Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarks

The research of open-domain dialog systems has been greatly prospered by neural models trained on large-scale corpora, however, such corpora often introduce various safety problems (e.g., offensive languages, biases, and toxic behaviors) that significantly hinder the deployment of dialog systems in practice. Among all these unsafe issues, addressing social bias is more complex as its negative impact on marginalized populations is usually expressed implicitly, thus requiring normative reasoning and rigorous analysis. In this paper, we focus our investigation on social bias detection of dialog safety problems. We first propose a novel Dial-Bias Frame for analyzing the social bias in conversations pragmatically, which considers more comprehensive bias-related analyses rather than simple dichotomy annotations. Based on the proposed framework, we further introduce CDail-Bias Dataset that, to our knowledge, is the first well-annotated Chinese social bias dialog dataset. In addition, we establish several dialog bias detection benchmarks at different label granularities and input types (utterance-level and context-level). We show that the proposed in-depth analyses together with these benchmarks in our Dial-Bias Frame are necessary and essential to bias detection tasks and can benefit building safe dialog systems in practice

MCR-ALS-based muscle synergy extraction method combined with LSTM neural network for motion intention detection

IntroductionThe time-varying and individual variability of surface electromyographic signals (sEMG) can lead to poorer motor intention detection results from different subjects and longer temporal intervals between training and testing datasets. The consistency of using muscle synergy between the same tasks may be beneficial to improve the detection accuracy over long time ranges. However, the conventional muscle synergy extraction methods, such as non-negative matrix factorization (NMF) and principal component analysis (PCA) have some limitations in the field of motor intention detection, especially in the continuous estimation of upper limb joint angles.MethodsIn this study, we proposed a reliable multivariate curve-resolved-alternating least squares (MCR-ALS) muscle synergy extraction method combined with long-short term memory neural network (LSTM) to estimate continuous elbow joint motion by using the sEMG datasets from different subjects and different days. The pre-processed sEMG signals were then decomposed into muscle synergies by MCR-ALS, NMF and PCA methods, and the decomposed muscle activation matrices were used as sEMG features. The sEMG features and elbow joint angular signals were input to LSTM to establish a neural network model. Finally, the established neural network models were tested by using sEMG dataset from different subjects and different days, and the detection accuracy was measured by correlation coefficient.ResultsThe detection accuracy of elbow joint angle was more than 85% by using the proposed method. This result was significantly higher than the detection accuracies obtained by using NMF and PCA methods. The results showed that the proposed method can improve the accuracy of motor intention detection results from different subjects and different acquisition timepoints.DiscussionThis study successfully improves the robustness of sEMG signals in neural network applications using an innovative muscle synergy extraction method. It contributes to the application of human physiological signals in human-machine interaction

EVALUATION OF ANALGESIC AND ANTI-INFLAMMATORY ACTIVITIES OF COMPOUND HERBS PUXING YINYANG SAN

Background: Bovine mastitis is one of the most relevant and problematic diseases to treat and control in practice. Puxing Yinyang San (PYS) is a compound of herbs to treat bovine mastitis in China. This study was performed to evaluate the analgesic and anti-inflammatory activities of PYS in mice and rats. Materials and Methods: The analgesic and anti-inflammatory activities of PYS were determined using acetic acid-induced writhing response, hot plate test, xylene-induced ear swelling test, carrageenan-induced paw edema test, and acetic acid-induced capillary permeability and leukocyte infiltration test with oral doses of 155, 310 and 620 mg/kg·bw in mice or rats. Results: The acetic acid-induced writhing response was dose-dependently inhibited by oral administration of PYS and the latency time to thermal stimuli was increased in the hot plate test, especially 90 minutes after treatment. In the xylene-induced ear swelling, PYS significantly decreased swelling degree in a dose-dependent manner. Additionally, PYS significantly suppressed the peritoneal capillary permeability and leukocyte infiltration in mice induced by intraperitoneal injection of acetic acid. PYS also significantly reduced the carrageenan-induced rat paw edema at 2, 3, and 4 h after the carrageenan injection. The results suggested that PYS possessed significant analgesic and anti-inflammatory activities. Conclusion: This study was the first to demonstrate that oral administration of PYS might play an important role in the process of analgesia and anti-inflammation, supporting its treatment for mastitis. Future investigations will focus on the broader involvement of the ingredients and mechanisms responsible for pharmacological activities of PYS

Providing HIV-related services in China for men who have sex with men.

PROBLEM: In China, human immunodeficiency virus (HIV) care provided by community-based organizations and the public sector are not well integrated. APPROACH: A community-based organization and experts from the Guangzhou Center for Disease Control and Prevention developed internet-based services for men who have sex with men, in Guangzhou, China. The internet services were linked to clinical services offering HIV testing and care. LOCAL SETTING: The expanding HIV epidemic among men who have sex with men is a public health problem in China. HIV control and prevention measures are implemented primarily through the public system. Only a limited number of community organizations are involved in providing HIV services. RELEVANT CHANGES: The programme integrated community and public sector HIV services including health education, online HIV risk assessment, on-site HIV counselling and testing, partner notification, psychosocial care and support, counting of CD4+ T-lymphocytes and treatment guidance. LESSONS LEARNT: The internet can facilitate HIV prevention among a subset of men who have sex with men by enhancing awareness, service uptake, retention in care and adherence to treatment. Collaboration between the public sector and the community group promoted acceptance by the target population. Task sharing by community groups can increase access of this high-risk group to available HIV-related services

A Survey of Chinese Pig Farms and Human Healthcare Isolates Reveals Separate Human and Animal Methicillin-Resistant Staphylococcus aureus Populations.

There has been increasing concern that the overuse of antibiotics in livestock farming is contributing to the burden of antimicrobial resistance in people. Farmed animals in Europe and North America, particularly pigs, provide a reservoir for livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA ST398 lineage) found in people. This study is designed to investigate the contribution of MRSA from Chinese pig farms to human infection. A collection of 483 MRSA are isolated from 55 farms and 4 hospitals in central China, a high pig farming density area. CC9 MRSA accounts for 97.2% of all farm isolates, but is not present in hospital isolates. ST398 isolates are found on farms and hospitals, but none of them formed part of the "LA-MRSA ST398 lineage" present in Europe and North America. The hospital ST398 MRSA isolate form a clade that is clearly separate from the farm ST398 isolates. Despite the presence of high levels of MRSA found on Chinese pig farms, the authors find no evidence of them spilling over to the human population. Nevertheless, the ST398 MRSA obtained from hospitals appear to be part of a widely distributed lineage in China. The new animal-adapted ST398 lineage that has emerged in China is of concern

Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

Nuclear facilities have a regulatory requirement to measure radiation levels within Post Operational Cleanout (POCO) around nuclear facilities each year, resulting in a trend towards robotic deployments to gain an improved understanding during nuclear decommissioning phases. The UK Nuclear Decommissioning Authority supports the view that human-in-the-loop robotic deployments are a solution to improve procedures and reduce risks within radiation haracterisation of nuclear sites. We present a novel implementation of a Cyber-Physical System (CPS) deployed in an analogue nuclear environment, comprised of a multi-robot team coordinated by a human-in-the-loop operator through a digital twin interface. The development of the CPS created efficient partnerships across systems including robots, digital systems and human. This was presented as a multi-staged mission within an inspection scenario for the heterogeneous Symbiotic Multi-Robot Fleet (SMuRF). Symbiotic interactions were achieved across the SMuRF where robots utilised automated collaborative governance to work together where a single robot would face challenges in full characterisation of radiation. Key contributions include the demonstration of symbiotic autonomy and query-based learning of an autonomous mission supporting scalable autonomy and autonomy as a service. The coordination of the CPS was a success and displayed further challenges and improvements related to future multi-robot fleets

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