New method for estimating molecular cloud distances based on Gaia, 2MASS, and the TRILEGAL galaxy model

We propose a new method for estimating the distances of molecular clouds traced by CO line emission. Stars from 2MASS and Gaia EDR3 are selected as on-cloud stars when they are projected on a cloud. The background on-cloud stars have redder colors on average than the foreground stars. Instead of searching for stars projected away from the cloud, we employed the TRILEGA galaxy model to mimic the stellar population without cloud extinction along the sightline toward the cloud. Our method does not require an exact boundary of a cloud. The boundaries are highly variable and depend on the sensitivity of the molecular line data. For each cloud, we compared the distributions of on-cloud stars to the TRILEGAL stellar populations in the diagram of $J-K_s$ color versus distance. The intrinsic $J-K_s$ colors of main-sequence and evolved stars from TRILEGAL were considered separately, and they were used as the baseline for subtracting the observed $J-K_s$ colors. The baseline-corrected $J-K_s$ color was deployed with the Bayesian analysis and Markov chain Monte Carlo sampling to determine the distance at which the $J-K_s$ color jump is largest. This method was successfully applied to measure the distances of 27 molecular clouds, which were selected from previously published cloud samples. By replacing TRILEGAL with the GALAXIA galaxy model, we were able to measure the distances for 21 of the 27 clouds. The distances of the 21 clouds based on the GALAXIA model agree well with those based on the TRILEGAL model. The distances of the 27 clouds estimated by this method are consistent with previous estimates. We will apply this new method to a larger region of the gaseous galactic plane, in particular, for the inner galactic region, where a region free of CO emission is hard to separate from the crowded field of clouds.Comment: 11 pages, 11 figures, accepted by A&

Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss

Contrastive Learning (CL) has achieved impressive performance in self-supervised learning tasks, showing superior generalization ability. Inspired by the success, adopting CL into collaborative filtering (CF) is prevailing in semi-supervised top-K recommendations. The basic idea is to routinely conduct heuristic-based data augmentation and apply contrastive losses (e.g., InfoNCE) on the augmented views. Yet, some CF-tailored challenges make this adoption suboptimal, such as the issue of out-of-distribution, the risk of false negatives, and the nature of top-K evaluation. They necessitate the CL-based CF scheme to focus more on mining hard negatives and distinguishing false negatives from the vast unlabeled user-item interactions, for informative contrast signals. Worse still, there is limited understanding of contrastive loss in CF methods, especially w.r.t. its generalization ability. To bridge the gap, we delve into the reasons underpinning the success of contrastive loss in CF, and propose a principled Adversarial InfoNCE loss (AdvInfoNCE), which is a variant of InfoNCE, specially tailored for CF methods. AdvInfoNCE adaptively explores and assigns hardness to each negative instance in an adversarial fashion and further utilizes a fine-grained hardness-aware ranking criterion to empower the recommender's generalization ability. Training CF models with AdvInfoNCE, we validate the effectiveness of AdvInfoNCE on both synthetic and real-world benchmark datasets, thus showing its generalization ability to mitigate out-of-distribution problems. Given the theoretical guarantees and empirical superiority of AdvInfoNCE over most contrastive loss functions, we advocate its adoption as a standard loss in recommender systems, particularly for the out-of-distribution tasks. Codes are available at https://github.com/LehengTHU/AdvInfoNCE.Comment: Accepted to NeurIPS 202

FacetClumps: A Facet-based Molecular Clump Detection Algorithm

A comprehensive understanding of molecular clumps is essential for investigating star formation. We present an algorithm for molecular clump detection, called FacetClumps. This algorithm uses a morphological approach to extract signal regions from the original data. The Gaussian Facet model is employed to fit the signal regions, which enhances the resistance to noise and the stability of the algorithm in diverse overlapping areas. The introduction of the extremum determination theorem of multivariate functions offers theoretical guidance for automatically locating clump centers. To guarantee that each clump is continuous, the signal regions are segmented into local regions based on gradient, and then the local regions are clustered into the clump centers based on connectivity and minimum distance to identify the regional information of each clump. Experiments conducted with both simulated and synthetic data demonstrate that FacetClumps exhibits great recall and precision rates, small location error and flux loss, a high consistency between the region of detected clump and that of simulated clump, and is generally stable in various environments. Notably, the recall rate of FacetClumps in the synthetic data, which comprises $^{13}CO$ ($J = 1-0$) emission line of the MWISP within $11.7^{\circ} \leq l \leq 13.4^{\circ}$, $0.22^{\circ} \leq b \leq 1.05^{\circ}$ and 5 km s$^{-1}$ $\leq v \leq$ 35 km s$^{-1}$ and simulated clumps, reaches 90.2\%. Additionally, FacetClumps demonstrates satisfactory performance when applied to observational data.Comment: 27pages,28figure

Comparison of ultrasound−based ADNEX model with magnetic resonance imaging for discriminating adnexal masses: a multi-center study

ObjectivesThe ADNEX model offered a good diagnostic performance for discriminating adnexal tumors, but research comparing the abilities of the ADNEX model and MRI for characterizing adnexal tumors has not been reported to our knowledge. The aim of this study was to evaluate the diagnostic accuracy of the ultrasound-based ADNEX (Assessment of Different NEoplasias in the adneXa) model in comparison with that of magnetic resonance imaging (MRI) for differentiating benign, borderline and malignant adnexal masses.MethodsThis prospective study included 529 women with adnexal masses who underwent assessment via the ADNEX model and subjective MRI analysis before surgical treatment between October 2019 and April 2022 at two hospitals. Postoperative histological diagnosis was considered the gold standard.ResultsAmong the 529 women, 92 (17.4%) masses were diagnosed histologically as malignant tumors, 67 (12.7%) as borderline tumors, and 370 (69.9%) as benign tumors. For the diagnosis of malignancy, including borderline tumors, overall agreement between the ADNEX model and MRI pre-operation was 84.9%. The sensitivity of the ADNEX model of 0.91 (95% confidence interval [CI]: 0.85–0.95) was similar to that of MRI (0.89, 95% CI: 0.84–0.94; P=0.717). However, the ADNEX model had a higher specificity (0.90, 95% CI: 0.87–0.93) than MRI (0.81, 95% CI: 0.77–0.85; P=0.001). The greatest sensitivity (0.96, 95% CI: 0.92–0.99) and specificity (0.94, 95% CI: 0.91–0.96) were achieved by combining the ADNEX model and subjective MRI assessment. While the total diagnostic accuracy did not differ significantly between the two methods (P=0.059), the ADNEX model showed greater diagnostic accuracy for borderline tumors (P<0.001).ConclusionThe ultrasound-based ADNEX model demonstrated excellent diagnostic performance for adnexal tumors, especially borderline tumors, compared with MRI. Accordingly, we recommend that the ADNEX model, alone or with subjective MRI assessment, should be used for pre-operative assessment of adnexal masses

Linker-extended native cyanovirin-N facilitates PEGylation and potently inhibits HIV-1 by targeting the glycan ligand

Cyanovirin-N (CVN) potently inhibits human immunodeficiency virus type 1 (HIV-1) infection, but both cytotoxicity and immunogenicity have hindered the translation of this protein into a viable therapeutic. A molecular docking analysis suggested that up to 12 residues were involved in the interaction of the reverse parallel CVN dimer with the oligosaccharide targets, among which Leu-1 was the most prominent hot spot residue. This finding provided a possible explanation for the lack of anti-HIV-1 activity observed with N-terminal PEGylated CVN. Therefore, linker-CVN (LCVN) was designed as a CVN derivative with a flexible and hydrophilic linker (Gly4Ser)3 at the N-terminus. The N-terminal α-amine of LCVN was PEGylated to create 10 K PEG-aldehyde (ALD)-LCVN. LCVN and 10 K PEG-ALD-LCVN retained the specificity and affinity of CVN for high mannose N-glycans. Moreover, LCVN exhibited significant anti-HIV-1 activity with attenuated cytotoxicity in the HaCaT keratinocyte cell line and MT-4 T lymphocyte cell lines. 10 K PEG-ALD-LCVN also efficiently inactivated HIV-1 with remarkably decreased cytotoxicity and pronounced cell-to-cell fusion inhibitory activity in vitro. The linker-extended CVN and the mono-PEGylated derivative were determined to be promising candidates for the development of an anti-HIV-1 agent. This derivatization approach provided a model for the PEGylation of biologic candidates without introducing point mutations. © 2014 Chen et al

Sciences for The 2.5-meter Wide Field Survey Telescope (WFST)

The Wide Field Survey Telescope (WFST) is a dedicated photometric survey facility under construction jointly by the University of Science and Technology of China and Purple Mountain Observatory. It is equipped with a primary mirror of 2.5m in diameter, an active optical system, and a mosaic CCD camera of 0.73 Gpix on the main focus plane to achieve high-quality imaging over a field of view of 6.5 square degrees. The installation of WFST in the Lenghu observing site is planned to happen in the summer of 2023, and the operation is scheduled to commence within three months afterward. WFST will scan the northern sky in four optical bands (u, g, r, and i) at cadences from hourly/daily to semi-weekly in the deep high-cadence survey (DHS) and the wide field survey (WFS) programs, respectively. WFS reaches a depth of 22.27, 23.32, 22.84, and 22.31 in AB magnitudes in a nominal 30-second exposure in the four bands during a photometric night, respectively, enabling us to search tremendous amount of transients in the low-z universe and systematically investigate the variability of Galactic and extragalactic objects. Intranight 90s exposures as deep as 23 and 24 mag in u and g bands via DHS provide a unique opportunity to facilitate explorations of energetic transients in demand for high sensitivity, including the electromagnetic counterparts of gravitational-wave events detected by the second/third-generation GW detectors, supernovae within a few hours of their explosions, tidal disruption events and luminous fast optical transients even beyond a redshift of 1. Meanwhile, the final 6-year co-added images, anticipated to reach g about 25.5 mag in WFS or even deeper by 1.5 mag in DHS, will be of significant value to general Galactic and extragalactic sciences. The highly uniform legacy surveys of WFST will also serve as an indispensable complement to those of LSST which monitors the southern sky.Comment: 46 pages, submitted to SCMP

Research on Cracking Control of Immersed Tube Tunnels Concrete by Pre-heating treatment

Herein, the pre-heating treatments are researched. With diversity of zone and temperature, highest average temperature of the section 10cm below surface was 14.7°C, which is lower than that of the concrete block. And the distance of 20cm and 40cm to surface of section, the temperature is 11.8°C and 9.8°C， respectively. When the heating water of 60°C, the increase of 48h to 72h, the highest temperature is about 47.2°C and 49.6°C

Cloning and characterization of porcine 4Ig-B7-H3: a potent inhibitor of porcine T-cell activation.

BACKGROUND: Members of the B7 superfamily costimulate the proliferation of lymphocytes during the initiation and maintenance of antigen-specific humoral and cell-mediated immune responses. B7-H3 (CD276) is a newly identified member of the B7 superfamily. It has been shown that B7-H3 plays a significant role in regulating T cell response in humans and mice, but it is not known whether a counterpart of human or murine B7-H3 exists in porcine species. METHODOLOGY/PRINCIPAL FINDINGS: We cloned the porcine 4ig-b7-h3 gene using a blast search at the NCBI database with human b7-h3, RT-PCR and 3'-terminus RACE. Protein sequence analysis showed that the protein encoded by this gene contained 4Ig-like domains and was 90.88% identical with human 4Ig-B7-H3. Results of Dot-blot hybridization and RT-PCR showed that B7-H3 was broadly distributed in porcine tissues mainly as two isoforms, 2Ig-B7-H3 and 4Ig-B7-H3, of which 4Ig-B7-H3 was dominant. We further demonstrated that porcine 4Ig-B7-H3 was able to inhibit the proliferation and cytokine production of porcine T cells activated through the TCR pathway, similar to human B7-H3. CONCLUSION: We cloned the porcine 4ig-b7-h3 gene and demonstrated that the porcine 4Ig-B7-H3 serves as a negative regulator for the T-cell immune response