Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie

Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis

BACKGROUND: The treatment of trigger finger so far has heavily relied on clinicians’ evaluations for the severity of patients’ symptoms and the functionality of affected fingers. However, there is still a lack of pathological evidence supporting the criteria of clinical evaluations. This study’s aim was to correlate clinical classification and pathological changes for trigger finger based on the tissue abnormality observed from microscopic images. METHODS: Tissue samples were acquired, and microscopic images were randomly selected and then graded by three pathologists and two physicians, respectively. Moreover, the acquired images were automatically analyzed to derive two quantitative parameters, the size ratio of the abnormal tissue region and the number ratio of the abnormal nuclei, which can reflect tissue abnormality caused by trigger finger. A self-developed image analysis system was used to avoid human subjectivity during the quantification process. Finally, correlations between the quantitative image parameters, pathological grading, and clinical severity classification were assessed. RESULTS: One-way ANOVA tests revealed significant correlations between the image quantification and pathological grading as well as between the image quantification and clinical severity classification. The Cohen’s kappa coefficient test also depicted good consistency between pathological grading and clinical severity classification. CONCLUSIONS: The criteria of clinical classification were found to be highly associated with the pathological changes of affected tissues. The correlations serve as explicit evidence supporting clinicians in making a treatment strategy of trigger finger. In addition, our proposed computer-aided image analysis system was considered to be a promising and objective approach to determining trigger finger severity at the microscopic level

Prevalence and molecular characterization of plasmidmediated beta-lactamase genes among nosocomial Staphylococcus aureus isolated in Taiwan

Purpose: To analyze the drug susceptibility phenotypes and the patterns of plasmid-mediated β- lactamase genes among nosocomial Staphylococcus aureus drug resistance isolates in Taiwan.Methods: The antibiotic susceptibilities of 617 clinical Staphylococcus aureus isolates collected from 2005 - 2009 from Chiayi Christian Hospital (Chiayi, Taiwan) were examined in vitro against 8 antimicrobial agents using agar diffusion method. Among the clinical isolates, 114 strains of methicillinsensitive Staphylococcus aureus and 45 strains of methicillin-resistant Staphylococcus aureus (MRSA) isolates were selected for plasmid profile analysis. The patterns of β-lactamase genes presented in plasmids were investigated by polymerase chain reaction analysis.Results: Most test strains were resistant to multiple antibiotics, particularly for the traditional agents such as ampicillin, penicillin, cephalexin and kanamycin. Plasmid profile analysis revealed that up to 36 % of the clinical strains harbored plasmids and were able to develop multi-drug resistant. Among them, most of the isolates harbored at least one plasmid (range 1 – 7) with a size range of 2.3 to 23 Kb. Among the several types of β-lactamases, blaTEM was the most prevalent.Conclusion: The results obtained from this study can serve as a valuable reference for the future control for clinical antibiotic resistant strains and more thorough discussions on resistance mechanisms.Keywords: Staphylococcus aureus, Antibiotic susceptibility, Nosocomial pathogens, Plasmid profile, β- lactamase

Price Discovery in the Chinese Gold Market

This study conducts price discovery analysis in the Chinese gold market. Our result indicates that the price discovery in Chinese gold market occurs predominantly in the futures market. The result is robust to the different measures of price discovery, namely information share, component share, and information leadership share. Partitioning the daily trades into three trading sessions, we find that the dominance of the futures market occurs in all trading sessions. We further investigate the sequential price discovery within the spot market or futures market. We find that the price discovery of gold spot market and gold futures market occur in the night trading session

RhoGDIβ-induced hypertrophic growth in H9c2 cells is negatively regulated by ZAK

We found that overexpression of RhoGDIβ, a Rho GDP dissociation inhibitor, induced hypertrophic growth and suppressed cell cycle progression in a cultured cardiomyoblast cell line. Knockdown of RhoGDIβ expression by RNA interference blocked hypertrophic growth. We further demonstrated that RhoGDIβ physically interacts with ZAK and is phosphorylated by ZAK in vitro, and this phosphorylation negatively regulates RhoGDIβ functions. Moreover, the ZAK-RhoGDIβ interaction may maintain ZAK in an inactive hypophosphorylated form. These two proteins could negatively regulate one another such that ZAK suppresses RhoGDIβ functions through phosphorylation and RhoGDIβ counteracts the effects of ZAK by physical interaction. Knockdown of ZAK expression in ZAK- and RhoGDIβ-expressing cells by ZAK-specific RNA interference restored the full functions of RhoGDIβ

Evolution‐informed modeling improves outcome prediction for cancers

Despite wide applications of high‐throughput biotechnologies in cancer research, many biomarkers discovered by exploring large‐scale omics data do not provide satisfactory performance when used to predict cancer treatment outcomes. This problem is partly due to the overlooking of functional implications of molecular markers. Here, we present a novel computational method that uses evolutionary conservation as prior knowledge to discover bona fide biomarkers. Evolutionary selection at the molecular level is nature’s test on functional consequences of genetic elements. By prioritizing genes that show significant statistical association and high functional impact, our new method reduces the chances of including spurious markers in the predictive model. When applied to predicting therapeutic responses for patients with acute myeloid leukemia and to predicting metastasis for patients with prostate cancers, the new method gave rise to evolution‐informed models that enjoyed low complexity and high accuracy. The identified genetic markers also have significant implications in tumor progression and embrace potential drug targets. Because evolutionary conservation can be estimated as a gene‐specific, position‐specific, or allele‐specific parameter on the nucleotide level and on the protein level, this new method can be extended to apply to miscellaneous “omics” data to accelerate biomarker discoveries.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135247/1/eva12417_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135247/2/eva12417.pd

A Systematic Review of Recreation Therapy for Depression in Older Adults

Background: Recreation therapy (RT) provides a flexible and powerful treatment for depression associated with aging. This article reviewed the effectiveness of RT to treat depression in older adults. Method: Five electronic databases were employed to identify interventional studies on RT in depressed older adults: Pubmed, PsycINFO, ProQuest, Academic Search Premier and ERIC. Articles were screened against inclusion criteria and assessed with respect to methodological quality. Results: A systematic literature review included 18 articles. Fourteen studies reported improvement in depression but 6 studies lack adequate significance in the positive effect of RT. Methodological quality assessment of 13 randomizedcontrolled trials and 5 non-controlled studies indicated an overall mean of 5.67 ± 1.94 points out of 9. Conclusion: There were positive findings that RT is effective in improving geriatric depression. Future investigation is encouraged to explore the mechanism between physical activity RT and depression improvement