Prediction of Compaction Characteristics of Coal Bottom Ash

Compaction is the process of artificially improving the mechanical properties of soil. However, determination of compaction characteristics in laboratory using Proctor compaction test is time consuming and expensive. Hence, there is a need of correlating compaction characteristics with other physical properties of bottom ash which can be obtained easily. This paper describes an innovative solution to predict the compaction properties of coal bottom ash for the preliminary assessment prior to geotechnical engineering related field applications. The data for required parameters of bottom ash for the model development were collected through a literature survey representing different parts of the world. After stepwise regression analysis, specific gravity and uniformity coefficient were found to be the most significant input parameters to predict the compaction characteristics of bottom ash. These parameters were then used to develop the models to predict maximum dry density and optimum moisture content of bottom ash using multiple regression analysis. The developed models were accurate with a prediction accuracy less than ±3% for both maximum dry density and optimum moisture content models. These empirical models were also presented graphically. According to those predictive curves, maximum dry density increases with increasing uniformity coefficient and specific gravity while optimum moisture content reduced

Combinations of motor measures more strongly predict adverse health outcomes in old age: the rush memory and aging project, a community-based cohort study

<p>Abstract</p> <p>Objective</p> <p>Motor impairment in old age is a growing public-health concern, and several different constructs have been used to identify motor impairments in older people. We tested the hypothesis that combinations of motor constructs more strongly predict adverse health outcomes in older people.</p> <p>Methods</p> <p>In total, 949 people without dementia, history of stroke or Parkinson's disease, who were participating in the Rush Memory and Aging Project (a longitudinal community-based cohort study), underwent assessment at study entry. From this, three constructs were derived: 1) physical frailty based on grip strength, timed walk, body mass index and fatigue; 2) Parkinsonian Signs Score based on the modified motor section of the Unified Parkinson's Disease Rating Scale; and 3) a motor construct, based on nine strength measures and nine motor performances. Disability and cognitive status were assessed annually. A series of Cox proportional-hazards models, controlling for age, sex and education, were used to examine the association of each of these three constructs alone and in various combinations with death, disability and Alzheimer's disease (AD).</p> <p>Results</p> <p>All three constructs were related (mean <it>r </it>= 0.50, all <it>P </it>< 0.001), and when considered individually in separate proportional-hazards models, were associated with risk of death, incident disability and AD. However, when considered together, combinations of these constructs more strongly predicted adverse health outcomes.</p> <p>Conclusions</p> <p>Physical frailty, parkinsonian signs score and global motor score are related constructs that capture different aspects of motor function. Assessments using several motor constructs may more accurately identify people at the highest risk of adverse health consequences in old age.</p

Increased risk of cancer among relatives of patients with lung cancer in China

BACKGROUND: Genetic factors were considered as one of the risk factors for lung cancer or other cancers. The aim of this work was to determine whether a genetic predisposition accounts for such familial aggregation of cancer among relatives of lung cancer probands. METHODS: A case-control study was conducted in 800 case families identified by lung cancer patients (probands), and in 800 control families identified by the probands'spouses. The data were analysed with logistic regression analysis model. RESULTS: The data revealed a significantly greater overall risk of cancer (OR = 1.82, P < 0.01) in the proband group. The relatives of lung cancer probands maintained an increased risk of non-lung cancer (P < 0.05) after adjusting for confounder factors. The crude odds ratio of a proband family having one family member with cancer was 1.67 compared with control families. Proband families were 2.56 times more likely to have two other family members with cancer. For three cancers and four or more cancers, the risk increased to 3.50 and 5.91, respectively. The most striking differences in cancer prevalence between proband and control families were noted for cancer risk among female relatives. The strongest effects were for not only lung cancer in any female relatives (OR 2.17, 95%CI 1.60–3.64) and mothers (OR 2.78, 95%CI 1.23–5.12) and sisters (OR 2.03, 95%CI 1.26–3.97), but also non-lung cancer in females and mothers (OR 2.00, 95%CI 1.26–3.01, and OR 2.34, 95%CI 1.28–4.40, respectively). CONCLUSION: These data support the hypothesis of a genetic susceptibility to cancer in families with lung cancer, and the female genetic susceptibility to cancer might be greater than male

Differences in reproductive risk factors for breast cancer in middle-aged women in Marin County, California and a sociodemographically similar area of Northern California

<p>Abstract</p> <p>Background</p> <p>The Northern California county of Marin (MC) has historically had high breast cancer incidence rates. Because of MC's high socioeconomic status (SES) and racial homogeneity (non-Hispanic White), it has been difficult to assess whether these elevated rates result from a combination of established risk factors or other behavioral or environmental factors. This survey was designed to compare potential breast cancer risks and incidence rates for a sample of middle-aged MC women with those of a demographically similar population.</p> <p>Methods</p> <p>A random sample of 1500 middle-aged female members of a large Northern California health plan, half from Marin County (MC) and half from a comparison area in East/Central Contra Costa County (ECCC), were mailed a survey covering family history, reproductive history, use of oral contraceptives (OC) and hormone replacement therapy (HRT), behavioral health risks, recency of breast screening, and demographic characteristics. Weighted data were used to compare prevalence of individual breast cancer risk factors and Gail scores. Age-adjusted cumulative breast cancer incidence rates (2000–2004) were also calculated for female health plan members aged 40–64 residing in the two geographic areas.</p> <p>Results</p> <p>Survey response was 57.1% (n = 427) and 47.9% (n = 359) for MC and ECCC samples, respectively. Women in the two areas were similar in SES, race, obesity, exercise frequency, current smoking, ever use of OCs and HRT, age at onset of menarche, high mammography rates, family history of breast cancer, and Gail scores. However, MC women were significantly more likely than ECCC women to be former smokers (43.6% vs. 31.2%), have Ashkenazi Jewish heritage (12.8% vs. 7.1%), have no live births before age 30 (52.7% vs. 40.8%), and be nulliparous (29.2% vs. 15.4%), and less likely to never or rarely consume alcohol (34.4% vs. 41.9%). MC and ECCC women had comparable 2000–2004 invasive breast cancer incidence rates.</p> <p>Conclusion</p> <p>The effects of reproductive risks factors, Ashkenazi Jewish heritage, smoking history, and alcohol consumption with regard to breast cancer risk in Marin County should be further evaluated. When possible, future comparisons of breast cancer incidence rates between regions should adjust for differences in income and education in addition to age and race/ethnicity, preferably by using a sociodemographically similar comparison group.</p

Effect of betaine supplementation on cycling sprint performance

<p>Abstract</p> <p>Purpose</p> <p>To examine the effect of betaine supplementation on cycling sprint performance.</p> <p>Methods</p> <p>Sixteen recreationally active subjects (7 females and 9 males) completed three sprint tests, each consisting of four 12 sec efforts against a resistance equal to 5.5% of body weight; efforts were separated by 2.5 min of cycling at zero resistance. Test one established baseline; test two and three were preceded by seven days of daily consumption of 591 ml of a carbohydrate-electrolyte beverage as a placebo or a carbohydrate-electrolyte beverage containing 0.42% betaine (approximately 2.5 grams of betaine a day); half the beverage was consumed in the morning and the other half in the afternoon. We used a double blind random order cross-over design; there was a 3 wk washout between trials two and three. Average and maximum peak and mean power were analyzed with one-way repeated measures ANOVA and, where indicated, a Student Newman-Keuls.</p> <p>Results</p> <p>Compared to baseline, betaine ingestion increased average peak power (6.4%; p < 0.001), maximum peak power (5.7%; p < 0.001), average mean power (5.4%; p = 0.004), and maximum mean power (4.4%; p = 0.004) for all subjects combined. Compared to placebo, betaine ingestion significantly increased average peak power (3.4%; p = 0.026), maximum peak power max (3.8%; p = 0.007), average mean power (3.3%; p = 0.034), and maximum mean power (3.5%; p = 0.011) for all subjects combined. There were no differences between the placebo and baseline trials.</p> <p>Conclusions</p> <p>One week of betaine ingestion improved cycling sprint power in recreationally active males and females.</p

Perturbation of lipids and glucose metabolism associated with previous 2,4-D exposure: a cross-sectional study of NHANES III data, 1988-1994

<p>Abstract</p> <p>Background</p> <p>Results from previous population studies showed that mortality rates from acute myocardial infarction and type-2 diabetes during the 1980s and 1990s in rural, agricultural counties of Minnesota, Montana, North and South Dakota, were higher in counties with a higher level of spring wheat farming than in counties with lower levels of this crop. Spring wheat, one of the major field crops in these four states, was treated for 85% or more of its acreage with chlorophenoxy herbicides. In the current study NHANES III data were reviewed for associations of 2,4-dichlorophenoxy acetic acid (2,4-D) exposure, one of the most frequently used chlorophenoxy herbicides, with risk factors that are linked to the pathogenesis of acute myocardial infarction and type-2 diabetes, such as dyslipidemia and impaired glucose metabolism.</p> <p>Methods</p> <p>To investigate the toxicity pattern of chlorophenoxy herbicides, effects of a previous 2,4-D exposure were assessed by comparing levels of lipids, glucose metabolism, and thyroid stimulating hormone in healthy adult NHANES III subjects with urinary 2,4-D above and below the level of detection, using linear regression analysis. The analyses were conducted for all available subjects and for two susceptible subpopulations characterized by high glycosylated hemoglobin (upper 50^thpercentile) and low thyroxine (lower 50^thpercentile).</p> <p>Results</p> <p>Presence of urinary 2,4-D was associated with a decrease of HDL levels: 8.6% in the unadjusted data (p-value = 0.006), 4.8% in the adjusted data (p-value = 0.08), and 9% in the adjusted data for the susceptible subpopulation with low thyroxine (p-value = 0.02). An effect modification of the inverse triglycerides-HDL relation was observed in association with 2,4-D. Among subjects with low HDL, urinary 2,4-D was associated with increased levels of triglycerides, insulin, C-peptide, and thyroid stimulating hormone, especially in the susceptible subpopulations. In contrast, subjects with high HDL did not experience adverse 2,4-D associated effects.</p> <p>Conclusions</p> <p>The results indicate that exposure to 2,4-D was associated with changes in biomarkers that, based on the published literature, have been linked to risk factors for acute myocardial infarction and type-2 diabetes.</p

Multivariate random effects meta-analysis of diagnostic tests with multiple thresholds

Background. Bivariate random effects meta-analysis of diagnostic tests is becoming a well established approach when studies present one two-by-two table or one pair of sensitivity and specificity. When studies present multiple thresholds for test positivity, usually meta-analysts reduce the data to a two-by-two table or take one threshold value at a time and apply the well developed meta-analytic approaches. However, this approach does not fully exploi

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants

BACKGROUND: Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. METHODS: A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. RESULTS: CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0–1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. CONCLUSION: State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide