Relation Based Access Control in Campus Social Network System

AbstractAs one of the most popular network applications, online social network system has gained huge adoption in the past few years. Campus social network system is a special type of social network system which focuses on providing information communication, knowledge sharing, and online collaboration services to campus users in colleges and universities. In this paper, we discuss the design of relation based access control in campus social network system which is decided by the collective efforts system designers, system administrators, and especially users of the system. Generally speaking, relation based access control in campus social network system is defined in terms of users can establish relationships; and they can also assign relation based permissions on information and resources when they release them. It consists of user-centered access control and group-centered access control which deal with access control of information and resources released in users’ personal space and groups’ shared space respectively. Once a campus social network system is put online, access control in it is actually decided by the collective intelligence of its users. Specifically, it's built upon collective intelligence that is reflected through users’ identity, their social relationships and permissions that they set on their profile and created content. In a word, relation based access control in campus social network system adopts a collective intelligence model

A Combined Markov Chain Model and Generalized Projection Nonnegative Matrix Factorization Approach for Fault Diagnosis

The presence of sets of incomplete measurements is a significant issue in the real-world application of multivariate statistical process monitoring models for industrial process fault detection. Since the missing data in the incomplete measurements are usually correlated with some of the available variables, these measurements can be used if an efficient algorithm is presented. To resolve the problem, a novel method combining Markov chain model and generalized projection nonnegative matrix factorization (MCM-GPNMF) is proposed to detect and diagnose the faults in industrial process. The basic idea of the approach is to use MCM-GPNMF to extract the dominant variables from incomplete process data and to combine them with statistical process monitoring techniques. TG2 and SPEG statistics are defined as online monitoring quantities for fault detection and corresponding contribution plots are also considered for fault isolation. The proposed method is applied to a 1000 MW unit boiler process. The simulation results clearly illustrate the feasibility of the proposed method

Spear or Shield: Leveraging Generative AI to Tackle Security Threats of Intelligent Network Services

Generative AI (GAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. Despite their numerous applications and potential, such models create opportunities for novel security challenges. In this paper, we examine the challenges and opportunities of GAI in the realm of the security of intelligent network AIGC services such as suggesting security policies, acting as both a ``spear'' for potential attacks and a ``shield'' as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GAI's spear and shield roles, highlighting two primary categories of potential GAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GAI in enhancing network security

New Broad-Spectrum Viral Fusion Inhibitors Act by Deleterious Effect on the Viral Membrane through the Production Singlet Oxygen Molecules

Chitosan oligosaccharides (COS), the degraded products of chitosan, have been demonstrated to have versatile biological functions. In primary studies, it has displayed significant adjuvant effects when mixed with other vaccines. In this study, chitosan oligosaccharides with different deacetylation degrees were prepared and conjugated to porcine circovirus type 2 (PCV2) subunit vaccine to enhance its immunogenicity. The vaccine conjugates were designed by the covalent linkage of COSs to PCV2 molecules and administered to BALB/c mice three times at two-week intervals. The results indicate that, as compared to the PCV2 group, COS-PCV2 conjugates remarkably enhanced both humoral and cellular immunity against PCV2 by promoting lymphocyte proliferation and initiating a mixed T-helper 1 (Th1)/T-helper 2 (Th2) response, including raised levels of PCV2-specific antibodies and an increased production of inflammatory cytokines. Noticeably, with the increasing deacetylation degree, the stronger immune responses to PCV2 were observed in the groups with COS-PCV2 vaccination. In comparison with NACOS (chitin oligosaccharides)-PCV2 and LCOS (chitosan oligosaccharides with low deacetylation degree)-PCV2, HCOS (chitosan oligosaccharides with high deacetylation degree)-PCV2 showed the highest adjuvant effect, even comparable to that of PCV2/ISA206 (a commercialized adjuvant) group. In summary, COS conjugation might be a viable strategy to enhance the immune response to PCV2 subunit vaccine, and the adjuvant effect was positively correlated with the deacetylation degree of COS.</p

Morphology of Novel Chitosan Oligosaccharides Mod-ified Cross-linked Polyvinyl Alcohol Complex Foam (COS/cPVACF) Dressings with Fully Open-cell and Open-channel Microstructures via Active Molecules Cleaning Process for Wound Managements

The design of medical devices could be applied and developed for new treatment proce-dures instead of the traditional therapy procedures

Obesity and acute type A aortic dissection: unraveling surgical outcomes through the lens of the upper hemisternotomy approach

BackgroundAcute type A aortic dissection (ATAAD) is a pressing cardiovascular emergency necessitating prompt surgical intervention. Obesity, a pervasive health concern, has been identified as a significant risk factor for ATAAD, introducing unique surgical challenges that can influence postoperative outcomes. This study aimed to investigate the outcomes of ATAAD surgery across various body mass index (BMI) categories, focusing on the implications of the upper hemisternotomy (UHS) approach.MethodsBetween April 2017 and October 2023, 229 patients diagnosed with ATAAD underwent aortic arch intervention via UHS at the General Hospital of Northern Theater Command. Based on BMI (WS/T 428-2013), patients were categorized into normal weight, overweight, and obese. The primary outcomes included perioperative parameters, intraoperative details, and postoperative complications, with specific emphasis on hypoxemia, defined by the Berlin criteria as a PaO2/FiO2 ratio of ≤300 mmHg.ResultsThe average age of the cohort was 50.1 ± 11.2 years with a male predominance (174 males). Preoperatively, 49.0% presented with hypoxemia, with the Obese group exhibiting a significantly elevated rate (77.9%, P &lt; 0.001). Postoperatively, while the Normal group demonstrated a lower thoracic drainage volume 24 h post-surgery [180.0 (140.0) ml; P &lt; 0.001], the Obese group indicated prolonged durations for mechanical ventilation and ICU stay, without statistical significance. Unlike the Normal and Overweight groups, the Obese group showed no notable changes in pre- and postoperative PaO2/FiO2 ratio. No significant difference was observed in severe postoperative complications among the groups. Further ROC curve analysis identifies a BMI cutoff of 25.5 for predicting postoperative hypoxemia, with 76.3% sensitivity and 84.4% specificity. And multivariate analysis reveals BMI and preoperative hypoxemia as independent predictors of postoperative hypoxemia.ConclusionObesity, although presenting unique challenges in ATAAD interventions, does not necessarily portend adverse outcomes when managed with meticulous surgical planning and postoperative care. The study emphasizes the significance of individualized patient assessment and tailoring surgical strategies, suggesting the potential of UHS in addressing the surgical intricacies posed by obesity in ATAAD patients. Further research is warranted to consolidate these findings

Ultrafast ion sieving using nanoporous polymeric membranes

The great potential of nanoporous membranes for water filtration and chemical separation has been challenged by the trade-off between selectivity and permeability. Here we report on nanoporous polymer membranes with an excellent balance between selectivity and perme- ability of ions. Our membranes are fabricated by irradiating 2-μm-thick polyethylene ter- ephthalate Lumirror® films with GeV heavy ions followed by ultraviolet exposure. These membranes show a high transport rate of K+ ions of up to 14 mol h−1 m−2 and a selectivity of alkali metal ions over heavy metal ions of >500. Combining transport experiments and molecular dynamics simulations with a polymeric nanopore model, we demonstrate that the high permeability is attributable to the presence of nanopores with a radius of ~0.5 nm and a density of up to 5 × 1010 cm−2, and the selectivity is ascribed to the interaction between the partially dehydrated ions and the negatively charged nanopore wall.This work was supported by National Science Foundation of China (Grant Nos. 11335003 and 31670852) and the National Magnetic Confinement Fusion Energy Research Project of China (2015GB113000). F.L. acknowledges the support from Peking University’s 100-talent plan. P.K. acknowledges the Australian Research Council for financial support. Christina Trautmann acknowledges support from the Deutsche Forschungsgemeinschaft (DFG-FOR1583

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

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