Weakly Supervised Learning Method for Semantic Segmentation of Large-Scale 3D Point Cloud Based on Transformers

Nowadays, semantic segmentation results of 3D point cloud have been widely applied in the fields of robotics, autonomous driving, and augmented reality etc. Thanks to the development of relevant deep learning models (such as PointNet), supervised training methods have become hotspot, in which two common limitations exists: inferior feature representation of 3D points and massive annotations. To improve 3D point feature, inspired by the idea of transformer, we employ a so-call LCP network that extracts better feature by investigating attentions between target 3D points and its corresponding local neighbors via local context propagation. Training transformer-based network needs amount of training samples, which itself is a labor-intensive, costly and error-prone work, therefore, this work proposes a weakly supervised framework, in particular, pseudo-labels are estimated based on the feature distances between unlabeled points and prototypes, which are calculated based on labeled data. The extensive experimental results show that, the proposed PL-LCP can yield considerable results (67.6% mIOU for indoor and 67.3% for outdoor) even if only using 1% real labels, and comparing to several state-of-the-art method using all labels, we achieve superior results in mIOU, OA for indoor (65.9%, 89.2%)

Mega-NeRF++: An Improved Scalable NeRFs for High-resolution Photogrammetric Images

Over the last few years, implicit 3D representation has attracted more and more research endeavors, typified by the so-called Neural Radiance Fields (NeRF). The original NeRF and some relevant variants mostly address on small-scale scene (such as, indoor or tiny toys), which already show good novel views rendering results. It still remains challenging when dealing with wide coverage area that is captured by large number of high-resolution images, the time efficiency and rendering quality is generally limited. To cope with large-scale scenario, recently, Mega-NeRF was proposed to divide the area into several overlapping sub-area and train corresponding sub-NeRFs, respectively. Mega-NeRF adopts the method of parallel training of multiple sub-modules, which means sub-modules are absolutely independent of each other, which might in principle not be an optimal solution, as two sub-NeRFs of adjacent sub-models obtained by parallel training are likely to get different rendering results for the overlapping area, and the final rendering result is supposed to be negative affected. Therefore, we present Mega-NeRF++, and our goal is to improve Mega-NeRF by implementing extra sub-models optimization that alleviate the rendering discrepancy of overlapping sub-NeRFs. More specifically, we further fine tune the original Mega-NeRFs by considering the consistency of adjacent overlapping area, which means the training data used in the optimization are only from the overlapping region, and we also proposed a novel loss, so that it not only takes into account the difference between the prediction of each sub-model and the true value, but also considers the consistency of the predicted results between various adjacent sub-modules in the overlapping region. The experimental results show that, for the overlapping area, our Mega-NeRF++ can qualitatively render better images with higher fidelity and quantitively have higher PNSR and SSIM compare to original Mega-NeRF

Application of nanopore adaptive sequencing in pathogen detection of a patient with Chlamydia psittaci infection

IntroductionNanopore sequencing has been widely used in clinical metagenomic sequencing for pathogen detection with high portability and real-time sequencing. Oxford Nanopore Technologies has recently launched an adaptive sequencing function, which can enrich on-target reads through real-time alignment and eject uninteresting reads by reversing the voltage across the nanopore. Here we evaluated the utility of adaptive sequencing in clinical pathogen detection.MethodsNanopore adaptive sequencing and standard sequencing was performed on a same flow cell with a bronchoalveolar lavage fluid sample from a patient with Chlamydia psittacosis infection, and was compared with the previous mNGS results.ResultsNanopore adaptive sequencing identified 648 on-target stop receiving reads with the longest median read length(688bp), which account for 72.4% of all Chlamydia psittaci reads and 0.03% of total reads in enriched group. The read proportion matched to C. psittaci in the stop receiving group was 99.85%, which was much higher than that of the unblock (<0.01%) and fail to adapt (0.02%) groups. Nanopore adaptive sequencing generated similar data yield of C. psittaci compared with standard nanopore sequencing. The proportion of C. psittaci reads in adaptive sequencing is close to that of standard nanopore sequencing and mNGS, but generated lower genome coverage than mNGS.DiscussionNanopore adaptive sequencing can effectively identify target C. psittaci reads in real-time, but how to increase the targeted data of pathogens still needs to be further evaluated

Characteristics of the electrical explosion of fine metallic wires in vacuum

The experimental investigations on the electrical explosion of aluminum, silver, tungsten and platinum wires are carried out. The dependence of the parameters related to the specific energy deposition on the primary material properties is investigated. The polyimide coatings are applied to enhance the energy deposition for the exploding wires with percent of vaporized energy less than unit. The characteristics of the exploding wires of different materials with and without insulating coatings are studied. The effect of wire length on the percent of vaporization energy for exploding coated wires is presented. A laser probe is employed to construct the shadowgraphy, schlieren and interferometry diagnostics. The optical diagnostics demonstrate the morphology of the exploding products and structure of the energy deposition. The influence of insulating coatings on different wire materials is analyzed. The expansion trajectories of the exploding wires without and with insulating coatings are estimated from the shadowgram. More specific energy is deposited into the coated wires of shorter wire length, leading to faster expanding velocity of the high-density products

One-Step Quaternization/Hydroxypropylsulfonation to Improve Paste Stability, Adhesion, and Film Properties of Oxidized Starch

To investigate the influences of quaternization/hydroxypropylsulfonation on viscosity stability, adhesion to fibers and film properties of oxidized tapioca starch (OTS) for ameliorating its end-use ability in applications such as warp-sizing and paper-making, a series of quaternized and hydroxypropylsulfonated OTS (QHOTS) samples were synthesized by simultaneous quaternization and hydroxypropylsulfonation of OTS with N-(3-chloro-2-hydroxypropyl) trimethylammonium chloride (CHPTAC) and 3-chloro-2-hydroxy-1-propanesulfonic acid sodium salt (CHPS-Na). The QHOTS granules were characterized by Fourier transform infra-red spectroscopic and scanning electron microscope techniques. Apparent viscosity and viscosity stability were determined, and adhesion was evaluated by measuring the bonding force of starch to the fibers. Film properties were also estimated in terms of tensile strength, breaking elongation, bending endurance, degree of crystallinity, and moisture regain. It was showed that quaternization/hydroxypropylsulfonation was capable of obviously improving viscosity stability of gelatinized OTS paste, enhancing bonding forces of OTS to cotton and polylactic acid (PLA) fibers, increasing breaking elongation, bending endurance and moisture regain of film and decreasing its tensile strength and degree of crystallinity, thereby obviously stabilizing paste viscosity, improving adhesion to fibers and lessening film brittleness. Increasing the level of quaternization/hydroxypropylsulfonation favored improvement in the stability, enhancement in adhesion and decrease in brittleness. The QHOTS showed potential in the applications of cotton and PLA sizing

A Highly Breathable and Machine-Washable ePTFE-Aided Down-Proof Cotton Fabric

Feather and down textiles are widely used in our daily life, especially in winter. However, they are easily drilled out from the fabric body and are difficult to machine-wash, which thereby blocks their widespread application. In order to solve these issues, a highly anti-drilling, breathable and machine-washable ePTFE-aided down-proof cotton fabric was prepared in this work, which was done by modifying a plain-weave cotton fabric with expanded polytetrafluoroethylene (ePTFE) nanofiber membrane via point glue method. The fabrication procedure is simple, scalable and environmentally friendly, which is a prerequisite for large-scale production. The effects of tumble and washing cycles on pore size distribution and the corresponding anti-drilling behavior of the prepared down-proof fabric were systematically investigated. Furthermore, the machine washability, air permeability, thermal insulation and tensile properties of the fabric were studied. The results demonstrated that less than five drilled files escaped from the fabric surface, irrespective of tumble and/or laundering cycles, and it also has the advantages of being lightweight (<83 g/m2), having high breathability, a good thermal insulation rate (≈80%) and can be washed with surfactant by a laundry machine without explosion. Benefiting from the above characteristics, the as-prepared ePTFE-aided down-proof cotton fabric presents its potential application in the field of home textiles

Continuous, Strong, Porous Silk Firoin-Based Aerogel Fibers toward Textile Thermal Insulation

Aerogel fiber, with the characteristics of ultra-low density, ultra-high porosity, and high specific surface area, is the most potential candidate for manufacturing wearable thermal insulation material. However, aerogel fibers generally show weak mechanical properties and complex preparation processes. Herein, through firstly preparing a cellulose acetate/polyacrylic acid (CA/PAA) hollow fiber using coaxial wet-spinning followed by injecting the silk fibroin (SF) solution into the hollow fiber, the CA/PAA-wrapped SF aerogel fibers toward textile thermal insulation were successfully constructed after freeze-drying. The sheath (CA/PAA hollow fiber) possesses a multiscale porous structure, including micropores (11.37 ± 4.01 μm), sub-micron pores (217.47 ± 46.16 nm), as well as nanopores on the inner (44.00 ± 21.65 nm) and outer (36.43 ± 17.55 nm) surfaces, which is crucial to the formation of a SF aerogel core. Furthermore, the porous CA/PAA-wrapped SF aerogel fibers have many advantages, such as low density (0.21 g/cm3), high porosity (86%), high strength at break (2.6 ± 0.4 MPa), as well as potential continuous and large-scale production. The delicate structure of multiscale porous sheath and ultra-low-density SF aerogel core synergistically inhibit air circulation and limit convective heat transfer. Meanwhile, the high porosity of aerogel fibers weakens heat transfer and the SF aerogel cellular walls prevent infrared radiation. The results show that the mat composed of these aerogel fibers exhibits excellent thermal insulating properties with a wide working temperature from −20 to 100 °C. Therefore, this SF-based aerogel fiber can be considered as a practical option for high performance thermal insulation

Circular RNAs in atrial fibrillation: From bioinformatics analysis of circRNA-miRNA-mRNA network to serum expression

Atrial fibrillation (AF) is a common arrhythmia in clinical practice, and its incidence is increasing year by year, which seriously affects the survival and prognosis of patients. In recent years, circRNAs has played an important role in the diagnosis and treatment of AF. The purpose of this study was to search for differentially expressed circRNAs(DEcircRNAs) in the serum of AF patients by analyzing the expression profile of existing chips, combining bioinformatics technology and in vitro experiments, and to explore the regulatory mechanism of circRNAs in the occurrence and development of AF. By using the AF datasets in the Gene expression omnibus (GEO) database, serum samples of patients with AF were collected, and the expression level of selected circRNAs was verified by qPCR. We found that the expression of four circRNAs was increased in the serum of patients with AF, suggesting that these four DEcircRNAs may be used as auxiliary diagnostic markers for AF. Bioinformatics predicts the related signaling pathways that differentially expressed genes may regulate in the occurrence and development of AF, providing a new theoretical basis for the molecular mechanism of the occurrence of atrial fibrillation and auxiliary diagnostic targets