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Teeth scans are essential for many applications in orthodontics, where the teeth structures are virtualized to facilitate the design and fabrication of the prosthetic piece. Nevertheless, due to the limitations caused by factors such as viewing angles, occlusions, and sensor resolution, the 3D scanned point clouds (PCs) could be noisy or incomplete. Hence, there is a critical need to enhance the quality of the teeth PCs to ensure a suitable dental treatment. Toward this end, we propose a systematic framework including a two-step data augmentation (DA) technique to augment the limited teeth PCs and a hybrid deep learning (DL) method to complete the incomplete PCs. For the two-step DA, we first mirror and combine the PCs based on the bilateral symmetry of the human teeth and then augment the PCs based on an iterative generative adversarial network (GAN). Two filters are designed to avoid the outlier and duplicated PCs during the DA. For the hybrid DL, we first use a deep autoencoder (AE) to represent the PCs. Then, we propose a hybrid approach that selects the best completion to the teeth PCs from AE and a reinforcement learning (RL) agent-controlled GAN. Ablation study is performed to analyze each component’s contribution. We compared our method with other benchmark methods including point cloud network (PCN), cascaded refinement network (CRN), and variational relational point completion network (VRC-Net), and demonstrated that the proposed framework is suitable for completing teeth PCs with good accuracy over different scenarios.

 

Mouse is probably the most important model organism to study mammal biology and human diseases. A better understanding of the mouse genome will help understand the human genome, biology and diseases. However, despite the recent progress, the characterization of the regulatory sequences in the mouse genome is still far from complete, limiting its use to understand the regulatory sequences in the human genome.

Here, by integrating binding peaks in ~ 9,000 transcription factor (TF) ChIP-seq datasets that cover 79.9% of the mouse mappable genome using an efficient pipeline, we were able to partition these binding peak-covered genome regions into acis-regulatory module (CRM) candidate (CRMC) set and a non-CRMC set. The CRMCs contain 912,197 putative CRMs and 38,554,729 TF binding sites (TFBSs) islands, covering 55.5% and 24.4% of the mappable genome, respectively. The CRMCs tend to be under strong evolutionary constraints, indicating that they are likelycis-regulatory; while the non-CRMCs are largely selectively neutral, indicating that they are unlikelycis-regulatory. Based on evolutionary profiles of the genome positions, we further estimated that 63.8% and 27.4% of the mouse genome might code for CRMs and TFBSs, respectively.

Validation using experimental data suggests that at least most of the CRMCs are authentic. Thus, this unprecedentedly comprehensive map of CRMs and TFBSs can be a good resource to guide experimental studies of regulatory genomes in mice and humans.

 

Abstract Records of pressure variations on seismographs were historically considered unwanted noise; however, increased deployments of collocated seismic and acoustic instrumentation have driven recent efforts to use this effect induced by both wind and anthropogenic explosions to invert for near-surface Earth structure. These studies have been limited to shallow structure because the pressure signals have relatively short wavelengths (<∼300 m). However, the 2022 eruption of Hunga Tonga–Hunga Ha’apai (also called “Hunga”) volcano in Tonga generated rare, globally observed, high-amplitude infrasound signals with acoustic wavelengths of tens of kilometers. In this study, we examine the acoustic-to-seismic coupling generated by the Hunga eruption across 82 Global Seismographic Network (GSN) stations and show that ground motion amplitudes are related to upper (0 to ∼5 km) crust material properties. We find high (>0.8) correlations between pressure and vertical component ground motion at 83% of the stations, but only 30% of stations show this on the radial component, likely due to complex tilt effects. We use average elastic properties in the upper 5.2 km from the CRUST1.0 model to estimate vertical seismic/acoustic coupling coefficients (SV/A) across the GSN network and compare these to recorded observations. We exclude many island stations from these comparisons because the 1° resolution of the CRUST1.0 model places a water layer below these stations. Our simple modeling can predict observed SV/A within a factor of 2 for 94% of the 51 non-island GSN stations with high correlations between pressure and ground motion. These results indicate that analysis of acoustic-to-seismic coupling from the eruption could be used to place additional constraints on crustal structure models at stations with collocated seismic and pressure sensors. Ultimately, this could improve tomographic imaging models, which rely on methods that are sensitive to local structure. 

A series of BN-incorporated borafluorenate heterocycles, bis(borafluorene-phosphinimine)s (11–15), have been formed via intramolecular Staudinger-type reactions. The reactions were promoted by light or heat using monodentate phosphine-stabilized 9-azido-9-borafluorenes (R3P-BF-N3; 6–10) and involve the release of dinitrogen (N2), migration of phosphine from boron to nitrogen, and oxidation of the phosphorus center (PIII to PV). Density functional theory (DFT) calculations provide mechanistic insight into the formation of these compounds. Compounds 11–15 are blue emissive in the solution and solid states with absolute quantum yields (ΦF) ranging from 12 to 68%. 

Selective and site-specific boron-doping of polycyclic aromatic hydrocarbon frameworks often give rise to redox and/or photophysical properties that are not easily accessible with the analogous all-carbon systems. Herein, we report ligand-mediated control of boraphenanthrene closed- and open-shell electronic states, which has led to the first structurally characterized examples of neutral bis(9-boraphenanthrene) (2–3) and its corresponding biradical (4). Notably, compounds 2 and 3 show intramolecular charge transfer absorption from the 9-boraphenanthrene units to p-quinodimethane, exhibiting dual (red-shifted) emission in solution due to excited state conjugation enhancement (ESCE). Moreover, while boron-centered monoradicals are ubiquitous, biradical 4 represents a rare type of open-shell singlet compound with 95% biradical character, among the highest of any reported boron-based polycyclic species with two radical sites. 

The COVID-19 pandemic led the majority of educational institutions to rapidly shift to primarily conducting courses through online, remote delivery. Across different institutions, the tools used for synchronous online course delivery varied. They included traditional video conferencing tools like Zoom, Google Meet, and WebEx as well as non-traditional tools like Gather.Town, Gatherly, and YoTribe. The main distinguishing characteristic of these nontraditional tools is their utilization of 2-D maps to create virtual meeting spaces that mimic real-world spaces. In this work, we aim to explore how such tools are perceived by students in the context of learning. Our intuition is that utilizing a tool that features a 2-D virtual space that resembles a real world classroom has underlying benefits compared to the more traditional video conferencing tools. The results of our study indicate that students' perception of using a 2-D virtual classroom improved their interaction, collaboration and overall satisfaction with an online learning experience.