Eliminating Human Agency: Why Does Japan Abandon Predictive Simulations?

Prediction plays a vital role in every branch of our contemporary lives. While the credibility of quantitative simulations through mathematical modeling may seem to be universal, how they are perceived and embedded in policy processes may vary by society. Investigating the ecology of quantitative prediction tools, this article articulates the cultural specificity of Japanese society through the concept of Jasanoff’s “civic epistemology.” Taking COVID-19 and nuclear disasters as examples, this article examines how predictive simulations are mobilized, contested, and abandoned. In both cases, current empirical observation eventually replaces predictive future simulations, and mechanical application of preset criteria substitutes political judgment. These analyses suggest that the preferred register of objectivity in Japan—one of the constitutive dimensions of civic epistemology—consists not in producing numerical results, but in precluding human judgment. Such public calls to eliminate human agency both in knowledge and in policy-making can be a distinct character of Japanese civic epistemology, which may explain why Japan repeatedly withdraws from predictive simulations. It implies the possibility that Western societies’ faith in human judgment should not be taken for granted, but explained.

Modeling toes contributes to realistic stance knee mechanics in three-dimensional predictive simulations of walking

Physics-based predictive simulations have been shown to capture many salient features of human walking. Yet they often fail to produce realistic stance knee mechanics and terminal stance ankle plantarflexion. While the influence of the performance criterion on the predicted walking pattern has been previously studied, the influence of the mechanics has been less explored. Here, we investigated the influence of two mechanical assumptions on the predicted walking pattern: the complexity of the foot segment and the stiffness of the Achilles tendon. We found, through three-dimensional muscle-driven predictive simulations of walking, that modeling the toes and metatarsophalangeal joints, and thus using two-segment instead of single-segment foot models, contributed to robustly eliciting physiological stance knee flexion angles, knee extension torques, and knee extensor activity. Yet modeling toe joints did not improve ankle kinematics, nor did decreasing the Achilles tendon stiffness. The lack of predicted terminal stance ankle plantarflexion thereby remains an open question. Overall, this simulation study shows that not only the performance criterion but also mechanical assumptions affect predictive simulations of walking. Improving the realism of predictive simulations is required for their application in clinical contexts. Here, we suggest that using complex models is needed to yield such realism.

Predictive simulations of musculoskeletal function and jumping performance in a generalized bird

Jumping is a common, but demanding, behaviour that many animals employ during everyday activity. In contrast to jump-specialists such as anurans and some primates, jumping biomechanics and the factors that influence performance remains little studied for generalized species that lack marked adaptations for jumping. Computational biomechanical modelling approaches offer a way of addressing this in a rigorous, mechanistic fashion. Here, optimal control theory and musculoskeletal modelling are integrated to generate predictive simulations of maximal height jumping in a small ground-dwelling bird, a tinamou. A three-dimensional musculoskeletal model with 36 actuators per leg is used, and direct collocation is employed to formulate a rapidly solvable optimal control problem involving both liftoff and landing phases. The resulting simulation raises the whole-body centre of mass to over double its standing height, and key aspects of the simulated behaviour qualitatively replicate empirical observations for other jumping birds. However, quantitative performance is lower, with reduced ground forces, jump heights and muscle–tendon power. A pronounced countermovement manoeuvre is used during launch. The use of a countermovement is demonstrated to be critical to the achievement of greater jump heights, and this phenomenon may only need to exploit physical principles alone to be successful; amplification of muscle performance may not necessarily be a proximate reason for the use of this manoeuvre. Increasing muscle strength or contractile velocity above nominal values greatly improves jump performance, and interestingly has the greatest effect at more distal limb extensor muscles (i.e., those of the ankle), suggesting that the distal limb may be a critical link for jumping behaviour. These results warrant a re-evaluation of previous inferences of jumping ability in some extinct species with foreshortened distal limb segments, such as dromaeosaurid dinosaurs.

Benchmark of predictive simulations of block trajectories using field experiments

<p>A comparative analysis between block propagation experiments and predictive simulations of block trajectories was conducted to evaluate the predictive capacities of block propagation analyses. Approximately one hundred blocks were released on two propagation paths with topographical discontinuities and configurations promoting block rolling. The block propagation was analysed at specific locations of the paths, called evaluation screens. A significant variability of the block velocities was measured at the screens and bimodal distributions of the velocities were observed for the screens located downhill topographical discontinuities.</p><p>The comparative analysis between the experimental results and the predictive simulations shows a large variability of the simulations results, that illustrates the uncertainties related with these predictions, done without calibration data. Specific limitations of the block propagation models were shown as regards to the modelling of block propagation similar to rolling motion on soft soils. Finally, the simulations were shown more predictive for extreme velocities than for mean ones and for block passing probabilities.</p><div> <div> <div></div> <div>What do you want to do ?</div> New mail</div> </div><div> <div> <div></div> <div>What do you want to do ?</div> New mail</div> </div>

Perspective on musculoskeletal modelling and predictive simulations of human movement to assess the neuromechanics of gait

Locomotion results from complex interactions between the central nervous system and the musculoskeletal system with its many degrees of freedom and muscles. Gaining insight into how the properties of each subsystem shape human gait is challenging as experimental methods to manipulate and assess isolated subsystems are limited. Simulations that predict movement patterns based on a mathematical model of the neuro-musculoskeletal system without relying on experimental data can reveal principles of locomotion by elucidating cause–effect relationships. New computational approaches have enabled the use of such predictive simulations with complex neuro-musculoskeletal models. Here, we review recent advances in predictive simulations of human movement and how those simulations have been used to deepen our knowledge about the neuromechanics of gait. In addition, we give a perspective on challenges towards using predictive simulations to gain new fundamental insight into motor control of gait, and to help design personalized treatments in patients with neurological disorders and assistive devices that improve gait performance. Such applications will require more detailed neuro-musculoskeletal models and simulation approaches that take uncertainty into account, tools to efficiently personalize those models, and validation studies to demonstrate the ability of simulations to predict gait in novel circumstances.