Variability in perceived satisfaction of reservoir management objectives

USGS Publications Warehouse

Owen, W.J.; Gates, T.K.; Flug, M.

1997-01-01

Fuzzy set theory provides a useful model to address imprecision in interpreting linguistically described objectives for reservoir management. Fuzzy membership functions can be used to represent degrees of objective satisfaction for different values of management variables. However, lack of background information, differing experiences and qualifications, and complex interactions of influencing factors can contribute to significant variability among membership functions derived from surveys of multiple experts. In the present study, probabilistic membership functions are used to model variability in experts' perceptions of satisfaction of objectives for hydropower generation, fish habitat, kayaking, rafting, and scenery preservation on the Green River through operations of Flaming Gorge Dam. Degree of variability in experts' perceptions differed among objectives but resulted in substantial uncertainty in estimation of optimal reservoir releases.

The neural basis of precise visual short-term memory for complex recognisable objects.

PubMed

Veldsman, Michele; Mitchell, Daniel J; Cusack, Rhodri

2017-10-01

Recent evidence suggests that visual short-term memory (VSTM) capacity estimated using simple objects, such as colours and oriented bars, may not generalise well to more naturalistic stimuli. More visual detail can be stored in VSTM when complex, recognisable objects are maintained compared to simple objects. It is not yet known if it is recognisability that enhances memory precision, nor whether maintenance of recognisable objects is achieved with the same network of brain regions supporting maintenance of simple objects. We used a novel stimulus generation method to parametrically warp photographic images along a continuum, allowing separate estimation of the precision of memory representations and the number of items retained. The stimulus generation method was also designed to create unrecognisable, though perceptually matched, stimuli, to investigate the impact of recognisability on VSTM. We adapted the widely-used change detection and continuous report paradigms for use with complex, photographic images. Across three functional magnetic resonance imaging (fMRI) experiments, we demonstrated greater precision for recognisable objects in VSTM compared to unrecognisable objects. This clear behavioural advantage was not the result of recruitment of additional brain regions, or of stronger mean activity within the core network. Representational similarity analysis revealed greater variability across item repetitions in the representations of recognisable, compared to unrecognisable complex objects. We therefore propose that a richer range of neural representations support VSTM for complex recognisable objects. Copyright © 2017 Elsevier Inc. All rights reserved.

Enhanced Multiobjective Optimization Technique for Comprehensive Aerospace Design. Part A

NASA Technical Reports Server (NTRS)

Chattopadhyay, Aditi; Rajadas, John N.

1997-01-01

A multidisciplinary design optimization procedure which couples formal multiobjectives based techniques and complex analysis procedures (such as computational fluid dynamics (CFD) codes) developed. The procedure has been demonstrated on a specific high speed flow application involving aerodynamics and acoustics (sonic boom minimization). In order to account for multiple design objectives arising from complex performance requirements, multiobjective formulation techniques are used to formulate the optimization problem. Techniques to enhance the existing Kreisselmeier-Steinhauser (K-S) function multiobjective formulation approach have been developed. The K-S function procedure used in the proposed work transforms a constrained multiple objective functions problem into an unconstrained problem which then is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Weight factors are introduced during the transformation process to each objective function. This enhanced procedure will provide the designer the capability to emphasize specific design objectives during the optimization process. The demonstration of the procedure utilizes a computational Fluid dynamics (CFD) code which solves the three-dimensional parabolized Navier-Stokes (PNS) equations for the flow field along with an appropriate sonic boom evaluation procedure thus introducing both aerodynamic performance as well as sonic boom as the design objectives to be optimized simultaneously. Sensitivity analysis is performed using a discrete differentiation approach. An approximation technique has been used within the optimizer to improve the overall computational efficiency of the procedure in order to make it suitable for design applications in an industrial setting.

Cannabis Use and Memory Brain Function in Adolescent Boys: A Cross-Sectional Multicenter Functional Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Jager, Gerry; Block, Robert I.; Luijten, Maartje; Ramsey, Nick F.

2010-01-01

Objective: Early-onset cannabis use has been associated with later use/abuse, mental health problems (psychosis, depression), and abnormal development of cognition and brain function. During adolescence, ongoing neurodevelopmental maturation and experience shape the neural circuitry underlying complex cognitive functions such as memory and…

Computer simulation of functioning of elements of security systems

NASA Astrophysics Data System (ADS)

Godovykh, A. V.; Stepanov, B. P.; Sheveleva, A. A.

2017-01-01

The article is devoted to issues of development of the informational complex for simulation of functioning of the security system elements. The complex is described from the point of view of main objectives, a design concept and an interrelation of main elements. The proposed conception of the computer simulation provides an opportunity to simulate processes of security system work for training security staff during normal and emergency operation.

IRAS observations of the Rho Ophiuchi infrared cluster - Spectral energy distributions and luminosity function

NASA Technical Reports Server (NTRS)

Wilking, Bruce A.; Lada, Charles J.; Young, Eric T.

1989-01-01

High-sensitivity IRAS coadded survey data, coupled with new high-sensitivity near-IR observations, are used to investigate the nature of embedded objects over an 4.3-sq-pc area comprising the central star-forming cloud of the Ophiuchi molecular complex; the area encompasses the central cloud of the Rho Ophiuchi complex and includes the core region. Seventy-eight members of the embedded cluster were identified; spectral energy distributions were constructed for 53 objects and were compared with theoretical models to gain insight into their evolutionary status. Bolometric luminosities could be estimated for nearly all of the association members, leading to a revised luminosity function for this dust-embedded cluster.

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.

PubMed

Güçlü, Umut; van Gerven, Marcel A J

2015-07-08

Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream. Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0.

Computational complexity of Boolean functions

NASA Astrophysics Data System (ADS)

Korshunov, Aleksei D.

2012-02-01

Boolean functions are among the fundamental objects of discrete mathematics, especially in those of its subdisciplines which fall under mathematical logic and mathematical cybernetics. The language of Boolean functions is convenient for describing the operation of many discrete systems such as contact networks, Boolean circuits, branching programs, and some others. An important parameter of discrete systems of this kind is their complexity. This characteristic has been actively investigated starting from Shannon's works. There is a large body of scientific literature presenting many fundamental results. The purpose of this survey is to give an account of the main results over the last sixty years related to the complexity of computation (realization) of Boolean functions by contact networks, Boolean circuits, and Boolean circuits without branching. Bibliography: 165 titles.

A mechanism producing power law etc. distributions

NASA Astrophysics Data System (ADS)

Li, Heling; Shen, Hongjun; Yang, Bin

2017-07-01

Power law distribution is playing an increasingly important role in the complex system study. Based on the insolvability of complex systems, the idea of incomplete statistics is utilized and expanded, three different exponential factors are introduced in equations about the normalization condition, statistical average and Shannon entropy, with probability distribution function deduced about exponential function, power function and the product form between power function and exponential function derived from Shannon entropy and maximal entropy principle. So it is shown that maximum entropy principle can totally replace equal probability hypothesis. Owing to the fact that power and probability distribution in the product form between power function and exponential function, which cannot be derived via equal probability hypothesis, can be derived by the aid of maximal entropy principle, it also can be concluded that maximal entropy principle is a basic principle which embodies concepts more extensively and reveals basic principles on motion laws of objects more fundamentally. At the same time, this principle also reveals the intrinsic link between Nature and different objects in human society and principles complied by all.

Multiobjective optimization techniques for structural design

NASA Technical Reports Server (NTRS)

Rao, S. S.

1984-01-01

The multiobjective programming techniques are important in the design of complex structural systems whose quality depends generally on a number of different and often conflicting objective functions which cannot be combined into a single design objective. The applicability of multiobjective optimization techniques is studied with reference to simple design problems. Specifically, the parameter optimization of a cantilever beam with a tip mass and a three-degree-of-freedom vabration isolation system and the trajectory optimization of a cantilever beam are considered. The solutions of these multicriteria design problems are attempted by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It has been observed that the game theory approach required the maximum computational effort, but it yielded better optimum solutions with proper balance of the various objective functions in all the cases.

OB3D, a new set of 3D objects available for research: a web-based study

PubMed Central

Buffat, Stéphane; Chastres, Véronique; Bichot, Alain; Rider, Delphine; Benmussa, Frédéric; Lorenceau, Jean

2014-01-01

Studying object recognition is central to fundamental and clinical research on cognitive functions but suffers from the limitations of the available sets that cannot always be modified and adapted to meet the specific goals of each study. We here present a new set of 3D scans of real objects available on-line as ASCII files, OB3D. These files are lists of dots, each defined by a triplet of spatial coordinates and their normal that allow simple and highly versatile transformations and adaptations. We performed a web-based experiment to evaluate the minimal number of dots required for the denomination and categorization of these objects, thus providing a reference threshold. We further analyze several other variables derived from this data set, such as the correlations with object complexity. This new stimulus set, which was found to activate the Lower Occipital Complex (LOC) in another study, may be of interest for studies of cognitive functions in healthy participants and patients with cognitive impairments, including visual perception, language, memory, etc. PMID:25339920

[Influence of mental rotation of objects on psychophysiological functions of women].

PubMed

Chikina, L V; Fedorchuk, S V; Trushina, V A; Ianchuk, P I; Makarchuk, M Iu

2012-01-01

An integral part of activity of modern human beings is an involvement to work with the computer systems which, in turn, produces a nervous - emotional tension. Hence, a problem of control of the psychophysiological state of workmen with the purpose of health preservation and success of their activity and the problem of application of rehabilitational actions are actual. At present it is known that the efficiency of rehabilitational procedures rises following application of the complex of regenerative programs. Previously performed by us investigation showed that mental rotation is capable to compensate the consequences of a nervous - emotional tension. Therefore, in the present work we investigated how the complex of spatial tasks developed by us influences psychophysiological performances of tested women for which the psycho-emotional tension with the usage of computer technologies is more essential, and the procedure of mental rotation is more complex task for them, than for men. The complex of spatial tasks applied in the given work included: mental rotation of simple objects (letters and digits), mental rotation of complex objects (geometrical figures) and mental rotation of complex objects with the usage of a short-term memory. Execution of the complex of spatial tasks reduces the time of simple and complex sensomotor response, raises parameters of a short-term memory, brain work capacity and improves nervous processes. Collectively, mental rotation of objects can be recommended as a rehabilitational resource for compensation of consequences of any psycho-emotional strain, both for men, and for women.

EPR Characterization of Dinitrosyl Iron Complexes with Thiol-Containing Ligands as an Approach to Their Identification in Biological Objects: An Overview.

PubMed

Vanin, Anatoly F

2018-06-01

The overview demonstrates how the use of only one physico-chemical approach, viz., the electron paramagnetic resonance method, allowed detection and identification of dinitrosyl iron complexes with thiol-containing ligands in various animal and bacterial cells. These complexes are formed in biological objects in the paramagnetic (electron paramagnetic resonance-active) mononuclear and diamagnetic (electron paramagnetic resonance-silent) binuclear forms and control the activity of nitrogen monoxide, one of the most universal regulators of metabolic processes in the organism. The analysis of electronic and spatial structures of dinitrosyl iron complex sheds additional light on the mechanism whereby dinitrosyl iron complex with thiol-containing ligands function in human and animal cells as donors of nitrogen monoxide and its ionized form, viz., nitrosonium ions (NO + ).

Improvement of the F-Perceptory Approach Through Management of Fuzzy Complex Geographic Objects

NASA Astrophysics Data System (ADS)

Khalfi, B.; de Runz, C.; Faiz, S.; Akdag, H.

2015-08-01

In the real world, data is imperfect and in various ways such as imprecision, vagueness, uncertainty, ambiguity and inconsistency. For geographic data, the fuzzy aspect is mainly manifested in time, space and the function of objects and is due to a lack of precision. Therefore, the researchers in the domain emphasize the importance of modeling data structures in GIS but also their lack of adaptation to fuzzy data. The F-Perceptory approachh manages the modeling of imperfect geographic information with UML. This management is essential to maintain faithfulness to reality and to better guide the user in his decision-making. However, this approach does not manage fuzzy complex geographic objects. The latter presents a multiple object with similar or different geographic shapes. So, in this paper, we propose to improve the F-Perceptory approach by proposing to handle fuzzy complex geographic objects modeling. In a second step, we propose its transformation to the UML modeling.

Selective visual attention in object detection processes

NASA Astrophysics Data System (ADS)

Paletta, Lucas; Goyal, Anurag; Greindl, Christian

2003-03-01

Object detection is an enabling technology that plays a key role in many application areas, such as content based media retrieval. Attentive cognitive vision systems are here proposed where the focus of attention is directed towards the most relevant target. The most promising information is interpreted in a sequential process that dynamically makes use of knowledge and that enables spatial reasoning on the local object information. The presented work proposes an innovative application of attention mechanisms for object detection which is most general in its understanding of information and action selection. The attentive detection system uses a cascade of increasingly complex classifiers for the stepwise identification of regions of interest (ROIs) and recursively refined object hypotheses. While the most coarse classifiers are used to determine first approximations on a region of interest in the input image, more complex classifiers are used for more refined ROIs to give more confident estimates. Objects are modelled by local appearance based representations and in terms of posterior distributions of the object samples in eigenspace. The discrimination function to discern between objects is modeled by a radial basis functions (RBF) network that has been compared with alternative networks and been proved consistent and superior to other artifical neural networks for appearance based object recognition. The experiments were led for the automatic detection of brand objects in Formula One broadcasts within the European Commission's cognitive vision project DETECT.

Basic mathematical function libraries for scientific computation

NASA Technical Reports Server (NTRS)

Galant, David C.

1989-01-01

Ada packages implementing selected mathematical functions for the support of scientific and engineering applications were written. The packages provide the Ada programmer with the mathematical function support found in the languages Pascal and FORTRAN as well as an extended precision arithmetic and a complete complex arithmetic. The algorithms used are fully described and analyzed. Implementation assumes that the Ada type FLOAT objects fully conform to the IEEE 754-1985 standard for single binary floating-point arithmetic, and that INTEGER objects are 32-bit entities. Codes for the Ada packages are included as appendixes.

Multiscale moment-based technique for object matching and recognition

NASA Astrophysics Data System (ADS)

Thio, HweeLi; Chen, Liya; Teoh, Eam-Khwang

2000-03-01

A new method is proposed to extract features from an object for matching and recognition. The features proposed are a combination of local and global characteristics -- local characteristics from the 1-D signature function that is defined to each pixel on the object boundary, global characteristics from the moments that are generated from the signature function. The boundary of the object is first extracted, then the signature function is generated by computing the angle between two lines from every point on the boundary as a function of position along the boundary. This signature function is position, scale and rotation invariant (PSRI). The shape of the signature function is then described quantitatively by using moments. The moments of the signature function are the global characters of a local feature set. Using moments as the eventual features instead of the signature function reduces the time and complexity of an object matching application. Multiscale moments are implemented to produce several sets of moments that will generate more accurate matching. Basically multiscale technique is a coarse to fine procedure and makes the proposed method more robust to noise. This method is proposed to match and recognize objects under simple transformation, such as translation, scale changes, rotation and skewing. A simple logo indexing system is implemented to illustrate the performance of the proposed method.

Enabling complex queries to drug information sources through functional composition.

PubMed

Peters, Lee; Mortensen, Jonathan; Nguyen, Thang; Bodenreider, Olivier

2013-01-01

Our objective was to enable an end-user to create complex queries to drug information sources through functional composition, by creating sequences of functions from application program interfaces (API) to drug terminologies. The development of a functional composition model seeks to link functions from two distinct APIs. An ontology was developed using Protégé to model the functions of the RxNorm and NDF-RT APIs by describing the semantics of their input and output. A set of rules were developed to define the interoperable conditions for functional composition. The operational definition of interoperability between function pairs is established by executing the rules on the ontology. We illustrate that the functional composition model supports common use cases, including checking interactions for RxNorm drugs and deploying allergy lists defined in reference to drug properties in NDF-RT. This model supports the RxMix application (http://mor.nlm.nih.gov/RxMix/), an application we developed for enabling complex queries to the RxNorm and NDF-RT APIs.

Simulation and fitting of complex reaction network TPR: The key is the objective function

DOE PAGES

Savara, Aditya Ashi

2016-07-07

In this research, a method has been developed for finding improved fits during simulation and fitting of data from complex reaction network temperature programmed reactions (CRN-TPR). It was found that simulation and fitting of CRN-TPR presents additional challenges relative to simulation and fitting of simpler TPR systems. The method used here can enable checking the plausibility of proposed chemical mechanisms and kinetic models. The most important finding was that when choosing an objective function, use of an objective function that is based on integrated production provides more utility in finding improved fits when compared to an objective function based onmore » the rate of production. The response surface produced by using the integrated production is monotonic, suppresses effects from experimental noise, requires fewer points to capture the response behavior, and can be simulated numerically with smaller errors. For CRN-TPR, there is increased importance (relative to simple reaction network TPR) in resolving of peaks prior to fitting, as well as from weighting of experimental data points. Using an implicit ordinary differential equation solver was found to be inadequate for simulating CRN-TPR. Lastly, the method employed here was capable of attaining improved fits in simulation and fitting of CRN-TPR when starting with a postulated mechanism and physically realistic initial guesses for the kinetic parameters.« less

Development of structural model of adaptive training complex in ergatic systems for professional use

NASA Astrophysics Data System (ADS)

Obukhov, A. D.; Dedov, D. L.; Arkhipov, A. E.

2018-03-01

The article considers the structural model of the adaptive training complex (ATC), which reflects the interrelations between the hardware, software and mathematical model of ATC and describes the processes in this subject area. The description of the main components of software and hardware complex, their interaction and functioning within the common system are given. Also the article scrutinizers a brief description of mathematical models of personnel activity, a technical system and influences, the interactions of which formalize the regularities of ATC functioning. The studies of main objects of training complexes and connections between them will make it possible to realize practical implementation of ATC in ergatic systems for professional use.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Are we under-utilizing the talents of primary care personnel? A job analytic examination

PubMed Central

Hysong, Sylvia J; Best, Richard G; Moore, Frank I

2007-01-01

Background Primary care staffing decisions are often made unsystematically, potentially leading to increased costs, dissatisfaction, turnover, and reduced quality of care. This article aims to (1) catalogue the domain of primary care tasks, (2) explore the complexity associated with these tasks, and (3) examine how tasks performed by different job titles differ in function and complexity, using Functional Job Analysis to develop a new tool for making evidence-based staffing decisions. Methods Seventy-seven primary care personnel from six US Department of Veterans Affairs (VA) Medical Centers, representing six job titles, participated in two-day focus groups to generate 243 unique task statements describing the content of VA primary care. Certified job analysts rated tasks on ten dimensions representing task complexity, skills, autonomy, and error consequence. Two hundred and twenty-four primary care personnel from the same clinics then completed a survey indicating whether they performed each task. Tasks were catalogued using an adaptation of an existing classification scheme; complexity differences were tested via analysis of variance. Results Objective one: Task statements were categorized into four functions: service delivery (65%), administrative duties (15%), logistic support (9%), and workforce management (11%). Objective two: Consistent with expectations, 80% of tasks received ratings at or below the mid-scale value on all ten scales. Objective three: Service delivery and workforce management tasks received higher ratings on eight of ten scales (multiple functional complexity dimensions, autonomy, human error consequence) than administrative and logistic support tasks. Similarly, tasks performed by more highly trained job titles received higher ratings on six of ten scales than tasks performed by lower trained job titles. Contrary to expectations, the distribution of tasks across functions did not significantly vary by job title. Conclusion Primary care personnel are not being utilized to the extent of their training; most personnel perform many tasks that could reasonably be performed by personnel with less training. Primary care clinics should use evidence-based information to optimize job-person fit, adjusting clinic staff mix and allocation of work across staff to enhance efficiency and effectiveness. PMID:17397534

Lifetimes of the Vibrational States of DNA Molecules in Functionalized Complexes of Semiconductor Quantum Dots

NASA Astrophysics Data System (ADS)

Bayramov, F. B.; Poloskin, E. D.; Chernev, A. L.; Toporov, V. V.; Dubina, M. V.; Sprung, C.; Lipsanen, H. K.; Bairamov, B. Kh.

2018-01-01

Results of studying nanocrystalline nc-Si/SiO2 quantum dots (QDs) functionalized by short oligonucleotides show that complexes of isolated crystalline semiconductor QDs are unique objects for detecting the manifestation of new quantum confinement phenomena. It is established that narrow lines observed in high-resolution spectra of inelastic light scattering can be used for determining the characteristic time scale of vibrational excitations of separate nucleotide molecules and for studying structural-dynamic properties of fast oscillatory processes in biomacromolecules.

Evolution of natural agents: preservation, advance, and emergence of functional information.

PubMed

Sharov, Alexei A

2016-04-01

Biological evolution is often viewed narrowly as a change of morphology or allele frequency in a sequence of generations. Here I pursue an alternative informational concept of evolution, as preservation, advance, and emergence of functional information in natural agents. Functional information is a network of signs (e.g., memory, transient messengers, and external signs) that are used by agents to preserve and regulate their functions. Functional information is preserved in evolution via complex interplay of copying and construction processes: the digital components are copied, whereas interpreting subagents together with scaffolds, tools, and resources, are constructed. Some of these processes are simple and invariant, whereas others are complex and contextual. Advance of functional information includes improvement and modification of already existing functions. Although the genome information may change passively and randomly, the interpretation is active and guided by the logic of agent behavior and embryonic development. Emergence of new functions is based on the reinterpretation of already existing information, when old tools, resources, and control algorithms are adopted for novel functions. Evolution of functional information progressed from protosemiosis, where signs correspond directly to actions, to eusemiosis, where agents associate signs with objects. Language is the most advanced form of eusemiosis, where the knowledge of objects and models is communicated between agents.

Evolution of natural agents: preservation, advance, and emergence of functional information

PubMed Central

Sharov, Alexei A.

2016-01-01

Biological evolution is often viewed narrowly as a change of morphology or allele frequency in a sequence of generations. Here I pursue an alternative informational concept of evolution, as preservation, advance, and emergence of functional information in natural agents. Functional information is a network of signs (e.g., memory, transient messengers, and external signs) that are used by agents to preserve and regulate their functions. Functional information is preserved in evolution via complex interplay of copying and construction processes: the digital components are copied, whereas interpreting subagents together with scaffolds, tools, and resources, are constructed. Some of these processes are simple and invariant, whereas others are complex and contextual. Advance of functional information includes improvement and modification of already existing functions. Although the genome information may change passively and randomly, the interpretation is active and guided by the logic of agent behavior and embryonic development. Emergence of new functions is based on the reinterpretation of already existing information, when old tools, resources, and control algorithms are adopted for novel functions. Evolution of functional information progressed from protosemiosis, where signs correspond directly to actions, to eusemiosis, where agents associate signs with objects. Language is the most advanced form of eusemiosis, where the knowledge of objects and models is communicated between agents. PMID:27525048

Classifier-Guided Sampling for Complex Energy System Optimization

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

Backlund, Peter B.; Eddy, John P.

2015-09-01

This report documents the results of a Laboratory Directed Research and Development (LDRD) effort enti tled "Classifier - Guided Sampling for Complex Energy System Optimization" that was conducted during FY 2014 and FY 2015. The goal of this proj ect was to develop, implement, and test major improvements to the classifier - guided sampling (CGS) algorithm. CGS is type of evolutionary algorithm for perform ing search and optimization over a set of discrete design variables in the face of one or more objective functions. E xisting evolutionary algorithms, such as genetic algorithms , may require a large number of omore » bjecti ve function evaluations to identify optimal or near - optimal solutions . Reducing the number of evaluations can result in significant time savings, especially if the objective function is computationally expensive. CGS reduce s the evaluation count by us ing a Bayesian network classifier to filter out non - promising candidate designs , prior to evaluation, based on their posterior probabilit ies . In this project, b oth the single - objective and multi - objective version s of the CGS are developed and tested on a set of benchm ark problems. As a domain - specific case study, CGS is used to design a microgrid for use in islanded mode during an extended bulk power grid outage.« less

Incorporating Auditory Models in Speech/Audio Applications

NASA Astrophysics Data System (ADS)

Krishnamoorthi, Harish

2011-12-01

Following the success in incorporating perceptual models in audio coding algorithms, their application in other speech/audio processing systems is expanding. In general, all perceptual speech/audio processing algorithms involve minimization of an objective function that directly/indirectly incorporates properties of human perception. This dissertation primarily investigates the problems associated with directly embedding an auditory model in the objective function formulation and proposes possible solutions to overcome high complexity issues for use in real-time speech/audio algorithms. Specific problems addressed in this dissertation include: 1) the development of approximate but computationally efficient auditory model implementations that are consistent with the principles of psychoacoustics, 2) the development of a mapping scheme that allows synthesizing a time/frequency domain representation from its equivalent auditory model output. The first problem is aimed at addressing the high computational complexity involved in solving perceptual objective functions that require repeated application of auditory model for evaluation of different candidate solutions. In this dissertation, a frequency pruning and a detector pruning algorithm is developed that efficiently implements the various auditory model stages. The performance of the pruned model is compared to that of the original auditory model for different types of test signals in the SQAM database. Experimental results indicate only a 4-7% relative error in loudness while attaining up to 80-90 % reduction in computational complexity. Similarly, a hybrid algorithm is developed specifically for use with sinusoidal signals and employs the proposed auditory pattern combining technique together with a look-up table to store representative auditory patterns. The second problem obtains an estimate of the auditory representation that minimizes a perceptual objective function and transforms the auditory pattern back to its equivalent time/frequency representation. This avoids the repeated application of auditory model stages to test different candidate time/frequency vectors in minimizing perceptual objective functions. In this dissertation, a constrained mapping scheme is developed by linearizing certain auditory model stages that ensures obtaining a time/frequency mapping corresponding to the estimated auditory representation. This paradigm was successfully incorporated in a perceptual speech enhancement algorithm and a sinusoidal component selection task.

LDRD Final Report: Global Optimization for Engineering Science Problems

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

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.

Energy Center Structure Optimization by using Smart Technologies in Process Control System

NASA Astrophysics Data System (ADS)

Shilkina, Svetlana V.

2018-03-01

The article deals with practical application of fuzzy logic methods in process control systems. A control object - agroindustrial greenhouse complex, which includes its own energy center - is considered. The paper analyzes object power supply options taking into account connection to external power grids and/or installation of own power generating equipment with various layouts. The main problem of a greenhouse facility basic process is extremely uneven power consumption, which forces to purchase redundant generating equipment idling most of the time, which quite negatively affects project profitability. Energy center structure optimization is largely based on solving the object process control system construction issue. To cut investor’s costs it was proposed to optimize power consumption by building an energy-saving production control system based on a fuzzy logic controller. The developed algorithm of automated process control system functioning ensured more even electric and thermal energy consumption, allowed to propose construction of the object energy center with a smaller number of units due to their more even utilization. As a result, it is shown how practical use of microclimate parameters fuzzy control system during object functioning leads to optimization of agroindustrial complex energy facility structure, which contributes to a significant reduction in object construction and operation costs.

Recent experience in simultaneous control-structure optimization

NASA Technical Reports Server (NTRS)

Salama, M.; Ramaker, R.; Milman, M.

1989-01-01

To show the feasibility of simultaneous optimization as design procedure, low order problems were used in conjunction with simple control formulations. The numerical results indicate that simultaneous optimization is not only feasible, but also advantageous. Such advantages come at the expense of introducing complexities beyond those encountered in structure optimization alone, or control optimization alone. Examples include: larger design parameter space, optimization may combine continuous and combinatoric variables, and the combined objective function may be nonconvex. Future extensions to include large order problems, more complex objective functions and constraints, and more sophisticated control formulations will require further research to ensure that the additional complexities do not outweigh the advantages of simultaneous optimization. Some areas requiring more efficient tools than currently available include: multiobjective criteria and nonconvex optimization. Efficient techniques to deal with optimization over combinatoric and continuous variables, and with truncation issues for structure and control parameters of both the model space as well as the design space need to be developed.

Convergence analysis of sliding mode trajectories in multi-objective neural networks learning.

PubMed

Costa, Marcelo Azevedo; Braga, Antonio Padua; de Menezes, Benjamin Rodrigues

2012-09-01

The Pareto-optimality concept is used in this paper in order to represent a constrained set of solutions that are able to trade-off the two main objective functions involved in neural networks supervised learning: data-set error and network complexity. The neural network is described as a dynamic system having error and complexity as its state variables and learning is presented as a process of controlling a learning trajectory in the resulting state space. In order to control the trajectories, sliding mode dynamics is imposed to the network. It is shown that arbitrary learning trajectories can be achieved by maintaining the sliding mode gains within their convergence intervals. Formal proofs of convergence conditions are therefore presented. The concept of trajectory learning presented in this paper goes further beyond the selection of a final state in the Pareto set, since it can be reached through different trajectories and states in the trajectory can be assessed individually against an additional objective function. Copyright © 2012 Elsevier Ltd. All rights reserved.

Maintenance and Exchange of Learning Objects in a Web Services Based e-Learning System

ERIC Educational Resources Information Center

Vossen, Gottfried; Westerkamp, Peter

2004-01-01

"Web services" enable partners to exploit applications via the Internet. Individual services can be composed to build new and more complex ones with additional and more comprehensive functionality. In this paper, we apply the Web service paradigm to electronic learning, and show how to exchange and maintain learning objects is a…

Maximizing photovoltaic power generation of a space-dart configured satellite

NASA Astrophysics Data System (ADS)

Lee, Dae Young; Cutler, James W.; Mancewicz, Joe; Ridley, Aaron J.

2015-06-01

Many small satellites are power constrained due to their minimal solar panel area and the eclipse environment of low-Earth orbit. As with larger satellites, these small satellites, including CubeSats, use deployable power arrays to increase power production. This presents a design opportunity to develop various objective functions related to energy management and methods for optimizing these functions over a satellite design. A novel power generation model was created, and a simulation system was developed to evaluate various objective functions describing energy management for complex satellite designs. The model uses a spacecraft-body-fixed spherical coordinate system to analyze the complex geometry of a satellite's self-induced shadowing with computation provided by the Open Graphics Library. As an example design problem, a CubeSat configured as a space-dart with four deployable panels is optimized. Due to the fast computation speed of the solution, an exhaustive search over the design space is used to find the solar panel deployment angles which maximize total power generation. Simulation results are presented for a variety of orbit scenarios. The method is extendable to a variety of complex satellite geometries and power generation systems.

ERPs Differentially Reflect Automatic and Deliberate Processing of the Functional Manipulability of Objects

PubMed Central

Madan, Christopher R.; Chen, Yvonne Y.; Singhal, Anthony

2016-01-01

It is known that the functional properties of an object can interact with perceptual, cognitive, and motor processes. Previously we have found that a between-subjects manipulation of judgment instructions resulted in different manipulability-related memory biases in an incidental memory test. To better understand this effect we recorded electroencephalography (EEG) while participants made judgments about images of objects that were either high or low in functional manipulability (e.g., hammer vs. ladder). Using a between-subjects design, participants judged whether they had seen the object recently (Personal Experience), or could manipulate the object using their hand (Functionality). We focused on the P300 and slow-wave event-related potentials (ERPs) as reflections of attentional allocation. In both groups, we observed higher P300 and slow wave amplitudes for high-manipulability objects at electrodes Pz and C3. As P300 is thought to reflect bottom-up attentional processes, this may suggest that the processing of high-manipulability objects recruited more attentional resources. Additionally, the P300 effect was greater in the Functionality group. A more complex pattern was observed at electrode C3 during slow wave: processing the high-manipulability objects in the Functionality instruction evoked a more positive slow wave than in the other three conditions, likely related to motor simulation processes. These data provide neural evidence that effects of manipulability on stimulus processing are further mediated by automatic vs. deliberate motor-related processing. PMID:27536224

Four Common Simplifications of Multi-Criteria Decision Analysis do not hold for River Rehabilitation

PubMed Central

2016-01-01

River rehabilitation aims at alleviating negative effects of human impacts such as loss of biodiversity and reduction of ecosystem services. Such interventions entail difficult trade-offs between different ecological and often socio-economic objectives. Multi-Criteria Decision Analysis (MCDA) is a very suitable approach that helps assessing the current ecological state and prioritizing river rehabilitation measures in a standardized way, based on stakeholder or expert preferences. Applications of MCDA in river rehabilitation projects are often simplified, i.e. using a limited number of objectives and indicators, assuming linear value functions, aggregating individual indicator assessments additively, and/or assuming risk neutrality of experts. Here, we demonstrate an implementation of MCDA expert preference assessments to river rehabilitation and provide ample material for other applications. To test whether the above simplifications reflect common expert opinion, we carried out very detailed interviews with five river ecologists and a hydraulic engineer. We defined essential objectives and measurable quality indicators (attributes), elicited the experts´ preferences for objectives on a standardized scale (value functions) and their risk attitude, and identified suitable aggregation methods. The experts recommended an extensive objectives hierarchy including between 54 and 93 essential objectives and between 37 to 61 essential attributes. For 81% of these, they defined non-linear value functions and in 76% recommended multiplicative aggregation. The experts were risk averse or risk prone (but never risk neutral), depending on the current ecological state of the river, and the experts´ personal importance of objectives. We conclude that the four commonly applied simplifications clearly do not reflect the opinion of river rehabilitation experts. The optimal level of model complexity, however, remains highly case-study specific depending on data and resource availability, the context, and the complexity of the decision problem. PMID:26954353

[Tone psychology and music research as catalysts of experimental-scientific practice and methodology in the circle of Carl Stumpf].

PubMed

Klotz, Sebastian

2008-09-01

The study of acoustics, harmonics and of music has been providing scientific models since Greek Antiquity. Since the early modern ages, two separate cultures began to emerge out of the study of music: a technical acoustics and an aesthetically and philosophically inspired musical criticism. In the writings of Johann Friedrich Herbart (1811) a scientific approach to musical aesthetics and to music perception is taking shape that reinstalls the listening process as a highly complex and logical phenomenon. By opening music for a scientific psychological investigation, Herbart pioneered the physiologically and acoustically grounded seminal work by Hermann von Helmholtz On the sensations of tone (1863) which the author considered a prerequisite for musical aesthetics and music theory. Helmholtz in turn inspired the philosopher and psychologist Carl Stumpf to further investigate musical perception (beginning in 1883). To Stumpf, it provided a paradigm for experimental psychology as mental functions and phenomena could be studied in detail. These functions and phenomena are the actual objects of scientific study in Stumpf's inductive and descriptive psychology. Combining insights from statistics, ethnology, anthropology, psychoacoustics and the cultural history of mankind, Stumpf and his team developed a new blend of science which absorbs styles of reasoning, analytical procedures and academic convictions from natural history, the natural sciences and the humanities but at the same time identifies shortcomings of these approaches that fail to grasp the complexities of psychic functions. Despite their reliance on the quasi-objective phonograph and despite their commitment to objectivity, precision and measurement, mental phenomena relating to tonal perception and to music provided too complex a challenge to be easily articulated and shared by the scientific community after 1900. The essay illustrates these tensions against the background of a history of objectivity.

Impaired anticipatory control of grasp during obstacle crossing in Parkinson's disease.

PubMed

McIsaac, Tara L; Diermayr, Gudrun; Albert, Frederic

2012-05-16

During self-paced walking, people with Parkinson's disease maintain anticipatory control during object grasping. However, common functional tasks often include carrying an object while changing step patterns mid-path and maneuvering over obstacles, increasing task complexity and attentional demands. Thus, the present study investigated the effect of Parkinson's disease on the modulation of grasping force changes as a function of gait-related inertial forces. Subjects with Parkinson's disease maintained the ability to scale and to couple over time their grip and inertial forces while walking at irregular step lengths, but were unable to maintain the temporal coupling of grasping forces compared to controls during obstacle crossing. We suggest that this deterioration in anticipatory control is associated with the increased demands of task complexity and attention during obstacle crossing. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Solving a class of generalized fractional programming problems using the feasibility of linear programs.

PubMed

Shen, Peiping; Zhang, Tongli; Wang, Chunfeng

2017-01-01

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

Frontal–Occipital Connectivity During Visual Search

PubMed Central

Pantazatos, Spiro P.; Yanagihara, Ted K.; Zhang, Xian; Meitzler, Thomas

2012-01-01

Abstract Although expectation- and attention-related interactions between ventral and medial prefrontal cortex and stimulus category-selective visual regions have been identified during visual detection and discrimination, it is not known if similar neural mechanisms apply to other tasks such as visual search. The current work tested the hypothesis that high-level frontal regions, previously implicated in expectation and visual imagery of object categories, interact with visual regions associated with object recognition during visual search. Using functional magnetic resonance imaging, subjects searched for a specific object that varied in size and location within a complex natural scene. A model-free, spatial-independent component analysis isolated multiple task-related components, one of which included visual cortex, as well as a cluster within ventromedial prefrontal cortex (vmPFC), consistent with the engagement of both top-down and bottom-up processes. Analyses of psychophysiological interactions showed increased functional connectivity between vmPFC and object-sensitive lateral occipital cortex (LOC), and results from dynamic causal modeling and Bayesian Model Selection suggested bidirectional connections between vmPFC and LOC that were positively modulated by the task. Using image-guided diffusion-tensor imaging, functionally seeded, probabilistic white-matter tracts between vmPFC and LOC, which presumably underlie this effective interconnectivity, were also observed. These connectivity findings extend previous models of visual search processes to include specific frontal–occipital neuronal interactions during a natural and complex search task. PMID:22708993

Parana Basin Structure from Multi-Objective Inversion of Surface Wave and Receiver Function by Competent Genetic Algorithm

NASA Astrophysics Data System (ADS)

An, M.; Assumpcao, M.

2003-12-01

The joint inversion of receiver function and surface wave is an effective way to diminish the influences of the strong tradeoff among parameters and the different sensitivity to the model parameters in their respective inversions, but the inversion problem becomes more complex. Multi-objective problems can be much more complicated than single-objective inversion in the model selection and optimization. If objectives are involved and conflicting, models can be ordered only partially. In this case, Pareto-optimal preference should be used to select solutions. On the other hand, the inversion to get only a few optimal solutions can not deal properly with the strong tradeoff between parameters, the uncertainties in the observation, the geophysical complexities and even the incompetency of the inversion technique. The effective way is to retrieve the geophysical information statistically from many acceptable solutions, which requires more competent global algorithms. Competent genetic algorithms recently proposed are far superior to the conventional genetic algorithm and can solve hard problems quickly, reliably and accurately. In this work we used one of competent genetic algorithms, Bayesian Optimization Algorithm as the main inverse procedure. This algorithm uses Bayesian networks to draw out inherited information and can use Pareto-optimal preference in the inversion. With this algorithm, the lithospheric structure of Paran"› basin is inverted to fit both the observations of inter-station surface wave dispersion and receiver function.

3D Printing of Shape Memory Polymers for Flexible Electronic Devices.

PubMed

Zarek, Matt; Layani, Michael; Cooperstein, Ido; Sachyani, Ela; Cohn, Daniel; Magdassi, Shlomo

2016-06-01

The formation of 3D objects composed of shape memory polymers for flexible electronics is described. Layer-by-layer photopolymerization of methacrylated semicrystalline molten macromonomers by a 3D digital light processing printer enables rapid fabrication of complex objects and imparts shape memory functionality for electrical circuits. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Object-processing neural efficiency differentiates object from spatial visualizers.

PubMed

Motes, Michael A; Malach, Rafael; Kozhevnikov, Maria

2008-11-19

The visual system processes object properties and spatial properties in distinct subsystems, and we hypothesized that this distinction might extend to individual differences in visual processing. We conducted a functional MRI study investigating the neural underpinnings of individual differences in object versus spatial visual processing. Nine participants of high object-processing ability ('object' visualizers) and eight participants of high spatial-processing ability ('spatial' visualizers) were scanned, while they performed an object-processing task. Object visualizers showed lower bilateral neural activity in lateral occipital complex and lower right-lateralized neural activity in dorsolateral prefrontal cortex. The data indicate that high object-processing ability is associated with more efficient use of visual-object resources, resulting in less neural activity in the object-processing pathway.

Camouflage and visual perception

PubMed Central

Troscianko, Tom; Benton, Christopher P.; Lovell, P. George; Tolhurst, David J.; Pizlo, Zygmunt

2008-01-01

How does an animal conceal itself from visual detection by other animals? This review paper seeks to identify general principles that may apply in this broad area. It considers mechanisms of visual encoding, of grouping and object encoding, and of search. In most cases, the evidence base comes from studies of humans or species whose vision approximates to that of humans. The effort is hampered by a relatively sparse literature on visual function in natural environments and with complex foraging tasks. However, some general constraints emerge as being potentially powerful principles in understanding concealment—a ‘constraint’ here means a set of simplifying assumptions. Strategies that disrupt the unambiguous encoding of discontinuities of intensity (edges), and of other key visual attributes, such as motion, are key here. Similar strategies may also defeat grouping and object-encoding mechanisms. Finally, the paper considers how we may understand the processes of search for complex targets in complex scenes. The aim is to provide a number of pointers towards issues, which may be of assistance in understanding camouflage and concealment, particularly with reference to how visual systems can detect the shape of complex, concealed objects. PMID:18990671

High resolution near on-axis digital holography using constrained optimization approach with faster convergence

NASA Astrophysics Data System (ADS)

Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu

2017-09-01

A constrained optimization approach with faster convergence is proposed to recover the complex object field from a near on-axis digital holography (DH). We subtract the DC from the hologram after recording the object beam and reference beam intensities separately. The DC-subtracted hologram is used to recover the complex object information using a constrained optimization approach with faster convergence. The recovered complex object field is back propagated to the image plane using the Fresnel back-propagation method. The results reported in this approach provide high-resolution images compared with the conventional Fourier filtering approach and is 25% faster than the previously reported constrained optimization approach due to the subtraction of two DC terms in the cost function. We report this approach in DH and digital holographic microscopy using the U.S. Air Force resolution target as the object to retrieve the high-resolution image without DC and twin image interference. We also demonstrate the high potential of this technique in transparent microelectrode patterned on indium tin oxide-coated glass, by reconstructing a high-resolution quantitative phase microscope image. We also demonstrate this technique by imaging yeast cells.

Advanced functional network analysis in the geosciences: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

2013-04-01

Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

DEVELOPMENTS IN GRworkbench

NASA Astrophysics Data System (ADS)

Moylan, Andrew; Scott, Susan M.; Searle, Anthony C.

2006-02-01

The software tool GRworkbench is an ongoing project in visual, numerical General Relativity at The Australian National University. Recently, GRworkbench has been significantly extended to facilitate numerical experimentation in analytically-defined space-times. The numerical differential geometric engine has been rewritten using functional programming techniques, enabling objects which are normally defined as functions in the formalism of differential geometry and General Relativity to be directly represented as function variables in the C++ code of GRworkbench. The new functional differential geometric engine allows for more accurate and efficient visualisation of objects in space-times and makes new, efficient computational techniques available. Motivated by the desire to investigate a recent scientific claim using GRworkbench, new tools for numerical experimentation have been implemented, allowing for the simulation of complex physical situations.

On the recognition of complex structures: Computer software using artificial intelligence applied to pattern recognition

NASA Technical Reports Server (NTRS)

Yakimovsky, Y.

1974-01-01

An approach to simultaneous interpretation of objects in complex structures so as to maximize a combined utility function is presented. Results of the application of a computer software system to assign meaning to regions in a segmented image based on the principles described in this paper and on a special interactive sequential classification learning system, which is referenced, are demonstrated.

A Distributed Trajectory-Oriented Approach to Managing Traffic Complexity

NASA Technical Reports Server (NTRS)

Idris, Husni; Wing, David J.; Vivona, Robert; Garcia-Chico, Jose-Luis

2007-01-01

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which ground-based service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. While its architecture becomes more distributed, the goal of the Air Traffic Management (ATM) system remains to achieve objectives such as maintaining safety and efficiency. It is, therefore, critical to design appropriate control elements to ensure that aircraft and groundbased actions result in achieving these objectives without unduly restricting user-preferred trajectories. This paper presents a trajectory-oriented approach containing two such elements. One is a trajectory flexibility preservation function, by which aircraft plan their trajectories to preserve flexibility to accommodate unforeseen events. And the other is a trajectory constraint minimization function by which ground-based agents, in collaboration with air-based agents, impose just-enough restrictions on trajectories to achieve ATM objectives, such as separation assurance and flow management. The underlying hypothesis is that preserving trajectory flexibility of each individual aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by minimizing constraints without jeopardizing the intended ATM objectives. The paper presents conceptually how the two functions operate in a distributed control architecture that includes self separation. The paper illustrates the concept through hypothetical scenarios involving conflict resolution and flow management. It presents a functional analysis of the interaction and information flow between the functions. It also presents an analytical framework for defining metrics and developing methods to preserve trajectory flexibility and minimize its constraints. In this framework flexibility is defined in terms of robustness and adaptability to disturbances and the impact of constraints is illustrated through analysis of a trajectory solution space with limited degrees of freedom and in simple constraint situations involving meeting multiple times of arrival and resolving a conflict.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

Method for Evaluating Information to Solve Problems of Control, Monitoring and Diagnostics

NASA Astrophysics Data System (ADS)

Vasil'ev, V. A.; Dobrynina, N. V.

2017-06-01

The article describes a method for evaluating information to solve problems of control, monitoring and diagnostics. It is necessary for reducing the dimensionality of informational indicators of situations, bringing them to relative units, for calculating generalized information indicators on their basis, ranking them by characteristic levels, for calculating the efficiency criterion of a system functioning in real time. The design of information evaluation system has been developed on its basis that allows analyzing, processing and assessing information about the object. Such object can be a complex technical, economic and social system. The method and the based system thereof can find a wide application in the field of analysis, processing and evaluation of information on the functioning of the systems, regardless of their purpose, goals, tasks and complexity. For example, they can be used to assess the innovation capacities of industrial enterprises and management decisions.

A Java application for tissue section image analysis.

PubMed

Kamalov, R; Guillaud, M; Haskins, D; Harrison, A; Kemp, R; Chiu, D; Follen, M; MacAulay, C

2005-02-01

The medical industry has taken advantage of Java and Java technologies over the past few years, in large part due to the language's platform-independence and object-oriented structure. As such, Java provides powerful and effective tools for developing tissue section analysis software. The background and execution of this development are discussed in this publication. Object-oriented structure allows for the creation of "Slide", "Unit", and "Cell" objects to simulate the corresponding real-world objects. Different functions may then be created to perform various tasks on these objects, thus facilitating the development of the software package as a whole. At the current time, substantial parts of the initially planned functionality have been implemented. Getafics 1.0 is fully operational and currently supports a variety of research projects; however, there are certain features of the software that currently introduce unnecessary complexity and inefficiency. In the future, we hope to include features that obviate these problems.

Some single-machine scheduling problems with learning effects and two competing agents.

PubMed

Li, Hongjie; Li, Zeyuan; Yin, Yunqiang

2014-01-01

This study considers a scheduling environment in which there are two agents and a set of jobs, each of which belongs to one of the two agents and its actual processing time is defined as a decreasing linear function of its starting time. Each of the two agents competes to process its respective jobs on a single machine and has its own scheduling objective to optimize. The objective is to assign the jobs so that the resulting schedule performs well with respect to the objectives of both agents. The objective functions addressed in this study include the maximum cost, the total weighted completion time, and the discounted total weighted completion time. We investigate three problems arising from different combinations of the objectives of the two agents. The computational complexity of the problems is discussed and solution algorithms where possible are presented.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen

2015-11-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.

Age-related variation in EEG complexity to photic stimulation: A multiscale entropy analysis

PubMed Central

Takahashi, Tetsuya; Cho, Raymond Y.; Murata, Tetsuhito; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Mizukami, Kimiko; Kosaka, Hirotaka; Takahashi, Koichi; Wada, Yuji

2010-01-01

Objective This study was intended to examine variations in electroencephalographic (EEG) complexity in response to photic stimulation (PS) during aging to test the hypothesis that the aging process reduces physiologic complexity and functional responsiveness. Methods Multiscale entropy (MSE), an estimate of time-series signal complexity associated with long-range temporal correlation, is used as a recently proposed method for quantifying EEG complexity with multiple coarse-grained sequences. We recorded EEG in 13 healthy elderly subjects and 12 healthy young subjects during pre-PS and post-PS conditions and estimated their respective MSE values. Results For the pre-PS condition, no significant complexity difference was found between the groups. However, a significant MSE change (complexity increase) was found post-PS only in young subjects, thereby revealing a power-law scaling property, which means long-range temporal correlation. Conclusions Enhancement of long-range temporal correlation in young subjects after PS might reflect a cortical response to stimuli, which was absent in elderly subjects. These results are consistent with the general “loss of complexity/diminished functional response to stimuli” theory of aging. Significance Our findings demonstrate that application of MSE analysis to EEG is a powerful approach for studying age-related changes in brain function. PMID:19231279

PSB27: A thylakoid protein enabling Arabidopsis to adapt to changing light intensity

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

Hou, Xin; Garcia, Veder J.; Buchanan, Bob B.

Project Title: Immunophilins in the assembly and maintenance of photosynthetic electron transport chain in Arabidopsis Applicant: The Regents of the University of California PI: Sheng Luan, University of California at Berkeley Photosynthetic light energy conversion entails coordinated function of complex molecular machines that capture and convert light energy into chemical forms through photosynthetic electron transport chain. Each molecular machine, such as photosystem II (PSII), may consist of dozens of protein subunits and small molecule cofactors. Despite advanced understanding of the structure and function of these complexes, little is known about “How individual proteins and cofactors assemble into a functional machinemore » and how do these molecular machines maintain their structure and function under a highly hazardous lumenal environment.” Our studies on immunophilins have unexpectedly contributed to the understanding of this question. Originally defined as cellular receptors for immunosuppressants, immunophilins have been discovered in a wide range of organisms from bacteria, fungi, plants, to animals. Immunophilins function in protein folding processes as chaperones and foldases. Arabidopsis genome encodes ca. 50 immunophilins. The most striking finding is that 16 immunophilin members are targeted to chloroplast thylakoid lumen, by far the largest group in the lumenal proteome. What is the function of immunophilins in the thylakoid lumen? Our studies have demonstrated critical roles for several immunophilins in the biogenesis and maintenance of photosynthetic complexes such as PSII. These studies have made a critical link between immunophilins and the assembly of photosynthetic machines and thus opened up a new area of research in photosynthesis. Our goal is to dissect the roles of immunophilins and their partners in the assembly and maintenance of the photosynthetic electron transport chain. The specific objectives for this funding period will be: 1. To dissect the mechanism of action for CYP38. Our studies suggest an “autoinhibitory” model for CYP38 action. We plan to test this model and determine the mechanistic details for CYP38 function by biochemical and genetic procedures. 2. To determine the mechanism of action of FKBP20-2/FKBP16-3. Studies on FBKP16-3 and FKBP20-2 suggest that they may work together as a redox-dependent duo in PSII assembly. We will test this hypothesis using biochemical and genetic tools. 3. To determine the function of lumenal FKBPs by multi-gene mutagenesis approach. Using new genetic knockout (KO) procedures especially CRISPR/CAS9 system, we plan to generate multi-gene KO models that will likely provide vital information on those FKBPs with functional redundancy. 4. Functional analysis of thylakoid lumen network. We will focus our effort on objectives 1-3. Objective 4 represents a long-term goal to establish a more comprehensive network of proteins in the thylakoid lumen and their function in the assembly and maintenance of photosynthetic complexes. I hypothesize that the 16 immunophilin-type chaperones and foldases in the thylakoid lumen constitute an “assembly line” for the various components in the photosynthetic electron transport chain. Understanding this assembly line will enable further engineering of more efficient photosynthetic machines to capture more light energy and enhance plant productivity. Furthermore, it is envisioned that such molecular “assembly line” may be rebuilt to produce artificial photosynthesis in vitro or in non-photosynthetic organisms. These are highly relevant to the mission of “Photosynthetic Systems” and “Physical Biosciences” programs to “enhance our understanding of energy capture, conversion, and/or storage.” During the funding period, we have performed a number of experiments under the proposed objectives and obtained several new results. We have found in Objective 1 that CYP38 is associated to the thylokoid membrane with a larger complex that might be PSII supercomplex. Under objective 2, we have found that FKBP16-2 interacted with PSB27 that was further pursuited and published a research article in PNAS (attached). Under Objective 3, we have identified several mutants of other FKBPs in the thyalkoid lumen that should be further studied if future funding is available. Under Objective 4, we have started to build a network of lumenal proteins that play a number of roles in photosynthesis. For example, the CYP37 and CYP28 are linked to chloroplast signaling to nucleus, critical for controlling plant response to high light and adaptation to climate change. Unfortunately these studies have been terminated due to funding shortage.« less

The evolution of meaning: spatio-temporal dynamics of visual object recognition.

PubMed

Clarke, Alex; Taylor, Kirsten I; Tyler, Lorraine K

2011-08-01

Research on the spatio-temporal dynamics of visual object recognition suggests a recurrent, interactive model whereby an initial feedforward sweep through the ventral stream to prefrontal cortex is followed by recurrent interactions. However, critical questions remain regarding the factors that mediate the degree of recurrent interactions necessary for meaningful object recognition. The novel prediction we test here is that recurrent interactivity is driven by increasing semantic integration demands as defined by the complexity of semantic information required by the task and driven by the stimuli. To test this prediction, we recorded magnetoencephalography data while participants named living and nonliving objects during two naming tasks. We found that the spatio-temporal dynamics of neural activity were modulated by the level of semantic integration required. Specifically, source reconstructed time courses and phase synchronization measures showed increased recurrent interactions as a function of semantic integration demands. These findings demonstrate that the cortical dynamics of object processing are modulated by the complexity of semantic information required from the visual input.

Research on image complexity evaluation method based on color information

NASA Astrophysics Data System (ADS)

Wang, Hao; Duan, Jin; Han, Xue-hui; Xiao, Bo

2017-11-01

In order to evaluate the complexity of a color image more effectively and find the connection between image complexity and image information, this paper presents a method to compute the complexity of image based on color information.Under the complexity ,the theoretical analysis first divides the complexity from the subjective level, divides into three levels: low complexity, medium complexity and high complexity, and then carries on the image feature extraction, finally establishes the function between the complexity value and the color characteristic model. The experimental results show that this kind of evaluation method can objectively reconstruct the complexity of the image from the image feature research. The experimental results obtained by the method of this paper are in good agreement with the results of human visual perception complexity,Color image complexity has a certain reference value.

Objective Molecular Dynamics with Self-consistent Charge Density Functional Tight-Binding (SCC-DFTB) Method

NASA Astrophysics Data System (ADS)

Dumitrica, Traian; Hourahine, Ben; Aradi, Balint; Frauenheim, Thomas

We discus the coupling of the objective boundary conditions into the SCC density functional-based tight binding code DFTB+. The implementation is enabled by a generalization to the helical case of the classical Ewald method, specifically by Ewald-like formulas that do not rely on a unit cell with translational symmetry. The robustness of the method in addressing complex hetero-nuclear nano- and bio-fibrous systems is demonstrated with illustrative simulations on a helical boron nitride nanotube, a screw dislocated zinc oxide nanowire, and an ideal double-strand DNA. Work supported by NSF CMMI 1332228.

Virtual C Machine and Integrated Development Environment for ATMS Controllers.

DOT National Transportation Integrated Search

2000-04-01

The overall objective of this project is to develop a prototype virtual machine that fits on current Advanced Traffic Management Systems (ATMS) controllers and provides functionality for complex traffic operations.;Prepared in cooperation with Utah S...

Novel maximum-margin training algorithms for supervised neural networks.

PubMed

Ludwig, Oswaldo; Nunes, Urbano

2010-06-01

This paper proposes three novel training methods, two of them based on the backpropagation approach and a third one based on information theory for multilayer perceptron (MLP) binary classifiers. Both backpropagation methods are based on the maximal-margin (MM) principle. The first one, based on the gradient descent with adaptive learning rate algorithm (GDX) and named maximum-margin GDX (MMGDX), directly increases the margin of the MLP output-layer hyperplane. The proposed method jointly optimizes both MLP layers in a single process, backpropagating the gradient of an MM-based objective function, through the output and hidden layers, in order to create a hidden-layer space that enables a higher margin for the output-layer hyperplane, avoiding the testing of many arbitrary kernels, as occurs in case of support vector machine (SVM) training. The proposed MM-based objective function aims to stretch out the margin to its limit. An objective function based on Lp-norm is also proposed in order to take into account the idea of support vectors, however, overcoming the complexity involved in solving a constrained optimization problem, usually in SVM training. In fact, all the training methods proposed in this paper have time and space complexities O(N) while usual SVM training methods have time complexity O(N (3)) and space complexity O(N (2)) , where N is the training-data-set size. The second approach, named minimization of interclass interference (MICI), has an objective function inspired on the Fisher discriminant analysis. Such algorithm aims to create an MLP hidden output where the patterns have a desirable statistical distribution. In both training methods, the maximum area under ROC curve (AUC) is applied as stop criterion. The third approach offers a robust training framework able to take the best of each proposed training method. The main idea is to compose a neural model by using neurons extracted from three other neural networks, each one previously trained by MICI, MMGDX, and Levenberg-Marquard (LM), respectively. The resulting neural network was named assembled neural network (ASNN). Benchmark data sets of real-world problems have been used in experiments that enable a comparison with other state-of-the-art classifiers. The results provide evidence of the effectiveness of our methods regarding accuracy, AUC, and balanced error rate.

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

Generalized three-dimensional experimental lightning code (G3DXL) user's manual

NASA Technical Reports Server (NTRS)

Kunz, Karl S.

1986-01-01

Information concerning the programming, maintenance and operation of the G3DXL computer program is presented and the theoretical basis for the code is described. The program computes time domain scattering fields and surface currents and charges induced by a driving function on and within a complex scattering object which may be perfectly conducting or a lossy dielectric. This is accomplished by modeling the object with cells within a three-dimensional, rectangular problem space, enforcing the appropriate boundary conditions and differencing Maxwell's equations in time. In the present version of the program, the driving function can be either the field radiated by a lightning strike or a direct lightning strike. The F-106 B aircraft is used as an example scattering object.

On global optimization using an estimate of Lipschitz constant and simplicial partition

NASA Astrophysics Data System (ADS)

Gimbutas, Albertas; Žilinskas, Antanas

2016-10-01

A new algorithm is proposed for finding the global minimum of a multi-variate black-box Lipschitz function with an unknown Lipschitz constant. The feasible region is initially partitioned into simplices; in the subsequent iteration, the most suitable simplices are selected and bisected via the middle point of the longest edge. The suitability of a simplex for bisection is evaluated by minimizing of a surrogate function which mimics the lower bound for the considered objective function over that simplex. The surrogate function is defined using an estimate of the Lipschitz constant and the objective function values at the vertices of a simplex. The novelty of the algorithm is the sophisticated method of estimating the Lipschitz constant, and the appropriate method to minimize the surrogate function. The proposed algorithm was tested using 600 random test problems of different complexity, showing competitive results with two popular advanced algorithms which are based on similar assumptions.

A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.

PubMed

Brown, Angus M

2006-04-01

The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.

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.

Performance index and meta-optimization of a direct search optimization method

NASA Astrophysics Data System (ADS)

Krus, P.; Ölvander, J.

2013-10-01

Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannon's information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.

Experimentally-Based Ocean Acoustic Propagation and Coherence Studies

DTIC Science & Technology

2013-09-30

degradation and/or exploitation of available sonic information. OBJECTIVES An objective is to quantify and explain underwater sound fluctuation...focusing did not entirely match the data because of terrain uncertainty. The paper further notes that a rapid drop-off of received sound level from the...covariance functions of complex demodulated signals. The array gain is defined as the signal to noise ratio for coherently added (beam steered) acoustic

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

MOCASSIN-prot: A multi-objective clustering approach for protein similarity networks

USDA-ARS?s Scientific Manuscript database

Motivation: Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary h...

A collision detection algorithm for telerobotic arms

NASA Technical Reports Server (NTRS)

Tran, Doan Minh; Bartholomew, Maureen Obrien

1991-01-01

The telerobotic manipulator's collision detection algorithm is described. Its applied structural model of the world environment and template representation of objects is evaluated. Functional issues that are required for the manipulator to operate in a more complex and realistic environment are discussed.

Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study

PubMed Central

2012-01-01

Background The use of biological molecular network information for diagnostic and prognostic purposes and elucidation of molecular disease mechanism is a key objective in systems biomedicine. The network of regulatory miRNA-target and functional protein interactions is a rich source of information to elucidate the function and the prognostic value of miRNAs in cancer. The objective of this study is to identify miRNAs that have high influence on target protein complexes in prostate cancer as a case study. This could provide biomarkers or therapeutic targets relevant for prostate cancer treatment. Results Our findings demonstrate that a miRNA’s functional role can be explained by its target protein connectivity within a physical and functional interaction network. To detect miRNAs with high influence on target protein modules, we integrated miRNA and mRNA expression profiles with a sequence based miRNA-target network and human functional and physical protein interactions (FPI). miRNAs with high influence on target protein complexes play a role in prostate cancer progression and are promising diagnostic or prognostic biomarkers. We uncovered several miRNA-regulated protein modules which were enriched in focal adhesion and prostate cancer genes. Several miRNAs such as miR-96, miR-182, and miR-143 demonstrated high influence on their target protein complexes and could explain most of the gene expression changes in our analyzed prostate cancer data set. Conclusions We describe a novel method to identify active miRNA-target modules relevant to prostate cancer progression and outcome. miRNAs with high influence on protein networks are valuable biomarkers that can be used in clinical investigations for prostate cancer treatment. PMID:22929553

Maximum entropy perception-action space: a Bayesian model of eye movement selection

NASA Astrophysics Data System (ADS)

Colas, Francis; Bessière, Pierre; Girard, Benoît

2011-03-01

In this article, we investigate the issue of the selection of eye movements in a free-eye Multiple Object Tracking task. We propose a Bayesian model of retinotopic maps with a complex logarithmic mapping. This model is structured in two parts: a representation of the visual scene, and a decision model based on the representation. We compare different decision models based on different features of the representation and we show that taking into account uncertainty helps predict the eye movements of subjects recorded in a psychophysics experiment. Finally, based on experimental data, we postulate that the complex logarithmic mapping has a functional relevance, as the density of objects in this space in more uniform than expected. This may indicate that the representation space and control strategies are such that the object density is of maximum entropy.

Fractal morphometry of cell complexity.

PubMed

Losa, Gabriele A

2002-01-01

Irregularity and self-similarity under scale changes are the main attributes of the morphological complexity of both normal and abnormal cells and tissues. In other words, the shape of a self-similar object does not change when the scale of measurement changes, because each part of it looks similar to the original object. However, the size and geometrical parameters of an irregular object do differ when it is examined at increasing resolution, which reveals more details. Significant progress has been made over the past three decades in understanding how irregular shapes and structures in the physical and biological sciences can be analysed. Dominant influences have been the discovery of a new practical geometry of Nature, now known as fractal geometry, and the continuous improvements in computation capabilities. Unlike conventional Euclidean geometry, which was developed to describe regular and ideal geometrical shapes which are practically unknown in nature, fractal geometry can be used to measure the fractal dimension, contour length, surface area and other dimension parameters of almost all irregular and complex biological tissues. We have used selected examples to illustrate the application of the fractal principle to measuring irregular and complex membrane ultrastructures of cells at specific functional and pathological stage.

A complex ligase ribozyme evolved in vitro from a group I ribozyme domain

NASA Technical Reports Server (NTRS)

Jaeger, L.; Wright, M. C.; Joyce, G. F.; Bada, J. L. (Principal Investigator)

1999-01-01

Like most proteins, complex RNA molecules often are modular objects made up of distinct structural and functional domains. The component domains of a protein can associate in alternative combinations to form molecules with different functions. These observations raise the possibility that complex RNAs also can be assembled from preexisting structural and functional domains. To test this hypothesis, an in vitro evolution procedure was used to isolate a previously undescribed class of complex ligase ribozymes, starting from a pool of 10(16) different RNA molecules that contained a constant region derived from a large structural domain that occurs within self-splicing group I ribozymes. Attached to this constant region were three hypervariable regions, totaling 85 nucleotides, that gave rise to the catalytic motif within the evolved catalysts. The ligase ribozymes catalyze formation of a 3',5'-phosphodiester linkage between adjacent template-bound oligonucleotides, one bearing a 3' hydroxyl and the other a 5' triphosphate. Ligation occurs in the context of a Watson-Crick duplex, with a catalytic rate of 0.26 min(-1) under optimal conditions. The constant region is essential for catalytic activity and appears to retain the tertiary structure of the group I ribozyme. This work demonstrates that complex RNA molecules, like their protein counterparts, can share common structural domains while exhibiting distinct catalytic functions.

Conditioning 3D object-based models to dense well data

NASA Astrophysics Data System (ADS)

Wang, Yimin C.; Pyrcz, Michael J.; Catuneanu, Octavian; Boisvert, Jeff B.

2018-06-01

Object-based stochastic simulation models are used to generate categorical variable models with a realistic representation of complicated reservoir heterogeneity. A limitation of object-based modeling is the difficulty of conditioning to dense data. One method to achieve data conditioning is to apply optimization techniques. Optimization algorithms can utilize an objective function measuring the conditioning level of each object while also considering the geological realism of the object. Here, an objective function is optimized with implicit filtering which considers constraints on object parameters. Thousands of objects conditioned to data are generated and stored in a database. A set of objects are selected with linear integer programming to generate the final realization and honor all well data, proportions and other desirable geological features. Although any parameterizable object can be considered, objects from fluvial reservoirs are used to illustrate the ability to simultaneously condition multiple types of geologic features. Channels, levees, crevasse splays and oxbow lakes are parameterized based on location, path, orientation and profile shapes. Functions mimicking natural river sinuosity are used for the centerline model. Channel stacking pattern constraints are also included to enhance the geological realism of object interactions. Spatial layout correlations between different types of objects are modeled. Three case studies demonstrate the flexibility of the proposed optimization-simulation method. These examples include multiple channels with high sinuosity, as well as fragmented channels affected by limited preservation. In all cases the proposed method reproduces input parameters for the object geometries and matches the dense well constraints. The proposed methodology expands the applicability of object-based simulation to complex and heterogeneous geological environments with dense sampling.

Assessment of mitochondrial functions in Daphnia pulex clones using high-resolution respirometry.

PubMed

Kake-Guena, Sandrine A; Touisse, Kamal; Vergilino, Roland; Dufresne, France; Blier, Pierre U; Lemieux, Hélène

2015-06-01

The objectives of our study were to adapt a method to measure mitochondrial function in intact mitochondria from the small crustacean Daphnia pulex and to validate if this method was sensitive enough to characterize mitochondrial metabolism in clones of the pulex complex differing in ploidy levels, mitochondrial DNA haplotypes, and geographic origins. Daphnia clones belonging to the Daphnia pulex complex represent a powerful model to delineate the link between mitochondrial DNA evolution and mitochondrial phenotypes, as single genotypes with divergent mtDNA can be grown under various experimental conditions. Our study included two diploid clones from temperate environments and two triploid clones from subarctic environments. The whole animal permeabilization and measurement of respiration with high-resolution respirometry enabled the measurement of the functional capacity of specific mitochondrial complexes in four clones. When expressing the activity as ratios, our method detected significant interclonal variations. In the triploid subarctic clone from Kuujjurapik, a higher proportion of the maximal physiological oxidative phosphorylation (OXPHOS) capacity of mitochondria was supported by complex II, and a lower proportion by complex I. The triploid subarctic clone from Churchill (Manitoba) showed the lowest proportion of the maximal OXPHOS supported by complex II. Additional studies are required to determine if these differences in mitochondrial functions are related to differences in mitochondrial haplotypes or ploidy level and if they might be associated with fitness divergences and therefore selective value. © 2015 Wiley Periodicals, Inc.

The difficulties of using MACSYMA and the function of user aids

NASA Technical Reports Server (NTRS)

Genesereth, M. R.

1977-01-01

The size and complexity of the MACSYMA system may create learning difficulties for users. Deficiency in understanding the system leads to resource knowledge difficulties. A communication factor arises from a difference between the primitive objects, actions, and relations of a user's problem and those provided by the system. The functions of various user aids in handling each of these difficulties are discussed.

Telerobot operator control station requirements

NASA Technical Reports Server (NTRS)

Kan, Edwin P.

1988-01-01

The operator control station of a telerobot system has unique functional and human factors requirements. It has to satisfy the needs of a truly interactive and user-friendly complex system, a telerobot system being a hybrid between a teleoperated and an autonomous system. These functional, hardware and software requirements are discussed, with explicit reference to the design objectives and constraints of the JPL/NASA Telerobot Demonstrator System.

Workplace Exposures and Cognitive Function During Adulthood: Evidence From National Survey of Midlife Development and the O*NET.

PubMed

Grzywacz, Joseph G; Segel-Karpas, Dikla; Lachman, Margie E

2016-06-01

Expand understanding of the role of selected workplace exposures (ie, occupational complexity, conflict in the workplace, pace of work, and physical hazards) in adults' cognitive function. Cross-sectional data (n = 1991) from the second wave of the Midlife in the United States (MIDUS) study; restricted to participants who completed telephone-based cognitive assessments of episodic memory, executive functioning, and self-perceived memory. Occupational exposure data were harvested from the ONET Release 6.0. Greater complexity was associated with better self-perceived memory among women and men, and better episodic memory and executive functioning among women. Greater physical hazards were independently associated with poorer episodic memory and executive functioning. Objective assessments of physical and psychosocial exposures in the workplace are independently associated with cognitive outcomes in adulthood, with psychosocial exposures being particularly pronounced among women.

Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay

USGS Publications Warehouse

McGowan, Conor P.; Lyons, James E.; Smith, David

2015-01-01

Structured decision making (SDM) is an increasingly utilized approach and set of tools for addressing complex decisions in environmental management. SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. Developing utility functions to effectively reflect the management objectives allowed us to incorporate stakeholder risk aversion even though different stakeholder groups were averse to different or competing risks. While measurable objectives and quantitative utility functions seem scientific, developing these objectives was fundamentally driven by the values of the participating stakeholders.

Developing Objectives with Multiple Stakeholders: Adaptive Management of Horseshoe Crabs and Red Knots in the Delaware Bay

NASA Astrophysics Data System (ADS)

McGowan, Conor P.; Lyons, James E.; Smith, David R.

2015-04-01

Structured decision making (SDM) is an increasingly utilized approach and set of tools for addressing complex decisions in environmental management. SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. Developing utility functions to effectively reflect the management objectives allowed us to incorporate stakeholder risk aversion even though different stakeholder groups were averse to different or competing risks. While measurable objectives and quantitative utility functions seem scientific, developing these objectives was fundamentally driven by the values of the participating stakeholders.

The fundamentals of average local variance--Part I: Detecting regular patterns.

PubMed

Bøcher, Peder Klith; McCloy, Keith R

2006-02-01

The method of average local variance (ALV) computes the mean of the standard deviation values derived for a 3 x 3 moving window on a successively coarsened image to produce a function of ALV versus spatial resolution. In developing ALV, the authors used approximately a doubling of the pixel size at each coarsening of the image. They hypothesized that ALV is low when the pixel size is smaller than the size of scene objects because the pixels on the object will have similar response values. When the pixel and objects are of similar size, they will tend to vary in response and the ALV values will increase. As the size of pixels increase further, more objects will be contained in a single pixel and ALV will decrease. The authors showed that various cover types produced single peak ALV functions that inexplicitly peaked when the pixel size was 1/2 to 3/4 of the object size. This paper reports on work done to explore the characteristics of the various forms of the ALV function and to understand the location of the peaks that occur in this function. The work was conducted using synthetically generated image data. The investigation showed that the hypothesis originally proposed in is not adequate. A new hypothesis is proposed that the ALV function has peak locations that are related to the geometric size of pattern structures in the scene. These structures are not always the same as scene objects. Only in cases where the size of and separation between scene objects are equal does the ALV function detect the size of the objects. In situations where the distance between scene objects are larger than their size, the ALV function has a peak at the object separation, not at the object size. This work has also shown that multiple object structures of different sizes and distances in the image provide multiple peaks in the ALV function and that some of these structures are not implicitly recognized as such from our perspective. However, the magnitude of these peaks depends on the response mix in the structures, complicating their interpretation and analysis. The analysis of the ALV Function is, thus, more complex than that generally reported in the literature.

Multi-Objective Programming for Lot-Sizing with Quantity Discount

NASA Astrophysics Data System (ADS)

Kang, He-Yau; Lee, Amy H. I.; Lai, Chun-Mei; Kang, Mei-Sung

2011-11-01

Multi-objective programming (MOP) is one of the popular methods for decision making in a complex environment. In a MOP, decision makers try to optimize two or more objectives simultaneously under various constraints. A complete optimal solution seldom exists, and a Pareto-optimal solution is usually used. Some methods, such as the weighting method which assigns priorities to the objectives and sets aspiration levels for the objectives, are used to derive a compromise solution. The ɛ-constraint method is a modified weight method. One of the objective functions is optimized while the other objective functions are treated as constraints and are incorporated in the constraint part of the model. This research considers a stochastic lot-sizing problem with multi-suppliers and quantity discounts. The model is transformed into a mixed integer programming (MIP) model next based on the ɛ-constraint method. An illustrative example is used to illustrate the practicality of the proposed model. The results demonstrate that the model is an effective and accurate tool for determining the replenishment of a manufacturer from multiple suppliers for multi-periods.

Stable Local Volatility Calibration Using Kernel Splines

NASA Astrophysics Data System (ADS)

Coleman, Thomas F.; Li, Yuying; Wang, Cheng

2010-09-01

We propose an optimization formulation using L1 norm to ensure accuracy and stability in calibrating a local volatility function for option pricing. Using a regularization parameter, the proposed objective function balances the calibration accuracy with the model complexity. Motivated by the support vector machine learning, the unknown local volatility function is represented by a kernel function generating splines and the model complexity is controlled by minimizing the 1-norm of the kernel coefficient vector. In the context of the support vector regression for function estimation based on a finite set of observations, this corresponds to minimizing the number of support vectors for predictability. We illustrate the ability of the proposed approach to reconstruct the local volatility function in a synthetic market. In addition, based on S&P 500 market index option data, we demonstrate that the calibrated local volatility surface is simple and resembles the observed implied volatility surface in shape. Stability is illustrated by calibrating local volatility functions using market option data from different dates.

Comparison of global optimization approaches for robust calibration of hydrologic model parameters

NASA Astrophysics Data System (ADS)

Jung, I. W.

2015-12-01

Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

The Impact of Different Environmental Conditions on Cognitive Function: A Focused Review

PubMed Central

Taylor, Lee; Watkins, Samuel L.; Marshall, Hannah; Dascombe, Ben J.; Foster, Josh

2016-01-01

Cognitive function defines performance in objective tasks that require conscious mental effort. Extreme environments, namely heat, hypoxia, and cold can all alter human cognitive function due to a variety of psychological and/or biological processes. The aims of this Focused Review were to discuss; (1) the current state of knowledge on the effects of heat, hypoxic and cold stress on cognitive function, (2) the potential mechanisms underpinning these alterations, and (3) plausible interventions that may maintain cognitive function upon exposure to each of these environmental stressors. The available evidence suggests that the effects of heat, hypoxia, and cold stress on cognitive function are both task and severity dependent. Complex tasks are particularly vulnerable to extreme heat stress, whereas both simple and complex task performance appear to be vulnerable at even at moderate altitudes. Cold stress also appears to negatively impact both simple and complex task performance, however, the research in this area is sparse in comparison to heat and hypoxia. In summary, this focused review provides updated knowledge regarding the effects of extreme environmental stressors on cognitive function and their biological underpinnings. Tyrosine supplementation may help individuals maintain cognitive function in very hot, hypoxic, and/or cold conditions. However, more research is needed to clarify these and other postulated interventions. PMID:26779029

It's all connected: Pathways in visual object recognition and early noun learning.

PubMed

Smith, Linda B

2013-11-01

A developmental pathway may be defined as the route, or chain of events, through which a new structure or function forms. For many human behaviors, including object name learning and visual object recognition, these pathways are often complex and multicausal and include unexpected dependencies. This article presents three principles of development that suggest the value of a developmental psychology that explicitly seeks to trace these pathways and uses empirical evidence on developmental dependencies among motor development, action on objects, visual object recognition, and object name learning in 12- to 24-month-old infants to make the case. The article concludes with a consideration of the theoretical implications of this approach. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Battling Arrow's Paradox to Discover Robust Water Management Alternatives

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Reed, P. M.; Hadka, D.

2013-12-01

This study explores whether or not Arrow's Impossibility Theorem, a theory of social choice, affects the formulation of water resources systems planning problems. The theorem discusses creating an aggregation function for voters choosing from more than three alternatives for society. The Impossibility Theorem is also called Arrow's Paradox, because when trying to add more voters, a single individual's preference will dictate the optimal group decision. In the context of water resources planning, our study is motivated by recent theoretical work that has generalized the insights for Arrow's Paradox to the design of complex engineered systems. In this framing of the paradox, states of society are equivalent to water planning or design alternatives, and the voters are equivalent to multiple planning objectives (e.g. minimizing cost or maximizing performance). Seen from this point of view, multi-objective water planning problems are functionally equivalent to the social choice problem described above. Traditional solutions to such multi-objective problems aggregate multiple performance measures into a single mathematical objective. The Theorem implies that a subset of performance concerns will inadvertently dictate the overall design evaluations in unpredictable ways using such an aggregation. We suggest that instead of aggregation, an explicit many-objective approach to water planning can help overcome the challenges posed by Arrow's Paradox. Many-objective planning explicitly disaggregates measures of performance while supporting the discovery of the planning tradeoffs, employing multiobjective evolutionary algorithms (MOEAs) to find solutions. Using MOEA-based search to address Arrow's Paradox requires that the MOEAs perform robustly with increasing problem complexity, such as adding additional objectives and/or decisions. This study uses comprehensive diagnostic evaluation of MOEA search performance across multiple problem formulations (both aggregated and many-objective) to show whether or not aggregating performance measures biases decision making. In this study, we explore this hypothesis using an urban water portfolio management case study in the Lower Rio Grande Valley. The diagnostic analysis shows that modern self-adaptive MOEA search is efficient, effective, and reliable for the more complex many-objective LRGV planning formulations. Results indicate that although many classical water systems planning frameworks seek to account for multiple objectives, the common practice of reducing the problem into one or more highly aggregated performance measures can severely and negatively bias planning decisions.

Alternate Waveforms for a Low-Cost Civil Global Positioning System Receiver

DOT National Transportation Integrated Search

1980-06-01

This report examines the technical feasibility of alternate waveforms to perform the GPS functions and to result in less complex receivers than is possible with the GPS C/A waveform. The approach taken to accomplish this objective is (a) to identify,...

Nonlinear d10-ML2 Transition-Metal Complexes

PubMed Central

Wolters, Lando P; Bickelhaupt, F Matthias

2013-01-01

We have investigated the molecular geometries of a series of dicoordinated d10-transition-metal complexes ML2 (M=Co−, Rh−, Ir−, Ni, Pd, Pt, Cu+, Ag+, Au+; L=NH3, PH3, CO) using relativistic density functional theory (DFT) at ZORA-BLYP/TZ2P. Not all complexes have the expected linear ligand–metal–ligand (L–M–L) angle: this angle varies from 180° to 128.6° as a function of the metal as well as the ligands. Our main objective is to present a detailed explanation why ML2 complexes can become bent. To this end, we have analyzed the bonding mechanism in ML2 as a function of the L–M–L angle using quantitative Kohn–Sham molecular orbital (MO) theory in combination with an energy decomposition analysis (EDA) scheme. The origin of bent L–M–L structures is π backdonation. In situations of strong π backdonation, smaller angles increase the overlap of the ligand’s acceptor orbital with a higher-energy donor orbital on the metal-ligand fragment, and therefore favor π backdonation, resulting in additional stabilization. The angle of the complexes thus depends on the balance between this additional stabilization and increased steric repulsion that occurs as the complexes are bent. PMID:24551547

Minimal-scan filtered backpropagation algorithms for diffraction tomography.

PubMed

Pan, X; Anastasio, M A

1999-12-01

The filtered backpropagation (FBPP) algorithm, originally developed by Devaney [Ultrason. Imaging 4, 336 (1982)], has been widely used for reconstructing images in diffraction tomography. It is generally known that the FBPP algorithm requires scattered data from a full angular range of 2 pi for exact reconstruction of a generally complex-valued object function. However, we reveal that one needs scattered data only over the angular range 0 < or = phi < or = 3 pi/2 for exact reconstruction of a generally complex-valued object function. Using this insight, we develop and analyze a family of minimal-scan filtered backpropagation (MS-FBPP) algorithms, which, unlike the FBPP algorithm, use scattered data acquired from view angles over the range 0 < or = phi < or = 3 pi/2. We show analytically that these MS-FBPP algorithms are mathematically identical to the FBPP algorithm. We also perform computer simulation studies for validation, demonstration, and comparison of these MS-FBPP algorithms. The numerical results in these simulation studies corroborate our theoretical assertions.

The stellar population of the Lupus clouds

NASA Technical Reports Server (NTRS)

Hughes, Joanne; Hartigan, Patrick; Krautter, Joachim; Kelemen, Janos

1994-01-01

We present photometric and spectroscopic observations of the H alpha emission stars in the Lupus dark cloud complex. We estimate the effective temperatures of the stars from their spectral types and calculate the reddening towards each object from the (R-I) colors. From these data, we derive mass and age distributions for the Lupus stars using a new set of pre-main sequence evolutionar tracks. We compare the results for the Lupus stars with those for a similar population of young stellar objects in Taurus-Auriga and Chamaeleon and with the initial mass function for field stars in the solar neighborhood. From the H-R diagrams, Lupus appears to contain older stars than Taurus. The Lupus dark clouds form a greater proportion of low mass stars than the Taurus complex. Also, the proportion of low mass stars in Lupus is higher than that predicted by the Miller-Scalo initial mass function, and the lowest mass stars in Lupus are less active than similar T Tauri stars in other regions.

A Relationship Between Visual Complexity and Aesthetic Appraisal of Car Front Images: An Eye-Tracker Study.

PubMed

Chassy, Philippe; Lindell, Trym A E; Jones, Jessica A; Paramei, Galina V

2015-01-01

Image aesthetic pleasure (AP) is conjectured to be related to image visual complexity (VC). The aim of the present study was to investigate whether (a) two image attributes, AP and VC, are reflected in eye-movement parameters; and (b) subjective measures of AP and VC are related. Participants (N=26) explored car front images (M=50) while their eye movements were recorded. Following image exposure (10 seconds), its VC and AP were rated. Fixation count was found to positively correlate with the subjective VC and its objective proxy, JPEG compression size, suggesting that this eye-movement parameter can be considered an objective behavioral measure of VC. AP, in comparison, positively correlated with average dwelling time. Subjective measures of AP and VC were related too, following an inverted U-shape function best-fit by a quadratic equation. In addition, AP was found to be modulated by car prestige. Our findings reveal a close relationship between subjective and objective measures of complexity and aesthetic appraisal, which is interpreted within a prototype-based theory framework. © The Author(s) 2015.

Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images.

PubMed

Dzyubak, Oleksandr P; Ritman, Erik L

2011-01-01

The blood vessels and nerve trees consist of tubular objects interconnected into a complex tree- or web-like structure that has a range of structural scale 5 μm diameter capillaries to 3 cm aorta. This large-scale range presents two major problems; one is just making the measurements, and the other is the exponential increase of component numbers with decreasing scale. With the remarkable increase in the volume imaged by, and resolution of, modern day 3D imagers, it is almost impossible to make manual tracking of the complex multiscale parameters from those large image data sets. In addition, the manual tracking is quite subjective and unreliable. We propose a solution for automation of an adaptive nonsupervised system for tracking tubular objects based on multiscale framework and use of Hessian-based object shape detector incorporating National Library of Medicine Insight Segmentation and Registration Toolkit (ITK) image processing libraries.

Planning Ahead: Object-Directed Sequential Actions Decoded from Human Frontoparietal and Occipitotemporal Networks

PubMed Central

Gallivan, Jason P.; Johnsrude, Ingrid S.; Randall Flanagan, J.

2016-01-01

Object-manipulation tasks (e.g., drinking from a cup) typically involve sequencing together a series of distinct motor acts (e.g., reaching toward, grasping, lifting, and transporting the cup) in order to accomplish some overarching goal (e.g., quenching thirst). Although several studies in humans have investigated the neural mechanisms supporting the planning of visually guided movements directed toward objects (such as reaching or pointing), only a handful have examined how manipulatory sequences of actions—those that occur after an object has been grasped—are planned and represented in the brain. Here, using event-related functional MRI and pattern decoding methods, we investigated the neural basis of real-object manipulation using a delayed-movement task in which participants first prepared and then executed different object-directed action sequences that varied either in their complexity or final spatial goals. Consistent with previous reports of preparatory brain activity in non-human primates, we found that activity patterns in several frontoparietal areas reliably predicted entire action sequences in advance of movement. Notably, we found that similar sequence-related information could also be decoded from pre-movement signals in object- and body-selective occipitotemporal cortex (OTC). These findings suggest that both frontoparietal and occipitotemporal circuits are engaged in transforming object-related information into complex, goal-directed movements. PMID:25576538

Hyperspectral imaging simulation of object under sea-sky background

NASA Astrophysics Data System (ADS)

Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

2016-10-01

Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

Evaluation of partial coherence correction in X-ray ptychography

DOE PAGES

Burdet, Nicolas; Shi, Xiaowen; Parks, Daniel; ...

2015-02-23

Coherent X-ray Diffraction Imaging (CDI) and X-ray ptychography both heavily rely on the high degree of spatial coherence of the X-ray illumination for sufficient experimental data quality for reconstruction convergence. Nevertheless, the majority of the available synchrotron undulator sources have a limited degree of partial coherence, leading to reduced data quality and a lower speckle contrast in the coherent diffraction patterns. It is still an open question whether experimentalists should compromise the coherence properties of an X-ray source in exchange for a higher flux density at a sample, especially when some materials of scientific interest are relatively weak scatterers. Amore » previous study has suggested that in CDI, the best strategy for the study of strong phase objects is to maintain a high degree of coherence of the illuminating X-rays because of the broadening of solution space resulting from the strong phase structures. In this article, we demonstrate the first systematic analysis of the effectiveness of partial coherence correction in ptychography as a function of the coherence properties, degree of complexity of illumination (degree of phase diversity of the probe) and sample phase complexity. We have also performed analysis of how well ptychographic algorithms refine X-ray probe and complex coherence functions when those variables are unknown at the start of reconstructions, for noise-free simulated data, in the case of both real-valued and highly-complex objects.« less

Ontology of Earth's nonlinear dynamic complex systems

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Davarpanah, Armita

2017-04-01

As a complex system, Earth and its major integrated and dynamically interacting subsystems (e.g., hydrosphere, atmosphere) display nonlinear behavior in response to internal and external influences. The Earth Nonlinear Dynamic Complex Systems (ENDCS) ontology formally represents the semantics of the knowledge about the nonlinear system element (agent) behavior, function, and structure, inter-agent and agent-environment feedback loops, and the emergent collective properties of the whole complex system as the result of interaction of the agents with other agents and their environment. It also models nonlinear concepts such as aperiodic, random chaotic behavior, sensitivity to initial conditions, bifurcation of dynamic processes, levels of organization, self-organization, aggregated and isolated functionality, and emergence of collective complex behavior at the system level. By incorporating several existing ontologies, the ENDCS ontology represents the dynamic system variables and the rules of transformation of their state, emergent state, and other features of complex systems such as the trajectories in state (phase) space (attractor and strange attractor), basins of attractions, basin divide (separatrix), fractal dimension, and system's interface to its environment. The ontology also defines different object properties that change the system behavior, function, and structure and trigger instability. ENDCS will help to integrate the data and knowledge related to the five complex subsystems of Earth by annotating common data types, unifying the semantics of shared terminology, and facilitating interoperability among different fields of Earth science.

Clinical-Physiological Considerations in Patients Undergoing Staged Palliation for a Functionally Single Ventricle.

PubMed

Penny, Daniel J; Krishnamurthy, Rajesh

2016-08-01

The objectives of this review are to discuss the pathophysiology of the circulation with a functionally univentricular heart, with a focus on the unique physiologic characteristics, which provide the underpinnings for the management of these complex patients. MEDLINE and PubMed. The circulation of the patient with a functionally univentricular heart displays unique physiologic characteristics, which are quite different from those of the normal biventricular circulation. There are profound differences within the heart itself in terms of ventricular function, interventricular interactions, and myocardial architecture, which are likely to have significant implications for the efficiency of ventricular ejection and metabolism. The coupling between the systemic ventricle and the aorta also displays unique features. The 3D orientation of the Fontan anastomosis itself can profoundly impact cardiac output, although the "portal" pulmonary arterial bed is a crucial determinant of overall cardiovascular function. As a result, disease-specific approaches to improve cardiovascular function are required at all stages during the care of these complex patients.

Impaired recognition of faces and objects in dyslexia: Evidence for ventral stream dysfunction?

PubMed

Sigurdardottir, Heida Maria; Ívarsson, Eysteinn; Kristinsdóttir, Kristjana; Kristjánsson, Árni

2015-09-01

The objective of this study was to establish whether or not dyslexics are impaired at the recognition of faces and other complex nonword visual objects. This would be expected based on a meta-analysis revealing that children and adult dyslexics show functional abnormalities within the left fusiform gyrus, a brain region high up in the ventral visual stream, which is thought to support the recognition of words, faces, and other objects. 20 adult dyslexics (M = 29 years) and 20 matched typical readers (M = 29 years) participated in the study. One dyslexic-typical reader pair was excluded based on Adult Reading History Questionnaire scores and IS-FORM reading scores. Performance was measured on 3 high-level visual processing tasks: the Cambridge Face Memory Test, the Vanderbilt Holistic Face Processing Test, and the Vanderbilt Expertise Test. People with dyslexia are impaired in their recognition of faces and other visually complex objects. Their holistic processing of faces appears to be intact, suggesting that dyslexics may instead be specifically impaired at part-based processing of visual objects. The difficulty that people with dyslexia experience with reading might be the most salient manifestation of a more general high-level visual deficit. (c) 2015 APA, all rights reserved).

Performance of Geno-Fuzzy Model on rainfall-runoff predictions in claypan watersheds

USDA-ARS?s Scientific Manuscript database

Fuzzy logic provides a relatively simple approach to simulate complex hydrological systems while accounting for the uncertainty of environmental variables. The objective of this study was to develop a fuzzy inference system (FIS) with genetic algorithm (GA) optimization for membership functions (MF...

Clinical Practice Improvement Approach in Multiple Sclerosis Rehabilitation: A Pilot Study

ERIC Educational Resources Information Center

Khan, Fary

2010-01-01

The objective of this study was to explore methods examining patient complexity and therapy interventions in relation to functional outcomes from an inpatient multiple sclerosis (MS) rehabilitation program. Retrospective and prospective data for 24 consecutive inpatients at a tertiary rehabilitation facility assessed (i)…

THE ASSOCIATION BETWEEN SERUM FERRITIN AND URIC ACID IN HUMANS

EPA Science Inventory

OBJECTIVE: Urate forms a coordination complex with Fe(3+) which does not support electron transport. The only enzymatic source of urate is xanthine oxidoreductase. If a major purpose of xanthine oxidoreductase is the production of urate to function as an iron chelator and antioxi...

Executive Functioning and School Performance Among Pediatric Survivors of Complex Congenital Heart Disease

PubMed Central

Gerstle, Melissa; Beebe, Dean W.; Drotar, Dennis; Cassedy, Amy; Marino, Bradley S.

2016-01-01

Objective To investigate the presence and severity of real-world impairments in executive functioning– responsible for children’s regulatory skills (metacognition, behavioral regulation) – and its potential impact on school performance among pediatric survivors of complex congenital heart disease (CHD). Study design Survivors of complex CHD aged 8–16 years (n=143)and their parents/guardians from a regional CHD survivor registry participated (81% participation rate). Parents completed proxy measures of executive functioning, school competency, and school-related quality of life (QOL). Patients also completed a measure of school QOL and underwent IQ testing. Patients were categorized into two groups based on heart lesion complexity: two-ventricle or single-ventricle. Results Survivors of complex CHD performed significantly worse than norms for executive functioning, IQ, school competency, and school QOL. Metacognition was more severely affected than behavioral regulation, and metacognitive deficits were more often present in older children. Even after taking into account demographic factors, disease severity, and IQ, metacognition uniquely and strongly predicted poorer school performance. In exploratory analyses, patients with single-ventricle lesions were rated as having lower school competency and school QOL, and patients with two-ventricle lesions were rated as having poorer behavioral regulation. Conclusions Survivors of complex CHD experience greater executive functioning difficulties than healthy peers, with metacognition particularly impacted and particularly relevant for day-to-day school performance. Especially in older children, clinicians should watch for metacognitive deficits, such as problems with organization, planning, self-monitoring, and follow-through on tasks. PMID:26875011

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

Prediction of Human Activity by Discovering Temporal Sequence Patterns.

PubMed

Li, Kang; Fu, Yun

2014-08-01

Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

Parameterized hardware description as object oriented hardware model implementation

NASA Astrophysics Data System (ADS)

Drabik, Pawel K.

2010-09-01

The paper introduces novel model for design, visualization and management of complex, highly adaptive hardware systems. The model settles component oriented environment for both hardware modules and software application. It is developed on parameterized hardware description research. Establishment of stable link between hardware and software, as a purpose of designed and realized work, is presented. Novel programming framework model for the environment, named Graphic-Functional-Components is presented. The purpose of the paper is to present object oriented hardware modeling with mentioned features. Possible model implementation in FPGA chips and its management by object oriented software in Java is described.

On deformation of complex continuum immersed in a plane space

NASA Astrophysics Data System (ADS)

Kovalev, V. A.; Murashkin, E. V.; Radayev, Y. N.

2018-05-01

The present paper is devoted to mathematical modelling of complex continua deformations considered as immersed in an external plane space. The complex continuum is defined as a differential manifold supplied with metrics induced by the external space. A systematic derivation of strain tensors by notion of isometric immersion of the complex continuum into a plane space of a higher dimension is proposed. Problem of establishing complete systems of irreducible objective strain and extrastrain tensors for complex continuum immersed in an external plane space is resolved. The solution to the problem is obtained by methods of the field theory and the theory of rational algebraic invariants. Strain tensors of the complex continuum are derived as irreducible algebraic invariants of contravariant vectors of the external space emerging as functional arguments in the complex continuum action density. Present analysis is restricted to rational algebraic invariants. Completeness of the considered systems of rational algebraic invariants is established for micropolar elastic continua. Rational syzygies for non-quadratic invariants are discussed. Objective strain tensors (indifferent to frame rotations in the external plane space) for micropolar continuum are alternatively obtained by properly combining multipliers of polar decompositions of deformation and extra-deformation gradients. The latter is realized only for continua immersed in a plane space of the equal mathematical dimension.

Quantification of soil structure based on Minkowski functions

NASA Astrophysics Data System (ADS)

Vogel, H.-J.; Weller, U.; Schlüter, S.

2010-10-01

The structure of soils and other geologic media is a complex three-dimensional object. Most of the physical material properties including mechanical and hydraulic characteristics are immediately linked to the structure given by the pore space and its spatial distribution. It is an old dream and still a formidable challenge to relate structural features of porous media to their functional properties. Using tomographic techniques, soil structure can be directly observed at a range of spatial scales. In this paper we present a scale-invariant concept to quantify complex structures based on a limited set of meaningful morphological functions. They are based on d+1 Minkowski functionals as defined for d-dimensional bodies. These basic quantities are determined as a function of pore size or aggregate size obtained by filter procedures using mathematical morphology. The resulting Minkowski functions provide valuable information on the size of pores and aggregates, the pore surface area and the pore topology having the potential to be linked to physical properties. The theoretical background and the related algorithms are presented and the approach is demonstrated for the pore structure of an arable soil and the pore structure of a sand both obtained by X-ray micro-tomography. We also analyze the fundamental problem of limited resolution which is critical for any attempt to quantify structural features at any scale using samples of different size recorded at different resolutions. The results demonstrate that objects smaller than 5 voxels are critical for quantitative analysis.

Energy-density field approach for low- and medium-frequency vibroacoustic analysis of complex structures using a statistical computational model

NASA Astrophysics Data System (ADS)

Kassem, M.; Soize, C.; Gagliardini, L.

2009-06-01

In this paper, an energy-density field approach applied to the vibroacoustic analysis of complex industrial structures in the low- and medium-frequency ranges is presented. This approach uses a statistical computational model. The analyzed system consists of an automotive vehicle structure coupled with its internal acoustic cavity. The objective of this paper is to make use of the statistical properties of the frequency response functions of the vibroacoustic system observed from previous experimental and numerical work. The frequency response functions are expressed in terms of a dimensionless matrix which is estimated using the proposed energy approach. Using this dimensionless matrix, a simplified vibroacoustic model is proposed.

Dialectical Behavior Therapy (DBT) Applied to College Students: A Randomized Clinical Trial

ERIC Educational Resources Information Center

Pistorello, Jacqueline; Fruzzetti, Alan E.; MacLane, Chelsea; Gallop, Robert; Iverson, Katherine M.

2012-01-01

Objective: College counseling centers (CCCs) are increasingly being called upon to treat highly distressed students with complex clinical presentations. This study compared the effectiveness of Dialectical Behavior Therapy (DBT) for suicidal college students with an optimized control condition and analyzed baseline global functioning as a…

Case studies on optimization problems in MATLAB and COMSOL multiphysics by means of the livelink

NASA Astrophysics Data System (ADS)

Ozana, Stepan; Pies, Martin; Docekal, Tomas

2016-06-01

LiveLink for COMSOL is a tool that integrates COMSOL Multiphysics with MATLAB to extend one's modeling with scripting programming in the MATLAB environment. It allows user to utilize the full power of MATLAB and its toolboxes in preprocessing, model manipulation, and post processing. At first, the head script launches COMSOL with MATLAB and defines initial value of all parameters, refers to the objective function J described in the objective function and creates and runs the defined optimization task. Once the task is launches, the COMSOL model is being called in the iteration loop (from MATLAB environment by use of API interface), changing defined optimization parameters so that the objective function is minimized, using fmincon function to find a local or global minimum of constrained linear or nonlinear multivariable function. Once the minimum is found, it returns exit flag, terminates optimization and returns the optimized values of the parameters. The cooperation with MATLAB via LiveLink enhances a powerful computational environment with complex multiphysics simulations. The paper will introduce using of the LiveLink for COMSOL for chosen case studies in the field of technical cybernetics and bioengineering.

A method for real-time visual stimulus selection in the study of cortical object perception.

PubMed

Leeds, Daniel D; Tarr, Michael J

2016-06-01

The properties utilized by visual object perception in the mid- and high-level ventral visual pathway are poorly understood. To better establish and explore possible models of these properties, we adopt a data-driven approach in which we repeatedly interrogate neural units using functional Magnetic Resonance Imaging (fMRI) to establish each unit's image selectivity. This approach to imaging necessitates a search through a broad space of stimulus properties using a limited number of samples. To more quickly identify the complex visual features underlying human cortical object perception, we implemented a new functional magnetic resonance imaging protocol in which visual stimuli are selected in real-time based on BOLD responses to recently shown images. Two variations of this protocol were developed, one relying on natural object stimuli and a second based on synthetic object stimuli, both embedded in feature spaces based on the complex visual properties of the objects. During fMRI scanning, we continuously controlled stimulus selection in the context of a real-time search through these image spaces in order to maximize neural responses across pre-determined 1cm(3) rain regions. Elsewhere we have reported the patterns of cortical selectivity revealed by this approach (Leeds et al., 2014). In contrast, here our objective is to present more detailed methods and explore the technical and biological factors influencing the behavior of our real-time stimulus search. We observe that: 1) Searches converged more reliably when exploring a more precisely parameterized space of synthetic objects; 2) real-time estimation of cortical responses to stimuli is reasonably consistent; 3) search behavior was acceptably robust to delays in stimulus displays and subject motion effects. Overall, our results indicate that real-time fMRI methods may provide a valuable platform for continuing study of localized neural selectivity, both for visual object representation and beyond. Copyright © 2016 Elsevier Inc. All rights reserved.

A method for real-time visual stimulus selection in the study of cortical object perception

PubMed Central

Leeds, Daniel D.; Tarr, Michael J.

2016-01-01

The properties utilized by visual object perception in the mid- and high-level ventral visual pathway are poorly understood. To better establish and explore possible models of these properties, we adopt a data-driven approach in which we repeatedly interrogate neural units using functional Magnetic Resonance Imaging (fMRI) to establish each unit’s image selectivity. This approach to imaging necessitates a search through a broad space of stimulus properties using a limited number of samples. To more quickly identify the complex visual features underlying human cortical object perception, we implemented a new functional magnetic resonance imaging protocol in which visual stimuli are selected in real-time based on BOLD responses to recently shown images. Two variations of this protocol were developed, one relying on natural object stimuli and a second based on synthetic object stimuli, both embedded in feature spaces based on the complex visual properties of the objects. During fMRI scanning, we continuously controlled stimulus selection in the context of a real-time search through these image spaces in order to maximize neural responses across predetermined 1 cm3 brain regions. Elsewhere we have reported the patterns of cortical selectivity revealed by this approach (Leeds 2014). In contrast, here our objective is to present more detailed methods and explore the technical and biological factors influencing the behavior of our real-time stimulus search. We observe that: 1) Searches converged more reliably when exploring a more precisely parameterized space of synthetic objects; 2) Real-time estimation of cortical responses to stimuli are reasonably consistent; 3) Search behavior was acceptably robust to delays in stimulus displays and subject motion effects. Overall, our results indicate that real-time fMRI methods may provide a valuable platform for continuing study of localized neural selectivity, both for visual object representation and beyond. PMID:26973168

Measurement and simulation of the relatively competitive advantages and weaknesses between economies based on bipartite graph theory.

PubMed

Guan, Jun; Xu, Xiaoyu; Wu, Shan; Xing, Lizhi

2018-01-01

The input-output table is very comprehensive and detailed in describing the national economic systems with abundant economic relationships, which contain supply and demand information among various industrial sectors. The complex network, a theory, and method for measuring the structure of a complex system can depict the structural characteristics of the internal structure of the researched object by measuring the structural indicators of the social and economic systems, revealing the complex relationships between the inner hierarchies and the external economic functions. In this paper, functions of industrial sectors on the global value chain are to be distinguished with bipartite graph theory, and inter-sector competitive relationships are to be extracted through resource allocation process. Furthermore, quantitative analysis indices will be proposed under the perspective of a complex network, which will be used to bring about simulations on the variation tendencies of economies' status in different situations of commercial intercourses. Finally, a new econophysics analytical framework of international trade is to be established.

Measurement and simulation of the relatively competitive advantages and weaknesses between economies based on bipartite graph theory

PubMed Central

Guan, Jun; Xu, Xiaoyu; Wu, Shan

2018-01-01

The input-output table is very comprehensive and detailed in describing the national economic systems with abundant economic relationships, which contain supply and demand information among various industrial sectors. The complex network, a theory, and method for measuring the structure of a complex system can depict the structural characteristics of the internal structure of the researched object by measuring the structural indicators of the social and economic systems, revealing the complex relationships between the inner hierarchies and the external economic functions. In this paper, functions of industrial sectors on the global value chain are to be distinguished with bipartite graph theory, and inter-sector competitive relationships are to be extracted through resource allocation process. Furthermore, quantitative analysis indices will be proposed under the perspective of a complex network, which will be used to bring about simulations on the variation tendencies of economies’ status in different situations of commercial intercourses. Finally, a new econophysics analytical framework of international trade is to be established. PMID:29813083

Integration of the Gene Ontology into an object-oriented architecture.

PubMed

Shegogue, Daniel; Zheng, W Jim

2005-05-10

To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO) has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model. Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta) receptor complex assembly" (GO:0007181). We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.

An object-oriented class library for medical software development.

PubMed

O'Kane, K C; McColligan, E E

1996-12-01

The objective of this research is the development of a Medical Object Library (MOL) consisting of reusable, inheritable, portable, extendable C++ classes that facilitate rapid development of medical software at reduced cost and increased functionality. The result of this research is a library of class objects that range in function from string and hierarchical file handling entities to high level, procedural agents that perform increasingly complex, integrated tasks. A system built upon these classes is compatible with any other system similarly constructed with respect to data definitions, semantics, data organization and storage. As new objects are built, they can be added to the class library for subsequent use. The MOL is a toolkit of software objects intended to support a common file access methodology, a unified medical record structure, consistent message processing, standard graphical display facilities and uniform data collection procedures. This work emphasizes the relationship that potentially exists between the structure of a hierarchical medical record and procedural language components by means of a hierarchical class library and tree structured file access facility. In doing so, it attempts to establish interest in and demonstrate the practicality of the hierarchical medical record model in the modern context of object oriented programming.

Integration of the Gene Ontology into an object-oriented architecture

PubMed Central

Shegogue, Daniel; Zheng, W Jim

2005-01-01

Background To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO) has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model. Results Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta) receptor complex assembly" (GO:0007181). Conclusion We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes. PMID:15885145

The fractal geometry of life.

PubMed

Losa, Gabriele A

2009-01-01

The extension of the concepts of Fractal Geometry (Mandelbrot [1983]) toward the life sciences has led to significant progress in understanding complex functional properties and architectural / morphological / structural features characterising cells and tissues during ontogenesis and both normal and pathological development processes. It has even been argued that fractal geometry could provide a coherent description of the design principles underlying living organisms (Weibel [1991]). Fractals fulfil a certain number of theoretical and methodological criteria including a high level of organization, shape irregularity, functional and morphological self-similarity, scale invariance, iterative pathways and a peculiar non-integer fractal dimension [FD]. Whereas mathematical objects are deterministic invariant or self-similar over an unlimited range of scales, biological components are statistically self-similar only within a fractal domain defined by upper and lower limits, called scaling window, in which the relationship between the scale of observation and the measured size or length of the object can be established (Losa and Nonnenmacher [1996]). Selected examples will contribute to depict complex biological shapes and structures as fractal entities, and also to show why the application of the fractal principle is valuable for measuring dimensional, geometrical and functional parameters of cells, tissues and organs occurring within the vegetal and animal realms. If the criteria for a strict description of natural fractals are met, then it follows that a Fractal Geometry of Life may be envisaged and all natural objects and biological systems exhibiting self-similar patterns and scaling properties may be considered as belonging to the new subdiscipline of "fractalomics".

Using Multicriteria Analysis in Issues Concerning Adaptation of Historic Facilities for the Needs of Public Utility Buildings with a Function of a Theatre

NASA Astrophysics Data System (ADS)

Obracaj, Piotr; Fabianowski, Dariusz

2017-10-01

Implementations concerning adaptation of historic facilities for public utility objects are associated with the necessity of solving many complex, often conflicting expectations of future users. This mainly concerns the function that includes construction, technology and aesthetic issues. The list of issues is completed with proper protection of historic values, different in each case. The procedure leading to obtaining the expected solution is a multicriteria procedure, usually difficult to accurately define and requiring designer’s large experience. An innovative approach has been used for the analysis, namely - the modified EA FAHP (Extent Analysis Fuzzy Analytic Hierarchy Process) Chang’s method of a multicriteria analysis for the assessment of complex functional and spatial issues. Selection of optimal spatial form of an adapted historic building intended for the multi-functional public utility facility was analysed. The assumed functional flexibility was determined in the scope of: education, conference, and chamber spectacles, such as drama, concerts, in different stage-audience layouts.

Repair of acute injuries of the lateral ligament complex of the ankle by suture anchors

PubMed Central

Liu, Xiang-Fei; Fang, Yang; Cao, Zhong-Hua; Li, Guang-Feng; Yang, Guo-Qing

2015-01-01

Objective: The objective of this study was to investigate the clinical curative effect of stage I repair of acute injuries of the lateral ligament complex of the ankle by the application of suture anchors. Methods: We retrospectively analyzed 18 cases of III degree acute injuries of the lateral ligament complex of the ankle. Results: There were statistically significant differences in preoperative and last follow-up VAS pain scores and AOFAS ankle hind-foot function scores. The X-ray talus displacement values in the anterior drawer test and pressure anteroposterior X-ray talar tilt in the ankle talar tilt test also showed statistically significant differences. Complications occurred in 2 patients, incision surface infection in one, and postoperative lateral dorsal skin numbness in one. All these cases were cured after symptomatic treatment. At the last follow-up all patients’ ankle joint activity recovered to their preinjury function levels. Conclusion: The application of suture anchors for small incision stage I repair of the lateral collateral ligament of ankle joint degree III injury, can effectively restored the stability of ankle joint, and prevent the occurrence of chronic ankle instability complications. It is effective and feasible for the treatment of ankle joint lateral collateral ligament injuries. PMID:26885144

Haptically Guided Grasping. fMRI Shows Right-Hemisphere Parietal Stimulus Encoding, and Bilateral Dorso-Ventral Parietal Gradients of Object- and Action-Related Processing during Grasp Execution

PubMed Central

Marangon, Mattia; Kubiak, Agnieszka; Króliczak, Gregory

2016-01-01

The neural bases of haptically-guided grasp planning and execution are largely unknown, especially for stimuli having no visual representations. Therefore, we used functional magnetic resonance imaging (fMRI) to monitor brain activity during haptic exploration of novel 3D complex objects, subsequent grasp planning, and the execution of the pre-planned grasps. Haptic object exploration, involving extraction of shape, orientation, and length of the to-be-grasped targets, was associated with the fronto-parietal, temporo-occipital, and insular cortex activity. Yet, only the anterior divisions of the posterior parietal cortex (PPC) of the right hemisphere were significantly more engaged in exploration of complex objects (vs. simple control disks). None of these regions were re-recruited during the planning phase. Even more surprisingly, the left-hemisphere intraparietal, temporal, and occipital areas that were significantly invoked for grasp planning did not show sensitivity to object features. Finally, grasp execution, involving the re-recruitment of the critical right-hemisphere PPC clusters, was also significantly associated with two kinds of bilateral parieto-frontal processes. The first represents transformations of grasp-relevant target features and is linked to the dorso-dorsal (lateral and medial) parieto-frontal networks. The second monitors grasp kinematics and belongs to the ventro-dorsal networks. Indeed, signal modulations associated with these distinct functions follow dorso-ventral gradients, with left aIPS showing significant sensitivity to both target features and the characteristics of the required grasp. Thus, our results from the haptic domain are consistent with the notion that the parietal processing for action guidance reflects primarily transformations from object-related to effector-related coding, and these mechanisms are rather independent of sensory input modality. PMID:26779002

Haptically Guided Grasping. fMRI Shows Right-Hemisphere Parietal Stimulus Encoding, and Bilateral Dorso-Ventral Parietal Gradients of Object- and Action-Related Processing during Grasp Execution.

PubMed

Marangon, Mattia; Kubiak, Agnieszka; Króliczak, Gregory

2015-01-01

The neural bases of haptically-guided grasp planning and execution are largely unknown, especially for stimuli having no visual representations. Therefore, we used functional magnetic resonance imaging (fMRI) to monitor brain activity during haptic exploration of novel 3D complex objects, subsequent grasp planning, and the execution of the pre-planned grasps. Haptic object exploration, involving extraction of shape, orientation, and length of the to-be-grasped targets, was associated with the fronto-parietal, temporo-occipital, and insular cortex activity. Yet, only the anterior divisions of the posterior parietal cortex (PPC) of the right hemisphere were significantly more engaged in exploration of complex objects (vs. simple control disks). None of these regions were re-recruited during the planning phase. Even more surprisingly, the left-hemisphere intraparietal, temporal, and occipital areas that were significantly invoked for grasp planning did not show sensitivity to object features. Finally, grasp execution, involving the re-recruitment of the critical right-hemisphere PPC clusters, was also significantly associated with two kinds of bilateral parieto-frontal processes. The first represents transformations of grasp-relevant target features and is linked to the dorso-dorsal (lateral and medial) parieto-frontal networks. The second monitors grasp kinematics and belongs to the ventro-dorsal networks. Indeed, signal modulations associated with these distinct functions follow dorso-ventral gradients, with left aIPS showing significant sensitivity to both target features and the characteristics of the required grasp. Thus, our results from the haptic domain are consistent with the notion that the parietal processing for action guidance reflects primarily transformations from object-related to effector-related coding, and these mechanisms are rather independent of sensory input modality.

Web mapping system for complex processing and visualization of environmental geospatial datasets

NASA Astrophysics Data System (ADS)

Titov, Alexander; Gordov, Evgeny; Okladnikov, Igor

2016-04-01

Environmental geospatial datasets (meteorological observations, modeling and reanalysis results, etc.) are used in numerous research applications. Due to a number of objective reasons such as inherent heterogeneity of environmental datasets, big dataset volume, complexity of data models used, syntactic and semantic differences that complicate creation and use of unified terminology, the development of environmental geodata access, processing and visualization services as well as client applications turns out to be quite a sophisticated task. According to general INSPIRE requirements to data visualization geoportal web applications have to provide such standard functionality as data overview, image navigation, scrolling, scaling and graphical overlay, displaying map legends and corresponding metadata information. It should be noted that modern web mapping systems as integrated geoportal applications are developed based on the SOA and might be considered as complexes of interconnected software tools for working with geospatial data. In the report a complex web mapping system including GIS web client and corresponding OGC services for working with geospatial (NetCDF, PostGIS) dataset archive is presented. There are three basic tiers of the GIS web client in it: 1. Tier of geospatial metadata retrieved from central MySQL repository and represented in JSON format 2. Tier of JavaScript objects implementing methods handling: --- NetCDF metadata --- Task XML object for configuring user calculations, input and output formats --- OGC WMS/WFS cartographical services 3. Graphical user interface (GUI) tier representing JavaScript objects realizing web application business logic Metadata tier consists of a number of JSON objects containing technical information describing geospatial datasets (such as spatio-temporal resolution, meteorological parameters, valid processing methods, etc). The middleware tier of JavaScript objects implementing methods for handling geospatial metadata, task XML object, and WMS/WFS cartographical services interconnects metadata and GUI tiers. The methods include such procedures as JSON metadata downloading and update, launching and tracking of the calculation task running on the remote servers as well as working with WMS/WFS cartographical services including: obtaining the list of available layers, visualizing layers on the map, exporting layers in graphical (PNG, JPG, GeoTIFF), vector (KML, GML, Shape) and digital (NetCDF) formats. Graphical user interface tier is based on the bundle of JavaScript libraries (OpenLayers, GeoExt and ExtJS) and represents a set of software components implementing web mapping application business logic (complex menus, toolbars, wizards, event handlers, etc.). GUI provides two basic capabilities for the end user: configuring the task XML object functionality and cartographical information visualizing. The web interface developed is similar to the interface of such popular desktop GIS applications, as uDIG, QuantumGIS etc. Web mapping system developed has shown its effectiveness in the process of solving real climate change research problems and disseminating investigation results in cartographical form. The work is supported by SB RAS Basic Program Projects VIII.80.2.1 and IV.38.1.7.

Magnetotelluric inversion via reverse time migration algorithm of seismic data

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

Ha, Taeyoung; Shin, Changsoo

2007-07-01

We propose a new algorithm for two-dimensional magnetotelluric (MT) inversion. Our algorithm is an MT inversion based on the steepest descent method, borrowed from the backpropagation technique of seismic inversion or reverse time migration, introduced in the middle 1980s by Lailly and Tarantola. The steepest descent direction can be calculated efficiently by using the symmetry of numerical Green's function derived from a mixed finite element method proposed by Nedelec for Maxwell's equation, without calculating the Jacobian matrix explicitly. We construct three different objective functions by taking the logarithm of the complex apparent resistivity as introduced in the recent waveform inversionmore » algorithm by Shin and Min. These objective functions can be naturally separated into amplitude inversion, phase inversion and simultaneous inversion. We demonstrate our algorithm by showing three inversion results for synthetic data.« less

To what extent do joint attention, imitation, and object play behaviors in infancy predict later communication and intellectual functioning in ASD?

PubMed

Poon, Kenneth K; Watson, Linda R; Baranek, Grace T; Poe, Michele D

2012-06-01

The extent to which early social communication behaviors predict later communication and intellectual outcomes was investigated via retrospective video analysis. Joint attention, imitation, and complex object play behaviors were coded from edited home videos featuring scenes of 29 children with ASD at 9-12 and/or 15-18 months. A quantitative interval recording of behavior and a qualitative rating of the developmental level were applied. Social communication behaviors increased between 9-12 and 15-18 months. Their mean level during infancy, but not the rate of change, predicted both Vineland Communication scores and intellectual functioning at 3-7 years. The two methods of measurement yielded similar results. Thus, early social communicative behaviors may play pivotal roles in the development of subsequent communication and intellectual functioning.

Unraveling dynamics of human physical activity patterns in chronic pain conditions

NASA Astrophysics Data System (ADS)

Paraschiv-Ionescu, Anisoara; Buchser, Eric; Aminian, Kamiar

2013-06-01

Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a `signature' of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.

My Corporis Fabrica: an ontology-based tool for reasoning and querying on complex anatomical models

PubMed Central

2014-01-01

Background Multiple models of anatomy have been developed independently and for different purposes. In particular, 3D graphical models are specially useful for visualizing the different organs composing the human body, while ontologies such as FMA (Foundational Model of Anatomy) are symbolic models that provide a unified formal description of anatomy. Despite its comprehensive content concerning the anatomical structures, the lack of formal descriptions of anatomical functions in FMA limits its usage in many applications. In addition, the absence of connection between 3D models and anatomical ontologies makes it difficult and time-consuming to set up and access to the anatomical content of complex 3D objects. Results First, we provide a new ontology of anatomy called My Corporis Fabrica (MyCF), which conforms to FMA but extends it by making explicit how anatomical structures are composed, how they contribute to functions, and also how they can be related to 3D complex objects. Second, we have equipped MyCF with automatic reasoning capabilities that enable model checking and complex queries answering. We illustrate the added-value of such a declarative approach for interactive simulation and visualization as well as for teaching applications. Conclusions The novel vision of ontologies that we have developed in this paper enables a declarative assembly of different models to obtain composed models guaranteed to be anatomically valid while capturing the complexity of human anatomy. The main interest of this approach is its declarativity that makes possible for domain experts to enrich the knowledge base at any moment through simple editors without having to change the algorithmic machinery. This provides MyCF software environment a flexibility to process and add semantics on purpose for various applications that incorporate not only symbolic information but also 3D geometric models representing anatomical entities as well as other symbolic information like the anatomical functions. PMID:24936286

OBJECT REPRESENTATION, IDENTITY, AND THE PARADOX OF EARLY PERMANENCE: Steps Toward a New Framework.

PubMed

Meltzoff, Andrew N; Moore, M Keith

1998-01-01

The sensorimotor theory of infancy has been overthrown, but there is little consensus on a replacement. We hypothesize that a capacity for representation is the starting point for infant development, not its culmination. Logical distinctions are drawn between object representation, identity, and permanence. Modern experiments on early object permanence and deferred imitation suggest: (a) even for young infants, representations persist over breaks in sensory contact, (b) numerical identity of objects ( O s) is initially specified by spatiotemporal criteria (place and trajectory), (c) featural and functional identity criteria develop, (d) events are analyzed by comparing representations to current perception, and (e) representation operates both prospectively, anticipating future contacts with an O , and retrospectively, reidentifying an O as the "same one again." A model of the architecture and functioning of the early representational system is proposed. It accounts for young infants' behavior toward absent people and things in terms of their efforts to determine the identity of objects. Our proposal is developmental without denying innate structure and elevates the power of perception and representation while being cautious about attributing complex concepts to young infants.

OBJECT REPRESENTATION, IDENTITY, AND THE PARADOX OF EARLY PERMANENCE: Steps Toward a New Framework

PubMed Central

Meltzoff, Andrew N.; Moore, M. Keith

2013-01-01

The sensorimotor theory of infancy has been overthrown, but there is little consensus on a replacement. We hypothesize that a capacity for representation is the starting point for infant development, not its culmination. Logical distinctions are drawn between object representation, identity, and permanence. Modern experiments on early object permanence and deferred imitation suggest: (a) even for young infants, representations persist over breaks in sensory contact, (b) numerical identity of objects (Os) is initially specified by spatiotemporal criteria (place and trajectory), (c) featural and functional identity criteria develop, (d) events are analyzed by comparing representations to current perception, and (e) representation operates both prospectively, anticipating future contacts with an O, and retrospectively, reidentifying an O as the “same one again.” A model of the architecture and functioning of the early representational system is proposed. It accounts for young infants’ behavior toward absent people and things in terms of their efforts to determine the identity of objects. Our proposal is developmental without denying innate structure and elevates the power of perception and representation while being cautious about attributing complex concepts to young infants. PMID:25147418

Discrimination of complex synthetic echoes by an echolocating bottlenose dolphin

NASA Astrophysics Data System (ADS)

Helweg, David A.; Moore, Patrick W.; Dankiewicz, Lois A.; Zafran, Justine M.; Brill, Randall L.

2003-02-01

Bottlenose dolphins (Tursiops truncatus) detect and discriminate underwater objects by interrogating the environment with their native echolocation capabilities. Study of dolphins' ability to detect complex (multihighlight) signals in noise suggest echolocation object detection using an approximate 265-μs energy integration time window sensitive to the echo region of highest energy or containing the highlight with highest energy. Backscatter from many real objects contains multiple highlights, distributed over multiple integration windows and with varying amplitude relationships. This study used synthetic echoes with complex highlight structures to test whether high-amplitude initial highlights would interfere with discrimination of low-amplitude trailing highlights. A dolphin was trained to discriminate two-highlight synthetic echoes using differences in the center frequencies of the second highlights. The energy ratio (ΔdB) and the timing relationship (ΔT) between the first and second highlights were manipulated. An iso-sensitivity function was derived using a factorial design testing ΔdB at -10, -15, -20, and -25 dB and ΔT at 10, 20, 40, and 80 μs. The results suggest that the animal processed multiple echo highlights as separable analyzable features in the discrimination task, perhaps perceived through differences in spectral rippling across the duration of the echoes.

Measuring case-mix complexity of tertiary care hospitals using DRGs.

PubMed

Park, Hayoung; Shin, Youngsoo

2004-02-01

The objectives of the study were to develop a model that measures and evaluates case-mix complexity of tertiary care hospitals, and to examine the characteristics of such a model. Physician panels defined three classes of case complexity and assigned disease categories represented by Adjacent Diagnosis Related Groups (ADRGs) to one of three case complexity classes. Three types of scores, indicating proportions of inpatients in each case complexity class standardized by the proportions at the national level, were defined to measure the case-mix complexity of a hospital. Discharge information for about 10% of inpatient episodes at 85 hospitals with bed size larger than 400 and their input structure and research and education activity were used to evaluate the case-mix complexity model. Results show its power to predict hospitals with the expected functions of tertiary care hospitals, i.e. resource intensive care, expensive input structure, and high levels of research and education activities.

Using computational fluid dynamics to test functional and ecological hypotheses in fossil taxa

NASA Astrophysics Data System (ADS)

Rahman, Imran

2016-04-01

Reconstructing how ancient organisms moved and fed is a major focus of study in palaeontology. Traditionally, this has been hampered by a lack of objective data on the functional morphology of extinct species, especially those without a clear modern analogue. However, cutting-edge techniques for characterizing specimens digitally and in three dimensions, coupled with state-of-the-art computer models, now provide a robust framework for testing functional and ecological hypotheses even in problematic fossil taxa. One such approach is computational fluid dynamics (CFD), a method for simulating fluid flows around objects that has primarily been applied to complex engineering-design problems. Here, I will present three case studies of CFD applied to fossil taxa, spanning a range of specimen sizes, taxonomic groups and geological ages. First, I will show how CFD enabled a rigorous test of hypothesized feeding modes in an enigmatic Ediacaran organism with three-fold symmetry, revealing previously unappreciated complexity of pre-Cambrian ecosystems. Second, I will show how CFD was used to evaluate hydrodynamic performance and feeding in Cambrian stem-group echinoderms, shedding light on the probable feeding strategy of the latest common ancestor of all deuterostomes. Third, I will show how CFD allowed us to explore the link between form and function in Mesozoic ichthyosaurs. These case studies serve to demonstrate the enormous potential of CFD for addressing long-standing hypotheses for a variety of fossil taxa, opening up an exciting new avenue in palaeontological studies of functional morphology.

Monitoring fetal maturation—objectives, techniques and indices of autonomic function*

PubMed Central

Hoyer, Dirk; Żebrowski, Jan; Cysarz, Dirk; Gonçalves, Hernâni; Pytlik, Adelina; Amorim-Costa, Célia; Bernardes, João; Ayres-de-Campos, Diogo; Witte, Otto W; Schleußner, Ekkehard; Stroux, Lisa; Redman, Christopher; Georgieva, Antoniya; Payne, Stephen; Clifford, Gari; Signorini, Maria G; Magenes, Giovanni; Andreotti, Fernando; Malberg, Hagen; Zaunseder, Sebastian; Lakhno, Igor; Schneider, Uwe

2017-01-01

Objective Monitoring the fetal behavior does not only have implications for acute care but also for identifying developmental disturbances that burden the entire later life. The concept, of ‘fetal programming’, also known as ‘developmental origins of adult disease hypothesis’, e.g. applies for cardiovascular, metabolic, hyperkinetic, cognitive disorders. Since the autonomic nervous system is involved in all of those systems, cardiac autonomic control may provide relevant functional diagnostic and prognostic information. Approach The fetal heart rate patterns (HRP) are one of the few functional signals in the prenatal period that relate to autonomic control and, therefore, is key to fetal autonomic assessment. The development of sensitive markers of fetal maturation and its disturbances requires the consideration of physiological fundamentals, recording technology and HRP parameters of autonomic control. Main Results Based on the ESGCO2016 special session on monitoring the fetal maturation we herein report the most recent results on: (i) functional fetal autonomic brain age score (fABAS), Recurrence Quantitative Analysis and Binary Symbolic Dynamics of complex HRP resolve specific maturation periods, (ii) magnetocardiography (MCG) based fABAS was validated for cardiotocography (CTG), (iii) 30 min recordings are sufficient for obtaining episodes of high variability, important for intrauterine growth restriction (IUGR) detection in handheld Doppler, (iv) novel parameters from PRSA to identify Intra IUGR fetuses, (v) evaluation of fetal electrocardiographic (ECG) recordings, (vi) correlation between maternal and fetal HRV is disturbed in pre-eclampsia. Significance The reported novel developments significantly extend the possibilities for the established CTG methodology. Novel HRP indices improve the accuracy of assessment due to their more appropriate consideration of complex autonomic processes across the recording technologies (CTG, handheld Doppler, MCG, ECG). The ultimate objective is their dissemination into routine practice and studies of fetal developmental disturbances with implications for programming of adult diseases. PMID:28186000

A Study of the Congruency of Competencies and Criterion-Referenced Measures.

ERIC Educational Resources Information Center

Jones, John Wilbur, Jr.

The job of the 4-H extension agent involves fairly complex levels of performance. The curriculum for the extension agent program should produce youth workers who have the ability to perform competently and who possess the basic concepts and values required to function effectively. Performance objectives were written for each competency considered…

Tools for the 21st Century. Southwest Alabama Cooperative Literacy Project. Final Evaluation.

ERIC Educational Resources Information Center

Lipscomb, Judith D.; Cronin, C. Hines

The Southwest Alabama Cooperative Literacy Project was a workplace literacy program involving the University of South Alabama and seven manufacturing plants in the LeMoyne Industrial Complex in southwestern Alabama. The project's primary objective was to increase job productivity by teaching both conventional and functional literacy skills in…

Information and Complexity Measures Applied to Observed and Simulated Soil Moisture Time Series

USDA-ARS?s Scientific Manuscript database

Time series of soil moisture-related parameters provides important insights in functioning of soil water systems. Analysis of patterns within these time series has been used in several studies. The objective of this work was to compare patterns in observed and simulated soil moisture contents to u...

Parameter Optimization for Turbulent Reacting Flows Using Adjoints

NASA Astrophysics Data System (ADS)

Lapointe, Caelan; Hamlington, Peter E.

2017-11-01

The formulation of a new adjoint solver for topology optimization of turbulent reacting flows is presented. This solver provides novel configurations (e.g., geometries and operating conditions) based on desired system outcomes (i.e., objective functions) for complex reacting flow problems of practical interest. For many such problems, it would be desirable to know optimal values of design parameters (e.g., physical dimensions, fuel-oxidizer ratios, and inflow-outflow conditions) prior to real-world manufacture and testing, which can be expensive, time-consuming, and dangerous. However, computational optimization of these problems is made difficult by the complexity of most reacting flows, necessitating the use of gradient-based optimization techniques in order to explore a wide design space at manageable computational cost. The adjoint method is an attractive way to obtain the required gradients, because the cost of the method is determined by the dimension of the objective function rather than the size of the design space. Here, the formulation of a novel solver is outlined that enables gradient-based parameter optimization of turbulent reacting flows using the discrete adjoint method. Initial results and an outlook for future research directions are provided.

KBGIS-2: A knowledge-based geographic information system

NASA Technical Reports Server (NTRS)

Smith, T.; Peuquet, D.; Menon, S.; Agarwal, P.

1986-01-01

The architecture and working of a recently implemented knowledge-based geographic information system (KBGIS-2) that was designed to satisfy several general criteria for the geographic information system are described. The system has four major functions that include query-answering, learning, and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial objects 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 currently performing all its designated tasks successfully, although currently implemented on inadequate hardware. Future reports will detail the performance characteristics of the system, and various new extensions are planned in order to enhance the power of KBGIS-2.

Cloaking of arbitrarily shaped objects with homogeneous coatings

NASA Astrophysics Data System (ADS)

Forestiere, Carlo; Dal Negro, Luca; Miano, Giovanni

2014-05-01

We present a theory for the cloaking of arbitrarily shaped objects and demonstrate electromagnetic scattering cancellation through designed homogeneous coatings. First, in the small-particle limit, we expand the dipole moment of a coated object in terms of its resonant modes. By zeroing the numerator of the resulting rational function, we accurately predict the permittivity values of the coating layer that abates the total scattered power. Then, we extend the applicability of the method beyond the small-particle limit, deriving the radiation corrections of the scattering-cancellation permittivity within a perturbation approach. Our method permits the design of invisibility cloaks for irregularly shaped devices such as complex sensors and detectors.

Object processing in the infant: lessons from neuroscience.

PubMed

Wilcox, Teresa; Biondi, Marisa

2015-07-01

Object identification is a fundamental cognitive capacity that forms the basis for complex thought and behavior. The adult cortex is organized into functionally distinct visual object-processing pathways that mediate this ability. Insights into the origin of these pathways have begun to emerge through the use of neuroimaging techniques with infant populations. The outcome of this work supports the view that, from the early days of life, object-processing pathways are organized in a way that resembles that of the adult. At the same time, theoretically important changes in patterns of cortical activation are observed during the first year. These findings lead to a new understanding of the cognitive and neural architecture in infants that supports their emerging object-processing capacities. Copyright © 2015 Elsevier Ltd. All rights reserved.

The method of selecting an integrated development territory for the high-rise unique constructions

NASA Astrophysics Data System (ADS)

Sheina, Svetlana; Shevtsova, Elina; Sukhinin, Alexander; Priss, Elena

2018-03-01

On the basis of data provided by the Department of architecture and urban planning of the city of Rostov-on-don, the problem of the choice of the territory for complex development that will be in priority for the construction of high-rise and unique buildings is solved. The objective of the study was the development of a methodology for selection of the area and the implementation of the proposed method on the example of evaluation of four-territories complex development. The developed method along with standard indicators of complex evaluation considers additional indicators that assess the territory from the position of high-rise unique building. The final result of the study is the rankings of the functional priority areas that takes into account the construction of both residential and public and business objects of unique high-rise construction. The use of the developed methodology will allow investors and customers to assess the investment attractiveness of the future unique construction project on the proposed site.

Exploring novel objective functions for simulating muscle coactivation in the neck.

PubMed

Mortensen, J; Trkov, M; Merryweather, A

2018-04-11

Musculoskeletal modeling allows for analysis of individual muscles in various situations. However, current techniques to realistically simulate muscle response when significant amounts of intentional coactivation is required are inadequate. This would include stiffening the neck or spine through muscle coactivation in preparation for perturbations or impacts. Muscle coactivation has been modeled previously in the neck and spine using optimization techniques that seek to maximize the joint stiffness by maximizing total muscle activation or muscle force. These approaches have not sought to replicate human response, but rather to explore the possible effects of active muscle. Coactivation remains a challenging feature to include in musculoskeletal models, and may be improved by extracting optimization objective functions from experimental data. However, the components of such an objective function must be known before fitting to experimental data. This study explores the effect of components in several objective functions, in order to recommend components to be used for fitting to experimental data. Four novel approaches to modeling coactivation through optimization techniques are presented, two of which produce greater levels of stiffness than previous techniques. Simulations were performed using OpenSim and MATLAB cooperatively. Results show that maximizing the moment generated by a particular muscle appears analogous to maximizing joint stiffness. The approach of optimizing for maximum moment generated by individual muscles may be a good candidate for developing objective functions that accurately simulate muscle coactivation in complex joints. This new approach will be the focus of future studies with human subjects. Copyright © 2018 Elsevier Ltd. All rights reserved.

α7nAchR/NMDAR coupling affects NMDAR function and object recognition.

PubMed

Li, Shupeng; Nai, Qiang; Lipina, Tatiana V; Roder, John C; Liu, Fang

2013-12-20

The α7 nicotinic acetylcholine receptor (nAchR) and NMDA glutamate receptor (NMDAR) are both ligand-gated ion channels permeable to Ca2+ and Na+. Previous studies have demonstrated functional modulation of NMDARs by nAchRs, although the molecular mechanism remains largely unknown. We have previously reported that α7nAchR forms a protein complex with the NMDAR through a protein-protein interaction. We also developed an interfering peptide that is able to disrupt the α7nAchR-NMDAR complex and blocks cue-induced reinstatement of nicotine-seeking in rat models of relapse. In the present study, we investigated whether the α7nAchR-NMDAR interaction is responsible for the functional modulation of NMDAR by α7nAchR using both electrophysiological and behavioral tests. We have found that activation of α7nAchR upregulates NMDAR-mediated whole cell currents and LTP of mEPSC in cultured hippocampal neurons, which can be abolished by the interfering peptide that disrupts the α7nAchR-NMDAR interaction. Moreover, administration of the interfering peptide in mice impairs novel object recognition but not Morris water maze performance. Our results suggest that α7nAchR/NMDAR coupling may selectively affect some aspects of learning and memory.

Active printed materials for complex self-evolving deformations.

PubMed

Raviv, Dan; Zhao, Wei; McKnelly, Carrie; Papadopoulou, Athina; Kadambi, Achuta; Shi, Boxin; Hirsch, Shai; Dikovsky, Daniel; Zyracki, Michael; Olguin, Carlos; Raskar, Ramesh; Tibbits, Skylar

2014-12-18

We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus.

Active Printed Materials for Complex Self-Evolving Deformations

PubMed Central

Raviv, Dan; Zhao, Wei; McKnelly, Carrie; Papadopoulou, Athina; Kadambi, Achuta; Shi, Boxin; Hirsch, Shai; Dikovsky, Daniel; Zyracki, Michael; Olguin, Carlos; Raskar, Ramesh; Tibbits, Skylar

2014-01-01

We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus. PMID:25522053

On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions

DTIC Science & Technology

1994-01-01

torque general nature. We then provide in section 3 a precise at a particular joint of a robot arm , and x the set of an- statement of a specific...sampling Y according to first need to introduce some terminology and to define P(ylx). In the robot arm example described above, it a number of...mathematical objects. A summary of the would mean that one could move the robot arm into most common notations and definitions used in this pa- ’Note that

Object Segmentation Methods for Online Model Acquisition to Guide Robotic Grasping

NASA Astrophysics Data System (ADS)

Ignakov, Dmitri

A vision system is an integral component of many autonomous robots. It enables the robot to perform essential tasks such as mapping, localization, or path planning. A vision system also assists with guiding the robot's grasping and manipulation tasks. As an increased demand is placed on service robots to operate in uncontrolled environments, advanced vision systems must be created that can function effectively in visually complex and cluttered settings. This thesis presents the development of segmentation algorithms to assist in online model acquisition for guiding robotic manipulation tasks. Specifically, the focus is placed on localizing door handles to assist in robotic door opening, and on acquiring partial object models to guide robotic grasping. First, a method for localizing a door handle of unknown geometry based on a proposed 3D segmentation method is presented. Following segmentation, localization is performed by fitting a simple box model to the segmented handle. The proposed method functions without requiring assumptions about the appearance of the handle or the door, and without a geometric model of the handle. Next, an object segmentation algorithm is developed, which combines multiple appearance (intensity and texture) and geometric (depth and curvature) cues. The algorithm is able to segment objects without utilizing any a priori appearance or geometric information in visually complex and cluttered environments. The segmentation method is based on the Conditional Random Fields (CRF) framework, and the graph cuts energy minimization technique. A simple and efficient method for initializing the proposed algorithm which overcomes graph cuts' reliance on user interaction is also developed. Finally, an improved segmentation algorithm is developed which incorporates a distance metric learning (DML) step as a means of weighing various appearance and geometric segmentation cues, allowing the method to better adapt to the available data. The improved method also models the distribution of 3D points in space as a distribution of algebraic distances from an ellipsoid fitted to the object, improving the method's ability to predict which points are likely to belong to the object or the background. Experimental validation of all methods is performed. Each method is evaluated in a realistic setting, utilizing scenarios of various complexities. Experimental results have demonstrated the effectiveness of the handle localization method, and the object segmentation methods.

Object-oriented Persistent Homology

PubMed Central

Wang, Bao; Wei, Guo-Wei

2015-01-01

Persistent homology provides a new approach for the topological simplification of big data via measuring the life time of intrinsic topological features in a filtration process and has found its success in scientific and engineering applications. However, such a success is essentially limited to qualitative data classification and analysis. Indeed, persistent homology has rarely been employed for quantitative modeling and prediction. Additionally, the present persistent homology is a passive tool, rather than a proactive technique, for classification and analysis. In this work, we outline a general protocol to construct object-oriented persistent homology methods. By means of differential geometry theory of surfaces, we construct an objective functional, namely, a surface free energy defined on the data of interest. The minimization of the objective functional leads to a Laplace-Beltrami operator which generates a multiscale representation of the initial data and offers an objective oriented filtration process. The resulting differential geometry based object-oriented persistent homology is able to preserve desirable geometric features in the evolutionary filtration and enhances the corresponding topological persistence. The cubical complex based homology algorithm is employed in the present work to be compatible with the Cartesian representation of the Laplace-Beltrami flow. The proposed Laplace-Beltrami flow based persistent homology method is extensively validated. The consistence between Laplace-Beltrami flow based filtration and Euclidean distance based filtration is confirmed on the Vietoris-Rips complex for a large amount of numerical tests. The convergence and reliability of the present Laplace-Beltrami flow based cubical complex filtration approach are analyzed over various spatial and temporal mesh sizes. The Laplace-Beltrami flow based persistent homology approach is utilized to study the intrinsic topology of proteins and fullerene molecules. Based on a quantitative model which correlates the topological persistence of fullerene central cavity with the total curvature energy of the fullerene structure, the proposed method is used for the prediction of fullerene isomer stability. The efficiency and robustness of the present method are verified by more than 500 fullerene molecules. It is shown that the proposed persistent homology based quantitative model offers good predictions of total curvature energies for ten types of fullerene isomers. The present work offers the first example to design object-oriented persistent homology to enhance or preserve desirable features in the original data during the filtration process and then automatically detect or extract the corresponding topological traits from the data. PMID:26705370

Interpreting fMRI data: maps, modules and dimensions

PubMed Central

Op de Beeck, Hans P.; Haushofer, Johannes; Kanwisher, Nancy G.

2009-01-01

Neuroimaging research over the past decade has revealed a detailed picture of the functional organization of the human brain. Here we focus on two fundamental questions that are raised by the detailed mapping of sensory and cognitive functions and illustrate these questions with findings from the object-vision pathway. First, are functionally specific regions that are located close together best understood as distinct cortical modules or as parts of a larger-scale cortical map? Second, what functional properties define each cortical map or module? We propose a model in which overlapping continuous maps of simple features give rise to discrete modules that are selective for complex stimuli. PMID:18200027

An inherited immunoglobulin class-switch recombination deficiency associated with a defect in the INO80 chromatin remodeling complex

PubMed Central

Kracker, Sven; Di Virgilio, Michela; Schwartzentruber, Jeremy; Cuenin, Cyrille; Forveille, Monique; Deau, Marie-Céline; McBride, Kevin M.; Majewski, Jacek; Gazumyan, Anna; Seneviratne, Suranjith; Grimbacher, Bodo; Kutukculer, Necil; Herceg, Zdenko; Cavazzana, Marina; Jabado, Nada; Nussenzweig, Michel C.; Fischer, Alain; Durandy, Anne

2015-01-01

Background Immunoglobulin class-switch recombination defects (CSR-D) are rare primary immunodeficiencies characterized by impaired production of switched immunoglobulin isotypes and normal or elevated IgM levels. They are caused by impaired T:B cooperation or intrinsic B cell defects. However, many immunoglobulin CSR-Ds are still undefined at the molecular level. Objective This study's objective was to delineate new causes of immunoglobulin CSR-Ds and thus gain further insights into the process of immunoglobulin class-switch recombination (CSR). Methods Exome sequencing in 2 immunoglobulin CSR-D patients identified variations in the INO80 gene. Functional experiments were performed to assess the function of INO80 on immunoglobulin CSR. Results We identified recessive, nonsynonymous coding variations in the INO80 gene in 2 patients affected by defective immunoglobulin CSR. Expression of wild-type INO80 in patients' fibroblastic cells corrected their hypersensitivity to high doses of γ-irradiation. In murine CH12-F3 cells, the INO80 complex accumulates at Sα and Eμ regions of the IgH locus, and downregulation of INO80 as well as its partners Reptin and Pontin impaired CSR. In addition, Reptin and Pontin were shown to interact with activation-induced cytidine deaminase. Finally, an abnormal separation of sister chromatids was observed upon INO80 downregulation in CH12-F3 cells, pinpointing its role in cohesin activity. Conclusion INO80 deficiency appears to be associated with defective immunoglobulin CSR. We propose that the INO80 complex modulates cohesin function that may be required during immunoglobulin switch region synapsis. PMID:25312759

Exploration of complex visual feature spaces for object perception

PubMed Central

Leeds, Daniel D.; Pyles, John A.; Tarr, Michael J.

2014-01-01

The mid- and high-level visual properties supporting object perception in the ventral visual pathway are poorly understood. In the absence of well-specified theory, many groups have adopted a data-driven approach in which they progressively interrogate neural units to establish each unit's selectivity. Such methods are challenging in that they require search through a wide space of feature models and stimuli using a limited number of samples. To more rapidly identify higher-level features underlying human cortical object perception, we implemented a novel functional magnetic resonance imaging method in which visual stimuli are selected in real-time based on BOLD responses to recently shown stimuli. This work was inspired by earlier primate physiology work, in which neural selectivity for mid-level features in IT was characterized using a simple parametric approach (Hung et al., 2012). To extend such work to human neuroimaging, we used natural and synthetic object stimuli embedded in feature spaces constructed on the basis of the complex visual properties of the objects themselves. During fMRI scanning, we employed a real-time search method to control continuous stimulus selection within each image space. This search was designed to maximize neural responses across a pre-determined 1 cm3 brain region within ventral cortex. To assess the value of this method for understanding object encoding, we examined both the behavior of the method itself and the complex visual properties the method identified as reliably activating selected brain regions. We observed: (1) Regions selective for both holistic and component object features and for a variety of surface properties; (2) Object stimulus pairs near one another in feature space that produce responses at the opposite extremes of the measured activity range. Together, these results suggest that real-time fMRI methods may yield more widely informative measures of selectivity within the broad classes of visual features associated with cortical object representation. PMID:25309408

International Ultraviolet Explorer Observatory operations

NASA Technical Reports Server (NTRS)

1985-01-01

This volume contains the final report for the International Ultraviolet Explorer IUE Observatory Operations contract. The fundamental operational objective of the International Ultraviolet Explorer (IUE) program is to translate competitively selected observing programs into IUE observations, to reduce these observations into meaningful scientific data, and then to present these data to the Guest Observer in a form amenable to the pursuit of scientific research. The IUE Observatory is the key to this objective since it is the central control and support facility for all science operations functions within the IUE Project. In carrying out the operation of this facility, a number of complex functions were provided beginning with telescope scheduling and operation, proceeding to data processing, and ending with data distribution and scientific data analysis. In support of these critical-path functions, a number of other significant activities were also provided, including scientific instrument calibration, systems analysis, and software support. Routine activities have been summarized briefly whenever possible.

A Heuristic Bioinspired for 8-Piece Puzzle

NASA Astrophysics Data System (ADS)

Machado, M. O.; Fabres, P. A.; Melo, J. C. L.

2017-10-01

This paper investigates a mathematical model inspired by nature, and presents a Meta-Heuristic that is efficient in improving the performance of an informed search, when using strategy A * using a General Search Tree as data structure. The work hypothesis suggests that the investigated meta-heuristic is optimal in nature and may be promising in minimizing the computational resources required by an objective-based agent in solving high computational complexity problems (n-part puzzle) as well as In the optimization of objective functions for local search agents. The objective of this work is to describe qualitatively the characteristics and properties of the mathematical model investigated, correlating the main concepts of the A * function with the significant variables of the metaheuristic used. The article shows that the amount of memory required to perform this search when using the metaheuristic is less than using the A * function to evaluate the nodes of a general search tree for the eight-piece puzzle. It is concluded that the meta-heuristic must be parameterized according to the chosen heuristic and the level of the tree that contains the possible solutions to the chosen problem.

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed

O'Neill, M A; Hilgetag, C C

2001-08-29

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement.

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed Central

O'Neill, M A; Hilgetag, C C

2001-01-01

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement. PMID:11545702

Effect of fish gelatin-gum arabic interactions on structural and functional properties of concentrated emulsions.

PubMed

Anvari, Mohammad; Joyner Melito, Helen S

2017-12-01

Concentrated emulsions containing both proteins and polysaccharides are the basis for many commercial products; however, the effects of protein-polysaccharide interactions on the functional properties of these complex systems are often poorly understood from a fundamental standpoint. Hence, the objective of this study was to determine the effects of fish gelatin (FG)-gum arabic (GA) complexation at different aqueous phase pH (3.6, 5.0, and 9.0) on concentrated emulsion structure-function relationships. Concentrated emulsions were prepared using FG-GA mixtures and characterized by rheometry and confocal scanning laser microscopy (CSLM). CSLM images showed that all samples were O/W emulsions; emulsions with lower pH showed smaller oil droplets, greater homogeneity in size distribution, and higher stability. This was attributed to an increased number of FG-GA complexes in the emulsification. Electrostatic attractive interactions and charge neutralization created biopolymer associations with increased emulsification capacity. Samples with FG-GA mixtures at lower pH showed higher elastic moduli under small deformation and exhibited greater deviation between apparent and complex viscosities under the Cox-Merz rule, indicating increased gel network extension and greater intermolecular connectivity between adsorbed layers of adjacent oil droplets. These results can be used to incorporate protein-polysaccharide complexes as a suitable emulsifier in materials comprising concentrated emulsions. Copyright © 2017 Elsevier Ltd. All rights reserved.

3D Reasoning from Blocks to Stability.

PubMed

Zhaoyin Jia; Gallagher, Andrew C; Saxena, Ashutosh; Chen, Tsuhan

2015-05-01

Objects occupy physical space and obey physical laws. To truly understand a scene, we must reason about the space that objects in it occupy, and how each objects is supported stably by each other. In other words, we seek to understand which objects would, if moved, cause other objects to fall. This 3D volumetric reasoning is important for many scene understanding tasks, ranging from segmentation of objects to perception of a rich 3D, physically well-founded, interpretations of the scene. In this paper, we propose a new algorithm to parse a single RGB-D image with 3D block units while jointly reasoning about the segments, volumes, supporting relationships, and object stability. Our algorithm is based on the intuition that a good 3D representation of the scene is one that fits the depth data well, and is a stable, self-supporting arrangement of objects (i.e., one that does not topple). We design an energy function for representing the quality of the block representation based on these properties. Our algorithm fits 3D blocks to the depth values corresponding to image segments, and iteratively optimizes the energy function. Our proposed algorithm is the first to consider stability of objects in complex arrangements for reasoning about the underlying structure of the scene. Experimental results show that our stability-reasoning framework improves RGB-D segmentation and scene volumetric representation.

Relational and conjunctive binding functions dissociate in short-term memory.

PubMed

Parra, Mario A; Fabi, Katia; Luzzi, Simona; Cubelli, Roberto; Hernandez Valdez, Maria; Della Sala, Sergio

2015-02-01

Remembering complex events requires binding features within unified objects (conjunctions) and holding associations between objects (relations). Recent studies suggest that the two functions dissociate in long-term memory (LTM). Less is known about their functional organization in short-term memory (STM). The present study investigated this issue in patient AE affected by a stroke which caused damage to brain regions known to be relevant for relational functions both in LTM and in STM (i.e., the hippocampus). The assessment involved a battery of standard neuropsychological tasks and STM binding tasks. One STM binding task (Experiment 1) presented common objects and common colors forming either pairs (relations) or integrated objects (conjunctions). Free recall of relations or conjunctions was assessed. A second STM binding task used random polygons and non-primary colors instead (Experiment 2). Memory was assessed by selecting the features that made up the relations or the conjunctions from a set of single polygons and a set of single colors. The neuropsychological assessment revealed impaired delayed memory in AE. AE's pronounced relational STM binding deficits contrasted with his completely preserved conjunctive binding functions in both Experiments 1 and 2. Only 2.35% and 1.14% of the population were expected to have a discrepancy more extreme than that presented by AE in Experiments 1 and 2, respectively. Processing relations and conjunctions of very elementary nonspatial features in STM led to dissociating performances in AE. These findings may inform current theories of memory decline such as those linked to cognitive aging.

Cortical systems mediating visual attention to both objects and spatial locations

PubMed Central

Shomstein, Sarah; Behrmann, Marlene

2006-01-01

Natural visual scenes consist of many objects occupying a variety of spatial locations. Given that the plethora of information cannot be processed simultaneously, the multiplicity of inputs compete for representation. Using event-related functional MRI, we show that attention, the mechanism by which a subset of the input is selected, is mediated by the posterior parietal cortex (PPC). Of particular interest is that PPC activity is differentially sensitive to the object-based properties of the input, with enhanced activation for those locations bound by an attended object. Of great interest too is the ensuing modulation of activation in early cortical regions, reflected as differences in the temporal profile of the blood oxygenation level-dependent (BOLD) response for within-object versus between-object locations. These findings indicate that object-based selection results from an object-sensitive reorienting signal issued by the PPC. The dynamic circuit between the PPC and earlier sensory regions then enables observers to attend preferentially to objects of interest in complex scenes. PMID:16840559

Applying AN Object-Oriented Database Model to a Scientific Database Problem: Managing Experimental Data at Cebaf.

NASA Astrophysics Data System (ADS)

Ehlmann, Bryon K.

Current scientific experiments are often characterized by massive amounts of very complex data and the need for complex data analysis software. Object-oriented database (OODB) systems have the potential of improving the description of the structure and semantics of this data and of integrating the analysis software with the data. This dissertation results from research to enhance OODB functionality and methodology to support scientific databases (SDBs) and, more specifically, to support a nuclear physics experiments database for the Continuous Electron Beam Accelerator Facility (CEBAF). This research to date has identified a number of problems related to the practical application of OODB technology to the conceptual design of the CEBAF experiments database and other SDBs: the lack of a generally accepted OODB design methodology, the lack of a standard OODB model, the lack of a clear conceptual level in existing OODB models, and the limited support in existing OODB systems for many common object relationships inherent in SDBs. To address these problems, the dissertation describes an Object-Relationship Diagram (ORD) and an Object-oriented Database Definition Language (ODDL) that provide tools that allow SDB design and development to proceed systematically and independently of existing OODB systems. These tools define multi-level, conceptual data models for SDB design, which incorporate a simple notation for describing common types of relationships that occur in SDBs. ODDL allows these relationships and other desirable SDB capabilities to be supported by an extended OODB system. A conceptual model of the CEBAF experiments database is presented in terms of ORDs and the ODDL to demonstrate their functionality and use and provide a foundation for future development of experimental nuclear physics software using an OODB approach.

The Representation of Anatomical Structures through Computer Animation for Scientific, Educational and Artistic Applications.

ERIC Educational Resources Information Center

Stredney, Donald Larry

An overview of computer animation and the techniques involved in its creation is provided in the introduction to this masters thesis, which focuses on the problems encountered by students in learning the forms and functions of complex anatomical structures and ways in which computer animation can address these problems. The objectives for,…

Disturbance history and stand dynamics in secondary and old-growth forests of the Southern Appalachain Mountains, USA

Treesearch

Sarah M. Butler; Alan S. White; Katherine J. Elliott; Robert S. Seymour

2014-01-01

Understanding the patterns of past disturbance allows further insight into the complex composition, structure, and function of current and future forests, which is increasingly important in a world where disturbance characteristics are changing. Our objectives were to define disturbance causes, rates (percent disturbance per decade), magnitudes and frequency (time...

Functional Analysis and Treatment of Arranging and Ordering by Individuals with an Autism Spectrum Disorder

ERIC Educational Resources Information Center

Rodriguez, Nicole M.; Thompson, Rachel H.; Schlichenmeyer, Kevin; Stocco, Corey S.

2012-01-01

Of the diagnostic features of autism, relatively little research has been devoted to restricted and repetitive behavior, particularly topographically complex forms of restricted and repetitive behavior such as rigidity in routines or compulsive-like behavior (e.g., arranging objects in patterns or rows). Like vocal or motor stereotypy,…

Unveiling network-based functional features through integration of gene expression into protein networks.

PubMed

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Object-oriented design tools for supramolecular devices and biomedical nanotechnology.

PubMed

Lee, Stephen C; Bhalerao, Khaustaub; Ferrari, Mauro

2004-05-01

Nanotechnology provides multifunctional agents for in vivo use that increasingly blur the distinction between pharmaceuticals and medical devices. Realization of such therapeutic nanodevices requires multidisciplinary effort that is difficult for individual device developers to sustain, and identification of appropriate collaborations outside ones own field can itself be challenging. Further, as in vivo nanodevices become increasingly complex, their design will increasingly demand systems level thinking. System engineering tools such as object-oriented analysis, object-oriented design (OOA/D) and unified modeling language (UML) are applicable to nanodevices built from biological components, help logically manage the knowledge needed to design them, and help identify useful collaborative relationships for device designers. We demonstrate the utility of these systems engineering tools by reverse engineering an existing molecular device (the bacmid molecular cloning system) using them, and illustrate how object-oriented approaches identify fungible components (objects) in nanodevices in a way that facilitates design of families of related devices, rather than single inventions. We also explore the utility of object-oriented approaches for design of another class of therapeutic nanodevices, vaccines. While they are useful for design of current nanodevices, the power of systems design tools for biomedical nanotechnology will become increasingly apparent as the complexity and sophistication of in vivo nanosystems increases. The nested, hierarchical nature of object-oriented approaches allows treatment of devices as objects in higher-order structures, and so will facilitate concatenation of multiple devices into higher-order, higher-function nanosystems.

Rational Density Functional Selection Using Game Theory.

PubMed

McAnanama-Brereton, Suzanne; Waller, Mark P

2018-01-22

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

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Application of Adjoint Methodology to Supersonic Aircraft Design Using Reversed Equivalent Areas

NASA Technical Reports Server (NTRS)

Rallabhandi, Sriram K.

2013-01-01

This paper presents an approach to shape an aircraft to equivalent area based objectives using the discrete adjoint approach. Equivalent areas can be obtained either using reversed augmented Burgers equation or direct conversion of off-body pressures into equivalent area. Formal coupling with CFD allows computation of sensitivities of equivalent area objectives with respect to aircraft shape parameters. The exactness of the adjoint sensitivities is verified against derivatives obtained using the complex step approach. This methodology has the benefit of using designer-friendly equivalent areas in the shape design of low-boom aircraft. Shape optimization results with equivalent area cost functionals are discussed and further refined using ground loudness based objectives.

FIGENIX: Intelligent automation of genomic annotation: expertise integration in a new software platform

PubMed Central

Gouret, Philippe; Vitiello, Vérane; Balandraud, Nathalie; Gilles, André; Pontarotti, Pierre; Danchin, Etienne GJ

2005-01-01

Background Two of the main objectives of the genomic and post-genomic era are to structurally and functionally annotate genomes which consists of detecting genes' position and structure, and inferring their function (as well as of other features of genomes). Structural and functional annotation both require the complex chaining of numerous different software, algorithms and methods under the supervision of a biologist. The automation of these pipelines is necessary to manage huge amounts of data released by sequencing projects. Several pipelines already automate some of these complex chaining but still necessitate an important contribution of biologists for supervising and controlling the results at various steps. Results Here we propose an innovative automated platform, FIGENIX, which includes an expert system capable to substitute to human expertise at several key steps. FIGENIX currently automates complex pipelines of structural and functional annotation under the supervision of the expert system (which allows for example to make key decisions, check intermediate results or refine the dataset). The quality of the results produced by FIGENIX is comparable to those obtained by expert biologists with a drastic gain in terms of time costs and avoidance of errors due to the human manipulation of data. Conclusion The core engine and expert system of the FIGENIX platform currently handle complex annotation processes of broad interest for the genomic community. They could be easily adapted to new, or more specialized pipelines, such as for example the annotation of miRNAs, the classification of complex multigenic families, annotation of regulatory elements and other genomic features of interest. PMID:16083500

Cross-domain latent space projection for person re-identification

NASA Astrophysics Data System (ADS)

Pu, Nan; Wu, Song; Qian, Li; Xiao, Guoqiang

2018-04-01

In this paper, we research the problem of person re-identification and propose a cross-domain latent space projection (CDLSP) method to address the problems of the absence or insufficient labeled data in the target domain. Under the assumption that the visual features in the source domain and target domain share the similar geometric structure, we transform the visual features from source domain and target domain to a common latent space by optimizing the object function defined in the manifold alignment method. Moreover, the proposed object function takes into account the specific knowledge in the re-id with the aim to improve the performance of re-id under complex situations. Extensive experiments conducted on four benchmark datasets show the proposed CDLSP outperforms or is competitive with stateof- the-art methods for person re-identification.

Multi-objective optimization for model predictive control.

PubMed

Wojsznis, Willy; Mehta, Ashish; Wojsznis, Peter; Thiele, Dirk; Blevins, Terry

2007-06-01

This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC.

Embedded object concept: case balancing two-wheeled robot

NASA Astrophysics Data System (ADS)

Vallius, Tero; Röning, Juha

2007-09-01

This paper presents the Embedded Object Concept (EOC) and a telepresence robot system which is a test case for the EOC. The EOC utilizes common object-oriented methods used in software by applying them to combined Lego-like software-hardware entities. These entities represent objects in object-oriented design methods, and they are the building blocks of embedded systems. The goal of the EOC is to make the designing of embedded systems faster and easier. This concept enables people without comprehensive knowledge in electronics design to create new embedded systems, and for experts it shortens the design time of new embedded systems. We present the current status of a telepresence robot created with Atomi-objects, which is the name for our implementation of the embedded objects. The telepresence robot is a relatively complex test case for the EOC. The robot has been constructed using incremental device development, which is made possible by the architecture of the EOC. The robot contains video and audio exchange capability and a controlling system for driving with two wheels. The robot consists of Atomi-objects, demonstrating the suitability of the EOC for prototyping and easy modifications, and proving the capabilities of the EOC by realizing a function that normally requires a computer. The computer counterpart is a regular PC with audio and video capabilities running with a robot control application. The robot is functional and successfully tested.

Training in Goal-Oriented Attentional Self-Regulation Improves Executive Functioning in Veterans with Chronic TBI.

PubMed

Novakovic-Agopian, Tatjana; Kornblith, Erica S; Abrams, Gary; Burciaga-Rosales, Joaquin; Loya, Fred; D'Esposito, Mark; Chen, Anthony J-W

2018-05-02

Deficits in executive control functions are some of the most common and disabling consequences of both military and civilian brain injury. However, effective interventions are scant. The goal of this study was to assess whether cognitive rehabilitation training that was successfully applied in chronic civilian brain injury would be effective for military Veterans with TBI. In a prior study, participants with chronic acquired brain injury significantly improved after training in goal-oriented attentional self-regulation (GOALS) on measures of attention/executive function, functional task performance, and goal-directed control over neural processing on fMRI. The objective of this study was to assess effects of GOALS training in Veterans with chronic TBI. 33 Veterans with chronic TBI and executive difficulties in their daily life completed either five weeks of manualized Goal-Oriented Attentional Self-Regulation (GOALS) training or Brain-Health Education (BHE) matched in time and intensity. Evaluator-blinded assessments at baseline and post training included neuropsychological and complex functional task performance and self-report measures of emotional regulation. After GOALS, but not BHE training, participants significantly improved from baseline on primary outcome measures of: Overall Complex Attention/Executive Function composite neuropsychological performance score [F = 7.10, p =.01; partial 2 = .19], and on overall complex functional task performance (Goal Processing Scale Overall Performance) [F=6.92, p=.01, partial 2 =.20]. Additionally, post-GOALS participants indicated significant improvement on emotional regulation self-report measures [POMS Confusion Score F=6.05, p=.02, partial2=.20]. Training in attentional self-regulation applied to participant defined goals may improve cognitive functioning in Veterans with chronic TBI. Attention regulation training may not only impact executive control functioning in real world complex tasks, but may also improve emotional regulation and functioning. Implications for treatment of Veterans with TBI are discussed.

Collaborative activity between parietal and dorso-lateral prefrontal cortex in dynamic spatial working memory revealed by fMRI.

PubMed

Diwadkar, V A; Carpenter, P A; Just, M A

2000-07-01

Functional MRI was used to determine how the constituents of the cortical network subserving dynamic spatial working memory respond to two types of increases in task complexity. Participants mentally maintained the most recent location of either one or three objects as the three objects moved discretely in either a two- or three-dimensional array. Cortical activation in the dorsolateral prefrontal (DLPFC) and the parietal cortex increased as a function of the number of object locations to be maintained and the dimensionality of the display. An analysis of the response characteristics of the individual voxels showed that a large proportion were activated only when both the variables imposed the higher level of demand. A smaller proportion were activated specifically in response to increases in task demand associated with each of the independent variables. A second experiment revealed the same effect of dimensionality in the parietal cortex when the movement of objects was signaled auditorily rather than visually, indicating that the additional representational demands induced by 3-D space are independent of input modality. The comodulation of activation in the prefrontal and parietal areas by the amount of computational demand suggests that the collaboration between areas is a basic feature underlying much of the functionality of spatial working memory. Copyright 2000 Academic Press.

Overcoming Dynamic Disturbances in Imaging Systems

NASA Technical Reports Server (NTRS)

Young, Eric W.; Dente, Gregory C.; Lyon, Richard G.; Chesters, Dennis; Gong, Qian

2000-01-01

We develop and discuss a methodology with the potential to yield a significant reduction in complexity, cost, and risk of space-borne optical systems in the presence of dynamic disturbances. More robust systems almost certainly will be a result as well. Many future space-based and ground-based optical systems will employ optical control systems to enhance imaging performance. The goal of the optical control subsystem is to determine the wavefront aberrations and remove them. Ideally reducing an aberrated image of the object under investigation to a sufficiently clear (usually diffraction-limited) image. Control will likely be distributed over several elements. These elements may include telescope primary segments, telescope secondary, telescope tertiary, deformable mirror(s), fine steering mirror(s), etc. The last two elements, in particular, may have to provide dynamic control. These control subsystems may become elaborate indeed. But robust system performance will require evaluation of the image quality over a substantial range and in a dynamic environment. Candidate systems for improvement in the Earth Sciences Enterprise could include next generation Landsat systems or atmospheric sensors for dynamic imaging of individual, severe storms. The technology developed here could have a substantial impact on the development of new systems in the Space Science Enterprise; such as the Next Generation Space Telescope(NGST) and its follow-on the Next NGST. Large Interferometric Systems of non-zero field, such as Planet Finder and Submillimeter Probe of the Evolution of Cosmic Structure, could benefit. These systems most likely will contain large, flexible optomechanical structures subject to dynamic disturbance. Furthermore, large systems for high resolution imaging of planets or the sun from space may also benefit. Tactical and Strategic Defense systems will need to image very small targets as well and could benefit from the technology developed here. We discuss a novel speckle imaging technique with the potential to separate dynamic aberrations from static aberrations. Post-processing of a set of image data, using an algorithm based on this technique, should work for all but the lowest light levels and highest frequency dynamic environments. This technique may serve to reduce the complexity of the control system and provide for robust, fault-tolerant, reduced risk operation. For a given object, a short exposure image is "frozen" on the focal plane in the presence of the environmental disturbance (turbulence, jitter, etc.). A key factor is that this imaging data exhibits frame-to-frame linear shift invariance. Therefore, although the Point Spread Function is varying from frame to frame, the source is fixed; and each short exposure contains object spectrum data out to the diffraction limit of the imaging system. This novel speckle imaging technique uses the Knox-Thompson method. The magnitude of the complex object spectrum is straightforward to determine by well-established approaches. The phase of the complex object spectrum is decomposed into two parts. One is a single-valued function determined by the divergence of the optical phase gradient. The other is a multi-valued function determined by the circulation of the optical phase gradient-"hidden phase." Finite difference equations are developed for the phase. The novelty of this approach is captured in the inclusion of this "hidden phase." This technique allows the diffraction-limited reconstruction of the object from the ensemble of short exposure frames while simultaneously estimating the phase as a function of time from a set of exposures.

Overcoming Dynamic Disturbances in Imaging Systems

NASA Technical Reports Server (NTRS)

Young, Eric W.; Dente, Gregory C.; Lyon, Richard G.; Chesters, Dennis; Gong, Qian

2000-01-01

We develop and discuss a methodology with the potential to yield a significant reduction in complexity, cost, and risk of space-borne optical systems in the presence of dynamic disturbances. More robust systems almost certainly will be a result as well. Many future space-based and ground-based optical systems will employ optical control systems to enhance imaging performance. The goal of the optical control subsystem is to determine the wavefront aberrations and remove them. Ideally reducing an aberrated image of the object under investigation to a sufficiently clear (usually diffraction-limited) image. Control will likely be distributed over several elements. These elements may include telescope primary segments, telescope secondary, telescope tertiary, deformable mirror(s), fine steering mirror(s), etc. The last two elements, in particular, may have to provide dynamic control. These control subsystems may become elaborate indeed. But robust system performance will require evaluation of the image quality over a substantial range and in a dynamic environment. Candidate systems for improvement in the Earth Sciences Enterprise could include next generation Landsat systems or atmospheric sensors for dynamic imaging of individual, severe storms. The technology developed here could have a substantial impact on the development of new systems in the Space Science Enterprise; such as the Next Generation Space Telescope(NGST) and its follow-on the Next NGST. Large Interferometric Systems of non-zero field, such as Planet Finder and Submillimeter Probe of the Evolution of Cosmic Structure, could benefit. These systems most likely will contain large, flexible optormechanical structures subject to dynamic disturbance. Furthermore, large systems for high resolution imaging of planets or the sun from space may also benefit. Tactical and Strategic Defense systems will need to image very small targets as well and could benefit from the technology developed here. We discuss a novel speckle imaging technique with the potential to separate dynamic aberrations from static aberrations. Post-processing of a set of image data, using an algorithm based on this technique, should work for all but the lowest light levels and highest frequency dynamic environments. This technique may serve to reduce the complexity of the control system and provide for robust, fault-tolerant, reduced risk operation. For a given object, a short exposure image is "frozen" on the focal plane in the presence of the environmental disturbance (turbulence, jitter, etc.). A key factor is that this imaging data exhibits frame-to-frame linear shift invariance. Therefore, although the Point Spread Function is varying from frame to frame, the source is fixed; and each short exposure contains object spectrum data out to the diffraction limit of the imaging system. This novel speckle imaging technique uses the Knox-Thompson method. The magnitude of the complex object spectrum is straightforward to determine by well-established approaches. The phase of the complex object spectrum is decomposed into two parts. One is a single-valued function determined by the divergence of the optical phase gradient. The other is a multi-valued function determined by, the circulation of the optical phase gradient-"hidden phase." Finite difference equations are developed for the phase. The novelty of this approach is captured in the inclusion of this "hidden phase." This technique allows the diffraction-limited reconstruction of the object from the ensemble of short exposure frames while simultaneously estimating the phase as a function of time from a set of exposures.

Documentation of Functional Medication Management in Older Adults: A Retrospective Chart Review in Acute Care Hospitalization.

PubMed

Bolina, Monika; Jones, C Allyson; Koshman, Sheri; Heintz, Erin; Sadowski, Cheryl A

2016-12-01

Functional skills can affect the ability of older adults to appropriately manage their medication regimens. Research evaluating a patient's functional ability or the assessment of medication management is limited. Our objective was to describe the documented components of functional medication management (FMM) in adults aged ≥65 years during an acute hospital stay. The secondary objective was to describe the characteristics of the healthcare providers (HCP) who document FMM. This study was a retrospective chart review of a sample of patients aged ≥65 years admitted to medical units in a tertiary hospital from January 2013 to October 2014. FMM was defined as the steps required to take medications-including ordering, picking up, organizing, preparing, administering, and monitoring medications-and the functional abilities necessary to perform these tasks. The mean (standard deviation [SD]) age of patients was 78.9 (8.4) years; 72 (52 %) were female. Of the 190 charts screened, 140 were eligible for inclusion. The mean (SD) number of documented scheduled oral medications was eight (3.1) per patient, and 108 (77.1 %) charts contained documented FMM-related information. Commonly documented FMM components included whether the patient could administer medications independently (73 [52 %]) or schedule medication (46 [33 %]). These activities were most frequently documented by physicians (124 [39 %]) and occupational therapists (108 [34 %]). FMM assessments for older adult inpatients with multiple comorbidities and complex medication regimens were not documented comprehensively or frequently. Given the complexity of medication regimens and the functional skills required to manage medications at home, failing to document these assessments when evaluating patients in hospital reflects a lost opportunity.

Balancing Exploration, Uncertainty Representation and Computational Time in Many-Objective Reservoir Policy Optimization

NASA Astrophysics Data System (ADS)

Zatarain-Salazar, J.; Reed, P. M.; Quinn, J.; Giuliani, M.; Castelletti, A.

2016-12-01

As we confront the challenges of managing river basin systems with a large number of reservoirs and increasingly uncertain tradeoffs impacting their operations (due to, e.g. climate change, changing energy markets, population pressures, ecosystem services, etc.), evolutionary many-objective direct policy search (EMODPS) solution strategies will need to address the computational demands associated with simulating more uncertainties and therefore optimizing over increasingly noisy objective evaluations. Diagnostic assessments of state-of-the-art many-objective evolutionary algorithms (MOEAs) to support EMODPS have highlighted that search time (or number of function evaluations) and auto-adaptive search are key features for successful optimization. Furthermore, auto-adaptive MOEA search operators are themselves sensitive to having a sufficient number of function evaluations to learn successful strategies for exploring complex spaces and for escaping from local optima when stagnation is detected. Fortunately, recent parallel developments allow coordinated runs that enhance auto-adaptive algorithmic learning and can handle scalable and reliable search with limited wall-clock time, but at the expense of the total number of function evaluations. In this study, we analyze this tradeoff between parallel coordination and depth of search using different parallelization schemes of the Multi-Master Borg on a many-objective stochastic control problem. We also consider the tradeoff between better representing uncertainty in the stochastic optimization, and simplifying this representation to shorten the function evaluation time and allow for greater search. Our analysis focuses on the Lower Susquehanna River Basin (LSRB) system where multiple competing objectives for hydropower production, urban water supply, recreation and environmental flows need to be balanced. Our results provide guidance for balancing exploration, uncertainty, and computational demands when using the EMODPS framework to discover key tradeoffs within the LSRB system.

More than Memory Impairment in Voltage-Gated Potassium Channel Complex Encephalopathy

PubMed Central

Bettcher, Brianne M.; Gelfand, Jeffrey M.; Irani, Sarosh R.; Neuhaus, John; Forner, Sven; Hess, Christopher P.; Geschwind, Michael D.

2014-01-01

Objective Autoimmune encephalopathies (AE) are a heterogeneous group of neurological disorders that affect cognition. Although memory difficulties are commonly endorsed, few reports of AE inclusively assess all cognitive domains in detail. Our aim was to perform an unbiased cognitive evaluation of AE patients with voltage-gated potassium channel complex antibodies (VGKCC-Abs) in order to delineate cognitive strengths and weaknesses. Methods We assessed serial VGKCC-Abs AE subjects (n=12) with a comprehensive evaluation of memory, executive functions, visuospatial skills, and language. Clinical MRI (n=10/12) was evaluated. Five subjects had serial cognitive testing available, permitting descriptive analysis of change. Results Subjects demonstrated mild to moderate impairment in memory (mean Z=−1.9) and executive functions (mean Z=−1.5), with variable impairments in language and sparing of visuospatial skills. MRI findings showed T2 hyperintensities in medial temporal lobe (10/10) and basal ganglia (2/10). Serial cognitive examination revealed heterogeneity in cognitive function; whereas most patients improved in one or more domains, residual impairments were observed in some patients. Conclusions This study augments prior neuropsychological analyses in VGKCC-Ab AE by identifying not only memory and executive function deficits, but also language impairments, with preservation of visuospatial functioning. This study further highlights the importance of domain-specific testing to parse out the complex cognitive phenotypes of VGKCC-Ab AE. PMID:24981998

Structural optimization of large structural systems by optimality criteria methods

NASA Technical Reports Server (NTRS)

Berke, Laszlo

1992-01-01

The fundamental concepts of the optimality criteria method of structural optimization are presented. The effect of the separability properties of the objective and constraint functions on the optimality criteria expressions is emphasized. The single constraint case is treated first, followed by the multiple constraint case with a more complex evaluation of the Lagrange multipliers. Examples illustrate the efficiency of the method.

New Directions in Evaluating Social Problem Solving in Childhood: Early Precursors and Links to Adolescent Social Competence

ERIC Educational Resources Information Center

Landry, Susan H.; Smith, Karen E.; Swank, Paul R.

2009-01-01

A major objective of this chapter is to present a novel, ecologically sensitive social problem-solving task for school-aged children that captures the complexity of social and cognitive demands placed on children in naturalistic situations. Competence on this task correlates with a range of skills including executive functions, verbal reasoning,…

Women's Voices on Recovery: A Multi-Method Study of the Complexity of Recovery from Child Sexual Abuse

ERIC Educational Resources Information Center

Banyard, Victoria L.; Williams, Linda M.

2007-01-01

Objective: The current study was exploratory and used multiple methods to examine patterns of stability and change in resilient functioning across 7 years of early adulthood. Second, qualitative data were used to examine in greater detail survivors' own narratives about correlates of healing. Method: This study was longitudinal and used both…

White blood cell segmentation by circle detection using electromagnetism-like optimization.

PubMed

Cuevas, Erik; Oliva, Diego; Díaz, Margarita; Zaldivar, Daniel; Pérez-Cisneros, Marco; Pajares, Gonzalo

2013-01-01

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability.

White Blood Cell Segmentation by Circle Detection Using Electromagnetism-Like Optimization

PubMed Central

Oliva, Diego; Díaz, Margarita; Zaldivar, Daniel; Pérez-Cisneros, Marco; Pajares, Gonzalo

2013-01-01

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability. PMID:23476713

Robust active contour via additive local and global intensity information based on local entropy

NASA Astrophysics Data System (ADS)

Yuan, Shuai; Monkam, Patrice; Zhang, Feng; Luan, Fangjun; Koomson, Ben Alfred

2018-01-01

Active contour-based image segmentation can be a very challenging task due to many factors such as high intensity inhomogeneity, presence of noise, complex shape, weak boundaries objects, and dependence on the position of the initial contour. We propose a level set-based active contour method to segment complex shape objects from images corrupted by noise and high intensity inhomogeneity. The energy function of the proposed method results from combining the global intensity information and local intensity information with some regularization factors. First, the global intensity term is proposed based on a scheme formulation that considers two intensity values for each region instead of one, which outperforms the well-known Chan-Vese model in delineating the image information. Second, the local intensity term is formulated based on local entropy computed considering the distribution of the image brightness and using the generalized Gaussian distribution as the kernel function. Therefore, it can accurately handle high intensity inhomogeneity and noise. Moreover, our model is not dependent on the position occupied by the initial curve. Finally, extensive experiments using various images have been carried out to illustrate the performance of the proposed method.

Process Consistency in Models: the Importance of System Signatures, Expert Knowledge and Process Complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, Markus; Fovet, Ophelie; Ruiz, Laurent; Gascuel-Odoux, Chantal; Savenije, Hubert

2014-05-01

Hydrological models are frequently characterized by what is often considered to be adequate calibration performances. In many cases, however, these models experience a substantial uncertainty and performance decrease in validation periods, thus resulting in poor predictive power. Besides the likely presence of data errors, this observation can point towards wrong or insufficient representations of the underlying processes and their heterogeneity. In other words, right results are generated for the wrong reasons. Thus ways are sought to increase model consistency and to thereby satisfy the contrasting priorities of the need a) to increase model complexity and b) to limit model equifinality. In this study a stepwise model development approach is chosen to test the value of an exhaustive and systematic combined use of hydrological signatures, expert knowledge and readily available, yet anecdotal and rarely exploited, hydrological information for increasing model consistency towards generating the right answer for the right reasons. A simple 3-box, 7 parameter, conceptual HBV-type model, constrained by 4 calibration objective functions was able to adequately reproduce the hydrograph with comparatively high values for the 4 objective functions in the 5-year calibration period. However, closer inspection of the results showed a dramatic decrease of model performance in the 5-year validation period. In addition, assessing the model's skill to reproduce a range of 20 hydrological signatures including, amongst others, the flow duration curve, the autocorrelation function and the rising limb density, showed that it could not adequately reproduce the vast majority of these signatures, indicating a lack of model consistency. Subsequently model complexity was increased in a stepwise way to allow for more process heterogeneity. To limit model equifinality, increase in complexity was counter-balanced by a stepwise application of "realism constraints", inferred from expert knowledge (e.g. unsaturated storage capacity of hillslopes should exceed the one of wetlands) and anecdotal hydrological information (e.g. long-term estimates of actual evaporation obtained from the Budyko framework and long-term estimates of baseflow contribution) to ensure that the model is well behaved with respect to the modeller's perception of the system. A total of 11 model set-ups with increased complexity and an increased number of realism constraints was tested. It could be shown that in spite of largely unchanged calibration performance, compared to the simplest set-up, the most complex model set-up (12 parameters, 8 constraints) exhibited significantly increased performance in the validation period while uncertainty did not increase. In addition, the most complex model was characterized by a substantially increased skill to reproduce all 20 signatures, indicating a more suitable representation of the system. The results suggest that a model, "well" constrained by 4 calibration objective functions may still be an inadequate representation of the system and that increasing model complexity, if counter-balanced by realism constraints, can indeed increase predictive performance of a model and its skill to reproduce a range of hydrological signatures, but that it does not necessarily result in increased uncertainty. The results also strongly illustrate the need to move away from automated model calibration towards a more general expert-knowledge driven strategy of constraining models if a certain level of model consistency is to be achieved.

Spectrum analysis of radar life signal in the three kinds of theoretical models

NASA Astrophysics Data System (ADS)

Yang, X. F.; Ma, J. F.; Wang, D.

2017-02-01

In the single frequency continuous wave radar life detection system, based on the Doppler effect, the theory model of radar life signal is expressed by the real function, and there is a phenomenon that can't be confirmed by the experiment. When the phase generated by the distance between the measured object and the radar measuring head is л of integer times, the main frequency spectrum of life signal (respiration and heartbeat) is not existed in radar life signal. If this phase is л/2 of odd times, the main frequency spectrum of breath and heartbeat frequency is the strongest. In this paper, we use the Doppler effect as the basic theory, using three different mathematical expressions——real function, complex exponential function and Bessel's function expansion form. They are used to establish the theoretical model of radar life signal. Simulation analysis revealed that the Bessel expansion form theoretical model solve the problem of real function form. Compared with the theoretical model of the complex exponential function, the derived spectral line is greatly reduced in the theoretical model of Bessel expansion form, which is more consistent with the actual situation.

Binding of multiple features in memory by high-functioning adults with autism spectrum disorder.

PubMed

Bowler, Dermot M; Gaigg, Sebastian B; Gardiner, John M

2014-09-01

Diminished episodic memory and diminished use of semantic information to aid recall by individuals with autism spectrum disorder (ASD) are both thought to result from diminished relational binding of elements of complex stimuli. To test this hypothesis, we asked high-functioning adults with ASD and typical comparison participants to study grids in which some cells contained drawings of objects in non-canonical colours. Participants were told at study which features (colour, item, location) would be tested in a later memory test. In a second experiment, participants studied similar grids and were told that they would be tested on object-location or object-colour combinations. Recognition of combinations was significantly diminished in ASD, which survived covarying performance on the Color Trails Test (D'Elia et al. Color trails test. Professional manual. Psychological Assessment Resources, Lutz, 1996), a test of executive difficulties. The findings raise the possibility that medial temporal as well as frontal lobe processes are dysfunctional in ASD.

Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge

NASA Astrophysics Data System (ADS)

van Elk, Michiel; van Schie, Hein; Bekkering, Harold

2014-06-01

Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain.

Agent planning in AgScala

NASA Astrophysics Data System (ADS)

Tošić, Saša; Mitrović, Dejan; Ivanović, Mirjana

2013-10-01

Agent-oriented programming languages are designed to simplify the development of software agents, especially those that exhibit complex, intelligent behavior. This paper presents recent improvements of AgScala, an agent-oriented programming language based on Scala. AgScala includes declarative constructs for managing beliefs, actions and goals of intelligent agents. Combined with object-oriented and functional programming paradigms offered by Scala, it aims to be an efficient framework for developing both purely reactive, and more complex, deliberate agents. Instead of the Prolog back-end used initially, the new version of AgScala relies on Agent Planning Package, a more advanced system for automated planning and reasoning.

Algorithms and architectures for robot vision

NASA Technical Reports Server (NTRS)

Schenker, Paul S.

1990-01-01

The scope of the current work is to develop practical sensing implementations for robots operating in complex, partially unstructured environments. A focus in this work is to develop object models and estimation techniques which are specific to requirements of robot locomotion, approach and avoidance, and grasp and manipulation. Such problems have to date received limited attention in either computer or human vision - in essence, asking not only how perception is in general modeled, but also what is the functional purpose of its underlying representations. As in the past, researchers are drawing on ideas from both the psychological and machine vision literature. Of particular interest is the development 3-D shape and motion estimates for complex objects when given only partial and uncertain information and when such information is incrementally accrued over time. Current studies consider the use of surface motion, contour, and texture information, with the longer range goal of developing a fused sensing strategy based on these sources and others.

OpenFOAM: Open source CFD in research and industry

NASA Astrophysics Data System (ADS)

Jasak, Hrvoje

2009-12-01

The current focus of development in industrial Computational Fluid Dynamics (CFD) is integration of CFD into Computer-Aided product development, geometrical optimisation, robust design and similar. On the other hand, in CFD research aims to extend the boundaries ofpractical engineering use in "non-traditional " areas. Requirements of computational flexibility and code integration are contradictory: a change of coding paradigm, with object orientation, library components, equation mimicking is proposed as a way forward. This paper describes OpenFOAM, a C++ object oriented library for Computational Continuum Mechanics (CCM) developed by the author. Efficient and flexible implementation of complex physical models is achieved by mimicking the form ofpartial differential equation in software, with code functionality provided in library form. Open Source deployment and development model allows the user to achieve desired versatility in physical modeling without the sacrifice of complex geometry support and execution efficiency.

Triangular Alignment (TAME). A Tensor-based Approach for Higher-order Network Alignment

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

Mohammadi, Shahin; Gleich, David F.; Kolda, Tamara G.

2015-11-01

Network alignment is an important tool with extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the network alignment problem that extends topological similarity to higher-order structures and provide a new objective function that maximizes the number of aligned substructures. This objective function corresponds to an integer programming problem, which is NP-hard. Consequently, we approximate this objective function as a surrogate function whose maximization results in a tensor eigenvalue problem. Based on this formulation, we present an algorithm called Triangularmore » AlignMEnt (TAME), which attempts to maximize the number of aligned triangles across networks. We focus on alignment of triangles because of their enrichment in complex networks; however, our formulation and resulting algorithms can be applied to general motifs. Using a case study on the NAPABench dataset, we show that TAME is capable of producing alignments with up to 99% accuracy in terms of aligned nodes. We further evaluate our method by aligning yeast and human interactomes. Our results indicate that TAME outperforms the state-of-art alignment methods both in terms of biological and topological quality of the alignments.« less

Recognition Of Complex Three Dimensional Objects Using Three Dimensional Moment Invariants

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz A.

1985-01-01

A technique for the recognition of complex three dimensional objects is presented. The complex 3-D objects are represented in terms of their 3-D moment invariants, algebraic expressions that remain invariant independent of the 3-D objects' orientations and locations in the field of view. The technique of 3-D moment invariants has been used successfully for simple 3-D object recognition in the past. In this work we have extended this method for the representation of more complex objects. Two complex objects are represented digitally; their 3-D moment invariants have been calculated, and then the invariancy of these 3-D invariant moment expressions is verified by changing the orientation and the location of the objects in the field of view. The results of this study have significant impact on 3-D robotic vision, 3-D target recognition, scene analysis and artificial intelligence.

Forest, Trees, Dynamics: Results from a Novel Wisconsin Card Sorting Test Variant Protocol for Studying Global-Local Attention and Complex Cognitive Processes

PubMed Central

Cowley, Benjamin; Lukander, Kristian

2016-01-01

Background: Recognition of objects and their context relies heavily on the integrated functioning of global and local visual processing. In a realistic setting such as work, this processing becomes a sustained activity, implying a consequent interaction with executive functions. Motivation: There have been many studies of either global-local attention or executive functions; however it is relatively novel to combine these processes to study a more ecological form of attention. We aim to explore the phenomenon of global-local processing during a task requiring sustained attention and working memory. Methods: We develop and test a novel protocol for global-local dissociation, with task structure including phases of divided (“rule search”) and selective (“rule found”) attention, based on the Wisconsin Card Sorting Task (WCST). We test it in a laboratory study with 25 participants, and report on behavior measures (physiological data was also gathered, but not reported here). We develop novel stimuli with more naturalistic levels of information and noise, based primarily on face photographs, with consequently more ecological validity. Results: We report behavioral results indicating that sustained difficulty when participants test their hypotheses impacts matching-task performance, and diminishes the global precedence effect. Results also show a dissociation between subjectively experienced difficulty and objective dimension of performance, and establish the internal validity of the protocol. Contribution: We contribute an advance in the state of the art for testing global-local attention processes in concert with complex cognition. With three results we establish a connection between global-local dissociation and aspects of complex cognition. Our protocol also improves ecological validity and opens options for testing additional interactions in future work. PMID:26941689

Filtered Mass Density Function for Design Simulation of High Speed Airbreathing Propulsion Systems

NASA Technical Reports Server (NTRS)

Givi, P.; Madnia, C. K.; Gicquel, L. Y. M.; Sheikhi, M. R. H.; Drozda, T. G.

2002-01-01

The objective of this research is to improve and implement the filtered mass density function (FDF) methodology for large eddy simulation (LES) of high speed reacting turbulent flows. NASA is interested in the design of various components involved in air breathing propulsion systems such as the scramjet. There is a demand for development of robust tools that can aid in the design procedure. The physics of high speed reactive flows is rich with many complexities. LES is regarded as one of the most promising means of simulating turbulent reacting flows.

Identification and its vicissitudes.

PubMed

Etchegoyen, R H

1985-01-01

This paper attempts to understand the vicissitudes of identification within the co-ordinates of narcissism and the object relation. Firstly the dialectic pair primary identification/secondary identification are studied, and primary narcissism is suggested as the hypothesis which best explains them. The complex identification processes in the primary scene are considered next and the importance of the introjection of the oedipal parents for the formation of the superego is underlined. The importance of the structuring function of the introjection and projection mechanisms becomes embodied in the concept of projective identification, which comes to question the postulate of primary narcissism. The theory of projective-introjective identification is an extremely powerful instrument for explaining phenomena, however it obliges one to accept that the first introjections are radically different from the others. They have nothing to do with mourning but rather with primitive mechanisms which question the subject/object polarity and, so this author believes, spring basically from envy. Lastly, it is maintained that envy and libido are factors of a dialectic from which the object relation and the earliest processes of identification, previous to the Oedipus complex, proceed at one and the same time.

Object-oriented Tools for Distributed Computing

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1993-01-01

Distributed computing systems are proliferating, owing to the availability of powerful, affordable microcomputers and inexpensive communication networks. A critical problem in developing such systems is getting application programs to interact with one another across a computer network. Remote interprogram connectivity is particularly challenging across heterogeneous environments, where applications run on different kinds of computers and operating systems. NetWorks! (trademark) is an innovative software product that provides an object-oriented messaging solution to these problems. This paper describes the design and functionality of NetWorks! and illustrates how it is being used to build complex distributed applications for NASA and in the commercial sector.

Temperature-dependent and optimized thermal emission by spheres

NASA Astrophysics Data System (ADS)

Nguyen, K. L.; Merchiers, O.; Chapuis, P.-O.

2018-03-01

We investigate the temperature and size dependencies of thermal emission by homogeneous spheres as a function of their dielectric properties. Different power laws obtained in this work show that the emitted power can depart strongly from the usual fourth power of temperature given by Planck's law and from the square or the cube of the radius. We also show how to optimize the thermal emission by selecting permittivities leading to resonances, which allow for the so-called super-Planckian regime. These results will be useful as spheres, i.e. the simplest finite objects, are often considered as building blocks of more complex objects.

Risk-Based Object Oriented Testing

NASA Technical Reports Server (NTRS)

Rosenberg, Linda H.; Stapko, Ruth; Gallo, Albert

2000-01-01

Software testing is a well-defined phase of the software development life cycle. Functional ("black box") testing and structural ("white box") testing are two methods of test case design commonly used by software developers. A lesser known testing method is risk-based testing, which takes into account the probability of failure of a portion of code as determined by its complexity. For object oriented programs, a methodology is proposed for identification of risk-prone classes. Risk-based testing is a highly effective testing technique that can be used to find and fix the most important problems as quickly as possible.

Complex-Spectrum Magnetic Environment enhances and/or modifies Bioeffects of Hypokinetic Stress Condition: an Animal Study

NASA Astrophysics Data System (ADS)

Temuriantz, N. A.; Martinyuk, V. S.; Ptitsyna, N. G.; Villoresi, G.; Iucci, N.; Tyasto, M. I.; Dorman, L. I.

During last decades it was shown by many authors that ultra-low and extremely low frequency electric and magnetic fields ULF 0-10 Hz ELF 10-1000 Hz may produce biological effects and consequently may be a possible source for health problems Spaceflight electric and magnetic environments are characterized by complex combination of static and time-varying components in ULF-ELF range and by high variability The objective of this study was to investigate the possible influence of such magnetic fields on rats to understand the pathway regarding functional state of cardiovascular system Magnetic field MF pattern with variable complex spectra in 0-150 Hz frequency range was simulated using 3-axial Helmholtz coils and special computer-based equipment The effect of the real world MF exposure on rats was also tested in combination with hypokinetic stress condition which is typical for spaceflights It was revealed that variable complex-spectrum MF acts as a weak or moderate stress-like factor which amplifies and or modifies the functional shifts caused by other stress-factors The value and direction of the functional shifts caused by MF exposure significantly depend on gender individual-typological constitutional features and also on the physiological state norm stress of organism Our results support the idea that variable complex-spectrum MF action involves sympathetic activation overload in cholesterol transport in blood and also secretor activation of tissue basophyls mast cells that can influence the regional haemodynamics These

Multisensory object perception in infancy: 4-month-olds perceive a mistuned harmonic as a separate auditory and visual object

PubMed Central

A. Smith, Nicholas; A. Folland, Nicholas; Martinez, Diana M.; Trainor, Laurel J.

2017-01-01

Infants learn to use auditory and visual information to organize the sensory world into identifiable objects with particular locations. Here we use a behavioural method to examine infants' use of harmonicity cues to auditory object perception in a multisensory context. Sounds emitted by different objects sum in the air and the auditory system must figure out which parts of the complex waveform belong to different sources (auditory objects). One important cue to this source separation is that complex tones with pitch typically contain a fundamental frequency and harmonics at integer multiples of the fundamental. Consequently, adults hear a mistuned harmonic in a complex sound as a distinct auditory object (Alain et al., 2003). Previous work by our group demonstrated that 4-month-old infants are also sensitive to this cue. They behaviourally discriminate a complex tone with a mistuned harmonic from the same complex with in-tune harmonics, and show an object-related event-related potential (ERP) electrophysiological (EEG) response to the stimulus with mistuned harmonics. In the present study we use an audiovisual procedure to investigate whether infants perceive a complex tone with an 8% mistuned harmonic as emanating from two objects, rather than merely detecting the mistuned cue. We paired in-tune and mistuned complex tones with visual displays that contained either one or two bouncing balls. Four-month-old infants showed surprise at the incongruous pairings, looking longer at the display of two balls when paired with the in-tune complex and at the display of one ball when paired with the mistuned harmonic complex. We conclude that infants use harmonicity as a cue for source separation when integrating auditory and visual information in object perception. PMID:28346869

A mathematical function to evaluate surgical complexity of cleft lip and palate.

PubMed

Ortiz-Posadas, M R; Vega-Alvarado, L; Toni, B

2009-06-01

The objective of this work is to show the modeling of a similarity function adapted to the medical environment using the logical-combinatorial approach of pattern recognition theory, and its application comparing the condition of patients with congenital malformations in the lip and/or palate, which are called cleft-primary palate and/or cleft-secondary palate, respectively. The similarity function is defined by the comparison criteria determined for each variable, taking into account their type (qualitative or quantitative), their domain and their initial space representation. In all, we defined 18 variables, with their domains and six different comparison criteria (fuzzy and absolute difference type). The model includes, further, the importance of every variable as well as a weight which reflects the surgical complexity of the cleft. Likewise, the usefulness of this function is shown by calculating the similarity among three patients. This work was developed jointly with the Cleft Palate Team at the Reconstructive Surgery Service of the Pediatric Hospital of Tacubaya, which belongs to the Health Institute of the Federal District in Mexico City.

Visual short-term memory capacity for simple and complex objects.

PubMed

Luria, Roy; Sessa, Paola; Gotler, Alex; Jolicoeur, Pierre; Dell'Acqua, Roberto

2010-03-01

Does the capacity of visual short-term memory (VSTM) depend on the complexity of the objects represented in memory? Although some previous findings indicated lower capacity for more complex stimuli, other results suggest that complexity effects arise during retrieval (due to errors in the comparison process with what is in memory) that is not related to storage limitations of VSTM, per se. We used ERPs to track neuronal activity specifically related to retention in VSTM by measuring the sustained posterior contralateral negativity during a change detection task (which required detecting if an item was changed between a memory and a test array). The sustained posterior contralateral negativity, during the retention interval, was larger for complex objects than for simple objects, suggesting that neurons mediating VSTM needed to work harder to maintain more complex objects. This, in turn, is consistent with the view that VSTM capacity depends on complexity.

Evidence for a distributed hierarchy of action representation in the brain

PubMed Central

Grafton, Scott T.; de C. Hamilton, Antonia F.

2007-01-01

Complex human behavior is organized around temporally distal outcomes. Behavioral studies based on tasks such as normal prehension, multi-step object use and imitation establish the existence of relative hierarchies of motor control. The retrieval errors in apraxia also support the notion of a hierarchical model for representing action in the brain. In this review, three functional brain imaging studies of action observation using the method of repetition suppression are used to identify a putative neural architecture that supports action understanding at the level of kinematics, object centered goals and ultimately, motor outcomes. These results, based on observation, may match a similar functional anatomic hierarchy for action planning and execution. If this is true, then the findings support a functional anatomic model that is distributed across a set of interconnected brain areas that are differentially recruited for different aspects of goal oriented behavior, rather than a homogeneous mirror neuron system for organizing and understanding all behavior. PMID:17706312

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

Bioengineering Human Myocardium on Native Extracellular Matrix

PubMed Central

Guyette, Jacques P.; Charest, Jonathan M; Mills, Robert W; Jank, Bernhard J.; Moser, Philipp T.; Gilpin, Sarah E.; Gershlak, Joshua R.; Okamoto, Tatsuya; Gonzalez, Gabriel; Milan, David J.; Gaudette, Glenn R.; Ott, Harald C.

2015-01-01

Rationale More than 25 million individuals suffer from heart failure worldwide, with nearly 4,000 patients currently awaiting heart transplantation in the United States. Donor organ shortage and allograft rejection remain major limitations with only about 2,500 hearts transplanted each year. As a theoretical alternative to allotransplantation, patient-derived bioartificial myocardium could provide functional support and ultimately impact the treatment of heart failure. Objective The objective of this study is to translate previous work to human scale and clinically relevant cells, for the bioengineering of functional myocardial tissue based on the combination of human cardiac matrix and human iPS-derived cardiac myocytes. Methods and Results To provide a clinically relevant tissue scaffold, we translated perfusion-decellularization to human scale and obtained biocompatible human acellular cardiac scaffolds with preserved extracellular matrix composition, architecture, and perfusable coronary vasculature. We then repopulated this native human cardiac matrix with cardiac myocytes derived from non-transgenic human induced pluripotent stem cells (iPSCs) and generated tissues of increasing three-dimensional complexity. We maintained such cardiac tissue constructs in culture for 120 days to demonstrate definitive sarcomeric structure, cell and matrix deformation, contractile force, and electrical conduction. To show that functional myocardial tissue of human scale can be built on this platform, we then partially recellularized human whole heart scaffolds with human iPSC-derived cardiac myocytes. Under biomimetic culture, the seeded constructs developed force-generating human myocardial tissue, showed electrical conductivity, left ventricular pressure development, and metabolic function. Conclusions Native cardiac extracellular matrix scaffolds maintain matrix components and structure to support the seeding and engraftment of human iPS-derived cardiac myocytes, and enable the bioengineering of functional human myocardial-like tissue of multiple complexities. PMID:26503464

Knowledge Development Generic Framework Concept

DTIC Science & Technology

2008-12-18

requirements. The conceptual model serves as a communication interface among analysts, military staff, and other actors involved [22015] Systems Analysis will...It designates all long- lived basic mechanisms of material and institutional kind, which guarantee the functioning of a complex community . 2.2.3.2...cooperation with users) • Analyze and decide whether it is better to communicate an information object automatically (“document-to-people”) or via human

Programmable gradational micropatterning of functional materials using maskless lithography controlling absorption.

PubMed

Jung, Yushin; Lee, Howon; Park, Tae-Joon; Kim, Sungsik; Kwon, Sunghoon

2015-10-22

The demand for patterning functional materials precisely on surfaces of stimuli-responsive devices has increased in many research fields. In situ polymerization technology is one of the most convenient ways to place the functional materials on a desired location with micron-scale accuracy. To fabricate stimuli-responsive surfaces, controlling concentration of the functional material is much as important as micropatterning them. However, patterning and controlling concentration of the functional materials simultaneously requires an additional process, such as preparing multiple co-flow microfluidic structures and numbers of solutions with various concentrations. Despite applying these processes, fabricating heterogeneous patterns in large scale (millimeter scale) is still impossible. In this study, we propose an advanced in situ polymerization technique to pattern the surface in micron scale in a concentration-controlled manner. Because the concentration of the functional materials is manipulated by self-assembly on the surface, a complex pattern could be easily fabricated without any additional procedure. The complex pattern is pre-designed with absorption amount of the functional material, which is pre-determined by the duration of UV exposure. We show that the resolution reaches up to 2.5 μm and demonstrate mm-scale objects, maintaining the same resolution. We also fabricated Multi-bit barcoded micro particles verify the flexibility of our system.

Optimizing Functional Network Representation of Multivariate Time Series

NASA Astrophysics Data System (ADS)

Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; Pozo, Francisco Del; Menasalvas, Ernestina; Boccaletti, Stefano

2012-09-01

By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

Optimizing Functional Network Representation of Multivariate Time Series

PubMed Central

Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; Pozo, Francisco del; Menasalvas, Ernestina; Boccaletti, Stefano

2012-01-01

By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks. PMID:22953051

Interactions of Memory and Perception in Amnesia: The Figure–Ground Perspective

PubMed Central

Ngo, Joan K. W.; Hung, Lily H. T.; Peterson, Mary A.

2012-01-01

The medial temporal lobes (MTLs) have been thought to function exclusively in service of declarative memory. Recent research shows that damage to the perirhinal cortex (PRC) of the MTL impairs the discrimination of objects sharing many similar parts/features, leading to the hypothesis that the PRC contributes to the perception when the feature configurations, rather than the individual features, are required to solve the task. It remains uncertain, however, whether the previous research demands a slight extension of PRC function to include working memory or a more dramatic extension to include perception. We present 2 experiments assessing the implicit effects of familiar configuration on figure assignment, an early and fundamental perceptual outcome. Unlike controls, PRC-damaged individuals failed to perceive the regions portraying familiar configurations, as figure more often, than the regions comprising the same parts rearranged into novel configurations. They were also impaired in identifying the familiar objects. In a third experiment, PRC-damaged individuals performed poorly when asked to choose a familiar object from pairs of familiar and novel objects comprising the same parts. Our results demonstrate that the PRC is involved in both implicit and explicit perceptual discriminations of novel and familiar configurations. These results reveal that complex object representations in the PRC subserve both perception and memory. PMID:22172579

Interactions of memory and perception in amnesia: the figure-ground perspective.

PubMed

Barense, Morgan D; Ngo, Joan K W; Hung, Lily H T; Peterson, Mary A

2012-11-01

The medial temporal lobes (MTLs) have been thought to function exclusively in service of declarative memory. Recent research shows that damage to the perirhinal cortex (PRC) of the MTL impairs the discrimination of objects sharing many similar parts/features, leading to the hypothesis that the PRC contributes to the perception when the feature configurations, rather than the individual features, are required to solve the task. It remains uncertain, however, whether the previous research demands a slight extension of PRC function to include working memory or a more dramatic extension to include perception. We present 2 experiments assessing the implicit effects of familiar configuration on figure assignment, an early and fundamental perceptual outcome. Unlike controls, PRC-damaged individuals failed to perceive the regions portraying familiar configurations, as figure more often, than the regions comprising the same parts rearranged into novel configurations. They were also impaired in identifying the familiar objects. In a third experiment, PRC-damaged individuals performed poorly when asked to choose a familiar object from pairs of familiar and novel objects comprising the same parts. Our results demonstrate that the PRC is involved in both implicit and explicit perceptual discriminations of novel and familiar configurations. These results reveal that complex object representations in the PRC subserve both perception and memory.

Semantic attributes are encoded in human electrocorticographic signals during visual object recognition.

PubMed

Rupp, Kyle; Roos, Matthew; Milsap, Griffin; Caceres, Carlos; Ratto, Christopher; Chevillet, Mark; Crone, Nathan E; Wolmetz, Michael

2017-03-01

Non-invasive neuroimaging studies have shown that semantic category and attribute information are encoded in neural population activity. Electrocorticography (ECoG) offers several advantages over non-invasive approaches, but the degree to which semantic attribute information is encoded in ECoG responses is not known. We recorded ECoG while patients named objects from 12 semantic categories and then trained high-dimensional encoding models to map semantic attributes to spectral-temporal features of the task-related neural responses. Using these semantic attribute encoding models, untrained objects were decoded with accuracies comparable to whole-brain functional Magnetic Resonance Imaging (fMRI), and we observed that high-gamma activity (70-110Hz) at basal occipitotemporal electrodes was associated with specific semantic dimensions (manmade-animate, canonically large-small, and places-tools). Individual patient results were in close agreement with reports from other imaging modalities on the time course and functional organization of semantic processing along the ventral visual pathway during object recognition. The semantic attribute encoding model approach is critical for decoding objects absent from a training set, as well as for studying complex semantic encodings without artificially restricting stimuli to a small number of semantic categories. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Automated object-based classification of topography from SRTM data

PubMed Central

Drăguţ, Lucian; Eisank, Clemens

2012-01-01

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download. PMID:22485060

Automated object-based classification of topography from SRTM data

NASA Astrophysics Data System (ADS)

Drăguţ, Lucian; Eisank, Clemens

2012-03-01

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download.

Maximum entropy production, carbon assimilation, and the spatial organization of vegetation in river basins

PubMed Central

del Jesus, Manuel; Foti, Romano; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2012-01-01

The spatial organization of functional vegetation types in river basins is a major determinant of their runoff production, biodiversity, and ecosystem services. The optimization of different objective functions has been suggested to control the adaptive behavior of plants and ecosystems, often without a compelling justification. Maximum entropy production (MEP), rooted in thermodynamics principles, provides a tool to justify the choice of the objective function controlling vegetation organization. The application of MEP at the ecosystem scale results in maximum productivity (i.e., maximum canopy photosynthesis) as the thermodynamic limit toward which the organization of vegetation appears to evolve. Maximum productivity, which incorporates complex hydrologic feedbacks, allows us to reproduce the spatial macroscopic organization of functional types of vegetation in a thoroughly monitored river basin, without the need for a reductionist description of the underlying microscopic dynamics. The methodology incorporates the stochastic characteristics of precipitation and the associated soil moisture on a spatially disaggregated framework. Our results suggest that the spatial organization of functional vegetation types in river basins naturally evolves toward configurations corresponding to dynamically accessible local maxima of the maximum productivity of the ecosystem. PMID:23213227

Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge.

PubMed

van Elk, Michiel; van Schie, Hein; Bekkering, Harold

2014-06-01

Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain. Copyright © 2013 Elsevier B.V. All rights reserved.

Continuous motion scan ptychography: characterization for increased speed in coherent x-ray imaging

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

Deng, Junjing; Nashed, Youssef S. G.; Chen, Si

2015-01-01

Ptychography is a coherent diffraction imaging (CDI) method for extended objects in which diffraction patterns are acquired sequentially from overlapping coherent illumination spots. The object's complex transmission function can be reconstructed from those diffraction patterns at a spatial resolution limited only by the scattering strength of the object and the detector geometry. Most experiments to date have positioned the illumination spots on the sample using a move-settle-measure sequence in which the move and settle steps can take longer to complete than the measure step. We describe here the use of a continuous "fly-scan" mode for ptychographic data collection in whichmore » the sample is moved continuously, so that the experiment resembles one of integrating the diffraction patterns from multiple probe positions. This allows one to use multiple probe mode reconstruction methods to obtain an image of the object and also of the illumination function. We show in simulations, and in x-ray imaging experiments, some of the characteristics of fly-scan ptychography, including a factor of 25 reduction in the data acquisition time. This approach will become increasingly important as brighter x-ray sources are developed, such as diffraction limited storage rings.« less

Continuous motion scan ptychography: characterization for increased speed in coherent x-ray imaging.

PubMed

Deng, Junjing; Nashed, Youssef S G; Chen, Si; Phillips, Nicholas W; Peterka, Tom; Ross, Rob; Vogt, Stefan; Jacobsen, Chris; Vine, David J

2015-03-09

Ptychography is a coherent diffraction imaging (CDI) method for extended objects in which diffraction patterns are acquired sequentially from overlapping coherent illumination spots. The object's complex transmission function can be reconstructed from those diffraction patterns at a spatial resolution limited only by the scattering strength of the object and the detector geometry. Most experiments to date have positioned the illumination spots on the sample using a move-settle-measure sequence in which the move and settle steps can take longer to complete than the measure step. We describe here the use of a continuous "fly-scan" mode for ptychographic data collection in which the sample is moved continuously, so that the experiment resembles one of integrating the diffraction patterns from multiple probe positions. This allows one to use multiple probe mode reconstruction methods to obtain an image of the object and also of the illumination function. We show in simulations, and in x-ray imaging experiments, some of the characteristics of fly-scan ptychography, including a factor of 25 reduction in the data acquisition time. This approach will become increasingly important as brighter x-ray sources are developed, such as diffraction limited storage rings.

The importance of chemistry in creating well-defined nanoscopic embedded therapeutics: devices capable of the dual functions of imaging and therapy.

PubMed

Nyström, Andreas M; Wooley, Karen L

2011-10-18

Nanomedicine is a rapidly evolving field, for which polymer building blocks are proving useful for the construction of sophisticated devices that provide enhanced diagnostic imaging and treatment of disease, known as theranostics. These well-defined nanoscopic objects have high loading capacities, can protect embedded therapeutic cargo, and offer control over the conditions and rates of release. Theranostics also offer external surface area for the conjugation of ligands to impart stealth characteristics and/or direct their interactions with biological receptors and provide a framework for conjugation of imaging agents to track delivery to diseased site(s). The nanoscopic dimensions allow for extensive biological circulation. The incorporation of such multiple functions is complicated, requiring exquisite chemical control during production and rigorous characterization studies to confirm the compositions, structures, properties, and performance. We are particularly interested in the study of nanoscopic objects designed for treatment of lung infections and acute lung injury, urinary tract infections, and cancer. This Account highlights our work over several years to tune the assembly of unique nanostructures. We provide examples of how the composition, structure, dimensions, and morphology of theranostic devices can tune their performance as drug delivery agents for the treatment of infectious diseases and cancer. The evolution of nanostructured materials from relatively simple overall shapes and internal morphologies to those of increasing complexity is driving the development of synthetic methodologies for the preparation of increasingly complex nanomedicine devices. Our nanomedicine devices are derived from macromolecules that have well-defined compositions, structures, and topologies, which provide a framework for their programmed assembly into nanostructures with controlled sizes, shapes, and morphologies. The inclusion of functional units within selective compartments/domains allows us to create (multi)functional materials. We employ combinations of controlled radical and ring-opening polymerizations, chemical transformations, and supramolecular assembly to construct such materials as functional entities. The use of multifunctional monomers with selective polymerization chemistries affords regiochemically functionalized polymers. Further supramolecular assembly processes in water with further chemical transformations provide discrete nanoscopic objects within aqueous solutions. This approach echoes processes in nature, whereby small molecules (amino acids, nucleic acids, saccharides) are linked into polymers (proteins, DNA/RNA, polysaccharides, respectively) and then those polymers fold into three-dimensional conformations that can lead to nanoscopic functional entities.

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

NASA Astrophysics Data System (ADS)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

OLYMPEX Data Workshop: GPM View

NASA Technical Reports Server (NTRS)

Petersen, W.

2017-01-01

OLYMPEX Primary Objectives: Datasets to enable: (1) Direct validation over complex terrain at multiple scales, liquid and frozen precip types, (a) Do we capture terrain and synoptic regime transitions, orographic enhancements/structure, full range of precipitation intensity (e.g., very light to heavy) and types, spatial variability? (b) How well can we estimate space/time-accumulated precipitation over terrain (liquid + frozen)? (2) Physical validation of algorithms in mid-latitude cold season frontal systems over ocean and complex terrain, (a) What are the column properties of frozen, melting, liquid hydrometeors-their relative contributions to estimated surface precipitation, transition under the influence of terrain gradients, and systematic variability as a function of synoptic regime? (3) Integrated hydrologic validation in complex terrain, (a) Can satellite estimates be combined with modeling over complex topography to drive improved products (assimilation, downscaling) [Level IV products] (b) What are capabilities and limitations for use of satellite-based precipitation estimates in stream/river flow forecasting?

Observation of atmospheric time variation of Mira stars using Interferometry

NASA Astrophysics Data System (ADS)

Lacour, S.; Perrin, G.; Haubois, X.; Meimon, S.; Monnier, J.; Berger, J. P.; Traub, W.; Schuller, P.

2006-08-01

Interferometric data of Mira type stars in the near-infrared have already produce radial visibility curves with a shape far from simple limb darkening profile. The measured visibilities as a function of wavelength revealed the presence in K band of a close ( at a ~ 1 stellar radius distance above the photosphere ) molecular layer. However, thanks to the phase closure and telescope mobility of the IOTA interferometer, we have now access to the two dimensional complex visibility profile. We will present the u-v plane of different Mira stars at different epochs, and we will discuss the problems and advantages of analyzing complex objects in the Fourier domain.

Psychodynamic psychotherapy for complex trauma: targets, focus, applications, and outcomes

PubMed Central

Spermon, Deborah; Darlington, Yvonne; Gibney, Paul

2010-01-01

Complex trauma describes that category of severe, chronic interpersonal trauma usually originating in the formative years of a child. In the adult, this can result in global dissociative difficulties across areas of cognitive, affective, somatic, and behavioral functions. Targeting this field of traumatic pathology, this article reviews the contributions and developments within one broad approach: psychodynamic theory and practice. Brief descriptions of aspects of analytical, Jungian, relational, object relations, and attachment therapeutic approaches are given, along with understandings of pathology and the formulation of therapeutic goals. Major practices within client sessions are canvassed and the issues of researching treatment outcomes are discussed. PMID:22110335

Sci-Vis Framework

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

Arthur Bleeker, PNNL

2015-03-11

SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. The SVF framework handles much of the lifecycle and complex tasks required for a 3d visualization. Unlike a game framework SVF was designed to use fewer resources, work well in a windowed environment, and only render when necessary. The scene also takes advantage of multiple threads to free up the UI thread as much as possible. Shapes (actors) in the scene are created by adding or removing functionality (through support objects) during runtime. This allows a highly flexible and dynamic means of creating highlymore » complex actors without the code complexity (it also helps overcome the lack of multiple inheritance in Java.) All classes are highly customizable and there are abstract classes which are intended to be subclassed to allow a developer to create more complex and highly performant actors. There are multiple demos included in the framework to help the developer get started and shows off nearly all of the functionality. Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states« less

Some thoughts on the management of large, complex international space ventures

NASA Technical Reports Server (NTRS)

Lee, T. J.; Kutzer, Ants; Schneider, W. C.

1992-01-01

Management issues relevant to the development and deployment of large international space ventures are discussed with particular attention given to previous experience. Management approaches utilized in the past are labeled as either simple or complex, and signs of efficient management are examined. Simple approaches include those in which experiments and subsystems are developed for integration into spacecraft, and the Apollo-Soyuz Test Project is given as an example of a simple multinational approach. Complex approaches include those for ESA's Spacelab Project and the Space Station Freedom in which functional interfaces cross agency and political boundaries. It is concluded that individual elements of space programs should be managed by individual participating agencies, and overall configuration control is coordinated by level with a program director acting to manage overall objectives and project interfaces.

Enhancing Aesthetic Outcomes of Soft Tissue Coverage of the Hand

PubMed Central

Rehim, Shady A.; Kowalski, Evan; Chung, Kevin C.

2016-01-01

Hand aesthetics in general and aesthetic refinements of soft-tissue coverage of the hand in particular have been increasingly considered over the past few years. Advancements of microsurgery together with the traditional methods of tissue transfer have expanded the armamentarium of the reconstructive surgeon, thus shifting the reconstructive paradigm from simply ‘filling the defect’ to reconstructive refinement to provide the best functional and aesthetic results. However, drawing the boundary between what does and what does not constitute ‘aesthetic’ reconstruction of the hand is not straightforward. The selection amongst the vast amount of currently available reconstructive methods and the difficulties in objectively measuring or quantifying aesthetics has made this task complex and rather arbitrary. In this article we divide the hand into several units and subunits to simplify our understanding of the basic functional and aesthetic requirements of these regions that may ultimately bring order to complexity. PMID:25626826

Gravity induced wave function collapse

NASA Astrophysics Data System (ADS)

Gasbarri, G.; Toroš, M.; Donadi, S.; Bassi, A.

2017-11-01

Starting from an idea of S. L. Adler [in Quantum Nonlocality and Reality: 50 Years of Bell's Theorem, edited by M. Bell and S. Gao (Cambridge University Press, Cambridge, England 2016)], we develop a novel model of gravity induced spontaneous wave function collapse. The collapse is driven by complex stochastic fluctuations of the spacetime metric. After deriving the fundamental equations, we prove the collapse and amplification mechanism, the two most important features of a consistent collapse model. Under reasonable simplifying assumptions, we constrain the strength ξ of the complex metric fluctuations with available experimental data. We show that ξ ≥10-26 in order for the model to guarantee classicality of macro-objects, and at the same time ξ ≤10-20 in order not to contradict experimental evidence. As a comparison, in the recent discovery of gravitational waves in the frequency range 35 to 250 Hz, the (real) metric fluctuations reach a peak of ξ ˜10-21.

High fat, high sucrose diet causes cardiac mitochondrial dysfunction due in part to oxidative post-translational modification of mitochondrial complex II

PubMed Central

Sverdlov, Aaron L.; Elezaby, Aly; Behring, Jessica B.; Bachschmid, Markus M.; Luptak, Ivan; Tu, Vivian H.; Siwik, Deborah A.; Miller, Edward J.; Liesa, Marc; Shirihai, Orian S; Pimentel, David R.; Cohen, Richard A.; Colucci, Wilson S.

2014-01-01

Background Diet-induced obesity leads to metabolic heart disease (MHD) characterized by increased oxidative stress that may cause oxidative post-translational modifications (OPTM) of cardiac mitochondrial proteins. The functional consequences of OPTM of cardiac mitochondrial proteins in MHD are unknown. Our objective was to determine whether cardiac mitochondrial dysfunction in MHD due to diet-induced obesity is associated with cysteine OPTM. Methods and results Male C57Bl/6J mice were fed either a high-fat, high-sucrose (HFHS) or control diet for 8 months. Cardiac mitochondria from HFHS-fed mice (vs. control diet) had an increased rate of H2O2 production, a decreased GSH/GSSG ratio, a decreased rate of complex II substrate-driven ATP synthesis and decreased complex II activity. Complex II substrate-driven ATP synthesis and complex II activity were partially restored ex-vivo by reducing conditions. A biotin switch assay showed that HFHS feeding increased cysteine OPTM in complex II subunits A (SDHA) and B (SDHB). Using iodo-TMT multiplex tags we found that HFHS feeding is associated with reversible oxidation of cysteines 89 and 231 in SDHA, and 100, 103 and 115 in SDHB. Conclusions MHD due to consumption of a HFHS “Western” diet causes increased H2O2 production and oxidative stress in cardiac mitochondria associated with decreased ATP synthesis and decreased complex II activity. Impaired complex II activity and ATP production are associated with reversible cysteine OPTM of complex II. Possible sites of reversible cysteine OPTM in SDHA and SDHB were identified by iodo-TMT tag labeling. Mitochondrial ROS may contribute to the pathophysiology of MHD by impairing the function of complex II. PMID:25109264

Solving the inverse scattering problem in reflection-mode dynamic speckle-field phase microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhou, Renjie; So, Peter T. C.; Yaqoob, Zahid; Jin, Di; Hosseini, Poorya; Kuang, Cuifang; Singh, Vijay Raj; Kim, Yang-Hyo; Dasari, Ramachandra R.

2017-02-01

Most of the quantitative phase microscopy systems are unable to provide depth-resolved information for measuring complex biological structures. Optical diffraction tomography provides a non-trivial solution to it by 3D reconstructing the object with multiple measurements through different ways of realization. Previously, our lab developed a reflection-mode dynamic speckle-field phase microscopy (DSPM) technique, which can be used to perform depth resolved measurements in a single shot. Thus, this system is suitable for measuring dynamics in a layer of interest in the sample. DSPM can be also used for tomographic imaging, which promises to solve the long-existing "missing cone" problem in 3D imaging. However, the 3D imaging theory for this type of system has not been developed in the literature. Recently, we have developed an inverse scattering model to rigorously describe the imaging physics in DSPM. Our model is based on the diffraction tomography theory and the speckle statistics. Using our model, we first precisely calculated the defocus response and the depth resolution in our system. Then, we further calculated the 3D coherence transfer function to link the 3D object structural information with the axially scanned imaging data. From this transfer function, we found that in the reflection mode excellent sectioning effect exists in the low lateral spatial frequency region, thus allowing us to solve the "missing cone" problem. Currently, we are working on using this coherence transfer function to reconstruct layered structures and complex cells.

Aspect-Oriented Programming

NASA Technical Reports Server (NTRS)

Elrad, Tzilla (Editor); Filman, Robert E. (Editor); Bader, Atef (Editor)

2001-01-01

Computer science has experienced an evolution in programming languages and systems from the crude assembly and machine codes of the earliest computers through concepts such as formula translation, procedural programming, structured programming, functional programming, logic programming, and programming with abstract data types. Each of these steps in programming technology has advanced our ability to achieve clear separation of concerns at the source code level. Currently, the dominant programming paradigm is object-oriented programming - the idea that one builds a software system by decomposing a problem into objects and then writing the code of those objects. Such objects abstract together behavior and data into a single conceptual and physical entity. Object-orientation is reflected in the entire spectrum of current software development methodologies and tools - we have OO methodologies, analysis and design tools, and OO programming languages. Writing complex applications such as graphical user interfaces, operating systems, and distributed applications while maintaining comprehensible source code has been made possible with OOP. Success at developing simpler systems leads to aspirations for greater complexity. Object orientation is a clever idea, but has certain limitations. We are now seeing that many requirements do not decompose neatly into behavior centered on a single locus. Object technology has difficulty localizing concerns invoking global constraints and pandemic behaviors, appropriately segregating concerns, and applying domain-specific knowledge. Post-object programming (POP) mechanisms that look to increase the expressiveness of the OO paradigm are a fertile arena for current research. Examples of POP technologies include domain-specific languages, generative programming, generic programming, constraint languages, reflection and metaprogramming, feature-oriented development, views/viewpoints, and asynchronous message brokering. (Czarneclu and Eisenecker s book includes a good survey of many of these technologies).

Synthesis of Systemic Functional Theory & Dynamical Systems Theory for Socio-Cultural Modeling

DTIC Science & Technology

2011-01-26

is, language and other resources (e.g. images and sound resources) are conceptualised as inter-locking systems of meaning which realise four...hierarchical ranks and strata (e.g. sounds, word groups, clauses, and complex discourse structures in language, and elements, figures and episodes in images ...integrating platform for describing how language and other resources (e.g. images and sound) work together to fulfil particular objectives. While

Spatial relationship of biomass and species distribution in an old-growth Pseudotsuga Tsuga forest.

Treesearch

Jiquan Chen; Bo Song; Mark Rudnicki; Melinda Moeur; Ken Bible; Malcolm North; Dave C. Shaw; Jerry F. Franklin; Dave M. Braun

2003-01-01

Old-growth forests are known for their complex and variable structure and function. In a 12-ha plot (300 m x 400 m) of an old-growth Douglas-fir forest within the T.T. Munger Research Natural Area in southern Washington, we mapped and recorded live/dead condition, species, and diameter at breast height to address the following objectives: (1) to quantify the...

Broadband Impedance Microscopy for Research on Complex Quantum Materials

DTIC Science & Technology

2016-02-08

function in various materials. Figure 2. Sensitivity limit of the broadband impedance microscope (BIM). Figure 3. Preliminary BIM data on YMnO3...2 Statement of the Problem The objective of this DURIP award is to construct a broadband impedance microscope (BIM) for frequency-dependent...platforms and specialized cantilever probes [1] in the PI’s lab, the BIM can now simultaneously obtain microscopic (10 – 100 nm) and quasi- spectroscopic

Modeling of the structure-specific kinetics of abiotic, dark reduction of Hg(II) complexed by O/N and S functional groups in humic acids while accounting for time-dependent structural rearrangement

USDA-ARS?s Scientific Manuscript database

Redox transformations involving electron transfer from natural organic matter (NOM) are important for the mercury (Hg) biogeochemical cycle. In the water column light drives the reduction of Hg(II) to Hg(0), whereas in soils and sediments dark reduction of Hg(II) is of greater importance. The object...

Current audiological diagnostics

PubMed Central

Hoth, Sebastian; Baljić, Izet

2017-01-01

Today’s audiological functional diagnostics is based on a variety of hearing tests, whose large number takes account of the variety of malfunctions of a complex sensory organ system and the necessity to examine it in a differentiated manner and at any age of life. The objective is to identify nature and origin of the hearing loss and to quantify its extent as far as necessary to dispose of the information needed to initiate the adequate medical (conservative or operational) treatment or the provision with technical hearing aids or prostheses. Moreover, audiometry provides the basis for the assessment of impairment and handicap as well as for the calculation of the degree of disability. In the present overview, the current state of the method inventory available for practical use is described, starting from basic diagnostics over to complex special techniques. The presentation is systematically grouped in subjective procedures, based on psychoacoustic exploration, and objective methods, based on physical measurements: preliminary hearing tests, pure tone threshold, suprathreshold processing of sound intensity, directional hearing, speech understanding in quiet and in noise, dichotic hearing, tympanogram, acoustic reflex, otoacoustic emissions and auditory evoked potentials. Apart from a few still existing gaps, this method inventory covers the whole spectrum of all clinically relevant functional deficits of the auditory system. PMID:29279727

Model and algorithm for container ship stowage planning based on bin-packing problem

NASA Astrophysics Data System (ADS)

Zhang, Wei-Ying; Lin, Yan; Ji, Zhuo-Shang

2005-09-01

In a general case, container ship serves many different ports on each voyage. A stowage planning for container ship made at one port must take account of the influence on subsequent ports. So the complexity of stowage planning problem increases due to its multi-ports nature. This problem is NP-hard problem. In order to reduce the computational complexity, the problem is decomposed into two sub-problems in this paper. First, container ship stowage problem (CSSP) is regarded as “packing problem”, ship-bays on the board of vessel are regarded as bins, the number of slots at each bay are taken as capacities of bins, and containers with different characteristics (homogeneous containers group) are treated as items packed. At this stage, there are two objective functions, one is to minimize the number of bays packed by containers and the other is to minimize the number of overstows. Secondly, containers assigned to each bays at first stage are allocate to special slot, the objective functions are to minimize the metacentric height, heel and overstows. The taboo search heuristics algorithm are used to solve the subproblem. The main focus of this paper is on the first subproblem. A case certifies the feasibility of the model and algorithm.

Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database.

PubMed

Wang, Shur-Jen; Laulederkind, Stanley J F; Hayman, G Thomas; Petri, Victoria; Smith, Jennifer R; Tutaj, Marek; Nigam, Rajni; Dwinell, Melinda R; Shimoyama, Mary

2016-08-01

Cardiovascular diseases are complex diseases caused by a combination of genetic and environmental factors. To facilitate progress in complex disease research, the Rat Genome Database (RGD) provides the community with a disease portal where genome objects and biological data related to cardiovascular diseases are systematically organized. The purpose of this study is to present biocuration at RGD, including disease, genetic, and pathway data. The RGD curation team uses controlled vocabularies/ontologies to organize data curated from the published literature or imported from disease and pathway databases. These organized annotations are associated with genes, strains, and quantitative trait loci (QTLs), thus linking functional annotations to genome objects. Screen shots from the web pages are used to demonstrate the organization of annotations at RGD. The human cardiovascular disease genes identified by annotations were grouped according to data sources and their annotation profiles were compared by in-house tools and other enrichment tools available to the public. The analysis results show that the imported cardiovascular disease genes from ClinVar and OMIM are functionally different from the RGD manually curated genes in terms of pathway and Gene Ontology annotations. The inclusion of disease genes from other databases enriches the collection of disease genes not only in quantity but also in quality. Copyright © 2016 the American Physiological Society.

Free-form geometric modeling by integrating parametric and implicit PDEs.

PubMed

Du, Haixia; Qin, Hong

2007-01-01

Parametric PDE techniques, which use partial differential equations (PDEs) defined over a 2D or 3D parametric domain to model graphical objects and processes, can unify geometric attributes and functional constraints of the models. PDEs can also model implicit shapes defined by level sets of scalar intensity fields. In this paper, we present an approach that integrates parametric and implicit trivariate PDEs to define geometric solid models containing both geometric information and intensity distribution subject to flexible boundary conditions. The integrated formulation of second-order or fourth-order elliptic PDEs permits designers to manipulate PDE objects of complex geometry and/or arbitrary topology through direct sculpting and free-form modeling. We developed a PDE-based geometric modeling system for shape design and manipulation of PDE objects. The integration of implicit PDEs with parametric geometry offers more general and arbitrary shape blending and free-form modeling for objects with intensity attributes than pure geometric models.

Altering the orientation of a fused protein to the RNA-binding ribosomal protein L7Ae and its derivatives through circular permutation.

PubMed

Ohuchi, Shoji J; Sagawa, Fumihiko; Sakamoto, Taiichi; Inoue, Tan

2015-10-23

RNA-protein complexes (RNPs) are useful for constructing functional nano-objects because a variety of functional proteins can be displayed on a designed RNA scaffold. Here, we report circular permutations of an RNA-binding protein L7Ae based on the three-dimensional structure information to alter the orientation of the displayed proteins on the RNA scaffold. An electrophoretic mobility shift assay and atomic force microscopy (AFM) analysis revealed that most of the designed circular permutants formed an RNP nano-object. Moreover, the alteration of the enhanced green fluorescent protein (EGFP) orientation was confirmed with AFM by employing EGFP on the L7Ae permutant on the RNA. The results demonstrate that targeted fine-tuning of the stereo-specific fixation of a protein on a protein-binding RNA is feasible by using the circular permutation technique. Copyright © 2015 Elsevier Inc. All rights reserved.

Identifying multiple influential spreaders based on generalized closeness centrality

NASA Astrophysics Data System (ADS)

Liu, Huan-Li; Ma, Chuang; Xiang, Bing-Bing; Tang, Ming; Zhang, Hai-Feng

2018-02-01

To maximize the spreading influence of multiple spreaders in complex networks, one important fact cannot be ignored: the multiple spreaders should be dispersively distributed in networks, which can effectively reduce the redundance of information spreading. For this purpose, we define a generalized closeness centrality (GCC) index by generalizing the closeness centrality index to a set of nodes. The problem converts to how to identify multiple spreaders such that an objective function has the minimal value. By comparing with the K-means clustering algorithm, we find that the optimization problem is very similar to the problem of minimizing the objective function in the K-means method. Therefore, how to find multiple nodes with the highest GCC value can be approximately solved by the K-means method. Two typical transmission dynamics-epidemic spreading process and rumor spreading process are implemented in real networks to verify the good performance of our proposed method.

Identifying thematic roles from neural representations measured by functional magnetic resonance imaging.

PubMed

Wang, Jing; Cherkassky, Vladimir L; Yang, Ying; Chang, Kai-Min Kevin; Vargas, Robert; Diana, Nicholas; Just, Marcel Adam

2016-01-01

The generativity and complexity of human thought stem in large part from the ability to represent relations among concepts and form propositions. The current study reveals how a given object such as rabbit is neurally encoded differently and identifiably depending on whether it is an agent ("the rabbit punches the monkey") or a patient ("the monkey punches the rabbit"). Machine-learning classifiers were trained on functional magnetic resonance imaging (fMRI) data evoked by a set of short videos that conveyed agent-verb-patient propositions. When tested on a held-out video, the classifiers were able to reliably identify the thematic role of an object from its associated fMRI activation pattern. Moreover, when trained on one subset of the study participants, classifiers reliably identified the thematic roles in the data of a left-out participant (mean accuracy = .66), indicating that the neural representations of thematic roles were common across individuals.

Altering the orientation of a fused protein to the RNA-binding ribosomal protein L7Ae and its derivatives through circular permutation

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

Ohuchi, Shoji J.; Sagawa, Fumihiko; Sakamoto, Taiichi

RNA-protein complexes (RNPs) are useful for constructing functional nano-objects because a variety of functional proteins can be displayed on a designed RNA scaffold. Here, we report circular permutations of an RNA-binding protein L7Ae based on the three-dimensional structure information to alter the orientation of the displayed proteins on the RNA scaffold. An electrophoretic mobility shift assay and atomic force microscopy (AFM) analysis revealed that most of the designed circular permutants formed an RNP nano-object. Moreover, the alteration of the enhanced green fluorescent protein (EGFP) orientation was confirmed with AFM by employing EGFP on the L7Ae permutant on the RNA. Themore » results demonstrate that targeted fine-tuning of the stereo-specific fixation of a protein on a protein-binding RNA is feasible by using the circular permutation technique.« less

Jealousy in dogs.

PubMed

Harris, Christine R; Prouvost, Caroline

2014-01-01

It is commonly assumed that jealousy is unique to humans, partially because of the complex cognitions often involved in this emotion. However, from a functional perspective, one might expect that an emotion that evolved to protect social bonds from interlopers might exist in other social species, particularly one as cognitively sophisticated as the dog. The current experiment adapted a paradigm from human infant studies to examine jealousy in domestic dogs. We found that dogs exhibited significantly more jealous behaviors (e.g., snapping, getting between the owner and object, pushing/touching the object/owner) when their owners displayed affectionate behaviors towards what appeared to be another dog as compared to nonsocial objects. These results lend support to the hypothesis that jealousy has some "primordial" form that exists in human infants and in at least one other social species besides humans.

Complex Pupil Masks for Aberrated Imaging of Closely Spaced Objects

NASA Astrophysics Data System (ADS)

Reddy, A. N. K.; Sagar, D. K.; Khonina, S. N.

2017-12-01

Current approach demonstrates the suppression of optical side-lobes and the contraction of the main lobe in the composite image of two object points of the optical system under the influence of defocusing effect when an asymmetric phase edges are imposed over the apodized circular aperture. The resolution of two point sources having different intensity ratio is discussed in terms of the modified Sparrow criterion, functions of the degree of coherence of the illumination, the intensity difference and the degree of asymmetric phase masking. Here we have introduced and explored the effects of focus aberration (defect-of-focus) on the two-point resolution of the optical systems. Results on the aberrated composite image of closely spaced objects with amplitude mask and asymmetric phase masks forms a significant contribution in astronomical and microscopic observations.

An fMRI Study of Episodic Memory: Retrieval of Object, Spatial, and Temporal Information

PubMed Central

Hayes, Scott M.; Ryan, Lee; Schnyer, David M.; Nadel, Lynn

2011-01-01

Sixteen participants viewed a videotaped tour of 4 houses, highlighting a series of objects and their spatial locations. Participants were tested for memory of object, spatial, and temporal order information while undergoing functional Magnetic Resonance Imaging. Preferential activation was observed in right parahippocampal gyrus during the retrieval of spatial location information. Retrieval of contextual information (spatial location and temporal order) was associated with activation in right dorsolateral prefrontal cortex. In bilateral posterior parietal regions, greater activation was associated with processing of visual scenes, regardless of the memory judgment. These findings support current theories positing roles for frontal and medial temporal regions during episodic retrieval and suggest a specific role for the hippocampal complex in the retrieval of spatial location information PMID:15506871

Advances in the quantification of mitochondrial function in primary human immune cells through extracellular flux analysis.

PubMed

Nicholas, Dequina; Proctor, Elizabeth A; Raval, Forum M; Ip, Blanche C; Habib, Chloe; Ritou, Eleni; Grammatopoulos, Tom N; Steenkamp, Devin; Dooms, Hans; Apovian, Caroline M; Lauffenburger, Douglas A; Nikolajczyk, Barbara S

2017-01-01

Numerous studies show that mitochondrial energy generation determines the effectiveness of immune responses. Furthermore, changes in mitochondrial function may regulate lymphocyte function in inflammatory diseases like type 2 diabetes. Analysis of lymphocyte mitochondrial function has been facilitated by introduction of 96-well format extracellular flux (XF96) analyzers, but the technology remains imperfect for analysis of human lymphocytes. Limitations in XF technology include the lack of practical protocols for analysis of archived human cells, and inadequate data analysis tools that require manual quality checks. Current analysis tools for XF outcomes are also unable to automatically assess data quality and delete untenable data from the relatively high number of biological replicates needed to power complex human cell studies. The objectives of work presented herein are to test the impact of common cellular manipulations on XF outcomes, and to develop and validate a new automated tool that objectively analyzes a virtually unlimited number of samples to quantitate mitochondrial function in immune cells. We present significant improvements on previous XF analyses of primary human cells that will be absolutely essential to test the prediction that changes in immune cell mitochondrial function and fuel sources support immune dysfunction in chronic inflammatory diseases like type 2 diabetes.

Shape and color conjunction stimuli are represented as bound objects in visual working memory.

PubMed

Luria, Roy; Vogel, Edward K

2011-05-01

The integrated object view of visual working memory (WM) argues that objects (rather than features) are the building block of visual WM, so that adding an extra feature to an object does not result in any extra cost to WM capacity. Alternative views have shown that complex objects consume additional WM storage capacity so that it may not be represented as bound objects. Additionally, it was argued that two features from the same dimension (i.e., color-color) do not form an integrated object in visual WM. This led some to argue for a "weak" object view of visual WM. We used the contralateral delay activity (the CDA) as an electrophysiological marker of WM capacity, to test those alternative hypotheses to the integrated object account. In two experiments we presented complex stimuli and color-color conjunction stimuli, and compared performance in displays that had one object but varying degrees of feature complexity. The results supported the integrated object account by showing that the CDA amplitude corresponded to the number of objects regardless of the number of features within each object, even for complex objects or color-color conjunction stimuli. Copyright © 2010 Elsevier Ltd. All rights reserved.

Differential binding of colors to objects in memory: red and yellow stick better than blue and green.

PubMed

Kuhbandner, Christof; Spitzer, Bernhard; Lichtenfeld, Stephanie; Pekrun, Reinhard

2015-01-01

Both evolutionary considerations and recent research suggest that the color red serves as a signal indicating an object's importance. However, until now, there is no evidence that this signaling function of red is also reflected in human memory. To examine the effect of red on memory, we conducted four experiments in which we presented objects colored in four different colors (red, green, blue, and yellow) and measured later memory for the presence of an object and for the color of an object. Across experiments, we varied the type of objects (words vs. pictures), task complexity (single objects vs. multiple objects in visual scenes), and intentionality of encoding (intentional vs. incidental learning). Memory for the presence of an object was not influenced by color. However, in all four experiments, memory for the color of an object depended on color type and was particularly high for red and yellow-colored objects and particularly low for green-colored objects, indicating that the binding of colors into object memory representations varies as a function of color type. Analyzing the observers' confidence in their color memories revealed that color not only influenced objective memory performance but also subjective confidence. Subjective confidence judgments differentiated well between correct and incorrect color memories for red-colored objects, but poorly for green-colored objects. Our findings reveal a previously unknown color effect which may be of considerable interest for both basic color research and applied settings like eyewitness testimony in which memory for color features is relevant. Furthermore, our results indicate that feature binding in memory is not a uniform process by which any attended feature is automatically bound into unitary memory representations. Rather, memory binding seems to vary across different subtypes of features, a finding that supports recent research showing that object features are stored in memory rather independently from each other.

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos

2013-09-05

The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomassmore » transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.« less

Human brain regions involved in recognizing environmental sounds.

PubMed

Lewis, James W; Wightman, Frederic L; Brefczynski, Julie A; Phinney, Raymond E; Binder, Jeffrey R; DeYoe, Edgar A

2004-09-01

To identify the brain regions preferentially involved in environmental sound recognition (comprising portions of a putative auditory 'what' pathway), we collected functional imaging data while listeners attended to a wide range of sounds, including those produced by tools, animals, liquids and dropped objects. These recognizable sounds, in contrast to unrecognizable, temporally reversed control sounds, evoked activity in a distributed network of brain regions previously associated with semantic processing, located predominantly in the left hemisphere, but also included strong bilateral activity in posterior portions of the middle temporal gyri (pMTG). Comparisons with earlier studies suggest that these bilateral pMTG foci partially overlap cortex implicated in high-level visual processing of complex biological motion and recognition of tools and other artifacts. We propose that the pMTG foci process multimodal (or supramodal) information about objects and object-associated motion, and that this may represent 'action' knowledge that can be recruited for purposes of recognition of familiar environmental sound-sources. These data also provide a functional and anatomical explanation for the symptoms of pure auditory agnosia for environmental sounds reported in human lesion studies.

Assessing visual function in children with complex disabilities: the Bradford visual function box.

PubMed

Pilling, Rachel F; Outhwaite, Louise; Bruce, Alison

2016-08-01

Assessment of children with complex and severe learning disabilities is challenging and the children may not respond to the monochrome stimuli of traditional tests. The International Association of Scientific Studies on Intellectual Disability recommends that visual function assessment in poorly or non-cooperative children should be undertaken in an objective manner. We have developed a functional visual assessment tool to assess vision in children with complex and multiple disabilities. The Bradford visual function box (BVFB) comprises a selection of items (small toys) of different size and colour, which are presented to the child and the response observed. The aim of this study is to establish its intertester validity in children with severe learning disability. The visual function of 22 children with severe learning disability was assessed using the BVFB. The children were assessed by experienced practitioners on two separate occasions. The assessors were unaware of each other's findings. In 15/22 of the children, no difference was found in the results of the two assessors. The test was shown to have a good intertester agreement, weighted κ=0.768. The results of this clinical study show that the BVFB is a reliable tool for assessing the visual function in children with severe learning disability in whom other tests fail to elicit a response. The need for a tool which is quick to administer and portable has previously been highlighted. The BVFB offers an option for children for whom other formal tests are unsuccessful in eliciting a response. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex.

PubMed Central

Malach, R; Reppas, J B; Benson, R R; Kwong, K K; Jiang, H; Kennedy, W A; Ledden, P J; Brady, T J; Rosen, B R; Tootell, R B

1995-01-01

The stages of integration leading from local feature analysis to object recognition were explored in human visual cortex by using the technique of functional magnetic resonance imaging. Here we report evidence for object-related activation. Such activation was located at the lateral-posterior aspect of the occipital lobe, just abutting the posterior aspect of the motion-sensitive area MT/V5, in a region termed the lateral occipital complex (LO). LO showed preferential activation to images of objects, compared to a wide range of texture patterns. This activation was not caused by a global difference in the Fourier spatial frequency content of objects versus texture images, since object images produced enhanced LO activation compared to textures matched in power spectra but randomized in phase. The preferential activation to objects also could not be explained by different patterns of eye movements: similar levels of activation were observed when subjects fixated on the objects and when they scanned the objects with their eyes. Additional manipulations such as spatial frequency filtering and a 4-fold change in visual size did not affect LO activation. These results suggest that the enhanced responses to objects were not a manifestation of low-level visual processing. A striking demonstration that activity in LO is uniquely correlated to object detectability was produced by the "Lincoln" illusion, in which blurring of objects digitized into large blocks paradoxically increases their recognizability. Such blurring led to significant enhancement of LO activation. Despite the preferential activation to objects, LO did not seem to be involved in the final, "semantic," stages of the recognition process. Thus, objects varying widely in their recognizability (e.g., famous faces, common objects, and unfamiliar three-dimensional abstract sculptures) activated it to a similar degree. These results are thus evidence for an intermediate link in the chain of processing stages leading to object recognition in human visual cortex. Images Fig. 1 Fig. 2 Fig. 3 PMID:7667258

Differential binding of colors to objects in memory: red and yellow stick better than blue and green

PubMed Central

Kuhbandner, Christof; Spitzer, Bernhard; Lichtenfeld, Stephanie; Pekrun, Reinhard

2015-01-01

Both evolutionary considerations and recent research suggest that the color red serves as a signal indicating an object’s importance. However, until now, there is no evidence that this signaling function of red is also reflected in human memory. To examine the effect of red on memory, we conducted four experiments in which we presented objects colored in four different colors (red, green, blue, and yellow) and measured later memory for the presence of an object and for the color of an object. Across experiments, we varied the type of objects (words vs. pictures), task complexity (single objects vs. multiple objects in visual scenes), and intentionality of encoding (intentional vs. incidental learning). Memory for the presence of an object was not influenced by color. However, in all four experiments, memory for the color of an object depended on color type and was particularly high for red and yellow-colored objects and particularly low for green-colored objects, indicating that the binding of colors into object memory representations varies as a function of color type. Analyzing the observers’ confidence in their color memories revealed that color not only influenced objective memory performance but also subjective confidence. Subjective confidence judgments differentiated well between correct and incorrect color memories for red-colored objects, but poorly for green-colored objects. Our findings reveal a previously unknown color effect which may be of considerable interest for both basic color research and applied settings like eyewitness testimony in which memory for color features is relevant. Furthermore, our results indicate that feature binding in memory is not a uniform process by which any attended feature is automatically bound into unitary memory representations. Rather, memory binding seems to vary across different subtypes of features, a finding that supports recent research showing that object features are stored in memory rather independently from each other. PMID:25784892

Autonomous Space Object Catalogue Construction and Upkeep Using Sensor Control Theory

NASA Astrophysics Data System (ADS)

Moretti, N.; Rutten, M.; Bessell, T.; Morreale, B.

The capability to track objects in space is critical to safeguard domestic and international space assets. Infrequent measurement opportunities, complex dynamics and partial observability of orbital state makes the tracking of resident space objects nontrivial. It is not uncommon for human operators to intervene with space tracking systems, particularly in scheduling sensors. This paper details the development of a system that maintains a catalogue of geostationary objects through dynamically tasking sensors in real time by managing the uncertainty of object states. As the number of objects in space grows the potential for collision grows exponentially. Being able to provide accurate assessment to operators regarding costly collision avoidance manoeuvres is paramount; the accuracy of which is highly dependent on how object states are estimated. The system represents object state and uncertainty using particles and utilises a particle filter for state estimation. Particle filters capture the model and measurement uncertainty accurately, allowing for a more comprehensive representation of the state’s probability density function. Additionally, the number of objects in space is growing disproportionally to the number of sensors used to track them. Maintaining precise positions for all objects places large loads on sensors, limiting the time available to search for new objects or track high priority objects. Rather than precisely track all objects our system manages the uncertainty in orbital state for each object independently. The uncertainty is allowed to grow and sensor data is only requested when the uncertainty must be reduced. For example when object uncertainties overlap leading to data association issues or if the uncertainty grows to beyond a field of view. These control laws are formulated into a cost function, which is optimised in real time to task sensors. By controlling an optical telescope the system has been able to construct and maintain a catalogue of approximately 100 geostationary objects.

Spatiotemporal dynamics in understanding hand—object interactions

PubMed Central

Avanzini, Pietro; Fabbri-Destro, Maddalena; Campi, Cristina; Pascarella, Annalisa; Barchiesi, Guido; Cattaneo, Luigi; Rizzolatti, Giacomo

2013-01-01

It is generally accepted that visual perception results from the activation of a feed-forward hierarchy of areas, leading to increasingly complex representations. Here we present evidence for a fundamental role of backward projections to the occipito-temporal region for understanding conceptual object properties. The evidence is based on two studies. In the first study, using high-density EEG, we showed that during the observation of how objects are used there is an early activation of occipital and temporal areas, subsequently reaching the pole of the temporal lobe, and a late reactivation of the visual areas. In the second study, using transcranial magnetic stimulation over the occipital lobe, we showed a clear impairment in the accuracy of recognition of how objects are used during both early activation and, most importantly, late occipital reactivation. These findings represent strong neurophysiological evidence that a top-down mechanism is fundamental for understanding conceptual object properties, and suggest that a similar mechanism might be also present for other higher-order cognitive functions. PMID:24043805

Underwater binocular imaging of aerial objects versus the position of eyes relative to the flat water surface.

PubMed

Barta, András; Horváth, Gábor

2003-12-01

The apparent position, size, and shape of aerial objects viewed binocularly from water change as a result of the refraction of light at the water surface. Earlier studies of the refraction-distorted structure of the aerial binocular visual field of underwater observers were restricted to either vertically or horizontally oriented eyes. Here we calculate the position of the binocular image point of an aerial object point viewed by two arbitrarily positioned underwater eyes when the water surface is flat. Assuming that binocular image fusion is performed by appropriate vergent eye movements to bring the object's image onto the foveae, the structure of the aerial binocular visual field is computed and visualized as a function of the relative positions of the eyes. We also analyze two erroneous representations of the underwater imaging of aerial objects that have occurred in the literature. It is demonstrated that the structure of the aerial binocular visual field of underwater observers distorted by refraction is more complex than has been thought previously.

Superstructure-based Design and Optimization of Batch Biodiesel Production Using Heterogeneous Catalysts

NASA Astrophysics Data System (ADS)

Nuh, M. Z.; Nasir, N. F.

2017-08-01

Biodiesel as a fuel comprised of mono alkyl esters of long chain fatty acids derived from renewable lipid feedstock, such as vegetable oil and animal fat. Biodiesel production is complex process which need systematic design and optimization. However, no case study using the process system engineering (PSE) elements which are superstructure optimization of batch process, it involves complex problems and uses mixed-integer nonlinear programming (MINLP). The PSE offers a solution to complex engineering system by enabling the use of viable tools and techniques to better manage and comprehend the complexity of the system. This study is aimed to apply the PSE tools for the simulation of biodiesel process and optimization and to develop mathematical models for component of the plant for case A, B, C by using published kinetic data. Secondly, to determine economic analysis for biodiesel production, focusing on heterogeneous catalyst. Finally, the objective of this study is to develop the superstructure for biodiesel production by using heterogeneous catalyst. The mathematical models are developed by the superstructure and solving the resulting mixed integer non-linear model and estimation economic analysis by using MATLAB software. The results of the optimization process with the objective function of minimizing the annual production cost by batch process from case C is 23.2587 million USD. Overall, the implementation a study of process system engineering (PSE) has optimized the process of modelling, design and cost estimation. By optimizing the process, it results in solving the complex production and processing of biodiesel by batch.

Process consistency in models: The importance of system signatures, expert knowledge, and process complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J.; Savenije, H. H. G.; Gascuel-Odoux, C.

2014-09-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus, ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study, the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by four calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce a suite of hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by "prior constraints," inferred from expert knowledge to ensure a model which behaves well with respect to the modeler's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model setup exhibited increased performance in the independent test period and skill to better reproduce all tested signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if counter-balanced by prior constraints, can significantly increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge-driven strategy of constraining models.

An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis

USGS Publications Warehouse

McKenna, J.E.

2003-01-01

The biosphere is filled with complex living patterns and important questions about biodiversity and community and ecosystem ecology are concerned with structure and function of multispecies systems that are responsible for those patterns. Cluster analysis identifies discrete groups within multivariate data and is an effective method of coping with these complexities, but often suffers from subjective identification of groups. The bootstrap testing method greatly improves objective significance determination for cluster analysis. The BOOTCLUS program makes cluster analysis that reliably identifies real patterns within a data set more accessible and easier to use than previously available programs. A variety of analysis options and rapid re-analysis provide a means to quickly evaluate several aspects of a data set. Interpretation is influenced by sampling design and a priori designation of samples into replicate groups, and ultimately relies on the researcher's knowledge of the organisms and their environment. However, the BOOTCLUS program provides reliable, objectively determined groupings of multivariate data.

Identifying online user reputation of user-object bipartite networks

NASA Astrophysics Data System (ADS)

Liu, Xiao-Lu; Liu, Jian-Guo; Yang, Kai; Guo, Qiang; Han, Jing-Ti

2017-02-01

Identifying online user reputation based on the rating information of the user-object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part of all user opinions. The experimental results show that the AUC values of the presented algorithm could reach 0.8929 and 0.8483 for the MovieLens and Netflix data sets, respectively, which is better than the results generated by the CR and IARR methods. Furthermore, the experimental results for different user groups indicate that the presented algorithm outperforms the iterative ranking methods in both ranking accuracy and computation complexity. Moreover, the results for the synthetic networks show that the computation complexity of the presented algorithm is a linear function of the network size, which suggests that the presented algorithm is very effective and efficient for the large scale dynamic online systems.

Combining color and shape information for illumination-viewpoint invariant object recognition.

PubMed

Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

2006-01-01

In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.

Gamifying Video Object Segmentation.

PubMed

Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

2017-10-01

Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

Structural Integration of Sensors/Actuators by Laser Beam Melting for Tailored Smart Components

NASA Astrophysics Data System (ADS)

Töppel, Thomas; Lausch, Holger; Brand, Michael; Hensel, Eric; Arnold, Michael; Rotsch, Christian

2018-03-01

Laser beam melting (LBM), an additive laser powder bed fusion technology, enables the structural integration of temperature-sensitive sensors and actuators in complex monolithic metallic structures. The objective is to embed a functional component inside a metal part without losing its functionality by overheating. The first part of this paper addresses the development of a new process chain for bonded embedding of temperature-sensitive sensor/actuator systems by LBM. These systems are modularly built and coated by a multi-material/multi-layer thermal protection system of ceramic and metallic compounds. The characteristic of low global heat input in LBM is utilized for the functional embedding. In the second part, the specific functional design and optimization for tailored smart components with embedded functionalities are addressed. Numerical and experimental validated results are demonstrated on a smart femoral hip stem.

Plasmodium falciparum-infected erythrocytes induce Tissue Factor expression in endothelial cells and support the assembly of multimolecular coagulation complexes

PubMed Central

Francischetti, Ivo MB; Seydel, Karl B; Monteiro, Robson Q; Whitten, Richard O; Erexson, Cindy R; Noronha, Almério LL; Ostera, Graciela R.; Kamiza, Steve B; Molyneux, Malcolm E; Ward, Jerrold M; Taylor, Terrie E

2010-01-01

Summary Background Plasmodium falciparum malaria infects 300–500 million people every year causing 1–2 million deaths annually. Evidence of a coagulation disorder, activation of endothelial cells (EC) and increase in inflammatory cytokines are often present in malaria. Objectives We have asked whether parasitized red blood cells (pRBC) interaction with EC induces Tissue Factor expression in vitro and in vivo. The potential of phosphatidylserine-containing pRBC to support the assembly of blood coagulation complexes was also investigated. Results We demonstrate that mature forms of pRBC induce functional expression of tissue factor (TF) by endothelial cells (EC) in vitro with productive assembly of the extrinsic Xnase complex and initiation of the coagulation cascade. Late stage pRBC also support the prothrombinase and intrinsic Xnase complex formation in vitro, and may function as activated platelets in the amplification phase of the blood coagulation. Notably, postmortem brain sections obtained from P. falciparum-infected children who died from Cerebral Malaria and other causes display a consistent staining for TF in the EC. Conclusions These findings place TF expression by endothelium and the amplification of the coagulation cascade by pRBC and/or activated platelets as potentially critical steps in the pathogenesis of malaria. Furthermore, it may allow investigators to test other therapeutic alternatives targeting TF or modulators of EC function in the treatment of malaria and/or its complications. PMID:17002660

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

PubMed

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

Improved Holistic Analysis of Rayleigh Waves for Single- and Multi-Offset Data: Joint Inversion of Rayleigh-Wave Particle Motion and Vertical- and Radial-Component Velocity Spectra

NASA Astrophysics Data System (ADS)

Dal Moro, Giancarlo; Moustafa, Sayed S. R.; Al-Arifi, Nassir S.

2018-01-01

Rayleigh waves often propagate according to complex mode excitation so that the proper identification and separation of specific modes can be quite difficult or, in some cases, just impossible. Furthermore, the analysis of a single component (i.e., an inversion procedure based on just one objective function) necessarily prevents solving the problems related to the non-uniqueness of the solution. To overcome these issues and define a holistic analysis of Rayleigh waves, we implemented a procedure to acquire data that are useful to define and efficiently invert the three objective functions defined from the three following "objects": the velocity spectra of the vertical- and radial-components and the Rayleigh-wave particle motion (RPM) frequency-offset data. Two possible implementations are presented. In the first case we consider classical multi-offset (and multi-component) data, while in a second possible approach we exploit the data recorded by a single three-component geophone at a fixed offset from the source. Given the simple field procedures, the method could be particularly useful for the unambiguous geotechnical exploration of large areas, where more complex acquisition procedures, based on the joint acquisition of Rayleigh and Love waves, would not be economically viable. After illustrating the different kinds of data acquisition and the data processing, the results of the proposed methodology are illustrated in a case study. Finally, a series of theoretical and practical aspects are discussed to clarify some issues involved in the overall procedure (data acquisition and processing).

Time Scale Hierarchies in the Functional Organization of Complex Behaviors

PubMed Central

Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor K.

2011-01-01

Traditional approaches to cognitive modelling generally portray cognitive events in terms of ‘discrete’ states (point attractor dynamics) rather than in terms of processes, thereby neglecting the time structure of cognition. In contrast, more recent approaches explicitly address this temporal dimension, but typically provide no entry points into cognitive categorization of events and experiences. With the aim to incorporate both these aspects, we propose a framework for functional architectures. Our approach is grounded in the notion that arbitrary complex (human) behaviour is decomposable into functional modes (elementary units), which we conceptualize as low-dimensional dynamical objects (structured flows on manifolds). The ensemble of modes at an agent’s disposal constitutes his/her functional repertoire. The modes may be subjected to additional dynamics (termed operational signals), in particular, instantaneous inputs, and a mechanism that sequentially selects a mode so that it temporarily dominates the functional dynamics. The inputs and selection mechanisms act on faster and slower time scales then that inherent to the modes, respectively. The dynamics across the three time scales are coupled via feedback, rendering the entire architecture autonomous. We illustrate the functional architecture in the context of serial behaviour, namely cursive handwriting. Subsequently, we investigate the possibility of recovering the contributions of functional modes and operational signals from the output, which appears to be possible only when examining the output phase flow (i.e., not from trajectories in phase space or time). PMID:21980278

PyMCT: A Very High Level Language Coupling Tool For Climate System Models

NASA Astrophysics Data System (ADS)

Tobis, M.; Pierrehumbert, R. T.; Steder, M.; Jacob, R. L.

2006-12-01

At the Climate Systems Center of the University of Chicago, we have been examining strategies for applying agile programming techniques to complex high-performance modeling experiments. While the "agile" development methodology differs from a conventional requirements process and its associated milestones, the process remain a formal one. It is distinguished by continuous improvement in functionality, large numbers of small releases, extensive and ongoing testing strategies, and a strong reliance on very high level languages (VHLL). Here we report on PyMCT, which we intend as a core element in a model ensemble control superstructure. PyMCT is a set of Python bindings for MCT, the Fortran-90 based Model Coupling Toolkit, which forms the infrastructure for the inter-component communication in the Community Climate System Model (CCSM). MCT provides a scalable model communication infrastructure. In order to take maximum advantage of agile software development methodologies, we exposed MCT functionality to Python, a prominent VHLL. We describe how the scalable architecture of MCT allows us to overcome the relatively weak runtime performance of Python, so that the performance of the combined system is not severely impacted. To demonstrate these advantages, we reimplemented the CCSM coupler in Python. While this alone offers no new functionality, it does provide a rigorous test of PyMCT functionality and performance. We reimplemented the CPL6 library, presenting an interesting case study of the comparison between conventional Fortran-90 programming and the higher abstraction level provided by a VHLL. The powerful abstractions provided by Python will allow much more complex experimental paradigms. In particular, we hope to build on the scriptability of our coupling strategy to enable systematic sensitivity tests. Our most ambitious objective is to combine our efforts with Bayesian inverse modeling techniques toward objective tuning at the highest level, across model architectures.

Development of Three-Dimensional Completion of Complex Objects

ERIC Educational Resources Information Center

Soska, Kasey C.; Johnson, Scott P.

2013-01-01

Three-dimensional (3D) object completion, the ability to perceive the backs of objects seen from a single viewpoint, emerges at around 6 months of age. Yet, only relatively simple 3D objects have been used in assessing its development. This study examined infants' 3D object completion when presented with more complex stimuli. Infants…

Viewing and Editing Earth Science Metadata MOBE: Metadata Object Browser and Editor in Java

NASA Astrophysics Data System (ADS)

Chase, A.; Helly, J.

2002-12-01

Metadata is an important, yet often neglected aspect of successful archival efforts. However, to generate robust, useful metadata is often a time consuming and tedious task. We have been approaching this problem from two directions: first by automating metadata creation, pulling from known sources of data, and in addition, what this (paper/poster?) details, developing friendly software for human interaction with the metadata. MOBE and COBE(Metadata Object Browser and Editor, and Canonical Object Browser and Editor respectively), are Java applications for editing and viewing metadata and digital objects. MOBE has already been designed and deployed, currently being integrated into other areas of the SIOExplorer project. COBE is in the design and development stage, being created with the same considerations in mind as those for MOBE. Metadata creation, viewing, data object creation, and data object viewing, when taken on a small scale are all relatively simple tasks. Computer science however, has an infamous reputation for transforming the simple into complex. As a system scales upwards to become more robust, new features arise and additional functionality is added to the software being written to manage the system. The software that emerges from such an evolution, though powerful, is often complex and difficult to use. With MOBE the focus is on a tool that does a small number of tasks very well. The result has been an application that enables users to manipulate metadata in an intuitive and effective way. This allows for a tool that serves its purpose without introducing additional cognitive load onto the user, an end goal we continue to pursue.

Pregnenolone sulphate enhances spatial orientation and object discrimination in adult male rats: evidence from a behavioural and electrophysiological study.

PubMed

Plescia, Fulvio; Sardo, Pierangelo; Rizzo, Valerio; Cacace, Silvana; Marino, Rosa Anna Maria; Brancato, Anna; Ferraro, Giuseppe; Carletti, Fabio; Cannizzaro, Carla

2014-01-01

Neurosteroids can alter neuronal excitability interacting with specific neurotransmitter receptors, thus affecting several functions such as cognition and emotionality. In this study we investigated, in adult male rats, the effects of the acute administration of pregnenolone-sulfate (PREGS) (10mg/kg, s.c.) on cognitive processes using the Can test, a non aversive spatial/visual task which allows the assessment of both spatial orientation-acquisition and object discrimination in a simple and in a complex version of the visual task. Electrophysiological recordings were also performed in vivo, after acute PREGS systemic administration in order to investigate on the neuronal activation in the hippocampus and the perirhinal cortex. Our results indicate that, PREGS induces an improvement in spatial orientation-acquisition and in object discrimination in the simple and in the complex visual task; the behavioural responses were also confirmed by electrophysiological recordings showing a potentiation in the neuronal activity of the hippocampus and the perirhinal cortex. In conclusion, this study demonstrates that PREGS systemic administration in rats exerts cognitive enhancing properties which involve both the acquisition and utilization of spatial information, and object discrimination memory, and also correlates the behavioural potentiation observed to an increase in the neuronal firing of discrete cerebral areas critical for spatial learning and object recognition. This provides further evidence in support of the role of PREGS in exerting a protective and enhancing role on human memory. Copyright © 2013. Published by Elsevier B.V.

Direct-to-digital holography reduction of reference hologram noise and fourier space smearing

DOEpatents

Voelkl, Edgar

2006-06-27

Systems and methods are described for reduction of reference hologram noise and reduction of Fourier space smearing, especially in the context of direct-to-digital holography (off-axis interferometry). A method of reducing reference hologram noise includes: recording a plurality of reference holograms; processing the plurality of reference holograms into a corresponding plurality of reference image waves; and transforming the corresponding plurality of reference image waves into a reduced noise reference image wave. A method of reducing smearing in Fourier space includes: recording a plurality of reference holograms; processing the plurality of reference holograms into a corresponding plurality of reference complex image waves; transforming the corresponding plurality of reference image waves into a reduced noise reference complex image wave; recording a hologram of an object; processing the hologram of the object into an object complex image wave; and dividing the complex image wave of the object by the reduced noise reference complex image wave to obtain a reduced smearing object complex image wave.

Validation of inertial measurement units with an optoelectronic system for whole-body motion analysis.

PubMed

Robert-Lachaine, Xavier; Mecheri, Hakim; Larue, Christian; Plamondon, André

2017-04-01

The potential of inertial measurement units (IMUs) for ergonomics applications appears promising. However, previous IMUs validation studies have been incomplete regarding aspects of joints analysed, complexity of movements and duration of trials. The objective was to determine the technological error and biomechanical model differences between IMUs and an optoelectronic system and evaluate the effect of task complexity and duration. Whole-body kinematics from 12 participants was recorded simultaneously with a full-body Xsens system where an Optotrak cluster was fixed on every IMU. Short functional movements and long manual material handling tasks were performed and joint angles were compared between the two systems. The differences attributed to the biomechanical model showed significantly greater (P ≤ .001) RMSE than the technological error. RMSE was systematically higher (P ≤ .001) for the long complex task with a mean on all joints of 2.8° compared to 1.2° during short functional movements. Definition of local coordinate systems based on anatomical landmarks or single posture was the most influent difference between the two systems. Additionally, IMUs accuracy was affected by the complexity and duration of the tasks. Nevertheless, technological error remained under 5° RMSE during handling tasks, which shows potential to track workers during their daily labour.

Bioinspired, Mobile Robots With High Stability, Functionality and Low Cost

DTIC Science & Technology

2014-02-19

actuators with complex actuating modes (e.g., extending and multiple bending modes; Figure 5-3). Figure 5-1. (left panel) 3D printed molds...failure (e.g., cellulose , KevlarTM, polystyrene). We designed a two part mold (Figure 6-a) to pattern the exterior and interior pleating and then...variety of objects. The 3D molding technique used to fabricate this actuator, however, limits the pneumatic channel geometry. To achieve pneu-net

Self-organization in complex oxide thin films: from 2D to 0D nanostructures of SrRuO3 and CoCr2O4

NASA Astrophysics Data System (ADS)

Sánchez, F.; Lüders, U.; Herranz, G.; Infante, I. C.; Fontcuberta, J.; García-Cuenca, M. V.; Ferrater, C.; Varela, M.

2005-05-01

We report here on the controlled fabrication of nanostructures of varied dimensionality by self-organization processes in the heteroepitaxial growth of SrRuO3 (SRO) and CoCr2O4 (CCO) films. The surface of SRO films on SrTiO3(001) substrates can show extremely smooth terraces (2D objects) separated by atomic steps, a structure of faceted islands (0D objects), a cross-hatch morphology (1D objects), an array of finger-like units (1D objects), or an array of giant bunched steps (1D objects). The surface can be tailored to a particular structure by controlling the vicinality of the substrate and the growth rate and nominal thickness of the film. In the case of CCO films, grown on (001)-oriented MgAl2O4 or MgO substrates, high aspect ratio {111}-faceted pyramids and hut clusters (0D objects), highly oriented and having a similar size, appear above a critical thickness. The size and spatial density can be tuned by varying deposition temperature, nominal thickness, and substrate. This dependence allows the fabrication of surfaces being fully faceted (2D objects), or having arrays of dislocated pyramids of up to micrometric size, or small coherently lattice strained pyramids having a nanometric size. We discuss the driving forces that originate the peculiar SRO and CCO nanostructures. The findings illustrate that the growth of complex oxides can promote a variety of novel self-organized morphologies, and suggest original strategies to fabricate templates or hybrid structures of oxides combining varied functionalities.

Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness

PubMed Central

Samonds, Jason M.; Potetz, Brian R.; Lee, Tai Sing

2014-01-01

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically. Because skewness does not depend on a specific model or function of tuning, it is especially appealing to cases of sharpening where recurrent interactions among neurons produce sharper tuning curves that deviate in a complex manner from the feedforward function of tuning. Since tuning curves for all neurons are not typically well described by a single parametric function, this model independence additionally allows skewness to be applied to all recorded neurons, maximizing the statistical power of a set of data. We also compare skewness with other nonparametric measures of tuning curve sharpness and selectivity. Compared to these other nonparametric measures tested, skewness is best used for capturing the sharpness of multimodal tuning curves defined by narrow peaks (maximum) and broad valleys (minima). Finally, we provide a more formal definition of sharpness using a shape-based information gain measure and derive and show that skewness is correlated with this definition. PMID:24555451

Reflection full-waveform inversion using a modified phase misfit function

NASA Astrophysics Data System (ADS)

Cui, Chao; Huang, Jian-Ping; Li, Zhen-Chun; Liao, Wen-Yuan; Guan, Zhe

2017-09-01

Reflection full-waveform inversion (RFWI) updates the low- and highwavenumber components, and yields more accurate initial models compared with conventional full-waveform inversion (FWI). However, there is strong nonlinearity in conventional RFWI because of the lack of low-frequency data and the complexity of the amplitude. The separation of phase and amplitude information makes RFWI more linear. Traditional phase-calculation methods face severe phase wrapping. To solve this problem, we propose a modified phase-calculation method that uses the phase-envelope data to obtain the pseudo phase information. Then, we establish a pseudophase-information-based objective function for RFWI, with the corresponding source and gradient terms. Numerical tests verify that the proposed calculation method using the phase-envelope data guarantees the stability and accuracy of the phase information and the convergence of the objective function. The application on a portion of the Sigsbee2A model and comparison with inversion results of the improved RFWI and conventional FWI methods verify that the pseudophase-based RFWI produces a highly accurate and efficient velocity model. Moreover, the proposed method is robust to noise and high frequency.

DNA origami compliant nanostructures with tunable mechanical properties.

PubMed

Zhou, Lifeng; Marras, Alexander E; Su, Hai-Jun; Castro, Carlos E

2014-01-28

DNA origami enables fabrication of precise nanostructures by programming the self-assembly of DNA. While this approach has been used to make a variety of complex 2D and 3D objects, the mechanical functionality of these structures is limited due to their rigid nature. We explore the fabrication of deformable, or compliant, objects to establish a framework for mechanically functional nanostructures. This compliant design approach is used in macroscopic engineering to make devices including sensors, actuators, and robots. We build compliant nanostructures by utilizing the entropic elasticity of single-stranded DNA (ssDNA) to locally bend bundles of double-stranded DNA into bent geometries whose curvature and mechanical properties can be tuned by controlling the length of ssDNA strands. We demonstrate an ability to achieve a wide range of geometries by adjusting a few strands in the nanostructure design. We further developed a mechanical model to predict both geometry and mechanical properties of our compliant nanostructures that agrees well with experiments. Our results provide a basis for the design of mechanically functional DNA origami devices and materials.

Resting-State fMRI Activity Predicts Unsupervised Learning and Memory in an Immersive Virtual Reality Environment

PubMed Central

Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T.

2014-01-01

In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

No Evidence for a Fixed Object Limit in Working Memory: Spatial Ensemble Representations Inflate Estimates of Working Memory Capacity for Complex Objects

ERIC Educational Resources Information Center

Brady, Timothy F.; Alvarez, George A.

2015-01-01

A central question for models of visual working memory is whether the number of objects people can remember depends on object complexity. Some influential "slot" models of working memory capacity suggest that people always represent 3-4 objects and that only the fidelity with which these objects are represented is affected by object…

Motor cortical activity changes during neuroprosthetic-controlled object interaction.

PubMed

Downey, John E; Brane, Lucas; Gaunt, Robert A; Tyler-Kabara, Elizabeth C; Boninger, Michael L; Collinger, Jennifer L

2017-12-05

Brain-computer interface (BCI) controlled prosthetic arms are being developed to restore function to people with upper-limb paralysis. This work provides an opportunity to analyze human cortical activity during complex tasks. Previously we observed that BCI control became more difficult during interactions with objects, although we did not quantify the neural origins of this phenomena. Here, we investigated how motor cortical activity changed in the presence of an object independently of the kinematics that were being generated using intracortical recordings from two people with tetraplegia. After identifying a population-wide increase in neural firing rates that corresponded with the hand being near an object, we developed an online scaling feature in the BCI system that operated without knowledge of the task. Online scaling increased the ability of two subjects to control the robotic arm when reaching to grasp and transport objects. This work suggests that neural representations of the environment, in this case the presence of an object, are strongly and consistently represented in motor cortex but can be accounted for to improve BCI performance.

A no-reference video quality assessment metric based on ROI

NASA Astrophysics Data System (ADS)

Jia, Lixiu; Zhong, Xuefei; Tu, Yan; Niu, Wenjuan

2015-01-01

A no reference video quality assessment metric based on the region of interest (ROI) was proposed in this paper. In the metric, objective video quality was evaluated by integrating the quality of two compressed artifacts, i.e. blurring distortion and blocking distortion. The Gaussian kernel function was used to extract the human density maps of the H.264 coding videos from the subjective eye tracking data. An objective bottom-up ROI extraction model based on magnitude discrepancy of discrete wavelet transform between two consecutive frames, center weighted color opponent model, luminance contrast model and frequency saliency model based on spectral residual was built. Then only the objective saliency maps were used to compute the objective blurring and blocking quality. The results indicate that the objective ROI extraction metric has a higher the area under the curve (AUC) value. Comparing with the conventional video quality assessment metrics which measured all the video quality frames, the metric proposed in this paper not only decreased the computation complexity, but improved the correlation between subjective mean opinion score (MOS) and objective scores.

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

NASA Technical Reports Server (NTRS)

Ortiz, Francisco

2004-01-01

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

An efficient non-dominated sorting method for evolutionary algorithms.

PubMed

Fang, Hongbing; Wang, Qian; Tu, Yi-Cheng; Horstemeyer, Mark F

2008-01-01

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-dominated fronts takes the majority of total computational time (excluding the cost of fitness evaluations) of NSGA-II, making this algorithm faster will significantly improve the overall efficiency of NSGA-II and other genetic algorithms using non-dominated sorting. The new non-dominated sorting algorithm proposed in this study reduces the number of redundant comparisons existing in the algorithm of NSGA-II by recording the dominance information among solutions from their first comparisons. By utilizing a new data structure called the dominance tree and the divide-and-conquer mechanism, the new algorithm is faster than NSGA-II for different numbers of objective functions. Although the number of solution comparisons by the proposed algorithm is close to that of NSGA-II when the number of objectives becomes large, the total computational time shows that the proposed algorithm still has better efficiency because of the adoption of the dominance tree structure and the divide-and-conquer mechanism.

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

Jealousy in Dogs

PubMed Central

Harris, Christine R.; Prouvost, Caroline

2014-01-01

It is commonly assumed that jealousy is unique to humans, partially because of the complex cognitions often involved in this emotion. However, from a functional perspective, one might expect that an emotion that evolved to protect social bonds from interlopers might exist in other social species, particularly one as cognitively sophisticated as the dog. The current experiment adapted a paradigm from human infant studies to examine jealousy in domestic dogs. We found that dogs exhibited significantly more jealous behaviors (e.g., snapping, getting between the owner and object, pushing/touching the object/owner) when their owners displayed affectionate behaviors towards what appeared to be another dog as compared to nonsocial objects. These results lend support to the hypothesis that jealousy has some “primordial” form that exists in human infants and in at least one other social species besides humans. PMID:25054800

Progress in developing Poisson-Boltzmann equation solvers

PubMed Central

Li, Chuan; Li, Lin; Petukh, Marharyta; Alexov, Emil

2013-01-01

This review outlines the recent progress made in developing more accurate and efficient solutions to model electrostatics in systems comprised of bio-macromolecules and nano-objects, the last one referring to objects that do not have biological function themselves but nowadays are frequently used in biophysical and medical approaches in conjunction with bio-macromolecules. The problem of modeling macromolecular electrostatics is reviewed from two different angles: as a mathematical task provided the specific definition of the system to be modeled and as a physical problem aiming to better capture the phenomena occurring in the real experiments. In addition, specific attention is paid to methods to extend the capabilities of the existing solvers to model large systems toward applications of calculations of the electrostatic potential and energies in molecular motors, mitochondria complex, photosynthetic machinery and systems involving large nano-objects. PMID:24199185

Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT

PubMed Central

2014-01-01

Accurate reconstruction of the object from sparse-view sampling data is an appealing issue for ultrasound diffraction tomography (UDT). In this paper, we present a reconstruction method based on compressed sensing framework for sparse-view UDT. Due to the piecewise uniform characteristics of anatomy structures, the total variation is introduced into the cost function to find a more faithful sparse representation of the object. The inverse problem of UDT is iteratively resolved by conjugate gradient with nonuniform fast Fourier transform. Simulation results show the effectiveness of the proposed method that the main characteristics of the object can be properly presented with only 16 views. Compared to interpolation and multiband method, the proposed method can provide higher resolution and lower artifacts with the same view number. The robustness to noise and the computation complexity are also discussed. PMID:24868241

Multi-sensor image fusion algorithm based on multi-objective particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Xie, Xia-zhu; Xu, Ya-wei

2017-11-01

On the basis of DT-CWT (Dual-Tree Complex Wavelet Transform - DT-CWT) theory, an approach based on MOPSO (Multi-objective Particle Swarm Optimization Algorithm) was proposed to objectively choose the fused weights of low frequency sub-bands. High and low frequency sub-bands were produced by DT-CWT. Absolute value of coefficients was adopted as fusion rule to fuse high frequency sub-bands. Fusion weights in low frequency sub-bands were used as particles in MOPSO. Spatial Frequency and Average Gradient were adopted as two kinds of fitness functions in MOPSO. The experimental result shows that the proposed approach performances better than Average Fusion and fusion methods based on local variance and local energy respectively in brightness, clarity and quantitative evaluation which includes Entropy, Spatial Frequency, Average Gradient and QAB/F.

Function follows form: combining nanoimprint and inkjet printing

NASA Astrophysics Data System (ADS)

Muehlberger, M.; Haslinger, M. J.; Kurzmann, J.; Ikeda, M.; Fuchsbauer, A.; Faury, T.; Koepplmayr, T.; Ausserhuber, H.; Kastner, J.; Woegerer, C.; Fechtig, D.

2017-06-01

We are investigating the possibilities and the technical requirements to do nanopatterning on arbitrary curved surfaces. This is done considering the opportunities and possibilities of additive manufacturing. One of the key elements is the necessity to deposit material in well-defined areas of various complex 3D objects. In order to achieve this we are developing a robot-based inkjet printing. We report on our progress with this respect and also on our efforts to perform nanoimprinting on curved, possibly 3D-printed objects using materials that can be deposited by inkjet printing. In the framework of this article, we provide an overview over our current status, the challenges and an outlook.

RNACompress: Grammar-based compression and informational complexity measurement of RNA secondary structure.

PubMed

Liu, Qi; Yang, Yu; Chen, Chun; Bu, Jiajun; Zhang, Yin; Ye, Xiuzi

2008-03-31

With the rapid emergence of RNA databases and newly identified non-coding RNAs, an efficient compression algorithm for RNA sequence and structural information is needed for the storage and analysis of such data. Although several algorithms for compressing DNA sequences have been proposed, none of them are suitable for the compression of RNA sequences with their secondary structures simultaneously. This kind of compression not only facilitates the maintenance of RNA data, but also supplies a novel way to measure the informational complexity of RNA structural data, raising the possibility of studying the relationship between the functional activities of RNA structures and their complexities, as well as various structural properties of RNA based on compression. RNACompress employs an efficient grammar-based model to compress RNA sequences and their secondary structures. The main goals of this algorithm are two fold: (1) present a robust and effective way for RNA structural data compression; (2) design a suitable model to represent RNA secondary structure as well as derive the informational complexity of the structural data based on compression. Our extensive tests have shown that RNACompress achieves a universally better compression ratio compared with other sequence-specific or common text-specific compression algorithms, such as Gencompress, winrar and gzip. Moreover, a test of the activities of distinct GTP-binding RNAs (aptamers) compared with their structural complexity shows that our defined informational complexity can be used to describe how complexity varies with activity. These results lead to an objective means of comparing the functional properties of heteropolymers from the information perspective. A universal algorithm for the compression of RNA secondary structure as well as the evaluation of its informational complexity is discussed in this paper. We have developed RNACompress, as a useful tool for academic users. Extensive tests have shown that RNACompress is a universally efficient algorithm for the compression of RNA sequences with their secondary structures. RNACompress also serves as a good measurement of the informational complexity of RNA secondary structure, which can be used to study the functional activities of RNA molecules.

RNACompress: Grammar-based compression and informational complexity measurement of RNA secondary structure

PubMed Central

Liu, Qi; Yang, Yu; Chen, Chun; Bu, Jiajun; Zhang, Yin; Ye, Xiuzi

2008-01-01

Background With the rapid emergence of RNA databases and newly identified non-coding RNAs, an efficient compression algorithm for RNA sequence and structural information is needed for the storage and analysis of such data. Although several algorithms for compressing DNA sequences have been proposed, none of them are suitable for the compression of RNA sequences with their secondary structures simultaneously. This kind of compression not only facilitates the maintenance of RNA data, but also supplies a novel way to measure the informational complexity of RNA structural data, raising the possibility of studying the relationship between the functional activities of RNA structures and their complexities, as well as various structural properties of RNA based on compression. Results RNACompress employs an efficient grammar-based model to compress RNA sequences and their secondary structures. The main goals of this algorithm are two fold: (1) present a robust and effective way for RNA structural data compression; (2) design a suitable model to represent RNA secondary structure as well as derive the informational complexity of the structural data based on compression. Our extensive tests have shown that RNACompress achieves a universally better compression ratio compared with other sequence-specific or common text-specific compression algorithms, such as Gencompress, winrar and gzip. Moreover, a test of the activities of distinct GTP-binding RNAs (aptamers) compared with their structural complexity shows that our defined informational complexity can be used to describe how complexity varies with activity. These results lead to an objective means of comparing the functional properties of heteropolymers from the information perspective. Conclusion A universal algorithm for the compression of RNA secondary structure as well as the evaluation of its informational complexity is discussed in this paper. We have developed RNACompress, as a useful tool for academic users. Extensive tests have shown that RNACompress is a universally efficient algorithm for the compression of RNA sequences with their secondary structures. RNACompress also serves as a good measurement of the informational complexity of RNA secondary structure, which can be used to study the functional activities of RNA molecules. PMID:18373878

Design and Use of a Learning Object for Finding Complex Polynomial Roots

ERIC Educational Resources Information Center

Benitez, Julio; Gimenez, Marcos H.; Hueso, Jose L.; Martinez, Eulalia; Riera, Jaime

2013-01-01

Complex numbers are essential in many fields of engineering, but students often fail to have a natural insight of them. We present a learning object for the study of complex polynomials that graphically shows that any complex polynomials has a root and, furthermore, is useful to find the approximate roots of a complex polynomial. Moreover, we…

Application of response surface techniques to helicopter rotor blade optimization procedure

NASA Technical Reports Server (NTRS)

Henderson, Joseph Lynn; Walsh, Joanne L.; Young, Katherine C.

1995-01-01

In multidisciplinary optimization problems, response surface techniques can be used to replace the complex analyses that define the objective function and/or constraints with simple functions, typically polynomials. In this work a response surface is applied to the design optimization of a helicopter rotor blade. In previous work, this problem has been formulated with a multilevel approach. Here, the response surface takes advantage of this decomposition and is used to replace the lower level, a structural optimization of the blade. Problems that were encountered and important considerations in applying the response surface are discussed. Preliminary results are also presented that illustrate the benefits of using the response surface.

Modelling microbial metabolic rewiring during growth in a complex medium.

PubMed

Fondi, Marco; Bosi, Emanuele; Presta, Luana; Natoli, Diletta; Fani, Renato

2016-11-24

In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA.

A system architecture for a planetary rover

NASA Technical Reports Server (NTRS)

Smith, D. B.; Matijevic, J. R.

1989-01-01

Each planetary mission requires a complex space vehicle which integrates several functions to accomplish the mission and science objectives. A Mars Rover is one of these vehicles, and extends the normal spacecraft functionality with two additional functions: surface mobility and sample acquisition. All functions are assembled into a hierarchical and structured format to understand the complexities of interactions between functions during different mission times. It can graphically show data flow between functions, and most importantly, the necessary control flow to avoid unambiguous results. Diagrams are presented organizing the functions into a structured, block format where each block represents a major function at the system level. As such, there are six blocks representing telecomm, power, thermal, science, mobility and sampling under a supervisory block called Data Management/Executive. Each block is a simple collection of state machines arranged into a hierarchical order very close to the NASREM model for Telerobotics. Each layer within a block represents a level of control for a set of state machines that do the three primary interface functions: command, telemetry, and fault protection. This latter function is expanded to include automatic reactions to the environment as well as internal faults. Lastly, diagrams are presented that trace the system operations involved in moving from site to site after site selection. The diagrams clearly illustrate both the data and control flows. They also illustrate inter-block data transfers and a hierarchical approach to fault protection. This systems architecture can be used to determine functional requirements, interface specifications and be used as a mechanism for grouping subsystems (i.e., collecting groups of machines, or blocks consistent with good and testable implementations).

Homological scaffolds of brain functional networks

PubMed Central

Petri, G.; Expert, P.; Turkheimer, F.; Carhart-Harris, R.; Nutt, D.; Hellyer, P. J.; Vaccarino, F.

2014-01-01

Networks, as efficient representations of complex systems, have appealed to scientists for a long time and now permeate many areas of science, including neuroimaging (Bullmore and Sporns 2009 Nat. Rev. Neurosci. 10, 186–198. (doi:10.1038/nrn2618)). Traditionally, the structure of complex networks has been studied through their statistical properties and metrics concerned with node and link properties, e.g. degree-distribution, node centrality and modularity. Here, we study the characteristics of functional brain networks at the mesoscopic level from a novel perspective that highlights the role of inhomogeneities in the fabric of functional connections. This can be done by focusing on the features of a set of topological objects—homological cycles—associated with the weighted functional network. We leverage the detected topological information to define the homological scaffolds, a new set of objects designed to represent compactly the homological features of the correlation network and simultaneously make their homological properties amenable to networks theoretical methods. As a proof of principle, we apply these tools to compare resting-state functional brain activity in 15 healthy volunteers after intravenous infusion of placebo and psilocybin—the main psychoactive component of magic mushrooms. The results show that the homological structure of the brain's functional patterns undergoes a dramatic change post-psilocybin, characterized by the appearance of many transient structures of low stability and of a small number of persistent ones that are not observed in the case of placebo. PMID:25401177

Support vector regression scoring of receptor-ligand complexes for rank-ordering and virtual screening of chemical libraries.

PubMed

Li, Liwei; Wang, Bo; Meroueh, Samy O

2011-09-26

The community structure-activity resource (CSAR) data sets are used to develop and test a support vector machine-based scoring function in regression mode (SVR). Two scoring functions (SVR-KB and SVR-EP) are derived with the objective of reproducing the trend of the experimental binding affinities provided within the two CSAR data sets. The features used to train SVR-KB are knowledge-based pairwise potentials, while SVR-EP is based on physicochemical properties. SVR-KB and SVR-EP were compared to seven other widely used scoring functions, including Glide, X-score, GoldScore, ChemScore, Vina, Dock, and PMF. Results showed that SVR-KB trained with features obtained from three-dimensional complexes of the PDBbind data set outperformed all other scoring functions, including best performing X-score, by nearly 0.1 using three correlation coefficients, namely Pearson, Spearman, and Kendall. It was interesting that higher performance in rank ordering did not translate into greater enrichment in virtual screening assessed using the 40 targets of the Directory of Useful Decoys (DUD). To remedy this situation, a variant of SVR-KB (SVR-KBD) was developed by following a target-specific tailoring strategy that we had previously employed to derive SVM-SP. SVR-KBD showed a much higher enrichment, outperforming all other scoring functions tested, and was comparable in performance to our previously derived scoring function SVM-SP.

Functionalizing the γ-Position of α-Diazo-β-ketoesters.

PubMed

Nguyen, Thu Q; Alqurafi, Maha; Edwards, Cash; Nguyen, Pauline; Kim, Jean; Casco, Samuel; Bennet, Maricka; Chiang, Christopher; Lohry, Maureen; Cox, Melina; Meshram, Byron; Le, Duyen; Kim, Eugene; Smriti, Snigdha; Oelschlaeger, Peter; Buynak, John D

2016-06-27

Although α-diazo-β-ketoesters are synthetically versatile intermediates, methodology for introducing this functionality into complex molecules is still limited, most frequently involving a carboxylic acid precursor, which is then activated and transformed into a β-ketoester, with the diazo group being subsequently added with a diazo transfer reagent. While introducing this highly functional moiety in a convergent one step process would be ideal, such an objective is limited by the relatively few studies which address functionalization of the α-diazo-β-ketoester at the γ-position. In the present investigation, we evaluate strategies, both new and established, for functionalizing α-diazo-β-ketoesters, particularly with regard to generating compounds prospectively useful in the synthesis of C1-substituted carbapenems. We report the first δ-aldehydo-α-diazo-β-ketoester as well as a method for its oxidation to the corresponding methyl ester, and the formation of a new substituted pyrazole under basic conditions.

Predictive model of complexity in early palliative care: a cohort of advanced cancer patients (PALCOM study).

PubMed

Tuca, Albert; Gómez-Martínez, Mónica; Prat, Aleix

2018-01-01

Model of early palliative care (PC) integrated in oncology is based on shared care from the diagnosis to the end of life and is mainly focused on patients with greater complexity. However, there is no definition or tools to evaluate PC complexity. The objectives of the study were to identify the factors influencing level determination of complexity, propose predictive models, and build a complexity scale of PC. We performed a prospective, observational, multicenter study in a cohort of advanced cancer patients with an estimated prognosis ≤ 6 months. An ad hoc structured evaluation including socio-demographic and clinical data, symptom burden, functional and cognitive status, psychosocial problems, and existential-ethic dilemmas was recorded systematically. According to this multidimensional evaluation, investigator classified patients as high, medium, or low palliative complexity, associated to need of basic or specialized PC. Logistic regression was used to identify the variables influencing determination of level of PC complexity and explore predictive models. We included 324 patients; 41% were classified as having high PC complexity and 42.9% as medium, both levels being associated with specialized PC. Variables influencing determination of PC complexity were as follows: high symptom burden (OR 3.19 95%CI: 1.72-6.17), difficult pain (OR 2.81 95%CI:1.64-4.9), functional status (OR 0.99 95%CI:0.98-0.9), and social-ethical existential risk factors (OR 3.11 95%CI:1.73-5.77). Logistic analysis of variables allowed construct a complexity model and structured scales (PALCOM 1 and 2) with high predictive value (AUC ROC 76%). This study provides a new model and tools to assess complexity in palliative care, which may be very useful to manage referral to specialized PC services, and agree intensity of their intervention in a model of early-shared care integrated in oncology.

ARC-VM: An architecture real options complexity-based valuation methodology for military systems-of-systems acquisitions

NASA Astrophysics Data System (ADS)

Domercant, Jean Charles

The combination of today's national security environment and mandated acquisition policies makes it necessary for military systems to interoperate with each other to greater degrees. This growing interdependency results in complex Systems-of-Systems (SoS) that only continue to grow in complexity to meet evolving capability needs. Thus, timely and affordable acquisition becomes more difficult, especially in the face of mounting budgetary pressures. To counter this, architecting principles must be applied to SoS design. The research objective is to develop an Architecture Real Options Complexity-Based Valuation Methodology (ARC-VM) suitable for acquisition-level decision making, where there is a stated desire for more informed tradeoffs between cost, schedule, and performance during the early phases of design. First, a framework is introduced to measure architecture complexity as it directly relates to military SoS. Development of the framework draws upon a diverse set of disciplines, including Complexity Science, software architecting, measurement theory, and utility theory. Next, a Real Options based valuation strategy is developed using techniques established for financial stock options that have recently been adapted for use in business and engineering decisions. The derived complexity measure provides architects with an objective measure of complexity that focuses on relevant complex system attributes. These attributes are related to the organization and distribution of SoS functionality and the sharing and processing of resources. The use of Real Options provides the necessary conceptual and visual framework to quantifiably and traceably combine measured architecture complexity, time-valued performance levels, as well as programmatic risks and uncertainties. An example suppression of enemy air defenses (SEAD) capability demonstrates the development and usefulness of the resulting architecture complexity & Real Options based valuation methodology. Different portfolios of candidate system types are used to generate an array of architecture alternatives that are then evaluated using an engagement model. This performance data is combined with both measured architecture complexity and programmatic data to assign an acquisition value to each alternative. This proves useful when selecting alternatives most likely to meet current and future capability needs.

Visual object agnosia is associated with a breakdown of object-selective responses in the lateral occipital cortex.

PubMed

Ptak, Radek; Lazeyras, François; Di Pietro, Marie; Schnider, Armin; Simon, Stéphane R

2014-07-01

Patients with visual object agnosia fail to recognize the identity of visually presented objects despite preserved semantic knowledge. Object agnosia may result from damage to visual cortex lying close to or overlapping with the lateral occipital complex (LOC), a brain region that exhibits selectivity to the shape of visually presented objects. Despite this anatomical overlap the relationship between shape processing in the LOC and shape representations in object agnosia is unknown. We studied a patient with object agnosia following isolated damage to the left occipito-temporal cortex overlapping with the LOC. The patient showed intact processing of object structure, yet often made identification errors that were mainly based on the global visual similarity between objects. Using functional Magnetic Resonance Imaging (fMRI) we found that the damaged as well as the contralateral, structurally intact right LOC failed to show any object-selective fMRI activity, though the latter retained selectivity for faces. Thus, unilateral damage to the left LOC led to a bilateral breakdown of neural responses to a specific stimulus class (objects and artefacts) while preserving the response to a different stimulus class (faces). These findings indicate that representations of structure necessary for the identification of objects crucially rely on bilateral, distributed coding of shape features. Copyright © 2014 Elsevier Ltd. All rights reserved.

Understanding Current Safety Issues for Trajectory Based Operations

NASA Technical Reports Server (NTRS)

Feary, Michael; Stewart, Michael

2016-01-01

Increases in procedural complexity were investigated as a possible contributor to flight path deviations in airline operations. Understanding current operational issues and their causes must be embraced to maintain current safety standards while increasing future functionality. ASRS data and expert narratives were used to discover factors relating to pilot deviations. Our investigation pointed to ATC intervention, automation confusion, procedure design, and mixed equipment as primary issues. Future work will need to include objective data and mitigation strategies.

A Framework for Hierarchical Perception-Action Learning Utilizing Fuzzy Reasoning.

PubMed

Windridge, David; Felsberg, Michael; Shaukat, Affan

2013-02-01

Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.

Getting a Grip on Complexes

PubMed Central

Nie, Yan; Viola, Cristina; Bieniossek, Christoph; Trowitzsch, Simon; Vijay-achandran, Lakshmi Sumitra; Chaillet, Maxime; Garzoni, Frederic; Berger, Imre

2009-01-01

We are witnessing tremendous advances in our understanding of the organization of life. Complete genomes are being deciphered with ever increasing speed and accuracy, thereby setting the stage for addressing the entire gene product repertoire of cells, towards understanding whole biological systems. Advances in bioinformatics and mass spectrometric techniques have revealed the multitude of interactions present in the proteome. Multiprotein complexes are emerging as a paramount cornerstone of biological activity, as many proteins appear to participate, stably or transiently, in large multisubunit assemblies. Analysis of the architecture of these assemblies and their manifold interactions is imperative for understanding their function at the molecular level. Structural genomics efforts have fostered the development of many technologies towards achieving the throughput required for studying system-wide single proteins and small interaction motifs at high resolution. The present shift in focus towards large multiprotein complexes, in particular in eukaryotes, now calls for a likewise concerted effort to develop and provide new technologies that are urgently required to produce in quality and quantity the plethora of multiprotein assemblies that form the complexome, and to routinely study their structure and function at the molecular level. Current efforts towards this objective are summarized and reviewed in this contribution. PMID:20514218

Preface: cardiac control pathways: signaling and transport phenomena.

PubMed

Sideman, Samuel

2008-03-01

Signaling is part of a complex system of communication that governs basic cellular functions and coordinates cellular activity. Transfer of ions and signaling molecules and their interactions with appropriate receptors, transmembrane transport, and the consequent intracellular interactions and functional cellular response represent a complex system of interwoven phenomena of transport, signaling, conformational changes, chemical activation, and/or genetic expression. The well-being of the cell thus depends on a harmonic orchestration of all these events and the existence of control mechanisms that assure the normal behavior of the various parameters involved and their orderly expression. The ability of cells to sustain life by perceiving and responding correctly to their microenvironment is the basis for development, tissue repair, and immunity, as well as normal tissue homeostasis. Natural deviations, or human-induced interference in the signaling pathways and/or inter- and intracellular transport and information transfer, are responsible for the generation, modulation, and control of diseases. The present overview aims to highlight some major topics of the highly complex cellular information transfer processes and their control mechanisms. Our goal is to contribute to the understanding of the normal and pathophysiological phenomena associated with cardiac functions so that more efficient therapeutic modalities can be developed. Our objective in this volume is to identify and enhance the study of some basic passive and active physical and chemical transport phenomena, physiological signaling pathways, and their biological consequences.

Automated Surgical Approach Planning for Complex Skull Base Targets: Development and Validation of a Cost Function and Semantic At-las.

PubMed

Aghdasi, Nava; Whipple, Mark; Humphreys, Ian M; Moe, Kris S; Hannaford, Blake; Bly, Randall A

2018-06-01

Successful multidisciplinary treatment of skull base pathology requires precise preoperative planning. Current surgical approach (pathway) selection for these complex procedures depends on an individual surgeon's experiences and background training. Because of anatomical variation in both normal tissue and pathology (eg, tumor), a successful surgical pathway used on one patient is not necessarily the best approach on another patient. The question is how to define and obtain optimized patient-specific surgical approach pathways? In this article, we demonstrate that the surgeon's knowledge and decision making in preoperative planning can be modeled by a multiobjective cost function in a retrospective analysis of actual complex skull base cases. Two different approaches- weighted-sum approach and Pareto optimality-were used with a defined cost function to derive optimized surgical pathways based on preoperative computed tomography (CT) scans and manually designated pathology. With the first method, surgeon's preferences were input as a set of weights for each objective before the search. In the second approach, the surgeon's preferences were used to select a surgical pathway from the computed Pareto optimal set. Using preoperative CT and magnetic resonance imaging, the patient-specific surgical pathways derived by these methods were similar (85% agreement) to the actual approaches performed on patients. In one case where the actual surgical approach was different, revision surgery was required and was performed utilizing the computationally derived approach pathway.

Engineering complex orthopaedic tissues via strategic biomimicry.

PubMed

Qu, Dovina; Mosher, Christopher Z; Boushell, Margaret K; Lu, Helen H

2015-03-01

The primary current challenge in regenerative engineering resides in the simultaneous formation of more than one type of tissue, as well as their functional assembly into complex tissues or organ systems. Tissue-tissue synchrony is especially important in the musculoskeletal system, wherein overall organ function is enabled by the seamless integration of bone with soft tissues such as ligament, tendon, or cartilage, as well as the integration of muscle with tendon. Therefore, in lieu of a traditional single-tissue system (e.g., bone, ligament), composite tissue scaffold designs for the regeneration of functional connective tissue units (e.g., bone-ligament-bone) are being actively investigated. Closely related is the effort to re-establish tissue-tissue interfaces, which is essential for joining these tissue building blocks and facilitating host integration. Much of the research at the forefront of the field has centered on bioinspired stratified or gradient scaffold designs which aim to recapitulate the structural and compositional inhomogeneity inherent across distinct tissue regions. As such, given the complexity of these musculoskeletal tissue units, the key question is how to identify the most relevant parameters for recapitulating the native structure-function relationships in the scaffold design. Therefore, the focus of this review, in addition to presenting the state-of-the-art in complex scaffold design, is to explore how strategic biomimicry can be applied in engineering tissue connectivity. The objective of strategic biomimicry is to avoid over-engineering by establishing what needs to be learned from nature and defining the essential matrix characteristics that must be reproduced in scaffold design. Application of this engineering strategy for the regeneration of the most common musculoskeletal tissue units (e.g., bone-ligament-bone, muscle-tendon-bone, cartilage-bone) will be discussed in this review. It is anticipated that these exciting efforts will enable integrative and functional repair of soft tissue injuries, and moreover, lay the foundation for the development of composite tissue systems and ultimately, total limb or joint regeneration.

Engineering Complex Orthopaedic Tissues via Strategic Biomimicry

PubMed Central

Qu, Dovina; Mosher, Christopher Z.; Boushell, Margaret K.; Lu, Helen H.

2014-01-01

The primary current challenge in regenerative engineering resides in the simultaneous formation of more than one type of tissue, as well as their functional assembly into complex tissues or organ systems. Tissue-tissue synchrony is especially important in the musculoskeletal system, whereby overall organ function is enabled by the seamless integration of bone with soft tissues such as ligament, tendon, or cartilage, as well as the integration of muscle with tendon. Therefore, in lieu of a traditional single-tissue system (e.g. bone, ligament), composite tissue scaffold designs for the regeneration of functional connective tissue units (e.g. bone-ligament-bone) are being actively investigated. Closely related is the effort to re-establish tissue-tissue interfaces, which is essential for joining these tissue building blocks and facilitating host integration. Much of the research at the forefront of the field has centered on bioinspired stratified or gradient scaffold designs which aim to recapitulate the structural and compositional inhomogeneity inherent across distinct tissue regions. As such, given the complexity of these musculoskeletal tissue units, the key question is how to identify the most relevant parameters for recapitulating the native structure-function relationships in the scaffold design. Therefore, the focus of this review, in addition to presenting the state-of-the-art in complex scaffold design, is to explore how strategic biomimicry can be applied in engineering tissue connectivity. The objective of strategic biomimicry is to avoid over-engineering by establishing what needs to be learned from nature and defining the essential matrix characteristics that must be reproduced in scaffold design. Application of this engineering strategy for the regeneration of the most common musculoskeletal tissue units (e.g. bone-ligament-bone, muscle-tendon-bone, cartilage-bone) will be discussed in this review. It is anticipated that these exciting efforts will enable integrative and functional repair of soft tissue injuries, and moreover, lay the foundation for the development of composite tissue systems and ultimately, total limb or joint regeneration. PMID:25465616

Exocyst Complex Protein Expression in the Human Placenta

PubMed Central

Gonzalez, I.M.; Ackerman, W.E.; Vandre, D.D.; Robinson, J.M.

2014-01-01

Introduction Protein production and secretion are essential to syncytiotrophoblast function and are associated with cytotrophoblast cell fusion and differentiation. Syncytiotrophoblast hormone secretion is a crucial determinant of maternal-fetal health, and can be misregulated in pathological pregnancies. Although, polarized secretion is a key component of placental function, the mechanisms underlying this process are poorly understood. Objective While the octameric exocyst complex is classically regarded as a master regulator of secretion in various mammalian systems, its expression in the placenta remained unexplored. We hypothesized that the syncytiotrophoblast would express all exocyst complex components and effector proteins requisite for vesicle-mediated secretion more abundantly than cytotrophoblasts in tissue specimens. Methods A two-tiered immunobiological approach was utilized to characterize exocyst and ancillary proteins in normal, term human placentas. Exocyst protein expression and localization was documented in tissue homogenates via immunoblotting and immunofluorescence labeling of placental sections. Results The eight exocyst proteins, EXOC1, 2, 3, 4, 5, 6, 7, and 8, were found in the human placenta. In addition, RAB11, an important exocyst complex modulator, was also expressed. Exocyst and Rab protein expression appeared to be regulated during trophoblast differentiation, as the syncytiotrophoblast expressed these proteins with little, if any, expression in cytotrophoblast cells. Additionally, exocyst proteins were localized at or near the syncytiotrophoblast apical membrane, the major site of placental secretion Discussion/Conclusion Our findings highlight exocyst protein expression as novel indicators of trophoblast differentiation. The exocyst’s regulated localization within the syncytiotrophoblast in conjunction with its well known functions suggests a possible role in placental polarized secretion PMID:24856041

The impact of symptomatic mild traumatic brain injury on complex everyday activities and the link with alterations in cerebral functioning: Exploratory case studies.

PubMed

Bottari, Carolina; Gosselin, Nadia; Chen, Jen-Kai; Ptito, Alain

2017-07-01

The objective of the study was to explore the neurophysiological correlates of altered functional independence using functional magnetic resonance imaging (fMRI) and event-related potentials (ERP) after a mild traumatic brain injury (mTBI). The participants consisted of three individuals with symptomatic mTBI (3.9 ± 3.6 months post-mTBI) and 12 healthy controls. The main measures used were the Instrumental Activities of Daily Living (IADL) Profile observation-based assessment; a visual externally ordered working memory task combined to event-related potentials (ERP) and fMRI recordings; neuropsychological tests; post-concussion symptoms questionnaires; and the Activities of Daily Living (ADL) Profile interview. Compared to normal controls, all three patients had difficulty with a real-world complex budgeting activity due to deficits in planning, ineffective strategy use and/or a prolonged time to detect and correct errors. Reduced activations in the right mid-dorsolateral prefrontal cortex on fMRI as well as abnormal frontal or parietal components of the ERP occurred alongside these deficits. Results of this exploratory study suggest that reduced independence in complex everyday activities in symptomatic mTBI may be at least partly explained by a decrease in brain activation in the prefrontal cortex, abnormal ERP, or slower reaction times on working memory tasks. The study presents an initial attempt at combining research in neuroscience with ecological real-world evaluation research to further our understanding of the difficulties in complex everyday activities experienced by individuals with mTBI.

Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär

2017-02-01

The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.

Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

PubMed Central

Cadieu, Charles F.; Hong, Ha; Yamins, Daniel L. K.; Pinto, Nicolas; Ardila, Diego; Solomon, Ethan A.; Majaj, Najib J.; DiCarlo, James J.

2014-01-01

The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition). This remarkable performance is mediated by the representation formed in inferior temporal (IT) cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs). It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of “kernel analysis” that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds. PMID:25521294

Visual Short-Term Memory Capacity for Simple and Complex Objects

ERIC Educational Resources Information Center

Luria, Roy; Sessa, Paola; Gotler, Alex; Jolicoeur, Pierre; Dell'Acqua, Roberto

2010-01-01

Does the capacity of visual short-term memory (VSTM) depend on the complexity of the objects represented in memory? Although some previous findings indicated lower capacity for more complex stimuli, other results suggest that complexity effects arise during retrieval (due to errors in the comparison process with what is in memory) that is not…

Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

PubMed

Kujur, Alice; Saxena, Maneesha S; Bajaj, Deepak; Laxmi; Parida, Swarup K

2013-12-01

The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

Ecological Virtual Reality Evaluation of Neglect Symptoms (EVENS): Effects of Virtual Scene Complexity in the Assessment of Poststroke Unilateral Spatial Neglect.

PubMed

Ogourtsova, Tatiana; Archambault, Philippe; Sangani, Samir; Lamontagne, Anouk

2018-01-01

Unilateral spatial neglect (USN) is a highly prevalent and disabling poststroke impairment. USN is traditionally assessed with paper-and-pencil tests that lack ecological validity, generalization to real-life situations and are easily compensated for in chronic stages. Virtual reality (VR) can, however, counteract these limitations. We aimed to examine the feasibility of a novel assessment of USN symptoms in a functional shopping activity, the Ecological VR-based Evaluation of Neglect Symptoms (EVENS). EVENS is immersive and consists of simple and complex 3-dimensional scenes depicting grocery shopping shelves, where joystick-based object detection and navigation tasks are performed while seated. Effects of virtual scene complexity on navigational and detection abilities in patients with (USN+, n = 12) and without (USN-, n = 15) USN following a right hemisphere stroke and in age-matched healthy controls (HC, n = 9) were determined. Longer detection times, larger mediolateral deviations from ideal paths and longer navigation times were found in USN+ versus USN- and HC groups, particularly in the complex scene. EVENS detected lateralized and nonlateralized USN-related deficits, performance alterations that were dependent or independent of USN severity, and performance alterations in 3 USN- subjects versus HC. EVENS' environmental changing complexity, along with the functional tasks of far space detection and navigation can potentially be clinically relevant and warrant further empirical investigation. Findings are discussed in terms of attentional models, lateralized versus nonlateralized deficits in USN, and tasks-specific mechanisms.

THREE-DIMENSIONAL RANDOM ACCESS MULTIPHOTON MICROSCOPY FOR FAST FUNCTIONAL IMAGING OF NEURONAL ACTIVITY

PubMed Central

Reddy, Gaddum Duemani; Kelleher, Keith; Fink, Rudy; Saggau, Peter

2009-01-01

The dynamic ability of neuronal dendrites to shape and integrate synaptic responses is the hallmark of information processing in the brain. Effectively studying this phenomenon requires concurrent measurements at multiple sites on live neurons. Significant progress has been made by optical imaging systems which combine confocal and multiphoton microscopy with inertia-free laser scanning. However, all systems developed to date restrict fast imaging to two dimensions. This severely limits the extent to which neurons can be studied, since they represent complex three-dimensional (3D) structures. Here we present a novel imaging system that utilizes a unique arrangement of acousto-optic deflectors to steer a focused ultra-fast laser beam to arbitrary locations in 3D space without moving the objective lens. As we demonstrate, this highly versatile random-access multiphoton microscope supports functional imaging of complex 3D cellular structures such as neuronal dendrites or neural populations at acquisition rates on the order of tens of kilohertz. PMID:18432198

On the effectiveness of noise masks: naturalistic vs. un-naturalistic image statistics.

PubMed

Hansen, Bruce C; Hess, Robert F

2012-05-01

It has been argued that the human visual system is optimized for identification of broadband objects embedded in stimuli possessing orientation averaged power spectra fall-offs that obey the 1/f(β) relationship typically observed in natural scene imagery (i.e., β=2.0 on logarithmic axes). Here, we were interested in whether individual spatial channels leading to recognition are functionally optimized for narrowband targets when masked by noise possessing naturalistic image statistics (β=2.0). The current study therefore explores the impact of variable β noise masks on the identification of narrowband target stimuli ranging in spatial complexity, while simultaneously controlling for physical or perceived differences between the masks. The results show that β=2.0 noise masks produce the largest identification thresholds regardless of target complexity, and thus do not seem to yield functionally optimized channel processing. The differential masking effects are discussed in the context of contrast gain control. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Role models for complex networks

NASA Astrophysics Data System (ADS)

Reichardt, J.; White, D. R.

2007-11-01

We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.

A Simplified Design with a Toothed Belt and Non-Circular Pulleys to Separate Parts from a Magazine File

NASA Astrophysics Data System (ADS)

Hanke, U.; Modler, K.-H.; Neumann, R.; Fischer, C.

The objective of this paper is to simplify a very complex guidance mechanism, currently used for lid separating issues in a packaging-machine. The task of this machine is to pick up a lid from a magazine file, rotate it around 180° and place it on tins. The developed mechanism works successfully but with a very complex construction. It consists of a planetary cam mechanism, combined with a toothed gear (with a constant transmission ratio) and a guiding mechanism with a toothed belt and circular pulleys. Such complex constructions are very common in industrial solutions. The idea of the authors is to show a much simpler design in solving the same problem. They developed a guidance mechanism realizing the same function, consisting only of a toothed belt with non-circular pulleys. The used parts are common trade articles.

Vectors a Fortran 90 module for 3-dimensional vector and dyadic arithmetic

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

Brock, B.C.

1998-02-01

A major advance contained in the new Fortran 90 language standard is the ability to define new data types and the operators associated with them. Writing computer code to implement computations with real and complex three-dimensional vectors and dyadics is greatly simplified if the equations can be implemented directly, without the need to code the vector arithmetic explicitly. The Fortran 90 module described here defines new data types for real and complex 3-dimensional vectors and dyadics, along with the common operations needed to work with these objects. Routines to allow convenient initialization and output of the new types are alsomore » included. In keeping with the philosophy of data abstraction, the details of the implementation of the data types are maintained private, and the functions and operators are made generic to simplify the combining of real, complex, single- and double-precision vectors and dyadics.« less

3D Bioprinting of Tissue/Organ Models.

PubMed

Pati, Falguni; Gantelius, Jesper; Svahn, Helene Andersson

2016-04-04

In vitro tissue/organ models are useful platforms that can facilitate systematic, repetitive, and quantitative investigations of drugs/chemicals. The primary objective when developing tissue/organ models is to reproduce physiologically relevant functions that typically require complex culture systems. Bioprinting offers exciting prospects for constructing 3D tissue/organ models, as it enables the reproducible, automated production of complex living tissues. Bioprinted tissues/organs may prove useful for screening novel compounds or predicting toxicity, as the spatial and chemical complexity inherent to native tissues/organs can be recreated. In this Review, we highlight the importance of developing 3D in vitro tissue/organ models by 3D bioprinting techniques, characterization of these models for evaluating their resemblance to native tissue, and their application in the prioritization of lead candidates, toxicity testing, and as disease/tumor models. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mitochondrial network complexity emerges from fission/fusion dynamics.

PubMed

Zamponi, Nahuel; Zamponi, Emiliano; Cannas, Sergio A; Billoni, Orlando V; Helguera, Pablo R; Chialvo, Dante R

2018-01-10

Mitochondrial networks exhibit a variety of complex behaviors, including coordinated cell-wide oscillations of energy states as well as a phase transition (depolarization) in response to oxidative stress. Since functional and structural properties are often interwinded, here we characterized the structure of mitochondrial networks in mouse embryonic fibroblasts using network tools and percolation theory. Subsequently we perturbed the system either by promoting the fusion of mitochondrial segments or by inducing mitochondrial fission. Quantitative analysis of mitochondrial clusters revealed that structural parameters of healthy mitochondria laid in between the extremes of highly fragmented and completely fusioned networks. We confirmed our results by contrasting our empirical findings with the predictions of a recently described computational model of mitochondrial network emergence based on fission-fusion kinetics. Altogether these results offer not only an objective methodology to parametrize the complexity of this organelle but also support the idea that mitochondrial networks behave as critical systems and undergo structural phase transitions.

Visuo-spatial orienting during active exploratory behavior: Processing of task-related and stimulus-related signals.

PubMed

Macaluso, Emiliano; Ogawa, Akitoshi

2018-05-01

Functional imaging studies have associated dorsal and ventral fronto-parietal regions with the control of visuo-spatial attention. Previous studies demonstrated that the activity of both the dorsal and the ventral attention systems can be modulated by many different factors, related both to the stimuli and the task. However, the vast majority of this work utilized stereotyped paradigms with simple and repeated stimuli. This is at odd with any real life situation that instead involve complex combinations of different types of co-occurring signals, thus raising the question of the ecological significance of the previous findings. Here we investigated how the brain responds to task-related and stimulus-related signals using an innovative approach that involved active exploration of a virtual environment. This enabled us to study visuo-spatial orienting in conditions entailing a dynamic and coherent flow of visual signals, to some extent analogous to real life situations. The environment comprised colored/textured spheres and cubes, which allowed us to implement a standard feature-conjunction search task (task-related signals), and included one physically salient object that served to track the processing of stimulus-related signals. The imaging analyses showed that the posterior parietal cortex (PPC) activated when the participants' gaze was directed towards the salient-objects. By contrast, the right inferior partial cortex was associated with the processing of the target-objects and of distractors that shared the target-color and shape, consistent with goal-directed template-matching operations. The study highlights the possibility of combining measures of gaze orienting and functional imaging to investigate the processing of different types of signals during active behavior in complex environments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visual Input to the Drosophila Central Complex by Developmentally and Functionally Distinct Neuronal Populations.

PubMed

Omoto, Jaison Jiro; Keleş, Mehmet Fatih; Nguyen, Bao-Chau Minh; Bolanos, Cheyenne; Lovick, Jennifer Kelly; Frye, Mark Arthur; Hartenstein, Volker

2017-04-24

The Drosophila central brain consists of stereotyped neural lineages, developmental-structural units of macrocircuitry formed by the sibling neurons of single progenitors called neuroblasts. We demonstrate that the lineage principle guides the connectivity and function of neurons, providing input to the central complex, a collection of neuropil compartments important for visually guided behaviors. One of these compartments is the ellipsoid body (EB), a structure formed largely by the axons of ring (R) neurons, all of which are generated by a single lineage, DALv2. Two further lineages, DALcl1 and DALcl2, produce neurons that connect the anterior optic tubercle, a central brain visual center, with R neurons. Finally, DALcl1/2 receive input from visual projection neurons of the optic lobe medulla, completing a three-legged circuit that we call the anterior visual pathway (AVP). The AVP bears a fundamental resemblance to the sky-compass pathway, a visual navigation circuit described in other insects. Neuroanatomical analysis and two-photon calcium imaging demonstrate that DALcl1 and DALcl2 form two parallel channels, establishing connections with R neurons located in the peripheral and central domains of the EB, respectively. Although neurons of both lineages preferentially respond to bright objects, DALcl1 neurons have small ipsilateral, retinotopically ordered receptive fields, whereas DALcl2 neurons share a large excitatory receptive field in the contralateral hemifield. DALcl2 neurons become inhibited when the object enters the ipsilateral hemifield and display an additional excitation after the object leaves the field of view. Thus, the spatial position of a bright feature, such as a celestial body, may be encoded within this pathway. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-objective calibration and uncertainty analysis of hydrologic models; A comparative study between formal and informal methods

NASA Astrophysics Data System (ADS)

Shafii, M.; Tolson, B.; Matott, L. S.

2012-04-01

Hydrologic modeling has benefited from significant developments over the past two decades. This has resulted in building of higher levels of complexity into hydrologic models, which eventually makes the model evaluation process (parameter estimation via calibration and uncertainty analysis) more challenging. In order to avoid unreasonable parameter estimates, many researchers have suggested implementation of multi-criteria calibration schemes. Furthermore, for predictive hydrologic models to be useful, proper consideration of uncertainty is essential. Consequently, recent research has emphasized comprehensive model assessment procedures in which multi-criteria parameter estimation is combined with statistically-based uncertainty analysis routines such as Bayesian inference using Markov Chain Monte Carlo (MCMC) sampling. Such a procedure relies on the use of formal likelihood functions based on statistical assumptions, and moreover, the Bayesian inference structured on MCMC samplers requires a considerably large number of simulations. Due to these issues, especially in complex non-linear hydrological models, a variety of alternative informal approaches have been proposed for uncertainty analysis in the multi-criteria context. This study aims at exploring a number of such informal uncertainty analysis techniques in multi-criteria calibration of hydrological models. The informal methods addressed in this study are (i) Pareto optimality which quantifies the parameter uncertainty using the Pareto solutions, (ii) DDS-AU which uses the weighted sum of objective functions to derive the prediction limits, and (iii) GLUE which describes the total uncertainty through identification of behavioral solutions. The main objective is to compare such methods with MCMC-based Bayesian inference with respect to factors such as computational burden, and predictive capacity, which are evaluated based on multiple comparative measures. The measures for comparison are calculated both for calibration and evaluation periods. The uncertainty analysis methodologies are applied to a simple 5-parameter rainfall-runoff model, called HYMOD.

Hippocampus, perirhinal cortex, and complex visual discriminations in rats and humans

PubMed Central

Hales, Jena B.; Broadbent, Nicola J.; Velu, Priya D.

2015-01-01

Structures in the medial temporal lobe, including the hippocampus and perirhinal cortex, are known to be essential for the formation of long-term memory. Recent animal and human studies have investigated whether perirhinal cortex might also be important for visual perception. In our study, using a simultaneous oddity discrimination task, rats with perirhinal lesions were impaired and did not exhibit the normal preference for exploring the odd object. Notably, rats with hippocampal lesions exhibited the same impairment. Thus, the deficit is unlikely to illuminate functions attributed specifically to perirhinal cortex. Both lesion groups were able to acquire visual discriminations involving the same objects used in the oddity task. Patients with hippocampal damage or larger medial temporal lobe lesions were intact in a similar oddity task that allowed participants to explore objects quickly using eye movements. We suggest that humans were able to rely on an intact working memory capacity to perform this task, whereas rats (who moved slowly among the objects) needed to rely on long-term memory. PMID:25593294

Neuronal integration in visual cortex elevates face category tuning to conscious face perception

PubMed Central

Fahrenfort, Johannes J.; Snijders, Tineke M.; Heinen, Klaartje; van Gaal, Simon; Scholte, H. Steven; Lamme, Victor A. F.

2012-01-01

The human brain has the extraordinary capability to transform cluttered sensory input into distinct object representations. For example, it is able to rapidly and seemingly without effort detect object categories in complex natural scenes. Surprisingly, category tuning is not sufficient to achieve conscious recognition of objects. What neural process beyond category extraction might elevate neural representations to the level where objects are consciously perceived? Here we show that visible and invisible faces produce similar category-selective responses in the ventral visual cortex. The pattern of neural activity evoked by visible faces could be used to decode the presence of invisible faces and vice versa. However, only visible faces caused extensive response enhancements and changes in neural oscillatory synchronization, as well as increased functional connectivity between higher and lower visual areas. We conclude that conscious face perception is more tightly linked to neural processes of sustained information integration and binding than to processes accommodating face category tuning. PMID:23236162

A Fuzzy Robust Optimization Model for Waste Allocation Planning Under Uncertainty

PubMed Central

Xu, Ye; Huang, Guohe; Xu, Ling

2014-01-01

Abstract In this study, a fuzzy robust optimization (FRO) model was developed for supporting municipal solid waste management under uncertainty. The Development Zone of the City of Dalian, China, was used as a study case for demonstration. Comparing with traditional fuzzy models, the FRO model made improvement by considering the minimization of the weighted summation among the expected objective values, the differences between two extreme possible objective values, and the penalty of the constraints violation as the objective function, instead of relying purely on the minimization of expected value. Such an improvement leads to enhanced system reliability and the model becomes especially useful when multiple types of uncertainties and complexities are involved in the management system. Through a case study, the applicability of the FRO model was successfully demonstrated. Solutions under three future planning scenarios were provided by the FRO model, including (1) priority on economic development, (2) priority on environmental protection, and (3) balanced consideration for both. The balanced scenario solution was recommended for decision makers, since it respected both system economy and reliability. The model proved valuable in providing a comprehensive profile about the studied system and helping decision makers gain an in-depth insight into system complexity and select cost-effective management strategies. PMID:25317037

A Fuzzy Robust Optimization Model for Waste Allocation Planning Under Uncertainty.

PubMed

Xu, Ye; Huang, Guohe; Xu, Ling

2014-10-01

In this study, a fuzzy robust optimization (FRO) model was developed for supporting municipal solid waste management under uncertainty. The Development Zone of the City of Dalian, China, was used as a study case for demonstration. Comparing with traditional fuzzy models, the FRO model made improvement by considering the minimization of the weighted summation among the expected objective values, the differences between two extreme possible objective values, and the penalty of the constraints violation as the objective function, instead of relying purely on the minimization of expected value. Such an improvement leads to enhanced system reliability and the model becomes especially useful when multiple types of uncertainties and complexities are involved in the management system. Through a case study, the applicability of the FRO model was successfully demonstrated. Solutions under three future planning scenarios were provided by the FRO model, including (1) priority on economic development, (2) priority on environmental protection, and (3) balanced consideration for both. The balanced scenario solution was recommended for decision makers, since it respected both system economy and reliability. The model proved valuable in providing a comprehensive profile about the studied system and helping decision makers gain an in-depth insight into system complexity and select cost-effective management strategies.

A Possible Role for End-Stopped V1 Neurons in the Perception of Motion: A Computational Model

PubMed Central

Zarei Eskikand, Parvin; Kameneva, Tatiana; Ibbotson, Michael R.; Burkitt, Anthony N.; Grayden, David B.

2016-01-01

We present a model of the early stages of processing in the visual cortex, in particular V1 and MT, to investigate the potential role of end-stopped V1 neurons in solving the aperture problem. A hierarchical network is used in which the incoming motion signals provided by complex V1 neurons and end-stopped V1 neurons proceed to MT neurons at the next stage. MT neurons are categorized into two types based on their function: integration and segmentation. The role of integration neurons is to propagate unambiguous motion signals arriving from those V1 neurons that emphasize object terminators (e.g. corners). Segmentation neurons detect the discontinuities in the input stimulus to control the activity of integration neurons. Although the activity of the complex V1 neurons at the terminators of the object accurately represents the direction of the motion, their level of activity is less than the activity of the neurons along the edges. Therefore, a model incorporating end-stopped neurons is essential to suppress ambiguous motion signals along the edges of the stimulus. It is shown that the unambiguous motion signals at terminators propagate over the rest of the object to achieve an accurate representation of motion. PMID:27741307

Continuous motion scan ptychography: Characterization for increased speed in coherent x-ray imaging

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

Deng, Junjing; Nashed, Youssef S. G.; Chen, Si

Ptychography is a coherent diffraction imaging (CDI) method for extended objects in which diffraction patterns are acquired sequentially from overlapping coherent illumination spots. The object’s complex transmission function can be reconstructed from those diffraction patterns at a spatial resolution limited only by the scattering strength of the object and the detector geometry. Most experiments to date have positioned the illumination spots on the sample using a move-settle-measure sequence in which the move and settle steps can take longer to complete than the measure step. We describe here the use of a continuous “fly-scan” mode for ptychographic data collection in whichmore » the sample is moved continuously, so that the experiment resembles one of integrating the diffraction patterns from multiple probe positions. This allows one to use multiple probe mode reconstruction methods to obtain an image of the object and also of the illumination function. We show in simulations, and in x-ray imaging experiments, some of the characteristics of fly-scan ptychography, including a factor of 25 reduction in the data acquisition time. This approach will become increasingly important as brighter x-ray sources are developed, such as diffraction limited storage rings.« less

Continuous motion scan ptychography: Characterization for increased speed in coherent x-ray imaging

DOE PAGES

Deng, Junjing; Nashed, Youssef S. G.; Chen, Si; ...

2015-02-23

Ptychography is a coherent diffraction imaging (CDI) method for extended objects in which diffraction patterns are acquired sequentially from overlapping coherent illumination spots. The object’s complex transmission function can be reconstructed from those diffraction patterns at a spatial resolution limited only by the scattering strength of the object and the detector geometry. Most experiments to date have positioned the illumination spots on the sample using a move-settle-measure sequence in which the move and settle steps can take longer to complete than the measure step. We describe here the use of a continuous “fly-scan” mode for ptychographic data collection in whichmore » the sample is moved continuously, so that the experiment resembles one of integrating the diffraction patterns from multiple probe positions. This allows one to use multiple probe mode reconstruction methods to obtain an image of the object and also of the illumination function. We show in simulations, and in x-ray imaging experiments, some of the characteristics of fly-scan ptychography, including a factor of 25 reduction in the data acquisition time. This approach will become increasingly important as brighter x-ray sources are developed, such as diffraction limited storage rings.« less

Dypas: A dynamic payload scheduler for shuttle missions

NASA Technical Reports Server (NTRS)

Davis, Stephen

1988-01-01

Decision and analysis systems have had broad and very practical application areas in the human decision making process. These software systems range from the help sections in simple accounting packages, to the more complex computer configuration programs. Dypas is a decision and analysis system that aids prelaunch shutlle scheduling, and has added functionality to aid the rescheduling done in flight. Dypas is written in Common Lisp on a Symbolics Lisp machine. Dypas differs from other scheduling programs in that it can draw its knowledge from different rule bases and apply them to different rule interpretation schemes. The system has been coded with Flavors, an object oriented extension to Common Lisp on the Symbolics hardware. This allows implementation of objects (experiments) to better match the problem definition, and allows a more coherent solution space to be developed. Dypas was originally developed to test a programmer's aptitude toward Common Lisp and the Symbolics software environment. Since then the system has grown into a large software effort with several programmers and researchers thrown into the effort. Dypas is currently using two expert systems and three inferencing procedures to generate a many object schedule. The paper will review the abilities of Dypas and comment on its functionality.

NanoDesign: Concepts and Software for a Nanotechnology Based on Functionalized Fullerenes

NASA Technical Reports Server (NTRS)

Globus, Al; Jaffe, Richard; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Eric Drexler has proposed a hypothetical nanotechnology based on diamond and investigated the properties of such molecular systems. While attractive, diamonoid nanotechnology is not physically accessible with straightforward extensions of current laboratory techniques. We propose a nanotechnology based on functionalized fullerenes and investigate carbon nanotube based gears with teeth added via a benzyne reaction known to occur with C60. The gears are single-walled carbon nanotubes with appended coenzyme groups for teeth. Fullerenes are in widespread laboratory use and can be functionalized in many ways. Companion papers computationally demonstrate the properties of these gears (they appear to work) and the accessibility of the benzyne/nanotube reaction. This paper describes the molecular design techniques and rationale as well as the software that implements these design techniques. The software is a set of persistent C++ objects controlled by TCL command scripts. The c++/tcl interface is automatically generated by a software system called tcl_c++ developed by the author and described here. The objects keep track of different portions of the molecular machinery to allow different simulation techniques and boundary conditions to be applied as appropriate. This capability has been required to demonstrate (computationally) our gear's feasibility. A new distributed software architecture featuring a WWW universal client, CORBA distributed objects, and agent software is under consideration. The software architecture is intended to eventually enable a widely disbursed group to develop complex simulated molecular machines.

A computer vision based candidate for functional balance test.

PubMed

Nalci, Alican; Khodamoradi, Alireza; Balkan, Ozgur; Nahab, Fatta; Garudadri, Harinath

2015-08-01

Balance in humans is a motor skill based on complex multimodal sensing, processing and control. Ability to maintain balance in activities of daily living (ADL) is compromised due to aging, diseases, injuries and environmental factors. Center for Disease Control and Prevention (CDC) estimate of the costs of falls among older adults was $34 billion in 2013 and is expected to reach $54.9 billion in 2020. In this paper, we present a brief review of balance impairments followed by subjective and objective tools currently used in clinical settings for human balance assessment. We propose a novel computer vision (CV) based approach as a candidate for functional balance test. The test will take less than a minute to administer and expected to be objective, repeatable and highly discriminative in quantifying ability to maintain posture and balance. We present an informal study with preliminary data from 10 healthy volunteers, and compare performance with a balance assessment system called BTrackS Balance Assessment Board. Our results show high degree of correlation with BTrackS. The proposed system promises to be a good candidate for objective functional balance tests and warrants further investigations to assess validity in clinical settings, including acute care, long term care and assisted living care facilities. Our long term goals include non-intrusive approaches to assess balance competence during ADL in independent living environments.

DFT study of the interaction between DOTA chelator and competitive alkali metal ions.

PubMed

Frimpong, E; Skelton, A A; Honarparvar, B

2017-09-01

1, 4, 7, 10-tetraazacyclododecane-1, 4, 7, 10-tetracetic acid (DOTA) is an important chelator for radiolabeling of pharmaceuticals. The ability of alkali metals found in the body to complex with DOTA and compete with radio metal ions can alter the radiolabeling process. Non-covalent interactions between DOTA complexed with alkali metals Li + , Na + , K + and Rb + , are investigated with density functional theory using B3LYP and ωB97XD functionals. Conformational possibilities of DOTA were explored with a varying number of carboxylic pendant arms of DOTA in close proximity to the ions. It is found that the case in which four arms of DOTA are interacting with ions is more stable than other conformations. The objective of this study is to explore the electronic structure properties upon complexation of alkali metals Li + Na + , K + and Rb + with a DOTA chelator. Interaction energies, relaxation energies, entropies, Gibbs free energies and enthalpies show that the stability of DOTA, complexed with alkali metals decreases down the group of the periodic table. Implicit water solvation affects the complexation of DOTA-ions leading to decreases in the stability of the complexes. NBO analysis through the natural population charges and the second order perturbation theory, revealed a charge transfer between DOTA and alkali metals. Conceptual DFT-based properties such as HOMO/LUMO energies, ΔE HOMO-LUMO and chemical hardness and softness indicated a decrease in the chemical stability of DOTA-alkali metal complexes down the alkali metal series. This study serves as a guide to researchers in the field of organometallic chelators, particularly, radiopharmaceuticals in finding the efficient optimal match between chelators and various metal ions. Copyright © 2017 Elsevier Inc. All rights reserved.

A SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES

EPA Science Inventory

Evaluation and analysis of multiple objectives are very important in designing environmentally benign processes. They require a systematic procedure for solving multi-objective decision-making problems due to the complex nature of the problems and the need for complex assessment....

High fat, high sucrose diet causes cardiac mitochondrial dysfunction due in part to oxidative post-translational modification of mitochondrial complex II.

PubMed

Sverdlov, Aaron L; Elezaby, Aly; Behring, Jessica B; Bachschmid, Markus M; Luptak, Ivan; Tu, Vivian H; Siwik, Deborah A; Miller, Edward J; Liesa, Marc; Shirihai, Orian S; Pimentel, David R; Cohen, Richard A; Colucci, Wilson S

2015-01-01

Diet-induced obesity leads to metabolic heart disease (MHD) characterized by increased oxidative stress that may cause oxidative post-translational modifications (OPTM) of cardiac mitochondrial proteins. The functional consequences of OPTM of cardiac mitochondrial proteins in MHD are unknown. Our objective was to determine whether cardiac mitochondrial dysfunction in MHD due to diet-induced obesity is associated with cysteine OPTM. Male C57BL/6J mice were fed either a high-fat, high-sucrose (HFHS) or control diet for 8months. Cardiac mitochondria from HFHS-fed mice (vs. control diet) had an increased rate of H2O2 production, a decreased GSH/GSSG ratio, a decreased rate of complex II substrate-driven ATP synthesis and decreased complex II activity. Complex II substrate-driven ATP synthesis and complex II activity were partially restored ex-vivo by reducing conditions. A biotin switch assay showed that HFHS feeding increased cysteine OPTM in complex II subunits A (SDHA) and B (SDHB). Using iodo-TMT multiplex tags we found that HFHS feeding is associated with reversible oxidation of cysteines 89 and 231 in SDHA, and 100, 103 and 115 in SDHB. MHD due to consumption of a HFHS "Western" diet causes increased H2O2 production and oxidative stress in cardiac mitochondria associated with decreased ATP synthesis and decreased complex II activity. Impaired complex II activity and ATP production are associated with reversible cysteine OPTM of complex II. Possible sites of reversible cysteine OPTM in SDHA and SDHB were identified by iodo-TMT tag labeling. Mitochondrial ROS may contribute to the pathophysiology of MHD by impairing the function of complex II. This article is part of a Special Issue entitled "Mitochondria: From Basic Mitochondrial Biology to Cardiovascular Disease". Copyright © 2014 Elsevier Ltd. All rights reserved.

Universal approximators for multi-objective direct policy search in water reservoir management problems: a comparative analysis

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Mason, Emanuele; Castelletti, Andrea; Pianosi, Francesca

2014-05-01

The optimal operation of water resources systems is a wide and challenging problem due to non-linearities in the model and the objectives, high dimensional state-control space, and strong uncertainties in the hydroclimatic regimes. The application of classical optimization techniques (e.g., SDP, Q-learning, gradient descent-based algorithms) is strongly limited by the dimensionality of the system and by the presence of multiple, conflicting objectives. This study presents a novel approach which combines Direct Policy Search (DPS) and Multi-Objective Evolutionary Algorithms (MOEAs) to solve high-dimensional state and control space problems involving multiple objectives. DPS, also known as parameterization-simulation-optimization in the water resources literature, is a simulation-based approach where the reservoir operating policy is first parameterized within a given family of functions and, then, the parameters optimized with respect to the objectives of the management problem. The selection of a suitable class of functions to which the operating policy belong to is a key step, as it might restrict the search for the optimal policy to a subspace of the decision space that does not include the optimal solution. In the water reservoir literature, a number of classes have been proposed. However, many of these rules are based largely on empirical or experimental successes and they were designed mostly via simulation and for single-purpose reservoirs. In a multi-objective context similar rules can not easily inferred from the experience and the use of universal function approximators is generally preferred. In this work, we comparatively analyze two among the most common universal approximators: artificial neural networks (ANN) and radial basis functions (RBF) under different problem settings to estimate their scalability and flexibility in dealing with more and more complex problems. The multi-purpose HoaBinh water reservoir in Vietnam, accounting for hydropower production and flood control, is used as a case study. Preliminary results show that the RBF policy parametrization is more effective than the ANN one. In particular, the approximated Pareto front obtained with RBF control policies successfully explores the full tradeoff space between the two conflicting objectives, while most of the ANN solutions results to be Pareto-dominated by the RBF ones.

Identification of complex stiffness tensor from waveform reconstruction

NASA Astrophysics Data System (ADS)

Leymarie, N.; Aristégui, C.; Audoin, B.; Baste, S.

2002-03-01

An inverse method is proposed in order to determine the viscoelastic properties of composite-material plates from the plane-wave transmitted acoustic field. Analytical formulations of both the plate transmission coefficient and its first and second derivatives are established, and included in a two-step inversion scheme. Two objective functions to be minimized are then designed by considering the well-known maximum-likelihood principle and by using an analytic signal formulation. Through these innovative objective functions, the robustness of the inversion process against high level of noise in waveforms is improved and the method can be applied to a very thin specimen. The suitability of the inversion process for viscoelastic property identification is demonstrated using simulated data for composite materials with different anisotropy and damping degrees. A study of the effect of the rheologic model choice on the elastic property identification emphasizes the relevance of using a phenomenological description considering viscosity. Experimental characterizations show then the good reliability of the proposed approach. Difficulties arise experimentally for particular anisotropic media.

Job shop scheduling problem with late work criterion

NASA Astrophysics Data System (ADS)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.

Effects of Gait Self-Efficacy and Lower-Extremity Physical Function on Dual-Task Performance in Older Adults

PubMed Central

Banducci, Sarah E.; Daugherty, Ana M.; Fanning, Jason; Awick, Elizabeth A.; Porter, Gwenndolyn C.; Burzynska, Agnieszka; Shen, Sa; Kramer, Arthur F.; McAuley, Edward

2017-01-01

Objectives. Despite evidence of self-efficacy and physical function's influences on functional limitations in older adults, few studies have examined relationships in the context of complex, real-world tasks. The present study tested the roles of self-efficacy and physical function in predicting older adults' street-crossing performance in single- and dual-task simulations. Methods. Lower-extremity physical function, gait self-efficacy, and street-crossing success ratio were assessed in 195 older adults (60–79 years old) at baseline of a randomized exercise trial. During the street-crossing task, participants walked on a self-propelled treadmill in a virtual reality environment. Participants crossed the street without distraction (single-task trials) and conversed on a cell phone (dual-task trials). Structural equation modeling was used to test hypothesized associations independent of demographic and clinical covariates. Results. Street-crossing performance was better on single-task trials when compared with dual-task trials. Direct effects of self-efficacy and physical function on success ratio were observed in dual-task trials only. The total effect of self-efficacy was significant in both conditions. The indirect path through physical function was evident in the dual-task condition only. Conclusion. Physical function can predict older adults' performance on high fidelity simulations of complex, real-world tasks. Perceptions of function (i.e., self-efficacy) may play an even greater role. The trial is registered with United States National Institutes of Health ClinicalTrials.gov (ID: NCT01472744; Fit & Active Seniors Trial). PMID:28255557

IL-15 super-agonist (ALT-803) enhances natural killer (NK) cell function against ovarian cancer

PubMed Central

Felices, M.; Chu, S.; Kodal, B.; Bendzick, L.; Ryan, C.; Lenvik, A.J.; Boylan, K.L.M.; Wong, H.C.; Skubitz, A.P.N.; Miller, J.S.; Geller, M.A.

2017-01-01

Objective Natural killer (NK) cells represent a powerful immunotherapeutic target as they lyse tumors directly, do not require differentiation, and can elicit potent inflammatory responses. The objective of these studies was to use an IL-15 super-agonist complex, ALT-803 (Altor BioScience Corporation), to enhance the function of both normal and ovarian cancer patient derived NK cells by increasing cytotoxicity and cytokine production. Methods NK cell function from normal donor peripheral blood mononuclear cells (PBMCs) and ovarian cancer patient ascites was assessed using flow cytometry and chromium release assays +/− ALT-803 stimulation. To evaluate the ability of ALT-803 to enhance NK cell function in vivo against ovarian cancer, we used a MA148-luc ovarian cancer NOD scid gamma (NSG) xenogeneic mouse model with transferred human NK cells. Results ALT-803 potently enhanced functionality of NK cells against all ovarian cancer cell lines with significant increases seen in CD107a, IFNγ and TNFα expression depending on target cell line. Function was also rescued in NK cells derived from ovarian cancer patient ascites. Finally, only animals treated with intraperitoneal ALT-803 displayed an NK dependent significant decrease in tumor. Conclusions ALT-803 enhances NK cell cytotoxicity against ovarian cancer in vitro and in vivo and is able to rescue functionality of NK cells derived from ovarian cancer patient ascites. These findings suggest that ALT-803 has the potential to enhance NK-cell-based immunotherapeutic approaches for the treatment of ovarian cancer. PMID:28236454

The role of under-determined approximations in engineering and science application

NASA Technical Reports Server (NTRS)

Carpenter, William C.

1992-01-01

There is currently a great deal of interest in using response surfaces in the optimization of aircraft performance. The objective function and/or constraint equations involved in these optimization problems may come from numerous disciplines such as structures, aerodynamics, environmental engineering, etc. In each of these disciplines, the mathematical complexity of the governing equations usually dictates that numerical results be obtained from large computer programs such as a finite element method program. Thus, when performing optimization studies, response surfaces are a convenient way of transferring information from the various disciplines to the optimization algorithm as opposed to bringing all the sundry computer programs together in a massive computer code. Response surfaces offer another advantage in the optimization of aircraft structures. A characteristic of these types of optimization problems is that evaluation of the objective function and response equations (referred to as a functional evaluation) can be very expensive in a computational sense. Because of the computational expense in obtaining functional evaluations, the present study was undertaken to investigate under-determinined approximations. An under-determined approximation is one in which there are fewer training pairs (pieces of information about a function) than there are undetermined parameters (coefficients or weights) associated with the approximation. Both polynomial approximations and neural net approximations were examined. Three main example problems were investigated: (1) a function of one design variable was considered; (2) a function of two design variables was considered; and (3) a 35 bar truss with 4 design variables was considered.

Analysis and Recognition of Curve Type as The Basis of Object Recognition in Image

NASA Astrophysics Data System (ADS)

Nugraha, Nurma; Madenda, Sarifuddin; Indarti, Dina; Dewi Agushinta, R.; Ernastuti

2016-06-01

An object in an image when analyzed further will show the characteristics that distinguish one object with another object in an image. Characteristics that are used in object recognition in an image can be a color, shape, pattern, texture and spatial information that can be used to represent objects in the digital image. The method has recently been developed for image feature extraction on objects that share characteristics curve analysis (simple curve) and use the search feature of chain code object. This study will develop an algorithm analysis and the recognition of the type of curve as the basis for object recognition in images, with proposing addition of complex curve characteristics with maximum four branches that will be used for the process of object recognition in images. Definition of complex curve is the curve that has a point of intersection. By using some of the image of the edge detection, the algorithm was able to do the analysis and recognition of complex curve shape well.

Concept Of Revitalization Of Selected Military Facilities Of Dragoons Barracks In Olsztyn

NASA Astrophysics Data System (ADS)

Zagroba, Marek

2015-12-01

Revitalization is a complex program to restore the functioning of the neglected urban areas in terms of spatial, economic and social. Revitalization activities on post-military facilities are stopping negative phenomena, such as degradation of space, social pathology or lack of proper functioning of the area, adapted to modern needs. The object of the work is to present some aspects with the revitalization of former military facilities in the area of the Artyleryjska Street in Olsztyn. The presented design concept aims to revitalize a neglected area of the barracks, which will enable the activation site and include it in the city urban space. The method adopted in this work is the architectural project of adapting selected post-military facilities for new functions, affecting the economic development and social integration of people.

[From symmetries to the laws of evolution. I. Chirality as a means of active media stratification].

PubMed

Tverdislov, V A; Sidorova, A É; Iakovenko, L V

2012-01-01

Features of the hypothetical evolution of a hierarchy of chiral objects formed by active media are discussed. On the basis of experimental facts a new synergetic generalization is made: an evolving system can repeatedly broaden the spectrum of its symmetry types within one level of organization which increases its complexity and change the sign of chirality during transition to a higher level. Switching the chirality sign of macroscopic objects provides irreversibility of stratification. The known chirality of biological structures at different levels suggests that the chiral L/D-stratification should be universal and the hierarchical paths are stable and determined. A high level enantiomorph with reciprocal chirality demonstrates a wider spectrum of functionality. A fractal description of natural hierarchical systems is pointed out to be inadequate because it implicates invariance of the chirality sign of the objects at different scales.

Clinical simulation as a boundary object in design of health IT-systems.

PubMed

Rasmussen, Stine Loft; Jensen, Sanne; Lyng, Karen Marie

2013-01-01

Healthcare organizations are very complex, holding numerous stakeholders with various approaches and goals towards the design of health IT-systems. Some of these differences may be approached by applying the concept of boundary objects in a participatory IT-design process. Traditionally clinical simulation provides the opportunity to evaluate the design and the usage of clinical IT-systems without endangering the patients and interrupting clinical work. In this paper we present how clinical simulation additionally holds the potential to function as a boundary object in the design process. The case points out that clinical simulation provides an opportunity for discussions and mutual learning among the various stakeholders involved in design of standardized electronic clinical documentation templates. The paper presents and discusses the use of clinical simulation in the translation, transfer and transformation of knowledge between various stakeholders in a large healthcare organization.

Threat captures attention but does not affect learning of contextual regularities.

PubMed

Yamaguchi, Motonori; Harwood, Sarah L

2017-04-01

Some of the stimulus features that guide visual attention are abstract properties of objects such as potential threat to one's survival, whereas others are complex configurations such as visual contexts that are learned through past experiences. The present study investigated the two functions that guide visual attention, threat detection and learning of contextual regularities, in visual search. Search arrays contained images of threat and non-threat objects, and their locations were fixed on some trials but random on other trials. Although they were irrelevant to the visual search task, threat objects facilitated attention capture and impaired attention disengagement. Search time improved for fixed configurations more than for random configurations, reflecting learning of visual contexts. Nevertheless, threat detection had little influence on learning of the contextual regularities. The results suggest that factors guiding visual attention are different from factors that influence learning to guide visual attention.

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

PubMed Central

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-01-01

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

PubMed

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-06-10

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

NASA Technical Reports Server (NTRS)

Englander, Jacob; Vavrina, Matthew; Ghosh, Alexander

2015-01-01

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed and in some cases the final destination. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very diserable. This work presents such as an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

Seeing mathematics: perceptual experience and brain activity in acquired synesthesia.

PubMed

Brogaard, Berit; Vanni, Simo; Silvanto, Juha

2013-01-01

We studied the patient JP who has exceptional abilities to draw complex geometrical images by hand and a form of acquired synesthesia for mathematical formulas and objects, which he perceives as geometrical figures. JP sees all smooth curvatures as discrete lines, similarly regardless of scale. We carried out two preliminary investigations to establish the perceptual nature of synesthetic experience and to investigate the neural basis of this phenomenon. In a functional magnetic resonance imaging (fMRI) study, image-inducing formulas produced larger fMRI responses than non-image inducing formulas in the left temporal, parietal and frontal lobes. Thus our main finding is that the activation associated with his experience of complex geometrical images emerging from mathematical formulas is restricted to the left hemisphere.

A statistical learning strategy for closed-loop control of fluid flows

NASA Astrophysics Data System (ADS)

Guéniat, Florimond; Mathelin, Lionel; Hussaini, M. Yousuff

2016-12-01

This work discusses a closed-loop control strategy for complex systems utilizing scarce and streaming data. A discrete embedding space is first built using hash functions applied to the sensor measurements from which a Markov process model is derived, approximating the complex system's dynamics. A control strategy is then learned using reinforcement learning once rewards relevant with respect to the control objective are identified. This method is designed for experimental configurations, requiring no computations nor prior knowledge of the system, and enjoys intrinsic robustness. It is illustrated on two systems: the control of the transitions of a Lorenz'63 dynamical system, and the control of the drag of a cylinder flow. The method is shown to perform well.

The perception of odor objects in everyday life: a review on the processing of odor mixtures

PubMed Central

Thomas-Danguin, Thierry; Sinding, Charlotte; Romagny, Sébastien; El Mountassir, Fouzia; Atanasova, Boriana; Le Berre, Elodie; Le Bon, Anne-Marie; Coureaud, Gérard

2014-01-01

Smelling monomolecular odors hardly ever occurs in everyday life, and the daily functioning of the sense of smell relies primarily on the processing of complex mixtures of volatiles that are present in the environment (e.g., emanating from food or conspecifics). Such processing allows for the instantaneous recognition and categorization of smells and also for the discrimination of odors among others to extract relevant information and to adapt efficiently in different contexts. The neurophysiological mechanisms underpinning this highly efficient analysis of complex mixtures of odorants is beginning to be unraveled and support the idea that olfaction, as vision and audition, relies on odor-objects encoding. This configural processing of odor mixtures, which is empirically subject to important applications in our societies (e.g., the art of perfumers, flavorists, and wine makers), has been scientifically studied only during the last decades. This processing depends on many individual factors, among which are the developmental stage, lifestyle, physiological and mood state, and cognitive skills; this processing also presents striking similarities between species. The present review gathers the recent findings, as observed in animals, healthy subjects, and/or individuals with affective disorders, supporting the perception of complex odor stimuli as odor objects. It also discusses peripheral to central processing, and cognitive and behavioral significance. Finally, this review highlights that the study of odor mixtures is an original window allowing for the investigation of daily olfaction and emphasizes the need for knowledge about the underlying biological processes, which appear to be crucial for our representation and adaptation to the chemical environment. PMID:24917831

Uncertainty Analysis of Simulated Hydraulic Fracturing

NASA Astrophysics Data System (ADS)

Chen, M.; Sun, Y.; Fu, P.; Carrigan, C. R.; Lu, Z.

2012-12-01

Artificial hydraulic fracturing is being used widely to stimulate production of oil, natural gas, and geothermal reservoirs with low natural permeability. Optimization of field design and operation is limited by the incomplete characterization of the reservoir, as well as the complexity of hydrological and geomechanical processes that control the fracturing. Thus, there are a variety of uncertainties associated with the pre-existing fracture distribution, rock mechanics, and hydraulic-fracture engineering that require evaluation of their impact on the optimized design. In this study, a multiple-stage scheme was employed to evaluate the uncertainty. We first define the ranges and distributions of 11 input parameters that characterize the natural fracture topology, in situ stress, geomechanical behavior of the rock matrix and joint interfaces, and pumping operation, to cover a wide spectrum of potential conditions expected for a natural reservoir. These parameters were then sampled 1,000 times in an 11-dimensional parameter space constrained by the specified ranges using the Latin-hypercube method. These 1,000 parameter sets were fed into the fracture simulators, and the outputs were used to construct three designed objective functions, i.e. fracture density, opened fracture length and area density. Using PSUADE, three response surfaces (11-dimensional) of the objective functions were developed and global sensitivity was analyzed to identify the most sensitive parameters for the objective functions representing fracture connectivity, which are critical for sweep efficiency of the recovery process. The second-stage high resolution response surfaces were constructed with dimension reduced to the number of the most sensitive parameters. An additional response surface with respect to the objective function of the fractal dimension for fracture distributions was constructed in this stage. Based on these response surfaces, comprehensive uncertainty analyses were conducted among input parameters and objective functions. In addition, reduced-order emulation models resulting from this analysis can be used for optimal control of hydraulic fracturing. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Reference Avionics Architecture for Lunar Surface Systems

NASA Technical Reports Server (NTRS)

Somervill, Kevin M.; Lapin, Jonathan C.; Schmidt, Oron L.

2010-01-01

Developing and delivering infrastructure capable of supporting long-term manned operations to the lunar surface has been a primary objective of the Constellation Program in the Exploration Systems Mission Directorate. Several concepts have been developed related to development and deployment lunar exploration vehicles and assets that provide critical functionality such as transportation, habitation, and communication, to name a few. Together, these systems perform complex safety-critical functions, largely dependent on avionics for control and behavior of system functions. These functions are implemented using interchangeable, modular avionics designed for lunar transit and lunar surface deployment. Systems are optimized towards reuse and commonality of form and interface and can be configured via software or component integration for special purpose applications. There are two core concepts in the reference avionics architecture described in this report. The first concept uses distributed, smart systems to manage complexity, simplify integration, and facilitate commonality. The second core concept is to employ extensive commonality between elements and subsystems. These two concepts are used in the context of developing reference designs for many lunar surface exploration vehicles and elements. These concepts are repeated constantly as architectural patterns in a conceptual architectural framework. This report describes the use of these architectural patterns in a reference avionics architecture for Lunar surface systems elements.

Converging on the function of intrinsically disordered nucleoporins in the nuclear pore complex.

PubMed

Peleg, Orit; Lim, Roderick Y H

2010-07-01

Several biological mechanisms involve proteins or proteinaceous components that are intrinsically disordered. A case in point pertains to the nuclear pore complex (NPC), which regulates molecular transport between the nucleus and the cytoplasm. NPC functionality is dependent on unfolded domains rich in Phe-Gly (FG) repeats (i.e., FG-domains) that collectively act to promote or hinder cargo translocation. To a large extent, our understanding of FG-domain behavior is limited to in vitro investigations given the difficulty to resolve them directly in the NPC. Nevertheless, recent findings indicate a collective convergence towards rationalizing FG-domain function. This review aims to glean further insight into this fascinating problem by taking an objective look at the boundary conditions and contextual details underpinning FG-domain behavior in the NPC. Here, we treat the FG-domains as being commensurate with polymeric chains to address ambiguities such as for instance, how FG-domains tethered to the central channel of the NPC would behave differently as compared with their free-floating counterparts in solution. By bringing such fundamental questions to the fore, this review seeks to illuminate the importance of how such parameters can hold influence over the structure-function relation of intrinsically disordered proteins in the NPC and beyond.

The reliability and validity of the Complex Task Performance Assessment: A performance-based assessment of executive function.

PubMed

Wolf, Timothy J; Dahl, Abigail; Auen, Colleen; Doherty, Meghan

2017-07-01

The objective of this study was to evaluate the inter-rater reliability, test-retest reliability, concurrent validity, and discriminant validity of the Complex Task Performance Assessment (CTPA): an ecologically valid performance-based assessment of executive function. Community control participants (n = 20) and individuals with mild stroke (n = 14) participated in this study. All participants completed the CTPA and a battery of cognitive assessments at initial testing. The control participants completed the CTPA at two different times one week apart. The intra-class correlation coefficient (ICC) for inter-rater reliability for the total score on the CTPA was .991. The ICCs for all of the sub-scores of the CTPA were also high (.889-.977). The CTPA total score was significantly correlated to Condition 4 of the DKEFS Color-Word Interference Test (p = -.425), and the Wechsler Test of Adult Reading (p  = -.493). Finally, there were significant differences between control subjects and individuals with mild stroke on the total score of the CTPA (p = .007) and all sub-scores except interpretation failures and total items incorrect. These results are also consistent with other current executive function performance-based assessments and indicate that the CTPA is a reliable and valid performance-based measure of executive function.

Why Bother to Calibrate? Model Consistency and the Value of Prior Information

NASA Astrophysics Data System (ADS)

Hrachowitz, Markus; Fovet, Ophelie; Ruiz, Laurent; Euser, Tanja; Gharari, Shervan; Nijzink, Remko; Savenije, Hubert; Gascuel-Odoux, Chantal

2015-04-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by 4 calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce 20 hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by using prior information about the system to impose "prior constraints", inferred from expert knowledge and to ensure a model which behaves well with respect to the modeller's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model set-up exhibited increased performance in the independent test period and skill to reproduce all 20 signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if efficiently counter-balanced by available prior constraints, can increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge driven strategy of constraining models.

Why Bother and Calibrate? Model Consistency and the Value of Prior Information.

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J. E.; Savenije, H.; Gascuel-Odoux, C.

2014-12-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by 4 calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce 20 hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by using prior information about the system to impose "prior constraints", inferred from expert knowledge and to ensure a model which behaves well with respect to the modeller's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model set-up exhibited increased performance in the independent test period and skill to reproduce all 20 signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if efficiently counter-balanced by available prior constraints, can increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge driven strategy of constraining models.

Nicotine deprivation elevates neural representation of smoking-related cues in object-sensitive visual cortex: a proof of concept study.

PubMed

Havermans, Anne; van Schayck, Onno C P; Vuurman, Eric F P M; Riedel, Wim J; van den Hurk, Job

2017-08-01

In the current study, we use functional magnetic resonance imaging (fMRI) and multi-voxel pattern analysis (MVPA) to investigate whether tobacco addiction biases basic visual processing in favour of smoking-related images. We hypothesize that the neural representation of smoking-related stimuli in the lateral occipital complex (LOC) is elevated after a period of nicotine deprivation compared to a satiated state, but that this is not the case for object categories unrelated to smoking. Current smokers (≥10 cigarettes a day) underwent two fMRI scanning sessions: one after 10 h of nicotine abstinence and the other one after smoking ad libitum. Regional blood oxygenated level-dependent (BOLD) response was measured while participants were presented with 24 blocks of 8 colour-matched pictures of cigarettes, pencils or chairs. The functional data of 10 participants were analysed through a pattern classification approach. In bilateral LOC clusters, the classifier was able to discriminate between patterns of activity elicited by visually similar smoking-related (cigarettes) and neutral objects (pencils) above empirically estimated chance levels only during deprivation (mean = 61.0%, chance (permutations) = 50.0%, p = .01) but not during satiation (mean = 53.5%, chance (permutations) = 49.9%, ns.). For all other stimulus contrasts, there was no difference in discriminability between the deprived and satiated conditions. The discriminability between smoking and non-smoking visual objects was elevated in object-selective brain region LOC after a period of nicotine abstinence. This indicates that attention bias likely affects basic visual object processing.

Heart rhythm complexity impairment in patients undergoing peritoneal dialysis

NASA Astrophysics Data System (ADS)

Lin, Yen-Hung; Lin, Chen; Ho, Yi-Heng; Wu, Vin-Cent; Lo, Men-Tzung; Hung, Kuan-Yu; Liu, Li-Yu Daisy; Lin, Lian-Yu; Huang, Jenq-Wen; Peng, Chung-Kang

2016-06-01

Cardiovascular disease is one of the leading causes of death in patients with advanced renal disease. The objective of this study was to investigate impairments in heart rhythm complexity in patients with end-stage renal disease. We prospectively analyzed 65 patients undergoing peritoneal dialysis (PD) without prior cardiovascular disease and 72 individuals with normal renal function as the control group. Heart rhythm analysis including complexity analysis by including detrended fractal analysis (DFA) and multiscale entropy (MSE) were performed. In linear analysis, the PD patients had a significantly lower standard deviation of normal RR intervals (SDRR) and percentage of absolute differences in normal RR intervals greater than 20 ms (pNN20). Of the nonlinear analysis indicators, scale 5, area under the MSE curve for scale 1 to 5 (area 1-5) and 6 to 20 (area 6-20) were significantly lower than those in the control group. In DFA anaylsis, both DFA α1 and DFA α2 were comparable in both groups. In receiver operating characteristic curve analysis, scale 5 had the greatest discriminatory power for two groups. In both net reclassification improvement model and integrated discrimination improvement models, MSE parameters significantly improved the discriminatory power of SDRR, pNN20, and pNN50. In conclusion, PD patients had worse cardiac complexity parameters. MSE parameters are useful to discriminate PD patients from patients with normal renal function.

Taking aim at Alzheimer’s disease through the mammalian target of rapamycin

PubMed Central

Maiese, Kenneth

2014-01-01

A significant portion of the world’s population suffers from sporadic Alzheimer’s disease (AD) with available present therapies limited to symptomatic care that does not alter disease progression. Over the next decade, advancing age of the global population will dramatically increase the incidence of AD and severely impact health care resources, necessitating novel, safe, and efficacious strategies for AD. The mammalian target of rapamycin (mTOR) and its protein complexes mTOR Complex 1 (mTORC1) and mTOR Complex 2 (mTORC2) offer exciting and unique avenues of intervention for AD through the oversight of programmed cell death pathways of apoptosis, autophagy, and necroptosis. mTOR modulates multi-faceted signal transduction pathways that involve phosphoinositide 3-kinase (PI 3-K), protein kinase B (Akt), hamartin (tuberous sclerosis 1)/tuberin (tuberous sclerosis 2) (TSC1/TSC2) complex, proline-rich Akt substrate 40 kDa (PRAS40), and p70 ribosomal S6 kinase (p70S6K) and can interface with the neuroprotective pathways of growth factors, sirtuins, wingless, fork-head transcription factors, and glycogen synthase kinase-3β. With the ability of mTOR to broadly impact cellular function, clinical strategies for AD that implement mTOR must achieve parallel objectives of protecting neuronal, vascular, and immune cell survival in conjunction with preserving networks that determine memory and cognitive function. PMID:25105207

Temporal evolution of brain reorganization under cross-modal training: insights into the functional architecture of encoding and retrieval networks

NASA Astrophysics Data System (ADS)

Likova, Lora T.

2015-03-01

This study is based on the recent discovery of massive and well-structured cross-modal memory activation generated in the primary visual cortex (V1) of totally blind people as a result of novel training in drawing without any vision (Likova, 2012). This unexpected functional reorganization of primary visual cortex was obtained after undergoing only a week of training by the novel Cognitive-Kinesthetic Method, and was consistent across pilot groups of different categories of visual deprivation: congenitally blind, late-onset blind and blindfolded (Likova, 2014). These findings led us to implicate V1 as the implementation of the theoretical visuo-spatial 'sketchpad' for working memory in the human brain. Since neither the source nor the subsequent 'recipient' of this non-visual memory information in V1 is known, these results raise a number of important questions about the underlying functional organization of the respective encoding and retrieval networks in the brain. To address these questions, an individual totally blind from birth was given a week of Cognitive-Kinesthetic training, accompanied by functional magnetic resonance imaging (fMRI) both before and just after training, and again after a two-month consolidation period. The results revealed a remarkable temporal sequence of training-based response reorganization in both the hippocampal complex and the temporal-lobe object processing hierarchy over the prolonged consolidation period. In particular, a pattern of profound learning-based transformations in the hippocampus was strongly reflected in V1, with the retrieval function showing massive growth as result of the Cognitive-Kinesthetic memory training and consolidation, while the initially strong hippocampal response during tactile exploration and encoding became non-existent. Furthermore, after training, an alternating patch structure in the form of a cascade of discrete ventral regions underwent radical transformations to reach complete functional specialization in terms of either encoding or retrieval as a function of the stage of learning. Moreover, several distinct patterns of learning-evolution within the patches as a function of their anatomical location, implying a complex reorganization of the object processing sub-networks through the learning period. These first findings of complex patterns of training-based encoding/retrieval reorganization thus have broad implications for a newly emerging view of the perception/memory interactions and their reorganization through the learning process. Note that the temporal evolution of these forms of extended functional reorganization could not be uncovered with conventional assessment paradigms used in the traditional approaches to functional mapping, which may therefore have to be revisited. Moreover, as the present results are obtained in learning under life-long blindness, they imply modality-independent operations, transcending the usual tight association with visual processing. The present approach of memory drawing training in blindness, has the dual-advantage of being both non-visual and causal intervention, which makes it a promising 'scalpel' to disentangle interactions among diverse cognitive functions.

3D Visible-Light Invisibility Cloak.

PubMed

Zheng, Bin; Zhu, Rongrong; Jing, Liqiao; Yang, Yihao; Shen, Lian; Wang, Huaping; Wang, Zuojia; Zhang, Xianmin; Liu, Xu; Li, Erping; Chen, Hongsheng

2018-06-01

The concept of an invisibility cloak is a fixture of science fiction, fantasy, and the collective imagination. However, a real device that can hide an object from sight in visible light from absolutely any viewpoint would be extremely challenging to build. The main obstacle to creating such a cloak is the coupling of the electromagnetic components of light, which would necessitate the use of complex materials with specific permittivity and permeability tensors. Previous cloaking solutions have involved circumventing this obstacle by functioning either in static (or quasistatic) fields where these electromagnetic components are uncoupled or in diffusive light scattering media where complex materials are not required. In this paper, concealing a large-scale spherical object from human sight from three orthogonal directions is reported. This result is achieved by developing a 3D homogeneous polyhedral transformation and a spatially invariant refractive index discretization that considerably reduce the coupling of the electromagnetic components of visible light. This approach allows for a major simplification in the design of 3D invisibility cloaks, which can now be created at a large scale using homogeneous and isotropic materials.

Programming Cells for Dynamic Assembly of Inorganic Nano-Objects with Spatiotemporal Control.

PubMed

Wang, Xinyu; Pu, Jiahua; An, Bolin; Li, Yingfeng; Shang, Yuequn; Ning, Zhijun; Liu, Yi; Ba, Fang; Zhang, Jiaming; Zhong, Chao

2018-04-01

Programming living cells to organize inorganic nano-objects (NOs) in a spatiotemporally precise fashion would advance new techniques for creating ordered ensembles of NOs and new bio-abiotic hybrid materials with emerging functionalities. Bacterial cells often grow in cellular communities called biofilms. Here, a strategy is reported for programming dynamic biofilm formation for the synchronized assembly of discrete NOs or hetero-nanostructures on diverse interfaces in a dynamic, scalable, and hierarchical fashion. By engineering Escherichia coli to sense blue light and respond by producing biofilm curli fibers, biofilm formation is spatially controlled and the patterned NOs' assembly is simultaneously achieved. Diverse and complex fluorescent quantum dot patterns with a minimum patterning resolution of 100 µm are demonstrated. By temporally controlling the sequential addition of NOs into the culture, multilayered heterostructured thin films are fabricated through autonomous layer-by-layer assembly. It is demonstrated that biologically dynamic self-assembly can be used to advance a new repertoire of nanotechnologies and materials with increasing complexity that would be otherwise challenging to produce. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Assessment of nutritional status in the elderly: a proposed function-driven model

PubMed Central

Engelheart, Stina; Brummer, Robert

2018-01-01

Background There is no accepted or standardized definition of ‘malnutrition’. Hence, there is also no definition of what constitutes an adequate nutritional status. In elderly people, assessment of nutritional status is complex and is complicated by multi-morbidity and disabilities combined with nutrition-related problems, such as dysphagia, decreased appetite, fatigue, and muscle weakness. Objective We propose a nutritional status model that presents nutritional status from a comprehensive functional perspective. This model visualizes the complexity of the nutritional status in elderly people. Design and results The presented model could be interpreted as the nutritional status is conditional to a person’s optimal function or situation. Another way of looking at it might be that a person’s nutritional status affects his or her optimal situation. The proposed model includes four domains: (1) physical function and capacity; (2) health and somatic disorders; (3) food and nutrition; and (4) cognitive, affective, and sensory function. Each domain has a major impact on nutritional status, which in turn has a major impact on the outcome of each domain. Conclusions Nutritional status is a multifaceted concept and there exist several knowledge gaps in the diagnosis, prevention, and optimization of treatment of inadequate nutritional status in elderly people. The nutritional status model may be useful in nutritional assessment research, as well as in the clinical setting. PMID:29720931

Nanomaterial interactions with biomembranes: Bridging the gap between soft matter models and biological context.

PubMed

Werner, Marco; Auth, Thorsten; Beales, Paul A; Fleury, Jean Baptiste; Höök, Fredrik; Kress, Holger; Van Lehn, Reid C; Müller, Marcus; Petrov, Eugene P; Sarkisov, Lev; Sommer, Jens-Uwe; Baulin, Vladimir A

2018-04-03

Synthetic polymers, nanoparticles, and carbon-based materials have great potential in applications including drug delivery, gene transfection, in vitro and in vivo imaging, and the alteration of biological function. Nature and humans use different design strategies to create nanomaterials: biological objects have emerged from billions of years of evolution and from adaptation to their environment resulting in high levels of structural complexity; in contrast, synthetic nanomaterials result from minimalistic but controlled design options limited by the authors' current understanding of the biological world. This conceptual mismatch makes it challenging to create synthetic nanomaterials that possess desired functions in biological media. In many biologically relevant applications, nanomaterials must enter the cell interior to perform their functions. An essential transport barrier is the cell-protecting plasma membrane and hence the understanding of its interaction with nanomaterials is a fundamental task in biotechnology. The authors present open questions in the field of nanomaterial interactions with biological membranes, including: how physical mechanisms and molecular forces acting at the nanoscale restrict or inspire design options; which levels of complexity to include next in computational and experimental models to describe how nanomaterials cross barriers via passive or active processes; and how the biological media and protein corona interfere with nanomaterial functionality. In this Perspective, the authors address these questions with the aim of offering guidelines for the development of next-generation nanomaterials that function in biological media.

SSME Electrical Harness and Cable Development and Evolution

NASA Technical Reports Server (NTRS)

Abrams, Russ; Heflin, Johnny; Burns, Bob; Camper, Scott J.; Hill, Arthur J.

2010-01-01

The Space Shuttle Main Engine (SSME) electrical harness and cable system consists of the various interconnecting devices necessary for operation of complex rocket engine functions. Thirty seven harnesses incorporate unique connectors, backshell adapters, conductors, insulation, shielding, and physical barriers for a long maintenance-free life while providing the means to satisfy performance requirements and to mitigate adverse environmental influences. The objective of this paper is to provide a description of the SSME electrical harness and cable designs as well as the development history and lessons learned.

Building a global business continuity programme.

PubMed

Lazcano, Michael

2014-01-01

Business continuity programmes provide an important function within organisations, especially when aligned with and supportive of the organisation's goals, objectives and organisational culture. Continuity programmes for large, complex international organisations, unlike those for compact national companies, are more difficult to design, build, implement and maintain. Programmes for international organisations require attention to structural design, support across organisational leadership and hierarchy, seamless integration with the organisation's culture, measured success and demonstrated value. This paper details practical, but sometimes overlooked considerations for building successful global business continuity programmes.

Necessity of creating digital tools to ensure efficiency of technical means

NASA Astrophysics Data System (ADS)

Rakov, V. I.; Zakharova, O. V.

2018-05-01

The authors estimated the problems of functioning of technical objects. The article notes that the increasing complexity of automation systems may lead to an increase of the redundant resource in proportion to the number of components and relationships in the system, and to the need of the redundant resource constant change that can make implementation of traditional structures with redundancy unnecessarily costly (Standby System, Fault Tolerance, High Availability). It proposes the idea of creating digital tools to ensure efficiency of technical facilities.

Teleman localization of Hochschild homology in a singular setting

NASA Astrophysics Data System (ADS)

Brasselet, J.-P.; Legrand, A.

2009-09-01

The aim of this paper is to generalize the Hochschild-Kostant-Rosenberg theorem to the case of singular varieties, more precisely, to manifolds with boundary and to varieties with isolated singularities. In these situations, we define suitable algebras of functions and study the localization of the corresponding Hochschild homology. The tool we use is the Teleman localization process. In the case of isolated singularities, the closed Hochschild homology corresponds to the intersection complex which relates the objects defined here to intersection homology.

Using Software Technology to Specify Abstract Interfaces in VLSI Design.

DTIC Science & Technology

1985-01-01

the information required for the specification should be provided "and nothir- g more." He felt that a chief source of specification failure was...this complexity control objective by mix i g two potentially separable kinds of information, i.e. functional/electrical and scheduling semantics...strength Syntactic: immaterial PINS Name AccFn C/D scim G -Scanln C scout PScanOut D routbar PDataOut D p )sh SShift D p2shbar SHold D plshbar S

Control/display trade-off study for single-pilot instrument flight rule operations

NASA Technical Reports Server (NTRS)

Hoh, R.

1983-01-01

The objectives were to determine minimum autopilot functions and displays required to keep pilot workload at an acceptable level; to determine what constitutes an acceptable level of workload; to identify critical tasks; and to suggest specific experiments required to refine conclusions. It was determined that workload relief is derived from basic stability augmentation; that complex autopilots can lead to serious blunders; and that displays need to enhance positional awareness and minimize the likelihood of false hypothesis.

Connectome analysis for pre-operative brain mapping in neurosurgery

PubMed Central

Hart, Michael G.; Price, Stephen J.; Suckling, John

2016-01-01

Abstract Object: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains ‘wiring diagram’. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Methods: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal–parietal–occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Results: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Conclusions: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits. PMID:27447756

Link predication based on matrix factorization by fusion of multi class organizations of the network.

PubMed

Jiao, Pengfei; Cai, Fei; Feng, Yiding; Wang, Wenjun

2017-08-21

Link predication aims at forecasting the latent or unobserved edges in the complex networks and has a wide range of applications in reality. Almost existing methods and models only take advantage of one class organization of the networks, which always lose important information hidden in other organizations of the network. In this paper, we propose a link predication framework which makes the best of the structure of networks in different level of organizations based on nonnegative matrix factorization, which is called NMF 3 here. We first map the observed network into another space by kernel functions, which could get the different order organizations. Then we combine the adjacency matrix of the network with one of other organizations, which makes us obtain the objective function of our framework for link predication based on the nonnegative matrix factorization. Third, we derive an iterative algorithm to optimize the objective function, which converges to a local optimum, and we propose a fast optimization strategy for large networks. Lastly, we test the proposed framework based on two kernel functions on a series of real world networks under different sizes of training set, and the experimental results show the feasibility, effectiveness, and competitiveness of the proposed framework.

Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique

NASA Astrophysics Data System (ADS)

Bandaru, Sunith; Deb, Kalyanmoy

2011-09-01

In this article, a methodology is proposed for automatically extracting innovative design principles which make a system or process (subject to conflicting objectives) optimal using its Pareto-optimal dataset. Such 'higher knowledge' would not only help designers to execute the system better, but also enable them to predict how changes in one variable would affect other variables if the system has to retain its optimal behaviour. This in turn would help solve other similar systems with different parameter settings easily without the need to perform a fresh optimization task. The proposed methodology uses a clustering-based optimization technique and is capable of discovering hidden functional relationships between the variables, objective and constraint functions and any other function that the designer wishes to include as a 'basis function'. A number of engineering design problems are considered for which the mathematical structure of these explicit relationships exists and has been revealed by a previous study. A comparison with the multivariate adaptive regression splines (MARS) approach reveals the practicality of the proposed approach due to its ability to find meaningful design principles. The success of this procedure for automated innovization is highly encouraging and indicates its suitability for further development in tackling more complex design scenarios.

Investigating multi-objective fluence and beam orientation IMRT optimization

NASA Astrophysics Data System (ADS)

Potrebko, Peter S.; Fiege, Jason; Biagioli, Matthew; Poleszczuk, Jan

2017-07-01

Radiation Oncology treatment planning requires compromises to be made between clinical objectives that are invariably in conflict. It would be beneficial to have a ‘bird’s-eye-view’ perspective of the full spectrum of treatment plans that represent the possible trade-offs between delivering the intended dose to the planning target volume (PTV) while optimally sparing the organs-at-risk (OARs). In this work, the authors demonstrate Pareto-aware radiotherapy evolutionary treatment optimization (PARETO), a multi-objective tool featuring such bird’s-eye-view functionality, which optimizes fluence patterns and beam angles for intensity-modulated radiation therapy (IMRT) treatment planning. The problem of IMRT treatment plan optimization is managed as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. To achieve this, PARETO is built around a powerful multi-objective evolutionary algorithm, called Ferret, which simultaneously optimizes multiple fitness functions that encode the attributes of the desired dose distribution for the PTV and OARs. The graphical interfaces within PARETO provide useful information such as: the convergence behavior during optimization, trade-off plots between the competing objectives, and a graphical representation of the optimal solution database allowing for the rapid exploration of treatment plan quality through the evaluation of dose-volume histograms and isodose distributions. PARETO was evaluated for two relatively complex clinical cases, a paranasal sinus and a pancreas case. The end result of each PARETO run was a database of optimal (non-dominated) treatment plans that demonstrated trade-offs between the OAR and PTV fitness functions, which were all equally good in the Pareto-optimal sense (where no one objective can be improved without worsening at least one other). Ferret was able to produce high quality solutions even though a large number of parameters, such as beam fluence and beam angles, were included in the optimization.

Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay

USGS Publications Warehouse

McGowan, Conor P.; Smith, David R.; Nichols, James D.; Lyons, James E.; Sweka, John A.; Kalasz, Kevin; Niles, Lawrence J.; Wong, Richard; Brust, Jeffrey; Davis, Michelle C.; Spear, Braddock

2015-01-01

Decision analytic approaches have been widely recommended as well suited to solving disputed and ecologically complex natural resource management problems with multiple objectives and high uncertainty. However, the difference between theory and practice is substantial, as there are very few actual resource management programs that represent formal applications of decision analysis. We applied the process of structured decision making to Atlantic horseshoe crab harvest decisions in the Delaware Bay region to develop a multispecies adaptive management (AM) plan, which is currently being implemented. Horseshoe crab harvest has been a controversial management issue since the late 1990s. A largely unregulated horseshoe crab harvest caused a decline in crab spawning abundance. That decline coincided with a major decline in migratory shorebird populations that consume horseshoe crab eggs on the sandy beaches of Delaware Bay during spring migration. Our approach incorporated multiple stakeholders, including fishery and shorebird conservation advocates, to account for diverse management objectives and varied opinions on ecosystem function. Through consensus building, we devised an objective statement and quantitative objective function to evaluate alternative crab harvest policies. We developed a set of competing ecological models accounting for the leading hypotheses on the interaction between shorebirds and horseshoe crabs. The models were initially weighted based on stakeholder confidence in these hypotheses, but weights will be adjusted based on monitoring and Bayesian model weight updating. These models were used together to predict the effects of management actions on the crab and shorebird populations. Finally, we used a dynamic optimization routine to identify the state dependent optimal harvest policy for horseshoe crabs, given the possible actions, the stated objectives and our competing hypotheses about system function. The AM plan was reviewed, accepted and implemented by the Atlantic States Marine Fisheries Commission in 2012 and 2013. While disagreements among stakeholders persist, structured decision making enabled unprecedented progress towards a transparent and consensus driven management plan for crabs and shorebirds in Delaware Bay.

Auditory brainstem response to complex sounds: a tutorial

PubMed Central

Skoe, Erika; Kraus, Nina

2010-01-01

This tutorial provides a comprehensive overview of the methodological approach to collecting and analyzing auditory brainstem responses to complex sounds (cABRs). cABRs provide a window into how behaviorally relevant sounds such as speech and music are processed in the brain. Because temporal and spectral characteristics of sounds are preserved in this subcortical response, cABRs can be used to assess specific impairments and enhancements in auditory processing. Notably, subcortical function is neither passive nor hardwired but dynamically interacts with higher-level cognitive processes to refine how sounds are transcribed into neural code. This experience-dependent plasticity, which can occur on a number of time scales (e.g., life-long experience with speech or music, short-term auditory training, online auditory processing), helps shape sensory perception. Thus, by being an objective and non-invasive means for examining cognitive function and experience-dependent processes in sensory activity, cABRs have considerable utility in the study of populations where auditory function is of interest (e.g., auditory experts such as musicians, persons with hearing loss, auditory processing and language disorders). This tutorial is intended for clinicians and researchers seeking to integrate cABRs into their clinical and/or research programs. PMID:20084007

Examining the Influence of Measures of Adiposity on Cognitive Function in Middle Age and Older African Americans.

PubMed

Wright, Regina S; Cole, Angela P; Ali, Mana K; Skinner, Jeannine; Whitfield, Keith E; Mwendwa, Denée T

2016-02-01

The objectives of the study were to examine whether measures of total obesity (body mass index [BMI]) and central obesity (waist circumference [WC] and waist-to-hip ratio [WHR]) are associated with cognitive function in African Americans, and whether sex moderates these associations. A sample of 194 African Americans, with a mean age of 58.97 years, completed a battery of cognitive tests and a self-reported health questionnaire. Height, weight, waist and hip circumference, and blood pressure were assessed. Linear regression analyses were run. Results suggested lower performance on measures of verbal fluency and complex attention/cognitive flexibility was accounted for by higher levels of central adiposity. Among men, higher WHR was more strongly related to complex attention/cognitive flexibility performance, but for women, WC was a salient predictor. Higher BMI was associated with poorer verbal memory performance among men, but poorer nonverbal memory performance among women. Findings suggest a need for healthy lifestyle interventions for African Americans to maintain healthy weight and cognitive function. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Real-time scene and signature generation for ladar and imaging sensors

NASA Astrophysics Data System (ADS)

Swierkowski, Leszek; Christie, Chad L.; Antanovskii, Leonid; Gouthas, Efthimios

2014-05-01

This paper describes development of two key functionalities within the VIRSuite scene simulation program, broadening its scene generation capabilities and increasing accuracy of thermal signatures. Firstly, a new LADAR scene generation module has been designed. It is capable of simulating range imagery for Geiger mode LADAR, in addition to the already existing functionality for linear mode systems. Furthermore, a new 3D heat diffusion solver has been developed within the VIRSuite signature prediction module. It is capable of calculating the temperature distribution in complex three-dimensional objects for enhanced dynamic prediction of thermal signatures. With these enhancements, VIRSuite is now a robust tool for conducting dynamic simulation for missiles with multi-mode seekers.

Effect of Simvastatin on Cognitive Functioning in Children With Neurofibromatosis Type 1

PubMed Central

Krab, Lianne C.; de Goede-Bolder, Arja; Aarsen, Femke K.; Pluijm, Saskia M. F.; Bouman, Marlies J.; van der Geest, Jos N.; Lequin, Maarten; Catsman, Coriene E.; Arts, Willem Frans M.; Kushner, Steven A.; Silva, Alcino J.; de Zeeuw, Chris I.; Moll, Henriëtte A.; Elgersma, Ype

2009-01-01

Context Neurofibromatosis type 1 (NF1) is among the most common genetic disorders that cause learning disabilities. Recently, it was shown that statin-mediated inhibition of 3-hydroxy-3-methylglutaryl coenzyme A reductase restores the cognitive deficits in an NF1 mouse model. Objective To determine the effect of simvastatin on neuropsychological, neurophysiological, and neuroradiological outcome measures in children with NF1. Design, Setting, and Participants Sixty-two of 114 eligible children (54%) with NF1 participated in a randomized, double-blind, placebo-controlled trial conducted between January 20, 2006, and February 8, 2007, at an NF1 referral center at a Dutch university hospital. Intervention Simvastatin or placebo treatment once daily for 12 weeks. Main Outcome Measures Primary outcomes were scores on a Rey complex figure test (delayed recall), cancellation test (speed), prism adaptation, and the mean brain apparent diffusion coefficient based on magnetic resonance imaging. Secondary outcome measures were scores on the cancellation test (standard deviation), Stroop color word test, block design, object assembly, Rey complex figure test (copy), Beery developmental test of visual-motor integration, and judgment of line orientation. Scores were corrected for baseline performance, age, and sex. Results No significant differences were observed between the simvastatin and placebo groups on any primary outcome measure: Rey complex figure test (β=0.10; 95% confidence interval [CI], −0.36 to 0.56); cancellation test (β=−0.19; 95% CI, −0.67 to 0.29); prism adaptation (odds ratio=2.0; 95% CI, 0.55 to 7.37); and mean brain apparent diffusion coefficient (β=0.06; 95% CI, −0.07 to 0.20). In the secondary outcome measures, we found a significant improvement in the simvastatin group in object assembly scores (β=0.54; 95% CI, 0.08 to 1.01), which was specifically observed in children with poor baseline performance (β =0.80; 95% CI, 0.29 to 1.30). Other secondary outcome measures revealed no significant effect of simvastatin treatment. Conclusion In this 12-week trial, simvastatin did not improve cognitive function in children with NF1. PMID:18632543

Optical properties of photoreceptor and retinal pigment epithelium cells investigated with adaptive optics optical coherence tomography

NASA Astrophysics Data System (ADS)

Liu, Zhuolin

Human vision starts when photoreceptors collect and respond to light. Photoreceptors do not function in isolation though, but share close interdependence with neighboring photoreceptors and underlying retinal pigment epithelium (RPE) cells. These cellular interactions are essential for normal function of the photoreceptor-RPE complex, but methods to assess these in the living human eye are limited. One approach that has gained increased promise is high-resolution retinal imaging that has undergone tremendous technological advances over the last two decades to probe the living retina at the cellular level. Pivotal in these advances has been adaptive optics (AO) and optical coherence tomography (OCT) that together allow unprecedented spatial resolution of retinal structures in all three dimensions. Using these high-resolution systems, cone photoreceptor are now routinely imaged in healthy and diseased retina enabling fundamental structural properties of cones to be studied such as cell spacing, packing arrangement, and alignment. Other important cell properties, however, have remained elusive to investigation as even better imaging performance is required and thus has resulted in an incomplete understanding of how cells in the photoreceptor-RPE complex interact with light. To address this technical bottleneck, we expanded the imaging capability of AO-OCT to detect and quantify more accurately and completely the optical properties of cone photoreceptor and RPE cells at the cellular level in the living human retina. The first objective of this thesis was development of a new AO-OCT method that is more precise and sensitive, thus enabling a more detailed view of the 3D optical signature of the photoreceptor-RPE complex than was previously possible (Chapter 2). Using this new system, the second objective was quantifying the waveguide properties of individual cone photoreceptor inner and outer segments across the macula (Chapter 3). The third objective extended the AO-OCT method to RPE cell imaging. This entailed using AO-OCT in conjunction with organelle motility as a novel contrast mechanism to visualize RPE cells and to characterize their 3D reflectance profile (Chapter 4).

Concealing with structured light.

PubMed

Sun, Jingbo; Zeng, Jinwei; Wang, Xi; Cartwright, Alexander N; Litchinitser, Natalia M

2014-02-13

While making objects less visible (or invisible) to a human eye or a radar has captured people's imagination for centuries, current attempts towards realization of this long-awaited functionality range from various stealth technologies to recently proposed cloaking devices. A majority of proposed approaches share a number of common deficiencies such as design complexity, polarization effects, bandwidth, losses and the physical size or shape requirement complicating their implementation especially at optical frequencies. Here we demonstrate an alternative way to conceal macroscopic objects by structuring light itself. In our approach, the incident light is transformed into an optical vortex with a dark core that can be used to conceal macroscopic objects. Once such a beam passed around the object it is transformed back into its initial Gaussian shape with minimum amplitude and phase distortions. Therefore, we propose to use that dark core of the vortex beam to conceal an object that is macroscopic yet small enough to fit the dark (negligibly low intensity) region of the beam. The proposed concealing approach is polarization independent, easy to fabricate, lossless, operates at wavelengths ranging from 560 to 700 nm, and can be used to hide macroscopic objects providing they are smaller than vortex core.

Topicality and Complexity in the Acquisition of Norwegian Object Shift

ERIC Educational Resources Information Center

Anderssen, Merete; Bentzen, Kristine; Rodina, Yulia

2012-01-01

This article investigates the acquisition of object shift in Norwegian child language. We show that object shift is complex derivationally, distributionally, and referentially, and propose a new analysis in terms of IP-internal topicalization. The results of an elicited production study with 27 monolingual Norwegian-speaking children (ages…

Simulating evolution of protein complexes through gene duplication and co-option.

PubMed

Haarsma, Loren; Nelesen, Serita; VanAndel, Ethan; Lamine, James; VandeHaar, Peter

2016-06-21

We present a model of the evolution of protein complexes with novel functions through gene duplication, mutation, and co-option. Under a wide variety of input parameters, digital organisms evolve complexes of 2-5 bound proteins which have novel functions but whose component proteins are not independently functional. Evolution of complexes with novel functions happens more quickly as gene duplication rates increase, point mutation rates increase, protein complex functional probability increases, protein complex functional strength increases, and protein family size decreases. Evolution of complexity is inhibited when the metabolic costs of making proteins exceeds the fitness gain of having functional proteins, or when point mutation rates get so large the functional proteins undergo deleterious mutations faster than new functional complexes can evolve. Copyright © 2016 Elsevier Ltd. All rights reserved.

A new effective operator for the hybrid algorithm for solving global optimisation problems

NASA Astrophysics Data System (ADS)

Duc, Le Anh; Li, Kenli; Nguyen, Tien Trong; Yen, Vu Minh; Truong, Tung Khac

2018-04-01

Hybrid algorithms have been recently used to solve complex single-objective optimisation problems. The ultimate goal is to find an optimised global solution by using these algorithms. Based on the existing algorithms (HP_CRO, PSO, RCCRO), this study proposes a new hybrid algorithm called MPC (Mean-PSO-CRO), which utilises a new Mean-Search Operator. By employing this new operator, the proposed algorithm improves the search ability on areas of the solution space that the other operators of previous algorithms do not explore. Specifically, the Mean-Search Operator helps find the better solutions in comparison with other algorithms. Moreover, the authors have proposed two parameters for balancing local and global search and between various types of local search, as well. In addition, three versions of this operator, which use different constraints, are introduced. The experimental results on 23 benchmark functions, which are used in previous works, show that our framework can find better optimal or close-to-optimal solutions with faster convergence speed for most of the benchmark functions, especially the high-dimensional functions. Thus, the proposed algorithm is more effective in solving single-objective optimisation problems than the other existing algorithms.

Self-paced model learning for robust visual tracking

NASA Astrophysics Data System (ADS)

Huang, Wenhui; Gu, Jason; Ma, Xin; Li, Yibin

2017-01-01

In visual tracking, learning a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and the frequency of model updating, which contains many details that could affect the tracking results. Self-paced learning (SPL) has recently been attracting considerable interest in the fields of machine learning and computer vision. SPL is inspired by the learning principle underlying the cognitive process of humans, whose learning process is generally from easier samples to more complex aspects of a task. We propose a tracking method that integrates the learning paradigm of SPL into visual tracking, so reliable samples can be automatically selected for model learning. In contrast to many existing model learning strategies in visual tracking, we discover the missing link between sample selection and model learning, which are combined into a single objective function in our approach. Sample weights and model parameters can be learned by minimizing this single objective function. Additionally, to solve the real-valued learning weight of samples, an error-tolerant self-paced function that considers the characteristics of visual tracking is proposed. We demonstrate the robustness and efficiency of our tracker on a recent tracking benchmark data set with 50 video sequences.

Neural Correlates of Temporal Complexity and Synchrony during Audiovisual Correspondence Detection.

PubMed

Baumann, Oliver; Vromen, Joyce M G; Cheung, Allen; McFadyen, Jessica; Ren, Yudan; Guo, Christine C

2018-01-01

We often perceive real-life objects as multisensory cues through space and time. A key challenge for audiovisual integration is to match neural signals that not only originate from different sensory modalities but also that typically reach the observer at slightly different times. In humans, complex, unpredictable audiovisual streams lead to higher levels of perceptual coherence than predictable, rhythmic streams. In addition, perceptual coherence for complex signals seems less affected by increased asynchrony between visual and auditory modalities than for simple signals. Here, we used functional magnetic resonance imaging to determine the human neural correlates of audiovisual signals with different levels of temporal complexity and synchrony. Our study demonstrated that greater perceptual asynchrony and lower signal complexity impaired performance in an audiovisual coherence-matching task. Differences in asynchrony and complexity were also underpinned by a partially different set of brain regions. In particular, our results suggest that, while regions in the dorsolateral prefrontal cortex (DLPFC) were modulated by differences in memory load due to stimulus asynchrony, areas traditionally thought to be involved in speech production and recognition, such as the inferior frontal and superior temporal cortex, were modulated by the temporal complexity of the audiovisual signals. Our results, therefore, indicate specific processing roles for different subregions of the fronto-temporal cortex during audiovisual coherence detection.

Neural Correlates of Temporal Complexity and Synchrony during Audiovisual Correspondence Detection

PubMed Central

Ren, Yudan

2018-01-01

Abstract We often perceive real-life objects as multisensory cues through space and time. A key challenge for audiovisual integration is to match neural signals that not only originate from different sensory modalities but also that typically reach the observer at slightly different times. In humans, complex, unpredictable audiovisual streams lead to higher levels of perceptual coherence than predictable, rhythmic streams. In addition, perceptual coherence for complex signals seems less affected by increased asynchrony between visual and auditory modalities than for simple signals. Here, we used functional magnetic resonance imaging to determine the human neural correlates of audiovisual signals with different levels of temporal complexity and synchrony. Our study demonstrated that greater perceptual asynchrony and lower signal complexity impaired performance in an audiovisual coherence-matching task. Differences in asynchrony and complexity were also underpinned by a partially different set of brain regions. In particular, our results suggest that, while regions in the dorsolateral prefrontal cortex (DLPFC) were modulated by differences in memory load due to stimulus asynchrony, areas traditionally thought to be involved in speech production and recognition, such as the inferior frontal and superior temporal cortex, were modulated by the temporal complexity of the audiovisual signals. Our results, therefore, indicate specific processing roles for different subregions of the fronto-temporal cortex during audiovisual coherence detection. PMID:29354682

Assessment of executive functions in children and adolescents with acquired brain injury (ABI) using a novel complex multi-tasking computerised task: The Jansari assessment of Executive Functions for Children (JEF-C©).

PubMed

Gilboa, Yafit; Jansari, Ashok; Kerrouche, Bernadette; Uçak, Emel; Tiberghien, Anne; Benkhaled, Ouarda; Aligon, Delphine; Mariller, Aude; Verdier, Valentine; Mintegui, Amaia; Abada, Geneviève; Canizares, Céline; Goldstein, Andrew; Chevignard, Mathilde

2017-12-28

The Jansari assessment of Executive Functions for Children (JEF-C © ) is a new non-immersive computerised assessment of executive functions. The objectives of the study were to test the feasibility and validity of JEF-C © in children and adolescents with acquired brain injury (ABI). Twenty-nine patients with ABI aged 10-18 years and 30 age-and gender-matched controls were tested. Participants performed JEF-C © , Wechsler Abbreviated Scale of Intelligence (WASI) and the Behavioural Assessment of the Dysexecutive Syndrome for Children (BADS-C), while parents completed the Behaviour Rating Inventory of Executive Function (BRIEF) questionnaire. The JEF-C © task proved feasible in patients with ABI. The internal consistency was medium (Cronbach's alpha = 0.62 and significant intercorrelations between individual JEF-C © constructs). Patients performed significantly worse than controls on most of the JEF-C © subscales and total score, with 41.4% of participants with ABI classified as having severe executive dysfunction. No significant correlations were found between JEF-C © total score, the BRIEF indices, and the BADS-C. Significant correlations were found between JEF-C © and demographic characteristics of the sample and intellectual ability, but not with severity/medical variables. JEF-C © is a playful complex task that appears to be a sensitive and ecologically valid assessment tool, especially for relatively high-functioning individuals.

Object grouping based on real-world regularities facilitates perception by reducing competitive interactions in visual cortex

PubMed Central

Kaiser, Daniel; Stein, Timo; Peelen, Marius V.

2014-01-01

In virtually every real-life situation humans are confronted with complex and cluttered visual environments that contain a multitude of objects. Because of the limited capacity of the visual system, objects compete for neural representation and cognitive processing resources. Previous work has shown that such attentional competition is partly object based, such that competition among elements is reduced when these elements perceptually group into an object based on low-level cues. Here, using functional MRI (fMRI) and behavioral measures, we show that the attentional benefit of grouping extends to higher-level grouping based on the relative position of objects as experienced in the real world. An fMRI study designed to measure competitive interactions among objects in human visual cortex revealed reduced neural competition between objects when these were presented in commonly experienced configurations, such as a lamp above a table, relative to the same objects presented in other configurations. In behavioral visual search studies, we then related this reduced neural competition to improved target detection when distracter objects were shown in regular configurations. Control studies showed that low-level grouping could not account for these results. We interpret these findings as reflecting the grouping of objects based on higher-level spatial-relational knowledge acquired through a lifetime of seeing objects in specific configurations. This interobject grouping effectively reduces the number of objects that compete for representation and thereby contributes to the efficiency of real-world perception. PMID:25024190

Numerical simulation of deformation and failure processes of a complex technical object under impact loading

NASA Astrophysics Data System (ADS)

Kraus, E. I.; Shabalin, I. I.; Shabalin, T. I.

2018-04-01

The main points of development of numerical tools for simulation of deformation and failure of complex technical objects under nonstationary conditions of extreme loading are presented. The possibility of extending the dynamic method for construction of difference grids to the 3D case is shown. A 3D realization of discrete-continuum approach to the deformation and failure of complex technical objects is carried out. The efficiency of the existing software package for 3D modelling is shown.

Stereotyped behavior of severely disabled children in classroom and free-play settings.

PubMed

Thompson, T J; Berkson, G

1985-05-01

The relationships between stereotyped behavior, object manipulation, self-manipulation, teacher attention, and various developmental measures were examined in 101 severely developmentally disabled children in their classrooms and a free-play setting. Stereotyped behavior without objects was positively correlated with self-manipulation and CA and was negatively correlated with complex object manipulation, developmental age, developmental quotient, and teacher attention. Stereotyped behavior with objects was negatively correlated with complex object manipulation. Partial correlations showed that age, self-manipulation, and developmental age shared unique variance with stereotyped behavior without objects.

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

Representing and Learning Complex Object Interactions

PubMed Central

Zhou, Yilun; Konidaris, George

2017-01-01

We present a framework for representing scenarios with complex object interactions, in which a robot cannot directly interact with the object it wishes to control, but must instead do so via intermediate objects. For example, a robot learning to drive a car can only indirectly change its pose, by rotating the steering wheel. We formalize such complex interactions as chains of Markov decision processes and show how they can be learned and used for control. We describe two systems in which a robot uses learning from demonstration to achieve indirect control: playing a computer game, and using a hot water dispenser to heat a cup of water. PMID:28593181

Patients with Parkinson's disease learn to control complex systems-an indication for intact implicit cognitive skill learning.

PubMed

Witt, Karsten; Daniels, Christine; Daniel, Victoria; Schmitt-Eliassen, Julia; Volkmann, Jens; Deuschl, Günther

2006-01-01

Implicit memory and learning mechanisms are composed of multiple processes and systems. Previous studies demonstrated a basal ganglia involvement in purely cognitive tasks that form stimulus response habits by reinforcement learning such as implicit classification learning. We will test the basal ganglia influence on two cognitive implicit tasks previously described by Berry and Broadbent, the sugar production task and the personal interaction task. Furthermore, we will investigate the relationship between certain aspects of an executive dysfunction and implicit learning. To this end, we have tested 22 Parkinsonian patients and 22 age-matched controls on two implicit cognitive tasks, in which participants learned to control a complex system. They interacted with the system by choosing an input value and obtaining an output that was related in a complex manner to the input. The objective was to reach and maintain a specific target value across trials (dynamic system learning). The two tasks followed the same underlying complex rule but had different surface appearances. Subsequently, participants performed an executive test battery including the Stroop test, verbal fluency and the Wisconsin card sorting test (WCST). The results demonstrate intact implicit learning in patients, despite an executive dysfunction in the Parkinsonian group. They lead to the conclusion that the basal ganglia system affected in Parkinson's disease does not contribute to the implicit acquisition of a new cognitive skill. Furthermore, the Parkinsonian patients were able to reach a specific goal in an implicit learning context despite impaired goal directed behaviour in the WCST, a classic test of executive functions. These results demonstrate a functional independence of implicit cognitive skill learning and certain aspects of executive functions.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

Tracking of Maneuvering Complex Extended Object with Coupled Motion Kinematics and Extension Dynamics Using Range Extent Measurements

PubMed Central

Sun, Lifan; Ji, Baofeng; Lan, Jian; He, Zishu; Pu, Jiexin

2017-01-01

The key to successful maneuvering complex extended object tracking (MCEOT) using range extent measurements provided by high resolution sensors lies in accurate and effective modeling of both the extension dynamics and the centroid kinematics. During object maneuvers, the extension dynamics of an object with a complex shape is highly coupled with the centroid kinematics. However, this difficult but important problem is rarely considered and solved explicitly. In view of this, this paper proposes a general approach to modeling a maneuvering complex extended object based on Minkowski sum, so that the coupled turn maneuvers in both the centroid states and extensions can be described accurately. The new model has a concise and unified form, in which the complex extension dynamics can be simply and jointly characterized by multiple simple sub-objects’ extension dynamics based on Minkowski sum. The proposed maneuvering model fits range extent measurements very well due to its favorable properties. Based on this model, an MCEOT algorithm dealing with motion and extension maneuvers is also derived. Two different cases of the turn maneuvers with known/unknown turn rates are specifically considered. The proposed algorithm which jointly estimates the kinematic state and the object extension can also be easily implemented. Simulation results demonstrate the effectiveness of the proposed modeling and tracking approaches. PMID:28937629

Mastery motivation in children with complex communication needs: longitudinal data analysis.

PubMed

Medeiros, Kara F; Cress, Cynthia J; Lambert, Matthew C

2016-09-01

This study compared longitudinal changes in mastery motivation during parent-child free play for 37 children with complex communication needs. Mastery motivation manifests as a willingness to work hard at tasks that are challenging, which is an important quality to overcoming the challenges involved in successful expressive communication using AAC. Unprompted parent-child play episodes were identified in three assessment sessions over an 18-month period and coded for nine categories of mastery motivation in social and object play. All of the object-oriented mastery motivation categories and one social mastery motivation category showed an influence of motor skills after controlling for receptive language. Object play elicited significantly more of all of the object-focused mastery motivation categories than social play, and social play elicited more of one type of social-focused mastery motivation behavior than object play. Mastery motivation variables did not differ significantly over time for children. Potential physical and interpersonal influences on mastery motivation for parents and children with complex communication needs are discussed, including broadening the procedures and definitions of mastery motivation beyond object-oriented measurements for children with complex communication needs.

Functionalized active-nucleus complex sensor

DOEpatents

Pines, Alexander; Wemmer, David E.; Spence, Megan; Rubin, Seth

2003-11-25

A functionalized active-nucleus complex sensor that selectively associates with one or more target species, and a method for assaying and screening for one or a plurality of target species utilizing one or a plurality of functionalized active-nucleus complexes with at least two of the functionalized active-nucleus complexes having an attraction affinity to different corresponding target species. The functionalized active-nucleus complex has an active-nucleus and a targeting carrier. The method involves functionalizing an active-nucleus, for each functionalized active-nucleus complex, by incorporating the active-nucleus into a macromolucular or molecular complex that is capable of binding one of the target species and then bringing the macromolecular or molecular complexes into contact with the target species and detecting the occurrence of or change in a nuclear magnetic resonance signal from each of the active-nuclei in each of the functionalized active-nucleus complexes.

Learning and memory in streptozotocin-induced diabetic rats in a novel spatial/object discrimination task.

PubMed

Popoviç, M; Biessels, G J; Isaacson, R L; Gispen, W H

2001-08-01

Diabetes mellitus is associated with disturbances of cognitive functioning. The aim of this study was to examine cognitive functioning in diabetic rats using the 'Can test', a novel spatial/object learning and memory task, without the use of aversive stimuli. Rats were trained to select a single rewarded can from seven cans. Mild water deprivation provided the motivation to obtain the reward (0.3 ml of water). After 5 days of baseline training, in which the rewarded can was marked by its surface and position in an open field, the animals were divided into two groups. Diabetes was induced in one group, by an intravenous injection of streptozotocin. Retention of baseline training was tested at 2-weekly intervals for 10 weeks. Next, two adapted versions of the task were used, with 4 days of training in each version. The rewarded can was a soft-drink can with coloured print. In a 'simple visual task' the soft-drink can was placed among six white cans, whereas in a 'complex visual task' it was placed among six soft-drink cans from different brands with distinct prints. In diabetic rats the number of correct responses was lower and number of reference and working memory errors higher than in controls in the various versions of the test. Switches between tasks and increases in task complexity accentuated the performance deficits, which may reflect an inability of diabetic rats to adapt behavioural strategies to the demands of the tasks.

Design of Distortion-Invariant Optical ID Tags for Remote Identification and Verification of Objects

NASA Astrophysics Data System (ADS)

Pérez-Cabré, Elisabet; Millán, María Sagrario; Javidi, Bahram

Optical identification (ID) tags [1] have a promising future in a number of applications such as the surveillance of vehicles in transportation, control of restricted areas for homeland security, item tracking on conveyor belts or other industrial environment, etc. More specifically, passive optical ID tag [1] was introduced as an optical code containing a signature (that is, a characteristic image or other relevant information of the object), which permits its real-time remote detection and identification. Since their introduction in the literature [1], some contributions have been proposed to increase their usefulness and robustness. To increase security and avoid counterfeiting, the signature was introduced in the optical code as an encrypted function [2-5] following the double-phase encryption technique [6]. Moreover, the design of the optical ID tag was done in such a way that tolerance to variations in scale and rotation was achieved [2-5]. To do that, the encrypted information was multiplexed and distributed in the optical code following an appropriate topology. Further studies were carried out to analyze the influence of different sources of noise. In some proposals [5, 7], the designed ID tag consists of two optical codes where the complex-valued encrypted signature was separately introduced in two real-valued functions according to its magnitude and phase distributions. This solution was introduced to overcome some difficulties in the readout of complex values in outdoors environments. Recently, the fully phase encryption technique [8] has been proposed to increase noise robustness of the authentication system.

Gaze control for an active camera system by modeling human pursuit eye movements

NASA Astrophysics Data System (ADS)

Toelg, Sebastian

1992-11-01

The ability to stabilize the image of one moving object in the presence of others by active movements of the visual sensor is an essential task for biological systems, as well as for autonomous mobile robots. An algorithm is presented that evaluates the necessary movements from acquired visual data and controls an active camera system (ACS) in a feedback loop. No a priori assumptions about the visual scene and objects are needed. The algorithm is based on functional models of human pursuit eye movements and is to a large extent influenced by structural principles of neural information processing. An intrinsic object definition based on the homogeneity of the optical flow field of relevant objects, i.e., moving mainly fronto- parallel, is used. Velocity and spatial information are processed in separate pathways, resulting in either smooth or saccadic sensor movements. The program generates a dynamic shape model of the moving object and focuses its attention to regions where the object is expected. The system proved to behave in a stable manner under real-time conditions in complex natural environments and manages general object motion. In addition it exhibits several interesting abilities well-known from psychophysics like: catch-up saccades, grouping due to coherent motion, and optokinetic nystagmus.

The Dynamic Multisensory Engram: Neural Circuitry Underlying Crossmodal Object Recognition in Rats Changes with the Nature of Object Experience.

PubMed

Jacklin, Derek L; Cloke, Jacob M; Potvin, Alphonse; Garrett, Inara; Winters, Boyer D

2016-01-27

Rats, humans, and monkeys demonstrate robust crossmodal object recognition (CMOR), identifying objects across sensory modalities. We have shown that rats' performance of a spontaneous tactile-to-visual CMOR task requires functional integration of perirhinal (PRh) and posterior parietal (PPC) cortices, which seemingly provide visual and tactile object feature processing, respectively. However, research with primates has suggested that PRh is sufficient for multisensory object representation. We tested this hypothesis in rats using a modification of the CMOR task in which multimodal preexposure to the to-be-remembered objects significantly facilitates performance. In the original CMOR task, with no preexposure, reversible lesions of PRh or PPC produced patterns of impairment consistent with modality-specific contributions. Conversely, in the CMOR task with preexposure, PPC lesions had no effect, whereas PRh involvement was robust, proving necessary for phases of the task that did not require PRh activity when rats did not have preexposure; this pattern was supported by results from c-fos imaging. We suggest that multimodal preexposure alters the circuitry responsible for object recognition, in this case obviating the need for PPC contributions and expanding PRh involvement, consistent with the polymodal nature of PRh connections and results from primates indicating a key role for PRh in multisensory object representation. These findings have significant implications for our understanding of multisensory information processing, suggesting that the nature of an individual's past experience with an object strongly determines the brain circuitry involved in representing that object's multisensory features in memory. The ability to integrate information from multiple sensory modalities is crucial to the survival of organisms living in complex environments. Appropriate responses to behaviorally relevant objects are informed by integration of multisensory object features. We used crossmodal object recognition tasks in rats to study the neurobiological basis of multisensory object representation. When rats had no prior exposure to the to-be-remembered objects, the spontaneous ability to recognize objects across sensory modalities relied on functional interaction between multiple cortical regions. However, prior multisensory exploration of the task-relevant objects remapped cortical contributions, negating the involvement of one region and significantly expanding the role of another. This finding emphasizes the dynamic nature of cortical representation of objects in relation to past experience. Copyright © 2016 the authors 0270-6474/16/361273-17$15.00/0.

Principal Components Analysis on the spectral Bidirectional Reflectance Distribution Function of ceramic colour standards.

PubMed

Ferrero, A; Campos, J; Rabal, A M; Pons, A; Hernanz, M L; Corróns, A

2011-09-26

The Bidirectional Reflectance Distribution Function (BRDF) is essential to characterize an object's reflectance properties. This function depends both on the various illumination-observation geometries as well as on the wavelength. As a result, the comprehensive interpretation of the data becomes rather complex. In this work we assess the use of the multivariable analysis technique of Principal Components Analysis (PCA) applied to the experimental BRDF data of a ceramic colour standard. It will be shown that the result may be linked to the various reflection processes occurring on the surface, assuming that the incoming spectral distribution is affected by each one of these processes in a specific manner. Moreover, this procedure facilitates the task of interpolating a series of BRDF measurements obtained for a particular sample. © 2011 Optical Society of America

DNA in a Tunnel: A Comfy Spot for Recognition - or -The Structure of BsoBI Complexed with DNA. What can we Learn about Function via Structure Determination and how can this be Applied to Bone or Muscle Biology?

NASA Technical Reports Server (NTRS)

vanderWoerd, Mark

2004-01-01

The structure and function of a biologically active molecule are related. To understand its function, it is necessary (but not always sufficient) to know the structure of the molecule. There are many ways of relating the molecular function with the structure. Mutation analysis can identify pertinent amino acids of an enzyme, or alternatively structure comparison of the of two similar molecules with different function may lead to understanding which parts are responsible for a functional aspect, or a series of "structural cartoons" - enzyme structure, enzyme plus substrate, enzyme with transition state analog, and enzyme with product - may give insight in the function of a molecule. As an example we will discuss the structure and function of the restriction enzyme BsoBI from Bacillus stearothemzophilus in complex with its cognate DNA. The enzyme forms a unique complex with DNA in that it completely encircles the DNA. The structure reveals the enzyme-DNA contacts, how the DNA is distorted compared with the canonical forms, and elegantly shows how two distinct DNA sequences can be recognized with the same efficiency. Based on the structure we may also propose a hypothesis how the enzymatic mechanism works. The knowledge gained thru studies such as this one can be used to alter the function by changing the molecular structure. Usually this is done by design of inhibitors specifically active against and fitting into an active site of the enzyme of choice. In the case of BsoBI one of the objectives of the study was to alter the enzyme specificity. In bone biology there are many candidates available for molecular study in order to explain, alter, or (temporarily) suspend activity. For example, the understanding of a pathway that negatively regulates bone formation may be a good target for drug design to stimulate bone formation and have good potential as the basis for new countermeasures against bone loss. In principle the same approach may aid muscle atrophy, radiation damage, immune response changes and other risks identified for long-duration Space travel.

Modeling Patient Treatment With Medical Records: An Abstraction Hierarchy to Understand User Competencies and Needs

PubMed Central

2017-01-01

Background Health care is a complex sociotechnical system. Patient treatment is evolving and needs to incorporate the use of technology and new patient-centered treatment paradigms. Cognitive work analysis (CWA) is an effective framework for understanding complex systems, and work domain analysis (WDA) is useful for understanding complex ecologies. Although previous applications of CWA have described patient treatment, due to their scope of work patients were previously characterized as biomedical machines, rather than patient actors involved in their own care. Objective An abstraction hierarchy that characterizes patients as beings with complex social values and priorities is needed. This can help better understand treatment in a modern approach to care. The purpose of this study was to perform a WDA to represent the treatment of patients with medical records. Methods The methods to develop this model included the analysis of written texts and collaboration with subject matter experts. Our WDA represents the ecology through its functional purposes, abstract functions, generalized functions, physical functions, and physical forms. Results Compared with other work domain models, this model is able to articulate the nuanced balance between medical treatment, patient education, and limited health care resources. Concepts in the analysis were similar to the modeling choices of other WDAs but combined them in as a comprehensive, systematic, and contextual overview. The model is helpful to understand user competencies and needs. Future models could be developed to model the patient’s domain and enable the exploration of the shared decision-making (SDM) paradigm. Conclusion Our work domain model links treatment goals, decision-making constraints, and task workflows. This model can be used by system developers who would like to use ecological interface design (EID) to improve systems. Our hierarchy is the first in a future set that could explore new treatment paradigms. Future hierarchies could model the patient as a controller and could be useful for mobile app development. PMID:28754650

Penalized Nonlinear Least Squares Estimation of Time-Varying Parameters in Ordinary Differential Equations

PubMed Central

Cao, Jiguo; Huang, Jianhua Z.; Wu, Hulin

2012-01-01

Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online. PMID:23155351

Motorizing fibres with geometric zero-energy modes

NASA Astrophysics Data System (ADS)

Baumann, Arthur; Sánchez-Ferrer, Antoni; Jacomine, Leandro; Martinoty, Philippe; Le Houerou, Vincent; Ziebert, Falko; Kulić, Igor M.

2018-06-01

Responsive materials1-3 have been used to generate structures with built-in complex geometries4-6, linear actuators7-9 and microswimmers10-12. These results suggest that complex, fully functional machines composed solely from shape-changing materials might be possible13. Nonetheless, to accomplish rotary motion in these materials still relies on the classical wheel and axle motifs. Here we explore geometric zero-energy modes to elicit rotary motion in elastic materials in the absence of a rigid wheel travelling around an axle. We show that prestrained polymer fibres closed into rings exhibit self-actuation and continuous motion when placed between two heat baths due to elastic deformations that arise from rotational-symmetry breaking around the rod's axis. Our findings illustrate a simple but robust model to create active motion in mechanically prestrained objects.

ControlShell: A real-time software framework

NASA Technical Reports Server (NTRS)

Schneider, Stanley A.; Chen, Vincent W.; Pardo-Castellote, Gerardo

1994-01-01

The ControlShell system is a programming environment that enables the development and implementation of complex real-time software. It includes many building tools for complex systems, such as a graphical finite state machine (FSM) tool to provide strategic control. ControlShell has a component-based design, providing interface definitions and mechanisms for building real-time code modules along with providing basic data management. Some of the system-building tools incorporated in ControlShell are a graphical data flow editor, a component data requirement editor, and a state-machine editor. It also includes a distributed data flow package, an execution configuration manager, a matrix package, and an object database and dynamic binding facility. This paper presents an overview of ControlShell's architecture and examines the functions of several of its tools.

Subliminal perception of complex visual stimuli.

PubMed

Ionescu, Mihai Radu

2016-01-01

Rationale: Unconscious perception of various sensory modalities is an active subject of research though its function and effect on behavior is uncertain. Objective: The present study tried to assess if unconscious visual perception could occur with more complex visual stimuli than previously utilized. Methods and Results: Videos containing slideshows of indifferent complex images with interspersed frames of interest of various durations were presented to 24 healthy volunteers. The perception of the stimulus was evaluated with a forced-choice questionnaire while awareness was quantified by self-assessment with a modified awareness scale annexed to each question with 4 categories of awareness. At values of 16.66 ms of stimulus duration, conscious awareness was not possible and answers regarding the stimulus were random. At 50 ms, nonrandom answers were coupled with no self-reported awareness suggesting unconscious perception of the stimulus. At larger durations of stimulus presentation, significantly correct answers were coupled with a certain conscious awareness. Discussion: At values of 50 ms, unconscious perception is possible even with complex visual stimuli. Further studies are recommended with a focus on a range of interest of stimulus duration between 50 to 16.66 ms.

Observing complex action sequences: The role of the fronto-parietal mirror neuron system.

PubMed

Molnar-Szakacs, Istvan; Kaplan, Jonas; Greenfield, Patricia M; Iacoboni, Marco

2006-11-15

A fronto-parietal mirror neuron network in the human brain supports the ability to represent and understand observed actions allowing us to successfully interact with others and our environment. Using functional magnetic resonance imaging (fMRI), we wanted to investigate the response of this network in adults during observation of hierarchically organized action sequences of varying complexity that emerge at different developmental stages. We hypothesized that fronto-parietal systems may play a role in coding the hierarchical structure of object-directed actions. The observation of all action sequences recruited a common bilateral network including the fronto-parietal mirror neuron system and occipito-temporal visual motion areas. Activity in mirror neuron areas varied according to the motoric complexity of the observed actions, but not according to the developmental sequence of action structures, possibly due to the fact that our subjects were all adults. These results suggest that the mirror neuron system provides a fairly accurate simulation process of observed actions, mimicking internally the level of motoric complexity. We also discuss the results in terms of the links between mirror neurons, language development and evolution.

Hypolocomotion, anxiety and serotonin syndrome-like behavior contribute to the complex phenotype of serotonin transporter knockout mice.

PubMed

Kalueff, A V; Fox, M A; Gallagher, P S; Murphy, D L

2007-06-01

Although mice with a targeted disruption of the serotonin transporter (SERT) have been studied extensively using various tests, their complex behavioral phenotype is not yet fully understood. Here we assess in detail the behavior of adult female SERT wild type (+/+), heterozygous (+/-) and knockout (-/-) mice on an isogenic C57BL/6J background subjected to a battery of behavioral paradigms. Overall, there were no differences in the ability to find food or a novel object, nest-building, self-grooming and its sequencing, and horizontal rod balancing, indicating unimpaired sensory functions, motor co-ordination and behavioral sequencing. In contrast, there were striking reductions in exploration and activity in novelty-based tests (novel object, sticky label and open field tests), accompanied by pronounced thigmotaxis, suggesting that combined hypolocomotion and anxiety (rather than purely anxiety) influence the SERT -/- behavioral phenotype. Social interaction behaviors were also markedly reduced. In addition, SERT -/- mice tended to move close to the ground, frequently displayed spontaneous Straub tail, tics, tremor and backward gait - a phenotype generally consistent with 'serotonin syndrome'-like behavior. In line with replicated evidence of much enhanced serotonin availability in SERT -/- mice, this serotonin syndrome-like state may represent a third factor contributing to their behavioral profile. An understanding of the emerging complexity of SERT -/- mouse behavior is crucial for a detailed dissection of their phenotype and for developing further neurobehavioral models using these mice.

Young stellar population and star formation history ofW4 HII region/Cluster Complex

NASA Astrophysics Data System (ADS)

Panwar, Neelam

2018-04-01

The HII region/cluster complex has been a subject of numerous investigations to study the feedback effect of massive stars on their surroundings. Massive stars not only alter the morphology of the parental molecular clouds, but also influence star formation, circumstellar disks and the mass function of low-mass stars in their vicinity. However, most of the studies of low-mass stellar content of the HII regions are limited only to the nearby regions. We study the star formation in the W4 HII region using deep optical observations obtained with the archival data from Canada - France - Hawaii Telescope, Two-Micron All Sky Survey, Spitzer, Herschel and Chandra. We investigate the spatial distribution of young stellar objects in the region, their association with the remnant molecular clouds, and search for the clustering to establish the sites of recent star formation. Our analysis suggests that the influence of massive stars on circumstellar disks is significant only to thei! r immediate neighborhood. The spatial correlation of the young stars with the distribution of gas and dust of the complex indicate that the clusters would have formed in a large filamentary cloud. The observing facilities at the 3.6-m Devasthal Optical Telescope (DOT), providing high-resolution spectral and imaging capabilities, will fulfill the major objectives in the study of HII regions.

High Abundance of Ions in Cosmic Ices

NASA Technical Reports Server (NTRS)

Gudipati, Murthy S.; Allamandola, Louis J.; Fonda, Mark (Technical Monitor)

2002-01-01

Water-rich, mixed molecular ices and polycyclic aromatic hydrocarbons (PAHs) are common throughout interstellar molecular clouds and the Solar System. Vacuum ultraviolet (VUV) irradiation and particle bombardment of these abiotic ices produces complex organic species, including important biogenic molecules such as amino acids and functionalized PAHs which may have played a role in the origin of life. This ability of such water-rich, oxygen dominated ices to promote production of complex organic species is surprising and points to an important, unusual, but previously overlooked mechanism at play within the ice. Here we report the nature of this mechanism using electronic spectroscopy. VUV-irradiation of PAH/H2O ices leads to an unprecedented and efficient (greater than 70 %) conversion of the neutral PAHs to their cation form (PAH+). Further, these H2O/PAH+ ices are stabile at temperatures below 50 K, a temperature domain common throughout interstellar clouds and the Solar System. Between 50 and 125 K they react to form the complex organics. In view of this, we conclude that charged PAHs and other molecular ions should be common and abundant in many cosmic ices. The chemical, spectroscopic and physical properties of these ion-rich ices can be of fundamental importance for objects as diverse as comets, planets, and molecular clouds and may account for several poorly understood phenomena associated with each of these object classes.

Interpolation on the manifold of K component GMMs.

PubMed

Kim, Hyunwoo J; Adluru, Nagesh; Banerjee, Monami; Vemuri, Baba C; Singh, Vikas

2015-12-01

Probability density functions (PDFs) are fundamental objects in mathematics with numerous applications in computer vision, machine learning and medical imaging. The feasibility of basic operations such as computing the distance between two PDFs and estimating a mean of a set of PDFs is a direct function of the representation we choose to work with. In this paper, we study the Gaussian mixture model (GMM) representation of the PDFs motivated by its numerous attractive features. (1) GMMs are arguably more interpretable than, say, square root parameterizations (2) the model complexity can be explicitly controlled by the number of components and (3) they are already widely used in many applications. The main contributions of this paper are numerical algorithms to enable basic operations on such objects that strictly respect their underlying geometry. For instance, when operating with a set of K component GMMs, a first order expectation is that the result of simple operations like interpolation and averaging should provide an object that is also a K component GMM. The literature provides very little guidance on enforcing such requirements systematically. It turns out that these tasks are important internal modules for analysis and processing of a field of ensemble average propagators (EAPs), common in diffusion weighted magnetic resonance imaging. We provide proof of principle experiments showing how the proposed algorithms for interpolation can facilitate statistical analysis of such data, essential to many neuroimaging studies. Separately, we also derive interesting connections of our algorithm with functional spaces of Gaussians, that may be of independent interest.

"Failure-to-Identify" Hunting Incidents: A Resilience Engineering Approach.

PubMed

Bridges, Karl E; Corballis, Paul M; Hollnagel, Erik

2018-03-01

Objective The objective was to develop an understanding, using the Functional Resonance Analysis Method (FRAM), of the factors that could cause a deer hunter to misidentify their intended target. Background Hunting is a popular activity in many communities. However, hunters vary considerably based on training, experience, and expertise. Surprisingly, safety in hunting has not received much attention, especially failure-to-identify hunting incidents. These are incidents in which the hunter, after spotting and targeting their quarry, discharge their firearm only to discover they have been spotting and targeting another human, an inanimate object, or flora by mistake. The hunter must consider environment, target, time of day, weather, and many other factors-continuously evaluating whether the hunt should continue. To understand how these factors can relate to one another is fundamental to begin to understand how incidents happen. Method Workshops with highly experienced and active hunters led to the development of a FRAM model detailing the functions of a "Hunting FRAM." The model was evaluated for correctness based on confidential and anonymous near-miss event submissions by hunters. Results A FRAM model presenting the functions of a hunt was produced, evaluated, and accepted. Using the model, potential sources of incidents or other unintended outcomes were identified, which in turn helped to improve the model. Conclusion Utilizing principles of understanding and visualization tools of the FRAM, the findings create a foundation for safety improvements potentially through training or safety messages based on an increased understanding of the complexity of hunting.

Differentiating zones at periodontal ligament-bone and periodontal ligament-cementum entheses.

PubMed

Lee, J-H; Pryce, B A; Schweitzer, R; Ryder, M I; Ho, S P

2015-12-01

The structural and functional integrity of bone-periodontal ligament (PDL)-cementum complex stems from the load-bearing attachment sites (entheses) between soft (PDL) and hard (bone, cementum) tissues. These attachment sites are responsible for the maintenance of a bone-PDL-cementum complex biomechanical function. The objective was to investigate changes in spatiotemporal expression of key biomolecules in developing and functionally active entheses. Multilabeling technique was performed on hemimandibles of 3 wk and 3 mo-old scleraxis-GFP transgenic mice for CD146, CD31, NG2, osterix and bone sialoprotein. Regions of dominant stretch within the PDL were evaluated by identifying directionality of collagen fibrils, PDL fibroblasts and PDL cell cytoskeleton. CD146+ cells adjacent to CD31+ vasculature were identified at PDL-bone enthesis. NG2+ cells were located at coronal bone-PDL and apical cementum-PDL entheses in the 3-wk-old group, but at 3 mo, NG2 was positive at the entheses of the apical region and alveolar crest. NG2 and osterix were colocalized at the osteoid and cementoid regions of the PDL-bone and PDL-cementum entheses. Bone sialoprotein was prominent at the apical region of 3-wk-old mice. The directionality of collagen fibers, fibroblasts and their cytoskeleton overlapped, except in the apical region of 3 wk. Colocalization of biomolecules at zones of the PDL adjacent to attachment sites may be essential for the formation of precementum and osteoid interfaces at a load-bearing bone-PDL-tooth fibrous joint. Biophysical cues resulting from development and function can regulate recruitment and differentiation of stem cells potentially from a vascular origin toward osteo- and cemento-blastic lineages at the PDL-bone and PDL-cementum entheses. Investigating the coupled effect of biophysical and biochemical stimuli leading to cell differentiation at the functional attachment sites is critical for developing regeneration strategies to enable functional reconstruction of the periodontal complex. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Designing effective animations for computer science instruction

NASA Astrophysics Data System (ADS)

Grillmeyer, Oliver

This study investigated the potential for animations of Scheme functions to help novice computer science students understand difficult programming concepts. These animations used an instructional framework inspired by theories of constructivism and knowledge integration. The framework had students make predictions, reflect, and specify examples to animate to promote autonomous learning and result in more integrated knowledge. The framework used animated pivotal cases to help integrate disconnected ideas and restructure students' incomplete ideas by illustrating weaknesses in their existing models. The animations scaffolded learners, making the thought processes of experts more visible by modeling complex and tacit information. The animation design was guided by prior research and a methodology of design and refinement. Analysis of pilot studies led to the development of four design concerns to aid animation designers: clearly illustrate the mapping between objects in animations with the actual objects they represent, show causal connections between elements, draw attention to the salient features of the modeled system, and create animations that reduce complexity. Refined animations based on these design concerns were compared to computer-based tools, text-based instruction, and simpler animations that do not embody the design concerns. Four studies comprised this dissertation work. Two sets of animated presentations of list creation functions were compared to control groups. No significant differences were found in support of animations. Three different animated models of traces of recursive functions ranging from concrete to abstract representations were compared. No differences in learning gains were found between the three models in test performance. Three models of animations of applicative operators were compared with students using the replacement modeler and the Scheme interpreter. Significant differences were found favoring animations that addressed causality and salience in their design. Lastly, two binary tree search algorithm animations designed to reduce complexity were compared with hand-tracing of calls. Students made fewer mistakes in predicting the tree traversal when guided by the animations. However, the posttest findings were inconsistent. In summary, animations designed based on the design concerns did not consistently add value to instruction in the form investigated in this research.

Locomotor activity, object exploration and space preference in children with autism and Down syndrome.

PubMed

Kawa, Rafał; Pisula, Ewa

2010-01-01

There have been ambiguous accounts of exploration in children with intellectual disabilities with respect to the course of that exploration, and in particular the relationship between the features of explored objects and exploratory behaviour. It is unclear whether reduced exploratory activity seen with object exploration but not with locomotor activity is autism-specific or if it is also present in children with other disabilities. The purpose of the present study was to compare preschool children with autism with their peers with Down syndrome and typical development in terms of locomotor activity and object exploration and to determine whether the complexity of explored objects affects the course of exploration activity in children with autism. In total there were 27 children in the study. The experimental room was divided into three zones equipped with experimental objects providing visual stimulation of varying levels of complexity. Our results indicate that children with autism and Down syndrome differ from children with typical development in terms of some measures of object exploration (i.e. looking at objects) and time spent in the zone with the most visually complex objects.

A simple, low-cost conductive composite material for 3D printing of electronic sensors.

PubMed

Leigh, Simon J; Bradley, Robert J; Purssell, Christopher P; Billson, Duncan R; Hutchins, David A

2012-01-01

3D printing technology can produce complex objects directly from computer aided digital designs. The technology has traditionally been used by large companies to produce fit and form concept prototypes ('rapid prototyping') before production. In recent years however there has been a move to adopt the technology as full-scale manufacturing solution. The advent of low-cost, desktop 3D printers such as the RepRap and Fab@Home has meant a wider user base are now able to have access to desktop manufacturing platforms enabling them to produce highly customised products for personal use and sale. This uptake in usage has been coupled with a demand for printing technology and materials able to print functional elements such as electronic sensors. Here we present formulation of a simple conductive thermoplastic composite we term 'carbomorph' and demonstrate how it can be used in an unmodified low-cost 3D printer to print electronic sensors able to sense mechanical flexing and capacitance changes. We show how this capability can be used to produce custom sensing devices and user interface devices along with printed objects with embedded sensing capability. This advance in low-cost 3D printing with offer a new paradigm in the 3D printing field with printed sensors and electronics embedded inside 3D printed objects in a single build process without requiring complex or expensive materials incorporating additives such as carbon nanotubes.

Dependence of behavioral performance on material category in an object grasping task with monkeys.

PubMed

Yokoi, Isao; Tachibana, Atsumichi; Minamimoto, Takafumi; Goda, Naokazu; Komatsu, Hidehiko

2018-05-02

Material perception is an essential part of our cognitive function that enables us to properly interact with our complex daily environment. One important aspect of material perception is its multimodal nature. When we see an object, we generally recognize its haptic properties as well as its visual properties. Consequently, one must examine behavior using real objects that are perceived both visually and haptically to fully understand the characteristics of material perception. As a first step, we examined whether there is any difference in the behavioral responses to different materials in monkeys trained to perform an object grasping task in which they saw and grasped rod-shaped real objects made of various materials. We found that the monkeys' behavior in the grasping task, measured based on the success rate and the pulling force, differed depending on the material category. Monkeys easily and correctly grasped objects of some materials, such as metal and glass, but failed to grasp objects of other materials. In particular, monkeys avoided grasping fur-covered objects. The differences in the behavioral responses to the material categories cannot be explained solely based on the degree of familiarity with the different materials. These results shed light on the organization of multimodal representation of materials, where their biological significance is an important factor. In addition, a monkey that avoided touching real fur-covered objects readily touched images of the same objects presented on a CRT display. This suggests employing real objects is important when studying behaviors related to material perception.

Coupling HYDRUS-1D Code with PA-DDS Algorithms for Inverse Calibration

NASA Astrophysics Data System (ADS)

Wang, Xiang; Asadzadeh, Masoud; Holländer, Hartmut

2017-04-01

Numerical modelling requires calibration to predict future stages. A standard method for calibration is inverse calibration where generally multi-objective optimization algorithms are used to find a solution, e.g. to find an optimal solution of the van Genuchten Mualem (VGM) parameters to predict water fluxes in the vadose zone. We coupled HYDRUS-1D with PA-DDS to add a new, robust function for inverse calibration to the model. The PA-DDS method is a recently developed multi-objective optimization algorithm, which combines Dynamically Dimensioned Search (DDS) and Pareto Archived Evolution Strategy (PAES). The results were compared to a standard method (Marquardt-Levenberg method) implemented in HYDRUS-1D. Calibration performance is evaluated using observed and simulated soil moisture at two soil layers in the Southern Abbotsford, British Columbia, Canada in the terms of the root mean squared error (RMSE) and the Nash-Sutcliffe Efficiency (NSE). Results showed low RMSE values of 0.014 and 0.017 and strong NSE values of 0.961 and 0.939. Compared to the results by the Marquardt-Levenberg method, we received better calibration results for deeper located soil sensors. However, VGM parameters were similar comparing with previous studies. Both methods are equally computational efficient. We claim that a direct implementation of PA-DDS into HYDRUS-1D should reduce the computation effort further. This, the PA-DDS method is efficient for calibrating recharge for complex vadose zone modelling with multiple soil layer and can be a potential tool for calibration of heat and solute transport. Future work should focus on the effectiveness of PA-DDS for calibrating more complex versions of the model with complex vadose zone settings, with more soil layers, and against measured heat and solute transport. Keywords: Recharge, Calibration, HYDRUS-1D, Multi-objective Optimization

Direct measurement of a nonequilibrium system entropy using a feedback trap

NASA Astrophysics Data System (ADS)

Gavrilov, Momčilo; Bechhoefer, John

2017-08-01

Feedback traps are tools for trapping single charged objects in solution. They periodically measure an object's position and apply a feedback force to counteract Brownian motion. The feedback force can be calculated as a gradient of a potential function, effectively creating a "virtual potential." Its flexibility regarding the choice of form of the potential gives an opportunity to explore various fundamental questions in stochastic thermodynamics. Here, we review the theory behind feedback traps and apply it to measuring the average work required to erase a fraction of a bit of information. The results agree with predictions based on the nonequilibrium system entropy. With this example, we also show how a feedback trap can easily implement the complex erasure protocols required to reach ultimate thermodynamic limits.

If You're Not Measuring, You're Guessing: The Advent of Objective Concussion Assessments.

PubMed

Broglio, Steven P; Guskiewicz, Kevin M; Norwig, John

2017-03-01

Sport-related concussion remains one of the most complex injuries presented to sports medicine professionals. Although the injury has been recognized since ancient times, the concussion-assessment process has seen significant advances over the last 30 years. This review outlines the addition of objective measures to the clinical evaluation of the concussed athlete, beginning in the 1980s and continuing through the modern age. International and domestic organizations now describe standardized symptom reports, neurostatus and neurocognitive-function evaluations, and postural-control measures as standards of medical care, a significant shift from a short time ago. Despite this progression, much about the injury remains unknown, including new clinical and research-based assessment techniques and how the injury may influence the athlete's cognitive health over the long term.

Mycobacteriophage genome database.

PubMed

Joseph, Jerrine; Rajendran, Vasanthi; Hassan, Sameer; Kumar, Vanaja

2011-01-01

Mycobacteriophage genome database (MGDB) is an exclusive repository of the 64 completely sequenced mycobacteriophages with annotated information. It is a comprehensive compilation of the various gene parameters captured from several databases pooled together to empower mycobacteriophage researchers. The MGDB (Version No.1.0) comprises of 6086 genes from 64 mycobacteriophages classified into 72 families based on ACLAME database. Manual curation was aided by information available from public databases which was enriched further by analysis. Its web interface allows browsing as well as querying the classification. The main objective is to collect and organize the complexity inherent to mycobacteriophage protein classification in a rational way. The other objective is to browse the existing and new genomes and describe their functional annotation. The database is available for free at http://mpgdb.ibioinformatics.org/mpgdb.php.

Abnormal computerized dynamic posturography findings in dizzy patients with normal ENG results.

PubMed

Sataloff, Robert T; Hawkshaw, Mary J; Mandel, Heidi; Zwislewski, Amy B; Armour, Jonathan; Mandel, Steven

2005-04-01

The complexities of the balance system create difficulties for professionals interested in testing equilibrium function objectively. Traditionally, electronystagmography (ENG) has been used for this purpose, but it provides information on only a limited portion of the equilibrium system. Computerized dynamic posturography (CDP) is less specific than ENG, but it provides more global insight into a patient's ability to maintain equilibrium under more challenging environmental circumstances. CD Palso appears to be valuable in obtaining objective confirmation of an abnormality in some dizzy patients whose ENG findings are normal. Our review of 33 patients with normal ENG results and abnormal CDP findings suggests that posturography is useful for confirming or quantifying a balance abnormality in some patients whose complaints cannot be confirmed by other tests frequently used by otologists.

Multispectral Wavefronts Retrieval in Digital Holographic Three-Dimensional Imaging Spectrometry

NASA Astrophysics Data System (ADS)

Yoshimori, Kyu

2010-04-01

This paper deals with a recently developed passive interferometric technique for retrieving a set of spectral components of wavefronts that are propagating from a spatially incoherent, polychromatic object. The technique is based on measurement of 5-D spatial coherence function using a suitably designed interferometer. By applying signal processing, including aperture synthesis and spectral decomposition, one may obtains a set of wavefronts of different spectral bands. Since each wavefront is equivalent to the complex Fresnel hologram at a particular spectrum of the polychromatic object, application of the conventional Fresnel transform yields 3-D image of different spectrum. Thus, this technique of multispectral wavefronts retrieval provides a new type of 3-D imaging spectrometry based on a fully passive interferometry. Experimental results are also shown to demonstrate the validity of the method.

Combining Multiobjective Optimization and Cluster Analysis to Study Vocal Fold Functional Morphology

PubMed Central

Palaparthi, Anil; Riede, Tobias

2017-01-01

Morphological design and the relationship between form and function have great influence on the functionality of a biological organ. However, the simultaneous investigation of morphological diversity and function is difficult in complex natural systems. We have developed a multiobjective optimization (MOO) approach in association with cluster analysis to study the form-function relation in vocal folds. An evolutionary algorithm (NSGA-II) was used to integrate MOO with an existing finite element model of the laryngeal sound source. Vocal fold morphology parameters served as decision variables and acoustic requirements (fundamental frequency, sound pressure level) as objective functions. A two-layer and a three-layer vocal fold configuration were explored to produce the targeted acoustic requirements. The mutation and crossover parameters of the NSGA-II algorithm were chosen to maximize a hypervolume indicator. The results were expressed using cluster analysis and were validated against a brute force method. Results from the MOO and the brute force approaches were comparable. The MOO approach demonstrated greater resolution in the exploration of the morphological space. In association with cluster analysis, MOO can efficiently explore vocal fold functional morphology. PMID:24771563

Multi-objective decoupling algorithm for active distance control of intelligent hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Luo, Yugong; Chen, Tao; Li, Keqiang

2015-12-01

The paper presents a novel active distance control strategy for intelligent hybrid electric vehicles (IHEV) with the purpose of guaranteeing an optimal performance in view of the driving functions, optimum safety, fuel economy and ride comfort. Considering the complexity of driving situations, the objects of safety and ride comfort are decoupled from that of fuel economy, and a hierarchical control architecture is adopted to improve the real-time performance and the adaptability. The hierarchical control structure consists of four layers: active distance control object determination, comprehensive driving and braking torque calculation, comprehensive torque distribution and torque coordination. The safety distance control and the emergency stop algorithms are designed to achieve the safety and ride comfort goals. The optimal rule-based energy management algorithm of the hybrid electric system is developed to improve the fuel economy. The torque coordination control strategy is proposed to regulate engine torque, motor torque and hydraulic braking torque to improve the ride comfort. This strategy is verified by simulation and experiment using a forward simulation platform and a prototype vehicle. The results show that the novel control strategy can achieve the integrated and coordinated control of its multiple subsystems, which guarantees top performance of the driving functions and optimum safety, fuel economy and ride comfort.

Topology-independent shape modeling scheme

NASA Astrophysics Data System (ADS)

Malladi, Ravikanth; Sethian, James A.; Vemuri, Baba C.

1993-06-01

Developing shape models is an important aspect of computer vision research. Geometric and differential properties of the surface can be computed from shape models. They also aid the tasks of object representation and recognition. In this paper we present an innovative new approach for shape modeling which, while retaining important features of the existing methods, overcomes most of their limitations. Our technique can be applied to model arbitrarily complex shapes, shapes with protrusions, and to situations where no a priori assumption about the object's topology can be made. A single instance of our model, when presented with an image having more than one object of interest, has the ability to split freely to represent each object. Our method is based on the level set ideas developed by Osher & Sethian to follow propagating solid/liquid interfaces with curvature-dependent speeds. The interface is a closed, nonintersecting, hypersurface flowing along its gradient field with constant speed or a speed that depends on the curvature. We move the interface by solving a `Hamilton-Jacobi' type equation written for a function in which the interface is a particular level set. A speed function synthesized from the image is used to stop the interface in the vicinity of the object boundaries. The resulting equations of motion are solved by numerical techniques borrowed from the technology of hyperbolic conservation laws. An added advantage of this scheme is that it can easily be extended to any number of space dimensions. The efficacy of the scheme is demonstrated with numerical experiments on synthesized images and noisy medical images.

TkPl_SU: An Open-source Perl Script Builder for Seismic Unix

NASA Astrophysics Data System (ADS)

Lorenzo, J. M.

2017-12-01

TkPl_SU (beta) is a graphical user interface (GUI) to select parameters for Seismic Unix (SU) modules. Seismic Unix (Stockwell, 1999) is a widely distributed free software package for processing seismic reflection and signal processing. Perl/Tk is a mature, well-documented and free object-oriented graphical user interface for Perl. In a classroom environment, shell scripting of SU modules engages students and helps focus on the theoretical limitations and strengths of signal processing. However, complex interactive processing stages, e.g., selection of optimal stacking velocities, killing bad data traces, or spectral analysis requires advanced flows beyond the scope of introductory classes. In a research setting, special functionality from other free seismic processing software such as SioSeis (UCSD-NSF) can be incorporated readily via an object-oriented style to programming. An object oriented approach is a first step toward efficient extensible programming of multi-step processes, and a simple GUI simplifies parameter selection and decision making. Currently, in TkPl_SU, Perl 5 packages wrap 19 of the most common SU modules that are used in teaching undergraduate and first-year graduate student classes (e.g., filtering, display, velocity analysis and stacking). Perl packages (classes) can advantageously add new functionality around each module and clarify parameter names for easier usage. For example, through the use of methods, packages can isolate the user from repetitive control structures, as well as replace the names of abbreviated parameters with self-describing names. Moose, an extension of the Perl 5 object system, greatly facilitates an object-oriented style. Perl wrappers are self-documenting via Perl programming document markup language.

Modeling Electromagnetic Scattering From Complex Inhomogeneous Objects

NASA Technical Reports Server (NTRS)

Deshpande, Manohar; Reddy, C. J.

2011-01-01

This software innovation is designed to develop a mathematical formulation to estimate the electromagnetic scattering characteristics of complex, inhomogeneous objects using the finite-element-method (FEM) and method-of-moments (MoM) concepts, as well as to develop a FORTRAN code called FEMOM3DS (Finite Element Method and Method of Moments for 3-Dimensional Scattering), which will implement the steps that are described in the mathematical formulation. Very complex objects can be easily modeled, and the operator of the code is not required to know the details of electromagnetic theory to study electromagnetic scattering.

Synthesis of Pyridine– and Pyrazine–BF 3 Complexes and Their Characterization in Solution and Solid State

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

Chénard, Etienne; Sutrisno, Andre; Zhu, Lingyang

2016-03-31

Following the discovery of the redox-active 1,4- bis-BF 3-quinoxaline complex, we undertook a structure- activity study with the objective to understand the active nature of the quinoxaline complex. Through systematic synthesis and characterization, we have compared complexes prepared from pyridine and pyrazine derivatives, as heterocyclic core analogues. This paper reports the structural requirements that give rise to the electrochemical features of the 1,4-bis-BF 3-quinoxaline adduct. Using solution and solidstate NMR spectroscopy, the role of aromatic ring fusion and nitrogen incorporation in bonding and electronics was elucidated. We establish the boron atom location and its interaction with its environment from 1Dmore » and 2D solution NMR, X-ray diffraction analysis, and 11B solid-state NMR experiments. Crystallographic analysis of single crystals helped to correlate the boron geometry with 11B quadrupolar coupling constant (CQ) and asymmetry parameter (ηQ), extracted from 11B solid-state NMR spectra. Additionally, computations based on density functional theory were performed to predict electrochemical behavior of the BF 3-heteroaromatic complexes. We then experimentally measured electrochemical potential using cyclic voltammetry and found that the redox potentials and CQ values are similarly affected by electronic changes in the complexes.« less

Long-Term Moderate Exercise Rescues Age-Related Decline in Hippocampal Neuronal Complexity and Memory.

PubMed

Tsai, Sheng-Feng; Ku, Nai-Wen; Wang, Tzu-Feng; Yang, Yan-Hsiang; Shih, Yao-Hsiang; Wu, Shih-Ying; Lee, Chu-Wan; Yu, Megan; Yang, Ting-Ting; Kuo, Yu-Min

2018-05-07

Aging impairs hippocampal neuroplasticity and hippocampus-related learning and memory. In contrast, exercise training is known to improve hippocampal neuronal function. However, whether exercise is capable of restoring memory function in old animals is less clear. Here, we investigated the effects of exercise on the hippocampal neuroplasticity and memory functions during aging. Young (3 months), middle-aged (9-12 months), and old (18 months) mice underwent moderate-intensity treadmill running training for 6 weeks, and their hippocampus-related learning and memory, and the plasticity of their CA1 neurons was evaluated. The memory performance (Morris water maze and novel object recognition tests), and dendritic complexity (branch and length) and spine density of their hippocampal CA1 neurons decreased as their age increased. The induction and maintenance of high-frequency stimulation-induced long-term potentiation in the CA1 area and the expressions of neuroplasticity-related proteins were not affected by age. Treadmill running increased CA1 neuron long-term potentiation and dendritic complexity in all three age groups, and it restored the learning and memory ability in middle-aged and old mice. Furthermore, treadmill running upregulated the hippocampal expressions of brain-derived neurotrophic factor and monocarboxylate transporter-4 in middle-aged mice, glutamine synthetase in old mice, and full-length TrkB in middle-aged and old mice. The hippocampus-related memory function declines from middle age, but long-term moderate-intensity running effectively increased hippocampal neuroplasticity and memory in mice of different ages, even when the memory impairment had progressed to an advanced stage. Thus, long-term, moderate intensity exercise training might be a way of delaying and treating aging-related memory decline. © 2018 S. Karger AG, Basel.

Rapamycin toxicity in MIN6 cells and rat and human islets is mediated by the inhibition of mTOR complex 2 (mTORC2).

PubMed

Barlow, A D; Xie, J; Moore, C E; Campbell, S C; Shaw, J A M; Nicholson, M L; Herbert, T P

2012-05-01

Rapamycin (sirolimus) is one of the primary immunosuppressants for islet transplantation. Yet there is evidence that the long-term treatment of islet-transplant patients with rapamycin may be responsible for subsequent loss of islet graft function and viability. Therefore, the primary objective of this study was to elucidate the molecular mechanism of rapamycin toxicity in beta cells. Experiments were performed on isolated rat and human islets of Langerhans and MIN6 cells. The effects of rapamycin and the roles of mammalian target of rapamycin complex 2 (mTORC2)/protein kinase B (PKB) on beta cell signalling, function and viability were investigated using cell viability assays, insulin ELISA assays, kinase assays, western blotting, pharmacological inhibitors, small interfering (si)RNA and through the overproduction of a constitutively active mutant of PKB. Rapamycin treatment of MIN6 cells and islets of Langerhans resulted in a loss of cell function and viability. Although rapamycin acutely inhibited mTOR complex 1 (mTORC1), the toxic effects of rapamycin were more closely correlated to the dissociation and inactivation of mTORC2 and the inhibition of PKB. Indeed, the overproduction of constitutively active PKB protected islets from rapamycin toxicity whereas the inhibition of PKB led to a loss of cell viability. Moreover, the selective inactivation of mTORC2 using siRNA directed towards rapamycin-insensitive companion of target of rapamycin (RICTOR), mimicked the toxic effects of chronic rapamycin treatment. This report provides evidence that rapamycin toxicity is mediated by the inactivation of mTORC2 and the inhibition of PKB and thus reveals the molecular basis of rapamycin toxicity and the essential role of mTORC2 in maintaining beta cell function and survival.

Optimisation of flight dynamic control based on many-objectives meta-heuristic: a comparative study

NASA Astrophysics Data System (ADS)

Bureerat, Sujin; Pholdee, Nantiwat; Radpukdee, Thana

2018-05-01

Development of many objective meta-heuristics (MnMHs) is a currently interesting topic as they are suitable to real applications of optimisation problems which usually require many ob-jectives. However, most of MnMHs have been mostly developed and tested based on stand-ard testing functions while the use of MnMHs to real applications is rare. Therefore, in this work, MnMHs are applied for optimisation design of flight dynamic control. The design prob-lem is posed to find control gains for minimising; the control effort, the spiral root, the damp-ing in roll root, sideslip angle deviation, and maximising; the damping ratio of the dutch-roll complex pair, the dutch-roll frequency, bank angle at pre-specified times 1 seconds and 2.8 second subjected to several constraints based on Military Specifications (1969) requirement. Several established many-objective meta-heuristics (MnMHs) are used to solve the problem while their performances are compared. With this research work, performance of several MnMHs for flight control is investigated. The results obtained will be the baseline for future development of flight dynamic and control.

Coastline complexity: A parameter for functional classification of coastal environments

USGS Publications Warehouse

Bartley, J.D.; Buddemeier, R.W.; Bennett, D.A.

2001-01-01

To understand the role of the world's coastal zone (CZ) in global biogeochemical fluxes (particularly those of carbon, nitrogen, phosphorus, and sediments) we must generalise from a limited number of observations associated with a few well-studied coastal systems to the global scale. Global generalisation must be based on globally available data and on robust techniques for classification and upscaling. These requirements impose severe constraints on the set of variables that can be used to extract information about local CZ functions such as advective and metabolic fluxes, and differences resulting from changes in biotic communities. Coastal complexity (plan-view tortuosity of the coastline) is a potentially useful parameter, since it interacts strongly with both marine and terrestrial forcing functions to determine coastal energy regimes and water residence times, and since 'open' vs. 'sheltered' categories are important components of most coastal habitat classification schemes. This study employs the World Vector Shoreline (WVS) dataset, originally developed at a scale of 1:250 000. Coastline complexity measures are generated using a modification of the Angle Measurement Technique (AMT), in which the basic measurement is the angle between two lines of specified length drawn from a selected point to the closest points of intersection with the coastline. Repetition of these measurements for different lengths at the same point yields a distribution of angles descriptive of the extent and scale of complexity in the vicinity of that point; repetition of the process at different points on the coast provides a basis for comparing both the extent and the characteristic scale of coastline variation along different reaches of the coast. The coast of northwestern Mexico (Baja California and the Gulf of California) was used as a case study for initial development and testing of the method. The characteristic angle distribution plots generated by the AMT analysis were clustered using LOICZVIEW, a high dimensionality clustering routine developed for large-scale coastal classification studies. The results show distinctive differences in coastal environments that have the potential for interpretation in terms of both biotic and hydrogeochemical environments, and that can be related to the resolution limits and uncertainties of the shoreline data used. These objective, quantitative measures of coastal complexity as a function of scale can be further developed and combined with other data sets to provide a key component of functional classification of coastal environments. ?? 2001 Elsevier Science B.V. All rights reserved.

Direct Metal Deposition of Functional Graded Structures in Ti- Al System

NASA Astrophysics Data System (ADS)

Shishkovsky, I.; Missemer, F.; Smurov, I.

A direct laser metal deposition (DLMD) technology with co-axial powder injection is used to fabricate a complex functional graded structure (FGS) fabrication. The aim of the study is to demonstrate the possibility to produce intermetallic phases in the Ti-Al powder systems in the course of a single-step DMD process. Besides, relationships between the main laser cladding parameters and the intermetallic phase structures of the built-up objects have been studied. In our research we applied the optical microscopy, X-ray analysis, microhardness measurement and SEM with EDX analysis of the laser-fabricated intermetallics. The discussion of the mechanisms of Ti x Al y (x,y = 1.3) intermetallic transformations in exothermal reactions is also offered in the report.

Aversive Learning Modulates Cortical Representations of Object Categories

PubMed Central

Dunsmoor, Joseph E.; Kragel, Philip A.; Martin, Alex; LaBar, Kevin S.

2014-01-01

Experimental studies of conditioned learning reveal activity changes in the amygdala and unimodal sensory cortex underlying fear acquisition to simple stimuli. However, real-world fears typically involve complex stimuli represented at the category level. A consequence of category-level representations of threat is that aversive experiences with particular category members may lead one to infer that related exemplars likewise pose a threat, despite variations in physical form. Here, we examined the effect of category-level representations of threat on human brain activation using 2 superordinate categories (animals and tools) as conditioned stimuli. Hemodynamic activity in the amygdala and category-selective cortex was modulated by the reinforcement contingency, leading to widespread fear of different exemplars from the reinforced category. Multivariate representational similarity analyses revealed that activity patterns in the amygdala and object-selective cortex were more similar among exemplars from the threat versus safe category. Learning to fear animate objects was additionally characterized by enhanced functional coupling between the amygdala and fusiform gyrus. Finally, hippocampal activity co-varied with object typicality and amygdala activation early during training. These findings provide novel evidence that aversive learning can modulate category-level representations of object concepts, thereby enabling individuals to express fear to a range of related stimuli. PMID:23709642

SimGen: A General Simulation Method for Large Systems.

PubMed

Taylor, William R

2017-02-03

SimGen is a stand-alone computer program that reads a script of commands to represent complex macromolecules, including proteins and nucleic acids, in a structural hierarchy that can then be viewed using an integral graphical viewer or animated through a high-level application programming interface in C++. Structural levels in the hierarchy range from α-carbon or phosphate backbones through secondary structure to domains, molecules, and multimers with each level represented in an identical data structure that can be manipulated using the application programming interface. Unlike most coarse-grained simulation approaches, the higher-level objects represented in SimGen can be soft, allowing the lower-level objects that they contain to interact directly. The default motion simulated by SimGen is a Brownian-like diffusion that can be set to occur across all levels of representation in the hierarchy. Links can also be defined between objects, which, when combined with large high-level random movements, result in an effective search strategy for constraint satisfaction, including structure prediction from predicted pairwise distances. The implementation of SimGen makes use of the hierarchic data structure to avoid unnecessary calculation, especially for collision detection, allowing it to be simultaneously run and viewed on a laptop computer while simulating large systems of over 20,000 objects. It has been used previously to model complex molecular interactions including the motion of a myosin-V dimer "walking" on an actin fibre, RNA stem-loop packing, and the simulation of cell motion and aggregation. Several extensions to this original functionality are described. Copyright © 2016 The Francis Crick Institute. Published by Elsevier Ltd.. All rights reserved.

Prior Knowledge about Objects Determines Neural Color Representation in Human Visual Cortex.

PubMed

Vandenbroucke, A R E; Fahrenfort, J J; Meuwese, J D I; Scholte, H S; Lamme, V A F

2016-04-01

To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and de Ruiter 2008). Here, we investigated the influence of object knowledge on the neural substrates underlying subjective color vision. In a functional magnetic resonance imaging experiment, human subjects viewed a color that lay midway between red and green (ambiguous with respect to its distance from red and green) presented on either typical red (e.g., tomato), typical green (e.g., clover), or semantically meaningless (nonsense) objects. Using decoding techniques, we could predict whether subjects viewed the ambiguous color on typical red or typical green objects based on the neural response of veridical red and green. This shift of neural response for the ambiguous color did not occur for nonsense objects. The modulation of neural responses was observed in visual areas (V3, V4, VO1, lateral occipital complex) involved in color and object processing, as well as frontal areas. This demonstrates that object memory influences wavelength information relatively early in the human visual system to produce subjective color vision. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Developing integrated parametric planning models for budgeting and managing complex projects

NASA Technical Reports Server (NTRS)

Etnyre, Vance A.; Black, Ken U.

1988-01-01

The applicability of integrated parametric models for the budgeting and management of complex projects is investigated. Methods for building a very flexible, interactive prototype for a project planning system, and software resources available for this purpose, are discussed and evaluated. The prototype is required to be sensitive to changing objectives, changing target dates, changing costs relationships, and changing budget constraints. To achieve the integration of costs and project and task durations, parametric cost functions are defined by a process of trapezoidal segmentation, where the total cost for the project is the sum of the various project cost segments, and each project cost segment is the integral of a linearly segmented cost loading function over a specific interval. The cost can thus be expressed algebraically. The prototype was designed using Lotus-123 as the primary software tool. This prototype implements a methodology for interactive project scheduling that provides a model of a system that meets most of the goals for the first phase of the study and some of the goals for the second phase.

A versatile petri net based architecture for modeling and simulation of complex biological processes.

PubMed

Nagasaki, Masao; Doi, Atsushi; Matsuno, Hiroshi; Miyano, Satoru

2004-01-01

The research on modeling and simulation of complex biological systems is getting more important in Systems Biology. In this respect, we have developed Hybrid Function Petri net (HFPN) that was newly developed from existing Petri net because of their intuitive graphical representation and their capabilities for mathematical analyses. However, in the process of modeling metabolic, gene regulatory or signal transduction pathways with the architecture, we have realized three extensions of HFPN, (i) an entity should be extended to contain more than one value, (ii) an entity should be extended to handle other primitive types, e.g. boolean, string, (iii) an entity should be extended to handle more advanced type called object that consists of variables and methods, are necessary for modeling biological systems with Petri net based architecture. To deal with it, we define a new enhanced Petri net called hybrid functional Petri net with extension (HFPNe). To demonstrate the effectiveness of the enhancements, we model and simulate with HFPNe four biological processes that are diffcult to represent with the previous architecture HFPN.

Methodological approach in determination of small spatial units in a highly complex terrain in atmospheric pollution research: the case of Zasavje region in Slovenia.

PubMed

Kukec, Andreja; Boznar, Marija Z; Mlakar, Primoz; Grasic, Bostjan; Herakovic, Andrej; Zadnik, Vesna; Zaletel-Kragelj, Lijana; Farkas, Jerneja; Erzen, Ivan

2014-05-01

The study of atmospheric air pollution research in complex terrains is challenged by the lack of appropriate methodology supporting the analysis of the spatial relationship between phenomena affected by a multitude of factors. The key is optimal design of a meaningful approach based on small spatial units of observation. The Zasavje region, Slovenia, was chosen as study area with the main objective to investigate in practice the role of such units in a test environment. The process consisted of three steps: modelling of pollution in the atmosphere with dispersion models, transfer of the results to geographical information system software, and then moving on to final determination of the function of small spatial units. A methodology capable of designing useful units for atmospheric air pollution research in highly complex terrains was created, and the results were deemed useful in offering starting points for further research in the field of geospatial health.

Characterization of branch complexity by fractal analyses and detect plant functional adaptations

USGS Publications Warehouse

Alados, C.L.; Escos, J.; Emlen, J.M.; Freeman, D.C.

1999-01-01

The comparison between complexity in the sense of space occupancy (box-counting fractal dimension Dc and information dimension DI ) and heterogeneity in the sense of space distribution (average evenness index and evenness variation coefficient JCV) were investigated in mathematical fractal objects and natural branch ¯ J structures. In general, increased fractal dimension was paired with low heterogeneity. Comparisons between branch architecture in Anthyllis cytisoides under different slope exposure and grazing impact revealed that branches were more complex and more homogeneously distributed for plants on northern exposures than southern, while grazing had no impact during a wet year. Developmental instability was also investigated by the statistical noise of the allometric relation between internode length and node order. In conclusion, our study demonstrated that fractal dimension of branch structure can be used to analyze the structural organization of plants, especially if we consider not only fractal dimension but also shoot distribution within the canopy (lacunarity). These indexes together with developmental instability analyses are good indicators of growth responses to the environment.

Therapeutic Jurisprudence in Health Research: Enlisting Legal Theory as a Methodological Guide in an Interdisciplinary Case Study of Mental Health and Criminal Law.

PubMed

Ferrazzi, Priscilla; Krupa, Terry

2015-09-01

Studies that seek to understand and improve health care systems benefit from qualitative methods that employ theory to add depth, complexity, and context to analysis. Theories used in health research typically emerge from social science, but these can be inadequate for studying complex health systems. Mental health rehabilitation programs for criminal courts are complicated by their integration within the criminal justice system and by their dual health-and-justice objectives. In a qualitative multiple case study exploring the potential for these mental health court programs in Arctic communities, we assess whether a legal theory, known as therapeutic jurisprudence, functions as a useful methodological theory. Therapeutic jurisprudence, recruited across discipline boundaries, succeeds in guiding our qualitative inquiry at the complex intersection of mental health care and criminal law by providing a framework foundation for directing the study's research questions and the related propositions that focus our analysis. © The Author(s) 2014.

[Psychosomatics is "expensive"].

PubMed

Hnízdil, J; Savlík, J

2005-01-01

Experience shoves that number of diseases where recognition and treatment is without limits of classical medicine is rising, however it is fully within the competence of psychosomatic approach. It does not concern the classical classification into organic and functional defects, but it concerns the possibility of complex approach. The theorem of "diagnosis per exclusionem" is still valid, as well as it is true that the means of medicine end at its biological limitations. We consider stressing in our article that psychosomatic diseases or psychosomatic patients do not exist and psychosomatics is not and independent specialization. Psychosomatics is, as inseparable unity of psychic and somatic activities, each human being. Complex biopsychosocial (psychosomatic) approach is the way of thinking and work, which considers human in unrepeatable oneness and context of his life. It does not mean to underestimate objective biological findings and results of instrumentally investigation, but their implanting into the complex network of consequences of the patient's life in order to choose the most appropriate methods of the care of the individual in healthiness and disease.

[Group specific peculiarities in the need for cultural entertainments for residents of nursing homes for the aged].

PubMed

Kuhlmey, J; Lautsch, E

1979-01-01

For the leading of the complex care as all social process the exact notice of need-structure among aged people important. The investigation of the complex need for cultural entertainments among inhabitants of geriatric nursing stations shows group-specific particularities, so that by taking cultural measures the didactiv principle is to be demanded to offer differentiated entertainments concerning the contents with different intentions. In our institution the complex need for cultural intertainments is satisfied by the real cultural offer with the exception of the indicators "moral-educational aspiration--special knowledge--compensation!" The existing difference must be used as a motiv power for increasing the cultural living standard. At a defined moment not all eventual and entitled aspects of the explored need can be satisfied, but the cultural measures must be set in relation to the objective [corrected] functions of a geriatric nursing station and to the orientation of action among the inhibitants.

CAD/CAM-generated high-density polymer restorations for the pretreatment of complex cases: a case report.

PubMed

Edelhoff, Daniel; Beuer, Florian; Schweiger, Josef; Brix, Oliver; Stimmelmayr, Michael; Guth, Jan-Frederik

2012-06-01

Complex rehabilitations represent a particular challenge for the restorative team, especially if the vertical dimension of occlusion (VDO) needs to be reconstructed or redefined. The use of provisional acrylic or composite materials allows clinicians to evaluate the treatment objective over a certain period of time and therefore generates a high predictability of the definitive rehabilitation in terms of esthetics and function. CAD/CAM technology enables the use of prefabricated polymer materials, which are fabricated under industrial conditions to form a highly homogeneous structure compared with those of direct fabrication. This increases long-term stability, biocompatibility, and resistance to wear. Furthermore, they offer more suitable CAD/CAM processing characteristics and can be used in thinner thicknesses than ceramic restorative materials. Also, based on the improved long-term stability, the transfer into the definitive restoration can be divided into multiple treatment steps. This article presents different clinical cases with minimally invasive indications for CAD/CAM-fabricated temporary restorations for the pretreatment of complex cases.

Quantification of effective exoelectrogens by most probable number (MPN) in a microbial fuel cell.

PubMed

Heidrich, Elizabeth S; Curtis, Thomas P; Woodcock, Stephen; Dolfing, Jan

2016-10-01

The objective of this work was to quantify the number of exoelectrogens in wastewater capable of producing current in a microbial fuel cell by adapting the classical most probable number (MPN) methodology using current production as end point. Inoculating a series of microbial fuel cells with various dilutions of domestic wastewater and with acetate as test substrate yielded an apparent number of exoelectrogens of 17perml. Using current as a proxy for activity the apparent exoelectrogen growth rate was 0.03h(-1). With starch or wastewater as more complex test substrates similar apparent growth rates were obtained, but the apparent MPN based numbers of exoelectrogens in wastewater were significantly lower, probably because in contrast to acetate, complex substrates require complex food chains to deliver the electrons to the electrodes. Consequently, the apparent MPN is a function of the combined probabilities of members of the food chain being present. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Detection of circuit-board components with an adaptive multiclass correlation filter

NASA Astrophysics Data System (ADS)

Diaz-Ramirez, Victor H.; Kober, Vitaly

2008-08-01

A new method for reliable detection of circuit-board components is proposed. The method is based on an adaptive multiclass composite correlation filter. The filter is designed with the help of an iterative algorithm using complex synthetic discriminant functions. The impulse response of the filter contains information needed to localize and classify geometrically distorted circuit-board components belonging to different classes. Computer simulation results obtained with the proposed method are provided and compared with those of known multiclass correlation based techniques in terms of performance criteria for recognition and classification of objects.

Building bridges between cellular and molecular structural biology.

PubMed

Patwardhan, Ardan; Brandt, Robert; Butcher, Sarah J; Collinson, Lucy; Gault, David; Grünewald, Kay; Hecksel, Corey; Huiskonen, Juha T; Iudin, Andrii; Jones, Martin L; Korir, Paul K; Koster, Abraham J; Lagerstedt, Ingvar; Lawson, Catherine L; Mastronarde, David; McCormick, Matthew; Parkinson, Helen; Rosenthal, Peter B; Saalfeld, Stephan; Saibil, Helen R; Sarntivijai, Sirarat; Solanes Valero, Irene; Subramaniam, Sriram; Swedlow, Jason R; Tudose, Ilinca; Winn, Martyn; Kleywegt, Gerard J

2017-07-06

The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures.

Nature versus design: synthetic biology or how to build a biological non-machine.

PubMed

Porcar, M; Peretó, J

2016-04-18

The engineering ideal of synthetic biology presupposes that organisms are composed of standard, interchangeable parts with a predictive behaviour. In one word, organisms are literally recognized as machines. Yet living objects are the result of evolutionary processes without any purposiveness, not of a design by external agents. Biological components show massive overlapping and functional degeneracy, standard-free complexity, intrinsic variation and context dependent performances. However, although organisms are not full-fledged machines, synthetic biologists may still be eager for machine-like behaviours from artificially modified biosystems.

Online Sentence Reading in People With Aphasia: Evidence From Eye Tracking

PubMed Central

Knilans, Jessica

2015-01-01

Purpose There is a lot of evidence that people with aphasia have more difficulty understanding structurally complex sentences (e.g., object clefts) than simpler sentences (subject clefts). However, subject clefts also occur more frequently in English than object clefts. Thus, it is possible that both structural complexity and frequency affect how people with aphasia understand these structures. Method Nine people with aphasia and 8 age-matched controls participated in the study. The stimuli consisted of 24 object cleft and 24 subject cleft sentences. The task was eye tracking during reading, which permits a more fine-grained analysis of reading performance than measures such as self-paced reading. Results As expected, controls had longer reading times for critical regions in object cleft sentences compared with subject cleft sentences. People with aphasia showed the predicted effects of structural frequency. Effects of structural complexity in people with aphasia did not emerge on their first pass through the sentence but were observed when they were rereading critical regions of complex sentences. Conclusions People with aphasia are sensitive to both structural complexity and structural frequency when reading. However, people with aphasia may use different reading strategies than controls when confronted with relatively infrequent and complex sentence structures. PMID:26383779

Online Sentence Reading in People With Aphasia: Evidence From Eye Tracking.

PubMed

Knilans, Jessica; DeDe, Gayle

2015-11-01

There is a lot of evidence that people with aphasia have more difficulty understanding structurally complex sentences (e.g., object clefts) than simpler sentences (subject clefts). However, subject clefts also occur more frequently in English than object clefts. Thus, it is possible that both structural complexity and frequency affect how people with aphasia understand these structures. Nine people with aphasia and 8 age-matched controls participated in the study. The stimuli consisted of 24 object cleft and 24 subject cleft sentences. The task was eye tracking during reading, which permits a more fine-grained analysis of reading performance than measures such as self-paced reading. As expected, controls had longer reading times for critical regions in object cleft sentences compared with subject cleft sentences. People with aphasia showed the predicted effects of structural frequency. Effects of structural complexity in people with aphasia did not emerge on their first pass through the sentence but were observed when they were rereading critical regions of complex sentences. People with aphasia are sensitive to both structural complexity and structural frequency when reading. However, people with aphasia may use different reading strategies than controls when confronted with relatively infrequent and complex sentence structures.

Resilience to the contralateral visual field bias as a window into object representations

PubMed Central

Garcea, Frank E.; Kristensen, Stephanie; Almeida, Jorge; Mahon, Bradford Z.

2016-01-01

Viewing images of manipulable objects elicits differential blood oxygen level-dependent (BOLD) contrast across parietal and dorsal occipital areas of the human brain that support object-directed reaching, grasping, and complex object manipulation. However, it is unknown which object-selective regions of parietal cortex receive their principal inputs from the ventral object-processing pathway and which receive their inputs from the dorsal object-processing pathway. Parietal areas that receive their inputs from the ventral visual pathway, rather than from the dorsal stream, will have inputs that are already filtered through object categorization and identification processes. This predicts that parietal regions that receive inputs from the ventral visual pathway should exhibit object-selective responses that are resilient to contralateral visual field biases. To test this hypothesis, adult participants viewed images of tools and animals that were presented to the left or right visual fields during functional magnetic resonance imaging (fMRI). We found that the left inferior parietal lobule showed robust tool preferences independently of the visual field in which tool stimuli were presented. In contrast, a region in posterior parietal/dorsal occipital cortex in the right hemisphere exhibited an interaction between visual field and category: tool-preferences were strongest contralateral to the stimulus. These findings suggest that action knowledge accessed in the left inferior parietal lobule operates over inputs that are abstracted from the visual input and contingent on analysis by the ventral visual pathway, consistent with its putative role in supporting object manipulation knowledge. PMID:27160998

Time Domain Version of the Uniform Geometrical Theory of Diffraction

NASA Astrophysics Data System (ADS)

Rousseau, Paul R.

1995-01-01

A time domain (TD) version of the uniform geometrical theory of diffraction which is referred to as the TD-UTD is developed to analyze the transient electromagnetic scattering from perfectly conducting objects that are large in terms of pulse width. In particular, the scattering from a perfectly conducting arbitrary curved wedge and an arbitrary smooth convex surface are treated in detail. Note that the canonical geometries of a circular cylinder and a sphere are special cases of the arbitrary smooth convex surface. These TD -UTD solutions are obtained in the form of relatively simple analytical expressions valid for early to intermediate times. The geometries treated here can be used to build up a transient solution to more complex radiating objects via space-time localization, in exactly the same way as is done by invoking spatial localization properties in the frequency domain UTD. The TD-UTD provides the response due to an excitation of a general astigmatic impulsive wavefront with any polarization. This generalized impulse response may then be convolved with other excitation time pulses, to find even more general solutions due to other excitation pulses. Since the TD-UTD uses the same rays as the frequency domain UTD, it provides a simple picture for transient radiation or scattering and is therefore just as physically appealing as the frequency domain UTD. The formulation of an analytic time transform (ATT), which produces an analytic time signal given a frequency response function, is given here. This ATT is used because it provides a very efficient method of inverting the asymptotic high frequency UTD representations to obtain the corresponding TD-UTD expressions even when there are special UTD transition functions which may not be well behaved at the low frequencies; also, using the ATT avoids the difficulties associated with the inversion of UTD ray fields that traverse line or smooth caustics. Another useful aspect of the ATT is the ability to perform an efficient convolution with a broad class of excitation pulse functions, where the frequency response of the excitation function must be expressed as a summation of complex exponential functions.

Reasons for Implementing Movement in Kinetic Architecture

NASA Astrophysics Data System (ADS)

Cudzik, Jan; Nyka, Lucyna

2017-10-01

The paper gives insights into different forms of movement in contemporary architecture and examines them based on the reasons for their implementation. The main objective of the paper is to determine: the degree to which the complexity of kinematic architecture results from functional and spatial needs and what other motivations there are. The method adopted to investigate these questions involves theoretical studies and comparative analyses of architectural objects with different forms of movement imbedded in their structure. Using both methods allowed delving into reasons that lie behind the implementation of movement in contemporary kinetic architecture. As research shows, there is a constantly growing range of applications with kinematic solutions inserted in buildings’ structures. The reasons for their implementation are manifold and encompass pursuits of functional qualities, environmental performance, spatial effects, social interactions and new aesthetics. In those early projects based on simple mechanisms, the main motives were focused on functional values and in later experiments - on improving buildings’ environmental performance. Additionally, in recent proposals, a significant quest could be detected toward kinematic solutions that are focused on factors related to alternative aesthetics and innovative spatial effects. Research reveals that the more complicated form of movement, the more often the reason for its implementation goes beyond the traditionally understood “function”. However, research also shows that the effects resulting from investigations on spatial qualities of architecture and new aesthetics often appear to provide creative insights into new functionalities in architecture.

Lensfree Computational Microscopy Tools and their Biomedical Applications

NASA Astrophysics Data System (ADS)

Sencan, Ikbal

Conventional microscopy has been a revolutionary tool for biomedical applications since its invention several centuries ago. Ability to non-destructively observe very fine details of biological objects in real time enabled to answer many important questions about their structures and functions. Unfortunately, most of these advance microscopes are complex, bulky, expensive, and/or hard to operate, so they could not reach beyond the walls of well-equipped laboratories. Recent improvements in optoelectronic components and computational methods allow creating imaging systems that better fulfill the specific needs of clinics or research related biomedical applications. In this respect, lensfree computational microscopy aims to replace bulky and expensive optical components with compact and cost-effective alternatives through the use of computation, which can be particularly useful for lab-on-a-chip platforms as well as imaging applications in low-resource settings. Several high-throughput on-chip platforms are built with this approach for applications including, but not limited to, cytometry, micro-array imaging, rare cell analysis, telemedicine, and water quality screening. The lack of optical complexity in these lensfree on-chip imaging platforms is compensated by using computational techniques. These computational methods are utilized for various purposes in coherent, incoherent and fluorescent on-chip imaging platforms e.g. improving the spatial resolution, to undo the light diffraction without using lenses, localization of objects in a large volume and retrieval of the phase or the color/spectral content of the objects. For instance, pixel super resolution approaches based on source shifting are used in lensfree imaging platforms to prevent under sampling, Bayer pattern, and aliasing artifacts. Another method, iterative phase retrieval, is utilized to compensate the lack of lenses by undoing the diffraction and removing the twin image noise of in-line holograms. This technique enables recovering the complex optical field from its intensity measurement(s) by using additional constraints in iterations, such as spatial boundaries and other known properties of objects. Another computational tool employed in lensfree imaging is compressive sensing (or decoding), which is a novel method taking advantage of the fact that natural signals/objects are mostly sparse or compressible in known bases. This inherent property of objects enables better signal recovery when the number of measurement is low, even below the Nyquist rate, and increases the additive noise immunity of the system.

Mapping and discrimination of networks in the complexity-entropy plane

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discriminate networks into different classes or categories. However, even with the present variety of characteristics at hand it still remains a subject of current research to appropriately quantify a network's complexity and correspondingly discriminate between different types of complex networks, like infrastructure or social networks, on such a basis. Here we explore the possibility to classify complex networks by means of a statistical complexity measure that has formerly been successfully applied to distinguish different types of chaotic and stochastic time series. It is composed of a network's averaged per-node entropic measure characterizing the network's information content and the associated Jenson-Shannon divergence as a measure of disequilibrium. We study 29 real-world networks and show that networks of the same category tend to cluster in distinct areas of the resulting complexity-entropy plane. We demonstrate that within our framework, connectome networks exhibit among the highest complexity while, e.g., transportation and infrastructure networks display significantly lower values. Furthermore, we demonstrate the utility of our framework by applying it to families of random scale-free and Watts-Strogatz model networks. We then show in a second application that the proposed framework is useful to objectively construct threshold-based networks, such as functional climate networks or recurrence networks, by choosing the threshold such that the statistical network complexity is maximized.

Fast and Careless or Careful and Slow? Apparent Holistic Processing in Mental Rotation Is Explained by Speed-Accuracy Trade-Offs

ERIC Educational Resources Information Center

Liesefeld, Heinrich René; Fu, Xiaolan; Zimmer, Hubert D.

2015-01-01

A major debate in the mental-rotation literature concerns the question of whether objects are represented holistically during rotation. Effects of object complexity on rotational speed are considered strong evidence against such holistic representations. In Experiment 1, such an effect of object complexity was markedly present. A closer look on…

On the optimization of electromagnetic geophysical data: Application of the PSO algorithm

NASA Astrophysics Data System (ADS)

Godio, A.; Santilano, A.

2018-01-01

Particle Swarm optimization (PSO) algorithm resolves constrained multi-parameter problems and is suitable for simultaneous optimization of linear and nonlinear problems, with the assumption that forward modeling is based on good understanding of ill-posed problem for geophysical inversion. We apply PSO for solving the geophysical inverse problem to infer an Earth model, i.e. the electrical resistivity at depth, consistent with the observed geophysical data. The method doesn't require an initial model and can be easily constrained, according to external information for each single sounding. The optimization process to estimate the model parameters from the electromagnetic soundings focuses on the discussion of the objective function to be minimized. We discuss the possibility to introduce in the objective function vertical and lateral constraints, with an Occam-like regularization. A sensitivity analysis allowed us to check the performance of the algorithm. The reliability of the approach is tested on synthetic, real Audio-Magnetotelluric (AMT) and Long Period MT data. The method appears able to solve complex problems and allows us to estimate the a posteriori distribution of the model parameters.

Robust video super-resolution with registration efficiency adaptation

NASA Astrophysics Data System (ADS)

Zhang, Xinfeng; Xiong, Ruiqin; Ma, Siwei; Zhang, Li; Gao, Wen

2010-07-01

Super-Resolution (SR) is a technique to construct a high-resolution (HR) frame by fusing a group of low-resolution (LR) frames describing the same scene. The effectiveness of the conventional super-resolution techniques, when applied on video sequences, strongly relies on the efficiency of motion alignment achieved by image registration. Unfortunately, such efficiency is limited by the motion complexity in the video and the capability of adopted motion model. In image regions with severe registration errors, annoying artifacts usually appear in the produced super-resolution video. This paper proposes a robust video super-resolution technique that adapts itself to the spatially-varying registration efficiency. The reliability of each reference pixel is measured by the corresponding registration error and incorporated into the optimization objective function of SR reconstruction. This makes the SR reconstruction highly immune to the registration errors, as outliers with higher registration errors are assigned lower weights in the objective function. In particular, we carefully design a mechanism to assign weights according to registration errors. The proposed superresolution scheme has been tested with various video sequences and experimental results clearly demonstrate the effectiveness of the proposed method.

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

Statistical tools for analysis and modeling of cosmic populations and astronomical time series: CUDAHM and TSE

NASA Astrophysics Data System (ADS)

Loredo, Thomas; Budavari, Tamas; Scargle, Jeffrey D.

2018-01-01

This presentation provides an overview of open-source software packages addressing two challenging classes of astrostatistics problems. (1) CUDAHM is a C++ framework for hierarchical Bayesian modeling of cosmic populations, leveraging graphics processing units (GPUs) to enable applying this computationally challenging paradigm to large datasets. CUDAHM is motivated by measurement error problems in astronomy, where density estimation and linear and nonlinear regression must be addressed for populations of thousands to millions of objects whose features are measured with possibly complex uncertainties, potentially including selection effects. An example calculation demonstrates accurate GPU-accelerated luminosity function estimation for simulated populations of $10^6$ objects in about two hours using a single NVIDIA Tesla K40c GPU. (2) Time Series Explorer (TSE) is a collection of software in Python and MATLAB for exploratory analysis and statistical modeling of astronomical time series. It comprises a library of stand-alone functions and classes, as well as an application environment for interactive exploration of times series data. The presentation will summarize key capabilities of this emerging project, including new algorithms for analysis of irregularly-sampled time series.

Post-learning hippocampal dynamics promote preferential retention of rewarding events

PubMed Central

Gruber, Matthias J.; Ritchey, Maureen; Wang, Shao-Fang; Doss, Manoj K.; Ranganath, Charan

2016-01-01

Reward motivation is known to modulate memory encoding, and this effect depends on interactions between the substantia nigra/ ventral tegmental area complex (SN/VTA) and the hippocampus. It is unknown, however, whether these interactions influence offline neural activity in the human brain that is thought to promote memory consolidation. Here, we used functional magnetic resonance imaging (fMRI) to test the effect of reward motivation on post-learning neural dynamics and subsequent memory for objects that were learned in high- or low-reward motivation contexts. We found that post-learning increases in resting-state functional connectivity between the SN/VTA and hippocampus predicted preferential retention of objects that were learned in high-reward contexts. In addition, multivariate pattern classification revealed that hippocampal representations of high-reward contexts were preferentially reactivated during post-learning rest, and the number of hippocampal reactivations was predictive of preferential retention of items learned in high-reward contexts. These findings indicate that reward motivation alters offline post-learning dynamics between the SN/VTA and hippocampus, providing novel evidence for a potential mechanism by which reward could influence memory consolidation. PMID:26875624

The influence of object shape and center of mass on grasp and gaze

PubMed Central

Desanghere, Loni; Marotta, Jonathan J.

2015-01-01

Recent experiments examining where participants look when grasping an object found that fixations favor the eventual index finger landing position on the object. Even though the act of picking up an object must involve complex high-level computations such as the visual analysis of object contours, surface properties, knowledge of an object’s function and center of mass (COM) location, these investigations have generally used simple symmetrical objects – where COM and horizontal midline overlap. Less research has been aimed at looking at how variations in object properties, such as differences in curvature and changes in COM location, affect visual and motor control. The purpose of this study was to examine grasp and fixation locations when grasping objects whose COM was positioned to the left or right of the objects horizontal midline (Experiment 1) and objects whose COM was moved progressively further from the midline of the objects based on the alteration of the object’s shape (Experiment 2). Results from Experiment 1 showed that object COM position influenced fixation locations and grasp locations differently, with fixations not as tightly linked to index finger grasp locations as was previously reported with symmetrical objects. Fixation positions were also found to be more central on the non-symmetrical objects. This difference in gaze position may provide a more holistic view, which would allow both index finger and thumb positions to be monitored while grasping. Finally, manipulations of COM distance (Experiment 2) exerted marked effects on the visual analysis of the objects when compared to its influence on grasp locations, with fixation locations more sensitive to these manipulations. Together, these findings demonstrate how object features differentially influence gaze vs. grasp positions during object interaction. PMID:26528207

Multiple utility constrained multi-objective programs using Bayesian theory

NASA Astrophysics Data System (ADS)

Abbasian, Pooneh; Mahdavi-Amiri, Nezam; Fazlollahtabar, Hamed

2018-03-01

A utility function is an important tool for representing a DM's preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utility functions. We induce the probability of the utilities for each objective function using Bayesian theory. Illustrative examples considering dependence and independence of variables are worked through to demonstrate the usefulness of the proposed model.