A Multi-Robot Cooperation Framework for Sewing Personalized Stent Grafts

This paper presents a multi-robot system for manufacturing personalized medical stent grafts. The proposed system adopts a modular design, which includes: a (personalized) mandrel module, a bimanual sewing module, and a vision module. The mandrel module incorporates the personalized geometry of patients, while the bimanual sewing module adopts a learning-by-demonstration approach to transfer human hand-sewing skills to the robots. The human demonstrations were firstly observed by the vision module and then encoded using a statistical model to generate the reference motion trajectories. During autonomous robot sewing, the vision module plays the role of coordinating multi-robot collaboration. Experiment results show that the robots can adapt to generalized stent designs. The proposed system can also be used for other manipulation tasks, especially for flexible production of customized products and where bimanual or multi-robot cooperation is required.Comment: 10 pages, 12 figures, accepted by IEEE Transactions on Industrial Informatics, Key words: modularity, medical device customization, multi-robot system, robot learning, visual servoing, robot sewin

Dexterous In-Hand Manipulation of Slender Cylindrical Objects through Deep Reinforcement Learning with Tactile Sensing

Continuous in-hand manipulation is an important physical interaction skill, where tactile sensing provides indispensable contact information to enable dexterous manipulation of small objects. This work proposed a framework for end-to-end policy learning with tactile feedback and sim-to-real transfer, which achieved fine in-hand manipulation that controls the pose of a thin cylindrical object, such as a long stick, to track various continuous trajectories through multiple contacts of three fingertips of a dexterous robot hand with tactile sensor arrays. We estimated the central contact position between the stick and each fingertip from the high-dimensional tactile information and showed that the learned policies achieved effective manipulation performance with the processed tactile feedback. The policies were trained with deep reinforcement learning in simulation and successfully transferred to real-world experiments, using coordinated model calibration and domain randomization. We evaluated the effectiveness of tactile information via comparative studies and validated the sim-to-real performance through real-world experiments.Comment: 10 pages, 12 figures, submitted to Transaction on Mechatronic

A modular approach to learning manipulation strategies from human demonstration

Object manipulation is a challenging task for robotics, as the physics involved in object interaction is com- plex and hard to express analytically. Here we introduce a modular approach for learning a manipulation strategy from human demonstration. Firstly we record a human perform- ing a task that requires an adaptive control strategy in differ- ent conditions, i.e. different task contexts. We then perform modular decomposition of the control strategy, using phases of the recorded actions to guide segmentation. Each mod- ule represents a part of the strategy, encoded as a pair of forward and inverse models. All modules contribute to the final control policy; their recommendations are integrated via a system of weighting based on their own estimated er- ror in the current task context. We validate our approach by demonstrating it, both in a simulation for clarity, and on a real robot platform to demonstrate robustness and capacity to generalise. The robot task is opening bottle caps. We show that our approach can modularize an adaptive control strategy and generate appropriate motor commands for the robot to accomplish the complete task, even for novel bottles

Enhanced drug loading capacity of polypyrrole nanowire network for confrolled drug release

For a conducting polymer (CP) based drug release system, drug loading is often accomplished by a doping process, in which drug is incorporated into polymer as dopant. Therefore, the drug loading capacity is relatively low and the range of drugs can be loaded is limited. In the present work, a polypyrrole (PPy) nanowire network is prepared by an electrochemical method and it is found that the micro- and nano- gaps among the individual nanowires of the PPy nanowire network can be used as reservoir to store drugs. Therefore, the drug loading capacity is dependent on the volume of these micro- and nano-vacancies, instead of the doping level. The range of loaded drugs also can be theoretically extended to any drugs, instead of only charged dopants. In fact, it is confirmed here that both hydrophilic and lipophilic drugs can be loaded into the micro- and nano-gaps due to the amphilicity of the PPy nanowire network. As a result, both drug loading capacity and the range of drugs can be loaded are significantly improved. After being covered with a protective PPy film, controlled drug release from the prepared system is achieved by electrical stimulation (cyclic voltammetry, CV) and the amount of drug released can be controlled by changing the scan rate of CV and the thickness of the protective PPy film.Web of Scienc

Mechanotransduction and growth factor signalling to engineer cellular microenvironments

Engineering cellular microenvironments involves biochemical factors, the extracellular matrix (ECM) and the interaction with neighbouring cells. This progress report provides a critical overview of key studies that incorporate growth factor (GF) signalling and mechanotransduction into the design of advanced microenvironments. Materials systems have been developed for surface-bound presentation of GFs, either covalently tethered or sequestered through physico-chemical affinity to the matrix, as an alternative to soluble GFs. Furthermore, some materials contain both GF and integrin binding regions and thereby enable synergistic signalling between the two. Mechanotransduction refers to the ability of the cells to sense physical properties of the ECM and to transduce them into biochemical signals. Various aspects of the physics of the ECM, i.e. stiffness, geometry and ligand spacing, as well as time-dependent properties, such as matrix stiffening, degradability, viscoelasticity, surface mobility as well as spatial patterns and gradients of physical cues are discussed. To conclude, various examples illustrate the potential for cooperative signalling of growth factors and the physical properties of the microenvironment for potential applications in regenerative medicine, cancer research and drug testing

Efficacy and safety of upadacitinib in a randomized trial of patients with Crohn’s disease

Background & Aims: We evaluated the efficacy and safety of upadacitinib, an oral selective Janus kinase 1 inhibitor, in a randomized trial of patients with Crohn's disease (CD). Methods: We performed a double-blind, phase 2 trial in adults with moderate to severe CD and inadequate response or intolerance to immunosuppressants or tumor necrosis factor antagonists. Patients were randomly assigned (1:1:1:1:1:1) to groups given placebo; or 3 mg, 6 mg, 12 mg, or 24 mg upadacitinib twice daily; or 24 mg upadacitinib once daily and were evaluated by ileocolonoscopy at weeks 12 or 16 of the induction period. Patients who completed week 16 were re-randomized to a 36-week period of maintenance therapy with upadacitinib. The primary endpoints were clinical remission at week 16 and endoscopic remission at week 12 or 16 using the multiple comparison procedure and modeling and the Cochran-Mantel-Haenszel test, with a 2-sided level of 10%. Results: Among the 220 patients in the study, clinical remission was achieved by 13% of patients receiving 3 mg upadacitinib, 27% of patients receiving 6 mg upadacitinib (P < .1 vs placebo), 11% of patients receiving 12 mg upadacitinib, and 22% of patients receiving 24 mg upadacitinib twice daily, and by 14% of patients receiving 24 mg upadacitinib once daily, vs 11% of patients receiving placebo. Endoscopic remission was achieved by 10% (P < .1 vs placebo), 8%, 8% (P < .1 vs placebo), 22% (P < .01 vs placebo), and 14% (P < .05 vs placebo) of patients receiving upadacitinib, respectively, vs none of the patients receiving placebo. Endoscopic but not clinical remission increased with dose during the induction period. Efficacy was maintained for most endpoints through week 52. During the induction period, patients in the upadacitinib groups had higher incidences of infections and serious infections vs placebo. Patients in the twice-daily 12 mg and 24 mg upadacitinib groups had significant increases in total, high-density lipoprotein, and low-density lipoprotein cholesterol levels compared with patients in the placebo group. Conclusions: In a phase 2 trial of patients with CD, upadacitinib induced endoscopic remission in a significant proportion of patients compared with placebo. Upadacitinib's benefit/risk profile supports further development for treatment of CD. (Clinicaltrials.gov, Number: NCT02365649

Preparation of Fe3O4Spherical Nanoporous Particles Facilitated by Polyethylene Glycol 4000

Much interest has been attracted to the magnetic materials with porous structure because of their unique properties and potential applications. In this report, Fe3O4nanoporous particles assembled from small Fe3O4nanoparticles have been prepared by thermal decomposition of iron acetylacetonate in the presence of polyethylene glycol 4000. The size of the spherical nanoporous particles is 100–200 nm. Surface area measurement shows that these Fe3O4nanoporous particles have a high surface area of 87.5 m2/g. Magnetization measurement and Mössbauer spectrum indicate that these particles are nearly superparamagnetic at room temperature. It is found that the morphology of the products is greatly influenced by polyethylene glycol concentration and the polymerization degree of polyethylene glycol. Polyethylene glycol molecules are believed to facilitate the formation of the spherical assembly