Towards Large-Scale Small Object Detection: Survey and Benchmarks

With the rise of deep convolutional neural networks, object detection has achieved prominent advances in past years. However, such prosperity could not camouflage the unsatisfactory situation of Small Object Detection (SOD), one of the notoriously challenging tasks in computer vision, owing to the poor visual appearance and noisy representation caused by the intrinsic structure of small targets. In addition, large-scale dataset for benchmarking small object detection methods remains a bottleneck. In this paper, we first conduct a thorough review of small object detection. Then, to catalyze the development of SOD, we construct two large-scale Small Object Detection dAtasets (SODA), SODA-D and SODA-A, which focus on the Driving and Aerial scenarios respectively. SODA-D includes 24828 high-quality traffic images and 278433 instances of nine categories. For SODA-A, we harvest 2513 high resolution aerial images and annotate 872069 instances over nine classes. The proposed datasets, as we know, are the first-ever attempt to large-scale benchmarks with a vast collection of exhaustively annotated instances tailored for multi-category SOD. Finally, we evaluate the performance of mainstream methods on SODA. We expect the released benchmarks could facilitate the development of SOD and spawn more breakthroughs in this field. Datasets and codes are available at: \url{https://shaunyuan22.github.io/SODA}

Production, purification and characterization of polyclonal antibody against the truncated gK of the duck enteritis virus

Duck virus enteritis (DVE) is an acute, contagious herpesvirus infection of ducks, geese, and swans, which has produced significant economic losses in domestic and wild waterfowl. With the purpose of decreasing economic losses in the commercial duck industry, studying the unknown glycoprotein K (gK) of DEV may be a new method for preferably preventing and curing this disease. So this is the first time to product and purify the rabbit anti-tgK polyclonal antibody. Through the western blot and ELISA assay, the truncated glycoprotein K (tgK) has good antigenicity, also the antibody possesses high specificity and affinity. Meanwhile the rabbit anti-tgK polyclonal antibody has the potential to produce subunit vaccines and the functions of neutralizing DEV and anti-DEV infection because of its neutralization titer. Indirect immunofluorescent microscopy using the purified rabbit anti-tgK polyclonal antibody as diagnostic antibody was susceptive to detect a small quantity of antigen in tissues or cells. This approach also provides effective experimental technology for epidemiological investigation and retrospective diagnose of the preservative paraffin blocks

Publisher Correction: Copper adparticle enabled selective electrosynthesis of n-propanol.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Clinical diagnostic biomarker “circulating tumor cells” in breast cancer - a meta-analysis

ObjectiveUsing meta-analysis, we evaluate circulating tumor cells(CTCs) as a potential diagnostic tool for breast cancer.MethodsA document search was conducted using publicly available databases up to May 2021. Specific inclusion and exclusion criteria were formulated and summarize relevant data through literature types, research types, case populations, samples, etc. Subgroup analysis of documents based on regions, enrichment methods, and detection methods. The included research projects were evaluated using DeeKs’ bias, and evaluation indicators such as specificity (SPE), sensitivity (SEN), diagnosis odds ratio (DOR) were used as evaluation indicators.Results16 studies on the use of circulating tumor cells to diagnose breast cancer were included in our meta-analysis. Overall sensitivity value was 0.50 (95%CI:0.48-0.52), specificity value was 0.93 (95%CI:0.92- 0.95), DOR value was 33.41 (95%CI:12.47-89.51), and AUC value was 0.8129.ConclusionIn meta-regressions and subgroup analysis, potential heterogeneity factors were analyzed, but the source of heterogeneity is still unclear. CTCs, as a novel tumor marker, have a good diagnostic value, but its enrichment and detection methods still need to continue to be developed to improve detection accuracy. Therefore, CTCs can be used as an auxiliary means of early detection, which is helpful to the diagnosis and screening of breast cancer

Development and Validation of an Effective CRISPR/Cas9 Vector for Efficiently Isolating Positive Transformants and Transgene-Free Mutants in a Wide Range of Plant Species

The CRISPR/Cas9 technique is a highly valuable tool in creating new materials for both basic and applied researches. Previously, we succeeded in effectively generating mutations in Brassica napus using an available CRISPR/Cas9 vector pKSE401, while isolation of Cas9-free mutants is laborious and inefficient. Here, we inserted a fluorescence tag (sGFP) driven by the constitutive 35S promoter into pKSE401 to facilitate a visual screen of mutants. This modified vector was named pKSE401G and tested in several dicot plant species, including Arabidopsis, B. napus, Fragaria vesca (strawberry), and Glycine max (soybean). Consequently, GFP-positive plants were readily identified through fluorescence screening in all of these species. Among these GFP-positive plants, the average mutation frequency ranged from 20.4 to 52.5% in Arabidopsis and B. napus with stable transformation, and was 90.0% in strawberry and 75.0% in soybean with transient transformation, indicating that the editing efficiency resembles that of the original vector. Moreover, transgene-free mutants were sufficiently identified in Arabidopsis in the T2 generation and B. napus in the T1 generation based on the absence of GFP fluorescence, and these mutants were stably transmissible to next generation without newly induced mutations. Collectively, pKSE401G provides us an effective tool to readily identify positive primary transformants and transgene-free mutants in later generations in a wide range of dicot plant species

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO