Highly skewed and non-negative data can often be modeled by the delta-lognormal distribution in fisheries research. However, the coverage probabilities of extant interval estimation procedures are less satisfactory in small sample sizes and highly skewed data. We propose a heuristic method of estimating confidence intervals for the mean of the delta-lognormal distribution. This heuristic method is an estimation based on asymptotic generalized pivotal quantity to construct generalized confidence interval for the mean of the delta-lognormal distribution. Simulation results show that the proposed interval estimation procedure yields satisfactory coverage probabilities, expected interval lengths and reasonable relative biases. Finally, the proposed method is employed in red cod densities data for a demonstration.

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Summary: Receiver operating characteristic (ROC) curves can be used to assess the accuracy of tests measured on ordinal or continuous scales. The most commonly used measure for the overall diagnostic accuracy of diagnostic tests is the area under the ROC curve (AUC). A gold standard test on the true disease status is required to estimate the AUC. However, a gold standard test may sometimes be too expensive or infeasible. Therefore, in many medical research studies, the true disease status of the subjects may remain unknown. Under the normality assumption on test results from each disease group of subjects, using the expectation-maximization (EM) algorithm in conjunction with a bootstrap method, we propose a maximum likelihood based procedure for construction of confidence intervals for the difference in paired areas under ROC curves in the absence of a gold standard test. Simulation results show that the proposed interval estimation procedure yields satisfactory coverage probabilities and interval lengths. The proposed method is illustrated with two examples.

A technology was developed to treat black tarry materials which contained pentachlorophenol and other hazardous compounds. The technology converted the difficult-to-handle materials to a substance with properties similar to petroleum-based asphalt through heat treatment and polymerization.

A fully sustainable sanitation system was developed for a rural hospital in Haiti. The system operates by converting human waste into biogas and fertilizer without using external energy. It is a hybrid anaerobic/aerobic system that maximizes methane production while producing quality compost. The system first separates liquid and solid human waste at the source to control carbon to nitrogen ratio and moisture content to facilitate enhanced biodegradation. It will then degrade human waste through anaerobic digestion and capture the methane gas for on-site use as a heating fuel. For anaerobic decomposition and methane harvesting a bioreactor with two-stage batch process was designed. Finally, partially degraded human waste is extracted from the bioreactor with two-stage batch process and applied to land farming type aerobic composter to produce fertilizer. The proposed system is optimized in design by considering local conditions such as waste composition, waste generation, reaction temperature, residence time, construction materials, and current practice. It is above ground with low maintenance requirements.

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To study the leaching of metals and organic chemicals from Water Treatment Plant (WTP) residuals, a model monofill was constructed. Samples of leachate were collected from the monofill at three different times during a 1-year period. TCLP and total metal analyses were conducted on water treatment plant residual samples. It was found that the concentrations of the 39 regulated constituents were less than the TCLP regulatory limits. Total metal and TCLP test results reveal information regarding of leaching capacities of various metals in the residual. Total metal and TCLP tests show that manganese has the highest leaching capacity, followed by calcium, sodium, aluminum, magnesium, and iron. It was observed that the quantities of calcium in the leachate increased appreciably with time, causing a change in the sequence of leaching of the three samples tested.