Sequential Dexterity: Chaining Dexterous Policies for Long-Horizon Manipulation

Many real-world manipulation tasks consist of a series of subtasks that are significantly different from one another. Such long-horizon, complex tasks highlight the potential of dexterous hands, which possess adaptability and versatility, capable of seamlessly transitioning between different modes of functionality without the need for re-grasping or external tools. However, the challenges arise due to the high-dimensional action space of dexterous hand and complex compositional dynamics of the long-horizon tasks. We present Sequential Dexterity, a general system based on reinforcement learning (RL) that chains multiple dexterous policies for achieving long-horizon task goals. The core of the system is a transition feasibility function that progressively finetunes the sub-policies for enhancing chaining success rate, while also enables autonomous policy-switching for recovery from failures and bypassing redundant stages. Despite being trained only in simulation with a few task objects, our system demonstrates generalization capability to novel object shapes and is able to zero-shot transfer to a real-world robot equipped with a dexterous hand. More details and video results could be found at https://sequential-dexterity.github.ioComment: CoRL 202

Dynamic Handover: Throw and Catch with Bimanual Hands

Humans throw and catch objects all the time. However, such a seemingly common skill introduces a lot of challenges for robots to achieve: The robots need to operate such dynamic actions at high-speed, collaborate precisely, and interact with diverse objects. In this paper, we design a system with two multi-finger hands attached to robot arms to solve this problem. We train our system using Multi-Agent Reinforcement Learning in simulation and perform Sim2Real transfer to deploy on the real robots. To overcome the Sim2Real gap, we provide multiple novel algorithm designs including learning a trajectory prediction model for the object. Such a model can help the robot catcher has a real-time estimation of where the object will be heading, and then react accordingly. We conduct our experiments with multiple objects in the real-world system, and show significant improvements over multiple baselines. Our project page is available at \url{https://binghao-huang.github.io/dynamic_handover/}.Comment: Accepted at CoRL 2023. https://binghao-huang.github.io/dynamic_handover

Trojan Horse nanotheranostics with dual transformability and multifunctionality for highly effective cancer treatment.

Nanotheranostics with integrated diagnostic and therapeutic functions show exciting potentials towards precision nanomedicine. However, targeted delivery of nanotheranostics is hindered by several biological barriers. Here, we report the development of a dual size/charge- transformable, Trojan-Horse nanoparticle (pPhD NP) for delivery of ultra-small, full active pharmaceutical ingredients (API) nanotheranostics with integrated dual-modal imaging and trimodal therapeutic functions. pPhD NPs exhibit ideal size and charge for drug transportation. In tumour microenvironment, pPhD NPs responsively transform to full API nanotheranostics with ultra-small size and higher surface charge, which dramatically facilitate the tumour penetration and cell internalisation. pPhD NPs enable visualisation of biodistribution by near-infrared fluorescence imaging, tumour accumulation and therapeutic effect by magnetic resonance imaging. Moreover, the synergistic photothermal-, photodynamic- and chemo-therapies achieve a 100% complete cure rate on both subcutaneous and orthotopic oral cancer models. This nanoplatform with powerful delivery efficiency and versatile theranostic functions shows enormous potentials to improve cancer treatment

Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation. Thanks to its impressive capabilities in all-round segmentation tasks and its prompt-based interface, SAM has sparked intensive discussion within the community. It is even said by many prestigious experts that image segmentation task has been "finished" by SAM. However, medical image segmentation, although an important branch of the image segmentation family, seems not to be included in the scope of Segmenting "Anything". Many individual experiments and recent studies have shown that SAM performs subpar in medical image segmentation. A natural question is how to find the missing piece of the puzzle to extend the strong segmentation capability of SAM to medical image segmentation. In this paper, instead of fine-tuning the SAM model, we propose Med SAM Adapter, which integrates the medical specific domain knowledge to the segmentation model, by a simple yet effective adaptation technique. Although this work is still one of a few to transfer the popular NLP technique Adapter to computer vision cases, this simple implementation shows surprisingly good performance on medical image segmentation. A medical image adapted SAM, which we have dubbed Medical SAM Adapter (MSA), shows superior performance on 19 medical image segmentation tasks with various image modalities including CT, MRI, ultrasound image, fundus image, and dermoscopic images. MSA outperforms a wide range of state-of-the-art (SOTA) medical image segmentation methods, such as nnUNet, TransUNet, UNetr, MedSegDiff, and also outperforms the fully fine-turned MedSAM with a considerable performance gap. Code will be released at: https://github.com/WuJunde/Medical-SAM-Adapter

On the Circular Polarisation of Repeating Fast Radio Bursts

Fast spinning (e.g., sub-second) neutron star with ultra-strong magnetic fields (or so-called magnetar) is one of the promising origins of repeating fast radio bursts (FRBs). Here we discuss circularly polarised emissions produced by propagation effects in the magnetosphere of fast spinning magnetars. We argue that the polarisation-limiting region is well beyond the light cylinder, suggesting that wave mode coupling effects are unlikely to produce strong circular polarisation for fast spinning magnetars. Cyclotron absorption could be significant if the secondary plasma density is high. However, high degrees of circular polarisation can only be produced with large asymmetries in electrons and positrons. We draw attention to the non-detection of circular polarisation in current observations of known repeating FRBs. We suggest that the circular polarisation of FRBs could provide key information on their origins and help distinguish different radiation mechanisms.Comment: ApJ accepte

Combined detection of PAX1 methylation and p16/Ki-67 dual staining improves diagnostic performance for atypical squamous cells in cervical cancer

Objective To compare paired boxed gene 1(PAX1) methylation and p16/Ki-67 double staining alone and in combination in thinprep cytologic test (TCT) for distinguishing atypical squamous cells of undetermined significance (ASC-US) and low-grade squamous intraepithelial lesion (LSIL) population. Methods A total of 247 patients with TCT results of ASC-US and LSIL admitted in our hospital from January 2021 to December 2022 were enrolled in this study.Detection efficacy of PAX1 methylation and p16/Ki-67 double staining alone and in combination was evaluated with colposcopic pathologic results as the gold standard and the sensitivity, specificity, accuracy and area under the curve (AUC) as evaluation indexes. Results The positive rates of PAX1 methylation and p16/Ki-67 double staining were increased with the severity of pathological findings.Combined detection of PAX1 methylation and p16/Ki-67 assay had a sensitivity of 91.25%, specificity of 97.72% and accuracy of 95.51% in the women with TCT of ASC-US, and these values were statistically better than those of PAX1 methylation and p16/Ki-67 double staining alone (P < 0.01). Conclusion The combination of PAX1 methylation and p16/Ki-67 double-staining assay can further improve the diagnostic efficacy in patients with ASC-US on TCT results

Microstructure Evolution and Properties Induced by Multi-Pass Drawing of Graphene/Copper Nanocomposite

The influence of multi-pass cold drawing on the evolution of microstructure, texture, and properties of Cu matrix composite, reinforced by in situ grown graphene, has been systematically investigated. Under continuous and severe plastic deformation, the grains in the composite were continuously refined to nanoscale. In addition, graphene in the composite could be gradually refined, exfoliated, and redispersed. Interestingly, dynamic recrystallization of the composite was formed after 80% drawing reduction and its formation mechanism was discussed. The texture of the as-drawn composite comprised a mixture of fiber textures with dominated &lt;111&gt; and minor &lt;100&gt; orientation after 99.7% severe drawing reduction. The tensile properties and electrical conductivity of the as-drawn composites were also investigated. This work provides a better guideline on the plastic deformation behavior of the advanced graphene/metal nanocomposite

Impact Mechanism of the Urban Network on Carbon Emissions in Rapidly Developing Regions: Example of 47 Cities in Southwest China

Southwest China faces harsh environmental pollution challenges and rapid development. Against this backdrop, exploring the impact mechanism of the urban network on carbon emissions in rapidly developing regions is of great significance to the balance between regional development and carbon emissions reduction, as well as regional sustainable development. The objective of this study is to quantify the relationship between carbon emissions and the urban network, using panel data analysis for 47 cities in southwest China from 2010 to 2019. Therefore, several urban network indices were selected and quantitatively studied by using the spatial Durbin model to reveal the impact mechanism of the urban network on carbon emissions in rapidly developing regions. The results show that: (1) the growth of carbon emissions in a city has a significant positive spatial spillover effect on the surrounding areas; (2) the temporal and spatial distribution of carbon emissions is highly coincident with the urban network; (3) the urban network has a two-sided impact mechanism of promoting and inhibiting carbon emissions; and (4) the effect of the impact mechanism is affected by regional development conditions, and the promotion effect plays the main role in rapidly developing regions