Finding behavior patterns and evaluating orderliness of dynamical systems by spanning tree invariants

[[abstract]]Identifying the behavior patterns is the main goal for a dynamical system. It provides the useful information in behavior prediction of a dynamical system. On the other hand, measuring the orderliness of a dynamical system improves the prediction of behavior patterns. In this study, substitution sequences are used to model the long-term correlation of a dynamical system and evaluate the degree of randomness, where the degree of homogeneity is evaluated by the spanning tree invariant. The results show that the more contiguous patterns the sequence has, the smaller the value of the spanning tree invariant is. In fact, the spanning tree invariant can be an effective tool to measure the orderliness of sequences by comparing the computed value with the value of one

Applying a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements

[[abstract]]This study applies a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements from probabilities viewpoints. In reality, the needed probabilities can be computed based upon the experts' opinions for economic conditions as well as the customers' surveys by asking customers' preferences under different economic conditions. Each customer requirement can be analyzed as time goes by. In addition, the changes for each technical measure can be closely examined from time to time. More importantly, when new customers' surveys are conducted and available as well as the new economic conditions analyzed by experts have been updated, both customer requirements and technical measures can be adjusted in a timely basis to reflect and fulfill the dynamic customer requirements. As a result, this proposed approach provides a decision maker to analyze and satisfy both past and present customer needs early on such that a better strategy can be made based upon the most updated customers' surveys and economic conditions

Applying a complexity-based Choquet integral to evaluate students' performance

[[abstract]]The weighted arithmetic mean and the regression methods are the most often used operators to aggregate criteria in decision making problems with the assumption that there are no interactions among criteria. When interactions among criteria exist, the discrete Choquet integral is proved to be an adequate aggregation operator by further taking into accounts the interactions. In this study, we propose a complexity-based method to construct fuzzy measures needed by the discrete Choquet integral and a real data set is analyzed. The advantage of the complexity-based method is that no population probability is to be estimated such that the error of estimating the population probability is reduced. Four methods, including weighted arithmetic method, regress ion-based method, the discrete Choquet integral with the entropy-based method, and our proposed discrete Choquet integral with the complexity-based method, are used in this study to evaluate the students' performance based on a Basic Competence Test. The results show that the students' overall performance evaluated by our proposed discrete Choquet integral with the complexity-based method is the best among the four methods when the interactions among criteria exist. (C) 2008 Elsevier Ltd. All rights reserved

Applying importance-performance analysis to compare the changes of a convenient store

[[abstract]]This study applies importance-performance analysis to examine how the services provided by the convenient store (Hi-Life) located in Asia University have been changed when a competitor of a 7-11 convenient store opens nearby the university. In this case study, the performance for each item in the survey was measured by the average value, while the importance was evaluated by the variance-based methods. With the use of importance- performance analysis, a comparison of provided services at Hi-Life can be evaluated by two four-quadrant matrices to see how the services have been changed when the 7-11 becomes the competitor nearby the university

Hyperglycemia-induced Renal P2X7 Receptor Activation Enhances Diabetes-related Injury

Diabetes is a leading cause of renal disease. Glomerular mesangial expansion and fibrosis are hallmarks of diabetic nephropathy and this is thought to be promoted by infiltration of circulating macrophages. Monocyte chemoattractant protein-1 (MCP-1) has been shown to attract macrophages in kidney diseases. P2X7 receptors (P2X7R) are highly expressed on macrophages and are essential components of pro-inflammatory signaling in multiple tissues. Here we show that in diabetic patients, renal P2X7R expression is associated with severe mesangial expansion, impaired glomerular filtration (≤40 ml/min/1.73 sq. m.), and increased interstitial fibrosis. P2X7R activation enhanced the release of MCP-1 in human mesangial cells cultured under high glucose conditions. In mice, P2X7R-deficiency prevented glomerular macrophage attraction and collagen IV deposition; however, the more severe interstitial inflammation and fibrosis often seen in human diabetic kidney diseases was not modelled. Finally, we demonstrate that a P2X7R inhibitor (AZ11657312) can reduce renal macrophage accrual following the establishment of hyperglycemia in a model of diabetic nephropathy. Collectively these data suggest that P2X7R activation may contribute to the high prevalence of kidney disease found in diabetics

Maximization of negative correlations in time-course gene expression data for enhancing understanding of molecular pathways

Positive correlation can be diversely instantiated as shifting, scaling or geometric pattern, and it has been extensively explored for time-course gene expression data and pathway analysis. Recently, biological studies emerge a trend focusing on the notion of negative correlations such as opposite expression patterns, complementary patterns and self-negative regulation of transcription factors (TFs). These biological ideas and primitive observations motivate us to formulate and investigate the problem of maximizing negative correlations. The objective is to discover all maximal negative correlations of statistical and biological significance from time-course gene expression data for enhancing our understanding of molecular pathways. Given a gene expression matrix, a maximal negative correlation is defined as an activation–inhibition two-way expression pattern (AIE pattern). We propose a parameter-free algorithm to enumerate the complete set of AIE patterns from a data set. This algorithm can identify significant negative correlations that cannot be identified by the traditional clustering/biclustering methods. To demonstrate the biological usefulness of AIE patterns in the analysis of molecular pathways, we conducted deep case studies for AIE patterns identified from Yeast cell cycle data sets. In particular, in the analysis of the Lysine biosynthesis pathway, new regulation modules and pathway components were inferred according to a significant negative correlation which is likely caused by a co-regulation of the TFs at the higher layer of the biological network. We conjecture that maximal negative correlations between genes are actually a common characteristic in molecular pathways, which can provide insights into the cell stress response study, drug response evaluation, etc

An Adaptive Monitoring Scheme for Automatic Control of Anaesthesia in dynamic surgical environments based on Bispectral Index and Blood Pressure.

During surgical procedures, bispectral index (BIS) is a well-known measure used to determine the patient's depth of anesthesia (DOA). However, BIS readings can be subject to interference from many factors during surgery, and other parameters such as blood pressure (BP) and heart rate (HR) can provide more stable indicators. However, anesthesiologist still consider BIS as a primary measure to determine if the patient is correctly anaesthetized while relaying on the other physiological parameters to monitor and ensure the patient's status is maintained. The automatic control of administering anesthesia using intelligent control systems has been the subject of recent research in order to alleviate the burden on the anesthetist to manually adjust drug dosage in response physiological changes for sustaining DOA. A system proposed for the automatic control of anesthesia based on type-2 Self Organizing Fuzzy Logic Controllers (T2-SOFLCs) has been shown to be effective in the control of DOA under simulated scenarios while contending with uncertainties due to signal noise and dynamic changes in pharmacodynamics (PD) and pharmacokinetic (PK) effects of the drug on the body. This study considers both BIS and BP as part of an adaptive automatic control scheme, which can adjust to the monitoring of either parameter in response to changes in the availability and reliability of BIS signals during surgery. The simulation of different control schemes using BIS data obtained during real surgical procedures to emulate noise and interference factors have been conducted. The use of either or both combined parameters for controlling the delivery Propofol to maintain safe target set points for DOA are evaluated. The results show that combing BIS and BP based on the proposed adaptive control scheme can ensure the target set points and the correct amount of drug in the body is maintained even with the intermittent loss of BIS signal that could otherwise disrupt an automated control system

p63 is an alternative p53 repressor in melanoma that confers chemoresistance and a poor prognosis.

The role of apoptosis in melanoma pathogenesis and chemoresistance is poorly characterized. Mutations in TP53 occur infrequently, yet the TP53 apoptotic pathway is often abrogated. This may result from alterations in TP53 family members, including the TP53 homologue TP63. Here we demonstrate that TP63 has an antiapoptotic role in melanoma and is responsible for mediating chemoresistance. Although p63 was not expressed in primary melanocytes, up-regulation of p63 mRNA and protein was observed in melanoma cell lines and clinical samples, providing the first evidence of significant p63 expression in this lineage. Upon genotoxic stress, endogenous p63 isoforms were stabilized in both nuclear and mitochondrial subcellular compartments. Our data provide evidence of a physiological interaction between p63 with p53 whereby translocation of p63 to the mitochondria occurred through a codependent process with p53, whereas accumulation of p53 in the nucleus was prevented by p63. Using RNA interference technology, both isoforms of p63 (TA and ΔNp63) were demonstrated to confer chemoresistance, revealing a novel oncogenic role for p63 in melanoma cells. Furthermore, expression of p63 in both primary and metastatic melanoma clinical samples significantly correlated with melanoma-specific deaths in these patients. Ultimately, these observations provide a possible explanation for abrogation of the p53-mediated apoptotic pathway in melanoma, implicating novel approaches aimed at sensitizing melanoma to therapeutic agents

Improving the Performance in Occupational Health and Safety Management in the Electric Sector: An Integrated Methodology Using Fuzzy Multicriteria Approach

The electric sector is fundamental for the economic and social development of society, impacting on essential aspects such as health, education, employment generation, industrial production, and the provision of various services. In addition to the above, the growing trend in energy consumption worldwide could increase, according to expert estimates, up to 40% by 2030, which in turn increases the efforts of the public and private sector to meet increasing demands and increase access to energy services under requirements of reliability and quality. However, the electricity sector presents challenges and complexities, one of which is the reduction of health and safety risks for workers, service users, and other stakeholders. In many countries, this sector is classified as high risk in occupational safety and health, due to its complexity and the impact of accidents and occupational diseases on the health of workers, in infrastructure, in operating costs and competitiveness of the energy sector. Worldwide, there are rigorous regulations for the electricity sector, from local and national government regulations to international standards to guarantee health and safety conditions. However, it is necessary to develop objective and comprehensive methodologies for evaluating occupational safety and health performance that provides solutions for the electricity sector, not only to comply with standards and regulations also as a continuous improvement tool that supports the decision-making processes given the complexity of the industry and the multiple criteria that are taken into account when evaluating and establishing improvement strategies. In scientific literature, different studies focus on the analysis of accident statistics, the factors that affect accidents and occupational diseases, and the risk assessment of the sector. Despite these considerations, studies that focus directly on the development of hybrid methodologies for the evaluation and improvement of performance in occupational safety and health in the electrical sector, under multiple criteria and uncertainty are mostly limited. Therefore, this document presents an integrated methodology for improving the performance in occupational health and safety in the electric sector through the application of two techniques of Multi-criteria Decision Methods (MCDM) uses in environments under uncertainly. First, the fuzzy Analytic Hierarchy Process (FAHP) is applied to estimate the initial relative weights of criteria and sub-criteria. The fuzzy set theory is incorporated to represent the uncertainty of decision-makers’ preferences. Then, the Decision-making Trial and Evaluation Laboratory (DEMATEL) used for evaluating the interrelations and feedback among criteria and sub-criteria. FAHP and DEMATEL are later combined for calculating the final criteria and sub-criteria weights under vagueness and interdependence. Subsequently, we applied the proposed methodology in a company of the energy sector for diagnosis of performance in OHS to establish improvement proposals, the work path, and implementation costs. Finally, we evaluate the impact of the strategies applied in the improvement of the performance of the company