456 research outputs found
Self‐Powered Mechanical Nanofluidic Generators Based on Gradient Charge‐Modified Sustainable Wood‐Derived Nanochannels
No full textAbstract The growing demand for self‐powered technology in portable and wearable electronics has spurred significant advancements in energy harvesting systems. However, conventional mechanical generators based on triboelectric and piezoelectric effects are limited by short discharge durations, despite achieving high output potentials. Here, a mechanical nanofluidic generator (MNG) is reported with gradient charge‐modified nanochannels, designed for mechanical energy harvesting. The MNG features highly aligned nanochannels with engineered surface charges, enabling a peak output voltage of 10.58 ± 1.29 V and a prolonged energy release time of 675.80 ± 112.08 s, with orders of magnitude longer than traditional generators that normally discharge in milliseconds to microseconds. This superior performance is attributed to the synergistic effects of gradient surface charge modification and enhanced interactions between transport ions and surface charges. This performance is attributed to the synergistic effects of surface charge gradients and strengthened ion–surface interactions, underscoring the MNG's potential for next‐generation self‐powered systems.Natural Sciences and Engineering Research Council of Canada https://doi.org/10.13039/501100000038Alexander von Humboldt-Stiftung https://doi.org/10.13039/100005156Deutsche Forschungsgemeinschaft https://doi.org/10.13039/501100001659China Scholarship Council https://doi.org/10.13039/50110000454
Analyzing Gaze and Hand Movement Patterns in Leader-Follower Interactions During a Time-Continuous Cooperative Manipulation Task
No full textIn daily life, people often interact by taking on leader and follower roles. Unlike laboratory experiments, these interactions unfold naturally and continuously. Although it is well established that gaze typically precedes object manipulation, much less is known about how gaze–hand patterns evolve in interactive settings where one person must take the other’s actions into account. Here we examine predictive, planning-related behavior in a two-player tabletop game called “do-undo.” Participants alternated as Leader and Follower. The Leader performed simple pick-and-place actions to alter the arrangement of objects, while the Follower used other objects to restore the previous configuration. We recorded eye and hand movements, along with object trajectories, using a system that combined eye tracking with multi-camera motion capture. Touch sensors on the players’ hands provided precise timing of contacts, allowing us to segment cooperative action into well-defined temporal intervals. As expected, eye fixations consistently preceded manipulation, but clear role differences emerged. Leaders looked more often and earlier at target objects. In many trials, their gaze anticipated not only their own actions but also those required of the Follower. Leaders also more frequently checked the outcome of the do-undo sequence. Both roles showed gaze patterns consistent with memorization, but alternating gazes between objects and destinations were much more common in Leaders. Some patterns suggested longer-term planning beyond the immediate action. These findings reveal distinct decision-making and planning strategies in Leaders and Followers. Leaders consider not only their own next moves but also the potential actions of their partners, shedding light on the complex cognitive processes that underly everyday human interaction
Examples of the actual conservation practices applied to Cheng Zhi Hall.
No full textExamples of the actual conservation practices applied to Cheng Zhi Hall.</p
Experimental evaluation of the wicking and reinforcement functions of wicking nonwoven geotextile-geogrid composite in roads
No full textRoad performance is significantly enhanced by incorporating geosynthetics through their reinforcement and drainage functions. This study introduces a new geosynthetic that integrates all these functions. It is made of biaxial polypropylene geogrids heat-bonded to wicking nonwoven geotextiles (WNWGs). Unlike the wicking woven geotextiles comprising deep-grooved fibers, WNWGs are chemically treated to be hydrophilic and thus possess rapid wetting and wicking properties while preserving the large lateral drainage functionality of conventional nonwoven geotextiles. To assess the wicking behavior of the geotextile, a series of wicking tests were conducted in water alone and saturated soils under controlled temperature and relative humidity. Additionally, contact angle measurements and microscopic analyses with Scanning Electron Microscopy (SEM) were conducted to elucidate the underlying wicking mechanisms. To assess the combined reinforcement and wicking performance of the new composite, a series of model tests including rainfall simulation and plate loading tests were performed on the WNWG-geogrid composite reinforced bases over weak subgrade using a customized model test apparatus. The results confirmed that the inclusion of WNWG-geogrid composite significantly enhanced drainage, stiffness, and bearing capacity of road bases. The findings from this study demonstrate the promising performance of this new composite and provides valuable reference for full-scale tests and applications in roads.Graduate2025-12-0
Updating predictions in a complex repertoire of actions and its neural representation
No full textEven though actions we observe in everyday life seem to unfold in a continuous manner, they are automatically divided into meaningful chunks, that are single actions or segments, which provide information for the formation and updating of internal predictive models. Specifically, boundaries between actions constitute a hub for predictive processing since the prediction of the current action comes to an end and calls for updating of predictions for the next action. In the current study, we investigated neural processes which characterize such boundaries using a repertoire of complex action sequences with a predefined probabilistic structure. Action sequences consisted of actions that started with the hand touching an object (T) and ended with the hand releasing the object (U). These action boundaries were determined using an automatic computer vision algorithm. Participants trained all action sequences by imitating demo videos. Subsequently, they returned for an fMRI session during which the original action sequences were presented in addition to slightly modified versions thereof. Participants completed a post-fMRI memory test to assess the retention of original action sequences. The exchange of individual actions, and thus a violation of action prediction, resulted in increased activation of the action observation network and the anterior insula. At U events, marking the end of an action, increased brain activation in supplementary motor area, striatum, and lingual gyrus was indicative of the retrieval of the previously encoded action repertoire. As expected, brain activation at U events also reflected the predefined probabilistic branching structure of the action repertoire. At T events, marking the beginning of the next action, midline and hippocampal regions were recruited, reflecting the selected prediction of the unfolding action segment. In conclusion, our findings contribute to a better understanding of the various cerebral processes characterizing prediction during the observation of complex action repertoires
Action understanding and prediction during inter-agent interaction
No full textThe utilisation of robotics has seen a significant rise over the years, particularly fuelled by the burgeoning advancements in deep learning and artificial intelligence research and development. Despite this progress, the challenge of social acceptance remains a significant
hurdle in the widespread adoption of robots for practical applications. A prominent aspect of this challenge lies in the effectiveness and naturalness of HRI (Human-Robot Interaction). Enhancing robotic behaviours holds considerable potential to substantially improve the social
acceptance of robots. The approach to achieve the enhancement of HRI of this research is by firstly obtaining a profound comprehension of human behaviours in interactive situations of HHI (Human-Human Interaction). Subsequently, the research will use the unveiled insights and
principles to guide the design, evolution, and implementation of socially adept robots.
The research begins by crafting experiment paradigms centred on the concept of "double contingency," which is a term stands for a social situation that the agents perceive each other without having prior knowledge about the forthcoming events. Across the study, three distinct
experiment games are designed to simulate diverse interaction scenarios. Game 1 delves into competitive contexts, employing the do/undo paradigm and assigning two player roles: leader and follower. It challenges follower players to keenly observe the actions of the leader player
and counteract accordingly. Game 2 and Game 3 target collaborative scenarios, where two players are tasked with constructing a predefined combination of objects while constrained to act simultaneously.
Subsequently, the research targets at implementing a sophisticated experiment setup capable of capturing details of human behaviour patterns during interaction. Eye movement, touching/untouching events and hand movement are the three major types of data in this research. The
successful implementations have enabled the experiment setup to effectively and sufficiently interpret the patterns of human actions in the designed situations.
With the deployment of game 1, the study collects rich empirical data on human decision-making, prediction capabilities, and so on. Analysing the collected data uncovers the behavioural patterns in competitive interactive situations of HHI. Hypotheses are formulated and rigorously
tested to evaluate the predictive abilities of observers, and the timing of transition phases within interactions. It is found that, in the designed dyadic alternative interaction situation, on one hand, the observers can successfully predict the target objects and the target
locations of the actors in the majority of the cases, and the leader observers have higher successful prediction rate of the target of the actors compared to the follower observers, as they have prior knowledge about the upcoming counteractions of the followers. Moreover, during
observation, the observers tend to start the prediction of target locations of the actors before the actors have actually touched the target objects. In addition, the observers start their own action roughly 1.58 seconds after the actors finish their actions. On the other hand,
the actors have 2.31 candidate target objects and 1.15 candidate target locations on average when planning. When they plan the target objects, they transit their eye fixations on the candidates 5.54 or 7.27 times on average based on different planning types (type Alpha actors start
the target location selection before the Touching event and tye Beta actors start it after the Touching event). As for fixation transitions of candidate target locations, the average numbers are 5.15 and 2.70 for type Alpha and type Beta, respectively.
Overall, this thesis contributes to the advancement of HRI research by introducing innovative experiment paradigms, conducting rigorous analyses, and providing valuable insights into human behaviour dynamics, through interactive HHI situation experiments. The findings pave the way
for future research aimed at further enhancing robot behaviors and fostering greater social acceptance in human-robot interactions.2024-06-2
Recommended from our members
Spectroscopy of the Temperature and Current Driven Metal-Insulator Transition in Ca₂RuO₄
No full textThis thesis presents the study for the temperature-driven and current-driven metal-insulator phase transition (MIT) in Ca₂RuO₄ via home-built variable temperature Scanning Tunneling Microscope. Atomically resolved topography images along with temperature dependence of resistivity are taken verifying the quality of the single crystals used in this experiment. Tunneling spectra are measured under various temperatures across the Tmi = 357K, which clearly shows spectra evolution with temperature and the difference between the room- temperature insulator phase and the high-temprature metal phase. Compared with DMFT calculation, the STS indicates lattice structure plays a vital role in the phase transition. Same measurement is conducted on the crystals under a DC current, thanks to a custom designed sample holder. The evolution of the tunneling spectra with source current demon- strates similarity with the one of temperature-driven MIT. The comparison between the spectra taken at high-temperature metalic state and the high-current metalic state high- lights the similarity of these 2 phases, with both showing a DOS transfer from 1eV to lower energy, when compared with the ground state. Combined with a variety of other studies via transport, scattering technique and infrared thermal imaging, it is found that the local temperature dominates both temperature-driven and current-driven MIT. It is very likely that the current-driven is caused by the inevitable Joule heating generated by the current, indicating the high-current metallic phase might be the same with high-current metallic phase. Finally, surface roughness and autocorrelation length analysis suggests an inhomo- geneous surface topography stemmed from the coexistence of the insulating S* phase and conducting L* phase under current
Efficient Neural Network Architecture Search
No full textOne-Shot Neural Architecture Search (NAS) is a promising method to significantly reduce search time without any separate training. It can be treated as a Network Compression problem on the architecture parameters from an overparameterized network. However, there are two issues associated with most one-shot NAS methods. First, dependencies between a node and its predecessors and successors are often disregarded which result in improper treatment over zero operations. Second, architecture parameters pruning based on their magnitude is questionable. In this thesis, classic Bayesian learning approach is applied to alleviate these two issues. Unlike other NAS methods, we train the over-parameterized network for only one epoch before update network architecture. Impressively, this enabled us to find the optimal architecture in both proxy and proxyless tasks on CIFAR-10 within only 0.2 GPU days using a single GPU. As a byproduct, our approach can be transferred directly to convolutional neural networks compression by enforcing structural sparsity that is able to achieve extremely sparse networks without accuracy deterioration.Mechanical Engineering | Vehicle Engineerin
Numerical modelling of dowelled connections in Laminated Veneer Lumber
No full textThe complex mechanical behaviour of timber makes it hard to predict the failure modes in connections made of timber in Finite Element Models (FEM). The combination of various failure modes (brittle and ductile) , anisotropic behaviour, contact of steel elements and large deformations that can occur in a timber joint challenges the use of FEM. To this date no widely used approach is available for the modelling of timber connections. This knowledge gap impedes the use of large timber connections for high rise buildings in seismic regions like New Zealand. For tall seismic resilient structures a profound understanding of the various failure modes of a connection is needed to guarantee a safe design. In this thesis a new model approach with the use of cohesive elements to simulate cracking is investigated for the prediction of the mechanical behaviour of connections. An embedment test simulation is a logical step towards this connection model.Timber can be characterised by its strong longitudinal fibres and the lignin that forms the bonding between the fibres. This anisotropic structure of the material results in a strong and stiff parallel and a weaker perpendicular behaviour of the material. Timber reacts ductile to compression loading and brittle in tension and shear loading. A typical crushing action of the timber (with micro cracking and densification of the timber) occurs when the maximum compression parallel to the grain stress is reached. The specific manufacturing process of Laminated Veneer Lumber (LVL) reduces the inhomogeneous character of timber. This improves the strength and the predictability of the material. The cracks that occur in tension and shear can cause four different brittle failure modes in a dowelled connection (row shear, group tear out, failure of the net cross section and tensile splitting). A brittle failure mode can be prevented when minimum end or edge distances and spacing between fasteners are satisfied. In that case a ductile failure is expected with plastic deformation of the dowel and crushing of the timber underneath the dowel.FEM is a powerful tool that is able to solve complex partial differential equation problems. Its basis lies in the linear formulation of small elements that are linked by coinciding nodal degrees of freedom to form a structure. The linear formulation has limited validity and a failure criteria is needed to define the onset of nonlinear behaviour. Multiple nonlinear approaches are available to accurately simulate the complex behaviour of timber in connections. The most promising approach is the use of cohesive elements at the locations where cracks are expected. The anisotropic nature of wood makes the prediction of crack locations in connections possible. The cohesive elements have a damage formulation to simulate strength and stiffness loss after the material strength is reached. This softening model hinders the solution procedure and therefore special solution techniques (e.g. line search, automatic stabilization and viscous regularization) are employed.A first model is made to simulate the embedment behaviour in LVL. In the embedment tests conducted by Franke and Quenneville a steel dowel is pushed in a timber block with a pre-drilled hole. In the translation of this test to an accurate FEM model three nonlinear phenomena are simulated (cracking, crushing in compression and contact). The cracking behaviour in tension and shear is modelled with cohesive elements with a damage formulation. These cracks are inserted at the location of potential crack growth. The remaining timber has a trilinear isotropic plastic hardening formulation to accurately predict the deformations in the LVL under compression loading. The last nonlinear phenomena is contact between the steel and the timber. This is simulated as "hard" contact in normal direction and frictional contact in tangential direction. The implicit solver encountered difficulties in converging due to contact alterations (chatter) and the softening behaviour in the cohesive elements. The automatic time incrementation algorithm reduced the increment size to overcome these difficulties. The analysis resulted in a load displacement curve that had good agreement with the experimental curve. A parameter study proved that the small difference can be related to the natural variation of material properties.The approach of the embedment FEM was implemented in a more complex connection model. The connection tests conducted by Ottenhaus et al. that is simulated consists of 4 dowels that connect two outer LVL blocks with an inner steel plate. The spacing was chosen in such a way that a ductile failure mode was expected with brittle failure modes at large deformations. In the connection model plasticity in the steel dowels, the size of the specimens and the inclusion of tension parallel cracks increased the complexity of the model. This increased the convergence difficulties and the analysis ceased (at 0.43 mm) before the maximum load was reached .A study was made to improve the stability of the numerical solution procedure. The impact of changing the formulations of cohesive elements, contact and the solution procedure on the convergence is tested. The viscous regularization and the initial dummy stiffness of the cohesive elements had the most influence on the convergence. With increased viscous regularization the implicit solver becomes more stable and computes more displacement increments (up to 6.91 mm). However, viscous regularization introduces artificial forces that significantly decreased the damage evolution. This prevented the formation of brittle failure mechanism.By reducing the initial dummy stiffness of the cohesive elements (down to 2 times the timber element stiffness) the convergence improved significantly. With this initial cohesive stiffness the global softening behaviour (up to 10.08 mm) and failure development that are observed in the experiments could be simulated. The failure development consisted of the formation of plastic hinges in the dowels, tensile splitting and finally row shear failure that completely removed the supporting action of the timber under the dowels.The decrease of cohesive element stiffness has impact on the effective stiffness of the adjacent timber elements and decreases the accuracy of the model. The model needs to be improved to make the predictions of the brittle failure development more accurate. With arc-length control, an explicit solver or the sequential linear analysis method the convergence might be increased, without the accuracy loss that is attributed to cohesive stiffness decrease. Further research is needed to improve this connection model approach
A model platform for rapid, robust, directed, and long-range vibrational energy transport: Insights from a mixed quantum-classical study of a 1D molecular chain
No full text- …
