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

The Impacts Of Presentation Modes And Product Involvements On “Line” Short Message Service (SMS) Advertising Effectiveness

In today’s ubiquitous commerce (UC) era, short message service (SMS) advertisement has played an important role in the world of marketing. Convenience and economical reasons influence SMS usage frequency along with social involvement to influence attitudes towards SMS advertising. SMS advertising creates numerous opportunities for the marketers in promoting their products effectively. Adopting the competition for attention theory as the theoretical framework, we developed hypotheses to investigate the influences of presentation mode and involvement on SMS advertising performance (recall of advertising information). An experiment was conducted to examine the effects of three types of information presentation modes (text-only, image-text, and emoji-text) in the contexts of two product types (high- versus low-involvement products) in the “LINE” SMS environment. Specifically, in this current study, we allocate participants to six experimental environments (text-only for high-involvement products, text-only for low-involvement products, image-text for high-involvement products, image-text for low-involvement products, emoji-text for high-involvement products and emoji-text for low-involvement products) randomly to collected empirical data to examine the proposed hypotheses. The research findings are expected to provide instrumental guidelines for the practitioners to better achieve the goals of ads in the “LINE” SMS environment. Also, the empirical results may provide insights into the research of advertising interface design of SMS and integrating efforts from cognitive science and vision research to understand users’ involvement of SMS advertising processes

Designing primers and evaluation of the efficiency of propidium monoazide – Quantitative polymerase chain reaction for counting the viable cells of Lactobacillus gasseri and Lactobacillus salivarius

AbstractThe purpose of this study is to evaluate the efficiency of using propidium monoazide (PMA) real-time quantitative polymerase chain reaction (qPCR) to count the viable cells of Lactobacillus gasseri and Lactobacillus salivarius in probiotic products. Based on the internal transcription spacer and 23S rRNA genes, two primer sets specific for these two Lactobacillus species were designed. For a probiotic product, the total deMan Rogosa Sharpe plate count was 8.65±0.69 log CFU/g, while for qPCR, the cell counts of L. gasseri and L. salivarius were 8.39±0.14 log CFU/g and 8.57±0.24 log CFU/g, respectively. Under the same conditions, for its heat-killed product, qPCR counts for L. gasseri and L. salivarius were 6.70±0.16 log cells/g and 7.67±0.20 log cells/g, while PMA-qPCR counts were 5.33±0.18 log cells/g and 5.05±0.23 log cells/g, respectively. For cell dilutions with a viable cell count of 8.5 log CFU/mL for L. gasseri and L. salivarius, after heat killing, the PMA-qPCR count for both Lactobacillus species was near 5.5 log cells/mL. When the PMA-qPCR counts of these cell dilutions were compared before and after heat killing, although some DNA might be lost during the heat killing, significant qPCR signals from dead cells, i.e., about 4–5 log cells/mL, could not be reduced by PMA treatment. Increasing PMA concentrations from 100 μM to 200 μM or light exposure time from 5 minutes to 15 minutes had no or, if any, only minor effect on the reduction of qPCR signals from their dead cells. Thus, to differentiate viable lactic acid bacterial cells from dead cells using the PMA-qPCR method, the efficiency of PMA to reduce the qPCR signals from dead cells should be notable

AGROBEST: an efficient Agrobacterium-mediated transient expression method for versatile gene function analyses in Arabidopsis seedlings

Background: Transient gene expression via Agrobacterium-mediated DNA transfer offers a simple and fast method to analyze transgene functions. Although Arabidopsis is the most-studied model plant with powerful genetic and genomic resources, achieving highly efficient and consistent transient expression for gene function analysis in Arabidopsis remains challenging. Results: We developed a highly efficient and robust Agrobacterium-mediated transient expression system, named AGROBEST (Agrobacterium-mediated enhanced seedling transformation), which achieves versatile analysis of diverse gene functions in intact Arabidopsis seedlings. Using β-glucuronidase (GUS) as a reporter for Agrobacterium-mediated transformation assay, we show that the use of a specific disarmed Agrobacterium strain with vir gene pre-induction resulted in homogenous GUS staining in cotyledons of young Arabidopsis seedlings. Optimization with AB salts in plant culture medium buffered with acidic pH 5.5 during Agrobacterium infection greatly enhanced the transient expression levels, which were significantly higher than with two existing methods. Importantly, the optimized method conferred 100% infected seedlings with highly increased transient expression in shoots and also transformation events in roots of ~70% infected seedlings in both the immune receptor mutant efr-1 and wild-type Col-0 seedlings. Finally, we demonstrated the versatile applicability of the method for examining transcription factor action and circadian reporter-gene regulation as well as protein subcellular localization and protein–protein interactions in physiological contexts. Conclusions: AGROBEST is a simple, fast, reliable, and robust transient expression system enabling high transient expression and transformation efficiency in Arabidopsis seedlings. Demonstration of the proof-of-concept experiments elevates the transient expression technology to the level of functional studies in Arabidopsis seedlings in addition to previous applications in fluorescent protein localization and protein–protein interaction studies. In addition, AGROBEST offers a new way to dissect the molecular mechanisms involved in Agrobacterium-mediated DNA transfer

Monitoring Apnea in the Elderly by an Electromechanical System with a Carbon Nanotube-based Sensor

SummaryBackgroundBreathing, a part of respiration, is one of the vital functions. Breathing disorders are common in the elderly. An effective breathing sensor for real-time detection of apnea is important in clinical critical care. We aimed to construct a real-time warning platform with a combination of carbon nanotubes (CNTs) and related nano-electromechanical system (NEMS) for elderly care.MethodsThrough a specific acid-treated procedure, multiwalled carbon nanotubes (MWCNTs) were immobilized on a thin silicon dioxide (SiO2) film, coated on a heated silicon wafer. Techniques of photolithography and sputtering with chromium and gold were then implemented on the MWCNT film to develop micro-interdigitated electrodes as a base for the breathing sensor. The sensor was equipped with a programmed microchip processor to become a warning detector for abnormal human breathing, namely less than six breaths per minute. Elderly volunteers were enrolled for examining the effective sensitivity of this novel electromechanical device.ResultsThere were 15 elderly volunteers (9 males and 6 females) tested in this experiment. The dynamic analyses of the MWCNT sensor to exhaled breath showed that it had characteristics of rapid response, high aspect ratio, small tip ratio, and high electrical conductivity. Responses of the MWCNT sensor to exhaled breath was recorded according to different performance parameters, i.e., strength, frequency, flow rate, and breath components. In this study, variable pattern-simulated tests showed that a MWCNT sensor combined with a processor could accurately evoke warning signals (100% of sensitivity rate), indicating its effectiveness and usefulness for detecting abnormal breathing rates, especially apnea.ConclusionOur results showed that a new device composed of an NEMS by combining an MWCNT sensor and complementary metal-oxide semiconductor (CMOS) circuits could be integrated to effectively detect apnea in the elderly. This novel device may improve the pattern of safe respiratory care for the elderly in the future

Areca Users in Combination with Tobacco and Alcohol Use Are Associated with Younger Age of Diagnosed Esophageal Cancer in Taiwanese Men

BACKGROUND: Whether the habitual use of substances (tobacco, alcohol, or areca nut (seed of the Areca palm)) can affect the age of esophageal squamous cell carcinoma (ESCC) presentation has rarely been examined. METHODS: The study subjects were those who were males and the first time to be diagnosed as ESCC (ICD-9 150) and who visited any of three medical centers in Taiwan between 2000 and 2009. A standardized questionnaire was used to collect substance uses and other variables. RESULTS: Mean age (±SD) at presentation of ESCC was 59.2 (±11.3) years in a total of 668 cases. After adjusting for other covariates, alcohol drinkers were 3.58 years younger to have ESCC than non-drinkers (p = 0.002). A similar result was found among areca chewers, who were 6.34 years younger to have ESCC than non-chewers (p<0.0001), but not among cigarette smokers (p = 0.10). When compared to the group using 0-1 substances, subjects using both cigarettes and alcohol were nearly 3 years younger to contract ESCC. Furthermore, those who use areca plus another substance were 7-8 years younger. Subjects using all three substances had the greatest age difference, 9.20 years younger (p<0.0001), compared to the comparison group. CONCLUSION: Our findings suggest that habitually consuming tobacco, alcohol, and areca nut can influence the age-onset of ESCC. Since the development of ESCC is insidious and life-threatening, our observation is worthy to be reconfirmed in the large-scale and long-term follow-up prospective cohort studies to recommend the screening strategy of this disease

Application and comparison of scoring indices to predict outcomes in patients with healthcare-associated pneumonia

Introduction: Healthcare-associated pneumonia HCAP is a relatively new category of pneumonia. It refers to infections that occur prior to hospital admission in patients with specific risk factors following contact or exposure to a healthcare environment. There is currently no scoring index to predict the outcomes of HCAP patients. We applied and compared different community acquired pneumonia CAP scoring indices to predict 30-day mortality and 3-day and 14-day intensive care unit ICU admission in patients with HCAP. Methods: We conducted a retrospective cohort study based on an inpatient database from six medical centers, recruiting a total of 444 patients with HCAP between 1 January 2007 and 31 December 2007. Pneumonia severity scoring indices including PSI pneumonia severity index, CURB 65 confusion, urea, respiratory rate, blood pressure , age 65, IDSA/ATS Infectious Diseases Society of America/American Thoracic Society, modified ATS rule, SCAP severe community acquired pneumonia, SMART-COP systolic blood pressure, multilobar involvement, albumin, respiratory rate, tachycardia, confusion, oxygenation, pH, SMRT- CO systolic blood pressure, multilobar involvement, respiratory rate, tachycardia, confusion, oxygenation, and SOAR systolic blood pressure, oxygenation, age, respiratory rate were calculated for each patient. Patient characteristics, co-morbidities, pneumonia pathogen culture results, length of hospital stay LOS, and length of ICU stay were also recorded. Results: PSI > 90 has the highest sensitivity in predicting mortality, followed by CURB-65 >= 2 and SCAP > 9 SCAP score area under the curve AUC: 0.71, PSI AUC: 0.70 and CURB-65 AUC: 0.66. Compared to PSI, modified ATS, IDSA/ATS, SCAP, and SMART-COP were easy to calculate. For predicting ICU admission Day 3 and Day 14, modified ATS AUC: 0.84, 0.82 , SMART-COP AUC: 0.84, 0.82, SCAP AUC: 0.82, 0.80 and IDSA/ ATS AUC: 0.80, 0 .79 performed better statistically significant difference than PSI, CURB- 65, SOAR and SMRT-CO. Conclusions: The utility of the scoring indices for risk assessment in patients with healthcare-associated pneumonia shows that the scoring indices originally designed for CAP can be applied to HCAP