounced change in the IMFF. This change indicates that the formation of spokes apparently counteracts the return effect in HiPIMS. Based on the IMFF and the mean energy of the ions, the energy per deposited atom together with the overall energy flux onto the substrate is calculated. This allows us to determine an optimum for the peak power density around 0.5 kW cm-2 for chromium HiPIMS.

[A network of LIFE projects to promote the transfer and exchange of knowledge on environment and health].

PubMed

Cori, Liliana; Carducci, Annalaura; Donzelli, Gabriele; La Rocca, Cinzia; Bianchi, Fabrizio

2018-01-01

Eleven projects within the LIFE programme (through which the Directorate-General for Environment of the European Commission provides funding for projects aim at protecting environment and nature) addressing environmental-health-related issues have been involved in a collaborative network called KTE LIFE EnvHealth Network. The shared issues tackled by that projects are knowledge transfer and exchange (KTE). The objective of the LIFE programme is to support the implementation of the environmental legislation in the European Union, to provide new tools and knowledge that will help to better protect both the territory and the communities. Transferring knowledge to decision makers, at the appropriate and effective level, is therefore a central function of the projects. The Network promotes national and international networking, which intends to involve other projects, to provide methodological support, to make information and successful practices circulate, with the aim of multiplying the energies of each project involved.

Variability in energy density of forage fishes from the Bay of Biscay (north-east Atlantic Ocean): reliability of functional grouping based on prey quality.

PubMed

Spitz, J; Jouma'a, J

2013-06-01

Energy densities of 670 fishes belonging to nine species were measured to evaluate intraspecific variability. Functional groups based on energy density appeared to be sufficiently robust to individual variability to provide a classification of forage fish quality applicable in a variety of ecological fields including ecosystem modelling. © 2013 The Authors. Journal of Fish Biology © 2013 The Fisheries Society of the British Isles.

Genomics Portals: integrative web-platform for mining genomics data.

PubMed

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genomics Portals: integrative web-platform for mining genomics data

PubMed Central

2010-01-01

Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org. PMID:20070909

Hartree-Fock implementation using a Laguerre-based wave function for the ground state and correlation energies of two-electron atoms.

PubMed

King, Andrew W; Baskerville, Adam L; Cox, Hazel

2018-03-13

An implementation of the Hartree-Fock (HF) method using a Laguerre-based wave function is described and used to accurately study the ground state of two-electron atoms in the fixed nucleus approximation, and by comparison with fully correlated (FC) energies, used to determine accurate electron correlation energies. A variational parameter A is included in the wave function and is shown to rapidly increase the convergence of the energy. The one-electron integrals are solved by series solution and an analytical form is found for the two-electron integrals. This methodology is used to produce accurate wave functions, energies and expectation values for the helium isoelectronic sequence, including at low nuclear charge just prior to electron detachment. Additionally, the critical nuclear charge for binding two electrons within the HF approach is calculated and determined to be Z HF C =1.031 177 528.This article is part of the theme issue 'Modern theoretical chemistry'. © 2018 The Author(s).

Bioenergetics of the Archaea

PubMed Central

Schäfer, Günter; Engelhard, Martin; Müller, Volker

1999-01-01

In the late 1970s, on the basis of rRNA phylogeny, Archaea (archaebacteria) was identified as a distinct domain of life besides Bacteria (eubacteria) and Eucarya. Though forming a separate domain, archaea display an enormous diversity of lifestyles and metabolic capabilities. Many archaeal species are adapted to extreme environments with respect to salinity, temperatures around the boiling point of water, and/or extremely alkaline or acidic pH. This has posed the challenge of studying the molecular and mechanistic bases on which these organisms can cope with such adverse conditions. This review considers our cumulative knowledge on archaeal mechanisms of primary energy conservation, in relationship to those of bacteria and eucarya. Although the universal principle of chemiosmotic energy conservation also holds for Archaea, distinct features have been discovered with respect to novel ion-transducing, membrane-residing protein complexes and the use of novel cofactors in bioenergetics of methanogenesis. From aerobically respiring archaea, unusual electron-transporting supercomplexes could be isolated and functionally resolved, and a proposal on the organization of archaeal electron transport chains has been presented. The unique functions of archaeal rhodopsins as sensory systems and as proton or chloride pumps have been elucidated on the basis of recent structural information on the atomic scale. Whereas components of methanogenesis and of phototrophic energy transduction in halobacteria appear to be unique to archaea, respiratory complexes and the ATP synthase exhibit some chimeric features with respect to their evolutionary origin. Nevertheless, archaeal ATP synthases are to be considered distinct members of this family of secondary energy transducers. A major challenge to future investigations is the development of archaeal genetic transformation systems, in order to gain access to the regulation of bioenergetic systems and to overproducers of archaeal membrane proteins as a prerequisite for their crystallization. PMID:10477309

DFT-based method for more accurate adsorption energies: An adaptive sum of energies from RPBE and vdW density functionals

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

Hensley, Alyssa J. R.; Ghale, Kushal; Rieg, Carolin

In recent years, the popularity of density functional theory with periodic boundary conditions (DFT) has surged for the design and optimization of functional materials. However, no single DFT exchange–correlation functional currently available gives accurate adsorption energies on transition metals both when bonding to the surface is dominated by strong covalent or ionic bonding and when it has strong contributions from van der Waals interactions (i.e., dispersion forces). Here we present a new, simple method for accurately predicting adsorption energies on transition-metal surfaces based on DFT calculations, using an adaptively weighted sum of energies from RPBE and optB86b-vdW (or optB88-vdW) densitymore » functionals. This method has been benchmarked against a set of 39 reliable experimental energies for adsorption reactions. Our results show that this method has a mean absolute error and root mean squared error relative to experiments of 13.4 and 19.3 kJ/mol, respectively, compared to 20.4 and 26.4 kJ/mol for the BEEF-vdW functional. For systems with large van der Waals contributions, this method decreases these errors to 11.6 and 17.5 kJ/mol. Furthermore, this method provides predictions of adsorption energies both for processes dominated by strong covalent or ionic bonding and for those dominated by dispersion forces that are more accurate than those of any current standard DFT functional alone.« less

DFT-based method for more accurate adsorption energies: An adaptive sum of energies from RPBE and vdW density functionals

DOE PAGES

Hensley, Alyssa J. R.; Ghale, Kushal; Rieg, Carolin; ...

2017-01-26

In recent years, the popularity of density functional theory with periodic boundary conditions (DFT) has surged for the design and optimization of functional materials. However, no single DFT exchange–correlation functional currently available gives accurate adsorption energies on transition metals both when bonding to the surface is dominated by strong covalent or ionic bonding and when it has strong contributions from van der Waals interactions (i.e., dispersion forces). Here we present a new, simple method for accurately predicting adsorption energies on transition-metal surfaces based on DFT calculations, using an adaptively weighted sum of energies from RPBE and optB86b-vdW (or optB88-vdW) densitymore » functionals. This method has been benchmarked against a set of 39 reliable experimental energies for adsorption reactions. Our results show that this method has a mean absolute error and root mean squared error relative to experiments of 13.4 and 19.3 kJ/mol, respectively, compared to 20.4 and 26.4 kJ/mol for the BEEF-vdW functional. For systems with large van der Waals contributions, this method decreases these errors to 11.6 and 17.5 kJ/mol. Furthermore, this method provides predictions of adsorption energies both for processes dominated by strong covalent or ionic bonding and for those dominated by dispersion forces that are more accurate than those of any current standard DFT functional alone.« less

Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

PubMed

Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

2017-03-01

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity. Copyright © 2017. Published by Elsevier Inc.

Description of quasiparticle and satellite properties via cumulant expansions of the retarded one-particle Green's function

DOE PAGES

Mayers, Matthew Z.; Hybertsen, Mark S.; Reichman, David R.

2016-08-22

A cumulant-based GW approximation for the retarded one-particle Green's function is proposed, motivated by an exact relation between the improper Dyson self-energy and the cumulant generating function. We explore qualitative aspects of this method within a simple one-electron independent phonon model, where it is seen that the method preserves the energy moment of the spectral weight while also reproducing the exact Green's function in the weak-coupling limit. For the three-dimensional electron gas, this method predicts multiple satellites at the bottom of the band, albeit with inaccurate peak spacing. But, its quasiparticle properties and correlation energies are more accurate than bothmore » previous cumulant methods and standard G0W0. These results point to features that may be exploited within the framework of cumulant-based methods and suggest promising directions for future exploration and improvements of cumulant-based GW approaches.« less

Surface chemistry of oxygen on aluminum--Performance of the density functionals: PBE, PBE0, M06, and M06-L.

PubMed

Lousada, Cláudio M; Korzhavyi, Pavel A

2016-04-05

We investigated the performance of the density functional theory (DFT) functionals PBE, PBE0, M06, and M06-L for describing the molecular and dissociative adsorption of O2 onto pure and doped Al(111) surfaces. Adsorption of O2 was studied at the perfect Al(111) surface and compared with the case where an additional Al atom was present as an adatom. Additionally, we studied how these functionals perform when different dopants are present at the Al(111) surface in two distinct geometries: as an adatom or as a substitutional atom replacing an Al atom. The performance of the different functionals is greatly affected by the surface geometry. The inclusion of Hartree-Fock exchange in the functional leads to slight differences in adsorption energies for molecular adsorption of O2 . These differences become very pronounced for dissociative adsorption, with the hybrids PBE0 and M06 predicting more exergonic adsorption than PBE and M06-L. Furthermore, PBE0 and M06 predicted trends in adsorption energies for defective and perfect surfaces which are in line with the experimental knowledge of the effects of surface defects in adsorption energies. The predictions of the non-hybrids PBE and M06-L point in the opposite direction. The analysis of the contributions of the van der Waals (vdW) forces to the adsorption energies reveals that the PBE and PBE0 functionals have similar difficulties in describing vdW interactions for molecular adsorption of O2 while the M06 functional can give a description of these forces with an accuracy which is at least similar to that of the correction of the D3 type. © 2015 Wiley Periodicals, Inc.

An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong

2012-10-01

In this paper, a novel lesion segmentation within breast ultrasound (BUS) image based on the cellular automata principle is proposed. Its energy transition function is formulated based on global image information difference and local image information difference using different energy transfer strategies. First, an energy decrease strategy is used for modeling the spatial relation information of pixels. For modeling global image information difference, a seed information comparison function is developed using an energy preserve strategy. Then, a texture information comparison function is proposed for considering local image difference in different regions, which is helpful for handling blurry boundaries. Moreover, two neighborhood systems (von Neumann and Moore neighborhood systems) are integrated as the evolution environment, and a similarity-based criterion is used for suppressing noise and reducing computation complexity. The proposed method was applied to 205 clinical BUS images for studying its characteristic and functionality, and several overlapping area error metrics and statistical evaluation methods are utilized for evaluating its performance. The experimental results demonstrate that the proposed method can handle BUS images with blurry boundaries and low contrast well and can segment breast lesions accurately and effectively.

Ab Initio-Based Kinetic Modeling for the Design of Molecular Catalysts: The Case of H 2 Production Electrocatalysts

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

Ho, Ming-Hsun; Rousseau, Roger; Roberts, John A. S.

2015-09-04

Design of fast, efficient electrocatalysts for energy production and energy utilization requires a systematic approach to predict and tune the energetics of reaction intermediates and the kinetic barriers between them as well as to tune reaction conditions (e.g., concentration of reactants, acidity of the reaction medium, and applied electric potential). Thermodynamics schemes based on the knowledge of pKa values, hydride donor ability, redox potentials, and other relevant thermodynamic properties have been demonstrated to be very effective for exploring possible reaction pathways. We seek to identify high-energy intermediates, which may represent a catalytic bottleneck, and low-energy intermediates, which may represent amore » thermodynamic sink. In this study, working on a well-established Ni-based bioinspired electrocatalyst for H2 production, we performed a detailed kinetic analysis of the catalytic pathways to assess the limitations of our current (standard state) thermodynamic analysis with respect to prediction of optimal catalyst performance. To this end, we developed a microkinetic model based on extensive ab initio simulations. The model was validated against available experimental data, and it reproduces remarkably well the observed turnover rate as a function of the acid concentration and catalytic conditions, providing valuable information on the main factors limiting catalysis. Using this kinetic analysis as a reference, we show that indeed a purely thermodynamic analysis of the possible reaction pathways provides us with valuable information, such as a qualitative picture of the species involved during catalysis, identification of the possible branching points, and the origin of the observed overpotential, which are critical insights for electrocatalyst design. However, a significant limitation of this approach is understanding how these insights relate to rate, which is an equally critical piece of information. Taking our analysis a step further, we show that the kinetic model can easily be extended to different catalytic conditions by using linear free energy relationships for activation barriers based on simple thermodynamics quantities, such as pKa values. We also outline a possible procedure to extend it to other catalytic platforms, making it a general and effective way to design catalysts with improved performance.« less

A web-based knowledge management system integrating Western and Traditional Chinese Medicine for relational medical diagnosis.

PubMed

Herrera-Hernandez, Maria C; Lai-Yuen, Susana K; Piegl, Les A; Zhang, Xiao

2016-10-26

This article presents the design of a web-based knowledge management system as a training and research tool for the exploration of key relationships between Western and Traditional Chinese Medicine, in order to facilitate relational medical diagnosis integrating these mainstream healing modalities. The main goal of this system is to facilitate decision-making processes, while developing skills and creating new medical knowledge. Traditional Chinese Medicine can be considered as an ancient relational knowledge-based approach, focusing on balancing interrelated human functions to reach a healthy state. Western Medicine focuses on specialties and body systems and has achieved advanced methods to evaluate the impact of a health disorder on the body functions. Identifying key relationships between Traditional Chinese and Western Medicine opens new approaches for health care practices and can increase the understanding of human medical conditions. Our knowledge management system was designed from initial datasets of symptoms, known diagnosis and treatments, collected from both medicines. The datasets were subjected to process-oriented analysis, hierarchical knowledge representation and relational database interconnection. Web technology was implemented to develop a user-friendly interface, for easy navigation, training and research. Our system was prototyped with a case study on chronic prostatitis. This trial presented the system's capability for users to learn the correlation approach, connecting knowledge in Western and Traditional Chinese Medicine by querying the database, mapping validated medical information, accessing complementary information from official sites, and creating new knowledge as part of the learning process. By addressing the challenging tasks of data acquisition and modeling, organization, storage and transfer, the proposed web-based knowledge management system is presented as a tool for users in medical training and research to explore, learn and update relational information for the practice of integrated medical diagnosis. This proposal in education has the potential to enable further creation of medical knowledge from both Traditional Chinese and Western Medicine for improved care providing. The presented system positively improves the information visualization, learning process and knowledge sharing, for training and development of new skills for diagnosis and treatment, and a better understanding of medical diseases. © IMechE 2016.

Design of an assessment to probe teachers' content knowledge for teaching: An example from energy in high school physics

NASA Astrophysics Data System (ADS)

Etkina, Eugenia; Gitomer, Drew; Iaconangelo, Charles; Phelps, Geoffrey; Seeley, Lane; Vokos, Stamatis

2018-06-01

Research into teacher learning and practice over the last three decades shows that the teachers of a specific subject need to possess knowledge that is different from the knowledge of other content experts. Yet this specialized version of content knowledge that teachers need to plan instruction, respond to student ideas, and assess student understanding in real time is a theoretically elusive construct. It is crucial for the fields of precollege teacher preparation, teacher professional education, and postsecondary faculty professional development to (a) clarify the construct that underlies this specialized content knowledge, (b) operationalize it in some domain, (c) measure it in both static contexts and as it is enacted in the classroom, and (d) correlate its presence with "richness" of classroom instruction and its effect on student learning. This paper documents a piece of a multiyear, multi-institutional effort to investigate points (a)-(d) in the domain of energy in the first high school physics course. In particular, we describe the framework that we developed to clarify content knowledge for teaching in the context of high school energy learning. We then outline the process through which we developed, tested, and refined a "paper-and-pencil" assessment administered on a computer and discuss the substantive and psychometric features of several items based on a field test of the final form of the assessment. We choose to discuss these items for a dual purpose: to illustrate the application of our general framework and to present performance findings from a sample of 362 practicing high school teachers of physics.

Epistemological Beliefs and Epistemic Strategies in Self-Regulated Learning

ERIC Educational Resources Information Center

Richter, Tobias; Schmid, Sebastian

2010-01-01

How do epistemological attitudes and beliefs influence learning from text? We conceptualize epistemological attitudes and beliefs as components of metacognitive knowledge. As such, they serve an important function in regulating the use of epistemic strategies such as knowledge-based validation of information and checking arguments for internal…

Standards for Medical Library Technicians, Medical Library Association.

ERIC Educational Resources Information Center

Medical Library Association, Chicago, IL.

A medical library technician is a semiprofessional library employee whose duties require knowledge and skill based on a minimum of two years' general college education that includes library instruction beyond the clerical level. The medical library technician must have a practical knowledge of library functions and services, an understanding of…

STRUM: structure-based prediction of protein stability changes upon single-point mutation.

PubMed

Quan, Lijun; Lv, Qiang; Zhang, Yang

2016-10-01

Mutations in human genome are mainly through single nucleotide polymorphism, some of which can affect stability and function of proteins, causing human diseases. Several methods have been proposed to predict the effect of mutations on protein stability; but most require features from experimental structure. Given the fast progress in protein structure prediction, this work explores the possibility to improve the mutation-induced stability change prediction using low-resolution structure modeling. We developed a new method (STRUM) for predicting stability change caused by single-point mutations. Starting from wild-type sequences, 3D models are constructed by the iterative threading assembly refinement (I-TASSER) simulations, where physics- and knowledge-based energy functions are derived on the I-TASSER models and used to train STRUM models through gradient boosting regression. STRUM was assessed by 5-fold cross validation on 3421 experimentally determined mutations from 150 proteins. The Pearson correlation coefficient (PCC) between predicted and measured changes of Gibbs free-energy gap, ΔΔG, upon mutation reaches 0.79 with a root-mean-square error 1.2 kcal/mol in the mutation-based cross-validations. The PCC reduces if separating training and test mutations from non-homologous proteins, which reflects inherent correlations in the current mutation sample. Nevertheless, the results significantly outperform other state-of-the-art methods, including those built on experimental protein structures. Detailed analyses show that the most sensitive features in STRUM are the physics-based energy terms on I-TASSER models and the conservation scores from multiple-threading template alignments. However, the ΔΔG prediction accuracy has only a marginal dependence on the accuracy of protein structure models as long as the global fold is correct. These data demonstrate the feasibility to use low-resolution structure modeling for high-accuracy stability change prediction upon point mutations. http://zhanglab.ccmb.med.umich.edu/STRUM/ CONTACT: qiang@suda.edu.cn and zhng@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

STRUM: structure-based prediction of protein stability changes upon single-point mutation

PubMed Central

Quan, Lijun; Lv, Qiang; Zhang, Yang

2016-01-01

Motivation: Mutations in human genome are mainly through single nucleotide polymorphism, some of which can affect stability and function of proteins, causing human diseases. Several methods have been proposed to predict the effect of mutations on protein stability; but most require features from experimental structure. Given the fast progress in protein structure prediction, this work explores the possibility to improve the mutation-induced stability change prediction using low-resolution structure modeling. Results: We developed a new method (STRUM) for predicting stability change caused by single-point mutations. Starting from wild-type sequences, 3D models are constructed by the iterative threading assembly refinement (I-TASSER) simulations, where physics- and knowledge-based energy functions are derived on the I-TASSER models and used to train STRUM models through gradient boosting regression. STRUM was assessed by 5-fold cross validation on 3421 experimentally determined mutations from 150 proteins. The Pearson correlation coefficient (PCC) between predicted and measured changes of Gibbs free-energy gap, ΔΔG, upon mutation reaches 0.79 with a root-mean-square error 1.2 kcal/mol in the mutation-based cross-validations. The PCC reduces if separating training and test mutations from non-homologous proteins, which reflects inherent correlations in the current mutation sample. Nevertheless, the results significantly outperform other state-of-the-art methods, including those built on experimental protein structures. Detailed analyses show that the most sensitive features in STRUM are the physics-based energy terms on I-TASSER models and the conservation scores from multiple-threading template alignments. However, the ΔΔG prediction accuracy has only a marginal dependence on the accuracy of protein structure models as long as the global fold is correct. These data demonstrate the feasibility to use low-resolution structure modeling for high-accuracy stability change prediction upon point mutations. Availability and Implementation: http://zhanglab.ccmb.med.umich.edu/STRUM/ Contact: qiang@suda.edu.cn and zhng@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27318206

The research and application of the power big data

NASA Astrophysics Data System (ADS)

Zhang, Suxiang; Zhang, Dong; Zhang, Yaping; Cao, Jinping; Xu, Huiming

2017-01-01

Facing the increasing environment crisis, how to improve energy efficiency is the important problem. Power big data is main support tool to realize demand side management and response. With the promotion of smart power consumption, distributed clean energy and electric vehicles etc get wide application; meanwhile, the continuous development of the Internet of things technology, more applications access the endings in the grid power link, which leads to that a large number of electric terminal equipment, new energy access smart grid, and it will produce massive heterogeneous and multi-state electricity data. These data produce the power grid enterprise's precious wealth, as the power big data. How to transform it into valuable knowledge and effective operation becomes an important problem, it needs to interoperate in the smart grid. In this paper, we had researched the various applications of power big data and integrate the cloud computing and big data technology, which include electricity consumption online monitoring, the short-term power load forecasting and the analysis of the energy efficiency. Based on Hadoop, HBase and Hive etc., we realize the ETL and OLAP functions; and we also adopt the parallel computing framework to achieve the power load forecasting algorithms and propose a parallel locally weighted linear regression model; we study on energy efficiency rating model to comprehensive evaluate the level of energy consumption of electricity users, which allows users to understand their real-time energy consumption situation, adjust their electricity behavior to reduce energy consumption, it provides decision-making basis for the user. With an intelligent industrial park as example, this paper complete electricity management. Therefore, in the future, power big data will provide decision-making support tools for energy conservation and emissions reduction.

Nuclear fragmentation energy and momentum transfer distributions in relativistic heavy-ion collisions

NASA Technical Reports Server (NTRS)

Khandelwal, Govind S.; Khan, Ferdous

1989-01-01

An optical model description of energy and momentum transfer in relativistic heavy-ion collisions, based upon composite particle multiple scattering theory, is presented. Transverse and longitudinal momentum transfers to the projectile are shown to arise from the real and absorptive part of the optical potential, respectively. Comparisons of fragment momentum distribution observables with experiments are made and trends outlined based on our knowledge of the underlying nucleon-nucleon interaction. Corrections to the above calculations are discussed. Finally, use of the model as a tool for estimating collision impact parameters is indicated.

Using background knowledge for picture organization and retrieval

NASA Astrophysics Data System (ADS)

Quintana, Yuri

1997-01-01

A picture knowledge base management system is described that is used to represent, organize and retrieve pictures from a frame knowledge base. Experiments with human test subjects were conducted to obtain further descriptions of pictures from news magazines. These descriptions were used to represent the semantic content of pictures in frame representations. A conceptual clustering algorithm is described which organizes pictures not only on the observable features, but also on implicit properties derived from the frame representations. The algorithm uses inheritance reasoning to take into account background knowledge in the clustering. The algorithm creates clusters of pictures using a group similarity function that is based on the gestalt theory of picture perception. For each cluster created, a frame is generated which describes the semantic content of pictures in the cluster. Clustering and retrieval experiments were conducted with and without background knowledge. The paper shows how the use of background knowledge and semantic similarity heuristics improves the speed, precision, and recall of queries processed. The paper concludes with a discussion of how natural language processing of can be used to assist in the development of knowledge bases and the processing of user queries.

Stepwise Catalytic Mechanism via Short-Lived Intermediate Inferred from Combined QM/MM MERP and PES Calculations on Retaining Glycosyltransferase ppGalNAcT2

PubMed Central

Trnka, Tomáš; Kozmon, Stanislav; Tvaroška, Igor; Koča, Jaroslav

2015-01-01

The glycosylation of cell surface proteins plays a crucial role in a multitude of biological processes, such as cell adhesion and recognition. To understand the process of protein glycosylation, the reaction mechanisms of the participating enzymes need to be known. However, the reaction mechanism of retaining glycosyltransferases has not yet been sufficiently explained. Here we investigated the catalytic mechanism of human isoform 2 of the retaining glycosyltransferase polypeptide UDP-GalNAc transferase by coupling two different QM/MM-based approaches, namely a potential energy surface scan in two distance difference dimensions and a minimum energy reaction path optimisation using the Nudged Elastic Band method. Potential energy scan studies often suffer from inadequate sampling of reactive processes due to a predefined scan coordinate system. At the same time, path optimisation methods enable the sampling of a virtually unlimited number of dimensions, but their results cannot be unambiguously interpreted without knowledge of the potential energy surface. By combining these methods, we have been able to eliminate the most significant sources of potential errors inherent to each of these approaches. The structural model is based on the crystal structure of human isoform 2. In the QM/MM method, the QM region consists of 275 atoms, the remaining 5776 atoms were in the MM region. We found that ppGalNAcT2 catalyzes a same-face nucleophilic substitution with internal return (SNi). The optimized transition state for the reaction is 13.8 kcal/mol higher in energy than the reactant while the energy of the product complex is 6.7 kcal/mol lower. During the process of nucleophilic attack, a proton is synchronously transferred to the leaving phosphate. The presence of a short-lived metastable oxocarbenium intermediate is likely, as indicated by the reaction energy profiles obtained using high-level density functionals. PMID:25849117

Stepwise catalytic mechanism via short-lived intermediate inferred from combined QM/MM MERP and PES calculations on retaining glycosyltransferase ppGalNAcT2.

PubMed

Trnka, Tomáš; Kozmon, Stanislav; Tvaroška, Igor; Koča, Jaroslav

2015-04-01

The glycosylation of cell surface proteins plays a crucial role in a multitude of biological processes, such as cell adhesion and recognition. To understand the process of protein glycosylation, the reaction mechanisms of the participating enzymes need to be known. However, the reaction mechanism of retaining glycosyltransferases has not yet been sufficiently explained. Here we investigated the catalytic mechanism of human isoform 2 of the retaining glycosyltransferase polypeptide UDP-GalNAc transferase by coupling two different QM/MM-based approaches, namely a potential energy surface scan in two distance difference dimensions and a minimum energy reaction path optimisation using the Nudged Elastic Band method. Potential energy scan studies often suffer from inadequate sampling of reactive processes due to a predefined scan coordinate system. At the same time, path optimisation methods enable the sampling of a virtually unlimited number of dimensions, but their results cannot be unambiguously interpreted without knowledge of the potential energy surface. By combining these methods, we have been able to eliminate the most significant sources of potential errors inherent to each of these approaches. The structural model is based on the crystal structure of human isoform 2. In the QM/MM method, the QM region consists of 275 atoms, the remaining 5776 atoms were in the MM region. We found that ppGalNAcT2 catalyzes a same-face nucleophilic substitution with internal return (SNi). The optimized transition state for the reaction is 13.8 kcal/mol higher in energy than the reactant while the energy of the product complex is 6.7 kcal/mol lower. During the process of nucleophilic attack, a proton is synchronously transferred to the leaving phosphate. The presence of a short-lived metastable oxocarbenium intermediate is likely, as indicated by the reaction energy profiles obtained using high-level density functionals.

The generalized quadratic knapsack problem. A neuronal network approach.

PubMed

Talaván, Pedro M; Yáñez, Javier

2006-05-01

The solution of an optimization problem through the continuous Hopfield network (CHN) is based on some energy or Lyapunov function, which decreases as the system evolves until a local minimum value is attained. A new energy function is proposed in this paper so that any 0-1 linear constrains programming with quadratic objective function can be solved. This problem, denoted as the generalized quadratic knapsack problem (GQKP), includes as particular cases well-known problems such as the traveling salesman problem (TSP) and the quadratic assignment problem (QAP). This new energy function generalizes those proposed by other authors. Through this energy function, any GQKP can be solved with an appropriate parameter setting procedure, which is detailed in this paper. As a particular case, and in order to test this generalized energy function, some computational experiments solving the traveling salesman problem are also included.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Knowledge Translation: The Bridging Function of Cochrane Rehabilitation.

PubMed

Negrini, Stefano; Gimigliano, Francesca; Arienti, Chiara; Kiekens, Carlotte

2018-06-01

Cochrane Rehabilitation is aimed to ensure that all rehabilitation professionals can apply Evidence Based Clinical Practice and take decisions according to the best and most appropriate evidence in this specific field, combining the best available evidence as gathered by high-quality Cochrane systematic reviews, with their own clinical expertise and the values of patients. This mission can be pursued through knowledge translation. The aim of this article is to shortly present what knowledge translation is, how and why Cochrane (previously known as Cochrane Collaboration) is trying to reorganize itself in light of knowledge translation, and the relevance that this process has for Cochrane Rehabilitation and in the end for the whole world of rehabilitation. It is well known how it is difficult to effectively apply in everyday life what we would like to do and to apply the scientific knowledge in the clinical field: this is called the know-do gap. In the field of evidence-based medicine, where Cochrane belongs, it has been proven that high-quality evidence is not consistently applied in practice. A solution to these problems is the so-called knowledge translation. In this context, Cochrane Rehabilitation is organized to provide the best possible knowledge translation in both directions (bridging function), obviously toward the world of rehabilitation (spreading reviews), but also to the Cochrane community (production of reviews significant for rehabilitation). Cochrane is now strongly pushing to improve its knowledge translation activities, and this creates a strong base for Cochrane Rehabilitation work, focused not only on spreading the evidence but also on improving its production to make it more meaningful for the world of rehabilitation. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Density functional theory and an experimentally-designed energy functional of electron density.

PubMed

Miranda, David A; Bueno, Paulo R

2016-09-21

We herein demonstrate that capacitance spectroscopy (CS) experimentally allows access to the energy associated with the quantum mechanical ground state of many-electron systems. Priorly, electrochemical capacitance, C [small mu, Greek, macron] [ρ], was previously understood from conceptual and computational density functional theory (DFT) calculations. Thus, we herein propose a quantum mechanical experiment-based variational method for electron charging processes based on an experimentally-designed functional of the ground state electron density. In this methodology, the electron state density, ρ, and an energy functional of the electron density, E [small mu, Greek, macron] [ρ], can be obtained from CS data. CS allows the derivative of the electrochemical potential with respect to the electron density, (δ[small mu, Greek, macron][ρ]/δρ), to be obtained as a unique functional of the energetically minimised system, i.e., β/C [small mu, Greek, macron] [ρ], where β is a constant (associated with the size of the system) and C [small mu, Greek, macron] [ρ] is an experimentally observable quantity. Thus the ground state energy (at a given fixed external potential) can be obtained simply as E [small mu, Greek, macron] [ρ], from the experimental measurement of C [small mu, Greek, macron] [ρ]. An experimental data-set was interpreted to demonstrate the potential of this quantum mechanical experiment-based variational principle.

The identification of knowledge content and function in manual labour.

PubMed

Shalin, Valerie; Verdile, Charles

2003-06-10

Calls for an alternative conceptualization of cognition for applied concerns retain the core commitment of the basic research community to abstract cognition detached from a physical environment. The present paper attempts to break out of the dominant, narrow view of cognition and cognitive domains, with a cognitive analysis of digging ditches for the utility industry. To illustrate knowledge-based cognition in manual labour excerpts are presented from the journal entries of a moderately experienced student working a summer job, organized with a representation that distinguishes between the goals and methods of work. The journal entries illustrate the functions of knowledge for interacting with a physical environment; knowledge enables the selection, execution and monitoring of work methods, the interpretation of perceptual information, the application of task completion criteria and the ability for explanation and generalization. To emphasize the generality of the functions of cognition in ditch digging, comparable functions are indicated in a domain rarely regarded as a form of manual labour: the practice of internal medicine. Discussion of the results includes the implications for cognitive theory as well as practical implications for productivity, training and task analysis.

Developing Energy Literacy in US Middle-Level Students Using the Geospatial Curriculum Approach

NASA Astrophysics Data System (ADS)

Bodzin, Alec M.; Fu, Qiong; Peffer, Tamara E.; Kulo, Violet

2013-06-01

This quantitative study examined the effectiveness of a geospatial curriculum approach to promote energy literacy in an urban school district and examined factors that may account for energy content knowledge achievement. An energy literacy measure was administered to 1,044 eighth-grade students (ages 13-15) in an urban school district in Pennsylvania, USA. One group of students received instruction with a geospatial curriculum approach (geospatial technologies (GT)) and another group of students received 'business as usual' (BAU) curriculum instruction. For the GT students, findings revealed statistically significant gains from pretest to posttest (p < 0.001) on knowledge of energy resource acquisition, energy generation, storage and transport, and energy consumption and conservation. The GT students had year-end energy content knowledge scores significantly higher than those who learned with the BAU curriculum (p < 0.001; effect size being large). A multiple regression found that prior energy content knowledge was the only significant predictor to the year-end energy content knowledge achievement for the GT students (p < 0.001). The findings support that the implementation of a geospatial curriculum approach that employs learning activities that focus on the spatial nature of energy resources can improve the energy literacy of urban middle-level education students.

Creating Very True Quantum Algorithms for Quantum Energy Based Computing

NASA Astrophysics Data System (ADS)

Nagata, Koji; Nakamura, Tadao; Geurdes, Han; Batle, Josep; Abdalla, Soliman; Farouk, Ahmed; Diep, Do Ngoc

2018-04-01

An interpretation of quantum mechanics is discussed. It is assumed that quantum is energy. An algorithm by means of the energy interpretation is discussed. An algorithm, based on the energy interpretation, for fast determining a homogeneous linear function f( x) := s. x = s 1 x 1 + s 2 x 2 + ⋯ + s N x N is proposed. Here x = ( x 1, … , x N ), x j ∈ R and the coefficients s = ( s 1, … , s N ), s j ∈ N. Given the interpolation values (f(1), f(2),...,f(N))=ěc {y}, the unknown coefficients s = (s1(ěc {y}),\\dots , sN(ěc {y})) of the linear function shall be determined, simultaneously. The speed of determining the values is shown to outperform the classical case by a factor of N. Our method is based on the generalized Bernstein-Vazirani algorithm to qudit systems. Next, by using M parallel quantum systems, M homogeneous linear functions are determined, simultaneously. The speed of obtaining the set of M homogeneous linear functions is shown to outperform the classical case by a factor of N × M.

Creating Very True Quantum Algorithms for Quantum Energy Based Computing

NASA Astrophysics Data System (ADS)

Nagata, Koji; Nakamura, Tadao; Geurdes, Han; Batle, Josep; Abdalla, Soliman; Farouk, Ahmed; Diep, Do Ngoc

2017-12-01

An interpretation of quantum mechanics is discussed. It is assumed that quantum is energy. An algorithm by means of the energy interpretation is discussed. An algorithm, based on the energy interpretation, for fast determining a homogeneous linear function f(x) := s.x = s 1 x 1 + s 2 x 2 + ⋯ + s N x N is proposed. Here x = (x 1, … , x N ), x j ∈ R and the coefficients s = (s 1, … , s N ), s j ∈ N. Given the interpolation values (f(1), f(2),...,f(N))=ěc {y}, the unknown coefficients s = (s1(ěc {y}),\\dots , sN(ěc {y})) of the linear function shall be determined, simultaneously. The speed of determining the values is shown to outperform the classical case by a factor of N. Our method is based on the generalized Bernstein-Vazirani algorithm to qudit systems. Next, by using M parallel quantum systems, M homogeneous linear functions are determined, simultaneously. The speed of obtaining the set of M homogeneous linear functions is shown to outperform the classical case by a factor of N × M.

Leveraging the Affordances of YouTube: The Role of Pedagogical Knowledge and Mental Models of Technology Functions for Lesson Planning with Technology

ERIC Educational Resources Information Center

Krauskopf, Karsten; Zahn, Carmen; Hesse, Friedrich W.

2012-01-01

Web-based digital video tools enable learners to access video sources in constructive ways. To leverage these affordances teachers need to integrate their knowledge of a technology with their professional knowledge about teaching. We suggest that this is a cognitive process, which is strongly connected to a teacher's mental model of the tool's…

A recipe for free-energy functionals of polarizable molecular fluids

NASA Astrophysics Data System (ADS)

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Arias, T. A.

2014-04-01

Classical density-functional theory is the most direct approach to equilibrium structures and free energies of inhomogeneous liquids, but requires the construction of an approximate free-energy functional for each liquid of interest. We present a general recipe for constructing functionals for small-molecular liquids based only on bulk experimental properties and ab initio calculations of a single solvent molecule. This recipe combines the exact free energy of the non-interacting system with fundamental measure theory for the repulsive contribution and a weighted density functional for the short-ranged attractive interactions. We add to these ingredients a weighted polarization functional for the long-range correlations in both the rotational and molecular-polarizability contributions to the dielectric response. We also perform molecular dynamics calculations for the free energy of cavity formation and the high-field dielectric response, and show that our free-energy functional adequately describes these properties (which are key for accurate solvation calculations) for all three solvents in our study: water, chloroform, and carbon tetrachloride.

Opportunities for future supernova studies of cosmic acceleration.

PubMed

Weller, J; Albrecht, A

2001-03-05

We investigate the potential of a future supernova data set, as might be obtained by the proposed SNAP satellite, to discriminate among different "dark energy" theories that describe an accelerating Universe. We find that many such models can be distinguished with a fit to the effective pressure-to-density ratio w of this energy. More models can be distinguished when the effective slope dw/dz of a changing w is also fit, but only if our knowledge of the current mass density Omega(m) is improved. We investigate the use of "fitting functions" to interpret luminosity distance data from supernova searches.

A Framework for Creating a Function-based Design Tool for Failure Mode Identification

NASA Technical Reports Server (NTRS)

Arunajadai, Srikesh G.; Stone, Robert B.; Tumer, Irem Y.; Clancy, Daniel (Technical Monitor)

2002-01-01

Knowledge of potential failure modes during design is critical for prevention of failures. Currently industries use procedures such as Failure Modes and Effects Analysis (FMEA), Fault Tree analysis, or Failure Modes, Effects and Criticality analysis (FMECA), as well as knowledge and experience, to determine potential failure modes. When new products are being developed there is often a lack of sufficient knowledge of potential failure mode and/or a lack of sufficient experience to identify all failure modes. This gives rise to a situation in which engineers are unable to extract maximum benefits from the above procedures. This work describes a function-based failure identification methodology, which would act as a storehouse of information and experience, providing useful information about the potential failure modes for the design under consideration, as well as enhancing the usefulness of procedures like FMEA. As an example, the method is applied to fifteen products and the benefits are illustrated.

Diagrams for comprehensive molecular orbital-based chemical reaction analyses: reactive orbital energy diagrams.

PubMed

Tsuneda, Takao; Singh, Raman Kumar; Chattaraj, Pratim Kumar

2018-05-15

Reactive orbital energy diagrams are presented as a tool for comprehensively performing orbital-based reaction analyses. The diagrams rest on the reactive orbital energy theory, which is the expansion of conceptual density functional theory (DFT) to an orbital energy-based theory. The orbital energies on the intrinsic reaction coordinates of fundamental reactions are calculated by long-range corrected DFT, which is confirmed to provide accurate orbital energies of small molecules, combining with a van der Waals (vdW) correlation functional, in order to examine the vdW effect on the orbital energies. By analysing the reactions based on the reactive orbital energy theory using these accurate orbital energies, it is found that vdW interactions significantly affect the orbital energies in the initial reaction processes and that more than 70% of reactions are determined to be initially driven by charge transfer, while the remaining structural deformation (dynamics)-driven reactions are classified into identity, cyclization and ring-opening, unimolecular dissociation, and H2 reactions. The reactive orbital energy diagrams, which are constructed using these results, reveal that reactions progress so as to delocalize the occupied reactive orbitals, which are determined as contributing orbitals and are usually not HOMOs, by hybridizing the unoccupied reactive orbitals, which are usually not LUMOs. These diagrams also raise questions about conventional orbital-based diagrams such as frontier molecular orbital diagrams, even for the well-established interpretation of Diels-Alder reactions.

Commercial Building Energy Asset Score

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

This software (Asset Scoring Tool) is designed to help building owners and managers to gain insight into the as-built efficiency of their buildings. It is a web tool where users can enter their building information and obtain an asset score report. The asset score report consists of modeled building energy use (by end use and by fuel type), building systems (envelope, lighting, heating, cooling, service hot water) evaluations, and recommended energy efficiency measures. The intended users are building owners and operators who have limited knowledge of building energy efficiency. The scoring tool collects minimum building data (~20 data entries) frommore » users and build a full-scale energy model using the inference functionalities from Facility Energy Decision System (FEDS). The scoring tool runs real-time building energy simulation using EnergyPlus and performs life-cycle cost analysis using FEDS. An API is also under development to allow the third-party applications to exchange data with the web service of the scoring tool.« less

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

Creatine metabolism and psychiatric disorders: Does creatine supplementation have therapeutic value?

PubMed Central

Allen, Patricia J.

2012-01-01

Athletes, body builders, and military personnel use dietary creatine as an ergogenic aid to boost physical performance in sports involving short bursts of high-intensity muscle activity. Lesser known is the essential role creatine, a natural regulator of energy homeostasis, plays in brain function and development. Creatine supplementation has shown promise as a safe, effective, and tolerable adjunct to medication for the treatment of brain-related disorders linked with dysfunctional energy metabolism, such as Huntington’s Disease and Parkinson’s Disease. Impairments in creatine metabolism have also been implicated in the pathogenesis of psychiatric disorders, leaving clinicians, researchers and patients alike wondering if dietary creatine has therapeutic value for treating mental illness. The present review summarizes the neurobiology of the creatine-phosphocreatine circuit and its relation to psychological stress, schizophrenia, mood and anxiety disorders. While present knowledge of the role of creatine in cognitive and emotional processing is in its infancy, further research on this endogenous metabolite has the potential to advance our understanding of the biological bases of psychopathology and improve current therapeutic strategies. PMID:22465051

Shewanella oneidensis MR-1 nanowires are outer membrane and periplasmic extensions of the extracellular electron transport components

PubMed Central

Pirbadian, Sahand; Barchinger, Sarah E.; Leung, Kar Man; Byun, Hye Suk; Jangir, Yamini; Bouhenni, Rachida A.; Reed, Samantha B.; Romine, Margaret F.; Saffarini, Daad A.; Shi, Liang; Gorby, Yuri A.; Golbeck, John H.; El-Naggar, Mohamed Y.

2014-01-01

Bacterial nanowires offer an extracellular electron transport (EET) pathway for linking the respiratory chain of bacteria to external surfaces, including oxidized metals in the environment and engineered electrodes in renewable energy devices. Despite the global, environmental, and technological consequences of this biotic–abiotic interaction, the composition, physiological relevance, and electron transport mechanisms of bacterial nanowires remain unclear. We report, to our knowledge, the first in vivo observations of the formation and respiratory impact of nanowires in the model metal-reducing microbe Shewanella oneidensis MR-1. Live fluorescence measurements, immunolabeling, and quantitative gene expression analysis point to S. oneidensis MR-1 nanowires as extensions of the outer membrane and periplasm that include the multiheme cytochromes responsible for EET, rather than pilin-based structures as previously thought. These membrane extensions are associated with outer membrane vesicles, structures ubiquitous in Gram-negative bacteria, and are consistent with bacterial nanowires that mediate long-range EET by the previously proposed multistep redox hopping mechanism. Redox-functionalized membrane and vesicular extensions may represent a general microbial strategy for electron transport and energy distribution. PMID:25143589

Shewanella oneidensis MR-1 nanowires are outer membrane and periplasmic extensions of the extracellular electron transport components.

PubMed

Pirbadian, Sahand; Barchinger, Sarah E; Leung, Kar Man; Byun, Hye Suk; Jangir, Yamini; Bouhenni, Rachida A; Reed, Samantha B; Romine, Margaret F; Saffarini, Daad A; Shi, Liang; Gorby, Yuri A; Golbeck, John H; El-Naggar, Mohamed Y

2014-09-02

Bacterial nanowires offer an extracellular electron transport (EET) pathway for linking the respiratory chain of bacteria to external surfaces, including oxidized metals in the environment and engineered electrodes in renewable energy devices. Despite the global, environmental, and technological consequences of this biotic-abiotic interaction, the composition, physiological relevance, and electron transport mechanisms of bacterial nanowires remain unclear. We report, to our knowledge, the first in vivo observations of the formation and respiratory impact of nanowires in the model metal-reducing microbe Shewanella oneidensis MR-1. Live fluorescence measurements, immunolabeling, and quantitative gene expression analysis point to S. oneidensis MR-1 nanowires as extensions of the outer membrane and periplasm that include the multiheme cytochromes responsible for EET, rather than pilin-based structures as previously thought. These membrane extensions are associated with outer membrane vesicles, structures ubiquitous in Gram-negative bacteria, and are consistent with bacterial nanowires that mediate long-range EET by the previously proposed multistep redox hopping mechanism. Redox-functionalized membrane and vesicular extensions may represent a general microbial strategy for electron transport and energy distribution.

The role of the U.S. Geological Survey in the lithium industry

USGS Publications Warehouse

Vine, J.D.

1978-01-01

The U.S. Geological Survey has responsibility in the U.S. Department of the Interior to assess the nation's energy and mineral resources. The evaluation of reserves and resources of a commodity such as lithium should be a continuing process in the light of advancing technology and ever-growing knowledge of its geologic occurrence and geochemical behavior. Although reserves of lithium vary with market demand because of the investment required to find, develop, and appraise an ore body, total resources are a function of the geologic occurrence and geochemical behavior of lithium. By studying known deposits and publishing data on their origin and occurrence, the U.S. Geological Survey can aid in the discovery of new deposits and improve the resource base. Resource data are used both by the government and the private sector. Government funding for research on energy-related technologies such as electric vehicle batteries and fusion power requires assurance that there will be enough lithium available in time for commercialization. Questions of availability for all mineral commodities must be answered by the U.S. Geological Survey so that intelligent decisions can be made. ?? 1978.

Creatine metabolism and psychiatric disorders: Does creatine supplementation have therapeutic value?

PubMed

Allen, Patricia J

2012-05-01

Athletes, body builders, and military personnel use dietary creatine as an ergogenic aid to boost physical performance in sports involving short bursts of high-intensity muscle activity. Lesser known is the essential role creatine, a natural regulator of energy homeostasis, plays in brain function and development. Creatine supplementation has shown promise as a safe, effective, and tolerable adjunct to medication for the treatment of brain-related disorders linked with dysfunctional energy metabolism, such as Huntington's Disease and Parkinson's Disease. Impairments in creatine metabolism have also been implicated in the pathogenesis of psychiatric disorders, leaving clinicians, researchers and patients alike wondering if dietary creatine has therapeutic value for treating mental illness. The present review summarizes the neurobiology of the creatine-phosphocreatine circuit and its relation to psychological stress, schizophrenia, mood and anxiety disorders. While present knowledge of the role of creatine in cognitive and emotional processing is in its infancy, further research on this endogenous metabolite has the potential to advance our understanding of the biological bases of psychopathology and improve current therapeutic strategies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Density-based Energy Decomposition Analysis for Intermolecular Interactions with Variationally Determined Intermediate State Energies

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

Wu, Q.; Ayers, P.W.; Zhang, Y.

2009-10-28

The first purely density-based energy decomposition analysis (EDA) for intermolecular binding is developed within the density functional theory. The most important feature of this scheme is to variationally determine the frozen density energy, based on a constrained search formalism and implemented with the Wu-Yang algorithm [Q. Wu and W. Yang, J. Chem. Phys. 118, 2498 (2003) ]. This variational process dispenses with the Heitler-London antisymmetrization of wave functions used in most previous methods and calculates the electrostatic and Pauli repulsion energies together without any distortion of the frozen density, an important fact that enables a clean separation of these twomore » terms from the relaxation (i.e., polarization and charge transfer) terms. The new EDA also employs the constrained density functional theory approach [Q. Wu and T. Van Voorhis, Phys. Rev. A 72, 24502 (2005)] to separate out charge transfer effects. Because the charge transfer energy is based on the density flow in real space, it has a small basis set dependence. Applications of this decomposition to hydrogen bonding in the water dimer and the formamide dimer show that the frozen density energy dominates the binding in these systems, consistent with the noncovalent nature of the interactions. A more detailed examination reveals how the interplay of electrostatics and the Pauli repulsion determines the distance and angular dependence of these hydrogen bonds.« less

In Pursuit of the Far-Infrared Spectrum of Cyanogen Iso-Thiocyanate Ncncs, Under the Influence of the Energy Level Dislocation due to Quantum Monodromy

NASA Astrophysics Data System (ADS)

Winnewisser, Manfred; Winnewisser, Brenda P.; Medvedev, Ivan R.; De Lucia, Frank, C.; Ross, Stephen C.; Koput, Jacek

2010-06-01

Quantum Monodromy has a strong impact on the ro-vibrational energy levels of chain molecules whose bending potential energy function has the form of the bottom of a champagne bottle (i.e. with a hump or punt) around the linear configuration. NCNCS is a particularly good example of such a molecule and clearly exhibits a distinctive monodromy-induced dislocation of the energy level pattern at the top of the potential energy hump. The generalized semi-rigid bender (GSRB) wave functions are used to show that the expectation values of any physical quantity which varies with the large amplitude bending coordinate will also have monodromy-induced dislocations. This includes the electric dipole moment components. High level ab initio calculations not only provided the molecular equilibrium structure of NCNCS, but also the electric dipole moment components μa and μb as functions of the large-amplitude bending coordinate. The calculated expectation values of these quantities indicate large ro-vibrational transition moments that will be discussed in pursuit of possible far-infrared bands. To our knowledge there is no NCNCS infrared spectrum reported in the literature. B. P. Winnewisser, M. Winnewisser, I. R. Medvedev, F. C. De Lucia, S. C. Ross and J. Koput, Phys. Chem. Chem. Phys., 2010, DOI:10.1039/B922023B.

Calyx{trademark} EA implementation at AECB

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

NONE

1997-12-31

This report describes a project to examine the applicability of a knowledge-based decision support software for environmental assessment (Calyx) to assist the Atomic Energy Control Board in environmental screenings, assessment, management, and database searches. The report begins with background on the Calyx software and then reviews activities with regard to modification of the Calyx knowledge base for application to the nuclear sector. This is followed by lists of standard activities handled by the software and activities specific to the Board; the hierarchy of environmental components developed for the Board; details of impact rules that describe the conditions under which environmentalmore » impacts will occur (the bulk of the report); information on mitigation and monitoring rules and on instance data; and considerations for future work on implementing Calyx at the Board. Appendices include an introduction to expert systems and an overview of the Calyx knowledge base structure.« less

Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method.

PubMed

Sinha, Debalina; Pavanello, Michele

2015-08-28

The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term the Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.

Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method

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

Sinha, Debalina; Pavanello, Michele, E-mail: m.pavanello@rutgers.edu

2015-08-28

The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term themore » Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.« less

Nonlocal kinetic energy functional from the jellium-with-gap model: Applications to orbital-free density functional theory

NASA Astrophysics Data System (ADS)

Constantin, Lucian A.; Fabiano, Eduardo; Della Sala, Fabio

2018-05-01

Orbital-free density functional theory (OF-DFT) promises to describe the electronic structure of very large quantum systems, being its computational cost linear with the system size. However, the OF-DFT accuracy strongly depends on the approximation made for the kinetic energy (KE) functional. To date, the most accurate KE functionals are nonlocal functionals based on the linear-response kernel of the homogeneous electron gas, i.e., the jellium model. Here, we use the linear-response kernel of the jellium-with-gap model to construct a simple nonlocal KE functional (named KGAP) which depends on the band-gap energy. In the limit of vanishing energy gap (i.e., in the case of metals), the KGAP is equivalent to the Smargiassi-Madden (SM) functional, which is accurate for metals. For a series of semiconductors (with different energy gaps), the KGAP performs much better than SM, and results are close to the state-of-the-art functionals with sophisticated density-dependent kernels.

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

PubMed

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

NASA Astrophysics Data System (ADS)

Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

2014-05-01

Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction

NASA Technical Reports Server (NTRS)

Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

2000-01-01

This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

What energy functions can be minimized via graph cuts?

PubMed

Kolmogorov, Vladimir; Zabih, Ramin

2004-02-01

In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions are complex and highly specific to a particular energy function, graph cuts have seen limited application to date. In this paper, we give a characterization of the energy functions that can be minimized by graph cuts. Our results are restricted to functions of binary variables. However, our work generalizes many previous constructions and is easily applicable to vision problems that involve large numbers of labels, such as stereo, motion, image restoration, and scene reconstruction. We give a precise characterization of what energy functions can be minimized using graph cuts, among the energy functions that can be written as a sum of terms containing three or fewer binary variables. We also provide a general-purpose construction to minimize such an energy function. Finally, we give a necessary condition for any energy function of binary variables to be minimized by graph cuts. Researchers who are considering the use of graph cuts to optimize a particular energy function can use our results to determine if this is possible and then follow our construction to create the appropriate graph. A software implementation is freely available.

Evaluating knowledge benefits of automotive lightweighting materials R&D projects.

PubMed

Peretz, Jean H; Das, Sujit; Tonn, Bruce E

2009-08-01

This paper presents a set of metrics used to evaluate short-run knowledge benefits that accrued from research and development (R&D) projects funded in fiscal years 2000-2004 by automotive lightweighting materials (ALM) of the U.S. Department of Energy (DOE). Although DOE presents to Congress energy, environmental, and security benefits and costs of its R&D efforts under the Government Performance and Results Act, DOE has yet to include knowledge benefits in that report [U.S. Department of Energy. (2007). Projected benefits of federal energy efficiency and renewable energy programs: FY2008 budget request. NREL/TP-640-41347 (March). Washington, DC: National Renewable Energy Laboratory for DOE Energy Efficiency and Renewable Energy. Retrieved February 12, 2007 from http://www1.eere.energy.gov/ba/pba/2008_benefits.html]. ALM focuses on development and validation of advanced technologies that significantly reduce automotive vehicle body and chassis weight without compromising other attributes such as safety, performance, recyclability, and cost [U.S. Department of Energy. (2005a). Automotive lightweighting materials 2004 annual progress report. Washington, DC: DOE Energy Efficiency and Renewable Energy. Retrieved March 30, 2005 from http://www.eere.energy.gov/vehiclesandfuels/resources/fcvt_alm_fy04.shtml]. The ultimate goal of ALM to have lightweighter materials in vehicles hinges on many issues, including the (1) collaborative nature of ALMs R&D with the automobile industry and (2) manufacturing knowledge gained through the R&D effort. The ALM projects evaluated in this paper yielded numerous knowledge benefits in the short run. While these knowledge benefits are impressive, there remains uncertainty about whether the research will lead to incorporation of lightweight materials by the Big Three automakers into their manufacturing process and introduction of lightweight vehicles into the marketplace. The uncertainty illustrates a difference between (1) knowledge benefits and (2) energy, environmental, and security benefits emanating from R&D.

Correlation energy functional within the GW -RPA: Exact forms, approximate forms, and challenges

NASA Astrophysics Data System (ADS)

Ismail-Beigi, Sohrab

2010-05-01

In principle, the Luttinger-Ward Green’s-function formalism allows one to compute simultaneously the total energy and the quasiparticle band structure of a many-body electronic system from first principles. We present approximate and exact expressions for the correlation energy within the GW -random-phase approximation that are more amenable to computation and allow for developing efficient approximations to the self-energy operator and correlation energy. The exact form is a sum over differences between plasmon and interband energies. The approximate forms are based on summing over screened interband transitions. We also demonstrate that blind extremization of such functionals leads to unphysical results: imposing physical constraints on the allowed solutions (Green’s functions) is necessary. Finally, we present some relevant numerical results for atomic systems.

Density functional calculation of activation energies for lattice and grain boundary diffusion in alumina

NASA Astrophysics Data System (ADS)

Lei, Yinkai; Gong, Yu; Duan, Zhiyao; Wang, Guofeng

2013-06-01

To acquire knowledge on the lattice and grain boundary diffusion processes in alumina, we have determined the activation energies of elementary O and Al diffusive jumps in the bulk crystal, Σ3(0001) grain boundaries, and Σ3(101¯0) grain boundaries of α-Al2O3 using the first-principles density functional theory method. Specifically, we calculated the activation energies for four elementary jumps of both O and Al lattice diffusion in alumina. It was predicted that the activation energy of O lattice diffusion varied from 3.58 to 5.03 eV, while the activation energy of Al lattice diffusion ranged from 1.80 to 3.17 eV. As compared with experimental measurements, the theoretical predictions of the activation energy for lattice diffusion were lower and thus implied that there might be other high-energy diffusive jumps in the experimental alumina samples. Moreover, our results suggested that the Al lattice diffusion was faster than the O lattice diffusion in alumina, in agreement with experiment observations. Furthermore, it was found from our calculations for α-Al2O3 that the activation energies of O and Al grain boundary diffusion in the high-energy Σ3(0001) grain boundaries were significantly lower than those of the lattice diffusion. In contrast, the activation energies of O and Al grain boundary diffusion in the low-energy Σ3(101¯0) grain boundaries could be even higher than those of the lattice diffusion.

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

DOE PAGES

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

2016-09-01

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

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

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

The Extragalactic Background Light and the Gamma-ray Opacity of the Universe

NASA Technical Reports Server (NTRS)

Dwek, Eli; Krennrich, Frank

2012-01-01

The extragalactic background light (EBL) is one of the fundamental observational quantities in cosmology. All energy releases from resolved and unresolved extragalactic sources, and the light from any truly diffuse background, excluding the cosmic microwave background (CMB), contribute to its intensity and spectral energy distribution. It therefore plays a crucial role in cosmological tests for the formation and evolution of stellar objects and galaxies, and for setting limits on exotic energy releases in the universe. The EBL also plays an important role in the propagation of very high energy gamma-rays which are attenuated en route to Earth by pair producing gamma-gamma interactions with the EBL and CMB. The EBL affects the spectrum of the sources, predominantly blazars, in the approx 10 GeV to 10 TeV energy regime. Knowledge of the EBL intensity and spectrum will allow the determination of the intrinsic blazar spectrum in a crucial energy regime that can be used to test particle acceleration mechanisms and VHE gamma-ray production models. Conversely, knowledge of the intrinsic gamma-ray spectrum and the detection of blazars at increasingly higher redshifts will set strong limits on the EBL and its evolution. This paper reviews the latest developments in the determination of the EBL and its impact on the current understanding of the origin and production mechanisms of gamma-rays in blazars, and on energy releases in the universe. The review concludes with a summary and future directions in Cherenkov Telescope Array techniques and in infrared ground-based and space observatories that will greatly improve our knowledge of the EBL and the origin and production of very high energy gamma-rays.

Investigation on minimum ignition energy of mixtures of α-pinene-benzene/air.

PubMed

Coudour, B; Chetehouna, K; Rudz, S; Gillard, P; Garo, J P

2015-01-01

Minimum ignition energies (MIE) of α-pinene-benzene/air mixtures at a given temperature for different equivalence ratios and fuel proportions are experimented in this paper. We used a cylindrical chamber of combustion using a nanosecond pulse at 1,064 nm from a Q-switched Nd:YAG laser. Laser-induced spark ignitions were studied for two molar proportions of α-pinene/benzene mixtures, respectively 20-80% and 50-50%. The effect of the equivalence ratio (Φ) has been investigated for 0.7, 0.9, 1.1 and 1.5 and ignition of fuel/air mixtures has been experimented for two different incident laser energies: 25 and 33 mJ. This study aims at observing the influence of different α-pinene/benzene proportions on the flammability of the mixture to have further knowledge of the potential of biogenic volatile organic compounds (BVOCs) and smoke mixtures to influence forest fires, especially in the case of the accelerating forest fire phenomenon (AFF). Results of ignition probability and energy absorption are based on 400 laser shots for each studied fuel proportions. MIE results as functions of equivalence ratio compared to data of pure α-pinene and pure benzene demonstrate that the presence of benzene in α-pinene-air mixture tends to increase ignition probability and reduce MIE without depending strongly on the α-pinene/benzene proportion. Copyright © 2014 Elsevier B.V. All rights reserved.

Tritium

DTIC Science & Technology

2011-11-01

fusion energy -production processes of the particular type of reactor using a lithium (Li) blanket or related alloys such as the Pb-17Li eutectic. As such, tritium breeding is intimately connected with energy production, thermal management, radioactivity management, materials properties, and mechanical structures of any plausible future large-scale fusion power reactor. JASON is asked to examine the current state of scientific knowledge and engineering practice on the physical and chemical bases for large-scale tritium

Expert operator's associate: A knowledge based system for spacecraft control

NASA Technical Reports Server (NTRS)

Nielsen, Mogens; Grue, Klaus; Lecouat, Francois

1991-01-01

The Expert Operator's Associate (EOA) project is presented which studies the applicability of expert systems for day-to-day space operations. A prototype expert system is developed, which operates on-line with an existing spacecraft control system at the European Space Operations Centre, and functions as an 'operator's assistant' in controlling satellites. The prototype is demonstrated using an existing real-time simulation model of the MARECS-B2 telecommunication satellite. By developing a prototype system, the extent to which reliability and effectivens of operations can be enhanced by AI based support is examined. In addition the study examines the questions of acquisition and representation of the 'knowledge' for such systems, and the feasibility of 'migration' of some (currently) ground-based functions into future spaceborne autonomous systems.

Reciprocal Relations between Coalition Functioning and the Provision of Implementation Support

PubMed Central

Brown, Louis D.; Feinberg, Mark E.; Shapiro, Valerie B.; Greenberg, Mark T.

2014-01-01

Community coalitions have been promoted as a strategy to help overcome challenges to the dissemination and implementation of evidence-based prevention programs. This paper explores the characteristics of coalitions that enable the provision of implementation support for prevention programs in general, and for the implementation of evidence-based prevention programs with fidelity. Longitudinal cross-lagged panel models were used to study 74 Communities That Care (CTC) coalitions in Pennsylvania. These analyses provide evidence of a unidirectional influence of coalition functioning on the provision of implementation support. Coalition member knowledge of the CTC model best predicted the coalition’s provision of support for evidence-based program implementation with fidelity. Implications for developing and testing innovative methods for delivering training and technical assistance to enhance coalition member knowledge are discussed. PMID:24323363

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Slynko, Inna; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2016-09-01

High affinity ligands for a given target tend to share key molecular interactions with important anchoring amino acids and therefore often present quite conserved interaction patterns. This simple concept was formalized in a topological knowledge-based scoring function (GRIM) for selecting the most appropriate docking poses from previously X-rayed interaction patterns. GRIM first converts protein-ligand atomic coordinates (docking poses) into a simple 3D graph describing the corresponding interaction pattern. In a second step, proposed graphs are compared to that found from template structures in the Protein Data Bank. Last, all docking poses are rescored according to an empirical score (GRIMscore) accounting for overlap of maximum common subgraphs. Taking the opportunity of the public D3R Grand Challenge 2015, GRIM was used to rescore docking poses for 36 ligands (6 HSP90α inhibitors, 30 MAP4K4 inhibitors) prior to the release of the corresponding protein-ligand X-ray structures. When applied to the HSP90α dataset, for which many protein-ligand X-ray structures are already available, GRIM provided very high quality solutions (mean rmsd = 1.06 Å, n = 6) as top-ranked poses, and significantly outperformed a state-of-the-art scoring function. In the case of MAP4K4 inhibitors, for which preexisting 3D knowledge is scarce and chemical diversity is much larger, the accuracy of GRIM poses decays (mean rmsd = 3.18 Å, n = 30) although GRIM still outperforms an energy-based scoring function. GRIM rescoring appears to be quite robust with comparison to the other approaches competing for the same challenge (42 submissions for the HSP90 dataset, 27 for the MAP4K4 dataset) as it ranked 3rd and 2nd respectively, for the two investigated datasets. The rescoring method is quite simple to implement, independent on a docking engine, and applicable to any target for which at least one holo X-ray structure is available.

Extension of applicable neutron energy of DARWIN up to 1 GeV.

PubMed

Satoh, D; Sato, T; Endo, A; Matsufuji, N; Takada, M

2007-01-01

The radiation-dose monitor, DARWIN, needs a set of response functions of the liquid organic scintillator to assess a neutron dose. SCINFUL-QMD is a Monte Carlo based computer code to evaluate the response functions. In order to improve the accuracy of the code, a new light-output function based on the experimental data was developed for the production and transport of protons deuterons, tritons, (3)He nuclei and alpha particles, and incorporated into the code. The applicable energy of DARWIN was extended to 1 GeV using the response functions calculated by the modified SCINFUL-QMD code.

Foundational concepts and underlying theories for majors in "biochemistry and molecular biology".

PubMed

Tansey, John T; Baird, Teaster; Cox, Michael M; Fox, Kristin M; Knight, Jennifer; Sears, Duane; Bell, Ellis

2013-01-01

Over the past two years, through an NSF RCN UBE grant, the ASBMB has held regional workshops for faculty members and science educators from around the country that focused on identifying: 1) core principles of biochemistry and molecular biology, 2) essential concepts and underlying theories from physics, chemistry, and mathematics, and 3) foundational skills that undergraduate majors in biochemistry and molecular biology must understand to complete their major coursework. Using information gained from these workshops, as well as from the ASBMB accreditation working group and the NSF Vision and Change report, the Core Concepts working group has developed a consensus list of learning outcomes and objectives based on five foundational concepts (evolution, matter and energy transformation, homeostasis, information flow, and macromolecular structure and function) that represent the expected conceptual knowledge base for undergraduate degrees in biochemistry and molecular biology. This consensus will aid biochemistry and molecular biology educators in the development of assessment tools for the new ASBMB recommended curriculum. © 2013 by The International Union of Biochemistry and Molecular Biology.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Energy-efficient growth of phage Q Beta in Escherichia coli.

PubMed

Kim, Hwijin; Yin, John

2004-10-20

The role of natural selection in the optimal design of organisms is controversial. Optimal forms, functions, or behaviors of organisms have long been claimed without knowledge of how genotype contributes to phenotype, delineation of design constraints, or reference to alternative designs. Moreover, arguments for optimal designs have been often based on models that were difficult, if not impossible, to test. Here, we begin to address these issues by developing and probing a kinetic model for the intracellular growth of bacteriophage Q beta in Escherichia coli. The model accounts for the energetic costs of all template-dependent polymerization reactions, in ATP equivalents, including RNA-dependent RNA elongation by the phage replicase and synthesis of all phage proteins by the translation machinery of the E. coli host cell. We found that translation dominated phage growth, requiring 85% of the total energy expenditure. Only 10% of the total energy was applied to activities other than the direct synthesis of progeny phage components, reflecting primarily the cost of making the negative-strand RNA template that is needed for replication of phage genomic RNA. Further, we defined an energy efficiency of phage growth and showed its direct relationship to the yield of phage progeny. Finally, we performed a sensitivity analysis and found that the growth of wild-type phage was optimized for progeny yield or energy efficiency, suggesting that phage Q beta has evolved to optimally utilize the finite resources of its host cells.

Diffusion of molecules and macromolecules in thylakoid membranes.

PubMed

Kirchhoff, Helmut

2014-04-01

The survival and fitness of photosynthetic organisms is critically dependent on the flexible response of the photosynthetic machinery, harbored in thylakoid membranes, to environmental changes. A central element of this flexibility is the lateral diffusion of membrane components along the membrane plane. As demonstrated, almost all functions of photosynthetic energy conversion are dependent on lateral diffusion. The mobility of both small molecules (plastoquinone, xanthophylls) as well as large protein supercomplexes is very sensitive to changes in structural boundary conditions. Knowledge about the design principles that govern the mobility of photosynthetic membrane components is essential to understand the dynamic response of the photosynthetic machinery. This review summarizes our knowledge about the factors that control diffusion in thylakoid membranes and bridges structural membrane alterations to changes in mobility and function. This article is part of a Special Issue entitled: Dynamic and ultrastructure of bioenergetic membranes and their components. Copyright © 2013 Elsevier B.V. All rights reserved.

Energy Management Policies in Distributed Residential Energy Systems

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

Duan, Sisi; Sun, Jingtao

2016-01-01

In this paper, we study energy management problems in communities with several neighborhood-level Residential Energy Systems (RESs). We consider control problems from both community level and residential level to handle external changes such as restriction on peak demand and restriction on the total demand from the electricity grid. We propose three policies to handle the problems at community level. Based on the collected data from RESs such as predicted energy load, the community controller analyzes the policies, distribute the results to the RES, and each RES can then control and schedule its own energy load based on different coordination functions.more » We utilize a framework to integrate both policy analysis and coordination of functions. With the use of our approach, we show that the policies are useful to resolve the challenges of energy management under external changes.« less

Density-functional theory based on the electron distribution on the energy coordinate

NASA Astrophysics Data System (ADS)

Takahashi, Hideaki

2018-03-01

We developed an electronic density functional theory utilizing a novel electron distribution n(ɛ) as a basic variable to compute ground state energy of a system. n(ɛ) is obtained by projecting the electron density n({\\boldsymbol{r}}) defined on the space coordinate {\\boldsymbol{r}} onto the energy coordinate ɛ specified with the external potential {\\upsilon }ext}({\\boldsymbol{r}}) of interest. It was demonstrated that the Kohn-Sham equation can also be formulated with the exchange-correlation functional E xc[n(ɛ)] that employs the density n(ɛ) as an argument. It turned out an exchange functional proposed in our preliminary development suffices to describe properly the potential energies of several types of chemical bonds with comparable accuracies to the corresponding functional based on local density approximation. As a remarkable feature of the distribution n(ɛ) it inherently involves the spatially non-local information of the exchange hole at the bond dissociation limit in contrast to conventional approximate functionals. By taking advantage of this property we also developed a prototype of the static correlation functional E sc including no empirical parameters, which showed marked improvements in describing the dissociations of covalent bonds in {{{H}}}2,{{{C}}}2{{{H}}}4 and {CH}}4 molecules.

Thermionic Properties of Carbon Based Nanomaterials Produced by Microhollow Cathode PECVD

NASA Technical Reports Server (NTRS)

Haase, John R.; Wolinksy, Jason J.; Bailey, Paul S.; George, Jeffrey A.; Go, David B.

2015-01-01

Thermionic emission is the process in which materials at sufficiently high temperature spontaneously emit electrons. This process occurs when electrons in a material gain sufficient thermal energy from heating to overcome the material's potential barrier, referred to as the work function. For most bulk materials very high temperatures (greater than 1500 K) are needed to produce appreciable emission. Carbon-based nanomaterials have shown significant promise as emission materials because of their low work functions, nanoscale geometry, and negative electron affinity. One method of producing these materials is through the process known as microhollow cathode PECVD. In a microhollow cathode plasma, high energy electrons oscillate at very high energies through the Pendel effect. These high energy electrons create numerous radical species and the technique has been shown to be an effective method of growing carbon based nanomaterials. In this work, we explore the thermionic emission properties of carbon based nanomaterials produced by microhollow cathode PECVD under a variety of synthesis conditions. Initial studies demonstrate measureable current at low temperatures (approximately 800 K) and work functions (approximately 3.3 eV) for these materials.

Association between nutritional status and disease severity using the amyotrophic lateral sclerosis (ALS) functional rating scale in ALS patients.

PubMed

Park, Yongsoon; Park, Jinhee; Kim, Yeonsun; Baek, Heejoon; Kim, Seung Hyun

2015-01-01

The nutritional status of patients with amyotrophic lateral sclerosis (ALS) has been shown to be associated with mortality. However, there have not been, to our knowledge, any studies on the association between nutritional status and disease severity. The present study investigated the hypothesis that nutritional status was negatively associated with disease severity using the ALS functional rating scale (ALSFRS-R). One hundred ninety-three Korean ALS patients were divided into tertiles based on their ALSFRS-R score. Dietary intake was measured using 24 h recall and nutritional status was determined by body mass index (BMI) and geriatric nutritional risk index (GNRI). BMI and GNRI were significantly lower in patients in the lowest tertile of ALSFRS-R. BMI and GNRI also correlated with ALSFRS-R score, bulbar score, albumin levels, total lymphocyte count, and total daily energy expenditure. Intakes of energy and most nutrients were significantly lower in patients in the lowest tertiles of ALSFRS-R, but significances disappeared after adjusting for energy intake. Intakes of vegetables, grains, seasonings, and oils were also significantly lower in patients in the lowest tertile of ALSFRS-R. In addition, patients in the lowest tertile of ALSFRS-R were significantly younger at disease onset, had a longer duration of ALS, less regular exercise, and less sun exposure. Nutritional status, as assessed by BMI and GNRI, was negatively associated with disease severity using ALSFRS-R. The present study suggested that intake of nutrients decreases with disease progression in ALS patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Electronic and optical properties of pure and modified diamondoids studied by many-body perturbation theory and time-dependent density functional theory

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

Demján, Tamás; Institute for Solid State Physics and Optics, Wigner Research Center for Physics, Hungarian Academy of Sciences, P.O. Box 49, H-1525 Budapest; Vörös, Márton

2014-08-14

Diamondoids are small diamond nanoparticles (NPs) that are built up from diamond cages. Unlike usual semiconductor NPs, their atomic structure is exactly known, thus they are ideal test-beds for benchmarking quantum chemical calculations. Their usage in spintronics and bioimaging applications requires a detailed knowledge of their electronic structure and optical properties. In this paper, we apply density functional theory (DFT) based methods to understand the electronic and optical properties of a few selected pure and modified diamondoids for which accurate experimental data exist. In particular, we use many-body perturbation theory methods, in the G{sub 0}W{sub 0} and G{sub 0}W{sub 0}+BSEmore » approximations, and time-dependent DFT in the adiabatic local density approximation. We find large quasiparticle gap corrections that can exceed thrice the DFT gap. The electron-hole binding energy can be as large as 4 eV but it is considerably smaller than the GW corrections and thus G{sub 0}W{sub 0}+BSE optical gaps are about 50% larger than the Kohn-Sham (KS) DFT gaps. We find significant differences between KS time-dependent DFT and GW+BSE optical spectra on the selected diamondoids. The calculated G{sub 0}W{sub 0} quasiparticle levels agree well with the corresponding experimental vertical ionization energies. We show that nuclei dynamics in the ionization process can be significant and its contribution may reach about 0.5 eV in the adiabatic ionization energies.« less

Inhibitors of HIV-protease from computational design. A history of theory and synthesis still to be fully appreciated.

PubMed

Berti, Federico; Frecer, Vladimir; Miertus, Stanislav

2014-01-01

Despite the fact that HIV-Protease is an over 20 years old target, computational approaches to rational design of its inhibitors still have a great potential to stimulate the synthesis of new compounds and the discovery of new, potent derivatives, ever capable to overcome the problem of drug resistance. This review deals with successful examples of inhibitors identified by computational approaches, rather than by knowledge-based design. Such methodologies include the development of energy and scoring functions, docking protocols, statistical models, virtual combinatorial chemistry. Computations addressing drug resistance, and the development of related models as the substrate envelope hypothesis are also reviewed. In some cases, the identified structures required the development of synthetic approaches in order to obtain the desired target molecules; several examples are reported.

First-principles study of point defects in thorium carbide

NASA Astrophysics Data System (ADS)

Pérez Daroca, D.; Jaroszewicz, S.; Llois, A. M.; Mosca, H. O.

2014-11-01

Thorium-based materials are currently being investigated in relation with their potential utilization in Generation-IV reactors as nuclear fuels. One of the most important issues to be studied is their behavior under irradiation. A first approach to this goal is the study of point defects. By means of first-principles calculations within the framework of density functional theory, we study the stability and formation energies of vacancies, interstitials and Frenkel pairs in thorium carbide. We find that C isolated vacancies are the most likely defects, while C interstitials are energetically favored as compared to Th ones. These kind of results for ThC, to the best authors' knowledge, have not been obtained previously, neither experimentally, nor theoretically. For this reason, we compare with results on other compounds with the same NaCl-type structure.

Complex-energy approach to sum rules within nuclear density functional theory

DOE PAGES

Hinohara, Nobuo; Kortelainen, Markus; Nazarewicz, Witold; ...

2015-04-27

The linear response of the nucleus to an external field contains unique information about the effective interaction, correlations governing the behavior of the many-body system, and properties of its excited states. To characterize the response, it is useful to use its energy-weighted moments, or sum rules. By comparing computed sum rules with experimental values, the information content of the response can be utilized in the optimization process of the nuclear Hamiltonian or nuclear energy density functional (EDF). But the additional information comes at a price: compared to the ground state, computation of excited states is more demanding. To establish anmore » efficient framework to compute energy-weighted sum rules of the response that is adaptable to the optimization of the nuclear EDF and large-scale surveys of collective strength, we have developed a new technique within the complex-energy finite-amplitude method (FAM) based on the quasiparticle random- phase approximation. The proposed sum-rule technique based on the complex-energy FAM is a tool of choice when optimizing effective interactions or energy functionals. The method is very efficient and well-adaptable to parallel computing. As a result, the FAM formulation is especially useful when standard theorems based on commutation relations involving the nuclear Hamiltonian and external field cannot be used.« less

Automated quantitative assessment of proteins' biological function in protein knowledge bases.

PubMed

Mayr, Gabriele; Lepperdinger, Günter; Lackner, Peter

2008-01-01

Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

A Study Combining Criticism and Qualitative Research Techniques for Appraising Classroom Media.

ERIC Educational Resources Information Center

Swartz, James D.

Qualitative criticism is a method of understanding things, actions, and events within a social framework. It is a method of acquiring knowledge to guide decision making based on local knowledge and a synthesis of principles from criticism and qualitative research. The function of qualitative criticism is centered with Richard Rorty's theoretical…

Mathematical Learning Models that Depend on Prior Knowledge and Instructional Strategies

ERIC Educational Resources Information Center

Pritchard, David E.; Lee, Young-Jin; Bao, Lei

2008-01-01

We present mathematical learning models--predictions of student's knowledge vs amount of instruction--that are based on assumptions motivated by various theories of learning: tabula rasa, constructivist, and tutoring. These models predict the improvement (on the post-test) as a function of the pretest score due to intervening instruction and also…

A Novel Architecture for E-Learning Knowledge Assessment Systems

ERIC Educational Resources Information Center

Gierlowski, Krzysztof; Nowicki, Krzysztof

2009-01-01

In this article we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture, while well suited for…

Plato, Pascal, and the Dynamics of Personal Knowledge

ERIC Educational Resources Information Center

Otte, Michael Friedrich; Campos, Tania M. M.; Abido, Alexandre S.

2013-01-01

Educational practices are to be based on proven scientific knowledge, not least because the function science has to perform in human culture consists of unifying practical skills and general beliefs, the episteme and the techne (Amsterdamski, 1975, pp. 43-44). Now, modern societies first of all presuppose regular and standardized ways of…

Using Social Media to Facilitate Knowledge Transfer in Complex Engineering Environments: A Primer for Educators

ERIC Educational Resources Information Center

Murphy, Glen; Salomone, Sonia

2013-01-01

While highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Consequently, an essential challenge for engineering organisations wishing to overcome informational silos is to implement mechanisms that…

Verbal Knowledge, Working Memory, and Processing Speed as Predictors of Verbal Learning in Older Adults

ERIC Educational Resources Information Center

Rast, Philippe

2011-01-01

The present study aimed at modeling individual differences in a verbal learning task by means of a latent structured growth curve approach based on an exponential function that yielded 3 parameters: initial recall, learning rate, and asymptotic performance. Three cognitive variables--speed of information processing, verbal knowledge, working…

Case-Exercises, Diagnosis, and Explanations in a Knowledge Based Tutoring System for Project Planning.

ERIC Educational Resources Information Center

Pulz, Michael; Lusti, Markus

PROJECTTUTOR is an intelligent tutoring system that enhances conventional classroom instruction by teaching problem solving in project planning. The domain knowledge covered by the expert module is divided into three functions. Structural analysis, identifies the activities that make up the project, time analysis, computes the earliest and latest…

Efficient globally optimal segmentation of cells in fluorescence microscopy images using level sets and convex energy functionals.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2012-10-01

In high-throughput applications, accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression and the understanding of cell function. We propose an approach for segmenting cell nuclei which is based on active contours using level sets and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We consider three different well-known energy functionals for active contour-based segmentation and introduce convex formulations of these functionals. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images from different experiments comprising different cell types. We have also performed a quantitative comparison with previous segmentation approaches. Copyright © 2012 Elsevier B.V. All rights reserved.

Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology

NASA Astrophysics Data System (ADS)

Eid, Sameh; Saleh, Noureldin; Zalewski, Adam; Vedani, Angelo

2014-12-01

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof. Unfortunately, the tested functions were not capable of reproducing binding affinities in the studied complexes. To simplify the complex free-energy surface of carbohydrate-protein systems, we classified the studied proteins according to the topology and solvent exposure of the carbohydrate-binding site into five distinct categories. A free-energy model based on the proposed classification scheme reproduced binding affinities in the carbohydrate data set with an r 2 of 0.71 and root-mean-squared-error of 1.25 kcal/mol ( N = 236). The improvement in model performance underlines the significance of the differences in the local micro-environments of carbohydrate-binding sites and demonstrates the usefulness of calibrating free-energy functions individually according to binding-site topology and solvent exposure.

HCl dissociating on a rigid Au(111) surface: A six-dimensional quantum mechanical study on a new potential energy surface based on the RPBE functional.

PubMed

Liu, Tianhui; Fu, Bina; Zhang, Dong H

2017-04-28

The dissociative chemisorption of HCl on the Au(111) surface has recently been an interesting and important subject, regarding the discrepancy between the theoretical dissociation probabilities and the experimental sticking probabilities. We here constructed an accurate full-dimensional (six-dimensional (6D)) potential energy surface (PES) based on the density functional theory (DFT) with the revised Perdew-Burke-Ernzerhof (RPBE) functional, and performed 6D quantum mechanical (QM) calculations for HCl dissociating on a rigid Au(111) surface. The effects of vibrational excitations, rotational orientations, and site-averaging approximation on the present RPBE PES are investigated. Due to the much higher barrier height obtained on the RPBE PES than on the PW91 PES, the agreement between the present theoretical and experimental results is greatly improved. In particular, at the very low kinetic energy, the QM-RPBE dissociation probability agrees well with the experimental data. However, the computed QM-RPBE reaction probabilities are still markedly different from the experimental values at most of the energy regions. In addition, the QM-RPBE results achieve good agreement with the recent ab initio molecular dynamics calculations based on the RPBE functional at high kinetic energies.

Energy Optimization for a Weak Hybrid Power System of an Automobile Exhaust Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Fang, Wei; Quan, Shuhai; Xie, Changjun; Tang, Xinfeng; Ran, Bin; Jiao, Yatian

2017-11-01

An integrated starter generator (ISG)-type hybrid electric vehicle (HEV) scheme is proposed based on the automobile exhaust thermoelectric generator (AETEG). An eddy current dynamometer is used to simulate the vehicle's dynamic cycle. A weak ISG hybrid bench test system is constructed to test the 48 V output from the power supply system, which is based on engine exhaust-based heat power generation. The thermoelectric power generation-based system must ultimately be tested when integrated into the ISG weak hybrid mixed power system. The test process is divided into two steps: comprehensive simulation and vehicle-based testing. The system's dynamic process is simulated for both conventional and thermoelectric powers, and the dynamic running process comprises four stages: starting, acceleration, cruising and braking. The quantity of fuel available and battery pack energy, which are used as target vehicle energy functions for comparison with conventional systems, are simplified into a single energy target function, and the battery pack's output current is used as the control variable in the thermoelectric hybrid energy optimization model. The system's optimal battery pack output current function is resolved when its dynamic operating process is considered as part of the hybrid thermoelectric power generation system. In the experiments, the system bench is tested using conventional power and hybrid thermoelectric power for the four dynamic operation stages. The optimal battery pack curve is calculated by functional analysis. In the vehicle, a power control unit is used to control the battery pack's output current and minimize energy consumption. Data analysis shows that the fuel economy of the hybrid power system under European Driving Cycle conditions is improved by 14.7% when compared with conventional systems.

MCTDH on-the-fly: Efficient grid-based quantum dynamics without pre-computed potential energy surfaces

NASA Astrophysics Data System (ADS)

Richings, Gareth W.; Habershon, Scott

2018-04-01

We present significant algorithmic improvements to a recently proposed direct quantum dynamics method, based upon combining well established grid-based quantum dynamics approaches and expansions of the potential energy operator in terms of a weighted sum of Gaussian functions. Specifically, using a sum of low-dimensional Gaussian functions to represent the potential energy surface (PES), combined with a secondary fitting of the PES using singular value decomposition, we show how standard grid-based quantum dynamics methods can be dramatically accelerated without loss of accuracy. This is demonstrated by on-the-fly simulations (using both standard grid-based methods and multi-configuration time-dependent Hartree) of both proton transfer on the electronic ground state of salicylaldimine and the non-adiabatic dynamics of pyrazine.

Biomechanics and symmetry

NASA Astrophysics Data System (ADS)

Ott, Albrecht

2004-04-01

Molecular motors are of nm scale they are the smallest motors known. They are quasi-omnipresent in the biological organism and among their most promiment functions are muscle contraction, flagellar motion, intracellular transport and cellular motion. In most cases the "fuel" for these motors is provided by the cleavage of a molecule named adenosinetri-phosphate (ATP) to its diphosphate (ADP). How this chemically stored energy is transformed into motion, although a subject of major research all over the world, is only partly understood. Motor function is a dynamical problem, and no technique today is capable of monitoring dynamics at nm scale. The energies involved are close to thermal, making a good signal to noise ratio difficult to achieve. Last not not least, a great deal of knowledge is needed to understand the multiple facets of this problem, ranging from biochemistry, nm technology to theoretical physics.

Cognitive decline impairs financial and health literacy among community-based older persons without dementia

PubMed Central

Boyle, Patricia A.; Yu, Lei; Wilson, Robert S.; Segawa, Eisuke; Buchman, Aron S.; Bennett, David A.

2013-01-01

Literacy is an important determinant of health and well-being across the lifespan but is critical in aging, when many influential health and financial decisions are made. Prior studies suggest that older persons exhibit lower literacy than younger persons, particularly in the domains of financial and health literacy, but the reasons why remain unknown. The objectives of this study were to: a) examine pathways linking diverse resources (i.e., education, word knowledge, cognitive function, and decision making style) to health and financial literacy among older persons and determine the extent to which the relation of age with literacy represents a direct effect versus an indirect effect due to decrements in specific cognitive functions (i.e., executive functions and episodic memory), and b) test the hypothesis that declines in executive function and episodic memory are associated with lower literacy among older persons without dementia. 645 community-based older persons without dementia underwent detailed assessments of diverse resources, including education, word knowledge, cognitive function (i.e., executive function, episodic memory) and decision making style (i.e., risk aversion), and completed a measure of literacy that included items similar to those assessed in the Health and Retirement Study, such as numeracy, financial concepts such as compound inflation and knowledge of stocks and bonds, and important health concepts such as understanding of drug risk and Medicare Part D. Path analysis revealed a strong effect of age on literacy, with about half of the effect of age on literacy due to decrements in executive functions and episodic memory. In addition, executive function had an indirect effect on literacy via decision making style (i.e., risk aversion), and education and word knowledge had independent effects on literacy. Finally, among (n=447) persons with repeated cognitive assessments available for up to 14 years, regression analysis supported the association of multiple resources with literacy; moreover, more rapid declines in executive function and episodic memory over an average of 6.4 years prior to the literacy assessment predicted lower literacy scores (p’s<0.02), but rate of decline in word knowledge did not. These findings suggest that diverse individual resources contribute to financial and health literacy and lower literacy in old age is partially due to declines in executive function and episodic memory. PMID:23957225

Cognitive decline impairs financial and health literacy among community-based older persons without dementia.

PubMed

Boyle, Patricia A; Yu, Lei; Wilson, Robert S; Segawa, Eisuke; Buchman, Aron S; Bennett, David A

2013-09-01

Literacy is an important determinant of health and well-being across the life span but is critical in aging, when many influential health and financial decisions are made. Prior studies suggest that older persons exhibit lower literacy than younger persons, particularly in the domains of financial and health literacy, but the reasons why remain unknown. The objectives of this study were to: (a) examine pathways linking diverse resources (i.e., education, word knowledge, cognitive function, and decision making style) to health and financial literacy among older persons and determine the extent to which the relation of age with literacy represents a direct effect versus an indirect effect due to decrements in specific cognitive functions (i.e., executive functions and episodic memory); and (b) test the hypothesis that declines in executive function and episodic memory are associated with lower literacy among older persons without dementia. Six-hundred and forty-five community-based older persons without dementia underwent detailed assessments of diverse resources, including education, word knowledge, cognitive function (i.e., executive function, episodic memory) and decision making style (i.e., risk aversion), and completed a measure of literacy that included items similar to those used in the Health and Retirement Study, such as numeracy, financial concepts such as compound inflation and knowledge of stocks and bonds, and important health concepts such as understanding of drug risk and Medicare Part D. Path analysis revealed a strong effect of age on literacy, with about half of the effect of age on literacy due to decrements in executive functions and episodic memory. In addition, executive function had an indirect effect on literacy via decision making style (i.e., risk aversion), and education and word knowledge had independent effects on literacy. Finally, among (n = 447) persons with repeated cognitive assessments available for up to 14 years, regression analysis supported the association of multiple resources with literacy; moreover, more rapid declines in executive function and episodic memory over an average of 6.4 years prior to the literacy assessment predicted lower literacy scores (ps < 0.02), but rate of decline in word knowledge did not. These findings suggest that diverse individual resources contribute to financial and health literacy and lower literacy in old age is partially due to declines in executive function and episodic memory.

Cassava root membrane proteome reveals activities during storage root maturation.

PubMed

Naconsie, Maliwan; Lertpanyasampatha, Manassawe; Viboonjun, Unchera; Netrphan, Supatcharee; Kuwano, Masayoshi; Ogasawara, Naotake; Narangajavana, Jarunya

2016-01-01

Cassava (Manihot esculenta Crantz) is one of the most important crops of Thailand. Its storage roots are used as food, feed, starch production, and be the important source for biofuel and biodegradable plastic production. Despite the importance of cassava storage roots, little is known about the mechanisms involved in their formation. This present study has focused on comparison of the expression profiles of cassava root proteome at various developmental stages using two-dimensional gel electrophoresis and LC-MS/MS. Based on an anatomical study using Toluidine Blue, the secondary growth was confirmed to be essential during the development of cassava storage root. To investigate biochemical processes occurring during storage root maturation, soluble and membrane proteins were isolated from storage roots harvested from 3-, 6-, 9-, and 12-month-old cassava plants. The proteins with differential expression pattern were analysed and identified to be associated with 8 functional groups: protein folding and degradation, energy, metabolism, secondary metabolism, stress response, transport facilitation, cytoskeleton, and unclassified function. The expression profiling of membrane proteins revealed the proteins involved in protein folding and degradation, energy, and cell structure were highly expressed during early stages of development. Integration of these data along with the information available in genome and transcriptome databases is critical to expand knowledge obtained solely from the field of proteomics. Possible role of identified proteins were discussed in relation with the activities during storage root maturation in cassava.

Can Sgr A* flares reveal the molecular gas density PDF?

NASA Astrophysics Data System (ADS)

Churazov, E.; Khabibullin, I.; Sunyaev, R.; Ponti, G.

2017-11-01

Illumination of dense gas in the Central Molecular Zone by powerful X-ray flares from Sgr A* leads to prominent structures in the reflected emission that can be observed long after the end of the flare. By studying this emission, we learn about past activity of the supermassive black hole in our Galactic Center and, at the same time, we obtain unique information on the structure of molecular clouds that is essentially impossible to get by other means. Here we discuss how X-ray data can improve our knowledge of both sides of the problem. Existing data already provide (I) an estimate of the flare age, (II) a model-independent lower limit on the luminosity of Sgr A* during the flare and (III) an estimate of the total emitted energy during Sgr A* flare. On the molecular clouds side, the data clearly show a voids-and-walls structure of the clouds and can provide an almost unbiased probe of the mass/density distribution of the molecular gas with the hydrogen column densities lower than few 1023 cm-2. For instance, the probability distribution function of the gas density PDF(ρ) can be measured this way. Future high energy resolution X-ray missions will provide the information on the gas velocities, allowing, for example, a reconstruction of the velocity field structure functions and cross-matching the X-ray and molecular data based on positions and velocities.

Cost Function Network-based Design of Protein-Protein Interactions: predicting changes in binding affinity.

PubMed

Viricel, Clément; de Givry, Simon; Schiex, Thomas; Barbe, Sophie

2018-02-20

Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributions. Following the recent progresses of Artificial Intelligence-based algorithms for guaranteed NP-hard energy optimization and partition function computation, it becomes possible to quickly compute minimum energy conformations and to reliably estimate the entropic contribution of side-chains in the change of free energy of large protein interfaces. Using guaranteed Cost Function Network algorithms, Rosetta energy functions and Dunbrack's rotamer library, we developed and assessed EasyE and JayZ, two methods for binding affinity estimation that ignore or include conformational entropic contributions on a large benchmark of binding affinity experimental measures. If both approaches outperform most established tools, we observe that side-chain conformational entropy brings little or no improvement on most systems but becomes crucial in some rare cases. as open-source Python/C ++ code at sourcesup.renater.fr/projects/easy-jayz. thomas.schiex@inra.fr and sophie.barbe@insa-toulouse.fr. Supplementary data are available at Bioinformatics online.

Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction.

PubMed

Whittleton, Sarah R; Otero-de-la-Roza, A; Johnson, Erin R

2017-02-14

Accurate energy ranking is a key facet to the problem of first-principles crystal-structure prediction (CSP) of molecular crystals. This work presents a systematic assessment of B86bPBE-XDM, a semilocal density functional combined with the exchange-hole dipole moment (XDM) dispersion model, for energy ranking using 14 compounds from the first five CSP blind tests. Specifically, the set of crystals studied comprises 11 rigid, planar compounds and 3 co-crystals. The experimental structure was correctly identified as the lowest in lattice energy for 12 of the 14 total crystals. One of the exceptions is 4-hydroxythiophene-2-carbonitrile, for which the experimental structure was correctly identified once a quasi-harmonic estimate of the vibrational free-energy contribution was included, evidencing the occasional importance of thermal corrections for accurate energy ranking. The other exception is an organic salt, where charge-transfer error (also called delocalization error) is expected to cause the base density functional to be unreliable. Provided the choice of base density functional is appropriate and an estimate of temperature effects is used, XDM-corrected density-functional theory is highly reliable for the energetic ranking of competing crystal structures.

Knowledge acquisition and representation using fuzzy evidential reasoning and dynamic adaptive fuzzy Petri nets.

PubMed

Liu, Hu-Chen; Liu, Long; Lin, Qing-Lian; Liu, Nan

2013-06-01

The two most important issues of expert systems are the acquisition of domain experts' professional knowledge and the representation and reasoning of the knowledge rules that have been identified. First, during expert knowledge acquisition processes, the domain expert panel often demonstrates different experience and knowledge from one another and produces different types of knowledge information such as complete and incomplete, precise and imprecise, and known and unknown because of its cross-functional and multidisciplinary nature. Second, as a promising tool for knowledge representation and reasoning, fuzzy Petri nets (FPNs) still suffer a couple of deficiencies. The parameters in current FPN models could not accurately represent the increasingly complex knowledge-based systems, and the rules in most existing knowledge inference frameworks could not be dynamically adjustable according to propositions' variation as human cognition and thinking. In this paper, we present a knowledge acquisition and representation approach using the fuzzy evidential reasoning approach and dynamic adaptive FPNs to solve the problems mentioned above. As is illustrated by the numerical example, the proposed approach can well capture experts' diversity experience, enhance the knowledge representation power, and reason the rule-based knowledge more intelligently.

The KATE shell: An implementation of model-based control, monitor and diagnosis

NASA Technical Reports Server (NTRS)

Cornell, Matthew

1987-01-01

The conventional control and monitor software currently used by the Space Center for Space Shuttle processing has many limitations such as high maintenance costs, limited diagnostic capabilities and simulation support. These limitations have caused the development of a knowledge based (or model based) shell to generically control and monitor electro-mechanical systems. The knowledge base describes the system's structure and function and is used by a software shell to do real time constraints checking, low level control of components, diagnosis of detected faults, sensor validation, automatic generation of schematic diagrams and automatic recovery from failures. This approach is more versatile and more powerful than the conventional hard coded approach and offers many advantages over it, although, for systems which require high speed reaction times or aren't well understood, knowledge based control and monitor systems may not be appropriate.

Plant functional diversity increases grassland productivity-related water vapor fluxes: an Ecotron and modeling approach.

PubMed

Milcu, Alexandru; Eugster, Werner; Bachmann, Dörte; Guderle, Marcus; Roscher, Christiane; Gockele, Annette; Landais, Damien; Ravel, Olivier; Gessler, Arthur; Lange, Markus; Ebeling, Anne; Weisser, Wolfgang W; Roy, Jacques; Hildebrandt, Anke; Buchmann, Nina

2016-08-01

The impact of species richness and functional diversity of plants on ecosystem water vapor fluxes has been little investigated. To address this knowledge gap, we combined a lysimeter setup in a controlled environment facility (Ecotron) with large ecosystem samples/monoliths originating from a long-term biodiversity experiment (The Jena Experiment) and a modeling approach. Our goals were (1) quantifying the impact of plant species richness (four vs. 16 species) on day- and nighttime ecosystem water vapor fluxes; (2) partitioning ecosystem evapotranspiration into evaporation and plant transpiration using the Shuttleworth and Wallace (SW) energy partitioning model; and (3) identifying the most parsimonious predictors of water vapor fluxes using plant functional-trait-based metrics such as functional diversity and community weighted means. Daytime measured and modeled evapotranspiration were significantly higher in the higher plant diversity treatment, suggesting increased water acquisition. The SW model suggests that, at low plant species richness, a higher proportion of the available energy was diverted to evaporation (a non-productive flux), while, at higher species richness, the proportion of ecosystem transpiration (a productivity-related water flux) increased. While it is well established that LAI controls ecosystem transpiration, here we also identified that the diversity of leaf nitrogen concentration among species in a community is a consistent predictor of ecosystem water vapor fluxes during daytime. The results provide evidence that, at the peak of the growing season, higher leaf area index (LAI) and lower percentage of bare ground at high plant diversity diverts more of the available water to transpiration, a flux closely coupled with photosynthesis and productivity. Higher rates of transpiration presumably contribute to the positive effect of diversity on productivity. © 2016 by the Ecological Society of America.

10 CFR 1046.15 - Training and qualification for security skills and knowledge.

Code of Federal Regulations, 2010 CFR

2010-01-01

... knowledge. 1046.15 Section 1046.15 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) PHYSICAL PROTECTION OF... knowledge. (a) DOE contractors shall only employ as protective force personnel individuals who successfully... and Qualification for Security Skills and Knowledge,” to this subpart. The DOE contractor shall...

Energy deposition of H and He ion beams in hydroxyapatite films: a study with implications for ion-beam cancer therapy.

PubMed

Limandri, Silvina; de Vera, Pablo; Fadanelli, Raul C; Nagamine, Luiz C C M; Mello, Alexandre; Garcia-Molina, Rafael; Behar, Moni; Abril, Isabel

2014-02-01

Ion-beam cancer therapy is a promising technique to treat deep-seated tumors; however, for an accurate treatment planning, the energy deposition by the ions must be well known both in soft and hard human tissues. Although the energy loss of ions in water and other organic and biological materials is fairly well known, scarce information is available for the hard tissues (i.e., bone), for which the current stopping power information relies on the application of simple additivity rules to atomic data. Especially, more knowledge is needed for the main constituent of human bone, calcium hydroxyapatite (HAp), which constitutes 58% of its mass composition. In this work the energy loss of H and He ion beams in HAp films has been obtained experimentally. The experiments have been performed using the Rutherford backscattering technique in an energy range of 450-2000 keV for H and 400-5000 keV for He ions. These measurements are used as a benchmark for theoretical calculations (stopping power and mean excitation energy) based on the dielectric formalism together with the MELF-GOS (Mermin energy loss function-generalized oscillator strength) method to describe the electronic excitation spectrum of HAp. The stopping power calculations are in good agreement with the experiments. Even though these experimental data are obtained for low projectile energies compared with the ones used in hadron therapy, they validate the mean excitation energy obtained theoretically, which is the fundamental quantity to accurately assess energy deposition and depth-dose curves of ion beams at clinically relevant high energies. The effect of the mean excitation energy choice on the depth-dose profile is discussed on the basis of detailed simulations. Finally, implications of the present work on the energy loss of charged particles in human cortical bone are remarked.