Multi-scale feature fusion for pavement crack detection based on Transformer

Automated pavement crack image segmentation presents a significant challenge due to the difficulty in detecting slender cracks on complex pavement backgrounds, as well as the significant impact of lighting conditions. In this paper, we propose a novel approach for automated pavement crack detection using a multi-scale feature fusion network based on the Transformer architecture, leveraging an encoding-decoding structure. In the encoding phase, the Transformer is leveraged as a substitute for the convolution operation, which utilizes global modeling to enhance feature extraction capabilities and address long-distance dependence. Then, dilated convolution is employed to increase the receptive field of the feature map while maintaining resolution, thereby further improving context information acquisition. In the decoding phase, the linear layer is employed to adjust the length of feature sequence output by different encoder block, and the multi-scale feature map is obtained after dimension conversion. Detailed information of cracks can be restored by fusing multi-scale features, thereby improving the accuracy of crack detection. Our proposed method achieves an F1 score of 70.84% on the Crack500 dataset and 84.50% on the DeepCrack dataset, which are improvements of 1.42% and 2.07% over the state-of-the-art method, respectively. The experimental results show that the proposed method has higher detection accuracy, better generalization and better crack detection results can be obtained under both high and low brightness conditions

Unveiling Luminous Lyα\alpha Emitters at z≈6z\approx6 through JWST/NIRCam Imaging in the COSMOS Field

We study a sample of 14 spectroscopically confirmed Ly$\alpha$ Emitters (LAEs) in the late era of reionization (at redshift $z\approx6$) based on the JWST/NIRCam imaging dataset. These LAEs with high Ly$\alpha$ luminosity of $L$(Ly$\alpha$) $\sim10^{42.4-43.4}$ erg s$^{-1}$ have been covered by the (ongoing) COSMOS-Web survey (Kartaltepe et al. 2021; Casey et al. 2022) over $0.28$ deg$^2$ in four NIRCam bands (F115W, F150W, F277W, and F444W). With JWST imaging, we determine the UV continua with $M_{\rm UV}$ ranging from ${-}20.5$ to ${-}18.5$ mag. The UV slopes have a median value of $\beta \approx-2.35$, and the steepest slope can reach $\beta<-3$. Under an excellent spatial resolution of JWST, we identify three out of the sample as potential merging/interacting systems. The 14 LAEs (and their components) are compact in morphology residing substantially below the mass-size relation of high-$z$ galaxies. We further investigate the stellar mass ($M_*$) and star-formation rates (SFRs). Most of the LAEs lie on the SFR-$M_*$ main-sequence relation while two of them featured as "little red dots" likely host active galactic nuclei (AGN), implying a ${\sim}10\%$ AGN fraction. Moreover, we reveal that a new correlation may exist between Ly$\alpha$ equivalent width and the offset between Ly$\alpha$ and UV emission ($\Delta d_{\rm Ly\alpha}$) with a median $\Delta d_{\rm Ly\alpha} \sim 1$ kpc. This could be explained by Ly$\alpha$ radiative transfer process in both ISM and CGM. The results usher a new era of detailed analysis on high-$z$ LAEs with the JWST capability.Comment: 15 pages, 5 figures, accepted by ApJ

The Magellan M2FS Spectroscopic Survey of High-Redshift Galaxies: A Sample of 260 Lyα\alpha Emitters at Redshift z≈5.7z\approx5.7

We present a spectroscopic survey of Ly$\alpha$ emitters (LAEs) at $z\approx5.7$ using the multi-object spectrograph M2FS on the Magellan Clay telescope. This is part of a high-redshift galaxy survey carried out in several well-studied deep fields. These fields have deep images in multiple UV/optical bands, including a narrow NB816 band that has allowed an efficient selection of LAE candidates at $z\approx5.7$. Our sample consists of 260 LAEs and covers a total effective area of more than two square degrees on the sky. This is so far the largest (spectroscopically confirmed) sample of LAEs at this redshift. We use the secure redshifts and narrowband photometry to measure Ly$\alpha$ luminosities. We find that these LAEs span a Ly$\alpha$ luminosity range of $\sim 2\times10^{42} - 5\times10^{43}$ erg s$^{-1}$, and include some of the most luminous galaxies known at $z \ge 5.7$ in terms of Ly$\alpha$ luminosity. Most of them have rest-frame equivalent widths between 20 and 300 \r{A}, and more luminous Ly$\alpha$ emission lines tend to have broader line widths. We detect a clear offset of $\sim20$ \r{A} between the observed Ly$\alpha$ wavelength distribution and the NB816 filter transmission curve, which can be explained by the intergalactic medium absorption of continua blueward of Ly$\alpha$ in the high-redshift spectra. This sample is being used to study the Ly$\alpha$ luminosity function and galaxy properties at $z\approx5.7$.Comment: 16 pages, 12 figures, 3 tables; Accepted for publication in Ap

Breath-, air- and surface-borne SARS-CoV-2 in hospitals

The COVID-19 pandemic has brought an unprecedented crisis to the global health sector. When discharging COVID-19 patients in accordance with throat or nasal swab protocols using RT-PCR, the potential risk of reintroducing the infection source to humans and the environment must be resolved. Here, 14 patients including 10 COVID-19 subjects were recruited; exhaled breath condensate (EBC), air samples and surface swabs were collected and analyzed for SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR) in four hospitals with applied natural ventilation and disinfection practices in Wuhan. Here we discovered that 22.2% of COVID-19 patients (n = 9), who were ready for hospital discharge based on current guidelines, had SARS-CoV-2 in their exhaled breath (~10⁵ RNA copies/m³). Although fewer surface swabs (3.1%, n = 318) tested positive, medical equipment such as face shield frequently contacted/used by healthcare workers and the work shift floor were contaminated by SARS-CoV-2 (3–8 viruses/cm²). Three of the air samples (n = 44) including those collected using a robot-assisted sampler were detected positive by a digital PCR with a concentration level of 9–219 viruses/m³. RT-PCR diagnosis using throat swab specimens had a failure rate of more than 22% in safely discharging COVID-19 patients who were otherwise still exhaling the SARS-CoV-2 by a rate of estimated ~1400 RNA copies per minute into the air. Direct surface contact might not represent a major transmission route, and lower positive rate of air sample (6.8%) was likely due to natural ventilation (1.6–3.3 m/s) and regular disinfection practices. While there is a critical need for strengthening hospital discharge standards in preventing re-emergence of COVID-19 spread, use of breath sample as a supplement specimen could further guard the hospital discharge to ensure the safety of the public and minimize the pandemic re-emergence risk

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing reagents. This work was supported by the Shenzhen Basic Research Project for Excellent Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In addition, L.L. was supported by the National Natural Science Foundation of China (31900466), Y. Hou was supported by the Natural Science Foundation of Guangdong Province (2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award (419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science joint research project (GJHZ2093), the National Natural Science Foundation of China (92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075). M.L. was supported by the National Key Research and Development Program of China (2021YFC2600200).S

Purification and Characterization of Resistant Dextrin

In this study, an efficient method for the purification of resistant dextrin (RD) using membrane filtration and anion exchange resin decolorization was developed, then the purified RD was characterized. In the membrane filtration stage, suspended solids in RD were completely removed, and the resulting product had a negligible turbidity of 2.70 &plusmn; 0.18 NTU. Furthermore, approximately half of the pigments were removed. Static decolorization experiments revealed that the D285 anion exchange resin exhibited the best decolorization ratio (D%), 84.5 &plusmn; 2.03%, and recovery ratio (R%), 82.8 &plusmn; 1.41%, among all the tested resins. Under optimal dynamic decolorization conditions, the D% and R% of RD were 86.26 &plusmn; 0.63% and 85.23 &plusmn; 0.42%, respectively. The decolorization efficiency of the D285 resin was superior to those of activated carbon and H2O2. Moreover, the chemical characteristics and molecular weight of RD did not change significantly after purification. The nuclear magnetic resonance spectroscopy of RD showed the formation of new glycosidic linkages that are resistant to digestive enzymes. The superior water solubility (99.14%), thermal stability (up to 200 &deg;C), and rheological properties of RD make it possible to be widely used in food industry

Purification and Characterization of Resistant Dextrin

In this study, an efficient method for the purification of resistant dextrin (RD) using membrane filtration and anion exchange resin decolorization was developed, then the purified RD was characterized. In the membrane filtration stage, suspended solids in RD were completely removed, and the resulting product had a negligible turbidity of 2.70 ± 0.18 NTU. Furthermore, approximately half of the pigments were removed. Static decolorization experiments revealed that the D285 anion exchange resin exhibited the best decolorization ratio (D%), 84.5 ± 2.03%, and recovery ratio (R%), 82.8 ± 1.41%, among all the tested resins. Under optimal dynamic decolorization conditions, the D% and R% of RD were 86.26 ± 0.63% and 85.23 ± 0.42%, respectively. The decolorization efficiency of the D285 resin was superior to those of activated carbon and H2O2. Moreover, the chemical characteristics and molecular weight of RD did not change significantly after purification. The nuclear magnetic resonance spectroscopy of RD showed the formation of new glycosidic linkages that are resistant to digestive enzymes. The superior water solubility (99.14%), thermal stability (up to 200 °C), and rheological properties of RD make it possible to be widely used in food industry

The laser-prepared SiC nanocoating: preparation, properties and high-temperature oxidation performance

In this study, SiC nanocoatings were prepared on graphite substrates via a laser treatment process. Different laser energy densities were employed in the laser treatment. The surface morphology and elemental composition were systematically studied by scanning electron microscopy (SEM) and energy dispersive spectrometer (EDS). X-ray diffraction (XRD) and high-resolution transmission electron microscopy (TEM) were used to characterize the phase composition and coating microstructure. A high-temperature oxidation test was also conducted to determine their anti-oxidation performance. The results show that laser irradiation triggers the transformation from micro SiC particles into SiC nanocoating consisting of numerous polycrystalline SiC nanoparticles. At the laser energy density of 10.42 kJ cm ^−2 , the prepared SiC nanocoating reveals the best oxidation resistance at a high-temperature environment in tested samples. In addition to its dense and crack-free surface morphology, the formation of SiO _2 in the SiC nanocoating also helped to enhance the high-temperature oxidation resistance as a self-healing agent. Laser preparation of SiC nanocoating enhances the high-temperature oxidation resistance and protects the underneath graphite substrate, which serves as an efficient and effective manufacturing method for SiC protective coatings