Two-click based fast small object annotation in remote sensing images.

In the remote sensing field, detecting small objects is a pivotal task, yet achieving high performance in deep learning-based detectors heavily relies on extensive data annotation. The challenge intensifies as small objects in remote sensing imagery are typically densely distributed and numerous, leading to a substantial increase in the cost of creating large-scale annotated datasets. This elevated cost poses significant limitations on the application and advancement of small object detection. To address this issue, a Point-Based Annotation method (PBA) is proposed, which generates bounding boxes through graph-based segmentation. In this framework, user annotations categorize nodes into three distinct classes - positive, negative, and to-cut-facilitating a more intuitive and efficient annotation process. Utilizing the max-flow algorithm, our method seamlessly generates Oriented Bounding Boxes (OBBOX) from these classified nodes. The efficacy of PBA is underscored by our empirical findings. Notably, annotation efficiency is enhanced by at least 40%, a significant leap forward. Moreover, the Intersection over Union (IoU) metric of our OBBOX outperforms existing methods like "Segment Anything Model" by 10%. Finally, when applied in training, models annotated with PBA exhibit a 3% increase in the mean Average Precision (mAP) compared to those using traditional annotation methods. These results not only affirm the technical superiority of PBA but also its practical impact in advancing small object detection in remote sensing

The Role of Matrine and Mitogen-Ativated Protein Kinase/Extracellular Signal-Regulated Kinase Signal Transduction in the Inhibition of the Proliferation and Migration of Human Umbilical Veins Endothelial Cells Induced by Lung Cancer cells

Background and objective Matrine, one of the major alkaloid components of the traditional Chinese medicine Sophora roots, has a wide range of pharmacological effects including anti-inflammatory activities, growth inhibition and induction of cell differentiation and apoptosis. Motigen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) has found to be a crucial signaling pathway in endothelial cells. The aim of this study is to investigate the role of Matrine and MAPK/ERK signal transduction in the inhibition of the proliferation and migration of human umbilical veins endothelial cells (HUVECs) induced by lung cancer cells. Methods HUVECs were cultured with A549CM. Mat or PD98059 (i.e PD), specific inhibitor of MAPK/ERK, was added into the A549CM. The proliferation of the HUVECs was measured by cell counting. The migration of the HUVECs was observed by wound healing assay. The expression levels of ERK and p-ERK protein were detected by Western Blot analysis. Results On 24 hours after intervention, the A549CM significantly stimulated the proliferation, migration and expression of p-ERK of HUVECs. Compared with the A549CM group, Mat significantly inhibited the proliferation, migration and p-ERK expression of HUVECs induced by A549CM. While PD only decreased the proliferation and p-ERK expression of HUVECs induced by A549CM. PD had no effect in the migration of HUVECs. Conclusion The results demonstrated that Mat and PD98059 can effectively decrease proliferation and expression of p-ERK of HUVECs induced by A549CM. Furthermore Mat can also inhibit migration of HUVECs induced by A549CM that did not changed by PD98059. These data implied that suppressing MAPK/ERK signal transduction may play the crucial role in resisting lung cacinoma angiogenesis with Mat

Rapid detection of multi-QR codes based on multistage stepwise discrimination and a compressed mobilenet.

Poor real-time performance in multi-QR codes detection has been a bottleneck in QR code decoding based Internet-of-Things (IoT) systems. To tackle this issue, we propose in this paper a rapid detection approach, which consists of Multistage Stepwise Discrimination (MSD) and a Compressed MobileNet. Inspired by the object category determination analysis, the preprocessed QR codes are extracted accurately on a small scale using the MSD. Guided by the small scale of the image and the end-to-end detection model, we obtain a lightweight Compressed MobileNet in a deep weight compression manner to realize rapid inference of multi-QR codes. The Average Detection Precision (ADP), Multiple Box Rate (MBR) and running time are used for quantitative evaluation of the efficacy and efficiency. Compared with a few state-of-the-art methods, our approach has higher detection performance in rapid and accurate extraction of all the QR codes. The approach is conducive to embedded implementation in edge devices along with a bit of overhead computation to further benefit a wide range of real-time IoT applications

Performance of compact plastic scintillator strips with WLS-fiber and PMT/SiPM readout

This work presents the design and performance study of compact strips of plastic scintillator with WLS-fiber readout in a dimension of 0.1 * 0.02 * 2 m3, which evaluates as a candidate for cosmic-ray muon detector for JUNO-TAO. The strips coupling with 3-inch PMTs are measured and compared between the single-end and double-end readout options first, and the strip of double-end option coupling with SiPM is further measured and compared with the results of that with the PMTs. The performance of the strips determined by a detailed survey along their length with cosmic-ray muon after a detailed characterization of the used 3-inch PMTs and SiPMs.The proposed compact strip of plastic scintillator with WLS-fiber coupling with SiPM provides a good choice for cosmic-ray muon veto detector for limited detector dimension in particular

Coherent narrow-band light source for miniature endoscopes.

In this work, we report the successful implementation of a coherent narrow-band light source for miniature endoscopy applications. An RGB laser module that provides much higher luminosity than traditional incoherent white light sources is used for illumination, taking advantages of the laser light's high spatial coherence for efficient light coupling. Notably, the narrow spectral band of the laser light sources also enables spectrally resolved imaging, to distinguish certain biological tissues or components. A monochrome CMOS camera is employed to synchronize with the time lapsed RGB laser module illumination for color image acquisition and reconstruction, which provides better spatial resolution than a color CMOS camera of comparable pixel number, in addition to spectral resolving

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe

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

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

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

A cross-layer cognitive radio-based framework and CAC scheme in WiMAX networks

Quality of service (QoS) provisioning is an important issue in the deployment of broadband wireless access networks with real-time and non-real-time traffic integration. The Connection Admission Control (CAC) operation is essential to guarantee the QoS requirements of connections while achieving system efficiency. Cognitive Radio is seen as a solution to the current low usage of the radio spectrum and the problem of the fixed spectrum allocation. In this paper, we propose a novel cross-layer Cognitive Radio-based QoS support framework and Cognitive Radio-based CAC scheme in WiMAX point-to-multipoint systems. By using a cross-layer approach, the proposed solution can intelligently explore unused spectrums and spread to non-active spectrums to improve the capacity of the system significantly and provide QoS guaranteed service to real-time traffic. A queueing analytical modeling for the WiAMX system has been carried out. The key system performance parameters are obtained based on the queueing analytical model theoretically. Extensive simulation experiments have been carried out to evaluate the performance of our proposal. The simulation results show that our proposed solution can expand the capacity of WiMAX systems up to two times while providing QoS guaranteed service to real-time and non-real-time traffics