Evaluation of sonic, ultrasonic, and laser irrigation activation systems to eliminate bacteria from the dentinal tubules of the root canal system

Aiming to kill bacteria in dentin tubules of infected dental pulp cavities, we evaluated the effects of sodium hypochlorite (NaOCl) solution agitated by different irrigation protocols, i.e., conventional needle irrigation (CNI), passive ultrasonic irrigation (PUI), the EDDY tip, and the neodymium-doped yttrium aluminum perovskite (Nd:YAP) laser. The EDDY achieved good antibacterial effects as passive ultrasonic irrigation in the coronal and middle thirds. Nd:YAP laser irradiation and PUI were effective in the apical third of the root canal. Objectives: To evaluate the ability of NaOCl agitated by high-frequency sonic irrigation–EDDY, PUI, and Nd:YAP laser–to kill bacteria in infected root canal walls and if the associated temperature increases at the root surface during application. Methodology: Infected root canal models were established, and roots were randomly divided into six groups: negative control, positive control, CNI, PUI, sonic agitation with EDDY, and Nd:YAP laser groups. After irrigation, the teeth were split and stained using the LIVE/DEAD BacLight Bacterial Viability Kit. Dead bacteria depth was evaluated by a confocal laser scanning microscopy and the temperature at the root surface was assessed using a thermal imaging camera during the irrigation process. Results: In the coronal and middle thirds of the root canal, PUI and EDDY had stronger antibacterial effects than CNI (p<0.05); in the apical third, the antibacterial effects of PUI and Nd:YAP laser-activated irrigation were better than CNI (p<0.05). The maximum change in temperature was significantly greater during continuous Nd:YAP laser application compared with the other methods, but intermittent irrigation helped lessening this trend. Conclusions: NaOCl agitated by EDDY tip and PUI exhibited a similar bacteria elimination effect in the coronal and middle root canal. Nd:YAP laser was effective in the apical third and intermittent irrigation reduced its thermal impact

Light-LOAM: A Lightweight LiDAR Odometry and Mapping based on Graph-Matching

Simultaneous Localization and Mapping (SLAM) plays an important role in robot autonomy. Reliability and efficiency are the two most valued features for applying SLAM in robot applications. In this paper, we consider achieving a reliable LiDAR-based SLAM function in computation-limited platforms, such as quadrotor UAVs based on graph-based point cloud association. First, contrary to most works selecting salient features for point cloud registration, we propose a non-conspicuous feature selection strategy for reliability and robustness purposes. Then a two-stage correspondence selection method is used to register the point cloud, which includes a KD-tree-based coarse matching followed by a graph-based matching method that uses geometric consistency to vote out incorrect correspondences. Additionally, we propose an odometry approach where the weight optimizations are guided by vote results from the aforementioned geometric consistency graph. In this way, the optimization of LiDAR odometry rapidly converges and evaluates a fairly accurate transformation resulting in the back-end module efficiently finishing the mapping task. Finally, we evaluate our proposed framework on the KITTI odometry dataset and real-world environments. Experiments show that our SLAM system achieves a comparative level or higher level of accuracy with more balanced computation efficiency compared with the mainstream LiDAR-based SLAM solutions

THE STUDY OF TEAM RESULTANT FORCE VANISHING PERCENTAGE IN ELITE TUG OF WAR PLAYERS

This study was to analyze the factor of team pulling force vanishing percentage between groups with different numbers players and the largest pUlling force with unsteady motion in tug of war after sitting posture between players. The motion of nine female senior high school players(age =16.9 ± 0.6 years, height =163.8 ± 2.7 cm, mass =58.7 ± 4.3 kg) in tug of war was synchronized with a high-speed camera(JVC9800, 60 Hz)and a tensile (TEDEA, 900 Hz). The pulling force was gained by DASYlab6.0. The variance of the angle between the rope and ground was analyzed by Silicon Coach from the film, consisted by two to eight players. Results: The team pUlling resultant was smaller than the sum of individual players. The vanishing percentage of pulling force was increase with the number of players. The factor of force vanishing was the coordination between players. The larger numbers players are, the 'lower coordination was. This is so called Ringlemann effect; the factor was timing of the maximal pulling force with each player, therefore coordination was decreasing with the numbers of players, so was force

Benchmarking reconstructive spectrometer with multi-resonant cavities

Recent years have seen the rapid development of miniaturized reconstructive spectrometers (RSs), yet they still confront a range of technical challenges, such as bandwidth/resolution ratio, sensing speed, and/or power efficiency. Reported RS designs often suffer from insufficient decorrelation between sampling channels, which results in limited compressive sampling efficiency, in essence, due to inadequate engineering of sampling responses. This in turn leads to poor spectral-pixel-to-channel ratios (SPCRs), typically restricted at single digits. So far, there lacks a general guideline for manipulating RS sampling responses for the effectiveness of spectral information acquisition. In this study, we shed light on a fundamental parameter from the compressive sensing theory - the average mutual correlation coefficient v - and provide insight into how it serves as a critical benchmark in RS design with regards to the SPCR and reconstruction accuracy. To this end, we propose a novel RS design with multi-resonant cavities, consisting of a series of partial reflective interfaces. Such multi-cavity configuration offers an expansive parameter space, facilitating the superlative optimization of sampling matrices with minimized v. As a proof-of-concept demonstration, a single-shot, dual-band RS is implemented on a SiN platform, tailored for capturing signature spectral shapes across different wavelength regions, with customized photonic crystal nanobeam mirrors. Experimentally, the device demonstrates an overall operation bandwidth of 270 nm and a <0.5 nm resolution with only 15 sampling channels per band, leading to a record high SPCR of 18.0. Moreover, the proposed multi-cavity design can be readily adapted to various photonic platforms. For instance, we showcase that by employing multi-layer coatings, an ultra-broadband RS can be optimized to exhibit a 700 nm bandwidth with an SPCR of over 100

FAK Promotes Osteoblast Progenitor Cell Proliferation and Differentiation by Enhancing Wnt Signaling

Decreased bone formation is often associated with increased bone marrow adiposity. The molecular mechanisms that are accountable for the negative correlation between bone mass and bone marrow adiposity are incompletely understood. Focal adhesion kinase (FAK) has critical functions in proliferation and differentiation of many cell types; however, its roles in osteoblast lineage cells are largely unknown. We show herein that mice lacking FAK in Osterixâ expressing cells exhibited decreased osteoblast number and low bone mass as well as increased bone marrow adiposity. The decreased bone mass in FAKâ deficient mice was accounted for by decreased proliferation, compromised osteogenic differentiation, and increased adipogenic differentiation of bone marrow Osterixâ expressing cells resulting from downregulation of Wnt/βâ catenin signaling due to the reduced expression of canonical Wnt ligands. In contrast, FAK loss in calvarial preosteoblasts had no adverse effect on their proliferation and osteogenic differentiation and these cells had intact Wnt/βâ catenin signaling. © 2016 American Society for Bone and Mineral Research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135488/1/jbmr2908_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135488/2/jbmr2908-sup-0001-SuppData-S1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135488/3/jbmr2908.pd

Multi-modal In-Context Learning Makes an Ego-evolving Scene Text Recognizer

Scene text recognition (STR) in the wild frequently encounters challenges when coping with domain variations, font diversity, shape deformations, etc. A straightforward solution is performing model fine-tuning tailored to a specific scenario, but it is computationally intensive and requires multiple model copies for various scenarios. Recent studies indicate that large language models (LLMs) can learn from a few demonstration examples in a training-free manner, termed "In-Context Learning" (ICL). Nevertheless, applying LLMs as a text recognizer is unacceptably resource-consuming. Moreover, our pilot experiments on LLMs show that ICL fails in STR, mainly attributed to the insufficient incorporation of contextual information from diverse samples in the training stage. To this end, we introduce E$^2$STR, a STR model trained with context-rich scene text sequences, where the sequences are generated via our proposed in-context training strategy. E$^2$STR demonstrates that a regular-sized model is sufficient to achieve effective ICL capabilities in STR. Extensive experiments show that E$^2$STR exhibits remarkable training-free adaptation in various scenarios and outperforms even the fine-tuned state-of-the-art approaches on public benchmarks. The code is released at https://github.com/bytedance/E2STR .Comment: Accepted to CVPR202

Electrooxidation of Hydrogen on Ni-Organic Metal Complex Catalysts in Acidic Media for PEMFCs

Novel organic metal complexes with N2O2 coordination structure which showed high hydrogen oxidation reaction were synthesized. The catalytic activity was found to strongly depend on the heat-treatment temperature and the structural properties

Decoding the Neuroanatomical Basis of Reading Ability: A Multivoxel Morphometric Study

As a relatively recent cultural invention in human evolution, reading is an important gateway to personal development and socioeconomic success. Despite the well documented individual differences in reading ability, its neuroanatomical correlates have not been well understood, largely due to the fact that reading is a complex skill that consists of multiple components. Using a large sample of 416 college students and 7 reading tasks, the present study successfully identified three uncorrelated components of reading ability: phonological decoding, form-sound association, and naming speed. We then tried to predict individuals' scores in these components from their gray matter volume (GMV) on a subset of participants (N = 253) with high-quality structural images, adopting a multivariate support vector regression analysis with tenfold cross-validation. Our results revealed distinct neural regions that supported different aspects of reading ability: whereas phonological decoding was associated with the GMV in the left superior parietal lobe extending to the supramarginal gyrus, form-sound association was predicted by the GMV in the hippocampus and cerebellum. Naming speed was associated with GMV in distributed brain regions in the occipital, temporal, parietal, and frontal cortices. Phonological decoding and form-sound association were uncorrelated with general cognitive abilities. However, naming speed was correlated with intelligence and processing speed, and some of the regions that were predictive of naming speed also predicted these general cognitive abilities. These results provide further insights on the cognitive and neural architecture of reading and the structural basis of individual differences in reading abilities