An abrupt variance analysis of multiple sensor signals for dimension reduction in fault diagnosis and prognosis

Department of System Design and Control EngineeringMany studies related to condition based maintenance (CBM) have been conducted especially for quality monitoring in motor, shipbuilding and electronics industries and equipment diagnosis in large-scale plant or automation machines. Sensor data related to critical components are collected using many sensors to analyze complex system or equipment. When conducting fault diagnosis using high dimensional time series data composed of many sensors, pre-processing steps such as selecting sensors related to system failure is needed for effective analysis. In other words, selecting sensors is a kind of process to reduce dimension of multivariate data. Many researchers have studies dimension reduction techniques for hundreds of years. Among many dimension reduction techniques, Principal Component Analysis, Linear Discriminant Analysis, and Partial Least Squares are widely used methods. PCA, which is a bible in dimension reduction techniques, basically uses variation of each sensor to decide new principal components, which is newly made axes. However, due to these intrinsic characteristic emphasizing variance, sensor of which signal is highly fluctuating periodically can be ranked as a highly important sensor even though it does not have any relation with system failure. That is, there is a limit to improve fault diagnosis algorithm directly using PCA sensor selection since it only considers total variance of data not finding principal sensors distinguishing fault and no-fault state. Therefore, in this study (i) we discuss key characteristics of sensor signals which are effective to distinguish no-fault and fault state of a system and introduce indices considering those characteristics: abrupt variance, discernibility index, and sparse impulse, (ii) propose sensor selection methods considering proposed indices and (iii) propose new principal component using abrupt variance-based PCA. The proposed sensor selection methods is illustrated and demonstrated with the case studies of vehicle fault simulator and gear fault simulator.ope

Plant Location Selection for Food Production by Considering the Regional and Seasonal Supply Vulnerability of Raw Materials

A production capacity analysis considering market demand and raw materials is very important to design a new plant. However, in the food processing industry, the supply uncertainty of raw materials is very high, depending on the production site and the harvest season, and further, it is not straightforward to analyze too complex food production systems by using an analytical optimization model. For these reasons, this study presents a simulation-based decision support model to select the right location for a new food processing plant. We first define three supply vulnerability factors from the standpoint of regional as well as seasonal instability and present an assessment method for supply vulnerability based on fuzzy quantification. The evaluated vulnerability scores are then converted into raw material supply variations for food production simulation to predict the quarterly production volume of a new food processing plant. The proposed selection procedure is illustrated using a case study of semiprocessed kimchi production. The best plant location is proposed where we can reduce and mitigate risks when supplying raw material, thereby producing a target production volume steadily

Molecular Weight Dependent Glucose Lowering Effect of Low Molecular Weight Chitosan Oligosaccharide (GO2KA1) on Postprandial Blood Glucose Level in SD Rats Model

Abstract This research investigated the effect of enzymatically digested low molecular weight (MW) chitosan oligosaccharide on type 2 diabetes prevention. Three different chitosan oligosaccharide samples with varying MW were evaluated in vitro for inhibition of rat small intestinal α-glucosidase and porcine pancreatic α-amylase (GO2KA1; \u3c1000 Da, GO2KA2; 1000–10,000 Da, GO2KA3; MW \u3e 10,000 Da). The in vitro results showed that all tested samples had similar rat α-glucosidase inhibitory and porcine α-amylase inhibitory activity. Based on these observations, we decided to further investigate the effect of all three samples at a dose of 0.1 g/kg, on reducing postprandial blood glucose levels in Sprague-Dawley (SD) rat model after sucrose loading test. In the animal trial, all tested samples had postprandial blood glucose reduction effect, when compared to control, however GO2KA1 supplementation had the strongest effect. The glucose peak (Cmax) for GO2KA1 and control was 152 mg/dL and 193 mg/dL, respectively. The area under the blood glucose-time curve (AUC) for GO2KA1 and control was 262 h mg/dL and 305 h mg/dL, respectively. Furthermore, the time of peak plasma concentration of blood glucose (Tmax) for GO2KA1 was significantly delayed (0.9 h) compared to control (0.5 h). These results suggest that GO2KA1 could have a beneficial effect for blood glucose management relevant to diabetes prevention in normal and pre-diabetic individuals. The suggested mechanism of action is via inhibition of the carbohydrate hydrolysis enzyme α-glucosidase and since GO2KA1 (MW \u3c 1000 Da) had higher in vivo effect, we hypothesize that it is more readily absorbed and might exert further biological effect once it is absorbed in the blood stream, relevant to blood glucose management

Computational Approach to Identify Enzymes That Are Potential Therapeutic Candidates for Psoriasis

Psoriasis is well known as a chronic inflammatory dermatosis. The disease affects persons of all ages and is a burden worldwide. Psoriasis is associated with various diseases such as arthritis. The disease is characterized by well-demarcated lesions on the skin of the elbows and knees. Various genetic and environmental factors are related to the pathogenesis of psoriasis. In order to identify enzymes that are potential therapeutic targets for psoriasis, we utilized a computational approach, combining microarray analysis and protein interaction prediction. We found 6,437 genes (3,264 upregulated and 3,173 downregulated) that have significant differences in expression between regions with and without lesions in psoriasis patients. We identified potential candidates through protein-protein interaction predictions made using various protein interaction resources. By analyzing the hub protein of the networks with metrics such as degree and centrality, we detected 32 potential therapeutic candidates. After filtering these candidates through the ENZYME nomenclature database, we selected 5 enzymes: DNA helicase (RUVBL2), proteasome endopeptidase complex (PSMA2), nonspecific protein-tyrosine kinase (ZAP70), I-kappa-B kinase (IKBKE), and receptor protein-tyrosine kinase (EGFR). We adopted a computational approach to detect potential therapeutic targets; this approach may become an effective strategy for the discovery of new drug targets for psoriasis

Diagnostic Performance of Core Needle Biopsy and Fine Needle Aspiration Separately or Together in the Diagnosis of Intrathoracic Lesions Under C-arm Guidance

Purpose: To evaluate and compare the diagnostic accuracy of fine needle aspiration (FNA) and core needle biopsy (CNB) of intrathoracic lesions using the same coaxial guide-needle under a C-arm Cone-Beam computed tomography system. Materials and Methods: Two hundred and eighty-eight patients (181 male, 107 female; 65.8 ± 13.3 years) with 293 lesions underwent 300 procedures, in which both FNA and CNB were performed. After inserting the coaxial guide-needle into the target lesion, we performed 18-gauge CNB, followed by 20-gauge FNA through the same coaxial guide-needle. The comparison of the procedures in which both showed adequate sample was performed with McNemar’s test (n = 229). Results: Of 300 procedures, 293 were technically successful. Adequate samples were obtained in 248/300 FNA and 288/300 CNB cases. The sensitivity and specificity for diagnosis of malignancy were respectively 84.7% (133/157), 100% (72/72) for FNA, when atypical cells included benign entity; 97.5% (153/157), 100% (72/72) for FNA, when atypical cells included malignancy; 97.6% (162/166), 100% (102/102) for CNB; and 100% (166/166), 100% (102/102) for combined FNA and CNB. Diagnosis of malignancy was significantly higher for CNB than for FNA ('p' < 0.001); however, it was not significantly higher when atypical cells included malignancy for FNA. Pneumothorax occurred in 50 (16.7%) and hemoptysis in 18 (6.0%) procedures. Conclusions: Combined use of CNB and FNA using the same coaxial guide-needle showed better diagnostic performance than using one alone. When comparing CNB and FNA, CNB showed significantly better performance, when atypical cells included a benign entity in FNA

Elevation of cytosolic calcium of rat cardiac myocytes in phosphate depletion

Elevation of cytosolic calcium of rat cardiac myocytes in phosphate depletion. Phosphate depletion is associated with a rise in cytosolic calcium ([Ca2+]i) of cells and such a derangement is responsible in major part for organ dysfunction in phosphate depletion (PD). Cardiac function is impaired in PD, and it is possible that PD is also associated with rise in [Ca2+]i of cardiac myocytes. The present study examined the effect of PD on [Ca2+]i of cardiac myocytes and explored the mechanisms that may lead to the rise in their [Ca2+]i. The [Ca2+]i of cardiac myocytes began to rise and ATP content began to fall at the third week of PD. After six weeks of PD, the values of [Ca2+]i were significantly higher (P < 0.01) and those of ATP content were significantly lower (P < 0.01) than in control (PW) rats. The Vmax of Ca2+-ATPase and Na+,K+-ATPase as well as the Na+-Ca2+ exchange were significantly lower (P < 0.01) in PD than in PW animals. The data of the present study are consistent with the notion that the rise in [Ca2+]i of cardiac myocytes of PD rats is due to a decrease in calcium efflux out of them

5′-Triphosphate-RNA-independent activation of RIG-I via RNA aptamer with enhanced antiviral activity

RIG-I is a cytosolic receptor for non-self RNA that mediates immune responses against viral infections through IFNα/β production. In an attempt to identify novel tools that modulate IFNα/β production, we used SELEX technology to screen RNA aptamers that specifically target RIG-I protein. Most of the selected RIG-I aptamers contained polyU motifs in the second half regions that played critical roles in the activation of RIG-I-mediated IFNβ production. Unlike other known ligands, RIG-I aptamer bound and activated RIG-I in a 5′-triphosphate-independent manner. The helicase and RD domain of RIG-I were used for aptamer binding, but intact RIG-I protein was required to exert aptamer-mediated signaling activation. Furthermore, replication of NDV, VSV and influenza virus in infected host cells was efficiently blocked by pre- or post-treatment with RIG-I aptamer. Based on these data, we propose that RIG-I aptamer has strong potential to be an antiviral agent that specifically boosts the RIG-I-dependent signaling cascade