Browsing by Author "Liu C.-C"

We found some obvious abnormal strain induced by heavy rainfall from borehole strain-meters deployed in Western Taiwan. The strain induced by rainfall can be divided into two parts, one is the quick response for extra loads of rainwater on the ground, and another one is the slow response for rainwater infiltrating into the strata. The quick and slow rainfall responses of areal strain data are analyzed using the technique of recursive digital filtering. Moreover, the rainfall impact functions of the studied stations are calculated using deconvolution. We found, in most cases, the response strain will reach the maximum in half an hour after heavy rainfall, and then show an exponential decay, it might persist more than 200 h depending on the hydrogeological condition around the station. Whereas the river flowing beside the station will help accelerating the runoff dispersion and reducing rainfall decay time in the hill or mountain region. We also compare the results after calibration in term of isotropic and vertical coupling individually. We found that the response strains are smaller in vertical coupling rather than isotropic coupling. The effects of debris avalanches caused by intensive rainfall in the mountain areas can be viewed as two types of rock deformation: generated only under the influence of rainfall and generated by the increased load in the river channels due to rainfall-induced landslides or debris flow. When the cumulative rainfall exceeds a certain threshold, the strain response curves show a noticeable anomaly likely due to the effects of the debris flow events in places prone to landslides. ? 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Cyber-physical systems, such as smart grids, have received lots of attention recently. Unfortunately, security breaches in cyber-physical systems can result in catastrophic consequences, thus needing to be carefully monitored. For example, abnormal voltage quality events, which are more likely to happen because of unstable renewable energy sources in smart grids, harm delicate electronic devices. We thus focus on the quickest classification, or multi-hypothesis quickest change detection, which jointly detects and classifies multiple abnormal events. Both the classification delay and misclassification probability need to be low. Multiple smart meters are adopted, where each meter transmits its local decision to a fusion center for making the final decision. For energy saving, the bandwidth (link capacity) between each meter and the fusion center is limited to be one bit. Moreover, some meters may be faulty and mislead the final decision. To combat these faulty meters under the limited bandwidth, a code-based framework for quickest classification is proposed. Our contribution is two-fold. First, a new local decision rule based on the stochastic ordering theory is proposed. Compared with existing matrix-cumulative-sums algorithm, the newly proposed local decision rule has lower complexity and comparable performance. Second, a new fusion method based on codebook switching and minimum Hamming distance rule is developed. Compared with existing fault-tolerant methods, the newly-developed method can significantly lower the misclassification probabilities. © 2005-2012 IEEE.

To alleviate the vibration effect of the feed drive system, a traditional approach is to apply notch filters to suppress vibrations in the velocity loop. The current approach is to adjust the notch filter parameters such as the center frequency, damping and depth based on observing the frequency response diagram of servo velocity closed loop. In addition, the notch filters are generally provided in the velocity loop control for the commercialized controllers such as FANUC, Siemens, etc. However, the resonance of the transmission system also appears in the position loop when the linear scale is used as the position feedback. The notch filter design without consideration of the resonance behavior of the position loop might cause degradation of performance. To overcome this problem, the paper proposes an innovative method which could automatically determine the optimal parameters of the notch filter under the consideration of resonance behavior of position loop. With the optimal parameters, it is found that both the gains of position and velocity loop controller could be increased such that the bandwidths of the position/velocity loops are higher. Based on the simulation results, the rising time is improved by 33% and the time for reaching the steady state is improved by 72% as comparing the cases of using the optimal approach and traditional approach. ? 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

In this paper, we show that by integrating bottom-emitting flexible OLEDs and micro-optical structures such as micro-particle films and microlens films, quantum efficiency and cd/A efficiency can be enhanced, making flexible OLEDs more suitable for practical applications. © 2008 SID.

Canine melanoma is a malignant tumour that exhibits aggressive behaviour, and frequently metastasizes to regional lymph nodes and distant sites. Currently, there are no effective treatments or practical prognostic biomarkers for canine melanoma. The enzyme kynurenine 3-monooxygenase (KMO), which plays a central role in the tryptophan metabolism, has previously been identified as the main pathogenic factor in neurodegenerative diseases; however, it has recently been found to be positively associated with tumour malignancy in human hepatocellular carcinoma and canine mammary tumours. Signal transducer and activator of transcription 3 (STAT3) is a well-known oncoprotein contributing to the proliferation, survival, invasiveness and metastasis of a variety of cancers. Although whether STAT3 and KMO collaborate in tumorigenesis needs to be further verified, our previous findings showed that inhibition of KMO activity reduced activation of STAT3. This study investigated the expressions of KMO and STAT3/phosphorylated (pSTAT3) by immunohistochemical analysis in 85 cases of canine melanoma, showing their expression levels were high within highly mitotic melanoma cells. KMO Overexpression was significantly associated with increased STAT3 and pSTAT3 expressions. Melanoma tissues with higher KMO, STAT3 and pSTAT3 protein expressions were correlated with reduced survival rates of the canine patients. Moreover, inhibition of KMO activity in canine melanoma cells resulted in reduced cell viability, in addition to decreased expressions of STAT3 and pSTAT3. Our results indicated the significance of KMO and the potential role of KMO/STAT3 interaction in enhancing tumour development. Additionally, KMO and STAT3/pSTAT3 may be viewed as useful biomarkers for the prediction of prognosis of canine melanoma. ? 2020 John Wiley & Sons Ltd

Sodium benzoate (SBA) is a widely-used additive for preventing food spoilage and deterioration and extending the shelf life. However, the concentration of SBA must be controlled under safe regulations to avoid damaging human health. Accordingly, this study proposes a microfluidic colorimetric analysis (MCA) system composing of a wax-printed paper-microchip and a self-made smart analysis equipment for the concentration detection of SBA in common foods and beverages. In the presented method, the distilled SBA sample is mixed with NaOH to obtain a nitro compound and the compound is then dripped onto the reaction area of the paper-microchip, which is embedded with two layers of reagents (namely acetophenone and acetone). The paper-microchip is heated at 120 °C for 20 min to cause a colorimetric reaction and the reaction image is then obtained through a CMOS (complementary metal oxide semiconductor) device and transmitted to a cell-phone over a WiFi connection. Finally, use the self-developed RGB analysis software installed on the cell-phone to obtain the SBA concentration. A calibration curve is constructed using SBA samples with known concentrations ranging from 50 ppm (0.35 mM) to 5000 ppm (35 mM). It is shown that the R + G + B value (Y) of the reaction image and SBA concentration (X) are related via Y = ?0.034 X +737.40, with a determination coefficient of R2 = 0.9970. By measuring the SBA concentration of 15 commercially available food and beverage products, the actual feasibility of the current MCA system can be demonstrated. The results show that the difference from the measurement results obtained using the macroscale HPLC method does not exceed 6.0%. Overall, the current system provides a reliable and low-cost technique for quantifying the SBA concentration in food and drink products. ? 2020 Elsevier Ltd

Sodium dehydroacetate (NADH) has good antibacterial effects and is widely used as a preservative in dairy products. However, NADH is toxic in large amounts, so it must be added to food in accordance with regulations. Accordingly, the current study has developed a microfluidic analysis detection (MAD) system for the determination of NADH in foods incorporating a microfluidic PMMA-paper chip and a smart analysis device. In this system, the extracted NADH sample is dropped into the sample chamber of the microfluidic PMMA-paper chip and is then wicking/filtering through paper strips and transferred to a detection zone embedded with Fe-Alum reagent. The chip is heated at 35 °C for 5 min to produce a compound reaction and the color compound image acquired by a camera is then transmitted wirelessly to a smartphone, where the NADH concentration is obtained by the intensity inversion of RGB analysis. A standard calibration curve is determined using NADH control samples with concentrations in the range of 30–5000 ppm. The feasibility of the proposed MAD system is then evaluated by analyzing the NADH concentrations of 15 commercial dairy products. It is shown that the measured values deviate from those obtained using an official high performance liquid chromatography (HPLC) method by no more than 5.0%. © 2021 Elsevier B.V.

Accurate air quality prediction can provide better supervision and reference for management policies. Due to difficulties in data acquisition, combined spatio-temporal prediction is still inconclusive. This study utilizes the support vector machine (SVM) method to predict air quality of unknown space and time. Extracted from a geographic information system (GIS), geographic features such as population, land use, economy, pollution sources, and terrain parameters were added to a time series. Temporal prediction was first executed in the reference stations, and the predicted air quality index (AQI) was then used to spatially infer the future AQI of unknown locations. Verification indicated high accuracy for short-term temporal prediction. Various meteorological and climatic effects were observed to be influential in seasonal difference. In the spatial inference stage, urbanization and city types were spatial features that appeared to impact air quality. Agriculture and forest use, transportation use, residential use, and economic factors were clearly correlated to AQIs, whereas population and labor force were not. This study establishes a prediction framework in northern Taipei based on SVM. Other locations can build their own models based on local actual data to achieve better decision-making, urban planning, or other applications. ? 2021 Elsevier B.V.

Kynurenine 3-monooxygenase (KMO) is the pivotal enzyme in the kynurenine pathway and is located on the mitochondrial outer membrane. The dysregulation of KMO leads to various neurodegenerative diseases; however, it is rarely mentioned in cancer progression. Our previous study showed that KMO overexpression in canine mammary gland tumors (cMGT) is associated with poor prognosis in cMGT patients. Surprisingly, it was also found that KMO can be located on the cell membranes of cMGT cells, unlike its location in normal cells, where KMO is expressed only within the cytosol. Since cMGT and human breast cancer share similar morphologies and pathogenesis, this study investigated the possibility of detecting surface KMO in human breast cancers and the role of surface KMO in tumorigenesis. Using immunohistochemistry (IHC), flow cytometry (FC), immunofluorescence assay (IFA), and transmission electron microscopy (TEM), we demonstrated that KMO can be aberrantly and highly expressed on the cell membranes of breast cancer tissues and in an array of cell lines. Masking surface KMO with anti-KMO antibody reduced the cell viability and inhibited the migration and invasion of the triple-negative breast cancer cell line, MDA-MB-231. These results indicated that aberrant surface expression of KMO may be a potential therapeutic target for human breast cancers. ? The Author(s) 2021.