Using Pattern Recognition for Investment Decision Support in Taiwan Stock Market

In Taiwan stock market, it has been accumulated large amounts of time series stock data and successful investment strategies. The stock price, which is impacted by various factors, is the result of buyer-seller investment strategies. Since the stock price reflects numerous factors, its pattern can be described as the strategies of investors. In this paper, pattern recognition concept is adapted to match the current stock price trend with the repeatedly appearing past price data. Accordingly, a new method is introduced in this research that extracting features quickly from stock time series chart to find out the most critical feature points. The matching can be processed via the corresponding information of the feature points. In other words, the goal is to seek for the historical repeatedly appearing patterns, namely the similar trend, offering the investors to make investment strategies

The association of molecular typing, vancomycin MIC, and clinical outcome for patients with methicillin-resistant Staphylococcus aureus infections

AbstractBackground/PurposeThere are reports of an increase in vancomycin minimum inhibitory concentration (MIC) against methicillin-resistant Staphylococcus aureus (MRSA) over time, a phenomenon referred to as “MIC creep”, but some studies have conflicting results. The aim of this study is to evaluate the association of molecular typing, vancomycin MIC, and clinical outcome for patients with MRSA infections.MethodsThirty-two MRSA isolates from Taichung Veterans General Hospital (TCVGH), Taichung, Taiwan during the period of 2003 to 2008 were analyzed for the association of sequence typing, vancomycin MIC, and the correlated clinical outcome for patients with MRSA infections. The vancomycin MICs of 28 additional isolates from 2014 were used for the detection of MIC creep.ResultsAmong the genotypes of 32 isolates, there were 17 (53.1%) isolates with ST239-SCCmecIII, seven (21.9%) isolates with ST5-SCCmecII, six (18.8%) isolates with ST59-SCCmecIV, and two (6.2%) isolates with ST59-SCCmecVT. Two isolates had an MIC of 2 μg/mL and were identified as ST239-SCCmecIII. No statistically significant change in the distribution of MICs of all isolates was observed between 2003 and 2014 (p = 0.263). There was no significant difference in the mortality rates between two groups of patients with vancomycin MICs < 2 μg/mL and ≥ 2 μg/mL (p = > 0.99).ConclusionThere was no vancomycin MIC creep in the period from 2003 to 2014 in this study. Appropriate prognostic models for assessment of the association among sequence types, vancomycin MICs, and clinical outcome warrant further investigation

Successful treatment of an early invasive oral squamous cell carcinoma with topical 5-aminolevulinic acid-mediated photodynamic therapy

Our previous studies showed successful treatment of a series of 36 oral verrucous hyperplasia lesions and of an extensive oral verrucous carcinoma with a topical 5-aminolevulinic acid (ALA)-mediated photodynamic therapy (topical ALA-PDT) protocol (with a fluence rate of 100 mW/cm2 and a light exposure dose of 100 J/cm2) using a 635-nm light-emitting diode (LED) light source. In this case report, we tested whether an enhanced topical ALA-PDT protocol (with a fluence rate of 200 mW/cm2 and a light exposure dose of 200 J/cm2) could be used to treat an early invasive oral squamous cell carcinoma (OSCC) with a verrucous appearance of the left lower posterior edentulous alveolar mucosa of a 67-year-old male former areca-quid chewer and ex-smoker. The main verrucous lesion showed complete regression after eight treatments with PDT. However, 10 extra treatments were needed to eradicate the multiple residual leukoplakia lesions on the edentulous alveolar mucosa. Moderate to severe post-PDT pain was noted during the initial eight treatments, and the patient needed analgesics (codeine phosphate, 30 mg three times daily) to control the pain. No recurrence of the OSCC lesion was found after a follow-up period of 4 years. We suggest that our enhanced topical ALA-PDT protocol may have good potential to be used as a treatment of choice for a superficially invasive OSCC without regional or distant metastasis before the commencement of other effective therapies

High-throughput Automated Muropeptide Analysis (HAMA) Reveals Peptidoglycan Composition of Gut Microbial Cell Walls

Peptidoglycan (PGN), a net-like polymer constituted by muropeptides, provides protection for microorganisms and has been a major target for antibiotics for decades. Researchers have explored host-microbiome interactions through PGN recognition systems and discovered key muropeptides modulating host responses. However, most common characterization techniques for muropeptides are labor-intensive and require manual analysis of mass spectra due to the complex cross-linked PGN structures. Each species has unique moiety modifications and inter-/intra-bridges, which further complicates the structural analysis of PGN. Here, we developed a high-throughput automated muropeptide analysis (HAMA) platform leveraging tandem mass spectrometry and in silico muropeptide MS/MS fragmentation matching to comprehensively identify muropeptide structures, quantify their abundance, and infer PGN cross-linking types. We demonstrated the effectiveness of HAMA platform using well-characterized PGNs from E. coli and S. aureus and further applied it to common gut bacteria including Bifidobacterium, Bacteroides, Lactobacillus, Enterococcus, and Akkermansia muciiniphila. Specifically, we found that the stiffness and strength of the cell envelopes may correspond to the lengths and compositions of interpeptide bridges within Bifidobacterium species. In summary, the HAMA framework exhibits an automated, intuitive, and accurate analysis of PGN compositions, which may serve as a potential tool to investigate the post-synthetic modifications of saccharides, the variation in interpeptide bridges, and the types of cross-linking within bacterial PGNs.</p

A Study of Developing a System Dynamics Model for the Learning Effectiveness Evaluation

[[abstract]]This study used the research method of system dynamics and applied the Vensim software to develop a learning effectiveness evaluation model. This study developed four cause-and-effect chains affecting learning effectiveness, including teachers’ teaching enthusiasm, family involvement, school’s implementation of scientific activities, and creative teaching method, as well as the system dynamics model based on the four cause-and-effect chains. Based on the developed system dynamic model, this study performed simulation to investigate the relationship among family involvement, learning effectiveness, teaching achievement, creative teaching method, and students’ learning interest. The results of this study verified that there are positive correlations between family involvement and students’ learning effectiveness, as well as students’ learning effectiveness and teachers’ teaching achievements. The results also indicated that the use of creative teaching method is able to increase students’ learning interest and learning achievement.[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]電子版[[countrycodes]]US