Determination of Plastic Anisotropy of Extruded 7075 Aluminum Alloy Thick Plate for Simulation of Post-Extrusion Forming

In this study, the plastic anisotropy distribution of an extruded 7075 aluminum alloy thick plate was evaluated through small-cube compression tests. The extruded plate with a thickness of 15 mm was divided into five layers in order to verify the difference in plastic anisotropy along the thickness direction of the extruded thick plate. Small-cube specimens with a side length of 1 mm were extracted from each layer and subjected to compression tests in each direction to evaluate the directional r-values of the extruded material. The r-values were applied to Hill’s quadratic yield criterion to calculate the six coefficients for each layer. To consider the plastic anisotropy in the thickness direction, a finite element model divided into five layers in the thickness direction was applied. Upsetting tests were conducted to verify the accuracy of the finite element analysis using cube specimens with a side length of 15 and 10.6 mm, and the results of the finite element analysis and the upsetting test were compared and analyzed against each other. Consequently, the finite element analyses were precisely simulated the upsetting test results.

A Dynamic Model for Limb Selection

Two experiments and a model on limb selection are reported. In Experiment 1 left-handed and right-handed participants (N = 36) repeatedly used one hand for grasping a small cube. After a clear switch in the cube’s location, perseverative limb selection was revealed in both handedness groups. In Experiment 2 the cubes were presented in a clockwise and counter-clockwise sequence to right-handed participant (N = 15). A spatial delay in the switch point between right-hand use and left-hand use was observed. The model simulates the experiments, by implementing the multiple-timescale dynamics of the action-selection process underlying limb selection. It integrates two mechanisms that were earlier proposed to underlie this selection aspect of manual activity: limb dominance and attentional information. Finally, the model is used to simulate Gabbard et al.’s (1997) experiment, offering a concise coupling of strength and direction of handedness.

Compatibility between object size and response side in grasping: the left hand prefers smaller objects, the right hand prefers larger objects

It has been proposed that the brain processes quantities such as space, size, number, and other magnitudes using a common neural metric, and that this common representation system reflects a direct link to motor control, because the integration of spatial, temporal, and other quantity-related information is fundamental for sensorimotor transformation processes. In the present study, we examined compatibility effects between physical stimulus size and spatial (response) location during a sensorimotor task. Participants reached and grasped for a small or large object with either their non-dominant left or their dominant right hand. Our results revealed that participants initiated left hand movements faster when grasping the small cube compared to the large cube, whereas they initiated right hand movements faster when grasping the large cube compared to the small cube. Moreover, the compatibility effect influenced the timing of grip aperture kinematics. These findings indicate that the interaction between object size and response hand affects the planning of grasping movements and supports the notion of a strong link between the cognitive representation of (object) size, spatial (response) parameters, and sensorimotor control.

Compatibility between object size and response side in grasping: The left hand prefers smaller objects, the right hand prefers larger objects

It has been proposed that the brain processes quantities such as space, size, number, and other magnitudes using a common neural metric, and that this common representation system reflects a direct link to motor control, because the integration of spatial, temporal, and other quantity-related information is fundamental for sensorimotor transformation processes. In the present study, we examined compatibility effects between physical stimulus size and spatial (response) location during a sensorimotor task. Participants reached and grasped for a small or large object with either their non-dominant left or their dominant right hand. Our results revealed that participants initiated left hand movements faster when grasping the small cube compared to the large cube, whereas they initiated right hand movements faster when grasping the large cube compared to the small cube. Moreover, the compatibility effect influenced the timing of grip aperture kinematics. These findings indicate that the interaction between object size and response hand affects the planning of grasping movements and supports the notion of a strong link between the cognitive representation of (object) size, spatial (response) parameters, and sensorimotor control.

Compatibility between object size and response side in grasping: The left hand prefers smaller objects, the right hand prefers larger objects

It has been proposed that the brain processes quantities such as space, size, number, and other magnitudes using a common neural metric, and that this common representation system reflects a direct link to motor control, because the integration of spatial, temporal, and other quantity-related information is fundamental for sensorimotor transformation processes. In the present study, we examined compatibility effects between physical stimulus size and spatial (response) location during a sensorimotor task. Participants reached and grasped for a small or large object with either their non-dominant left or their dominant right hand. Our results revealed that participants initiated left hand movements faster when grasping the small cube compared to the large cube, whereas they initiated right hand movements faster when grasping the large cube compared to the small cube. Moreover, the compatibility effect influenced the timing of grip aperture kinematics. These findings indicate that the interaction between object size and response hand affects the planning of grasping movements and supports the notion of a strong link between the cognitive representation of (object) size, spatial (response) parameters, and sensorimotor control.

Material evidence: interaction of well-learned priors and sensorimotor memory when lifting objects

Skilled object lifting requires the prediction of object weight. When lifting new objects, such prediction is based on well-learned size-weight and material-density correlations, or priors. However, if the prediction is erroneous, people quickly learn the weight of the particular object and can use this knowledge, referred to as sensorimotor memory, when lifting the object again. In the present study, we explored how sensorimotor memory, gained when lifting a given object, interacts with well-learned material-density priors when predicting the weight of a larger but otherwise similar-looking object. Different groups of participants 1st lifted 1 of 4 small objects 10 times. These included a pair of wood-filled objects and a pair of brass-filled objects where 1 of each pair was covered in a wood veneer and the other was covered in a brass veneer. All groups then lifted a larger, brass-filled object with the same covering as the small object they had lifted. For each lift, we determined the initial peak rate of change of vertical load-force rate and the load-phase duration, which provide estimates of predicted object weight. Analysis of the 10th lift of the small cube revealed no effects of surface material, indicating participants learned the appropriate forces required to lift the small cube regardless of object appearance. However, both surface material and core material of the small cube affected the 1st lift of the large block. We conclude that sensorimotor memory related to object density can contribute to weight prediction when lifting novel objects but also that long-term priors related to material properties can influence the prediction.

A Fractal Function Related to the John–Nirenberg Inequality forQα(ℝn)

A borderline case functionfforQα(ℝn) spaces is defined as a Haar wavelet decomposition, with the coefficients depending on a fixed parameterβ> 0. On its supportI0= [0, 1]n,f(x) can be expressed by the binary expansions of the coordinates ofx. In particular,f=fβ∈Qα(ℝn) if and only if α <β<, while forβ= α, it was shown by Yue and Dafni thatfsatisfies a John–Nirenberg inequality forQα(ℝn). Whenβ≠ 1,fis a self-affine function. It is continuous almost everywhere and discontinuous at all dyadic points insideI0. In addition, it is not monotone along any coordinate direction in any small cube. When the parameterβ∈ (0, 1),fis onto fromI0 to, and the graph offhas a non-integer fractal dimensionn+ 1 −β.