A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction

This paper focuses on term-status pair extraction from medical dialogues (MD-TSPE), which is essential in diagnosis dialogue systems and the automatic scribe of electronic medical records (EMRs). In the past few years, works on MD-TSPE have attracted increasing research attention, especially after the remarkable progress made by generative methods. However, these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge, which demands a deeper understanding to model the relationship between terms and infer the status of each term. This paper presents a knowledge-enhanced two-stage generative framework (KTGF) to address the above challenges. Using task-specific prompts, we employ a single model to complete the MD-TSPE through two phases in a unified generative form: we generate all terms the first and then generate the status of each generated term. In this way, the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase, and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status generation. Furthermore, our proposed special status "not mentioned" makes more terms available and enriches the training data in the second phase, which is critical in the low-resource setting. The experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-resource settings.Comment: Published in Machine Intelligence Researc

VILAS: Exploring the Effects of Vision and Language Context in Automatic Speech Recognition

Enhancing automatic speech recognition (ASR) performance by leveraging additional multimodal information has shown promising results in previous studies. However, most of these works have primarily focused on utilizing visual cues derived from human lip motions. In fact, context-dependent visual and linguistic cues can also benefit in many scenarios. In this paper, we first propose ViLaS (Vision and Language into Automatic Speech Recognition), a novel multimodal ASR model based on the continuous integrate-and-fire (CIF) mechanism, which can integrate visual and textual context simultaneously or separately, to facilitate speech recognition. Next, we introduce an effective training strategy that improves performance in modal-incomplete test scenarios. Then, to explore the effects of integrating vision and language, we create VSDial, a multimodal ASR dataset with multimodal context cues in both Chinese and English versions. Finally, empirical results are reported on the public Flickr8K and self-constructed VSDial datasets. We explore various cross-modal fusion schemes, analyze fine-grained crossmodal alignment on VSDial, and provide insights into the effects of integrating multimodal information on speech recognition.Comment: Accepted to ICASSP 202

A van der Waals pn heterojunction with organic/inorganic semiconductors

van der Waals (vdW) heterojunctions formed by two-dimensional (2D) materials have attracted tremendous attention due to their excellent electrical/optical properties and device applications. However, current 2D heterojunctions are largely limited to atomic crystals, and hybrid organic/inorganic structures are rarely explored. Here, we fabricate hybrid 2D heterostructures with p-type dioctylbenzothienobenzothiophene (C8-BTBT) and n-type MoS2. We find that few-layer C8-BTBT molecular crystals can be grown on monolayer MoS2 by vdW epitaxy, with pristine interface and controllable thickness down to monolayer. The operation of the C8-BTBT/MoS2 vertical heterojunction devices is highly tunable by bias and gate voltages between three different regimes: interfacial recombination, tunneling and blocking. The pn junction shows diode-like behavior with rectifying ratio up to 105 at the room temperature. Our devices also exhibit photovoltaic responses with power conversion efficiency of 0.31% and photoresponsivity of 22mA/W. With wide material combinations, such hybrid 2D structures will offer possibilities for opto-electronic devices that are not possible from individual constituents.Comment: 16 pages, 4 figure

Optimal epidemic information dissemination in uncertain dynamic environment

Optimization of stochastic epidemic information dissemination plays a significant role in enhancing the reliability of epidemic networks. This letter proposes a multi-stage decision making optimization model for stochastic epidemic information dissemination based on dynamic programming, in which uncertainties in a dynamic environment are taken into account. We model the inherent bimodal dynamics of general epidemic mechanisms as a Markov chain, and a state transition equation is proposed based on this Markov chain. We further derive optimal policies and a theoretical closed-form expression for the maximal expected number of successfully delivered messages. The properties of the derived model are theoretically analyzed. Simulation results show an improvement in reliability, in terms of accumulative number of successfully delivered messages, of epidemic information dissemination in stochastic situations

Validation of Facial Action Unit for Happy Emotion Detection

One alternative to measure happiness is to use facial expression by measuring facial muscle movement namely facial coding unit or action unit. Rarely studies found to verify validity the action unit of happiness. Accordingly, we held one group pretest posttest experimental design to test the specificity and sensitivity facial expression of happiness. We applied a video experimental paradigm to stimulate facial happiness expression. Openface software was used to measure facial action unit. The participants of this research were 203 Indonesia university students. Happiness emotion stimuli was measured by single item with a scale 0- 10. To calculate the specificity and sensitivity we employed ROC (Receiver Operating Curve) statistical technique. Our result shown inconsistent finding for AU6 and AU12 due to Facial Coding Unit System (FCUS) to detect happy emotion. The co-occurrence of other emotion and individual differences in interpreting stimuli influenced the validity of measuremen

Effectiveness and safety of hydrogen inhalation as an adjunct treatment in Chinese type 2 diabetes patients: A retrospective, observational, double-arm, real-life clinical study

AimTo analyze the effectiveness and safety of hydrogen inhalation (HI) therapy as an adjunct treatment in Chinese type 2 diabetes mellitus (T2DM) patients in a real-life clinical setting.MethodsThis observational, non-interventional, retrospective, double-arm, 6-month clinical study included T2DM patients receiving conventional anti-diabetes medication with or without HI initiation from 2018 to 2021. Patients were assigned to the HI group or non-HI group (control group) after 1:1 propensity score matching (PSM). The mean change in glycated hemoglobin (HbA1c) after 6 months in different groups was evaluated primarily. The secondary outcome was composed of the mean change of fasting plasma glucose (FPG), weight, lipid profile, and homeostasis model assessment. Logistics regression was performed to evaluate the likelihood of reaching different HbA1c levels after 6-month treatment between the groups. Adverse event (AE) was also evaluated in patients of both groups.ResultsIn total, 1088 patients were selected into the analysis. Compared to the control group, subjects in HI group maintained greater improvement in the level of HbA1c (-0.94% vs -0.46%), FPG (-22.7 mg/dL vs -11.7 mg/dL), total cholesterol (-12.9 mg/dL vs -4.4 mg/dL), HOMA-IR (-0.76 vs -0.17) and HOMA-β (8.2% vs 1.98%) with all p< 0.001 post the treatment. Logistics regression revealed that the likelihood of reaching HbA1c< 7%, ≥ 7% to< 8% and > 1% reduction at the follow-up period was higher in the HI group, while patients in the control group were more likely to attain HbA1c ≥ 9%. Patients in HI group was observed a lower incidence of several AEs including hypoglycemia (2.0% vs 6.8%), vomiting (2.6% vs 7.4%), constipation (1.7% vs 4.4%) and giddiness (3.3% vs 6.3%) with significance in comparison to the control group.ConclusionHI as an adjunct therapy ameliorates glycemic control, lipid metabolism, insulin resistance and AE incidence of T2DM patients after 6-month treatment, presenting a noteworthy inspiration to existing clinical diabetic treatment

Preventive Effect of Lactobacillus paracasei FZU103 on Alcoholic Liver Injury in Mice

Objective: To explore the preventive effect of Lactobacillus paracasei FZU103 (LP-FZU103) on alcoholic liver injury (ALI). Methods: Altogether 36 specific pathogen free- (SPF-) grade ICR mice were randomly divided into three groups: control, model and experimental (LP-FZU103 intervention). After the six-week experiment, body mass, organ coefficients, serum and liver biochemical indexes, liver histopathology and inflammatory cytokines, the transcription of liver function-related genes and intestinal flora composition were measured. Results: Compared with the model group, intervention of LP-FZU103 improved the organ coefficients and pathological liver damage in ALI mice, significantly reduced the levels of total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) as well as the activity of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the serum, increased the serum concentration of high-density lipoprotein cholesterol (HDL-C), significantly increased the activity of catalase (CAT) and superoxide dismutase (SOD) and the content of glutathione (GSH) in the liver, and decreased MDA content and interleukin-6 (IL-6), interferon-γ (IFN-γ) levels in the liver. Moreover, LP-FZU103 intervention significantly up-regulated the mRNA expression level of the lipid metabolism-related gene Ldlr and down-regulated the mRNA expression level of Acc1, Hmgcr and Cd36 as well as increased the relative abundance of beneficial bacteria such as Lactobacillus johnsonii, Lactobacillus reuteri and Lactobacillus paracasei in the gut of mice. Conclusion: LP-FZU103 intervention can prevent and control the occurrence of alcoholic liver injury in mice, which is closely related to the improved intestinal flora and liver metabolic function

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Spatial Differences and Influential Factors of Urban Carbon Emissions in China under the Target of Carbon Neutrality

Cities are areas featuring a concentrated population and economy and are major sources of carbon emissions (CEs). The spatial differences and influential factors of urban carbon emissions (UCEs) need to be examined to reduce CEs and achieve the target of carbon neutrality. This paper selected 264 cities at the prefecture level in China from 2008 to 2018 as research objects. Their UCEs were calculated by the CE coefficient, and the spatial differences in them were analyzed using exploratory spatial data analysis (ESDA). The influential factors of UCEs were studied with Geodetector. The results are as follows: (1) The UCEs were increasing gradually. Cities with the highest CEs over the study period were located in the urban agglomerations of Beijing–Tianjin–Hebei, Yangtze River Delta, Pearl River Delta, middle reaches of the Yangtze River, and Chengdu–Chongqing. (2) The UCEs exhibited certain global and local spatial autocorrelations. (3) The industrial structure was the dominant factor influencing UCEs

A Comprehensive Investigation on the Fire Hazards and Environmental Risks in a Commercial Complex Based on Fault Tree Analysis and the Analytic Hierarchy Process

This paper focuses on the fire risk assessment for commercial complex, as the variety of fire accidental triggers inside could be a big threat to the public fire safety, leading to catastrophic loss in human lives and properties. Both the qualitative and quantitative analysis were imposed on a typical large commercial complex to recognize the potential fire-causative factors in this paper. Applying the fault tree analysis, the basic events leading to fire are acquired, and they are then further reclassified based on the analytic hierarchy process. Taking the damage of the accident as the target layer and the fire-causative factors, the equipment operation factors and firefighting factors as the criterion layer, the assessment index is well established. The risk of each factor is quantitatively evaluated, and the effect of each factor on the target layer is analyzed. The result of the fault tree analysis and analytic hierarchy process shows good consistency, in which human behavior is the main factor leading to the fire occurrence, followed by the combustible material, the rescue speed and the staff assignment factors. The results are beneficial for general decisions and measures in public fire safety management