MirrorNet: Bio-Inspired Camouflaged Object Segmentation

Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this paper, we propose a novel bio-inspired network, named the MirrorNet, that leverages both instance segmentation and mirror stream for the camouflaged object segmentation. Differently from existing networks for segmentation, our proposed network possesses two segmentation streams: the main stream and the mirror stream corresponding with the original image and its flipped image, respectively. The output from the mirror stream is then fused into the main stream's result for the final camouflage map to boost up the segmentation accuracy. Extensive experiments conducted on the public CAMO dataset demonstrate the effectiveness of our proposed network. Our proposed method achieves 89% in accuracy, outperforming the state-of-the-arts. Project Page: https://sites.google.com/view/ltnghia/research/camoComment: Under Revie

Targeting Radioresistant Breast Cancer Cells by Single Agent CHK1 Inhibitor via Enhancing Replication Stress

Radiotherapy (RT) remains a standard therapeutic modality for breast cancer patients. However, intrinsic or acquired resistance limits the efficacy of RT. Here, we demonstrate that CHK1 inhibitor AZD7762 alone significantly inhibited the growth of radioresistant breast cancer cells (RBCC). Given the critical role of ATR/CHK1 signaling in suppressing oncogene-induced replication stress (RS), we hypothesize that CHK1 inhibition leads to the specific killing for RBCC due to its abrogation in the suppression of RS induced by oncogenes. In agreement, the expression of oncogenes c-Myc/CDC25A/c-Src/H-ras/E2F1 and DNA damage response (DDR) proteins ATR/CHK1/BRCA1/CtIP were elevated in RBCC. AZD7762 exposure led to significantly higher levels of RS in RBCC, compared to the parental cells. The mechanisms by which CHK1 inhibition led to specific increase of RS in RBCC were related to the interruptions in the replication fork dynamics and the homologous recombination (HR). In summary, RBCC activate oncogenic pathways and thus depend upon mechanisms controlled by CHK1 signaling to maintain RS under control for survival. Our study provided the first example where upregulating RS by CHK1 inhibitor contributes to the specific killing of RBCC, and highlight the importance of the CHK1 as a potential target for treatment of radioresistant cancer cells

Targeting Radioresistant Breast Cancer Cells by Single Agent CHK1 Inhibitor via Enhancing Replication Stress

Radiotherapy (RT) remains a standard therapeutic modality for breast cancer patients. However, intrinsic or acquired resistance limits the efficacy of RT. Here, we demonstrate that CHK1 inhibitor AZD7762 alone significantly inhibited the growth of radioresistant breast cancer cells (RBCC). Given the critical role of ATR/CHK1 signaling in suppressing oncogene-induced replication stress (RS), we hypothesize that CHK1 inhibition leads to the specific killing for RBCC due to its abrogation in the suppression of RS induced by oncogenes. In agreement, the expression of oncogenes c-Myc/CDC25A/c-Src/H-ras/E2F1 and DNA damage response (DDR) proteins ATR/CHK1/BRCA1/CtIP were elevated in RBCC. AZD7762 exposure led to significantly higher levels of RS in RBCC, compared to the parental cells. The mechanisms by which CHK1 inhibition led to specific increase of RS in RBCC were related to the interruptions in the replication fork dynamics and the homologous recombination (HR). In summary, RBCC activate oncogenic pathways and thus depend upon mechanisms controlled by CHK1 signaling to maintain RS under control for survival. Our study provided the first example where upregulating RS by CHK1 inhibitor contributes to the specific killing of RBCC, and highlight the importance of the CHK1 as a potential target for treatment of radioresistant cancer cells

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

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

Camouflaged Object Segmentation in Images

Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this thesis, we propose a novel bio-inspired network, named the CamoNet, that leverages both instance segmentation and adversarial attack for the camouflaged object segmentation. Differently from existing networks for segmentation, our proposed network possesses two segmentation streams: the main stream and the adversarial stream corresponding with the original image and its flipped image, respectively. The output from the adversarial stream is then fused into the main stream\u27s result for the final camouflage map to boost up the segmentation accuracy. We also introduce the Data Augmentation in the Wild to solve the data insufficiency for network training. Extensive experiments conducted on the public CAMO dataset demonstrate the effectiveness of our proposed network. Our proposed method achieves 89% in accuracy, significantly outperforming the state-of-the-arts

Camouflaged Object Segmentation in Images

Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this thesis, we propose a novel bio-inspired network, named the CamoNet, that leverages both instance segmentation and adversarial attack for the camouflaged object segmentation. Differently from existing networks for segmentation, our proposed network possesses two segmentation streams: the main stream and the adversarial stream corresponding with the original image and its flipped image, respectively. The output from the adversarial stream is then fused into the main stream\u27s result for the final camouflage map to boost up the segmentation accuracy. We also introduce the Data Augmentation in the Wild to solve the data insufficiency for network training. Extensive experiments conducted on the public CAMO dataset demonstrate the effectiveness of our proposed network. Our proposed method achieves 89% in accuracy, significantly outperforming the state-of-the-arts

Design for Stakeholder Value Identification in Multi-stakeholder Projects: The SVI Process

With the rapid development of society, complex problems are becoming increasingly visible such as climate change, energy shortage, poverty, and migration. Many organizations are cooperating together to solve these problems because it is impossible for one organization to handle all the different expertise and skills. The projects that consist of lots of organizations working together to solve problems can be called multi-stakeholder projects. It appears aiming to solve complex social challenges of sustainable development. With multiple stakeholders, the stakeholder management becomes more difficult. It is essential to know what does each stakeholder desires for enhancing collaboration and satisfying stakeholders. Among these desires, stakeholders desired values are crucial to identify because values are the reason behind stakeholders’ actions and decisions. The LIFE project is a typical multi-stakeholder project initiate by the City of Amsterdam and AMS Institute as the leader of Stakeholder Engagement and Inclusion. As an important part of stakeholder engagement in multi-stakeholder projects, this project aims to make contributions in identifying stakeholders’ desired values in the multi-stakeholder project. The Barrett Model about organizational values is the key academic support of this project. It’s used as materials to build the concept structure and as the basic for developing details of concepts. Literature from some other fields has been studied in this project to generate insights for eliciting desired values from stakeholders. This project ends with a final strategy concept, the Stakeholder Value Identification (SVI) Process, which applies various intervention to increase stakeholders’ willingness and ability to express their desired values and uses a closed-ended task as the core of the concept. The concept could be used not only in this stage of the LIFE project but also other stages, as well as other multi-stakeholder projects.Integrated Product Desig

Dual-Frequency Polarized Reconfigurable Terahertz Antenna Based on Graphene Metasurface and TOPAS

A hybrid dual-frequency polarized reconfigurable terahertz antenna is designed and studied. Graphene and TOPAS are employed as the polarization conversion metasurface and dielectric substrate, respectively, enabling tunable polarization conversion and circular polarization. TOPAS is a good substrate material for broadband THz components due to its low absorption. By adjusting the chemical potential of graphene between 0 eV and 0.5 eV, the polarization state in the band of 1 THz (0.76–1.02 THz) and 2.5 THz (2.43–2.6 THz) can be reconstructed. Thanks to the multilayer graphene structure and low absorption TOPAS, the graphene metasurface exhibits a broad bandwidth of 0.26 and 0.17 THz, respectively, in the band of 1 THz and 2.5 THz. The working state of the circularly polarized antenna and linearly polarized antenna can be switched in the bands around 1 THz (0.7–0.75 THz, 0.96–1.04 THz) and 2.5 THz (2.42–2.52 THz), respectively, without changing the physical geometry. Moreover, the graphene antenna, metasurface, and hybrid structure are tested, respectively, to verify that the components do not interfere with each other in performance. The hybrid antenna shows great potential in tunable terahertz devices and related applications