Document Recommendation in Organizations with Personal Folders

In organizations, knowledge workers usually have their own personal folders that store and organize needed codified knowledge (textual documents) in taxonomy. In such personal folder environments, providing knowledge workers needed knowledge from other workers’ folders is important to facilitate knowledge sharing. This work adopts recommendation techniques to provide knowledge workers needed textual documents from other workers folders. Experiments are conducted to verify the performance of various methods using data collected from a research institute laboratory. The result shows that the CBF approach outperforms other methods

Effects of condensed tannins from Leucaena on methane reduction, rumen fermentation and populations of methaogens and protozoa in vitro

Different levels of purified condensed tannins (CT) extracted from Leucaena leucocephala hybrid-Rendang (LLR) were investigated for their effects on CH4 production, rumen fermentation parameters such as pH, dry matter (DM) degradability, N disappearance and volatile fatty acid (VFA) concentrations, as well as on populations of rumen methanogenic archaea and protozoa in vitro. Purified CT concentrations of 0 (control), 10, 15, 20, 25 and 30 mg, and 500 mg of oven dried guinea grass (Panicum maximum) with 40 ml of buffered rumen fluid were incubated for 24 h using an in vitro gas production procedure. Total gas (ml/g DM) decreased at a decreasing rate (linear P < 0.01; quadratic P < 0.05) with increased levels of CT inclusion. CH4 production (ml/g DM) decreased at a decreasing rate (linear P < 0.01; quadratic P < 0.01) with increasing levels of CT. Total VFA concentration (mmol/L) decreased at a decreasing rate (linear P < 0.01; quadratic P < 0.01) with increasing CT inclusions. In vitro DM degradation and N disappearance declined linearly (P < 0.01) with increasing levels of CT. Estimates of rumen methanogenic archaea and protozoa populations using microbiological methods and real-time PCR assay showed linear reductions in total methanogens (P < 0.01) and total protozoa (P < 0.01) with increasing levels of CT. Methanogens in the order Methanobacteriales also declined, but with quadratic and cubic aspects. Results suggest that CT from LLR at a relatively low level of 15 mg of CT/500 mg DM reduce CH4 production by 47%, with only 7% reduction in degradation of feed DM. However, higher CT inclusions, while further reducing CH4 emissions, have substantive negative effects on DM digestibility

Antimicrobial susceptibility patterns among Escherichia coli urinary isolates from community-onset health care-associated urinary tract infection

Urinary tract infection (UTI) is traditionally classified as community-acquired (CA) and hospital-acquired (HA). Community-onset health care-associated (HCA) infection is a new category that has gained increasing attention. The study aimed to compare the disk susceptibility of nonrepetitive Escherichia coli urinary isolates from HCA-UTI (n = 100) with that of E. coli isolates from CA-UTI (n = 85) and HA-UTI (n = 106). We found that the susceptibility pattern of HCA-UTI E. coli isolates was similar to that of HA-UTI E. coli isolates, but significantly different from that of CA-UTI E. coli isolates. In particular, the proportion of extended-spectrum β-lactamase-producing isolates was significantly higher in HCA-UTI than that in CA-UTI (30.0% vs. 3.5%, p < 0.001). We recommend that when treating HCA-UTI, it is necessary to take urine cultures for susceptibility testing to guide definite antibiotic therapy

Serum selenium concentration is associated with metabolic factors in the elderly: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Selenium is an essential micronutrient known for its antioxidant function. However, the association of serum selenium with lipid profiles and fasting glucose are inconsistent in populations with average intake of selenium. Furthermore, there were few studies conducted specifically for the elderly. This study examined the relationship of serum selenium concentration with serum lipids and fasting glucose in the Taiwanese elderly population.</p> <p>Methods</p> <p>This was a cross-sectional study of 200 males and females aged 65-85 years (mean 71.5 ± 4.6 years) from Taipei, Taiwan. Serum selenium was measured by inductively coupled plasma-mass spectrometer. The association between serum selenium and metabolic factors was examined using a multivariate linear regression analysis after controlling several confounders.</p> <p>Results</p> <p>The mean serum selenium concentration was 1.14 μmol/L, without significant difference between sexes. Total cholesterol, triglycerides, and LDL cholesterol increased significantly with serum selenium concentration (<it>P </it>< 0.001, <it>P </it>< 0.05 and <it>P </it>< 0.001, respectively) after adjusting for age, gender, anthropometric indices, lifestyle factors, and cardio-vascular risk factors in several linear regression models. Furthermore, there was a significantly positive association between serum selenium and serum fasting glucose concentrations (<it>P </it>< 0.05).</p> <p>Conclusions</p> <p>Total cholesterol, triglycerides, and LDL cholesterol, and fasting serum glucose concentrations increased significantly with serum selenium concentration in the Taiwanese elderly. The underlying mechanism warrants further research.</p

Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources

For languages with no annotated resources, transferring knowledge from rich-resource languages is an effective solution for named entity recognition (NER). While all existing methods directly transfer from source-learned model to a target language, in this paper, we propose to fine-tune the learned model with a few similar examples given a test case, which could benefit the prediction by leveraging the structural and semantic information conveyed in such similar examples. To this end, we present a meta-learning algorithm to find a good model parameter initialization that could fast adapt to the given test case and propose to construct multiple pseudo-NER tasks for meta-training by computing sentence similarities. To further improve the model's generalization ability across different languages, we introduce a masking scheme and augment the loss function with an additional maximum term during meta-training. We conduct extensive experiments on cross-lingual named entity recognition with minimal resources over five target languages. The results show that our approach significantly outperforms existing state-of-the-art methods across the board.Comment: This paper is accepted by AAAI2020. Code is available at https://github.com/microsoft/vert-papers/tree/master/papers/Meta-Cros

Highly porous chitosan beads embedded with silver-graphene oxide nanocomposites for antibacterial application

Incorporation of silver nanomaterial into polymer matrix can further accomplished their potential usage in real life applications. In our previous study, silver nanoparticles (AgNPs) and silver-graphene oxide nanocomposites (AgGO) were prepared via a rapid microwave-assisted method. Hereby, the as-synthesized AgNPs or AgGO was dispersed in a chitosan solution. Subsequently, the resultant mixture solution was further coagulated in a coagulation bath containing sodium hydroxide via a neutralization process. This resulted in the formation of spherical-shaped chitosan beads. The structure of the beads showed that the chitosan beads embedded with AgGO exhibited a more porous structure as compared to the plain chitosan beads. Furthermore, the chitosan beads containing AgNPs or AgGO were tested for their antibacterial activity against Escherichia coli and Staphylococcus aureus. The antibacterial results indicated that the silver nanomaterial contained chitosan beads could effectively inhibit the growth of both E. coli and S. aureus as compared to the bare chitosan beads. The produced chitosan nanocomposite envisioned that can be potentially employed for water disinfection purpose