Optimal effort investment for overcoming the weakest point: new insights from a computational model of neuromuscular adaptation

The occurrence of so-called sticking points in a lift is pervasive in weight training practice. Biomechanically complex exercises often exhibit multi modal variation of effective force exerted against the load as a function of the elevation and velocity of the load. This results in a variety of possible loci for the occurrence of sticking points and makes the problem of designing the optimal training strategy to overcome them challenging. In this article a case founded on theoretical grounds is made against a purely empirical method. It is argued that the nature of the problem considered and the wide range of variables involved limit the generality of conclusions which can be drawn from experimental studies alone. Instead an alternative is described, whereby a recently proposed mathematical model of neuromuscular adaptation is employed in a series of computer simulations. These are used to examine quantitatively the effects of differently targeted partial range of motion (ROM) training approaches. Counter-intuitively and in contrast to common training practices, the key novel insight inferred from the obtained results is that in some cases the most effective approach for improving performance in an exercise with a sticking point at a particular point in the ROM is to improve force production capability at a different and possibly remote position in the lift. In the context of the employed model, this result is explained by changes in the neuromuscular and biomechanical environment for force production.

Linguistic computational model based on 2-tuples and intervals

Herrera and Mart́inez initiated a 2-tuple fuzzy linguistic representation model for computing with words.Moreover, Wang and Hao further developed a new 2-tuple fuzzy linguistic representation model to deal with the linguistic term sets that are not uniformly and symmetrically distributed. This study proposes another linguistic computational model based on 2-tuples and intervals, which we call an interval version of the 2-tuple fuzzy linguistic representation model. The proposed model possesses three steps: 1) interval numerical scale; 2) computation based on interval numbers; and 3) a generalized inverse operation of the interval numerical scale. The first step transforms linguistic terms into interval numbers, based on which the second step is executed with output as an interval number. Finally, this number is then mapped into the interval of the linguistic 2-tuples by the generalized inverse operation. This study also generalizes the numerical scale approach, presented in the Wang and Hao model, to set the interval numerical scale, by considering the context where semantics of linguistic terms are defined by interval type-2 fuzzy sets (IT2 FSs). In order to compare the proposed model with the existing linguistic computational model based on IT2 FSs, we have conducted extensive simulations. The simulations demonstrate that the results obtained by our proposal are consistent with the results of the linguistic computational model based on IT2 FSs (in some sense) in a vast majority of cases.

Review of trust and machine ethics research: towards a bio-inspired computational model of ethical trust (CMET)

Recent advances in the fields of robotics, cyborg development, moral psychology, trust, multi agent-based systems and socionics have raised the need for a better understanding of ethics, moral reasoning, judgment and decision-making within the system of man and machines. Here we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the social moral norms at the collective end. We review salient works in the fields of trust and machine ethics research, underscore the importance and the need for a deeper understanding of ethical trust at the individual level and the development of collective social moral norms. Drawing upon the recent findings from neural sciences on mirror-neuron system (MNS) and social cognition, we present a bio-inspired Computational Model of Ethical Trust (CMET) to allow investigations of the interplay of ethical trust and social moral norms.

Computational studies to understand the role of social learning in team familiarity and its effects on team performance

This paper concerns social learning modes and their effects on team performance. Social learning, such as by observing others' actions and their outcomes, allows members of a team to learn what other members know. Knowing what other members know can reduce task communication and co-ordination overhead, which helps the team to perform faster since members can devote their attention to their tasks. This paper describes agent-based simulation studies using a computational model that implements different social learning modes as parameters that can be controlled in the simulations. The results show that social learning from both direct and indirect observations positively contributes to learning about what others know, but the value of social learning is sensitive to prior familiarity such that minimum thresholds of team familiarity are needed to realise the benefits of social learning. This threshold increases with task complexity. These findings clarify the level of influence that sociality has on social learning and sets up a formal framework by which to conduct studies on how social context influences learning and group performance.

A mathematical model of neuromuscular adaptation to resistance training and its application in a computer simulation of accommodating loads

A large corpus of data obtained by means of empirical study of neuromuscular adaptation is currently of limited use to athletes and their coaches. One of the reasons lies in the unclear direct practical utility of many individual trials. This paper introduces a mathematical model of adaptation to resistance training, which derives its elements from physiological fundamentals on the one side, and empirical findings on the other. The key element of the proposed model is what is here termed the athlete’s capability profile. This is a generalization of length and velocity dependent force production characteristics of individual muscles, to an exercise with arbitrary biomechanics. The capability profile, a two-dimensional function over the capability plane, plays the central role in the proposed model of the training-adaptation feedback loop. Together with a dynamic model of resistance the capability profile is used in the model’s predictive stage when exercise performance is simulated using a numerical approximation of differential equations of motion. Simulation results are used to infer the adaptational stimulus, which manifests itself through a fed back modification of the capability profile. It is shown how empirical evidence of exercise specificity can be formulated mathematically and integrated in this framework. A detailed description of the proposed model is followed by examples of its application—new insights into the effects of accommodating loading for powerlifting are demonstrated. This is followed by a discussion of the limitations of the proposed model and an overview of avenues for future work.

Generative experimentation and social simulation : exploring gaming for model vVerification and validation

The agent-based modelling paradigm has been actively applied to address social normative issues such as values, cognition, morality and behaviours. The abstraction of human and human-like social processes and mechanisms result in misalignment of computational model with existing verification and validation techniques and expose significant challenges. We argue that human sources represent a sound approach for verification and validation of agent-based social simulation models. We propose a novel conceptual gaming framework that extracts required information from relevant sources as part of game play

Interplay of ethical trust and social moral norms : environment modelling and computational mechanisms in agent-based social simulation

In many agent-based models theoretical and computational mechanisms are needed for model abstraction and design. However, it can be challenging to arrive at the appropriate mechanisms and models. This research on the interplay of ethical trust and social moral norms addresses that challenge via an analytical framework on the spread of moral norms, the modelling of social environment and the selection of spread mechanisms as applied to agent-based social simulation. We describe the mechanism alignment mapping, two forms of interaction modelling between the social environment and agents, and the results obtained from the simulation of our computational model. These results provide an insight into how the agent-based paradigm can be applied as a technique of investigation for normative moral processes in computational social sciences.

Numerical simulation of heat and mass transfer in fluidised bed heat treatment furnaces

In this paper, a novel combined theoretical and computational model is developed to simulate the heat and mass transfer between a fluidised bed and a workpiece surface, and within the workpiece by considering the fluidised bed as a medium consisting of a double-particle layer and an even porous layer. The heat and mass-transfer flux from the fluidised bed to the workpiece surface is contributed by dense and bubble phases, respectively. The convective heat and mass transfer is simulated by analysing the gas dynamics in the fluidised bed, while radiative heat transfer is modelled by simulating photon emission in a three-dimensional particle array. The simulation shows that convection is approximately constant, while radiation contributes significantly to the heat transfer. The heat-transfer coefficient on an immersed surface near particles is about 6–10 times that on other areas. The transient heat and mass-transfer coefficient, heat and mass-transfer flux on any surface of the workpiece, transient temperature and carbon distributions at any position of the workpiece during the metal carburising process are studied with the simulation.

Experimental investigation and numerical simulation of heat transfer in quenching fluidised beds

Fluidisation characteristics at different surfaces of a work-piece of complex geometry are conducted in a fluidised bed at various conditions including fluidising number, bed temperature and fluidising medium. The quenching of the work-piece is performed experimentally. In particular, the major frequency and energy of the pressure fluctuations are measured as a function of either fluidising velocity or heat transfer position and the results are used to develop a mathematic model. A computational model is developed to simulate gas dynamics and heat transfer between the fluidised bed and the work-piece surface, as well as simulating the temperature within the work-piece. The predicted cooling curves are in good agreement with the experimental results. Based on the simulation results, the flow characteristics of the gas and the temperature of the dense gas-solid phase near the work-piece surface are analysed to understand the heat transfer mechanism in the fluidised bed.

How important is team structure to team performance?

This paper discusses the effects of team structure on the performance of design teams. Three types of team structures are differentiated on the basis of the functional and social groups that result from task dependencies and interaction opportunities. The reported findings are based upon results from simulation-based studies using a computational model. Differences across the team structures are investigated through a series of simulations in which the team membership and the workload busyness of the team members are independent variables, and the team performance and formation of team mental models are the dependent variables. Team performance is measured in terms of the ability of the team members to coordinate the set of tasks the team needs to perform. Findings suggest that, in general, flat teams facilitate formation of team mental models, while functional teams are best for efficient task coordination.

Finding the beat : an analysis of the rhythmic elements of motion pictures

This paper presents a new study on the application of the framework of Computational Media Aesthetics to the problem of automated understanding of film. Leveraging Film Grammar as the means to closing the "semantic gap" in media analysis, we examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and enhance its lyrical quality experientially. The novelty of this paper lies in the specification and investigation of the rhythmic elements that are present in two cinematic devices; namely motion and editing patterns, and their potential usefulness to automated content annotation and management systems. In our rhythm model, motion behavior is classified as being either nonexistent, fluid or staccato for a given shot. Shot neighborhoods in movies are then grouped by proportional makeup of these motion behavioral classes to yield seven high-level rhythmic arrangements that prove to be adept at indicating likely scene content (e.g. dialogue or chase sequence) in our experiments. The second part of our investigation presents a computational model to detect editing patterns as either metric, accelerated, decelerated or free. Details of the algorithm for the extraction of these classes are presented, along with experimental results on real movie data. We show with an investigation of combined rhythmic patterns that, while detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/editing rhythms can allow us to determine that the content has changed and hypothesize as to why this is so. We present three such categories of change and demonstrate their efficacy for capturing useful film elements (e.g. scene change precipitated by plot event), by providing data support from five motion pictures.

Finding the beat : an analysis of the rhythmic elements of motion pictures

This paper forms a continuation of our work focused on exploiting film grammar for the task of automated film understanding. We examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and to enhance its lyrical quality experientially. Of the many, often complex, cinematic devices contributing to film rhythm, this paper investigates the rhythmic elements that are present in edited sequences of shots, and presents a novel computational model to detect shot structural rhythm as either metric, accelerated, decelerated, or free. Details of the algorithm for the extraction of these editing rhythm classes are presented, along with experimental results on real movie data. Following this we study the usefulness of combining the rhythmic patterns induced through both motion and editing in film. We show that, whilst detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/shot rhythm can allow us to determine that the content has changed and hypothesize as to why this is so. We present 3 such categories of change and demonstrate their efficacy for capturing useful film elements (e.g., scene change precipitated by plot event), by providing data support from 5 motion pictures.

Coupled modelling of hydrodynamics and mass transfer in membrane filtration

This research produced a novel predictive computational model for the water treatment processes of nanofiltration and reverse osmosis. This model combined commercial computational fluid dynamics codes with numerical mass transfer models developed by the candidate to provide a rigorous description of these processes’ hydrodynamic and pollutant removal behaviour.

Common variants of the resistance mechanism in the Smith Machine: analysis of mechanical loading characteristics and application to strength-oriented and hypertrophy-oriented training

The Smith machine is a pervasive weight-training apparatus, used extensively by a wide population of weight trainers, from novices to high-level athletes. The advantages of using a Smith machine over free-weight resistance are disputed, with conflicting findings reported in the literature. In this study, we are interested in practical differences between 3 types of loading mechanisms found in modern Smith machines. In addition to the basic design comprising a constrained weighted barbell, alterations with a counterweight and a viscous resistance component are examined. The approach taken is that of employing a recently proposed representation of force characteristics that may be exhibited by a trainee and a predictive model of thus effected adaptation. A computer simulation is used to predict the effects of the 3 linear Smith machine designs in the framework of different exercise protocols. Our results demonstrate that each resistance component, vertically constrained load, counterweight, and viscous, can be matched with a particular training context, in which it should be preferred. Thus, a number of practical guidelines for weight-training practitioners are recommended. In summary, (a) at low intensities (55–75% of 1 repetition maximum [1RM]) used in strength-endurance training, a viscous resistance containing the Smith machine was found to offer advantages over both a constrained load only and counterweighted designs; (b) at medium intensities (75–85% of 1RM) typically employed in hypertrophy-specific training, the counterweighted Smith machine design was found to offer the best choice in terms of high-force development and total external work performed; finally, (c) at high training intensity (90–100% of 1RM), the optimal prescription was found to be more dependent on the specific athlete’s weaknesses, highlighting the need for continual monitoring of the athlete’s force production capabilities. To ensure that appropriate adjustments are made to the athlete’s training regimen, the practitioner should consider the full set of findings of this article and the accompanying discussion.

Ethical trust and social moral norms simulation : a bio-inspired agent-based modelling approach

The understanding of the micro-macro link is an urgent need in the study of social systems. The complex adaptive nature of social systems adds to the challenges of understanding social interactions and system feedback and presents substantial scope and potential for extending the frontiers of computer-based research tools such as simulations and agent-based technologies. In this project, we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the development of collective social moral norms as representative sample of the bigger micro-macro link of social systems. We outline our computational model of ethical trust (CMET) informed by research findings from trust, machine ethics and neural science. Guided by the CMET architecture, we discuss key implementation ideas for the simulations of ethical trust and social moral norms.