Domain Agnostic Real-Valued Specificity Prediction

Sentence specificity quantifies the level of detail in a sentence, characterizing the organization of information in discourse. While this information is useful for many downstream applications, specificity prediction systems predict very coarse labels (binary or ternary) and are trained on and tailored toward specific domains (e.g., news). The goal of this work is to generalize specificity prediction to domains where no labeled data is available and output more nuanced real-valued specificity ratings. We present an unsupervised domain adaptation system for sentence specificity prediction, specifically designed to output real-valued estimates from binary training labels. To calibrate the values of these predictions appropriately, we regularize the posterior distribution of the labels towards a reference distribution. We show that our framework generalizes well to three different domains with 50%~68% mean absolute error reduction than the current state-of-the-art system trained for news sentence specificity. We also demonstrate the potential of our work in improving the quality and informativeness of dialogue generation systems.Comment: AAAI 2019 camera read

Learning Deep Latent Spaces for Multi-Label Classification

Multi-label classification is a practical yet challenging task in machine learning related fields, since it requires the prediction of more than one label category for each input instance. We propose a novel deep neural networks (DNN) based model, Canonical Correlated AutoEncoder (C2AE), for solving this task. Aiming at better relating feature and label domain data for improved classification, we uniquely perform joint feature and label embedding by deriving a deep latent space, followed by the introduction of label-correlation sensitive loss function for recovering the predicted label outputs. Our C2AE is achieved by integrating the DNN architectures of canonical correlation analysis and autoencoder, which allows end-to-end learning and prediction with the ability to exploit label dependency. Moreover, our C2AE can be easily extended to address the learning problem with missing labels. Our experiments on multiple datasets with different scales confirm the effectiveness and robustness of our proposed method, which is shown to perform favorably against state-of-the-art methods for multi-label classification.Comment: published in AAAI-201

Generating Dialogue Responses from a Semantic Latent Space

Existing open-domain dialogue generation models are usually trained to mimic the gold response in the training set using cross-entropy loss on the vocabulary. However, a good response does not need to resemble the gold response, since there are multiple possible responses to a given prompt. In this work, we hypothesize that the current models are unable to integrate information from multiple semantically similar valid responses of a prompt, resulting in the generation of generic and uninformative responses. To address this issue, we propose an alternative to the end-to-end classification on vocabulary. We learn the pair relationship between the prompts and responses as a regression task on a latent space instead. In our novel dialog generation model, the representations of semantically related sentences are close to each other on the latent space. Human evaluation showed that learning the task on a continuous space can generate responses that are both relevant and informative.Comment: EMNLP 202

Reliability and validity of the Chinese version of the Suicide Caring Competence Scale (SCCS) for family caregivers: Scale development

Session presented on Saturday, July 26, 2014: Purpose: To develop a Chinese version of the Suicide Caring Competence Scale (SCCS) for family Caregivers and to examine its reliability and validity. Methods: The study was a cross-sectional questionnaire survey. Participants came from a Suicide Prevention Center and two acute psychiatric hospitals in Taiwan. A convenience sample of 165 caregivers of people who attempted suicide. To be eligible to participate participants had to be a primary caregiver of people who had attempted suicide and be over 18 years of age. The questionnaire consisted of the Chinese version of the 20-item SCCS, developed by the authors and was based on a previous qualitative study. Item analysis was used to delete redundant items. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to examine the construct validity. The association between educational level and SCCS was used to examine the concurrent validity of SCCS. Cronbach\u27s alpha and test-retest reliability were examined to understand the reliability of SCCS. The study was conducted in 2008 and 2009. Results: EFA and CFA indicated that a second-order factorial model with five subscales and 19 items best fit the data. The five subscales were proactive prevention, daily living care, seeking assistance from professional resources, seeking assistance from laypersons, and seeking assistance from religious resources. The higher the educational level, the higher the SCCS was. Cronbach\u27s alpha and test-retest reliability of total and subscales ranged from 0.67 to 0.90 and from 0.62 to 0.82, respectively. The SCCS had acceptable validity and reliability. Conclusion: The Chinese version of SCCS has satisfactory reliability and validity. Nurses could use the SCCS to assess the family caregivers\u27 competence and provide proper education to improve their caring competence for their suicidal relatives

The long-term effects of a suicidal education intervention for family members of the suicidal patients

Purpose: The purpose of this study was to evaluate the longitudinal (one year after education) effects of a suicide care education intervention on the suicidal family\u27s caregivers. Methods: A quasi-experimental approach adopted using three instruments for testing the suicide care education intervention. The three instruments are: (1) the suicidal caring ability Scale (2) the caring stress Scale (3) the suicide attitudes Scale. The experimental group attended a two-hour personal information session and received an education handbook on caring for suicidal outpatients when beginning this research and the control group received routine discharge information. There was not any intervention after the three months suicide care education. The sample was recruited from the one suicide prevention center and psychiatric wards of two hospitals from April 2010 until May 2011 and was randomly assigned to experimental or control group. The total sample group for evaluating the longitudinal effects of a suicide care education intervention was 80 family members and was divided into an experimental group (n=36) and a control group (n=44). Data was analyzed using the Statistic Package for the Social Science 17.0 version. Descriptive statistic and Friedman method were used. Results: Results showed that the demographic data were no significant difference except age, working condition, and occupation between the experiment and control groups. The result for the longitudinal effects of a suicide care education intervention demonstrated that there was a statistically significant differences in variables related to \u27utilizing resources\u27. Our data indicate that the experimental group who attended the psycho-education program had an increased ability to utilize resources for their relatives who had attempted suicide. Conclusion: This suicide education only increased suicidal family members\u27 ability in utilizing resources after one year of education intervention. Therefore, health professionals should provide continual suicidal education to help suicidal family members take care of suicidal outpatients

Supercritical Fluid Extract of Spent Coffee Grounds Attenuates Melanogenesis through Downregulation of the PKA, PI3K/Akt, and MAPK Signaling Pathways

The mode of action of spent coffee grounds supercritical fluid CO2extract (SFE) in melanogenesis has never been reported. In the study, the spent coffee grounds were extracted by the supercritical fluid CO2extraction method; the chemical constituents of the SFE were investigated by gas chromatography-mass spectrometry (GC-MS). The effects of the SFE and its major fatty acid components on melanogenesis were evaluated by mushroom tyrosinase activity assay and determination of intracellular tyrosinase activity and melanin content. The expression level of melanogenesis-related proteins was analyzed by western blotting assay. The results revealed that the SFE of spent coffee grounds (1–10 mg/mL) and its major fatty acids such as linoleic acid and oleic acid (6.25–50 μM) effectively suppressed melanogenesis in the B16F10 murine melanoma cells. Furthermore, the SFE decreased the expression of melanocortin 1 receptor (MC1R), microphthalmia-associated transcription factor (MITF), tyrosinase, tyrosinase-related protein-1 (TRP-1), and tyrosinase-related protein-2 (TRP-2). The SFE also decreased the protein expression levels of p-JNK, p-p38, p-ERK, and p-CREB. Our results revealed that the SFE of spent coffee grounds attenuated melanogenesis in B16F10 cells by downregulation of protein kinase A (PKA), phosphatidylinositol-3-kinase (PI3K/Akt), and mitogen-activated protein kinases (MAPK) signaling pathways, which may be due to linoleic acid and oleic acid.</jats:p

Cytochrome P450 Metabolism of Betel Quid-Derived Compounds: Implications for the Development of Prevention Strategies for Oral and Pharyngeal Cancers

Betel quid (BQ) products, with or without tobacco, have been classified by the International Agency for Research on Cancer (IARC) as group I human carcinogens that are associated with an elevated risk of oral potentially malignant disorders (OPMDs) and cancers of the oral cavity and pharynx. There are estimated 600 million BQ users worldwide. In Taiwan alone there are 2 million habitual users (approximately 10% of the population). Oral and pharyngeal cancers result from interactions between genes and environmental factors (BQ exposure). Cytochrome p450 (CYP) families are implicated in the metabolic activation of BQ- and areca nut-specific nitrosamines. In this review, we summarize the current knowledge base regarding CYP genetic variants and related oral disorders. In clinical applications, we focus on cancers of the oral cavity and pharynx and OPMDs associated with CYP gene polymorphisms, including CYP1A1, CYP2A6, CYP2E1, and CYP26B1. Our discussion of CYP polymorphisms provides insight into the importance of screening tests in OPMDs patients for the prevention of oral and pharyngeal cancers. Future studies will establish a strong foundation for the development of chemoprevention strategies, polymorphism-based clinical diagnostic tools (e.g., specific single-nucleotide polymorphism (SNP) “barcodes”), and effective treatments for BQ-related oral disorders