Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning

Masked autoencoder has demonstrated its effectiveness in self-supervised point cloud learning. Considering that masking is a kind of corruption, in this work we explore a more general denoising autoencoder for point cloud learning (Point-DAE) by investigating more types of corruptions beyond masking. Specifically, we degrade the point cloud with certain corruptions as input, and learn an encoder-decoder model to reconstruct the original point cloud from its corrupted version. Three corruption families (\ie, density/masking, noise, and affine transformation) and a total of fourteen corruption types are investigated with traditional non-Transformer encoders. Besides the popular masking corruption, we identify another effective corruption family, \ie, affine transformation. The affine transformation disturbs all points globally, which is complementary to the masking corruption where some local regions are dropped. We also validate the effectiveness of affine transformation corruption with the Transformer backbones, where we decompose the reconstruction of the complete point cloud into the reconstructions of detailed local patches and rough global shape, alleviating the position leakage problem in the reconstruction. Extensive experiments on tasks of object classification, few-shot learning, robustness testing, part segmentation, and 3D object detection validate the effectiveness of the proposed method. The codes are available at \url{https://github.com/YBZh/Point-DAE}.Comment: The codes are available at \url{https://github.com/YBZh/Point-DAE

Dicylopenta­dien­yl[4-(4-vinyl­benz­yloxy)pyridine-2,6-dicarboxyl­ato]titanium(IV) monohydrate

The title compound, [Ti(C5H5)2(C16H11NO5)]·H2O, exhibits a titanocene unit coordinated to a styrene-substituted pyridine-2,6-dicarboxyl­ate ligand synthesized for use as a monomer for polymerization or copolymerization yielding metallocene-containing polymers. The compound crystallized as a monohydrate and the solvent water mol­ecule forms strong O—H⋯O hydrogen bonds with the carboxyl­ate O atoms of the Ti complex, which play an important role in the connection of adjacent mol­ecules. In addition, weak inter­molecular C—H⋯O hydrogen bonds also contribute to the crystal packing arrangement

Masked Surfel Prediction for Self-Supervised Point Cloud Learning

Masked auto-encoding is a popular and effective self-supervised learning approach to point cloud learning. However, most of the existing methods reconstruct only the masked points and overlook the local geometry information, which is also important to understand the point cloud data. In this work, we make the first attempt, to the best of our knowledge, to consider the local geometry information explicitly into the masked auto-encoding, and propose a novel Masked Surfel Prediction (MaskSurf) method. Specifically, given the input point cloud masked at a high ratio, we learn a transformer-based encoder-decoder network to estimate the underlying masked surfels by simultaneously predicting the surfel positions (i.e., points) and per-surfel orientations (i.e., normals). The predictions of points and normals are supervised by the Chamfer Distance and a newly introduced Position-Indexed Normal Distance in a set-to-set manner. Our MaskSurf is validated on six downstream tasks under three fine-tuning strategies. In particular, MaskSurf outperforms its closest competitor, Point-MAE, by 1.2\% on the real-world dataset of ScanObjectNN under the OBJ-BG setting, justifying the advantages of masked surfel prediction over masked point cloud reconstruction. Codes will be available at https://github.com/YBZh/MaskSurf.Comment: Codes will be available at https://github.com/YBZh/MaskSur

MoS2/TiO2 van der Waals heterostructures for promising photocatalytic performance: a first-principles study

Heterostructures have attracted extensive attention due to their van der Waals interactions between layers. The photocatalysts of Two-dimensional (2D) heterostructure based on MoS _2 have tempted more and more attention because of their eminent photocatalytic performance, but they are still limited by the weak absorption of visible light and lesser conversion efficiency of solar-to-hydrogen. In this work, we exhaustively investigate the electronic, optical and the structural properties of 2D MoS _2 /TiO _2 heterostructures by using first-principles calculations. The result shows that both MoS _2 /TiO _2 (100) and MoS _2 /TiO _2 (001) heterostructures are stable interfaces and direct Z-scheme photocatalysts, which is favourable for the separation and migration of electron and hole pairs under the excitation of light. And what’s more, both the MoS _2 /TiO _2 (100) and MoS _2 /TiO _2 (001) heterostructures exhibit direct band gap at the Γ point, this is conductive to better electronic transition and absorption of light because of lower energy depletion than indirect band gap semiconductors. The relatively small band gap (1.08 eV of MoS _2 /TiO _2 (001) and 0.52 eV of MoS _2 /TiO _2 (100)) cause the entire visible light region can be covered by the light absorption spectrum. The result is that building heterostructures of TiO _2 with MoS _2 advances the absorption of light and hastens the separation and migration of electron and hole pairs, the activity of photocatalysis could be advanced by all of these. The results provide a basis of heterostructure photocatalysts based on monolayer MoS _2 and deep comprehension of their physical mechanism

Preparation and Perfomance of an Aging-Resistant Nanocomposite Film of Binary Natural Polymer–Graphene Oxide

As one of the materials having a bionic structure, nacrelike layered composites, inspired by their natural hybrid structures, have been studied via a variety of approaches. Graphene oxide (GO), which differed from inert graphene, was used as a new building block because it could be readily chemically functionalized. Rather than natural polymers, synthetic polymers were most commonly used to fabricate nacrelike GO–polymer materials. However, naturally occurring polymers complied more easily with the requirements of biocompatibility, biodegradability, and nontoxicity. Here, a simple solution-casting method was used to mimic natural nacre and fabricate a self-assembled and aging-resistant binary natural polymer, (κ-carrageenan (κ-CAR)–Konjac glucomannan (KGM))–GO nanocomposites, with varying GO concentrations. The investigation results revealed that κ-CAR–KGM and GO mostly self-assemble via the formation of intermolecular hydrogen bonds to form a well-defined layered structure. The mechanical properties of the natural polymer–GO films were improved significantly compared to those of pure natural polymer films. With the addition of 7.5 wt % GO, the tensile strength (TS) and Young’s modulus were found to increase by 129.5 and 491.5%, respectively. In addition, the composite films demonstrated high reliability and aging resistance as well as a definite TS after cold and hot shock and ozone aging tests, especially showing a superior ozone resistance. The composite films can potentially be used as biomaterials or packing materials

External Quality Assessment for the Detection of Measles Virus by Reverse Transcription-PCR Using Armored RNA.

In recent years, nucleic acid tests for detection of measles virus RNA have been widely applied in laboratories belonging to the measles surveillance system of China. An external quality assessment program was established by the National Center for Clinical Laboratories to evaluate the performance of nucleic acid tests for measles virus. The external quality assessment panel, which consisted of 10 specimens, was prepared using armored RNAs, complex of noninfectious MS2 bacteriophage coat proteins encapsulated RNA of measles virus, as measles virus surrogate controls. Conserved sequences amplified from a circulating measles virus strain or from a vaccine strain were encapsulated into these armored RNAs. Forty-one participating laboratories from 15 provinces, municipalities, or autonomous regions that currently conduct molecular detection of measles virus enrolled in the external quality assessment program, including 40 measles surveillance system laboratories and one diagnostic reagent manufacturer. Forty laboratories used commercial reverse transcription-quantitative PCR kits, with only one laboratory applying a conventional PCR method developed in-house. The results indicated that most of the participants (38/41, 92.7%) were able to accurately detect the panel with 100% sensitivity and 100% specificity. Although a wide range of commercially available kits for nucleic acid extraction and reverse transcription polymerase chain reaction were used by the participants, only two false-negative results and one false-positive result were generated; these were generated by three separate laboratories. Both false-negative results were obtained with tests performed on specimens with the lowest concentration (1.2 × 104 genomic equivalents/mL). In addition, all 18 participants from Beijing achieved 100% sensitivity and 100% specificity. Overall, we conclude that the majority of the laboratories evaluated have reliable diagnostic capacities for the detection of measles virus

Composition of the EQA panel and qRT-PCR results.

<p>Composition of the EQA panel and qRT-PCR results.</p