On monitoring of multiple non-linear profiles

Most state-of-the-art profile monitoring methods involve studies of one profile. However, a process may contain several sensors or probes that generate multiple profiles over time. Quality characteristics presented in multiple profiles may be related multiple aspects of product or process quality. Existing charting methods for simultaneous monitoring of each multiple profile may result in high false alarm rates. Or worse, they cannot correctly detect potential relationship changes among profiles. In this study, we propose two approaches to detect process shifts in multiple non-linear profiles. A simulation study was conducted to evaluate the performance of the proposed approaches in terms of average run length under different process shift scenarios. Pros and cons of the proposed methods are discussed. A guideline for choosing the proposed methods is introduced. In addition, a hybrid method combining the salient points of both approaches is explored. Finally, a real-world data-set from a vulcanisation process is used to demonstrate the implementation of the proposed methods

Development of a Immunobiosensor for Noninvasive Prostate Cancer Detection

[[abstract]]2008年全球男性癌症死因中，前列腺癌佔居世界主要癌症死因第二位。依行政院衛生署的統計資料顯示，前列腺癌自民國95年至98年，已連續四年位居臺灣男性主要癌症死因第七位。本研究的目的在於研發一種短時間內即時測量前列腺癌標誌物－前列腺特異抗原之阻抗變化的生物感測器。其原理為結合電阻抗技術與免疫反應原理，發展出一種非侵入矩陣型阻抗式前列腺特異抗原免疫生物感測器。生物感測器包括感測器基材製作與生物分子固定化兩部分。感測器基材製作需經過銀線路、碳抗氧化保護層印刷及卡典西德線路保護層共三道製程；生物分子固定化則是戊二醛固定與前列腺特異抗原相對抗體/牛血清白蛋白-磷酸鹽緩衝溶液固定與封存工作電極共兩道程序。在生物感測器製作完成後，開始對感測器進行各項評估測試，並由各個測試的結果中，找出感測器的最佳輸入頻率範圍、靈敏度、線性度與量測濃度範圍及矩陣型感測器之訊噪比增幅。在矩陣型感測器與單一型感測器同時進行生物分子的量測比較，其矩陣型感測器輸出的阻抗變化訊號可大幅度的增加，但感測靈敏度無太大的影響。檢測濃度與阻抗變化量經對數處理後，發現其阻抗變化量檢測線性度於2.36 MHz時呈現最佳值R^2 = 0.9953，且斜率（M值）為正，更進一步證實出隨著抗原濃度增加，其阻抗量測變化量也會隨之增加。在訊噪比之比較中發現，於前列腺特異抗原最低檢測濃度為6.25 ng/mL時，其矩陣型感測器較單一型的增幅提昇約250％。總而言之，將電阻抗量測技術應用於免疫生物感測器以檢測前列腺特異抗原濃度，極具有相當的發展潛力與可行性。[[abstract]]In Taiwan, 87.3 people of per 100,000 population died of prostate cancer, and the patients’ age were over 75 years old. Under the statistics composed by Department of Health, prostate cancer for the past four consecutive years（2006 ~ 2009）to the 7th place, become the cause of cancer deaths for Taiwan. Traditional invasive testing methods are costly and time-consuming. Therefore, the purpose of this study for develop a new low-cost biosensors and were based on the impedance methods with the immune response. Measurement of biomolecules in the same time then comparison array type sensors with single type sensors, the array sensor's output impedance signal can significantly increase, but no impact on sensing sensitivity. Detection concentration and the amount of impedance change after treatment of Logarithmic, found that the amount of impedance change's detection linearity showed the best values of 2.36 MHz, R^2 = 0.9953 and the slope (M value) was confirmed with the antigen's concentration increases, the amount of impedance changes will also increase. The immune biosensors in the minimum detectable concentration of 6.25 ng/mL, the array type's signal to noise ratio（SNR）increase of about 250% than single type. Overall, we can use these immune biosensors made by ourselves to conduct a objective and reliable prostate specific antigen detection.[[note]]碩

Real-time detection of wave profile changes

[[abstract]]A statistical process control (SPC) framework is proposed to detect potential changes of a wave profile on a real-time basis. In regular profile monitoring, change detection takes place when a complete profile is generated. In this study, the detection of a potential profile change takes place before the entire information on the profile of interest is fully available. The main research goal is to make a correct process decision as soon as possible. A real-world example of condensation-water-temperature profile monitoring was used to demonstrate the proposed framework. A simulation study was also conducted. The simulation results confirm that the proposed framework is capable of detecting profile changes without having to wait for the entire profile to be generated.[[notice]]補正完

Towards Accurate Identification of Antibiotic-Resistant Pathogens through the Ensemble of Multiple Preprocessing Methods Based on MALDI-TOF Spectra

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has been used to identify microorganisms and predict antibiotic resistance. The preprocessing method for the MS spectrum is key to extracting critical information from complicated MS spectral data. Different preprocessing methods yield different data, and the optimal approach is unclear. In this study, we adopted an ensemble of multiple preprocessing methods––FlexAnalysis, MALDIquant, and continuous wavelet transform-based methods––to detect peaks and build machine learning classifiers, including logistic regressions, naïve Bayes classifiers, random forests, and a support vector machine. The aim was to identify antibiotic resistance in Acinetobacter baumannii, Acinetobacter nosocomialis, Enterococcus faecium, and Group B Streptococci (GBS) based on MALDI-TOF MS spectra collected from two branches of a referral tertiary medical center. The ensemble method was compared with the individual methods. Random forest models built with the data preprocessed by the ensemble method outperformed individual preprocessing methods and achieved the highest accuracy, with values of 84.37% (A. baumannii), 90.96% (A. nosocomialis), 78.54% (E. faecium), and 70.12% (GBS) on independent testing datasets. Through feature selection, important peaks related to antibiotic resistance could be detected from integrated information. The prediction model can provide an opinion for clinicians. The discriminative peaks enabling better prediction performance can provide a reference for further investigation of the resistance mechanism

Statistical process control for monitoring nonlinear profiles: a six sigma project on curing process

Curing duration and target temperature are the most critical process parameters for high- pressure hose products. The air temperature collected in the curing chamber is represented in the form of a profile. A proper statistical process control (SPC) implementation needs to consider both numeric as well as profile quality characteristics. This paper describes a successful six sigma project in the context of statistical engineering for integrating SPC, a statistical method, to the existing practice of engineering process control (EPC) according to science. A case study on a real production curing process is thoroughly investigated. It is shown that the new findings could potentially result in significant energy savings. The solutions provided in this study can be generalized into other curing processes and applications subjected to both EPC and SPC

Circulating androgen regulation by androgen-catabolizing gut bacteria in male mouse gut

ABSTRACTAbnormally high circulating androgen levels have been considered a causative factor for benign prostatic hypertrophy and prostate cancer in men. Recent animal studies on gut microbiome suggested that gut bacteria are involved in sex steroid metabolism; however, the underlying mechanisms and bacterial taxa remain elusive. Denitrifying betaproteobacteria Thauera spp. are metabolically versatile and often distributed in the animal gut. Thauera sp. strain GDN1 is an unusual betaproteobacterium capable of catabolizing androgen under both aerobic and anaerobic conditions. We administered C57BL/6 mice (aged 7 weeks) with strain GDN1 through oral gavage. The strain GDN1 administration caused a minor increase in the relative abundance of Thauera (≤0.1%); however, it has profound effects on the host physiology and gut bacterial community. The results of our ELISA assay and metabolite profile analysis indicated an approximately 50% reduction in serum androgen levels in the strain GDN1-administered male mice. Moreover, androgenic ring-cleaved metabolites were detected in the fecal extracts of the strain GDN1-administered mice. Furthermore, our RT – qPCR results revealed the expression of the androgen catabolism genes in the gut of the strain GDN1-administered mice. We found that the administered strain GDN1 regulated mouse serum androgen levels, possibly because it blocked androgen recycling through enterohepatic circulation. This study discovered that sex steroids serve as a carbon source of gut bacteria; moreover, host circulating androgen levels may be regulated by androgen-catabolizing gut bacteria. Our data thus indicate the possible applicability of androgen-catabolic gut bacteria as potent probiotics in alternative therapy of hyperandrogenism

Preoperative Proteinuria Predicts Adverse Renal Outcomes after Coronary Artery Bypass Grafting

Whether preoperative proteinuria associates with adverse renal outcomes after cardiac surgery is unknown. Here, we performed a secondary analysis of a prospectively enrolled cohort of adult patients undergoing coronary artery bypass grafting (CABG) at a medical center and its two affiliate hospitals between 2003 and 2007. We excluded patients with stage 5 CKD or those who received dialysis previously. We defined proteinuria, measured with a dipstick, as mild (trace to 1+) or heavy (2+ to 4+). Among a total of 1052 patients, cardiac surgery–associated acute kidney injury (CSA-AKI) developed in 183 (17.4%) patients and required renal replacement therapy (RRT) in 50 (4.8%) patients. In a multiple logistic regression model, mild and heavy proteinuria each associated with an increased odds of CSA-AKI, independent of CKD stage and the presence of diabetes mellitus (mild: OR 1.66, 95% CI 1.09 to 2.52; heavy: OR 2.30, 95% CI 1.35 to 3.90). Heavy proteinuria also associated with increased odds of postoperative RRT (OR 7.29, 95% CI 3.00 to 17.73). In summary, these data suggest that preoperative proteinuria is a predictor of CSA-AKI among patients undergoing CABG