Decision making in social neurobiological systems modeled as transitions in dynamic pattern formation

Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.

NEU-MODEL : a multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

Cost-effective biodiversity restoration with uncertain growth in forest habitat quality

This paper develops a dynamic model for cost-effective selection of sites for restoring biodiversity when habitat quality develops over time and is uncertain. A safety-first decision criterion is used for ensuring a minimum level of habitats, and this is formulated in a chance-constrained programming framework. The theoretical results show; (i) inclusion of quality growth reduces overall cost for achieving a future biodiversity target from relatively early establishment of habitats, but (ii) consideration of uncertainty in growth increases total cost and delays establishment, and (iii) cost-effective trading of habitat requires exchange rate between sites that varies over time. An empirical application to the red listed umbrella species - white-backed woodpecker - shows that the total cost of achieving habitat targets specified in the Swedish recovery plan is doubled if the target is to be achieved with high reliability, and that equilibrating price on a habitat trading market differs considerably between different quality growth combinations. © 2013 Elsevier GmbH.

Nanoparticle–electrode collisions as a dynamic seeding route for the growth of metallic nanostructures

The collisions between colloidal metal nanoparticles and a carbon electrode were explored as a dynamic method for the electrodeposition of a diverse range of electrocatalytically active Ag and Au nanostructures whose morphology is dominated by the electrostatic interaction between the charge of the nanoparticle and metal salt.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Catalytic activity evaluation of industrial Pd/C catalyst via gray-box dynamic modeling and simulation of hydropurification reactor

In this paper, dynamic modeling and simulation of the hydropurification reactor in a purified terephthalic acid production plant has been investigated by gray-box technique to evaluate the catalytic activity of palladium supported on carbon (0.5 wt.% Pd/C) catalyst. The reaction kinetics and catalyst deactivation trend have been modeled by employing artificial neural network (ANN). The network output has been incorporated with the reactor first principle model (FPM). The simulation results reveal that the gray-box model (FPM and ANN) is about 32 percent more accurate than FPM. The model demonstrates that the catalyst is deactivated after eleven months. Moreover, the catalyst lifetime decreases about two and half months in case of 7 percent increase of reactor feed flowrate. It is predicted that 10 percent enhancement of hydrogen flowrate promotes catalyst lifetime at the amount of one month. Additionally, the enhancement of 4-carboxybenzaldehyde concentration in the reactor feed improves CO and benzoic acid synthesis. CO is a poison to the catalyst, and benzoic acid might affect the product quality. The model can be applied into actual working plants to analyze the Pd/C catalyst efficient functioning and the catalytic reactor performance.

Watermarking capacity control for dynamic payload embedding

Despite significant improvements in capacity-distortion performance, a computationally efficient capacity control is still lacking in the recent watermarking schemes. In this paper, we propose an efficient capacity control framework to substantiate the notion of watermarking capacity control to be the process of maintaining “acceptable” distortion and running time, while attaining the required capacity. The necessary analysis and experimental results on the capacity control are reported to address practical aspects of the watermarking capacity problem, in dynamic (size) payload embedding.

Dynamic input to determine hip joint moments, power and work on the prosthetic limb of transfemoral amputees: ground reactions vs knee reactions

Study Design: Comparative analysis Background: Calculations of lower limbs kinetics are limited by floor-mounted force-plates. Objectives: Comparison of hip joint moments, power and mechanical work on the prosthetic limb of a transfemoral amputee calculated by inverse dynamics using either the ground reactions (force-plates) or knee reactions (transducer). Methods: Kinematics, ground reactions and knee reactions were collected using a motion analysis system, two force-plates and a multi-axial transducer mounted below the socket, respectively. Results: The inverse dynamics using ground reactions under-estimated the peaks of hip energy generation and absorption occurring at 63 % and 76 % of the gait cycle (GC) by 28 % and 54 %, respectively. This method over-estimated a phase of negative work at the hip (from 37 %GC to 56 %GC) by 24%. It under-estimated the phases of positive (from 57 %GC to 72 %GC) and negative (from 73 %GC to 98 %GC) work at the hip by 11 % and 58%, respectively. Conclusions: A transducer mounted within the prosthesis has the capacity to provide more realistic kinetics of the prosthetic limb because it enables assessment of multiple consecutive steps and a wide range of activities without issues of foot placement on force-plates. CLINICAL RELEVANCE The hip is the only joint that an amputee controls directly to set in motion the prosthesis. Hip joint kinetics are associated with joint degeneration, low back pain, risks of fall, etc. Therefore, realistic assessment of hip kinetics over multiple gait cycles and a wide range of activities is essential.

Analysing student programs in the PHP intelligent tutoring system

Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that supports students learning to program. The PHP ITS works by providing exercises for students to solve and then providing feedback based on their solutions. The major challenge here is to be able to identify many semantically equivalent solutions to a single exercise. The PHP ITS achieves this by using theories of Artificial Intelligence (AI) including first-order predicate logic and classical and hierarchical planning to model the subject matter taught by the system. This paper highlights the approach taken by the PHP ITS to analyse students’ programs that include a number of program constructs that are used by beginners of web development. The PHP ITS was built using this model and evaluated in a unit at the Queensland University of Technology. The results showed that it was capable of correctly analysing over 96 % of the solutions to exercises supplied by students.

Sectionalizing strategies for minimizing outage durations of critical loads in parallel power system restoration with bi-level programming

Fast restoration of critical loads and non-black-start generators can significantly reduce the economic losses caused by power system blackouts. In a parallel power system restoration scenario, the sectionalization of restoration subsystems plays a very important role in determining the pickup of critical loads before synchronization. Most existing research mainly focuses on the startup of non-black-start generators. The restoration of critical loads, especially the loads with cold load characteristics, has not yet been addressed in optimizing the subsystem divisions. As a result, sectionalized restoration subsystems cannot achieve the best coordination between the pickup of loads and the ramping of generators. In order to generate sectionalizing strategies considering the pickup of critical loads in parallel power system restoration scenarios, an optimization model considering power system constraints, the characteristics of the cold load pickup and the features of generator startup is proposed in this paper. A bi-level programming approach is employed to solve the proposed sectionalizing model. In the upper level the optimal sectionalizing problem for the restoration subsystems is addressed, while in the lower level the objective is to minimize the outage durations of critical loads. The proposed sectionalizing model has been validated by the New-England 39-bus system and the IEEE 118-bus system. Further comparisons with some existing methods are carried out as well.