Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting

Removing clutter from scenes is essential in many applications, ranging from privacy-concerned content filtering to data augmentation. In this work, we present an automatic system that removes clutter from 3D scenes and inpaints with coherent geometry and texture. We propose techniques for its two key components: 3D segmentation from shared properties and 3D inpainting, both of which are important problems. The definition of 3D scene clutter (frequently-moving objects) is not well captured by commonly-studied object categories in computer vision. To tackle the lack of well-defined clutter annotations, we group noisy fine-grained labels, leverage virtual rendering, and impose an instance-level area-sensitive loss. Once clutter is removed, we inpaint geometry and texture in the resulting holes by merging inpainted RGB-D images. This requires novel voting and pruning strategies that guarantee multi-view consistency across individually inpainted images for mesh reconstruction. Experiments on ScanNet and Matterport dataset show that our method outperforms baselines for clutter segmentation and 3D inpainting, both visually and quantitatively.Comment: 18 pages. ICCV 2023. Project page: https://weify627.github.io/clutter

Research on the Application of Cross-Specialty Education and Situational Simulation Teaching in Operation Nursing Practice Teaching

Objective To examine the practical effect of inter-professional education and situational simulation teaching implemented in surgical nursing practice teaching. Methods On the whole, 100 undergraduate nursing students in the operating room of the hospital of the authors from May 2019 to August 2020 were selected. These students fell to two groups with the random number table method. The control received the regular teaching, and the research group were given the interprofessional education and context. The Simulation teaching was conducted to compare the theoretical knowledge, skill level, various abilities of the two groups of students, as well as the satisfaction of the operating room doctors to the nursing cooperation of the interns. Results The research group achieved higher theoretical knowledge and a higher skill level than the control (p < 0.05); the various abilities of the research group were higher than those of the control (p < 0.05); the operating room doctors of the research group were more satisfied with the nursing cooperation of interns, as compared with those of the control (p < 0.05). Conclusion In the surgical nursing practice teaching, the inter-professional education and the situational simulation teaching have significant effects and are worth clinical applications

How to Survive between "Standardized Resident Training " and "Professional Master" -On the Difficulties Encountered in Undergraduate Clinical Practice

To review on the difficulties encountered by medical bachelor students for their career development after graduation, and to explore potential solutions to their current situation, thus provide them possibilities of making good use of professional training and skills acquired in campus

Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar

Conventional sensor systems record information about directly visible objects, whereas occluded scene components are considered lost in the measurement process. Non-line-of-sight (NLOS) methods try to recover such hidden objects from their indirect reflections - faint signal components, traditionally treated as measurement noise. Existing NLOS approaches struggle to record these low-signal components outside the lab, and do not scale to large-scale outdoor scenes and high-speed motion, typical in automotive scenarios. In particular, optical NLOS capture is fundamentally limited by the quartic intensity falloff of diffuse indirect reflections. In this work, we depart from visible-wavelength approaches and demonstrate detection, classification, and tracking of hidden objects in large-scale dynamic environments using Doppler radars that can be manufactured at low-cost in series production. To untangle noisy indirect and direct reflections, we learn from temporal sequences of Doppler velocity and position measurements, which we fuse in a joint NLOS detection and tracking network over time. We validate the approach on in-the-wild automotive scenes, including sequences of parked cars or house facades as relay surfaces, and demonstrate low-cost, real-time NLOS in dynamic automotive environments.Comment: First three authors contributed equally; Accepted at CVPR 202

Learning to Infer Semantic Parameters for 3D Shape Editing

Many applications in 3D shape design and augmentation require the ability to make specific edits to an object's semantic parameters (e.g., the pose of a person's arm or the length of an airplane's wing) while preserving as much existing details as possible. We propose to learn a deep network that infers the semantic parameters of an input shape and then allows the user to manipulate those parameters. The network is trained jointly on shapes from an auxiliary synthetic template and unlabeled realistic models, ensuring robustness to shape variability while relieving the need to label realistic exemplars. At testing time, edits within the parameter space drive deformations to be applied to the original shape, which provides semantically-meaningful manipulation while preserving the details. This is in contrast to prior methods that either use autoencoders with a limited latent-space dimensionality, failing to preserve arbitrary detail, or drive deformations with purely-geometric controls, such as cages, losing the ability to update local part regions. Experiments with datasets of chairs, airplanes, and human bodies demonstrate that our method produces more natural edits than prior work

A Blueprint of Microstructures and Stage-Specific Transcriptome Dynamics of Cuticle Formation in Bombyx mori

Insect cuticle is critical for the environmental adaptability and insecticide resistance of insects. However, there is no clear understanding of the structure and protein components of the cuticle during each developmental stage of holometabolous insects, and knowledge about the protein components within each layer is vague. We conducted serial sectioning, cuticular structure analysis, and transcriptome sequencing of the larval, pupal, and adult cuticles of Bombyx mori. The deposition processes of epicuticle, exocuticle, and endocuticle during larval, pupal, and adult cuticle formation were similar. Transcriptome analysis showed that these cuticle formations share 74% of the expressed cuticular protein (CP) genes and 20 other structural protein genes, such as larval serum protein and prisilkin. There are seven, six, and eleven stage-specific expressed CP genes in larval, pupal, and adult cuticles, respectively. The types and levels of CP genes may be the key determinants of the properties of each cuticular layer. For example, the CPs of the RR-2 protein family with high contents of histidine (His) are more essential for the exocuticle. Functional analysis suggested that BmorCPAP1-H is involved in cuticle formation. This study not only offers an in-depth understanding of cuticle morphology and protein components but also facilitates the elucidation of molecular mechanisms underlying cuticle formation in future studies

A tool to automatically design multiplex PCR primer pairs for specific targets using diverse templates

Abstract Multiplex PCR is an increasingly popular method for identifying species, investigating environmental diversity, and conducting phylogenetic analysis. The complexity and increasing availability of diverse templates necessitate a highly automated approach to design degenerate primer pairs for specific targets with multiple sequences. Existing tools for degenerate primer design suffer from poor maintenance, semi-automation, low adaptability, and low tolerance for gaps. We developed PMPrimer, a Python-based tool for automated design and evaluation of multiplex PCR primer pairs for specific targets using diverse templates. PMPrimer automatically designs optimal multiplex PCR primer pairs using a statistical-based template filter; performs multiple sequence alignment, conserved region identification, and primer design; and evaluates the primers based on template coverage, taxon specificity, and target specificity. PMPrimer identifies conserved regions using Shannon’s entropy method, tolerates gaps using a haplotype-based method, and evaluates multiplex PCR primer pairs based on template coverage and taxon specificity. We tested PMPrimer using datasets with diverse levels of conservation, sizes, and applications, including tuf genes of Staphylococci, hsp65 genes of Mycobacteriaceae, and 16S ribosomal RNA genes of Archaea. PMPrimer showed outstanding performance compared with existing tools and experimental validated primers. PMPrimer is available as a Python package at https://github.com/AGIScuipeng/PMPrimer

Evaluating the Effect of Expressing a Peanut Resveratrol Synthase Gene in Rice

<div><p>Resveratrol (Res) is a type of natural plant stilbenes and phytoalexins that only exists in a few plant species. Studies have shown that the Res could be biosynthesized and accumulated within plants, once the complete metabolic pathway and related enzymes, such as the key enzyme resveratrol synthase (RS), existed. In this study, a RS gene named <i>PNRS1</i> was cloned from the peanut, and the activity was confirmed in <i>E</i>. <i>coli</i>. Using transgenic approach, the <i>PNRS1</i> transgenic rice was obtained. In T₃ generation, the Res production and accumulation were further detected by HPLC. Our data revealed that compared to the wild type rice which <i>trans</i>-resveratrol was undetectable, in transgenic rice, the <i>trans</i>-resveratrol could be synthesized and achieved up to 0.697 μg/g FW in seedlings and 3.053 μg/g DW in seeds. Furthermore, the concentration of <i>trans</i>-resveratrol in transgenic rice seedlings could be induced up to eight or four-fold higher by ultraviolet (UV-C) or dark, respectively. Simultaneously, the endogenous increased of Res also showed the advantages in protecting the host plant from UV-C caused damage or dark-induced senescence. Our data indicated that Res was involved in host-defense responses against environmental stresses in transgenic rice. Here the results describes the processes of a peanut resveratrol synthase gene transformed into rice, and the detection of <i>trans</i>-resveratrol in transgenic rice, and the role of <i>trans</i>-resveratrol as a phytoalexin in transgenic rice when treated by UV-C and dark. These findings present new outcomes of transgenic approaches for functional genes and their corresponding physiological functions, and shed some light on broadening available resources of Res, nutritional improvement of crops, and new variety cultivation by genetic engineering.</p></div

Identification of trans-resveratrol in the seedlings and seeds of transgenic and wild-type rice by HPLC analysis.

<p>The chromatograms of standard <i>trans</i>-resveratrol (<b>A</b>), the extracts from L3 seedlings (<b>B</b>), wild-type rice seedlings (<b>C</b>), L3 seeds (<b>D</b>), wild-type rice seeds (<b>E</b>) and L3 seedlings treated by UV-C (<b>F</b>, introduced in the later section), were detected at 306 nm under the same conditions. The marker “↙”indicates the peak of <i>trans</i>-resveratrol.</p