5,973 results on '"Lloyd, John"'
Search Results
2. A vagal–brainstem interoceptive circuit for cough-like defensive behaviors in mice
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Gannot, Noam, Li, Xingyu, Phillips, Chrystian D., Ozel, Ayse Bilge, Uchima Koecklin, Karin Harumi, Lloyd, John P., Zhang, Lusi, Emery, Katie, Stern, Tomer, Li, Jun Z., and Li, Peng
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- 2024
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3. Pose and shear-based tactile servoing
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Lloyd, John and Lepora, Nathan F.
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Computer Science - Robotics - Abstract
Tactile servoing is an important technique because it enables robots to manipulate objects with precision and accuracy while adapting to changes in their environments in real-time. One approach for tactile servo control with high-resolution soft tactile sensors is to estimate the contact pose relative to an object surface using a convolutional neural network (CNN) for use as a feedback signal. In this paper, we investigate how the surface pose estimation model can be extended to include shear, and utilize these combined pose-and-shear models to develop a tactile robotic system that can be programmed for diverse non-prehensile manipulation tasks, such as object tracking, surface following, single-arm object pushing and dual-arm object pushing. In doing this, two technical challenges had to be overcome. Firstly, the use of tactile data that includes shear-induced slippage can lead to error-prone estimates unsuitable for accurate control, and so we modified the CNN into a Gaussian-density neural network and used a discriminative Bayesian filter to improve the predictions with a state dynamics model that utilizes the robot kinematics. Secondly, to achieve smooth robot motion in 3D space while interacting with objects, we used SE(3) velocity-based servo control, which required re-deriving the Bayesian filter update equations using Lie group theory, as many standard assumptions do not hold for state variables defined on non-Euclidean manifolds. In future, we believe that pose and shear-based tactile servoing will enable many object manipulation tasks and the fully-dexterous utilization of multi-fingered tactile robot hands. Video: https://www.youtube.com/watch?v=xVs4hd34ek0, Comment: Accepted in International Journal of Robotics Research (IJRR). 29 pages, 20 figures. Related technical report: arXiv:2306.08560. Video: https://www.youtube.com/watch?v=xVs4hd34ek0
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- 2023
4. The Simons Observatory: A fully remote controlled calibration system with a sparse wire grid for cosmic microwave background telescopes
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Murata, Masaaki, Nakata, Hironobu, Iijima, Kengo, Adachi, Shunsuke, Seino, Yudai, Kiuchi, Kenji, Matsuda, Frederick, Randall, Michael J., Arnold, Kam, Galitzki, Nicholas, Johnson, Bradley R., Keating, Brian, Kusaka, Akito, Lloyd, John B., Seibert, Joseph, Silva-Feaver, Maximiliano, Tajima, Osamu, Terasaki, Tomoki, and Yamada, Kyohei
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
For cosmic microwave background (CMB) polarization observations, calibration of detector polarization angles is essential. We have developed a fully remote controlled calibration system with a sparse wire grid that reflects linearly polarized light along the wire direction. The new feature is a remote-controlled system for regular calibration, which has not been possible in sparse wire grid calibrators in past experiments. The remote control can be achieved by two electric linear actuators that load or unload the sparse wire grid into a position centered on the optical axis of a telescope between the calibration time and CMB observation. Furthermore, the sparse wire grid can be rotated by a motor. A rotary encoder and a gravity sensor are installed on the sparse wire grid to monitor the wire direction. They allow us to achieve detector angle calibration with expected systematic error of $0.08^{\circ}$. The calibration system will be installed in small-aperture telescopes at Simons Observatory.
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- 2023
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5. Sim-to-Real Model-Based and Model-Free Deep Reinforcement Learning for Tactile Pushing
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Yang, Max, Lin, Yijiong, Church, Alex, Lloyd, John, Zhang, Dandan, Barton, David A. W., and Lepora, Nathan F.
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Computer Science - Robotics - Abstract
Object pushing presents a key non-prehensile manipulation problem that is illustrative of more complex robotic manipulation tasks. While deep reinforcement learning (RL) methods have demonstrated impressive learning capabilities using visual input, a lack of tactile sensing limits their capability for fine and reliable control during manipulation. Here we propose a deep RL approach to object pushing using tactile sensing without visual input, namely tactile pushing. We present a goal-conditioned formulation that allows both model-free and model-based RL to obtain accurate policies for pushing an object to a goal. To achieve real-world performance, we adopt a sim-to-real approach. Our results demonstrate that it is possible to train on a single object and a limited sample of goals to produce precise and reliable policies that can generalize to a variety of unseen objects and pushing scenarios without domain randomization. We experiment with the trained agents in harsh pushing conditions, and show that with significantly more training samples, a model-free policy can outperform a model-based planner, generating shorter and more reliable pushing trajectories despite large disturbances. The simplicity of our training environment and effective real-world performance highlights the value of rich tactile information for fine manipulation. Code and videos are available at https://sites.google.com/view/tactile-rl-pushing/., Comment: Accepted by IEEE Robotics and Automation Letters (RA-L)
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- 2023
6. Bi-Touch: Bimanual Tactile Manipulation with Sim-to-Real Deep Reinforcement Learning
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Lin, Yijiong, Church, Alex, Yang, Max, Li, Haoran, Lloyd, John, Zhang, Dandan, and Lepora, Nathan F.
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Computer Science - Robotics - Abstract
Bimanual manipulation with tactile feedback will be key to human-level robot dexterity. However, this topic is less explored than single-arm settings, partly due to the availability of suitable hardware along with the complexity of designing effective controllers for tasks with relatively large state-action spaces. Here we introduce a dual-arm tactile robotic system (Bi-Touch) based on the Tactile Gym 2.0 setup that integrates two affordable industrial-level robot arms with low-cost high-resolution tactile sensors (TacTips). We present a suite of bimanual manipulation tasks tailored towards tactile feedback: bi-pushing, bi-reorienting and bi-gathering. To learn effective policies, we introduce appropriate reward functions for these tasks and propose a novel goal-update mechanism with deep reinforcement learning. We also apply these policies to real-world settings with a tactile sim-to-real approach. Our analysis highlights and addresses some challenges met during the sim-to-real application, e.g. the learned policy tended to squeeze an object in the bi-reorienting task due to the sim-to-real gap. Finally, we demonstrate the generalizability and robustness of this system by experimenting with different unseen objects with applied perturbations in the real world. Code and videos are available at https://sites.google.com/view/bi-touch/., Comment: Accepted by IEEE Robotics and Automation Letters (RA-L)
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- 2023
7. A pose and shear-based tactile robotic system for object tracking, surface following and object pushing
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Lloyd, John and Lepora, Nathan
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Computer Science - Robotics - Abstract
Tactile perception is a crucial sensing modality in robotics, particularly in scenarios that require precise manipulation and safe interaction with other objects. Previous research in this area has focused extensively on tactile perception of contact poses as this is an important capability needed for tasks such as traversing an object's surface or edge, manipulating an object, or pushing an object along a predetermined path. Another important capability needed for tasks such as object tracking and manipulation is estimation of post-contact shear but this has received much less attention. Indeed, post-contact shear has often been considered a "nuisance variable" and is removed if possible because it can have an adverse effect on other types of tactile perception such as contact pose estimation. This paper proposes a tactile robotic system that can simultaneously estimate both the contact pose and post-contact shear, and use this information to control its interaction with other objects. Moreover, our new system is capable of interacting with other objects in a smooth and continuous manner, unlike the stepwise, position-controlled systems we have used in the past. We demonstrate the capabilities of our new system using several different controller configurations, on tasks including object tracking, surface following, single-arm object pushing, and dual-arm object pushing., Comment: A video demonstrating the methods described in this paper is available at https://www.youtube.com/watch?v=xVs4hd34ek0
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- 2023
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8. Journalism and PR : new media and public relations in the digital age.
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Lloyd, John and Toogood, Laura
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Journalism and public relations ,Mass media and public opinion - Abstract
Summary: Public relations and journalism have had a difficult relationship for over a century, characterised by mutual dependence and - often - mutual distrust. The two professions have vied with each other for primacy: journalists could open or close the gates, but PR had the stories, the contacts and often the budgets for extravagant campaigns. The arrival of the internet, and especially of social media, has changed much of that. These new technologies have turned the audience into players - who play an important part in making the reputation, and the brand, of everyone from heads of state to new car models vulnerable to viral tweets and social media attacks. Companies, parties and governments are seeking more protection - especially since individuals within these organisations can themselves damage, even destroy, their brand or reputation with an ill-chosen remark or an appearance of arrogance. The pressures, and the possibilities, of the digital age have given public figures and institutions both a necessity to protect themselves, and channels to promote themselves free of news media gatekeepers. Political and corporate communications professionals have become more essential, and more influential within the top echelons of business, politics and other institutions. Companies and governments can now - must now - become media themselves, putting out a message 24/7, establishing channels of their own, creating content to attract audiences and reaching out to their networks to involve them in their strategies. Journalism is being brought into these new, more influential and fast growing communications strategies. And, as newspapers struggle to stay alive, journalists must adapt to a world where old barriers are being smashed and new relationships built - this time with public relations in the driving seat. The world being created is at once more protected and more transparent; the communicators are at once more influential and more fragile. This unique study illuminates a new media age.
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- 2015
9. Tactile-Driven Gentle Grasping for Human-Robot Collaborative Tasks
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Ford, Christopher J., Li, Haoran, Lloyd, John, Catalano, Manuel G., Bianchi, Matteo, Psomopoulou, Efi, and Lepora, Nathan F.
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Computer Science - Robotics - Abstract
This paper presents a control scheme for force sensitive, gentle grasping with a Pisa/IIT anthropomorphic SoftHand equipped with a miniaturised version of the TacTip optical tactile sensor on all five fingertips. The tactile sensors provide high-resolution information about a grasp and how the fingers interact with held objects. We first describe a series of hardware developments for performing asynchronous sensor data acquisition and processing, resulting in a fast control loop sufficient for real-time grasp control. We then develop a novel grasp controller that uses tactile feedback from all five fingertip sensors simultaneously to gently and stably grasp 43 objects of varying geometry and stiffness, which is then applied to a human-to-robot handover task. These developments open the door to more advanced manipulation with underactuated hands via fast reflexive control using high-resolution tactile sensing., Comment: Manuscript accepted to ICRA 2023. 6+n pages, 7 figures
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- 2023
10. Death in the Haymarket: A Story of Chicago, the First Labor Movement and the Bombing that Divided Gilded Age America (review)
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Lloyd, John P
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- 2007
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11. Tactile Gym 2.0: Sim-to-real Deep Reinforcement Learning for Comparing Low-cost High-Resolution Robot Touch
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Lin, Yijiong, Lloyd, John, Church, Alex, and Lepora, Nathan F.
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Computer Science - Robotics - Abstract
High-resolution optical tactile sensors are increasingly used in robotic learning environments due to their ability to capture large amounts of data directly relating to agent-environment interaction. However, there is a high barrier of entry to research in this area due to the high cost of tactile robot platforms, specialised simulation software, and sim-to-real methods that lack generality across different sensors. In this letter we extend the Tactile Gym simulator to include three new optical tactile sensors (TacTip, DIGIT and DigiTac) of the two most popular types, Gelsight-style (image-shading based) and TacTip-style (marker based). We demonstrate that a single sim-to-real approach can be used with these three different sensors to achieve strong real-world performance despite the significant differences between real tactile images. Additionally, we lower the barrier of entry to the proposed tasks by adapting them to an inexpensive 4-DoF robot arm, further enabling the dissemination of this benchmark. We validate the extended environment on three physically-interactive tasks requiring a sense of touch: object pushing, edge following and surface following. The results of our experimental validation highlight some differences between these sensors, which may help future researchers select and customize the physical characteristics of tactile sensors for different manipulations scenarios.
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- 2022
12. DigiTac: A DIGIT-TacTip Hybrid Tactile Sensor for Comparing Low-Cost High-Resolution Robot Touch
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Lepora, Nathan F., Lin, Yijiong, Money-Coomes, Ben, and Lloyd, John
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Computer Science - Robotics - Abstract
Deep learning combined with high-resolution tactile sensing could lead to highly capable dexterous robots. However, progress is slow because of the specialist equipment and expertise. The DIGIT tactile sensor offers low-cost entry to high-resolution touch using GelSight-type sensors. Here we customize the DIGIT to have a 3D-printed sensing surface based on the TacTip family of soft biomimetic optical tactile sensors. The DIGIT-TacTip (DigiTac) enables direct comparison between these distinct tactile sensor types. For this comparison, we introduce a tactile robot system comprising a desktop arm, mounts and 3D-printed test objects. We use tactile servo control with a PoseNet deep learning model to compare the DIGIT, DigiTac and TacTip for edge- and surface-following over 3D-shapes. All three sensors performed similarly at pose prediction, but their constructions led to differing performances at servo control, offering guidance for researchers selecting or innovating tactile sensors. All hardware and software for reproducing this study will be openly released. Project website: www.lepora.com/digitac. Project repository: www.github.com/nlepora/digitac-design., Comment: 7 pages. Published in RA-L and accepted in IROS 2022
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- 2022
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13. Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces
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Chen, Dawei, Yang-Zhao, Samuel, Lloyd, John, and Ng, Kee Siong
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Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,68T37 ,I.2.6 - Abstract
This paper introduces factored conditional filters, new filtering algorithms for simultaneously tracking states and estimating parameters in high-dimensional state spaces. The conditional nature of the algorithms is used to estimate parameters and the factored nature is used to decompose the state space into low-dimensional subspaces in such a way that filtering on these subspaces gives distributions whose product is a good approximation to the distribution on the entire state space. The conditions for successful application of the algorithms are that observations be available at the subspace level and that the transition model can be factored into local transition models that are approximately confined to the subspaces; these conditions are widely satisfied in computer science, engineering, and geophysical filtering applications. We give experimental results on tracking epidemics and estimating parameters in large contact networks that show the effectiveness of our approach., Comment: 66 pages
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- 2022
14. One-Shot Domain-Adaptive Imitation Learning via Progressive Learning
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Zhang, Dandan, Fan, Wen, Lloyd, John, Yang, Chenguang, and Lepora, Nathan
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Computer Science - Robotics - Abstract
Traditional deep learning-based visual imitation learning techniques require a large amount of demonstration data for model training, and the pre-trained models are difficult to adapt to new scenarios. To address these limitations, we propose a unified framework using a novel progressive learning approach comprised of three phases: i) a coarse learning phase for concept representation, ii) a fine learning phase for action generation, and iii) an imaginary learning phase for domain adaptation. Overall, this approach leads to a one-shot domain-adaptive imitation learning framework. We use robotic pouring task as an example to evaluate its effectiveness. Our results show that the method has several advantages over contemporary end-to-end imitation learning approaches, including an improved success rate for task execution and more efficient training for deep imitation learning. In addition, the generalizability to new domains is improved, as demonstrated here with novel background, target container and granule combinations. We believe that the proposed method can be broadly applicable to different industrial or domestic applications that involve deep imitation learning for robotic manipulation, where the target scenarios have high diversity while the human demonstration data is limited., Comment: under review
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- 2022
15. Developing and Implementing FBA-BIPs in Elementary Classrooms: A Conceptual Replication
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Hirsch, Shanna E., Bruhn, Allison L., Randall, Kristina, Dunn, Michelle, Shelnut, Jill, and Lloyd, John Wills
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The majority of students with disabilities and behavioral challenges are taught in general education classrooms. Although these students may receive interventions resulting in positive behavioral changes, little is known about the collateral effects of implementing behavior intervention plans (BIP) on classroom peers with similar behavioral problems who are not receiving an intervention. The purpose of this study was to investigate the effects of functional behavioral assessments (FBAs) and BIPs for students with challenging behavior as well as their peers. We measured target student and peer academic engagement, as well as treatment integrity and social validity. As a result of the intervention, target students demonstrated increased academic engagement. In addition, results suggest that the FBA-BIPs had small effects on engagement for some peers.
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- 2020
16. To what extent can mastication functionality be restored following mandibular reconstruction surgery? A computer modeling approach
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Aftabi, Hamidreza, Sagl, Benedikt, Lloyd, John E., Prisman, Eitan, Hodgson, Antony, and Fels, Sidney
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- 2024
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17. Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image Translation
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Church, Alex, Lloyd, John, Hadsell, Raia, and Lepora, Nathan F.
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Computer Science - Robotics ,Computer Science - Artificial Intelligence - Abstract
Simulation has recently become key for deep reinforcement learning to safely and efficiently acquire general and complex control policies from visual and proprioceptive inputs. Tactile information is not usually considered despite its direct relation to environment interaction. In this work, we present a suite of simulated environments tailored towards tactile robotics and reinforcement learning. A simple and fast method of simulating optical tactile sensors is provided, where high-resolution contact geometry is represented as depth images. Proximal Policy Optimisation (PPO) is used to learn successful policies across all considered tasks. A data-driven approach enables translation of the current state of a real tactile sensor to corresponding simulated depth images. This policy is implemented within a real-time control loop on a physical robot to demonstrate zero-shot sim-to-real policy transfer on several physically-interactive tasks requiring a sense of touch.
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- 2021
18. Probabilistic Discriminative Models Address the Tactile Perceptual Aliasing Problem
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Lloyd, John, Lin, Yijiong, and Lepora, Nathan F.
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Computer Science - Robotics - Abstract
In this paper, our aim is to highlight Tactile Perceptual Aliasing as a problem when using deep neural networks and other discriminative models. Perceptual aliasing will arise wherever a physical variable extracted from tactile data is subject to ambiguity between stimuli that are physically distinct. Here we address this problem using a probabilistic discriminative model implemented as a 5-component mixture density network comprised of a deep neural network that predicts the parameters of a Gaussian mixture model. We show that discriminative regression models such as deep neural networks and Gaussian process regression perform poorly on aliased data, only making accurate predictions when the sources of aliasing are removed. In contrast, the mixture density network identifies aliased data with improved prediction accuracy. The uncertain predictions of the model form patterns that are consistent with the various sources of perceptual ambiguity. In our view, perceptual aliasing will become an unavoidable issue for robot touch as the field progresses to training robots that act in uncertain and unstructured environments, such as with deep reinforcement learning., Comment: 11 pages. Accepted in Robotics: Science & Systems (RSS 2021)
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- 2021
19. A Robust Controller for Stable 3D Pinching using Tactile Sensing
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Psomopoulou, Efi, Pestell, Nicholas, Papadopoulos, Fotios, Lloyd, John, Doulgeri, Zoe, and Lepora, Nathan F.
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Computer Science - Robotics ,Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper proposes a controller for stable grasping of unknown-shaped objects by two robotic fingers with tactile fingertips. The grasp is stabilised by rolling the fingertips on the contact surface and applying a desired grasping force to reach an equilibrium state. The validation is both in simulation and on a fully-actuated robot hand (the Shadow Modular Grasper) fitted with custom-built optical tactile sensors (based on the BRL TacTip). The controller requires the orientations of the contact surfaces, which are estimated by regressing a deep convolutional neural network over the tactile images. Overall, the grasp system is demonstrated to achieve stable equilibrium poses on various objects ranging in shape and softness, with the system being robust to perturbations and measurement errors. This approach also has promise to extend beyond grasping to stable in-hand object manipulation with multiple fingers., Comment: 8 pages, 10 figures, 1 appendix. Accepted for publication in IEEE Robotics and Automation Letters and in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021). Supplemental video: https://youtu.be/rfQesw3FDA4
- Published
- 2021
20. Neutron Star Quantum Death by Small Black Holes
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Giffin, Pierce, Lloyd, John, McDermott, Samuel D., and Profumo, Stefano
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High Energy Physics - Phenomenology ,Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Solar and Stellar Astrophysics ,General Relativity and Quantum Cosmology - Abstract
Neutron stars can be destroyed by black holes at their center accreting material and eventually swallowing the entire star. Here we note that the accretion model adopted in the literature, based on Bondi accretion or variations thereof, is inadequate for small black holes -- black holes whose Schwarzschild radius is comparable to, or smaller than, the neutron's de Broglie wavelength. In this case, quantum mechanical aspects of the accretion process cannot be neglected, and give rise to a completely different accretion rate. We show that for the case of black holes seeded by the collapse of bosonic dark matter, this is the case for electroweak-scale dark matter particles. In the case of fermionic dark matter, typically the black holes that would form at the center of a neutron star are more massive, unless the dark matter particle mass is very large, larger than about 10$^{10}$ GeV. We calculate the lifetime of neutron stars harboring a ``small'' black hole, and find that black holes lighter than $\sim 10^{11}$ kg quickly evaporate, leaving no trace. More massive black holes destroy neutron stars via quantum accretion on time-scales much shorter than the age of observed neutron stars. We find that the range where seed black holes inside neutron stars are massive enough that they do not quickly evaporate away, but not so massive that a fluid accretion picture is warranted is limited to between $\sim10^{11}$ and $10^{12}$ kg, but our results are key to accurately determine the actual critical black hole mass corresponding to the onset of neutron star destruction, Comment: 7 pages, 2 figures; v2 matches version accepted for publication in PRD
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- 2021
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21. Labor, Loyalty, and Rebellion: Southwestern Illinois Coal Miners and World War I (review)
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Lloyd, John
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- 2006
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22. Labor's Story in the United States (review)
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Lloyd, John
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- 2005
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23. Open Science and Single-Case Design Research
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Cook, Bryan G., Johnson, Austin H., Maggin, Daniel M., Therrien, William J., Barton, Erin E., Lloyd, John Wills, Reichow, Brian, Talbott, Elizabeth, and Travers, Jason C.
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Research indicating many study results do not replicate has raised questions about the credibility of science and prompted concerns about a potential reproducibility crisis. Moreover, most published research is not freely accessible, which limits the potential impact of science. Open science, which aims to make the research process more open and reproducible, has been proposed as one approach to increase the credibility and impact of scientific research. Although relatively little attention has been paid to open science in relation to single-case design, we propose that open-science practices can be applied to enhance the credibility and impact of single-case design research. In this article, we discuss how open-science practices align with other recent developments in single-case design research, describe four prominent open-science practices (i.e., preregistration, registered reports, data and materials sharing, and open access), and discuss potential benefits and limitations of each practice for single-case design.
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- 2022
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24. Towards integrated tactile sensorimotor control in anthropomorphic soft robotic hands
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Lepora, Nathan F., Stinchcombe, Andrew, Ford, Chris, Brown, Alfred, Lloyd, John, Catalano, Manuel G., Bianchi, Matteo, and Ward-Cherrier, Benjamin
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Computer Science - Robotics - Abstract
In this work, we report on the integrated sensorimotor control of the Pisa/IIT SoftHand, an anthropomorphic soft robot hand designed around the principle of adaptive synergies, with the BRL tactile fingertip (TacTip), a soft biomimetic optical tactile sensor based on the human sense of touch. Our focus is how a sense of touch can be used to control an anthropomorphic hand with one degree of actuation, based on an integration that respects the hand's mechanical functionality. We consider: (i) closed-loop tactile control to establish a light contact on an unknown held object, based on the structural similarity with an undeformed tactile image; and (ii) controlling the estimated pose of an edge feature of a held object, using a convolutional neural network approach developed for controlling other sensors in the TacTip family. Overall, this gives a foundation to endow soft robotic hands with human-like touch, with implications for autonomous grasping, manipulation, human-robot interaction and prosthetics. Supplemental video: https://youtu.be/ndsxj659bkQ, Comment: 7 pages, 10 figures. Supplemental video: https://youtu.be/ndsxj659bkQ
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- 2021
25. Symptomology following mRNA vaccination against SARS-CoV-2
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Ebinger, Joseph E, Lan, Roy, Sun, Nancy, Wu, Min, Joung, Sandy, Botwin, Gregory J, Botting, Patrick, Al-Amili, Daniah, Aronow, Harriet, Beekley, James, Coleman, Bernice, Contreras, Sandra, Cozen, Wendy, Davis, Jennifer, Debbas, Philip, Diaz, Jacqueline, Driver, Matthew, Fert-Bober, Justyna, Gu, Quanquan, Heath, Mallory, Herrera, Ergueen, Hoang, Amy, Hussain, Shehnaz K, Huynh, Carissa, Kim, Linda, Kittleson, Michelle, Liu, Yunxian, Lloyd, John, Luong, Eric, Malladi, Bhavya, Merchant, Akil, Merin, Noah, Mujukian, Angela, Nguyen, Nathalie, Nguyen, Trevor-Trung, Pozdnyakova, Valeriya, Rashid, Mohamad, Raedschelders, Koen, Reckamp, Karen L, Rhoades, Kylie, Sternbach, Sarah, Vallejo, Rocío, White, Shane, Tompkins, Rose, Wong, Melissa, Arditi, Moshe, Figueiredo, Jane C, Van Eyk, Jennifer E, Miles, Peggy B, Chavira, Cynthia, Shane, Rita, Sobhani, Kimia, Melmed, Gil Y, McGovern, Dermot PB, Braun, Jonathan G, Cheng, Susan, and Minissian, Margo B
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Epidemiology ,Public Health ,Health Sciences ,Prevention ,Infectious Diseases ,Emerging Infectious Diseases ,Clinical Research ,Pain Research ,Immunization ,Lung ,Pneumonia & Influenza ,Vaccine Related ,3.4 Vaccines ,Prevention of disease and conditions ,and promotion of well-being ,6.1 Pharmaceuticals ,Evaluation of treatments and therapeutic interventions ,Infection ,Good Health and Well Being ,COVID-19 ,COVID-19 Vaccines ,Female ,Humans ,RNA ,Messenger ,SARS-CoV-2 ,Vaccination ,Vaccine-associated symptoms ,Human Movement and Sports Sciences ,Public Health and Health Services ,Public health - Abstract
Despite demonstrated efficacy of vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of coronavirus disease-2019 (COVID-19), widespread hesitancy to vaccination persists. Improved knowledge regarding frequency, severity, and duration of vaccine-associated symptoms may help reduce hesitancy. In this prospective observational study, we studied 1032 healthcare workers who received both doses of the Pfizer-BioNTech SARS-CoV-2 mRNA vaccine and completed post-vaccine symptom surveys both after dose 1 and after dose 2. We defined appreciable post-vaccine symptoms as those of at least moderate severity and lasting at least 2 days. We found that symptoms were more frequent following the second vaccine dose than the first (74% vs. 60%, P 80% of all symptoms resolving within 2 days. The most common symptom was injection site pain, followed by fatigue and malaise. Overall, 20% of participants experienced appreciable symptoms after dose 1 and 30% after dose 2. In multivariable analyses, female sex was associated with greater odds of appreciable symptoms after both dose 1 (OR, 95% CI 1.73, 1.19-2.51) and dose 2 (1.76, 1.28-2.42). Prior COVID-19 was also associated with appreciable symptoms following dose 1, while younger age and history of hypertension were associated with appreciable symptoms after dose 2. We conclude that most post-vaccine symptoms are reportedly mild and last
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- 2021
26. Pose-Based Tactile Servoing: Controlled Soft Touch using Deep Learning
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Lepora, Nathan F. and Lloyd, John
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Computer Science - Robotics - Abstract
This article describes a new way of controlling robots using soft tactile sensors: pose-based tactile servo (PBTS) control. The basic idea is to embed a tactile perception model for estimating the sensor pose within a servo control loop that is applied to local object features such as edges and surfaces. PBTS control is implemented with a soft curved optical tactile sensor (the BRL TacTip) using a convolutional neural network trained to be insensitive to shear. In consequence, robust and accurate controlled motion over various complex 3D objects is attained. First, we review tactile servoing and its relation to visual servoing, before formalising PBTS control. Then, we assess tactile servoing over a range of regular and irregular objects. Finally, we reflect on the relation to visual servo control and discuss how controlled soft touch gives a route towards human-like dexterity in robots., Comment: A summary video is available here https://youtu.be/12-DJeRcfn0 *NL and JL contributed equally to this work
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- 2020
27. Goal-Driven Robotic Pushing Using Tactile and Proprioceptive Feedback
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Lloyd, John and Lepora, Nathan F.
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Computer Science - Robotics - Abstract
In robots, nonprehensile manipulation operations such as pushing are a useful way of moving large, heavy or unwieldy objects, moving multiple objects at once, or reducing uncertainty in the location or pose of objects. In this study, we propose a reactive and adaptive method for robotic pushing that uses rich feedback from a high-resolution optical tactile sensor to control push movements instead of relying on analytical or data-driven models of push interactions. Specifically, we use goal-driven tactile exploration to actively search for stable pushing configurations that cause the object to maintain its pose relative to the pusher while incrementally moving the pusher and object towards the target. We evaluate our method by pushing objects across planar and curved surfaces. For planar surfaces, we show that the method is accurate and robust to variations in initial contact position/angle, object shape and start position; for curved surfaces, the performance is degraded slightly. An immediate consequence of our work is that it shows that explicit models of push interactions might be sufficient but are not necessary for this type of task. It also raises the interesting question of which aspects of the system should be modelled to achieve the best performance and generalization across a wide range of scenarios. Finally, it highlights the importance of testing on non-planar surfaces and in other more complex environments when developing new methods for robotic pushing., Comment: Accepted in IEEE Transactions on Robotics. A video demonstrating the approach can be found at https://youtu.be/6fAlHWfLP7I
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- 2020
28. How well do isolated lignins mimic the inhibitory behaviour of cell wall lignins during enzymatic hydrolysis of hydrothermally treated softwood?
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MacAskill, Jessica J., Suckling, Ian D., Lloyd, John A., and Manley-Harris, Merilyn
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- 2023
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29. Deep Reinforcement Learning for Tactile Robotics: Learning to Type on a Braille Keyboard
- Author
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Church, Alex, Lloyd, John, Hadsell, Raia, and Lepora, Nathan F.
- Subjects
Computer Science - Robotics ,Computer Science - Artificial Intelligence - Abstract
Artificial touch would seem well-suited for Reinforcement Learning (RL), since both paradigms rely on interaction with an environment. Here we propose a new environment and set of tasks to encourage development of tactile reinforcement learning: learning to type on a braille keyboard. Four tasks are proposed, progressing in difficulty from arrow to alphabet keys and from discrete to continuous actions. A simulated counterpart is also constructed by sampling tactile data from the physical environment. Using state-of-the-art deep RL algorithms, we show that all of these tasks can be successfully learnt in simulation, and 3 out of 4 tasks can be learned on the real robot. A lack of sample efficiency currently makes the continuous alphabet task impractical on the robot. To the best of our knowledge, this work presents the first demonstration of successfully training deep RL agents in the real world using observations that exclusively consist of tactile images. To aid future research utilising this environment, the code for this project has been released along with designs of the braille keycaps for 3D printing and a guide for recreating the experiments. A brief video summary is also available at https://youtu.be/eNylCA2uE_E., Comment: Accepted in RAL and IROS 2020
- Published
- 2020
30. Optimal Deep Learning for Robot Touch
- Author
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Lepora, Nathan F. and Lloyd, John
- Subjects
Computer Science - Robotics - Abstract
This article illustrates the application of deep learning to robot touch by considering a basic yet fundamental capability: estimating the relative pose of part of an object in contact with a tactile sensor. We begin by surveying deep learning applied to tactile robotics, focussing on optical tactile sensors, which help bridge from deep learning for vision to touch. We then show how deep learning can be used to train accurate pose models of 3D surfaces and edges that are insensitive to nuisance variables such as motion-dependent shear. This involves including representative motions as unlabelled perturbations of the training data and using Bayesian optimization of the network and training hyperparameters to find the most accurate models. Accurate estimation of pose from touch will enable robots to safely and precisely control their physical interactions, underlying a wide range of object exploration and manipulation tasks., Comment: Accepted in IEEE Robotics & Automation Magazine Special Issue on Deep Learning and Machine Learning in Robotics. NL and JL contributed equally to this work
- Published
- 2020
31. An Exploratory Study of an Instructional Model for Co-Teaching
- Author
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Weiss, Margaret P., Glaser, Holly, and Lloyd, John Wills
- Abstract
Co-teaching is a widely used service delivery model for special education with significant variability in implementation. In this exploratory study, we examine a three-element model for instruction in co-teaching that is meant to reduce this variability and evaluate its implementation by three secondary co-teaching teams. Changes in teacher instructional behavior, feasibility, and factors affecting implementation are reported. We discuss the implications and limitations.
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- 2022
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32. Professional Learning and Development in Classroom Management for Novice Teachers: A Systematic Review
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Hirsch, Shanna E., Randall, Kristina, Bradshaw, Catherine, and Lloyd, John Wills
- Abstract
There is a growing awareness that novice teachers in particular are in need of support and additional professional learning and development (PLD), especially in the area of classroom management. Yet there is limited information regarding effective approaches for building novice teachers' skills related to classroom management. To address this gap, we conducted a systematic review of experimental studies related to novice teacher PLD in classroom management. We identified eight original experimental peer-reviewed studies published. We explored the research base, applying the Council for Exceptional Children Quality Indicators and coding studies to identify elements of practice-based professional development. Together, the available studies suggested that providing PLD increases classroom management practices while increasing student engagement. We discuss the implications of this review and conclude with implications for practice and future research related to novice teacher PLD.
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- 2021
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33. Targeted Professional Development: A Data-Driven Approach to Identifying Educators' Needs
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Hirsch, Shanna E., Ely, Emily, Lloyd, John Wills, and Isley, Deanna
- Abstract
Educator professional development (PD) is critical for improving instruction and student achievement. However, there are few frameworks for developing and designing PD based on educators' needs. We report the findings from a case study highlighting how an elementary school and university collaborated to address teachers' needs in the area of classroom management. From our experience, we provide key recommendations and resources for school and university partners.
- Published
- 2018
34. From pixels to percepts: Highly robust edge perception and contour following using deep learning and an optical biomimetic tactile sensor
- Author
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Lepora, Nathan F., Church, Alex, De Kerckhove, Conrad, Hadsell, Raia, and Lloyd, John
- Subjects
Computer Science - Robotics - Abstract
Deep learning has the potential to have the impact on robot touch that it has had on robot vision. Optical tactile sensors act as a bridge between the subjects by allowing techniques from vision to be applied to touch. In this paper, we apply deep learning to an optical biomimetic tactile sensor, the TacTip, which images an array of papillae (pins) inside its sensing surface analogous to structures within human skin. Our main result is that the application of a deep CNN can give reliable edge perception and thus a robust policy for planning contact points to move around object contours. Robustness is demonstrated over several irregular and compliant objects with both tapping and continuous sliding, using a model trained only by tapping onto a disk. These results relied on using techniques to encourage generalization to tasks beyond which the model was trained. We expect this is a generic problem in practical applications of tactile sensing that deep learning will solve. A video demonstrating the approach can be found at https://www.youtube.com/watch?v=QHrGsG9AHts, Comment: Accepted in RAL and ICRA 2019. N. Lepora and J. Lloyd contributed equally to this work
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- 2018
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35. Effects of a Multimedia Professional Development Package on Inclusive Science Teachers' Vocabulary Instruction
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Kennedy, Michael J., Rodgers, Wendy J., Romig, John Elwood, Lloyd, John Wills, and Brownell, Mary T.
- Abstract
Vocabulary knowledge is vital for students' success in school and beyond. However, students with disabilities and others who consistently score below their peers on various measures of vocabulary knowledge have difficulties in secondary-level content area courses. Because many students with disabilities are now educated primarily in general education classrooms, their teachers report needing more professional development on instructional strategies to support this population. Using a multiple-baseline design, we tested the efficacy of a multimedia, multicomponent professional development package in which middle school science teachers in inclusive classrooms promoted science vocabulary knowledge. The professional development package improved the quality of the teachers' use of evidence-based vocabulary practices and increased the amount of time they spent explicitly teaching vocabulary in their classes.
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- 2017
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36. Voronoi Features for Tactile Sensing: Direct Inference of Pressure, Shear, and Contact Locations
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Cramphorn, Luke, Lloyd, John, and Lepora, Nathan F.
- Subjects
Computer Science - Robotics - Abstract
There are a wide range of features that tactile contact provides, each with different aspects of information that can be used for object grasping, manipulation, and perception. In this paper inference of some key tactile features, tip displacement, contact location, shear direction and magnitude, is demonstrated by introducing a novel method of transducing a third dimension to the sensor data via Voronoi tessellation. The inferred features are displayed throughout the work in a new visualisation mode derived from the Voronoi tessellation; these visualisations create easier interpretation of data from an optical tactile sensor that measures local shear from displacement of internal pins (the TacTip). The output values of tip displacement and shear magnitude are calibrated to appropriate mechanical units and validate the direction of shear inferred from the sensor. We show that these methods can infer the direction of shear to $\sim$2.3$^{\circ}$ without the need for training a classifier or regressor. The approach demonstrated here will increase the versatility and generality of the sensors and thus allow sensor to be used in more unstructured and unknown environments, as well as improve the use of these tactile sensors in more complex systems such as robot hands., Comment: Presented at ICRA 2018
- Published
- 2018
37. Meta-Analysis of Prompt and Duration for Curriculum-Based Measurement of Written Language
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Romig, John Elwood, Miller, Alexandra A., Therrien, William J., and Lloyd, John W.
- Abstract
Researchers studying curriculum-based measurement of written expression have used a variety of writing prompt types and durations when establishing criterion validity of these tools. The purpose of this study was to determine through meta-analytic procedures whether any prompt type or duration was superior to others in terms of criterion validity. The literature search returned 24 articles (N = 24) that met our inclusion criteria. Included studies examined criterion validity for a variety of prompts: picture, story starters, expository, text copying, picture-word, and picture-story. These studies also reported criterion validity for writing durations ranging from 1.5 to 10 minutes. Results indicated no clear trends in criterion validity for prompt or duration. We provide suggestions for practitioners considering the use of CBM in written expression.
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- 2021
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38. A comparative analysis of 12 intraocular lens power formulas
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Pereira, Austin, Popovic, Marko M., Ahmed, Yusuf, Lloyd, John C., El-Defrawy, Sherif, Gorfinkel, John, and Schlenker, Matthew B.
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- 2021
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39. The Land Rover “Guest experience” marketing concept
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Lloyd, John
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- 2021
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40. Symptomology following mRNA vaccination against SARS-CoV-2
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Ebinger, Joseph E., Lan, Roy, Sun, Nancy, Wu, Min, Joung, Sandy, Botwin, Gregory J., Botting, Patrick, Al-Amili, Daniah, Aronow, Harriet, Beekley, James, Coleman, Bernice, Contreras, Sandra, Cozen, Wendy, Davis, Jennifer, Debbas, Philip, Diaz, Jacqueline, Driver, Matthew, Fert-Bober, Justyna, Gu, Quanquan, Heath, Mallory, Herrera, Ergueen, Hoang, Amy, Hussain, Shehnaz K., Huynh, Carissa, Kim, Linda, Kittleson, Michelle, Liu, Yunxian, Lloyd, John, Luong, Eric, Malladi, Bhavya, Merchant, Akil, Merin, Noah, Mujukian, Angela, Nguyen, Nathalie, Nguyen, Trevor-Trung, Pozdnyakova, Valeriya, Rashid, Mohamad, Raedschelders, Koen, Reckamp, Karen L., Rhoades, Kylie, Sternbach, Sarah, Vallejo, Rocío, White, Shane, Tompkins, Rose, Wong, Melissa, Arditi, Moshe, Figueiredo, Jane C., Van Eyk, Jennifer E., Miles, Peggy B., Chavira, Cynthia, Shane, Rita, Sobhani, Kimia, Melmed, Gil Y., McGovern, Dermot P.B., Braun, Jonathan G., Cheng, Susan, and Minissian, Margo B.
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- 2021
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41. Child health in the UK : we need to help children survive and thrive
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Craig, Michael and Lloyd, John
- Published
- 2020
42. Q&A : Scotland’s independence radicals
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Haggerty, Angela and Lloyd, John
- Published
- 2019
43. Will the Scots take the lone road?
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Lloyd, John
- Published
- 2019
44. Obesity epidemic : bold and decisive action needed
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Watson, Michael Craig and Lloyd, John
- Published
- 2019
45. Building Better Outcomes.
- Author
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Lloyd, John
- Subjects
- *
MILITARY readiness , *EMERGENCY management , *ECOLOGICAL resilience - Abstract
The article focuses on the critical role of the U.S. Army Corps of Engineers, North Atlantic Division, in enhancing military readiness and effectiveness. Topics include their efforts in infrastructure development to support Army lethality, the division's role in strategic mobility and emergency response, and their contributions to global defense operations and resilience.
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- 2024
46. Professional Development in Practice: Improving Novice Teachers' Use of Universal Classroom Management
- Author
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Hirsch, Shanna E., Lloyd, John Wills, and Kennedy, Michael J.
- Abstract
Employing universal classroom management practices (e.g., opportunities to respond, praise, precorrect) can reduce disruptive behavior and improve academic engagement for students with and without disabilities; however, novice educators often possess minimal knowledge of universal classroom management practices. This study examined the effect of a strategically designed professional development workshop on universal classroom management practices with 6 elementary teachers during their first 3 years of teaching. Using a multiple-baseline design across groups of teachers, results indicated that a program of professional development increased teachers' practice and decreased reprimands. Descriptive data revealed changes in teacher knowledge and student engagement. Implications for future research as well as novice teacher professional development are discussed.
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- 2019
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47. Preoperative measurements for cataract surgery: a comparison of ultrasound and optical biometric devices
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Pereira, Austin, Popovic, Marko, Lloyd, John C., El-Defrawy, Sherif, and Schlenker, Matthew B.
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- 2021
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48. A simple and cost-effective protocol for high-yield expression of deuterated and selectively isoleucine/leucine/valine methyl protonated proteins in Escherichia coli grown in shaker flasks
- Author
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Cai, Mengli, Huang, Ying, Lloyd, John, Craigie, Robert, and Clore, G. Marius
- Published
- 2021
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49. Pose-and-shear-based tactile servoing.
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Lloyd, John and Lepora, Nathan F.
- Subjects
- *
CONVOLUTIONAL neural networks , *ROBOT motion , *ROBOT hands , *LIE groups , *ROBOT kinematics , *OBJECT manipulation - Abstract
Tactile servoing is an important technique because it enables robots to manipulate objects with precision and accuracy while adapting to changes in their environments in real-time. One approach for tactile servo control with high-resolution soft tactile sensors is to estimate the contact pose relative to an object surface using a convolutional neural network (CNN) for use as a feedback signal. In this paper, we investigate how the surface pose estimation model can be extended to include shear, and utilise these combined pose-and-shear models to develop a tactile robotic system that can be programmed for diverse non-prehensile manipulation tasks, such as object tracking, surface-following, single-arm object pushing and dual-arm object pushing. In doing this, two technical challenges had to be overcome. Firstly, the use of tactile data that includes shear-induced slippage can lead to error-prone estimates unsuitable for accurate control, and so we modified the CNN into a Gaussian-density neural network and used a discriminative Bayesian filter to improve the predictions with a state dynamics model that utilises the robot kinematics. Secondly, to achieve smooth robot motion in 3D space while interacting with objects, we used SE (3) velocity-based servo control, which required re-deriving the Bayesian filter update equations using Lie group theory, as many standard assumptions do not hold for state variables defined on non-Euclidean manifolds. In future, we believe that pose-and-shear-based tactile servoing will enable many object manipulation tasks and the fully-dexterous utilisation of multi-fingered tactile robot hands. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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50. New Techniques for Combined FEM-Multibody Anatomical Simulation
- Author
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Lloyd, John E., Sánchez, Antonio, Widing, Erik, Stavness, Ian, Fels, Sidney, Niroomandi, Siamak, Perrier, Antoine, Payan, Yohan, Perrier, Pascal, Tavares, João Manuel R. S., Series Editor, Jorge, Renato Natal, Series Editor, and Fernandes, Paulo Rui, editor
- Published
- 2019
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