Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization

Instance segmentation on point clouds is crucially important for 3D scene understanding. Distance clustering is commonly used in state-of-the-art methods (SOTAs), which is typically effective but does not perform well in segmenting adjacent objects with the same semantic label (especially when they share neighboring points). Due to the uneven distribution of offset points, these existing methods can hardly cluster all instance points. To this end, we design a novel divide and conquer strategy and propose an end-to-end network named PBNet that binarizes each point and clusters them separately to segment instances. PBNet divides offset instance points into two categories: high and low density points (HPs vs.LPs), which are then conquered separately. Adjacent objects can be clearly separated by removing LPs, and then be completed and refined by assigning LPs via a neighbor voting method. To further reduce clustering errors, we develop an iterative merging algorithm based on mean size to aggregate fragment instances. Experiments on ScanNetV2 and S3DIS datasets indicate the superiority of our model. In particular, PBNet achieves so far the best AP50 and AP25 on the ScanNetV2 official benchmark challenge (Validation Set) while demonstrating high efficiency

From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion

We consider the problem of Multi-view 3D Face Reconstruction (MVR) with weakly supervised learning that leverages a limited number of 2D face images (e.g. 3) to generate a high-quality 3D face model with very light annotation. Despite their encouraging performance, present MVR methods simply concatenate multi-view image features and pay less attention to critical areas (e.g. eye, brow, nose and mouth). To this end, we propose a novel model called Deep Fusion MVR (DF-MVR) and design a multi-view encoding to a single decoding framework with skip connections, able to extract, integrate, and compensate deep features with attention from multi-view images. In addition, we develop a multi-view face parse network to learn, identify, and emphasize the critical common face area. Finally, though our model is trained with a few 2D images, it can reconstruct an accurate 3D model even if one single 2D image is input. We conduct extensive experiments to evaluate various multi-view 3D face reconstruction methods. Our proposed model attains superior performance, leading to 11.4% RMSE improvement over the existing best weakly supervised MVRs. Source codes are available in the supplementary materials

Research Progress of Functional Enzymes inTraditional Fermented Food

Traditional fermented foods could produce a variety of functional enzymes and plenty of flavor compounds through microbial fermentation. The production process of fermented foods would be constantly enriched with abundant enzymes, and it is the current hotspot to study these functional enzymes systematically and scientifically. In this study, the traditional isolation and culture of functional enzymes from fermented food are analyzed, and it can identify the enzyme activity of key functional enzymes. Furthermore, this work summarizes the recent research on functional enzymes in fermented foods by high-throughput technologies, such as PICRUSt analysis based on 16S rRNA and ITS sequencing, metagenome, metatranscriptome and metaproteome. It is found that, compared to analysis by traditional isolation and culture, single high-throughput technology can obtain more functional enzymes information, analyze complex metabolic pathways and identify active functional enzymes. The research on functional enzymes by combinations of high-throughput technologies is also reviewed, and it is found that combination of different methods can obtain more information to analyze the fermentation process of traditional food comprehensively and deeply. It is also found that, based on analysis of high-throughput technology, some researchers have analyzed the specific functional enzymes in traditional foods by heterologous expression. This study comprehensively summarizes results and methods of functional enzymes in various traditional fermented foods, aiming to provide technical foundation for the research and application of functional enzymes in traditional fermented foods

Research Progress on the Sources and Enrichment of Selenium and Selenium-Rich Dietary Resources

Selenium-rich foods serve the dual-function of providing nutrients and organic selenium. In the situation of selenium deficiency in the entire population, it is crucial to understand the sources of selenium and its circulation in the natural environment and biological systems. Current research on selenium-rich foods focuses mostly on chemical synthesis and bio-organic conversion, which is highly specialized and not suitable for horizontal comparison of different selenium-rich foods. There are few studies on the circulation of selenium and the selenium contents and health benefits of different selenium-rich foods. This article summarizes the sources, circulation and metabolism of selenium, the sources and forms of natural selenium in selenium-rich foods, and the selenium absorption and metabolism pathways in plants, animals, and microorganisms. Next, it reviews the current status of research on selenium-rich foods from various sources, and gives an outlook on the future of selenium-rich foods. This review may serve as a foundation for in-depth comparison of selenium-rich foods from various sources, and provide scientific guidance for the research and development of novel healthy selenium-rich foods

Simultaneously achieving high energy density and responsivity in submicron BaTiO3 film capacitors integrated on Si

In the research field of energy storage dielectrics, the “responsivity” parameter, defined as the recyclable/recoverable energy density per unit electric field, has become critically important for a comprehensive evaluation of the energy storage capability of a dielectric. In this work, high recyclable energy density and responsivity, i.e., Wrec = 161.1 J·cm–3 and ξ = 373.8 J·(kV·m2)–1, have been simultaneously achieved in a prototype perovskite dielectric, BaTiO3, which is integrated on Si at 500 ℃ in the form of a submicron thick film. This ferroelectric film features a multi-scale polar structure consisting of ferroelectric grains with different orientations and inner-grain ferroelastic domains. A LaNiO3 buffer layer is used to induce a {001} textured, columnar nanograin microstructure, while an elevated deposition temperature promotes lateral growth of the nanograins (in-plane diameter increases from ~10–20 nm at lower temperatures to ~30 nm). These preferably oriented and periodically regulated nanograins have resulted in a small remnant polarization and a delayed polarization saturation in the film’s P–E behavior, leading to a high recyclable energy density. Meanwhile, an improved polarizability/dielectric constant of the BaTiO3 film has produced a much larger maximum polarization than those deposited at lower temperatures at the same electric field, leading to a record-breaking responsivity for this simple perovskite

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A critical review of microplastic pollution in urban freshwater environments and legislative progress in China: Recommendations and insights

Freshwater systems are vitally important, supporting diversity and providing a range of ecosystem services. In China, rapid urbanization (over 800 million urban population) has led to multiple anthropogenic pressures that threaten urban freshwater environments. Microplastics (<5 mm) result from intensive production and use of plastic materials, but their effects in urban freshwater environments remain poorly understood. Rising concerns over the ecological effects of microplastics have resulted in increased attention being given to this contaminant in Chinese freshwater systems. Some studies provide quantitative data on contamination loads, but in general relevant knowledge in freshwater environment remains narrow in China, and lacking adequate understanding of threshold levels for detrimental effects. Notably, non-standardized sample collection and processing techniques for point and non-point sources have hindered comparisons of contamination loads and associated risk. Meanwhile, legislative frameworks for managing microplastics in China remain in their infancy. This manuscript critically reviews what is known of the nature and magnitude of microplastic pollution in Chinese freshwater environments, and summarizes relevant Chinese legislation. It provides recommendations for improving the legislative framework in China and identifies research gaps that need to be addressed to improve management and regulatory strategies for dealing with microplastic pollution in Chinese urban freshwater environments

Production-inventory and emission reduction investment decision under carbon cap-and-trade policy

The increasing amount of carbon emissions has caused global warming and challenged the sustainable development of environment. Governments around the world have implemented carbon policies including carbon cap-and-trade policy. In this paper, we focus on how a two-echelon supply chain manages its carbon footprints in production and inventory under carbon cap-and-trade policy. We extend the classical EOQ (economic order quantity) model and study decisions on production-inventory, carbon trading and emission reduction investment in the decentralized and centralized situations. The results show that emission permit sharing can effectively reduce the total cost and total carbon emissions of the supply chain. Moreover, the manufacturer’s emission reduction effort rises with the increase of the buying and selling prices of emission permits under centralized decision-making. In addition, a compensation mechanism is proposed for the centralized supply chain with emission permit sharing. It is observed that the buying and selling prices of emission permits have a positive influence on the permit sharing price in the compensation mechanism. Meanwhile, the retailer pays less for using the emission permits if it has a higher carbon cap, while the manufacturer with a higher carbon cap is more capable to provide a high compensation for the retailer

Long non-coding RNA LINC01194 promotes the inflammatory response and apoptosis of LPS-treated MLE 12 cells through the miR-203a-3p /MIP-2 axis

Acute lung injury (ALI) induced by bacteria LPS is characterized by the upregulation of the apoptosis rate of tissue cells and aggravation of inflammatory response. Although many studies have focused on the pathogenesis of this disease, its mechanism remains unknown. This study examined the regulatory role of long non-coding RNA (lncRNA) LINC01194 in the progression of ALI through various bioinformatics analyses and experimental work, including ELISA assay, dual-luciferase reporter assay, biotinylated RNA pull-down assay, and western blot analysis. The result showed that the LINC01194 was overexpressed in the ALI-induced mice model. We observed a significant upregulation of LINC01194 in LPS-treated Mouse lung epithelial type II cells (MLE-12 cells) after 24 hrs of induction. Bioinformatics analysis, Elisa assay, qRT-PCR analysis, Biotinylated RNA pull-down assay, apoptosis test, and western blot analysis demonstrated that the LINC01194 could act as a miR-203a-3p sponge to activate the inflammatory response in LPS-induced ALI model through post-transcriptional upregulation of MIP-2. We showed that LINC01194 regulates the inflammatory response and apoptosis of LPS-induced mice and MLE-12 cells via the miR-203a-3p/MIP-2 axis. LINC01194 could be a potential biomarker for early diagnosis and the treatment of ALI.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author