Data preprocessing for artificial neural network applications in prioritizing railroad projects â a practical experience in Taiwan

[[abstract]]Financial constraints necessitate the tradeoff among proposed railroad projects, so that the project priorities for implementation and budget allocation need to be determined by the ranking mechanisms in the government. At present, the Taiwan central government prioritizes funding allocations primarily using the analytic hierarchy process (AHP), a methodology that permits the synthesizing of subjective judgments systematically and logically into objective consensus. However, due to the coopetition and heterogeneity of railway projects, the proper priorities of railroad projects could not be always evaluated by the AHP. The decision makers prefer subjective judgments to referring to the AHP evaluation re- sults. This circumstance not only decreased the AHP advantages, but also raised the risk of the policies. A method to con- sider both objective measures and subjective judgments of project attributes can help reduce this problem. Accordingly, combining the AHP with the artificial neural network (ANN) methodologies would theoretically be a proper solution to bring a ranking predication model by creating the obscure relations between objective measures by the AHP and subjec- tive judgments. However, the inconsistency between the AHP evaluation and subjective judgments resulted in the inferior soundness of the AHP/ANN ranking forecast model. To overcome this problem, this study proposes the data prepro- cessing method (DPM) to calculate the correlation coefficient value using the subjective and objective ranking incidence matrixes; according to the correlation coefficient value, the consistency between the AHP rankings and subjective judg- ments of railroad projects can be evaluated and improved, so that the forecast accuracy of the AHP/ANN ranking forecast model can also be enhanced. Based on this concept, a practical railroad project ranking experience derived from the Insti- tute of Transportation of Taiwan is illustrated in this paper to reveal the feasibility of applying the DPM to the AHP/ANN ranking prediction model.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]電子版[[countrycodes]]LT

An Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm

For test-sheet composition systems, it is important to adaptively compose test sheets with diverse conceptual scopes, discrimination and difficulty degrees to meet various assessment requirements during real learning situations. Computation time and item exposure rate also influence performance and item bank security. Therefore, this study proposes an Adaptive Test Sheet Generation (ATSG) mechanism, where a Candidate Item Selection Strategy adaptively determines candidate test items and conceptual granularities according to desired conceptual scopes, and an Aggregate Objective Function applies Genetic Algorithm (GA) to figure out the approximate solution of mixed integer programming problem for the test-sheet composition. Experimental results show that the ATSG mechanism can efficiently, precisely generate test sheets to meet the various assessment requirements than existing ones. Furthermore, according to experimental finding, Fractal Time Series approach can be applied to analyze the self-similarity characteristics of GA’s fitness scores for improving the quality of the test-sheet composition in the near future

Generalist Versus Specialist Nurses\u27 Knowledge, Attitudes, and Behavioral Intentions Toward Promoting Pulmonary Rehabilitation for Patients with Chronic Obstructive Pulmonary Disease: A Cross-Sectional Correlational Study

Pulmonary rehabilitation (PR) is an effective strategy to manage chronic obstructive pulmonary disease (COPD), though its utilization rate is low. One reason for this low utilization rate is that nurses do not provide COPD patients with enough health education to increase the patient\u27s motivation for PR participation. This study examined knowledge, attitudes, and behavioral intention toward PR promotion. The study also investigated the correlates of behavioral intentions to promote PR among pulmonary nurses. A cross-sectional correlational design was used. Overall, 284 nurses (all women) from chest medicine and general internal medicine wards in 3 hospitals within Midwest Taiwan were recruited. Data were collected by anonymous, self-administered questionnaires. We aimed to understand if there would be differences in the Chest Medicine and Generalist nurses on these outcomes, given the specialty versus generalist nature of their practice. Results were analyzed using multiple linear regressions. Although the 2 groups of nurses (ie, Chest Medicine, General Medicine) showed no differences in PR knowledge, attitudes, or behavioral intentions, they lacked sufficient PR knowledge and skills. The accuracy rate of PR knowledge was approximately 12% and self-evaluated PR skills were less than 50%. Self-efficacy in promoting PR was above average (ie, 57%–60%), and the strength of attitudes and behavioral intentions was over 70%. A multiple linear regression revealed that behavioral intentions of nurses working in the chest medicine ward were influenced by behavioral attitudes, and also PR skills and self-efficacy (explanatory power 33.3%). Attitudes, skills, and self-efficacy heavily affected pulmonary nurses’ ability to promote PR; however, PR knowledge and skills remain low. Therefore, future implementation of practical PR training courses is needed to strengthen nurses’ behavioral intentions toward PR promotion. Improved pulmonary rehabilitation-related skill, attitudes, clinical experience of PR programs, and/or practical PR training are needed among both generalist and specialist nurses. Education courses and clinical practice training should be increased in the future to promote pulmonary rehabilitation of COPD patients

Involvement of the nuclear high mobility group B1 peptides released from injured hepatocytes in murine hepatic fibrogenesis

AbstractThis study investigated the pro-fibrogenic role of high mobility group box 1 (HMGB1) peptides in liver fibrogenesis. An animal model of carbon tetrachloride (CCl4)-induced liver fibrosis was used to examine the serum HMGB1 levels and its intrahepatic distribution. The increased serum HMGB1 levels were positively correlated with elevation of transforming growth factor-β1 (TGF-β1) and collagen deposition during fibrogenesis. The cytoplasmic distribution of HMGB1 was noted in the parenchymal hepatocytes of fibrotic livers. In vitro studies confirmed that exposure to hydrogen peroxide and CCl4 induced an intracellular mobilization and extracellular release of nuclear HMGB1 peptides in clone-9 and primary hepatocytes, respectively. An uptake of exogenous HMGB1 by hepatic stellate cells (HSCs) T6 cells indicated a possible paracrine action of hepatocytes on HSCs. Moreover, HMGB1 dose-dependently stimulated HSC proliferation, up-regulated de novo synthesis of collagen type I and α-smooth muscle actin (α-SMA), and triggered Smad2 phosphorylation and its nuclear translocation through a TGF-β1-independent mechanism. Blockade with neutralizing antibodies and gene silencing demonstrated the involvement of the receptor for advanced glycation end-products (RAGE), but not toll-like receptor 4, in cellular uptake of HMGB1 and the HMGB1-mediated Smad2 and ERK1/2 phosphorylation as well as α-SMA up-regulation in HSC-T6 cells. Furthermore, anti-RAGE treatment significantly ameliorated CCl4-induced liver fibrosis. In conclusion, the nuclear HMGB1 peptides released from parenchymal hepatocytes during liver injuries may directly activate HSCs through stimulating HSC proliferation and transformation, eventually leading to the fibrotic changes of livers. Blockade of HMGB1/RAGE signaling cascade may constitute a therapeutic strategy for treatment of liver fibrosis

Life expectancies and incidence rates of patients under prolonged mechanical ventilation: a population-based study during 1998 to 2007 in Taiwan

[[abstract]]Introduction: The present study examined the median survival, life expectancies, and cumulative incidence rate (CIR) of patients undergoing prolonged mechanical ventilation (PMV) stratified by different underlying diseases.Methods: According to the National Health Insurance Research Database of Taiwan, there were 8,906,406 individuals who obtained respiratory care during the period from 1997 to 2007. A random sample of this population was performed, and subjects who had continuously undergone mechanical ventilation for longer than 21 days were enrolled in the current study. Annual incidence rates and the CIR were calculated. After stratifying the patients according to their specific diagnoses, latent class analysis was performed to categorise PMV patients with multiple co-morbidities into several groups. The life expectancies of different groups were estimated using a semiparametric method with a hazard function based on the vital statistics of Taiwan.Results: The analysis of 50,481 PMV patients revealed that incidence rates increased as patients grew older and that the CIR (17 to 85 years old) increased from 0.103 in 1998 to 0.183 in 2004 before stabilising thereafter. The life expectancies of PMV patients suffering from degenerative neurological diseases, stroke, or injuries tended to be longer than those with chronic renal failure or cancer. Patients with chronic obstructive pulmonary disease survived longer than did those co-morbid with other underlying diseases, especially septicaemia/shock.Conclusions: PMV provides a direct means to treat respiratory tract diseases and to sustain respiration in individuals suffering from degenerative neurological diseases, and individuals with either of these types of conditions respond better to PMV than do those with other co-morbidities. Future research is required to determine the cost-effectiveness of this treatment paradigm

Statistical identification of gene association by CID in application of constructing ER regulatory network

<p>Abstract</p> <p>Background</p> <p>A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating <it>in silico </it>inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A).</p> <p>Results</p> <p>The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's <it>t</it>-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays.</p> <p>Conclusion</p> <p>CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers.</p> <p>Availability</p> <p>the implementation of CID in R codes can be freely downloaded from <url>http://homepage.ntu.edu.tw/~lyliu/BC/</url>.</p

High APACHE II score and long length of bowel resection impair the outcomes in patients with necrotic bowel induced hepatic portal venous gas

<p>Abstract</p> <p>Background</p> <p>Hepatic portal venous gas (HPVG) is a rare but potentially lethal condition, especially when it results from intestinal ischemia. Since the literatures regarding the prognostic factors of HPVG are still scarce, we aimed to investigate the risk factor of perioperative mortality in this study.</p> <p>Methods</p> <p>We analyzed data for patients with intestinal ischemia induced HPVG by chart review in our hospital between 2000 and 2007. Factors associated with perioperative mortality were specifically analyzed.</p> <p>Results</p> <p>There were 22 consecutive patients receiving definite bowel resection. 13 cases (59.1%) died after surgical intervention. When analyzing the mortality in patients after bowel resections, high Acute Physiology And Chronic health Evaluation (APACHE) II score (<it>p < 0.01</it>) and longer length of bowel resection (<it>p </it>= 0.047) were significantly associated with mortality in univariate analyses. The complication rate was 66.7% in alive patients after definite bowel resection.</p> <p>Conclusions</p> <p>Bowel resection was the only potential life-saving therapy for patients with mesenteric ischemia induced HPVG. High APACHE II score and severity of underlying necrotic bowel determined the results in patients after bowel resection.</p

Demographic and Clinical Characteristics of Patients with Severe Asthma in the Asian Pacific Region : data from the International Severe Asthma Registry (ISAR)

Peer reviewe

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities