Point-cloud Transformer for Three-dimensional Electrical Impedance Tomography

Electrical impedance tomography (EIT) is an emerging medical imaging modality that offers nonintrusive, label-free, fast, and portable features. However, the three-dimensional (3-D) EIT image reconstruction problem is thwarted by its high dimensionality and nonlinearity, thus suffering from low image quality. This article proposes a novel algorithm named point-cloud transformer for 3-D EIT image reconstruction (ptEIT) to tackle the challenges of 3-D EIT image reconstruction. ptEIT leverages the nonlinear representation ability of deep learning and effectively addresses the computational cost issue by using irregular-grid representation of the 3-D conductivity distribution in point clouds. The permutation invariant property rooted in the self-attention operator makes ptEIT particularly suitable for processing this type of data, and the objectwise chamfer distance (OWCD) effectively solves the mean-shaped behavior problem encountered in reconstructing multiple objects. Our experimental results demonstrate that ptEIT can simultaneously achieve high accuracy, spatial resolution, and visual quality, outperforming the state-of-the-art 3-D EIT image reconstruction approaches. ptEIT also offers the unique feature of variable resolution and demonstrates strong generalization ability toward different noise levels, showing evident superiority over voxel-based 3-D EIT approaches

Touch and deformation perception of soft manipulators with capacitive e-skins and deep learning

Tactile sensing in soft robots remains particularly challenging because of the coupling between contact and deformation information which the sensor is subject to during actuation and interaction with the environment. This often results in severe interference and makes disentangling tactile sensing and geometric deformation difficult. To address this problem, this paper proposes a soft capacitive e-skin with a sparse electrode distribution and deep learning for information decoupling. Our approach successfully separates tactile sensing from geometric deformation, enabling touch recognition on a soft pneumatic actuator subject to both internal (actuation) and external (manual handling) forces. Using a multi-layer perceptron, the proposed e-skin achieves 99.88\% accuracy in touch recognition across a range of deformations. When complemented with prior knowledge, a transformer-based architecture effectively tracks the deformation of the soft actuator. The average distance error in positional reconstruction of the manipulator is as low as 2.905$\pm$2.207 mm, even under operative conditions with different inflation states and physical contacts which lead to additional signal variations and consequently interfere with deformation tracking. These findings represent a tangible way forward in the development of e-skins that can endow soft robots with proprioception and exteroception

Coordination of transcription-coupled repair and repair-independent release of lesion-stalled RNA polymerase II.

Transcription-blocking lesions (TBLs) stall elongating RNA polymerase II (Pol II), which then initiates transcription-coupled repair (TCR) to remove TBLs and allow transcription recovery. In the absence of TCR, eviction of lesion-stalled Pol II is required for alternative pathways to address the damage, but the mechanism is unclear. Using Protein-Associated DNA Damage Sequencing (PADD-seq), this study reveals that the p97-proteasome pathway can evict lesion-stalled Pol II independently of repair. Both TCR and repair-independent eviction require CSA and ubiquitination. However, p97 is dispensable for TCR and Pol II eviction in TCR-proficient cells, highlighting repairs prioritization over repair-independent eviction. Moreover, ubiquitination of RPB1-K1268 is important for both pathways, with USP7s deubiquitinase activity promoting TCR without abolishing repair-independent Pol II release. In summary, this study elucidates the fate of lesion-stalled Pol II, and may shed light on the molecular basis of genetic diseases caused by the defects of TCR genes

Structural, Elastic, Electronic and Optical Properties of a New Layered-Ternary Ta4SiC3 Compound

We propose a new layered-ternary Ta4SiC3 with two different stacking sequences ({\alpha}- and {\beta}-phases) of the metal atoms along c axis and study their structural stability. The mechanical, electronic and optical properties are then calculated and compared with those of other compounds M4AX3 (M = V, Nb, Ta; A = Al, Si and X = C). The predicted compound in the {\alpha}-phase is found to possess higher hardness than any of these compounds. The independent elastic constants of the two phases are also evaluated and the results discussed. The electronic band structures for {\alpha}- and {\beta}-Ta4SiC3 show metallic conductivity. Ta 5d electrons are mainly contributing to the total density of states (DOS). We see that the hybridization peak of Ta 5d and C 2p lies lower in energy and the Ta 5d-C 2p bond is stronger than Ta 5d-Si 3p bond. Further an analysis of the different optical properties shows the compound to possess improved behavior compared to similar types of compounds.Comment: 9 pages, 5 figures; PACS: 60.20.Dc; 62.20.-x; 71.15.Mb; 78.20.Ci; Keywords: Ta4SiC3, First-principles; Elastic properties; Electronic properties; Optical propertie