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In the past few years a new scenario for robot-based applications has emerged. Service and mobile robots have opened new market niches. Also, new frameworks for shop-floor robot applications have been developed. In all these contexts, robots are requested to perform tasks within open-ended conditions, possibly dynamically varying. These new requirements ask also for a change of paradigm in the design of robots: on-line and safe feedback motion control becomes the core of modern robot systems. Future robots will learn autonomously, interact safely and possess qualities like self-maintenance. Attaining these features would have been relatively easy if a complete model of the environment was available, and if the robot actuators could execute motion commands perfectly relative to this model. Unfortunately, a complete world model is not available and robots have to plan and execute the tasks in the presence of environmental uncertainties which makes sensing an important component of new generation robots. For this reason, today's new generation robots are equipped with more and more sensing components, and consequently they are ready to actively deal with the high complexity of the real world. Complex sensorimotor tasks such as exploration require coordination between the motor system and the sensory feedback. For robot control purposes, sensory feedback should be adequately organized in terms of relevant features and the associated data representation. In this paper, we propose an overall functional picture linking sensing to action in closed-loop sensorimotor control of robots for touch (hands, fingers). Basic qualities of haptic perception in humans inspire the models and categories comprising the proposed classification. The objective is to provide a reasoned, principled perspective on the connections between different taxonomies used in the Robotics and human haptic literature. The specific case of active exploration is chosen to ground interesting use cases. Two reasons motivate this choice. First, in the literature on haptics, exploration has been treated only to a limited extent compared to grasping and manipulation. Second, exploration involves specific robot behaviors that exploit distributed and heterogeneous sensory data.

When we feel and see an object, the nervous system integrates visual and haptic information optimally, exploiting the redundancy in multiple signals to estimate properties more precisely than is possible from either signal alone. We examined whether optimal integration is similarly achieved when using articulated tools. Such tools (tongs, pliers, etc) are a defining characteristic of human hand function, but complicate the classical sensory ‘correspondence problem’ underlying multisensory integration. Optimal integration requires establishing the relationship between signals acquired by different sensors (hand and eye) and, therefore, in fundamentally unrelated units. The system must also determine when signals refer to the same property of the world—seeing and feeling the same thing—and only integrate those that do. This could be achieved by comparing the pattern of current visual and haptic input to known statistics of their normal relationship. Articulated tools disrupt this relationship, however, by altering the geometrical relationship between object properties and hand posture (the haptic signal). We examined whether different tool configurations are taken into account in visual–haptic integration. We indexed integration by measuring the precision of size estimates, and compared our results to optimal predictions from a maximum-likelihood integrator. Integration was near optimal, independent of tool configuration/hand posture, provided that visual and haptic signals referred to the same object in the world. Thus, sensory correspondence was determined correctly (trial-by-trial), taking tool configuration into account. This reveals highly flexible multisensory integration underlying tool use, consistent with the brain constructing internal models of tools’ properties.

Binocular vision is often assumed to make a specific, critical contribution to online visual control of grasping by providing precise information about the separation between digits and object. This account overlooks the ‘viewing geometry’ typically encountered in grasping, however. Separation of hand and object is rarely aligned precisely with the line of sight (the visual depth dimension), and analysis of the raw signals suggests that, for most other viewing angles, binocular feedback is less precise than monocular feedback. Thus, online grasp control relying selectively on binocular feedback would not be robust to natural changes in viewing geometry. Alternatively, sensory integration theory suggests that different signals contribute according to their relative precision, in which case the role of binocular feedback should depend on viewing geometry, rather than being ‘hard-wired’. We manipulated viewing geometry, and assessed the role of binocular feedback by measuring the effects on grasping of occluding one eye at movement onset. Loss of binocular feedback resulted in a significantly less extended final slow-movement phase when hand and object were separated primarily in the frontoparallel plane (where binocular information is relatively imprecise), compared to when they were separated primarily along the line of sight (where binocular information is relatively precise). Consistent with sensory integration theory, this suggests the role of binocular (and monocular) vision in online grasp control is not a fixed, ‘architectural’ property of the visuo-motor system, but arises instead from the interaction of viewer and situation, allowing robust online control across natural variations in viewing geometry.

The stochastic nature of environmental factors that govern the behavior of fire, such as wind and fuel, exposes wildfire modeling to a degree of uncertainty. In order to produce more realistic wildfire predictions, it is, therefore, necessary to incorporate these uncertainties within wildfire models in a way that reflects the influence of environmental stochasticity on wildfire propagation. Otherwise, the risks of the potential danger of a given wildfire may be under-represented. Specifically, environmental stochasticity in the form of wind variability results in considerable uncertainty in the output of fire spread models. Here, we consider two stochastic wind models and their implementation in the spark fire simulator framework to capture the environmental uncertainty related to wind variability. The results are compared with the output from purely deterministic wildfire spread models and are discussed in the context of the potential ramifications for wildfire risk management.

Ideal grasping movements should maintain an appropriate probability of success, while controlling movement-related costs, in the presence of varying visual (and motor) uncertainty. It is often assumed that the probability of errors is managed by adjusting a margin for error in hand opening (e.g., opening the hand wider with increased visual uncertainty). This idea is intuitive, but non-trivial. It implies not only that the brain can estimate the amount of uncertainty, but also that it can compute how different possible alterations to the movement will affect the probability of errors—which we term the ‘probability landscape’. Previous work suggests the amount of uncertainty is factored into grasping movements. Our aim was to determine whether grasping movements are also sensitive to the probability landscape. Subjects completed three different grasping tasks, with naturally different probability landscapes, such that appropriate margin-for-error responses to increased uncertainty were qualitatively different (opening the hand wider, the same amount, or less wide). We increased visual uncertainty by blurring vision, and by covering one eye. Movements were performed without visual feedback to isolate uncertainty in the brain’s initial estimate of object properties. Changes to hand opening in response to increased visual uncertainty closely resembled those predicted by the margin-for-error account, suggesting that grasping is sensitive to the probability landscape associated with different tasks. Our findings therefore support the intuitive idea that grasping movements employ a true margin-for-error mechanism, which exerts active control over the probability of errors across changing circumstances.

The role of binocular vision in grasping has frequently been assessed by measuring the effects on grasp kinematics of covering one eye. These studies have typically used three or fewer objects presented at three or fewer distances, raising the possibility that participants learn the properties of the stimulus set. If so, even relatively poor visual information may be sufficient to identify which object/distance configuration is presented on a given trial, in effect providing an additional source of depth information. Here we show that the availability of this uncontrolled cue leads to an underestimate of the effects of removing binocular information, and therefore to an overestimate of the effectiveness of the remaining cues. We measured the effects of removing binocular cues on visually open-loop grasps using (1) a conventional small stimulus-set, and (2) a large, pseudo-randomised stimulus set, which could not be learned. Removing binocular cues resulted in a significant change in grip aperture scaling in both conditions: peak grip apertures were larger (when reaching to small objects), and scaled less with increases in object size. However, this effect was significantly larger with the randomised stimulus set. These results confirm that binocular information makes a significant contribution to grasp planning. Moreover, they suggest that learned stimulus information can contribute to grasping in typical experiments, and so the contribution of information from binocular vision (and from other depth cues) may not have been measured accurately.

The nonlinear stability of cylindrically and spherically expanding detonation waves is investigated using numerical simulations for both directly (blast) initiated detonations and cases where the simulations are initialized by placing quasi-steady solutions corresponding to different initial shock radii onto the grid. First, high-resolution one-dimensional (axially or radially symmetric) simulations of pulsating detonations are performed. Emphasis is on comparing with the predictions of a recent one-dimensional linear stability analysis of weakly curved detonation waves. The simulations show that, in agreement with the linear analysis, increasing curvature has a rapid destabilizing effect on detonation waves. The initial size and growth rate of the pulsation amplitude decreases as the radius where the detonation first forms increases. The pulsations may reach a saturated nonlinear behaviour as the amplitude grows, such that the subsequent evolution is independent of the initial conditions. As the wave expands outwards towards higher (and hence more stable) radii, the nature of the saturated nonlinear dynamics evolves to that of more stable behaviour (e.g. the amplitude of the saturated nonlinear oscillation decreases, or for sufficiently unstable cases, the oscillations evolve from multi-mode to period-doubled to limit-cycle-type behaviour). For parameter regimes where the planar detonation is stable, the linear stability prediction of the neutrally stable curvature gives a good prediction of the location of the maximum amplitude (provided the stability boundary is reached before the oscillations saturate) and of the critical radius of formation above which no oscillations are seen. The linear analysis also predicts very well the dependence of the period on the radius, even in the saturated nonlinear regimes. Secondly, preliminary two-dimensional numerical simulations of expanding cellular detonations are performed, but it is shown that resolved and accurate calculations of the cellular dynamics are currently computationally prohibitive, even with a dynamically adaptive numerical scheme.

Determining the underlying cause of persistent eosinophilia is important for effective clinical management but remains a diagnostic challenge in many cases. We identified STAT5B N642H, an established oncogenic mutation, in 27/1715 (1.6%) cases referred for investigation of eosinophilia. Of the 27 mutated cases, a working diagnosis of hypereosinophilic syndrome (HES; n = 7) or a myeloid neoplasm with eosinophilia (n = 20) had been made prior to the detection of STAT5B N642H. Myeloid panel analysis identified a median of 2 additional mutated genes (range 0–4) with 4 cases having STAT5B N642H as a sole abnormality. STAT5B N642H was absent in cultured T cells of 4/4 positive cases. Individuals with SF3B1 mutations (9/27; 33%) or STAT5B N642H as a sole abnormality had a markedly better overall survival compared to cases with other additional mutations (median 65 months vs. 14 months; hazard ratio = 8.1; P < 0.001). The overall survival of STAT5B-mutated HES cases was only 30 months, suggesting that these cases should be reclassified as chronic eosinophilic leukemia, not otherwise specified (CEL-NOS). The finding of STAT5B N642H as a recurrent mutation in myeloid neoplasia with eosinophilia provides a new diagnostic and prognostic marker as well as a potential target for therapy.

Although substantial progress has been made in the pathophysiology and management of the post-thrombotic syndrome (PTS), several aspects still need clarification. Among them, the incidence and severity of PTS in the real world, the risk factors for its development, the value of patient’s self-evaluation, and the ability to identify patients at risk for severe PTS. Eligible participants (n = 1107) with proximal deep-vein thrombosis (DVT) from the global GARFIELD-VTE registry underwent conventional physician’s evaluation for PTS 36 months after diagnosis of their DVT using the Villalta score. In addition, 856 patients completed a Villalta questionnaire at 24 months. Variable selection was performed using stepwise algorithm, and predictors of severe PTS were incorporated into a multivariable risk model. The optimistic adjusted c-index was calculated using bootstrapping techniques. Over 36-months, 27.8% of patients developed incident PTS (mild in 18.7%, moderate in 5.7%, severe in 3.4%). Patients with incident PTS were older, had a lower prevalence of transient risk factors of DVT and a higher prevalence of persistent risk factors of DVT. Self-assessment of overall PTS at 24 months showed an agreement of 63.4% with respect to physician’s evaluations at 36 months. The severe PTS multivariable model provided an optimistic adjusted c-index of 0.68 (95% CI 0.59–0.77). Approximately a quarter of DVT patients experienced PTS over 36 months after VTE diagnosis. Patient’s self-assessment after 24 months provided added value for estimating incident PTS over 36 months. Multivariable risk analysis allowed good discrimination for severe PTS.