Crack identification of functionally graded beams using continuous wavelet transform

© 2018 Elsevier Ltd This paper proposes a new damage index for the crack identification of beams made of functionally graded materials (FGMs) by using the wavelet analysis. The damage index is defined based on the position of the wavelet coefficient modulus maxima in the scale space. The crack is assumed to be an open edge crack and is modeled by a massless rotational spring. It is assumed that the material properties follow exponential distributions along the beam thickness direction. The Timoshenko beam theory is employed to derive the governing equations which are solved analytically to obtain the frequency and mode shape of cracked FGM beams. Then, we apply the continuous wavelet transform (CWT) to the mode shapes of the cracked FGM beams. The locations of the cracks are determined from the sudden changes in the spatial variation of the damage index. An intensity factor, which relates to the size of the crack and the coefficient of the wavelet transform, is employed to estimate the crack depth. The effects of the crack size, the crack location and the Young's modulus ratio on the crack depth detection are investigated

A multilevel study of the determinants of area-level inequalities in colorectal cancer survival

Background: In Australia, associations between geographic remoteness, socioeconomic disadvantage, and colorectal cancer (CRC) survival show that survival rates are lowest among residents of geographically remote regions and those living in disadvantaged areas. At present we know very little about the reasons for these inequalities, hence our capacity to intervene to reduce the inequalities is limited. Methods/Design: This study, the first of its type in Australia, examines the association between CRC survival and key area- and individual-level factors. Specifically, we will use a multilevel framework to investigate the possible determinants of area- and individual-level inequalities in CRC survival and quantify the relative contribution of geographic remoteness, socioeconomic and demographic factors, disease stage, and access to diagnostic and treatment services, to these inequalities. The multilevel analysis will be based on survival data relating to people diagnosed with CRC in Queensland between 1996 and 2005 (n = 22,723) from the Queensland Cancer Registry (QCR), area-level data from other data custodians such as the Australian Bureau of Statistics, and individual-level data from the QCR (including extracting stage from pathology records) and Queensland Hospitals. For a subset of this period (2003 and 2004) we will utilise more detailed, individual-level data (n = 1,966) covering a greater range of risk factors from a concurrent research study. Geo-coding and spatial technology will be used to calculate road travel distances from patients’ residence to treatment centres. The analyses will be conducted using a multilevel Cox proportional hazards model with Level 1 comprising individual-level factors (e.g. occupation) and level 2 area level indicators of remoteness and area socioeconomic disadvantage. Discussion: This study focuses on the health inequalities for rural and disadvantaged populations that have often been documented but poorly understood, hence limiting our capacity to intervene. This study utilises and develops emerging statistical and spatial technologies that can then be applied to other cancers and health outcomes. The findings of this study will have direct implications for the targeting and resourcing of cancer control programs designed to reduce the burden of colorectal cancer, and for the provision of diagnostic and treatment services

Clinical, Virological and Immunological Features from Patients Infected with Re-Emergent Avian-Origin Human H7N9 Influenza Disease of Varying Severity in Guangdong Province

The second wave of avian influenza H7N9 virus outbreak in humans spread to the Guangdong province of China by August of 2013 and this virus is now endemic in poultry in this region.Background The second wave of avian influenza H7N9 virus outbreak in humans spread to the Guangdong province of China by August of 2013 and this virus is now endemic in poultry in this region. Methods Five patients with H7N9 virus infection admitted to our hospital during August 2013 to February 2014 were intensively investigated. Viral load in the respiratory tract was determined by quantitative polymerase chain reaction (Q-PCR) and cytokine levels were measured by bead-based flow cytometery. Results Four patients survived and one died. Viral load in different clinical specimens was correlated with cytokine levels in plasma and broncho-alveolar fluid (BALF), therapeutic modalities used and clinical outcome. Intravenous zanamivir appeared to be better than peramivir as salvage therapy in patients who failed to respond to oseltamivir. Higher and more prolonged viral load was found in the sputum or endotracheal aspirates compared to throat swabs. Upregulation of proinflammatory cytokines IP-10, MCP-1, MIG, MIP-1α/β, IL-1β and IL-8 was found in the plasma and BALF samples. The levels of cytokines in the plasma and viral load were correlated with disease severity. Reactivation of herpes simplex virus type 1(HSV-1) was found in three out of five patients (60%). Conclusion Expectorated sputum or endotracheal aspirate specimens are preferable to throat swabs for detecting and monitoring H7N9 virus. Severity of the disease was correlated to the viral load in the respiratory tract as well as the extents of cytokinemia. Reactivation of HSV-1 may contribute to clinical outcome.published_or_final_versio

Internet addiction: a 21st century epidemic?

Internet addiction, while not yet officially codified within a psychopathological framework, is growing both in prevalence and within the public consciousness as a potentially problematic condition with many parallels to existing recognized disorders. The rapid and unfettered increase in the number of people accessing a relatively unrestricted internet substantially increases the possibility that those suffering with an underlying psychological comorbidity may be at serious risk of developing an addiction to the internet, lending further credence to this hitherto understudied condition. In this commentary, I outline my recommendations for improved diagnosis, study and prevention of internet addiction

Identification and classification of high risk groups for Coal Workers' Pneumoconiosis using an artificial neural network based on occupational histories: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Coal workers' pneumoconiosis (CWP) is a preventable, but not fully curable occupational lung disease. More and more coal miners are likely to be at risk of developing CWP owing to an increase in coal production and utilization, especially in developing countries. Coal miners with different occupational categories and durations of dust exposure may be at different levels of risk for CWP. It is necessary to identify and classify different levels of risk for CWP in coal miners with different work histories. In this way, we can recommend different intervals for medical examinations according to different levels of risk for CWP. Our findings may provide a basis for further emending the measures of CWP prevention and control.</p> <p>Methods</p> <p>The study was performed using longitudinal retrospective data in the Tiefa Colliery in China. A three-layer artificial neural network with 6 input variables, 15 neurons in the hidden layer, and 1 output neuron was developed in conjunction with coal miners' occupational exposure data. Sensitivity and ROC analyses were adapted to explain the importance of input variables and the performance of the neural network. The occupational characteristics and the probability values predicted were used to categorize coal miners for their levels of risk for CWP.</p> <p>Results</p> <p>The sensitivity analysis showed that influence of the duration of dust exposure and occupational category on CWP was 65% and 67%, respectively. The area under the ROC in 3 sets was 0.981, 0.969, and 0.992. There were 7959 coal miners with a probability value < 0.001. The average duration of dust exposure was 15.35 years. The average duration of ex-dust exposure was 0.69 years. Of the coal miners, 79.27% worked in helping and mining. Most of the coal miners were born after 1950 and were first exposed to dust after 1970. One hundred forty-four coal miners had a probability value ≥0.1. The average durations of dust exposure and ex-dust exposure were 25.70 and 16.30 years, respectively. Most of the coal miners were born before 1950 and began to be exposed to dust before 1980. Of the coal miners, 90.28% worked in tunneling.</p> <p>Conclusion</p> <p>The duration of dust exposure and occupational category were the two most important factors for CWP. Coal miners at different levels of risk for CWP could be classified by the three-layer neural network analysis based on occupational history.</p

Identification of the risk for liver fibrosis on CHB patients using an artificial neural network based on routine and serum markers

<p>Abstract</p> <p>Background</p> <p>Liver fibrosis progression is commonly found in patients with CHB. Liver biopsy is a gold standard for identifying the extent of liver fibrosis, but has many draw-backs. It is essential to construct a noninvasive model to predict the levels of risk for liver fibrosis. It would provide very useful information to help reduce the number of liver biopsies of CHB patients.</p> <p>Methods</p> <p>339 chronic hepatitis B patients with HBsAg-positive were investigated retrospectively, and divided at random into 2 subsets with twice as many patients in the training set as in the validation set; 116 additional patients were consequently enrolled in the study as the testing set. A three-layer artificial neural network was developed using a Bayesian learning algorithm. Sensitivity and ROC analysis were performed to explain the importance of input variables and the performance of the neural network.</p> <p>Results</p> <p>There were 329 patients without significant fibrosis and 126 with significant fibrosis in the study. All markers except gender, HB, ALP and TP were found to be statistically significant factors associated with significant fibrosis. The sensitivity analysis showed that the most important factors in the predictive model were age, AST, platelet, and GGT, and the influence on the output variable among coal miners were 22.3-24.6%. The AUROC in 3 sets was 0.883, 0.884, and 0.920. In the testing set, for a decision threshold of 0.33, sensitivity and negative predictive values were 100% and all CHB patients with significant fibrosis would be identified.</p> <p>Conclusions</p> <p>The artificial neural network model based on routine and serum markers would predict the risk for liver fibrosis with a high accuracy. 47.4% of CHB patients at a decision threshold of 0.33 would be free of liver biopsy and wouldn't be missed.</p

Heusler type CoNiGa alloys with high martensitic transformation temperature

A strong need exists to develop new kinds of high-temperature shape-memory alloys. In this study, two series of CoNiGa alloys with different compositions have been studied to investigate their potentials as high-temperature shape-memory alloys, with regard to their microstructure, crystal structure, and martensitic transformation behavior. Optical observations and X-ray diffractions confirmed that single martensite phase was present for low cobalt samples, and dual phases containing martensite and gamma phase were present for high cobalt samples. It was also found that CoNiGa alloys in this study exhibit austenitic transformation temperatures higher than 340 degrees C, showing their great potentials for developing as high-temperature shape-memory alloys

Age at Menarche and Its Association with the Metabolic Syndrome and Its Components: Results from the KORA F4 Study

OBJECTIVE: The metabolic syndrome is a major public health challenge and identifies persons at risk for diabetes and cardiovascular disease. The aim of this study was to examine the association between age at menarche and the metabolic syndrome (IDF and NCEP ATP III classification) and its components. DESIGN: 1536 women aged 32 to 81 years of the German population based KORA F4 study were investigated. Data was collected by standardized interviews, physical examinations, and whole blood and serum measurements. RESULTS: Young age at menarche was significantly associated with elevated body mass index (BMI), greater waist circumference, higher fasting glucose levels, and 2 hour glucose (oral glucose tolerance test), even after adjusting for the difference between current BMI and BMI at age 25. The significant effect on elevated triglycerides and systolic blood pressure was attenuated after adjustment for the BMI change. Age at menarche was inversely associated with the metabolic syndrome adjusting for age (p-values: <0.001 IDF, 0.003 NCEP classification) and additional potential confounders including lifestyle and reproductive history factors (p-values: 0.001, 0.005). Associations remain significant when additionally controlling for recollected BMI at age 25 (p-values: 0.008, 0.033) or the BMI change since age 25 (p-values: 0.005, 0.022). CONCLUSION: Young age at menarche might play a role in the development of the metabolic syndrome. This association is only partially mediated by weight gain and increased BMI. A history of early menarche may help to identify women at risk for the metabolic syndrome

Sequential Metabolism of 7-Dehydrocholesterol to Steroidal 5,7-Dienes in Adrenal Glands and Its Biological Implication in the Skin

Since P450scc transforms 7-dehydrocholesterol (7DHC) to 7-dehydropregnenolone (7DHP) in vitro, we investigated sequential 7DHC metabolism by adrenal glands ex vivo. There was a rapid, time- and dose-dependent metabolism of 7DHC by adrenals from rats, pigs, rabbits and dogs with production of more polar 5,7-dienes as detected by RP-HPLC. Based on retention time (RT), UV spectra and mass spectrometry, we identified the major products common to all tested species as 7DHP, 22-hydroxy-7DHC and 20,22-dihydroxy-7DHC. The involvement of P450scc in adrenal metabolic transformation was confirmed by the inhibition of this process by DL-aminoglutethimide. The metabolism of 7DHC with subsequent production of 7DHP was stimulated by forscolin indicating involvement of cAMP dependent pathways. Additional minor products of 7DHC metabolism that were more polar than 7DHP were identified as 17-hydroxy-7DHP (in pig adrenals but not those of rats) and as pregna-4,7-diene-3,20-dione (7-dehydroprogesterone). Both products represented the major identifiable products of 7DHP metabolism in adrenal glands. Studies with purified enzymes show that StAR protein likely transports 7DHC to the inner mitochondrial membrane, that 7DHC can compete effectively with cholesterol for the substrate binding site on P450scc and that the catalytic efficiency of 3βHSD for 7DHP (Vm/Km) is 40% of that for pregnenolone. Skin mitochondria are capable of transforming 7DHC to 7DHP and the 7DHP is metabolized further by skin extracts. Finally, 7DHP, its photoderivative 20-oxopregnacalciferol, and pregnenolone exhibited biological activity in skin cells including inhibition of proliferation of epidermal keratinocytes and melanocytes, and melanoma cells. These findings define a novel steroidogenic pathway: 7DHC→22(OH)7DHC→20,22(OH)27DHC→7DHP, with potential further metabolism of 7DHP mediated by 3βHSD or CYP17, depending on mammalian species. The 5–7 dienal intermediates of the pathway can be a source of biologically active vitamin D3 derivatives after delivery to or production in the skin, an organ intermittently exposed to solar radiation